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5c55da3acbe2a3fb755637361be2db476d2ff4cc	979	py	Python	UnitTests/test_type_checker.py	mjdroz/StatisticsCalculator	6be77b650b16e1c3e8ed6160905d99e58449e9b4	[ "MIT" ]	null	null	null	UnitTests/test_type_checker.py	mjdroz/StatisticsCalculator	6be77b650b16e1c3e8ed6160905d99e58449e9b4	[ "MIT" ]	18	2020-11-02T00:14:07.000Z	2020-11-09T04:07:07.000Z	UnitTests/test_type_checker.py	mjdroz/StatisticsCalculator	6be77b650b16e1c3e8ed6160905d99e58449e9b4	[ "MIT" ]	null	null	null	import unittest from AdditionalModules.type_checker import is_valid_number if __name__ == '__main__': unittest.main()	31.580645	61	0.733401	import unittest from AdditionalModules.type_checker import is_valid_number class MyTestCase(unittest.TestCase): def test_valid_whole_positive_number_string(self): self.assertTrue(is_valid_number("12345")) self.assertTrue(is_valid_number("123456")) def test_valid_negative_number_string(self): self.assertTrue(is_valid_number("-12345")) def test_invalid_negative_number_mixed_with_string(self): self.assertFalse(is_valid_number("-12-12")) self.assertFalse(is_valid_number("-12asdf")) self.assertFalse(is_valid_number("12asdf")) def test_alphabetical_string_negative(self): self.assertFalse(is_valid_number("asdf")) self.assertFalse(is_valid_number("-asdf")) def test_valid_decimal_number(self): self.assertTrue(is_valid_number("33.33")) def test_invalid_decimal_number(self): self.assertFalse(is_valid_number("33..33")) if __name__ == '__main__': unittest.main()	655	15	185
be2c403274d5eaf1a9f49e212f01bb768a9e7069	59,185	py	Python	test/terra/backends/statevector_simulator/statevector_basics.py	sagarpahwa/qiskit-aer	77e40c8d99fd0490d85285e96f87e4905017b646	[ "Apache-2.0" ]	null	null	null	test/terra/backends/statevector_simulator/statevector_basics.py	sagarpahwa/qiskit-aer	77e40c8d99fd0490d85285e96f87e4905017b646	[ "Apache-2.0" ]	null	null	null	test/terra/backends/statevector_simulator/statevector_basics.py	sagarpahwa/qiskit-aer	77e40c8d99fd0490d85285e96f87e4905017b646	[ "Apache-2.0" ]	null	null	null	# This code is part of Qiskit. # # (C) Copyright IBM 2018, 2020. # # This code is licensed under the Apache License, Version 2.0. You may # obtain a copy of this license in the LICENSE.txt file in the root directory # of this source tree or at http://www.apache.org/licenses/LICENSE-2.0. # # Any modifications or derivative works of this code must retain this # copyright notice, and modified files need to carry a notice indicating # that they have been altered from the originals. """ StatevectorSimulator Integration Tests """ from numpy import exp, pi from test.terra.reference import ref_measure from test.terra.reference import ref_reset from test.terra.reference import ref_initialize from test.terra.reference import ref_conditionals from test.terra.reference import ref_1q_clifford from test.terra.reference import ref_2q_clifford from test.terra.reference import ref_non_clifford from test.terra.reference import ref_unitary_gate from test.terra.reference import ref_diagonal_gate from qiskit import execute, transpile, assemble from qiskit.providers.aer import StatevectorSimulator class StatevectorSimulatorTests: """StatevectorSimulator tests.""" SIMULATOR = StatevectorSimulator() BACKEND_OPTS = {} # --------------------------------------------------------------------- # Test initialize # --------------------------------------------------------------------- def test_initialize_1(self): """Test StatevectorSimulator initialize""" circuits = ref_initialize.initialize_circuits_1(final_measure=False) targets = ref_initialize.initialize_statevector_1() qobj = assemble(circuits, shots=1) sim_job = self.SIMULATOR.run(qobj, backend_options=self.BACKEND_OPTS) result = sim_job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_initialize_2(self): """Test StatevectorSimulator initialize""" circuits = ref_initialize.initialize_circuits_2(final_measure=False) targets = ref_initialize.initialize_statevector_2() qobj = assemble(circuits, shots=1) sim_job = self.SIMULATOR.run(qobj, backend_options=self.BACKEND_OPTS) result = sim_job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test reset # --------------------------------------------------------------------- def test_reset_deterministic(self): """Test StatevectorSimulator reset with for circuits with deterministic counts""" # For statevector output we can combine deterministic and non-deterministic # count output circuits circuits = ref_reset.reset_circuits_deterministic(final_measure=False) targets = ref_reset.reset_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_reset_nondeterministic(self): """Test StatevectorSimulator reset with for circuits with non-deterministic counts""" # For statevector output we can combine deterministic and non-deterministic # count output circuits circuits = ref_reset.reset_circuits_nondeterministic( final_measure=False) targets = ref_reset.reset_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test measure # --------------------------------------------------------------------- def test_measure(self): """Test StatevectorSimulator measure with deterministic counts""" circuits = ref_measure.measure_circuits_deterministic( allow_sampling=True) targets = ref_measure.measure_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test conditional # --------------------------------------------------------------------- def test_conditional_gate_1bit(self): """Test conditional gates on 1-bit conditional register.""" circuits = ref_conditionals.conditional_circuits_1bit( final_measure=False) targets = ref_conditionals.conditional_statevector_1bit() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_conditional_unitary_1bit(self): """Test conditional unitaries on 1-bit conditional register.""" circuits = ref_conditionals.conditional_circuits_1bit( final_measure=False, conditional_type='unitary') targets = ref_conditionals.conditional_statevector_1bit() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_conditional_gate_2bit(self): """Test conditional gates on 2-bit conditional register.""" circuits = ref_conditionals.conditional_circuits_2bit( final_measure=False) targets = ref_conditionals.conditional_statevector_2bit() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_conditional_unitary_2bit(self): """Test conditional unitary on 2-bit conditional register.""" circuits = ref_conditionals.conditional_circuits_2bit( final_measure=False, conditional_type='unitary') targets = ref_conditionals.conditional_statevector_2bit() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test h-gate # --------------------------------------------------------------------- def test_h_gate_deterministic_default_basis_gates(self): """Test h-gate circuits compiling to backend default basis_gates.""" circuits = ref_1q_clifford.h_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.h_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_h_gate_deterministic_waltz_basis_gates(self): """Test h-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_1q_clifford.h_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.h_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_h_gate_deterministic_minimal_basis_gates(self): """Test h-gate gate circuits compiling to u3,cx""" circuits = ref_1q_clifford.h_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.h_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_h_gate_nondeterministic_default_basis_gates(self): """Test h-gate circuits compiling to backend default basis_gates.""" circuits = ref_1q_clifford.h_gate_circuits_nondeterministic( final_measure=False) targets = ref_1q_clifford.h_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_h_gate_nondeterministic_waltz_basis_gates(self): """Test h-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_1q_clifford.h_gate_circuits_nondeterministic( final_measure=False) targets = ref_1q_clifford.h_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_h_gate_nondeterministic_minimal_basis_gates(self): """Test h-gate gate circuits compiling to u3,cx""" circuits = ref_1q_clifford.h_gate_circuits_nondeterministic( final_measure=False) targets = ref_1q_clifford.h_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test x-gate # --------------------------------------------------------------------- def test_x_gate_deterministic_default_basis_gates(self): """Test x-gate circuits compiling to backend default basis_gates.""" circuits = ref_1q_clifford.x_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.x_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_x_gate_deterministic_waltz_basis_gates(self): """Test x-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_1q_clifford.x_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.x_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_x_gate_deterministic_minimal_basis_gates(self): """Test x-gate gate circuits compiling to u3,cx""" circuits = ref_1q_clifford.x_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.x_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test z-gate # --------------------------------------------------------------------- def test_z_gate_deterministic_default_basis_gates(self): """Test z-gate circuits compiling to backend default basis_gates.""" circuits = ref_1q_clifford.z_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.z_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_z_gate_deterministic_waltz_basis_gates(self): """Test z-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_1q_clifford.z_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.z_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_z_gate_deterministic_minimal_basis_gates(self): """Test z-gate gate circuits compiling to u3,cx""" circuits = ref_1q_clifford.z_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.z_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test y-gate # --------------------------------------------------------------------- def test_y_gate_deterministic_default_basis_gates(self): """Test y-gate circuits compiling to backend default basis_gates.""" circuits = ref_1q_clifford.y_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.y_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_y_gate_deterministic_waltz_basis_gates(self): """Test y-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_1q_clifford.y_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.y_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_y_gate_deterministic_minimal_basis_gates(self): """Test y-gate gate circuits compiling to u3, cx.""" circuits = ref_1q_clifford.y_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.y_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test s-gate # --------------------------------------------------------------------- def test_s_gate_deterministic_default_basis_gates(self): """Test s-gate circuits compiling to backend default basis_gates.""" circuits = ref_1q_clifford.s_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.s_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_s_gate_deterministic_waltz_basis_gates(self): """Test s-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_1q_clifford.s_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.s_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_s_gate_deterministic_minimal_basis_gates(self): """Test s-gate gate circuits compiling to u3,cx""" circuits = ref_1q_clifford.s_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.s_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_s_gate_nondeterministic_default_basis_gates(self): """Test s-gate circuits compiling to backend default basis_gates.""" circuits = ref_1q_clifford.s_gate_circuits_nondeterministic( final_measure=False) targets = ref_1q_clifford.s_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_s_gate_nondeterministic_waltz_basis_gates(self): """Test s-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_1q_clifford.s_gate_circuits_nondeterministic( final_measure=False) targets = ref_1q_clifford.s_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_s_gate_nondeterministic_minimal_basis_gates(self): """Test s-gate gate circuits compiling to u3,cx""" circuits = ref_1q_clifford.s_gate_circuits_nondeterministic( final_measure=False) targets = ref_1q_clifford.s_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test sdg-gate # --------------------------------------------------------------------- def test_sdg_gate_deterministic_default_basis_gates(self): """Test sdg-gate circuits compiling to backend default basis_gates.""" circuits = ref_1q_clifford.sdg_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.sdg_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_sdg_gate_deterministic_waltz_basis_gates(self): """Test sdg-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_1q_clifford.sdg_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.sdg_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_sdg_gate_deterministic_minimal_basis_gates(self): """Test sdg-gate gate circuits compiling to u3,cx""" circuits = ref_1q_clifford.sdg_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.sdg_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_sdg_gate_nondeterministic_default_basis_gates(self): """Test sdg-gate circuits compiling to backend default basis_gates.""" circuits = ref_1q_clifford.sdg_gate_circuits_nondeterministic( final_measure=False) targets = ref_1q_clifford.sdg_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_sdg_gate_nondeterministic_waltz_basis_gates(self): """Test sdg-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_1q_clifford.sdg_gate_circuits_nondeterministic( final_measure=False) targets = ref_1q_clifford.sdg_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_sdg_gate_nondeterministic_minimal_basis_gates(self): """Test sdg-gate gate circuits compiling to u3,cx""" circuits = ref_1q_clifford.sdg_gate_circuits_nondeterministic( final_measure=False) targets = ref_1q_clifford.sdg_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test cx-gate # --------------------------------------------------------------------- def test_cx_gate_deterministic_default_basis_gates(self): """Test cx-gate circuits compiling to backend default basis_gates.""" circuits = ref_2q_clifford.cx_gate_circuits_deterministic( final_measure=False) targets = ref_2q_clifford.cx_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cx_gate_deterministic_waltz_basis_gates(self): """Test cx-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_2q_clifford.cx_gate_circuits_deterministic( final_measure=False) targets = ref_2q_clifford.cx_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cx_gate_deterministic_minimal_basis_gates(self): """Test cx-gate gate circuits compiling to u3,cx""" circuits = ref_2q_clifford.cx_gate_circuits_deterministic( final_measure=False) targets = ref_2q_clifford.cx_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cx_gate_nondeterministic_default_basis_gates(self): """Test cx-gate circuits compiling to backend default basis_gates.""" circuits = ref_2q_clifford.cx_gate_circuits_nondeterministic( final_measure=False) targets = ref_2q_clifford.cx_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cx_gate_nondeterministic_waltz_basis_gates(self): """Test cx-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_2q_clifford.cx_gate_circuits_nondeterministic( final_measure=False) targets = ref_2q_clifford.cx_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cx_gate_nondeterministic_minimal_basis_gates(self): """Test cx-gate gate circuits compiling to u3,cx""" circuits = ref_2q_clifford.cx_gate_circuits_nondeterministic( final_measure=False) targets = ref_2q_clifford.cx_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test cz-gate # --------------------------------------------------------------------- def test_cz_gate_deterministic_default_basis_gates(self): """Test cz-gate circuits compiling to backend default basis_gates.""" circuits = ref_2q_clifford.cz_gate_circuits_deterministic( final_measure=False) targets = ref_2q_clifford.cz_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cz_gate_deterministic_waltz_basis_gates(self): """Test cz-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_2q_clifford.cz_gate_circuits_deterministic( final_measure=False) targets = ref_2q_clifford.cz_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cz_gate_deterministic_minimal_basis_gates(self): """Test cz-gate gate circuits compiling to u3,cx""" circuits = ref_2q_clifford.cz_gate_circuits_deterministic( final_measure=False) targets = ref_2q_clifford.cz_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cz_gate_nondeterministic_default_basis_gates(self): """Test cz-gate circuits compiling to backend default basis_gates.""" circuits = ref_2q_clifford.cz_gate_circuits_nondeterministic( final_measure=False) targets = ref_2q_clifford.cz_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cz_gate_nondeterministic_waltz_basis_gates(self): """Test cz-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_2q_clifford.cz_gate_circuits_nondeterministic( final_measure=False) targets = ref_2q_clifford.cz_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cz_gate_nondeterministic_minimal_basis_gates(self): """Test cz-gate gate circuits compiling to u3,cx""" circuits = ref_2q_clifford.cz_gate_circuits_nondeterministic( final_measure=False) targets = ref_2q_clifford.cz_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test swap-gate # --------------------------------------------------------------------- def test_swap_gate_deterministic_default_basis_gates(self): """Test swap-gate circuits compiling to backend default basis_gates.""" circuits = ref_2q_clifford.swap_gate_circuits_deterministic( final_measure=False) targets = ref_2q_clifford.swap_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_swap_gate_deterministic_waltz_basis_gates(self): """Test swap-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_2q_clifford.swap_gate_circuits_deterministic( final_measure=False) targets = ref_2q_clifford.swap_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_swap_gate_deterministic_minimal_basis_gates(self): """Test swap-gate gate circuits compiling to u3,cx""" circuits = ref_2q_clifford.swap_gate_circuits_deterministic( final_measure=False) targets = ref_2q_clifford.swap_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_swap_gate_nondeterministic_default_basis_gates(self): """Test swap-gate circuits compiling to backend default basis_gates.""" circuits = ref_2q_clifford.swap_gate_circuits_nondeterministic( final_measure=False) targets = ref_2q_clifford.swap_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_swap_gate_nondeterministic_waltz_basis_gates(self): """Test swap-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_2q_clifford.swap_gate_circuits_nondeterministic( final_measure=False) targets = ref_2q_clifford.swap_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_swap_gate_nondeterministic_minimal_basis_gates(self): """Test swap-gate gate circuits compiling to u3,cx""" circuits = ref_2q_clifford.swap_gate_circuits_nondeterministic( final_measure=False) targets = ref_2q_clifford.swap_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test t-gate # --------------------------------------------------------------------- def test_t_gate_deterministic_default_basis_gates(self): """Test t-gate circuits compiling to backend default basis_gates.""" circuits = ref_non_clifford.t_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.t_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_t_gate_deterministic_waltz_basis_gates(self): """Test t-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_non_clifford.t_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.t_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_t_gate_deterministic_minimal_basis_gates(self): """Test t-gate gate circuits compiling to u3,cx""" circuits = ref_non_clifford.t_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.t_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_t_gate_nondeterministic_default_basis_gates(self): """Test t-gate circuits compiling to backend default basis_gates.""" circuits = ref_non_clifford.t_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.t_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_t_gate_nondeterministic_waltz_basis_gates(self): """Test t-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_non_clifford.t_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.t_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_t_gate_nondeterministic_minimal_basis_gates(self): """Test t-gate gate circuits compiling to u3,cx""" circuits = ref_non_clifford.t_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.t_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test tdg-gate # --------------------------------------------------------------------- def test_tdg_gate_deterministic_default_basis_gates(self): """Test tdg-gate circuits compiling to backend default basis_gates.""" circuits = ref_non_clifford.tdg_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.tdg_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_tdg_gate_deterministic_waltz_basis_gates(self): """Test tdg-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_non_clifford.tdg_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.tdg_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_tdg_gate_deterministic_minimal_basis_gates(self): """Test tdg-gate gate circuits compiling to u3,cx""" circuits = ref_non_clifford.tdg_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.tdg_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_tdg_gate_nondeterministic_default_basis_gates(self): """Test tdg-gate circuits compiling to backend default basis_gates.""" circuits = ref_non_clifford.tdg_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.tdg_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_tdg_gate_nondeterministic_waltz_basis_gates(self): """Test tdg-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_non_clifford.tdg_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.tdg_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_tdg_gate_nondeterministic_minimal_basis_gates(self): """Test tdg-gate gate circuits compiling to u3,cx""" circuits = ref_non_clifford.tdg_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.tdg_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test ccx-gate # --------------------------------------------------------------------- def test_ccx_gate_deterministic_default_basis_gates(self): """Test ccx-gate circuits compiling to backend default basis_gates.""" circuits = ref_non_clifford.ccx_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.ccx_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_ccx_gate_deterministic_waltz_basis_gates(self): """Test ccx-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_non_clifford.ccx_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.ccx_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_ccx_gate_deterministic_minimal_basis_gates(self): """Test ccx-gate gate circuits compiling to u3,cx""" circuits = ref_non_clifford.ccx_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.ccx_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_ccx_gate_nondeterministic_default_basis_gates(self): """Test ccx-gate circuits compiling to backend default basis_gates.""" circuits = ref_non_clifford.ccx_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.ccx_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_ccx_gate_nondeterministic_waltz_basis_gates(self): """Test ccx-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_non_clifford.ccx_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.ccx_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_ccx_gate_nondeterministic_minimal_basis_gates(self): """Test ccx-gate gate circuits compiling to u3,cx""" circuits = ref_non_clifford.ccx_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.ccx_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test unitary gate qobj instruction # --------------------------------------------------------------------- def test_unitary_gate(self): """Test simulation with unitary gate circuit instructions.""" circuits = ref_unitary_gate.unitary_gate_circuits_deterministic( final_measure=False) targets = ref_unitary_gate.unitary_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_diagonal_gate(self): """Test simulation with diagonal gate circuit instructions.""" circuits = ref_diagonal_gate.diagonal_gate_circuits_deterministic( final_measure=False) targets = ref_diagonal_gate.diagonal_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test cu1 gate # --------------------------------------------------------------------- def test_cu1_gate_nondeterministic_default_basis_gates(self): """Test cu1-gate gate circuits compiling to default basis.""" circuits = ref_non_clifford.cu1_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.cu1_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cu1_gate_nondeterministic_waltz_basis_gates(self): """Test cu1-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_non_clifford.cu1_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.cu1_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cu1_gate_nondeterministic_minimal_basis_gates(self): """Test cu1-gate gate circuits compiling to u3,cx""" circuits = ref_non_clifford.cu1_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.cu1_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test cswap-gate (Fredkin) # --------------------------------------------------------------------- def test_cswap_gate_deterministic_default_basis_gates(self): """Test cswap-gate circuits compiling to backend default basis_gates.""" circuits = ref_non_clifford.cswap_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.cswap_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cswap_gate_deterministic_minimal_basis_gates(self): """Test cswap-gate gate circuits compiling to u3,cx""" circuits = ref_non_clifford.cswap_gate_circuits_deterministic( final_measure=True) targets = ref_non_clifford.cswap_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cswap_gate_deterministic_waltz_basis_gates(self): """Test cswap-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_non_clifford.cswap_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.cswap_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cswap_gate_nondeterministic_default_basis_gates(self): """Test cswap-gate circuits compiling to backend default basis_gates.""" circuits = ref_non_clifford.cswap_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.cswap_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cswap_gate_nondeterministic_minimal_basis_gates(self): """Test cswap-gate gate circuits compiling to u3,cx""" circuits = ref_non_clifford.cswap_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.cswap_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cswap_gate_nondeterministic_waltz_basis_gates(self): """Test cswap-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_non_clifford.cswap_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.cswap_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test cu3-gate (Fredkin) # --------------------------------------------------------------------- def test_cu3_gate_deterministic_default_basis_gates(self): """Test cu3-gate circuits compiling to backend default basis_gates.""" circuits = ref_non_clifford.cu3_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.cu3_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cu3_gate_deterministic_minimal_basis_gates(self): """Test cu3-gate gate circuits compiling to u3,cx""" circuits = ref_non_clifford.cu3_gate_circuits_deterministic( final_measure=True) targets = ref_non_clifford.cu3_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cu3_gate_deterministic_waltz_basis_gates(self): """Test cu3-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_non_clifford.cu3_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.cu3_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test global phase # --------------------------------------------------------------------- def test_qobj_global_phase(self): """Test qobj global phase.""" circuits = ref_1q_clifford.h_gate_circuits_nondeterministic( final_measure=False) targets = ref_1q_clifford.h_gate_statevector_nondeterministic() qobj = assemble(transpile(circuits, self.SIMULATOR), shots=1, backend_options=self.BACKEND_OPTS) # Set global phases for i, _ in enumerate(circuits): global_phase = (-1) ** i * (pi / 4) qobj.experiments[i].header.global_phase = global_phase targets[i] = exp(1j * global_phase) * targets[i] result = self.SIMULATOR.run(qobj).result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets, ignore_phase=False)	45.986791	93	0.594019	# This code is part of Qiskit. # # (C) Copyright IBM 2018, 2020. # # This code is licensed under the Apache License, Version 2.0. You may # obtain a copy of this license in the LICENSE.txt file in the root directory # of this source tree or at http://www.apache.org/licenses/LICENSE-2.0. # # Any modifications or derivative works of this code must retain this # copyright notice, and modified files need to carry a notice indicating # that they have been altered from the originals. """ StatevectorSimulator Integration Tests """ from numpy import exp, pi from test.terra.reference import ref_measure from test.terra.reference import ref_reset from test.terra.reference import ref_initialize from test.terra.reference import ref_conditionals from test.terra.reference import ref_1q_clifford from test.terra.reference import ref_2q_clifford from test.terra.reference import ref_non_clifford from test.terra.reference import ref_unitary_gate from test.terra.reference import ref_diagonal_gate from qiskit import execute, transpile, assemble from qiskit.providers.aer import StatevectorSimulator class StatevectorSimulatorTests: """StatevectorSimulator tests.""" SIMULATOR = StatevectorSimulator() BACKEND_OPTS = {} # --------------------------------------------------------------------- # Test initialize # --------------------------------------------------------------------- def test_initialize_1(self): """Test StatevectorSimulator initialize""" circuits = ref_initialize.initialize_circuits_1(final_measure=False) targets = ref_initialize.initialize_statevector_1() qobj = assemble(circuits, shots=1) sim_job = self.SIMULATOR.run(qobj, backend_options=self.BACKEND_OPTS) result = sim_job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_initialize_2(self): """Test StatevectorSimulator initialize""" circuits = ref_initialize.initialize_circuits_2(final_measure=False) targets = ref_initialize.initialize_statevector_2() qobj = assemble(circuits, shots=1) sim_job = self.SIMULATOR.run(qobj, backend_options=self.BACKEND_OPTS) result = sim_job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test reset # --------------------------------------------------------------------- def test_reset_deterministic(self): """Test StatevectorSimulator reset with for circuits with deterministic counts""" # For statevector output we can combine deterministic and non-deterministic # count output circuits circuits = ref_reset.reset_circuits_deterministic(final_measure=False) targets = ref_reset.reset_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_reset_nondeterministic(self): """Test StatevectorSimulator reset with for circuits with non-deterministic counts""" # For statevector output we can combine deterministic and non-deterministic # count output circuits circuits = ref_reset.reset_circuits_nondeterministic( final_measure=False) targets = ref_reset.reset_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test measure # --------------------------------------------------------------------- def test_measure(self): """Test StatevectorSimulator measure with deterministic counts""" circuits = ref_measure.measure_circuits_deterministic( allow_sampling=True) targets = ref_measure.measure_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test conditional # --------------------------------------------------------------------- def test_conditional_gate_1bit(self): """Test conditional gates on 1-bit conditional register.""" circuits = ref_conditionals.conditional_circuits_1bit( final_measure=False) targets = ref_conditionals.conditional_statevector_1bit() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_conditional_unitary_1bit(self): """Test conditional unitaries on 1-bit conditional register.""" circuits = ref_conditionals.conditional_circuits_1bit( final_measure=False, conditional_type='unitary') targets = ref_conditionals.conditional_statevector_1bit() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_conditional_gate_2bit(self): """Test conditional gates on 2-bit conditional register.""" circuits = ref_conditionals.conditional_circuits_2bit( final_measure=False) targets = ref_conditionals.conditional_statevector_2bit() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_conditional_unitary_2bit(self): """Test conditional unitary on 2-bit conditional register.""" circuits = ref_conditionals.conditional_circuits_2bit( final_measure=False, conditional_type='unitary') targets = ref_conditionals.conditional_statevector_2bit() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test h-gate # --------------------------------------------------------------------- def test_h_gate_deterministic_default_basis_gates(self): """Test h-gate circuits compiling to backend default basis_gates.""" circuits = ref_1q_clifford.h_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.h_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_h_gate_deterministic_waltz_basis_gates(self): """Test h-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_1q_clifford.h_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.h_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_h_gate_deterministic_minimal_basis_gates(self): """Test h-gate gate circuits compiling to u3,cx""" circuits = ref_1q_clifford.h_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.h_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_h_gate_nondeterministic_default_basis_gates(self): """Test h-gate circuits compiling to backend default basis_gates.""" circuits = ref_1q_clifford.h_gate_circuits_nondeterministic( final_measure=False) targets = ref_1q_clifford.h_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_h_gate_nondeterministic_waltz_basis_gates(self): """Test h-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_1q_clifford.h_gate_circuits_nondeterministic( final_measure=False) targets = ref_1q_clifford.h_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_h_gate_nondeterministic_minimal_basis_gates(self): """Test h-gate gate circuits compiling to u3,cx""" circuits = ref_1q_clifford.h_gate_circuits_nondeterministic( final_measure=False) targets = ref_1q_clifford.h_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test x-gate # --------------------------------------------------------------------- def test_x_gate_deterministic_default_basis_gates(self): """Test x-gate circuits compiling to backend default basis_gates.""" circuits = ref_1q_clifford.x_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.x_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_x_gate_deterministic_waltz_basis_gates(self): """Test x-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_1q_clifford.x_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.x_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_x_gate_deterministic_minimal_basis_gates(self): """Test x-gate gate circuits compiling to u3,cx""" circuits = ref_1q_clifford.x_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.x_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test z-gate # --------------------------------------------------------------------- def test_z_gate_deterministic_default_basis_gates(self): """Test z-gate circuits compiling to backend default basis_gates.""" circuits = ref_1q_clifford.z_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.z_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_z_gate_deterministic_waltz_basis_gates(self): """Test z-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_1q_clifford.z_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.z_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_z_gate_deterministic_minimal_basis_gates(self): """Test z-gate gate circuits compiling to u3,cx""" circuits = ref_1q_clifford.z_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.z_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test y-gate # --------------------------------------------------------------------- def test_y_gate_deterministic_default_basis_gates(self): """Test y-gate circuits compiling to backend default basis_gates.""" circuits = ref_1q_clifford.y_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.y_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_y_gate_deterministic_waltz_basis_gates(self): """Test y-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_1q_clifford.y_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.y_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_y_gate_deterministic_minimal_basis_gates(self): """Test y-gate gate circuits compiling to u3, cx.""" circuits = ref_1q_clifford.y_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.y_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test s-gate # --------------------------------------------------------------------- def test_s_gate_deterministic_default_basis_gates(self): """Test s-gate circuits compiling to backend default basis_gates.""" circuits = ref_1q_clifford.s_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.s_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_s_gate_deterministic_waltz_basis_gates(self): """Test s-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_1q_clifford.s_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.s_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_s_gate_deterministic_minimal_basis_gates(self): """Test s-gate gate circuits compiling to u3,cx""" circuits = ref_1q_clifford.s_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.s_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_s_gate_nondeterministic_default_basis_gates(self): """Test s-gate circuits compiling to backend default basis_gates.""" circuits = ref_1q_clifford.s_gate_circuits_nondeterministic( final_measure=False) targets = ref_1q_clifford.s_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_s_gate_nondeterministic_waltz_basis_gates(self): """Test s-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_1q_clifford.s_gate_circuits_nondeterministic( final_measure=False) targets = ref_1q_clifford.s_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_s_gate_nondeterministic_minimal_basis_gates(self): """Test s-gate gate circuits compiling to u3,cx""" circuits = ref_1q_clifford.s_gate_circuits_nondeterministic( final_measure=False) targets = ref_1q_clifford.s_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test sdg-gate # --------------------------------------------------------------------- def test_sdg_gate_deterministic_default_basis_gates(self): """Test sdg-gate circuits compiling to backend default basis_gates.""" circuits = ref_1q_clifford.sdg_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.sdg_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_sdg_gate_deterministic_waltz_basis_gates(self): """Test sdg-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_1q_clifford.sdg_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.sdg_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_sdg_gate_deterministic_minimal_basis_gates(self): """Test sdg-gate gate circuits compiling to u3,cx""" circuits = ref_1q_clifford.sdg_gate_circuits_deterministic( final_measure=False) targets = ref_1q_clifford.sdg_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_sdg_gate_nondeterministic_default_basis_gates(self): """Test sdg-gate circuits compiling to backend default basis_gates.""" circuits = ref_1q_clifford.sdg_gate_circuits_nondeterministic( final_measure=False) targets = ref_1q_clifford.sdg_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_sdg_gate_nondeterministic_waltz_basis_gates(self): """Test sdg-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_1q_clifford.sdg_gate_circuits_nondeterministic( final_measure=False) targets = ref_1q_clifford.sdg_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_sdg_gate_nondeterministic_minimal_basis_gates(self): """Test sdg-gate gate circuits compiling to u3,cx""" circuits = ref_1q_clifford.sdg_gate_circuits_nondeterministic( final_measure=False) targets = ref_1q_clifford.sdg_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test cx-gate # --------------------------------------------------------------------- def test_cx_gate_deterministic_default_basis_gates(self): """Test cx-gate circuits compiling to backend default basis_gates.""" circuits = ref_2q_clifford.cx_gate_circuits_deterministic( final_measure=False) targets = ref_2q_clifford.cx_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cx_gate_deterministic_waltz_basis_gates(self): """Test cx-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_2q_clifford.cx_gate_circuits_deterministic( final_measure=False) targets = ref_2q_clifford.cx_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cx_gate_deterministic_minimal_basis_gates(self): """Test cx-gate gate circuits compiling to u3,cx""" circuits = ref_2q_clifford.cx_gate_circuits_deterministic( final_measure=False) targets = ref_2q_clifford.cx_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cx_gate_nondeterministic_default_basis_gates(self): """Test cx-gate circuits compiling to backend default basis_gates.""" circuits = ref_2q_clifford.cx_gate_circuits_nondeterministic( final_measure=False) targets = ref_2q_clifford.cx_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cx_gate_nondeterministic_waltz_basis_gates(self): """Test cx-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_2q_clifford.cx_gate_circuits_nondeterministic( final_measure=False) targets = ref_2q_clifford.cx_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cx_gate_nondeterministic_minimal_basis_gates(self): """Test cx-gate gate circuits compiling to u3,cx""" circuits = ref_2q_clifford.cx_gate_circuits_nondeterministic( final_measure=False) targets = ref_2q_clifford.cx_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test cz-gate # --------------------------------------------------------------------- def test_cz_gate_deterministic_default_basis_gates(self): """Test cz-gate circuits compiling to backend default basis_gates.""" circuits = ref_2q_clifford.cz_gate_circuits_deterministic( final_measure=False) targets = ref_2q_clifford.cz_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cz_gate_deterministic_waltz_basis_gates(self): """Test cz-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_2q_clifford.cz_gate_circuits_deterministic( final_measure=False) targets = ref_2q_clifford.cz_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cz_gate_deterministic_minimal_basis_gates(self): """Test cz-gate gate circuits compiling to u3,cx""" circuits = ref_2q_clifford.cz_gate_circuits_deterministic( final_measure=False) targets = ref_2q_clifford.cz_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cz_gate_nondeterministic_default_basis_gates(self): """Test cz-gate circuits compiling to backend default basis_gates.""" circuits = ref_2q_clifford.cz_gate_circuits_nondeterministic( final_measure=False) targets = ref_2q_clifford.cz_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cz_gate_nondeterministic_waltz_basis_gates(self): """Test cz-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_2q_clifford.cz_gate_circuits_nondeterministic( final_measure=False) targets = ref_2q_clifford.cz_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cz_gate_nondeterministic_minimal_basis_gates(self): """Test cz-gate gate circuits compiling to u3,cx""" circuits = ref_2q_clifford.cz_gate_circuits_nondeterministic( final_measure=False) targets = ref_2q_clifford.cz_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test swap-gate # --------------------------------------------------------------------- def test_swap_gate_deterministic_default_basis_gates(self): """Test swap-gate circuits compiling to backend default basis_gates.""" circuits = ref_2q_clifford.swap_gate_circuits_deterministic( final_measure=False) targets = ref_2q_clifford.swap_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_swap_gate_deterministic_waltz_basis_gates(self): """Test swap-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_2q_clifford.swap_gate_circuits_deterministic( final_measure=False) targets = ref_2q_clifford.swap_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_swap_gate_deterministic_minimal_basis_gates(self): """Test swap-gate gate circuits compiling to u3,cx""" circuits = ref_2q_clifford.swap_gate_circuits_deterministic( final_measure=False) targets = ref_2q_clifford.swap_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_swap_gate_nondeterministic_default_basis_gates(self): """Test swap-gate circuits compiling to backend default basis_gates.""" circuits = ref_2q_clifford.swap_gate_circuits_nondeterministic( final_measure=False) targets = ref_2q_clifford.swap_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_swap_gate_nondeterministic_waltz_basis_gates(self): """Test swap-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_2q_clifford.swap_gate_circuits_nondeterministic( final_measure=False) targets = ref_2q_clifford.swap_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_swap_gate_nondeterministic_minimal_basis_gates(self): """Test swap-gate gate circuits compiling to u3,cx""" circuits = ref_2q_clifford.swap_gate_circuits_nondeterministic( final_measure=False) targets = ref_2q_clifford.swap_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test t-gate # --------------------------------------------------------------------- def test_t_gate_deterministic_default_basis_gates(self): """Test t-gate circuits compiling to backend default basis_gates.""" circuits = ref_non_clifford.t_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.t_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_t_gate_deterministic_waltz_basis_gates(self): """Test t-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_non_clifford.t_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.t_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_t_gate_deterministic_minimal_basis_gates(self): """Test t-gate gate circuits compiling to u3,cx""" circuits = ref_non_clifford.t_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.t_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_t_gate_nondeterministic_default_basis_gates(self): """Test t-gate circuits compiling to backend default basis_gates.""" circuits = ref_non_clifford.t_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.t_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_t_gate_nondeterministic_waltz_basis_gates(self): """Test t-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_non_clifford.t_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.t_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_t_gate_nondeterministic_minimal_basis_gates(self): """Test t-gate gate circuits compiling to u3,cx""" circuits = ref_non_clifford.t_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.t_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test tdg-gate # --------------------------------------------------------------------- def test_tdg_gate_deterministic_default_basis_gates(self): """Test tdg-gate circuits compiling to backend default basis_gates.""" circuits = ref_non_clifford.tdg_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.tdg_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_tdg_gate_deterministic_waltz_basis_gates(self): """Test tdg-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_non_clifford.tdg_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.tdg_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_tdg_gate_deterministic_minimal_basis_gates(self): """Test tdg-gate gate circuits compiling to u3,cx""" circuits = ref_non_clifford.tdg_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.tdg_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_tdg_gate_nondeterministic_default_basis_gates(self): """Test tdg-gate circuits compiling to backend default basis_gates.""" circuits = ref_non_clifford.tdg_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.tdg_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_tdg_gate_nondeterministic_waltz_basis_gates(self): """Test tdg-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_non_clifford.tdg_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.tdg_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_tdg_gate_nondeterministic_minimal_basis_gates(self): """Test tdg-gate gate circuits compiling to u3,cx""" circuits = ref_non_clifford.tdg_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.tdg_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test ccx-gate # --------------------------------------------------------------------- def test_ccx_gate_deterministic_default_basis_gates(self): """Test ccx-gate circuits compiling to backend default basis_gates.""" circuits = ref_non_clifford.ccx_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.ccx_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_ccx_gate_deterministic_waltz_basis_gates(self): """Test ccx-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_non_clifford.ccx_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.ccx_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_ccx_gate_deterministic_minimal_basis_gates(self): """Test ccx-gate gate circuits compiling to u3,cx""" circuits = ref_non_clifford.ccx_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.ccx_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_ccx_gate_nondeterministic_default_basis_gates(self): """Test ccx-gate circuits compiling to backend default basis_gates.""" circuits = ref_non_clifford.ccx_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.ccx_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_ccx_gate_nondeterministic_waltz_basis_gates(self): """Test ccx-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_non_clifford.ccx_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.ccx_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_ccx_gate_nondeterministic_minimal_basis_gates(self): """Test ccx-gate gate circuits compiling to u3,cx""" circuits = ref_non_clifford.ccx_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.ccx_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test unitary gate qobj instruction # --------------------------------------------------------------------- def test_unitary_gate(self): """Test simulation with unitary gate circuit instructions.""" circuits = ref_unitary_gate.unitary_gate_circuits_deterministic( final_measure=False) targets = ref_unitary_gate.unitary_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_diagonal_gate(self): """Test simulation with diagonal gate circuit instructions.""" circuits = ref_diagonal_gate.diagonal_gate_circuits_deterministic( final_measure=False) targets = ref_diagonal_gate.diagonal_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test cu1 gate # --------------------------------------------------------------------- def test_cu1_gate_nondeterministic_default_basis_gates(self): """Test cu1-gate gate circuits compiling to default basis.""" circuits = ref_non_clifford.cu1_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.cu1_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cu1_gate_nondeterministic_waltz_basis_gates(self): """Test cu1-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_non_clifford.cu1_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.cu1_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cu1_gate_nondeterministic_minimal_basis_gates(self): """Test cu1-gate gate circuits compiling to u3,cx""" circuits = ref_non_clifford.cu1_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.cu1_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test cswap-gate (Fredkin) # --------------------------------------------------------------------- def test_cswap_gate_deterministic_default_basis_gates(self): """Test cswap-gate circuits compiling to backend default basis_gates.""" circuits = ref_non_clifford.cswap_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.cswap_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cswap_gate_deterministic_minimal_basis_gates(self): """Test cswap-gate gate circuits compiling to u3,cx""" circuits = ref_non_clifford.cswap_gate_circuits_deterministic( final_measure=True) targets = ref_non_clifford.cswap_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cswap_gate_deterministic_waltz_basis_gates(self): """Test cswap-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_non_clifford.cswap_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.cswap_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cswap_gate_nondeterministic_default_basis_gates(self): """Test cswap-gate circuits compiling to backend default basis_gates.""" circuits = ref_non_clifford.cswap_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.cswap_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cswap_gate_nondeterministic_minimal_basis_gates(self): """Test cswap-gate gate circuits compiling to u3,cx""" circuits = ref_non_clifford.cswap_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.cswap_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cswap_gate_nondeterministic_waltz_basis_gates(self): """Test cswap-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_non_clifford.cswap_gate_circuits_nondeterministic( final_measure=False) targets = ref_non_clifford.cswap_gate_statevector_nondeterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test cu3-gate (Fredkin) # --------------------------------------------------------------------- def test_cu3_gate_deterministic_default_basis_gates(self): """Test cu3-gate circuits compiling to backend default basis_gates.""" circuits = ref_non_clifford.cu3_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.cu3_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cu3_gate_deterministic_minimal_basis_gates(self): """Test cu3-gate gate circuits compiling to u3,cx""" circuits = ref_non_clifford.cu3_gate_circuits_deterministic( final_measure=True) targets = ref_non_clifford.cu3_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) def test_cu3_gate_deterministic_waltz_basis_gates(self): """Test cu3-gate gate circuits compiling to u1,u2,u3,cx""" circuits = ref_non_clifford.cu3_gate_circuits_deterministic( final_measure=False) targets = ref_non_clifford.cu3_gate_statevector_deterministic() job = execute(circuits, self.SIMULATOR, shots=1, basis_gates=['u1', 'u2', 'u3', 'cx'], backend_options=self.BACKEND_OPTS) result = job.result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets) # --------------------------------------------------------------------- # Test global phase # --------------------------------------------------------------------- def test_qobj_global_phase(self): """Test qobj global phase.""" circuits = ref_1q_clifford.h_gate_circuits_nondeterministic( final_measure=False) targets = ref_1q_clifford.h_gate_statevector_nondeterministic() qobj = assemble(transpile(circuits, self.SIMULATOR), shots=1, backend_options=self.BACKEND_OPTS) # Set global phases for i, _ in enumerate(circuits): global_phase = (-1) ** i * (pi / 4) qobj.experiments[i].header.global_phase = global_phase targets[i] = exp(1j * global_phase) * targets[i] result = self.SIMULATOR.run(qobj).result() self.assertSuccess(result) self.compare_statevector(result, circuits, targets, ignore_phase=False)	0	0	0
123ca78a2356ea365d65b74f4b9b8e4302d0f4f3	350	py	Python	account/migrations/0002_auto_20201105_1938.py	zzZ5/compost	00cc2cbc74df6626e07072c8c1e638ffd9bac8f1	[ "MIT" ]	1	2020-11-28T00:06:06.000Z	2020-11-28T00:06:06.000Z	account/migrations/0002_auto_20201105_1938.py	zzZ5/compost	00cc2cbc74df6626e07072c8c1e638ffd9bac8f1	[ "MIT" ]	null	null	null	account/migrations/0002_auto_20201105_1938.py	zzZ5/compost	00cc2cbc74df6626e07072c8c1e638ffd9bac8f1	[ "MIT" ]	null	null	null	# Generated by Django 3.0.8 on 2020-11-05 19:38 from django.db import migrations	18.421053	47	0.568571	# Generated by Django 3.0.8 on 2020-11-05 19:38 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('account', '0001_initial'), ] operations = [ migrations.RenameField( model_name='user', old_name='name', new_name='username', ), ]	0	244	23
ca706a41024e87211c983a6cb0fdc4ec44bdb20f	331	py	Python	tests/config.py	cjolowicz/muckr-service	014017ab92bd1d2034cd398f2e98a6fdaf30f164	[ "MIT" ]	null	null	null	tests/config.py	cjolowicz/muckr-service	014017ab92bd1d2034cd398f2e98a6fdaf30f164	[ "MIT" ]	12	2018-12-21T22:13:33.000Z	2019-08-03T20:03:19.000Z	tests/config.py	cjolowicz/muckr-service	014017ab92bd1d2034cd398f2e98a6fdaf30f164	[ "MIT" ]	null	null	null	"""Configuration for the test app.""" ADMIN_USERNAME = "admin" ADMIN_EMAIL = "admin@localhost" ADMIN_PASSWORD = "9V0aGfEGAkQTfn8GICqHjAqCzodsUL6IVp02GmtKML8" BCRYPT_LOG_ROUNDS = 4 SECRET_KEY = "lzlD6LdPmLI6rX-4eEMUeLsIcnkXaDDQYqrAIKahsdY" SQLALCHEMY_DATABASE_URI = "sqlite://" SQLALCHEMY_TRACK_MODIFICATIONS = False TESTING = True	33.1	62	0.821752	"""Configuration for the test app.""" ADMIN_USERNAME = "admin" ADMIN_EMAIL = "admin@localhost" ADMIN_PASSWORD = "9V0aGfEGAkQTfn8GICqHjAqCzodsUL6IVp02GmtKML8" BCRYPT_LOG_ROUNDS = 4 SECRET_KEY = "lzlD6LdPmLI6rX-4eEMUeLsIcnkXaDDQYqrAIKahsdY" SQLALCHEMY_DATABASE_URI = "sqlite://" SQLALCHEMY_TRACK_MODIFICATIONS = False TESTING = True	0	0	0
06c1e791f45b52a84e1415581c12c0bffeacd27b	3,932	py	Python	colordistance/app.py	chriskiehl/color-distance-tool	aa44db7bde5509d4b909cd635bc07a78adb0f4f0	[ "MIT" ]	1	2020-10-31T07:58:23.000Z	2020-10-31T07:58:23.000Z	colordistance/app.py	chriskiehl/color-distance-tool	aa44db7bde5509d4b909cd635bc07a78adb0f4f0	[ "MIT" ]	null	null	null	colordistance/app.py	chriskiehl/color-distance-tool	aa44db7bde5509d4b909cd635bc07a78adb0f4f0	[ "MIT" ]	null	null	null	import wx import wx.lib.mixins.inspection from pynput import mouse import sys import os import colordistance.core as core import colordistance.screen as screen from colordistance.components import ColorSelector, DifferenceLine from colordistance.util import assoc class Application(wx.Frame): """ Entry point for the application. This is a quick and dirty tool for grabbing pixel colors from any location / program on the the screen and listing their values and distances in various color spaces. """ def updateState(self, nextState): """ Update the main component's state and project new views to children. """ # propagate the new info to the children self.state = nextState for child in [self.leftSwatch, self.rightSwatch]: props = nextState[child.id] isSelected = nextState['selected'] == child.id child.updateProps(assoc(core.colorspaces(props), 'selected', isSelected)) self.difference.updateProps(core.computeDiff(nextState)) def onExternalMouseClick(self, x, y, button, pressed): """ Unhooks the external mouse listener when a click is registered. """ if core.isListening(self.state): self.stopInputListers() def onExternalMouseMove(self, x, y): """ Update the selected swatch with the color found at the current mouse coordinates. """ selected = self.state['selected'] rgb = screen.get_pixel(x, y) self.updateState(core.updateColor(self.state, selected, rgb)) def onStartColorSelection(self, swatchId): """ Select the supplied Swatch and install a global mouse listener. """ self.updateState(core.selectSwatch(self.state, swatchId)) self.startInputListeners() def startInputListeners(self): """ Start a mouse listener on a separate thread. """ if self.mouseListener: self.mouseListener.stop() # it's got some weird threading setup that # requires it to be destroyed / recreated self.mouseListener = mouse.Listener(on_click=self.onExternalMouseClick, on_move=self.onExternalMouseMove) self.mouseListener.start() def stopInputListers(self): """ Shut down the current listener """ self.mouseListener.stop() if __name__ == '__main__': run()	32.229508	113	0.637335	import wx import wx.lib.mixins.inspection from pynput import mouse import sys import os import colordistance.core as core import colordistance.screen as screen from colordistance.components import ColorSelector, DifferenceLine from colordistance.util import assoc class Application(wx.Frame): """ Entry point for the application. This is a quick and dirty tool for grabbing pixel colors from any location / program on the the screen and listing their values and distances in various color spaces. """ def __init__(self, args, kwargs): super(Application, self).__init__(args, **kwargs) self.keyboardListener = None self.mouseListener = None self.state = { 'selected': None, 'left': {'color': (255, 255, 255)}, 'right': {'color': (255, 255, 255)} } self.leftSwatch = ColorSelector(self, id='left', onClick=self.onStartColorSelection) self.rightSwatch = ColorSelector(self, id='right', onClick=self.onStartColorSelection) self.difference = DifferenceLine(self) path = os.path.join(os.path.dirname(__file__), 'icon.PNG') self.icon = wx.Icon(path, wx.BITMAP_TYPE_PNG) self.layout() self.updateState(self.state) def updateState(self, nextState): """ Update the main component's state and project new views to children. """ # propagate the new info to the children self.state = nextState for child in [self.leftSwatch, self.rightSwatch]: props = nextState[child.id] isSelected = nextState['selected'] == child.id child.updateProps(assoc(core.colorspaces(props), 'selected', isSelected)) self.difference.updateProps(core.computeDiff(nextState)) def onExternalMouseClick(self, x, y, button, pressed): """ Unhooks the external mouse listener when a click is registered. """ if core.isListening(self.state): self.stopInputListers() def onExternalMouseMove(self, x, y): """ Update the selected swatch with the color found at the current mouse coordinates. """ selected = self.state['selected'] rgb = screen.get_pixel(x, y) self.updateState(core.updateColor(self.state, selected, rgb)) def onStartColorSelection(self, swatchId): """ Select the supplied Swatch and install a global mouse listener. """ self.updateState(core.selectSwatch(self.state, swatchId)) self.startInputListeners() def startInputListeners(self): """ Start a mouse listener on a separate thread. """ if self.mouseListener: self.mouseListener.stop() # it's got some weird threading setup that # requires it to be destroyed / recreated self.mouseListener = mouse.Listener(on_click=self.onExternalMouseClick, on_move=self.onExternalMouseMove) self.mouseListener.start() def stopInputListers(self): """ Shut down the current listener """ self.mouseListener.stop() def layout(self): self.SetIcon(self.icon) self.SetSize(500, 250) self.SetBackgroundColour(self.leftSwatch.GetBackgroundColour()) self.SetTitle("Color Distance Tool") sizer = wx.BoxSizer(wx.HORIZONTAL) sizer.Add(self.leftSwatch, wx.EXPAND) sizer.Add(self.rightSwatch, wx.EXPAND) v = wx.BoxSizer(wx.VERTICAL) v.AddSpacer(10) v.Add(sizer, 1, wx.EXPAND) v.AddSpacer(10) line = wx.StaticLine(self, -1, style=wx.LI_HORIZONTAL) v.Add(line, 0, wx.EXPAND) v.Add(self.difference, 1, wx.EXPAND) self.SetSizer(v) def run(): app = wx.App(False) frame = Application(None) frame.Show(True) app.MainLoop() if __name__ == '__main__': run()	1,404	0	76
402a5f09a08992f4c3337ba570a6e028e88dbbac	657	py	Python	Conceptos/funciones_integradas.py	jaramosperez/Pythonizando	3571a6451b383ed5fea35f84e3444fd946c6560d	[ "MIT" ]	1	2020-07-13T04:34:34.000Z	2020-07-13T04:34:34.000Z	Conceptos/funciones_integradas.py	jaramosperez/Pythonizando	3571a6451b383ed5fea35f84e3444fd946c6560d	[ "MIT" ]	null	null	null	Conceptos/funciones_integradas.py	jaramosperez/Pythonizando	3571a6451b383ed5fea35f84e3444fd946c6560d	[ "MIT" ]	null	null	null	n = '10.5' print(n) float(n) print(n) cadena = "Un numero podría ser " + str(10) + ' y un decimal podria ser ' + str(12.4) print(cadena) # CONVERSION DE UN NUMERO A BINARIO print(bin(10)) # CONVERSION DE UN NUMERO A HEXADECIMAL print(hex(13)) #CONVERSION DE UNA CADENA A BINARIO print(int('0b1010', 2)) #CONVERSION DE UNA CADENA A HEXADECIMAL print(int('0xd', 16)) #VALOR ABSOLUTO print(abs(-10)) print(abs(10)) #REDONDEAR NUMEROS print(round(5.5)) print(round(5.4)) # FUNCION EVAL print(eval('2+6')) numero = 30 print(eval('(numero *3 +15)/2')) # FUNCION LEN(largo de una variable) print(len('Hola soy un pythonizado')) print(len([])) #FUNCION HELP	18.25	84	0.689498	n = '10.5' print(n) float(n) print(n) cadena = "Un numero podría ser " + str(10) + ' y un decimal podria ser ' + str(12.4) print(cadena) # CONVERSION DE UN NUMERO A BINARIO print(bin(10)) # CONVERSION DE UN NUMERO A HEXADECIMAL print(hex(13)) #CONVERSION DE UNA CADENA A BINARIO print(int('0b1010', 2)) #CONVERSION DE UNA CADENA A HEXADECIMAL print(int('0xd', 16)) #VALOR ABSOLUTO print(abs(-10)) print(abs(10)) #REDONDEAR NUMEROS print(round(5.5)) print(round(5.4)) # FUNCION EVAL print(eval('2+6')) numero = 30 print(eval('(numero *3 +15)/2')) # FUNCION LEN(largo de una variable) print(len('Hola soy un pythonizado')) print(len([])) #FUNCION HELP	0	0	0
499c5dcfc041d8549b4e3d3dd514330f36a6074d	361	py	Python	test7.py	Tealaves/mypython	151f29eb720889710c7705a0c674b097bcec50f3	[ "Apache-2.0" ]	null	null	null	test7.py	Tealaves/mypython	151f29eb720889710c7705a0c674b097bcec50f3	[ "Apache-2.0" ]	null	null	null	test7.py	Tealaves/mypython	151f29eb720889710c7705a0c674b097bcec50f3	[ "Apache-2.0" ]	null	null	null	#!/bin/python print('I am:', __name__) if __name__ == '__main__': print(minmax(lessthan, 4, 2, 1, 5, 6, 3)) print(minmax(grtrthan, 4, 2, 1, 5, 6, 3))	20.055556	45	0.554017	#!/bin/python print('I am:', __name__) def minmax(test, *args): res = args[0] for arg in args[:-1]: if test(arg, res): res = arg return res def lessthan(x, y): return x < y def grtrthan(x, y): return x > y if __name__ == '__main__': print(minmax(lessthan, 4, 2, 1, 5, 6, 3)) print(minmax(grtrthan, 4, 2, 1, 5, 6, 3))	133	0	68
44a2faac9c8324a37b1a4590881412884bc6bc79	4,116	py	Python	xc7/utils/prjxray_create_place_constraints.py	mjasperse/symbiflow-arch-defs	ff3aedec45c0f886260b34ff5288482a89411d13	[ "ISC" ]	null	null	null	xc7/utils/prjxray_create_place_constraints.py	mjasperse/symbiflow-arch-defs	ff3aedec45c0f886260b34ff5288482a89411d13	[ "ISC" ]	null	null	null	xc7/utils/prjxray_create_place_constraints.py	mjasperse/symbiflow-arch-defs	ff3aedec45c0f886260b34ff5288482a89411d13	[ "ISC" ]	null	null	null	""" Convert a PCF file into a VPR io.place file. """ from __future__ import print_function import argparse import sys import vpr_place_constraints import sqlite3 import lxml.etree as ET if __name__ == '__main__': main()	24.35503	79	0.629981	""" Convert a PCF file into a VPR io.place file. """ from __future__ import print_function import argparse import sys import vpr_place_constraints import sqlite3 import lxml.etree as ET def get_tile_capacities(arch_xml_filename): arch = ET.parse(arch_xml_filename, ET.XMLParser(remove_blank_text=True)) root = arch.getroot() tile_capacities = {} for el in root.iter('tile'): tile_name = el.attrib['name'] capacity = 1 if 'capacity' in el.attrib: capacity = int(el.attrib['capacity']) tile_capacities[tile_name] = capacity grid = {} for el in root.iter('single'): x = int(el.attrib['x']) y = int(el.attrib['y']) grid[(x, y)] = tile_capacities[el.attrib['type']] return grid def get_vpr_coords_from_site_name(conn, site_name, grid_capacities): site_name = site_name.replace('"', '') cur = conn.cursor() cur.execute( """ SELECT DISTINCT tile.pkey, tile.grid_x, tile.grid_y FROM site_instance INNER JOIN wire_in_tile ON site_instance.site_pkey = wire_in_tile.site_pkey INNER JOIN wire ON wire.phy_tile_pkey = site_instance.phy_tile_pkey AND wire_in_tile.pkey = wire.wire_in_tile_pkey INNER JOIN tile ON tile.pkey = wire.tile_pkey WHERE site_instance.name = ?;""", (site_name, ) ) results = cur.fetchall() assert len(results) == 1 tile_pkey, x, y = results[0] capacity = grid_capacities[(x, y)] if capacity == 1: return (x, y, 0) else: cur.execute( """ SELECT site_instance.name FROM site_instance INNER JOIN site ON site_instance.site_pkey = site.pkey INNER JOIN site_type ON site.site_type_pkey = site_type.pkey WHERE site_instance.phy_tile_pkey IN ( SELECT phy_tile_pkey FROM tile WHERE pkey = ? ) AND site_instance.site_pkey IN ( SELECT wire_in_tile.site_pkey FROM wire_in_tile WHERE wire_in_tile.pkey IN ( SELECT wire_in_tile_pkey FROM wire WHERE tile_pkey = ? ) ) ORDER BY site_type.name, site_instance.x_coord, site_instance.y_coord; """, (tile_pkey, tile_pkey) ) instance_idx = None for idx, (a_site_name, ) in enumerate(cur): if a_site_name == site_name: assert instance_idx is None, (tile_pkey, site_name) instance_idx = idx break assert instance_idx is not None, (tile_pkey, site_name) return (x, y, instance_idx) def main(): parser = argparse.ArgumentParser( description='Convert a PCF file into a VPR io.place file.' ) parser.add_argument( "--input", '-i', "-I", type=argparse.FileType('r'), default=sys.stdout, help='The output constraints place file' ) parser.add_argument( "--output", '-o', "-O", type=argparse.FileType('w'), default=sys.stdout, help='The output constraints place file' ) parser.add_argument( "--net", '-n', type=argparse.FileType('r'), required=True, help='top.net file' ) parser.add_argument( '--connection_database', help='Database of fabric connectivity', required=True ) parser.add_argument('--arch', help='Arch XML', required=True) args = parser.parse_args() for line in args.input: args.output.write(line) place_constraints = vpr_place_constraints.PlaceConstraints() place_constraints.load_loc_sites_from_net_file(args.net) grid_capacities = get_tile_capacities(args.arch) with sqlite3.connect(args.connection_database) as conn: for block, loc in place_constraints.get_loc_sites(): vpr_loc = get_vpr_coords_from_site_name(conn, loc, grid_capacities) place_constraints.constrain_block( block, vpr_loc, "Constraining block {}".format(block) ) place_constraints.output_place_constraints(args.output) if __name__ == '__main__': main()	3,818	0	69
ea5d3faa9c5f5e6eaf055e946f6ea32a73b4a57e	7,301	py	Python	da/examples/ratoken/spec.py	yagrawal-sbu/distalgo	10e6db89b7db05d3b076dcf9295ce4f189558323	[ "MIT" ]	null	null	null	da/examples/ratoken/spec.py	yagrawal-sbu/distalgo	10e6db89b7db05d3b076dcf9295ce4f189558323	[ "MIT" ]	null	null	null	da/examples/ratoken/spec.py	yagrawal-sbu/distalgo	10e6db89b7db05d3b076dcf9295ce4f189558323	[ "MIT" ]	null	null	null	# -- generated by 1.0.9 -- import da PatternExpr_243 = da.pat.TuplePattern([da.pat.ConstantPattern('access'), da.pat.FreePattern('newtok')]) PatternExpr_255 = da.pat.TuplePattern([da.pat.ConstantPattern('request'), da.pat.FreePattern('c'), da.pat.FreePattern('p')]) PatternExpr_283 = da.pat.TuplePattern([da.pat.ConstantPattern('request'), da.pat.FreePattern('c'), da.pat.BoundPattern('_BoundPattern288_')]) PatternExpr_318 = da.pat.TuplePattern([da.pat.ConstantPattern('access'), da.pat.FreePattern(None)]) PatternExpr_339 = da.pat.TuplePattern([da.pat.ConstantPattern('access'), da.pat.FreePattern('token1')]) PatternExpr_361 = da.pat.TuplePattern([da.pat.ConstantPattern('access'), da.pat.FreePattern('token2')]) PatternExpr_424 = da.pat.TuplePattern([da.pat.ConstantPattern('Done')]) PatternExpr_429 = da.pat.BoundPattern('_BoundPattern430_') PatternExpr_431 = da.pat.TuplePattern([da.pat.FreePattern(None), da.pat.TuplePattern([da.pat.FreePattern(None), da.pat.FreePattern(None), da.pat.BoundPattern('_BoundPattern437_')]), da.pat.TuplePattern([da.pat.ConstantPattern('Done')])]) _config_object = {} import sys	49	1,219	0.618819	# -- generated by 1.0.9 -- import da PatternExpr_243 = da.pat.TuplePattern([da.pat.ConstantPattern('access'), da.pat.FreePattern('newtok')]) PatternExpr_255 = da.pat.TuplePattern([da.pat.ConstantPattern('request'), da.pat.FreePattern('c'), da.pat.FreePattern('p')]) PatternExpr_283 = da.pat.TuplePattern([da.pat.ConstantPattern('request'), da.pat.FreePattern('c'), da.pat.BoundPattern('_BoundPattern288_')]) PatternExpr_318 = da.pat.TuplePattern([da.pat.ConstantPattern('access'), da.pat.FreePattern(None)]) PatternExpr_339 = da.pat.TuplePattern([da.pat.ConstantPattern('access'), da.pat.FreePattern('token1')]) PatternExpr_361 = da.pat.TuplePattern([da.pat.ConstantPattern('access'), da.pat.FreePattern('token2')]) PatternExpr_424 = da.pat.TuplePattern([da.pat.ConstantPattern('Done')]) PatternExpr_429 = da.pat.BoundPattern('_BoundPattern430_') PatternExpr_431 = da.pat.TuplePattern([da.pat.FreePattern(None), da.pat.TuplePattern([da.pat.FreePattern(None), da.pat.FreePattern(None), da.pat.BoundPattern('_BoundPattern437_')]), da.pat.TuplePattern([da.pat.ConstantPattern('Done')])]) _config_object = {} import sys class P(da.DistProcess): def __init__(self, procimpl, props): super().__init__(procimpl, props) self._PReceivedEvent_2 = [] self._PSentEvent_3 = [] self._PReceivedEvent_4 = [] self._PSentEvent_5 = [] self._PReceivedEvent_6 = [] self._events.extend([da.pat.EventPattern(da.pat.ReceivedEvent, '_PReceivedEvent_0', PatternExpr_243, sources=None, destinations=None, timestamps=None, record_history=None, handlers=[self._P_handler_242]), da.pat.EventPattern(da.pat.ReceivedEvent, '_PReceivedEvent_1', PatternExpr_255, sources=None, destinations=None, timestamps=None, record_history=None, handlers=[self._P_handler_254]), da.pat.EventPattern(da.pat.ReceivedEvent, '_PReceivedEvent_2', PatternExpr_283, sources=None, destinations=None, timestamps=None, record_history=True, handlers=[]), da.pat.EventPattern(da.pat.SentEvent, '_PSentEvent_3', PatternExpr_318, sources=None, destinations=None, timestamps=None, record_history=True, handlers=[]), da.pat.EventPattern(da.pat.ReceivedEvent, '_PReceivedEvent_4', PatternExpr_339, sources=None, destinations=None, timestamps=None, record_history=True, handlers=[]), da.pat.EventPattern(da.pat.SentEvent, '_PSentEvent_5', PatternExpr_361, sources=None, destinations=None, timestamps=None, record_history=True, handlers=[]), da.pat.EventPattern(da.pat.ReceivedEvent, '_PReceivedEvent_6', PatternExpr_424, sources=[PatternExpr_429], destinations=None, timestamps=None, record_history=True, handlers=[])]) def setup(self, ps, nrounds, orig_token, rest_519): super().setup(ps=ps, nrounds=nrounds, orig_token=orig_token, rest_519) self._state.ps = ps self._state.nrounds = nrounds self._state.orig_token = orig_token self._state.clock = 0 self._state.token = dict(((p, 0) for p in self._state.ps)) def run(self): def anounce(): self.output('In cs!') if self.token_present(): self.output("I'm lucky!") for i in range(self._state.nrounds): self.cs(anounce) self.send(('Done',), to=self._state.ps) super()._label('_st_label_415', block=False) p = None def UniversalOpExpr_416(): nonlocal p for p in self._state.ps: if (not PatternExpr_431.match_iter(self._PReceivedEvent_6, _BoundPattern437_=p, SELF_ID=self._id)): return False return True _st_label_415 = 0 while (_st_label_415 == 0): _st_label_415 += 1 if UniversalOpExpr_416(): _st_label_415 += 1 else: super()._label('_st_label_415', block=True) _st_label_415 -= 1 self.output('Done!') def cs(self, task): super()._label('request', block=False) if (not self.token_present()): self._state.clock += 1 self.send(('request', self._state.clock, self._id), to=self._state.ps) super()._label('_st_label_210', block=False) _st_label_210 = 0 while (_st_label_210 == 0): _st_label_210 += 1 if self.token_present(): _st_label_210 += 1 else: super()._label('_st_label_210', block=True) _st_label_210 -= 1 self._state.token[self._id] = self._state.clock task() super()._label('release', block=False) for p in self._state.ps: if (self.request_pending(p) and self.token_present()): self.send(('access', self._state.token), to=p) break def request_pending(self, p): c = None def ExistentialOpExpr_281(): nonlocal c for (_, _, (_ConstantPattern299_, c, _BoundPattern302_)) in self._PReceivedEvent_2: if (_ConstantPattern299_ == 'request'): if (_BoundPattern302_ == p): if (c > self._state.token[p]): return True return False return ExistentialOpExpr_281() def token_present(self): def ExistentialOpExpr_316(): for (_, _, (_ConstantPattern332_, _)) in self._PSentEvent_3: if (_ConstantPattern332_ == 'access'): if True: return True return False token1 = token2 = None def ExistentialOpExpr_337(): nonlocal token1, token2 for (_, _, (_ConstantPattern354_, token1)) in self._PReceivedEvent_4: if (_ConstantPattern354_ == 'access'): def ExistentialOpExpr_359(token1): nonlocal token2 for (_, _, (_ConstantPattern376_, token2)) in self._PSentEvent_5: if (_ConstantPattern376_ == 'access'): if (token2[self._id] > token1[self._id]): return True return False if (not ExistentialOpExpr_359(token1=token1)): return True return False return ((self._state.orig_token and (not ExistentialOpExpr_316())) or ExistentialOpExpr_337()) def _P_handler_242(self, newtok): self._state.token = newtok _P_handler_242._labels = None _P_handler_242._notlabels = None def _P_handler_254(self, c, p): if (self.request_pending(p) and self.token_present()): self.send(('access', self._state.token), to=p) _P_handler_254._labels = None _P_handler_254._notlabels = None class Node_(da.NodeProcess): def __init__(self, procimpl, props): super().__init__(procimpl, props) self._events.extend([]) def run(self): nprocs = (int(sys.argv[1]) if (len(sys.argv) > 1) else 10) nrounds = (int(sys.argv[2]) if (len(sys.argv) > 2) else 1) ps = self.new(P, num=nprocs) p = ps.pop() self._setup(ps, ((ps \| {p}), nrounds, False)) self._setup([p], ((ps \| {p}), nrounds, True)) self._start((ps \| {p}))	5,715	368	100
819231ebcb82e1951e26b4701c363d5616596d38	13,846	py	Python	backend/moonstreamapi/providers/moonworm_provider.py	lsheiba/moonstream	1cead0413e3e7ad96e2cded6b9cc3a95c6b7e7e0	[ "Apache-2.0" ]	67	2021-07-22T11:09:30.000Z	2022-03-30T07:38:19.000Z	backend/moonstreamapi/providers/moonworm_provider.py	lsheiba/moonstream	1cead0413e3e7ad96e2cded6b9cc3a95c6b7e7e0	[ "Apache-2.0" ]	246	2021-07-19T15:40:59.000Z	2022-03-24T20:30:55.000Z	backend/moonstreamapi/providers/moonworm_provider.py	lsheiba/moonstream	1cead0413e3e7ad96e2cded6b9cc3a95c6b7e7e0	[ "Apache-2.0" ]	21	2021-07-25T18:36:05.000Z	2022-03-30T16:30:24.000Z	import logging from dataclasses import dataclass, field from typing import Any, Dict, List, Optional, Tuple, cast from bugout.app import Bugout from bugout.data import BugoutResource from moonstreamdb.blockchain import AvailableBlockchainType, get_label_model from sqlalchemy import and_, or_, text from sqlalchemy.orm import Query, Session, query_expression from sqlalchemy.sql.expression import label from .. import data from ..stream_boundaries import validate_stream_boundary from ..stream_queries import StreamQuery logger = logging.getLogger(__name__) logger.setLevel(logging.WARN) ethereum_event_type = "ethereum_blockchain" polygon_event_type = "polygon_blockchain" allowed_tags = ["tag:erc721"] description = f"""Event provider for transactions from the Ethereum blockchain. To restrict your queries to this provider, add a filter of \"type:{ethereum_event_type}\{polygon_event_type}\" to your query (query parameter: \"q\") on the /streams endpoint.""" default_time_interval_seconds: int = 5 * 60 # 200 transactions per block, 4 blocks per minute. estimated_events_per_time_interval: float = 5 * 800 @dataclass @dataclass @dataclass @dataclass EthereumMoonwormProvider = MoonwormProvider( event_type="ethereum_smartcontract", blockchain=AvailableBlockchainType("ethereum"), description="Provider for resiving transactions from Ethereum tables.", streamboaundary_range_limit=2 * 60 * 60, ) PolygonMoonwormProvider = MoonwormProvider( event_type="polygon_smartcontract", blockchain=AvailableBlockchainType("polygon"), description="Provider for resiving transactions from Polygon tables.", streamboaundary_range_limit=2 * 60 * 60, )	34.187654	178	0.640546	import logging from dataclasses import dataclass, field from typing import Any, Dict, List, Optional, Tuple, cast from bugout.app import Bugout from bugout.data import BugoutResource from moonstreamdb.blockchain import AvailableBlockchainType, get_label_model from sqlalchemy import and_, or_, text from sqlalchemy.orm import Query, Session, query_expression from sqlalchemy.sql.expression import label from .. import data from ..stream_boundaries import validate_stream_boundary from ..stream_queries import StreamQuery logger = logging.getLogger(__name__) logger.setLevel(logging.WARN) ethereum_event_type = "ethereum_blockchain" polygon_event_type = "polygon_blockchain" allowed_tags = ["tag:erc721"] description = f"""Event provider for transactions from the Ethereum blockchain. To restrict your queries to this provider, add a filter of \"type:{ethereum_event_type}\{polygon_event_type}\" to your query (query parameter: \"q\") on the /streams endpoint.""" default_time_interval_seconds: int = 5 * 60 # 200 transactions per block, 4 blocks per minute. estimated_events_per_time_interval: float = 5 * 800 @dataclass class ArgsFilters: name: str value: Any type: str @dataclass class LabelsFilters: name: str type: str args: List[ArgsFilters] = field(default_factory=list) @dataclass class AddressFilters: address: str label_filters: List[LabelsFilters] = field(default_factory=list) @dataclass class Filters: addresses: List[AddressFilters] = field(default_factory=list) class MoonwormProvider: def __init__( self, event_type: str, blockchain: AvailableBlockchainType, description: str, streamboaundary_range_limit: int, ): self.event_type = event_type self.blockchain = blockchain self.description = description self.valid_period_seconds = streamboaundary_range_limit def default_filters(self, subscriptions: List[BugoutResource]) -> Filters: """ Default filter strings for the given list of subscriptions. """ filters = Filters() for subscription in subscriptions: subscription_address = cast( Optional[str], subscription.resource_data.get("address") ) if subscription_address is not None: # How apply labels? filters.addresses.append( AddressFilters(address=subscription_address, label_filters=[]) ) else: logger.warn( f"Could not find subscription address for subscription with resource id: {subscription.id}" ) return filters def apply_query_filters(self, filters: Filters, query_filters: StreamQuery): """ Required to implement filters wich depends on procider """ pass def events(self, row: Tuple) -> data.Event: """ Parses a result from the result set of a database query for Ethereum transactions with block timestamp into an Event object. """ ( block_number, address, transaction_hash, label_data, block_timestamp, log_index, created_at, ) = row return data.Event( event_type=self.event_type, event_timestamp=block_timestamp, event_data={ "hash": transaction_hash, "block_number": block_number, "address": address, "label_data": label_data, "log_index": log_index, "created_at": created_at, }, ) def parse_filters( self, query: StreamQuery, user_subscriptions: Dict[str, List[BugoutResource]], ) -> Optional[Filters]: """ Passes raw filter strings into a Filters object which is used to construct a database query for ethereum transactions. Right now support only addresses query. """ if query.subscription_types and not any( subtype == self.event_type for subtype in query.subscription_types ): return None provider_subscriptions = user_subscriptions.get(self.event_type) # If the user has no subscriptions to this event type, we do not have to return any data! if not provider_subscriptions: return None parsed_filters = self.default_filters(provider_subscriptions) self.apply_query_filters(parsed_filters, query) if not (parsed_filters.addresses): return None return parsed_filters def stream_boundary_validator( self, stream_boundary: data.StreamBoundary ) -> data.StreamBoundary: """ Stream boundary validator for the events provider. Checks that stream boundaries do not exceed periods of greater than 24 hours. Raises an error for invalid stream boundaries, else returns None. """ valid_period_seconds = self.valid_period_seconds _, stream_boundary = validate_stream_boundary( stream_boundary, valid_period_seconds, raise_when_invalid=True ) return stream_boundary def generate_events_query( self, db_session: Session, stream_boundary: data.StreamBoundary, parsed_filters: Filters, ) -> Query: """ Builds a database query for Ethereum transactions that occurred within the window of time that the given stream_boundary represents and satisfying the constraints of parsed_filters. """ Labels = get_label_model(self.blockchain) query = db_session.query( Labels.block_number, Labels.address, Labels.transaction_hash, Labels.label_data, Labels.block_timestamp, Labels.log_index, Labels.created_at, ).filter(Labels.label == "moonworm") if stream_boundary.include_start: query = query.filter(Labels.block_timestamp >= stream_boundary.start_time) else: query = query.filter(Labels.block_timestamp > stream_boundary.start_time) if stream_boundary.end_time is not None: if stream_boundary.include_end: query = query.filter(Labels.block_timestamp <= stream_boundary.end_time) else: query = query.filter(Labels.block_timestamp <= stream_boundary.end_time) addresses_filters = [] for address_filter in parsed_filters.addresses: labels_filters = [] for label_filter in address_filter.label_filters: labels_filters.append( and_( ( Labels.label_data["type"] == label_filter.type, Labels.label_data["name"] == label_filter.name, ) ) ) addresses_filters.append( and_( ( Labels.address == address_filter.address, or_(labels_filters), ) ) ) query = query.filter(or_(addresses_filters)) return query def get_events( self, db_session: Session, bugout_client: Bugout, data_journal_id: str, data_access_token: str, stream_boundary: data.StreamBoundary, query: StreamQuery, user_subscriptions: Dict[str, List[BugoutResource]], ) -> Optional[Tuple[data.StreamBoundary, List[data.Event]]]: """ Returns blockchain events for the given addresses in the time period represented by stream_boundary. If the query does not require any data from this provider, returns None. """ stream_boundary = self.stream_boundary_validator(stream_boundary) parsed_filters = self.parse_filters(query, user_subscriptions) if parsed_filters is None: return None ethereum_transactions = self.generate_events_query( db_session, stream_boundary, parsed_filters ) ethereum_transactions = ethereum_transactions.order_by( text("block_timestamp desc") ) # TODO(zomglings): Catch the operational error denoting that the statement timed out here # and wrap it in an error that tells the API to return the appropriate 400 response. Currently, # when the statement times out, the API returns a 500 status code to the client, which doesn't # do anything to help them get data from teh backend. # The error message on the API side when the statement times out: # > sqlalchemy.exc.OperationalError: (psycopg2.errors.QueryCanceled) canceling statement due to statement timeout events: List[data.Event] = [self.events(row) for row in ethereum_transactions] if (stream_boundary.end_time is None) and events: stream_boundary.end_time = events[0].event_timestamp stream_boundary.include_end = True return stream_boundary, events def latest_events( self, db_session: Session, bugout_client: Bugout, data_journal_id: str, data_access_token: str, query: StreamQuery, num_events: int, user_subscriptions: Dict[str, List[BugoutResource]], ) -> Optional[List[data.Event]]: """ Returns the num_events latest events from the current provider, subject to the constraints imposed by the given filters. If the query does not require any data from this provider, returns None. """ assert num_events > 0, f"num_events ({num_events}) should be positive." stream_boundary = data.StreamBoundary( start_time=0, include_start=True, end_time=None, include_end=False ) parsed_filters = self.parse_filters(query, user_subscriptions) if parsed_filters is None: return None ethereum_transactions = ( self.generate_events_query(db_session, stream_boundary, parsed_filters) .order_by(text("block_timestamp desc")) .limit(num_events) ) return [self.events(row) for row in ethereum_transactions] def next_event( self, db_session: Session, bugout_client: Bugout, data_journal_id: str, data_access_token: str, stream_boundary: data.StreamBoundary, query: StreamQuery, user_subscriptions: Dict[str, List[BugoutResource]], ) -> Optional[data.Event]: """ Returns the earliest event occuring after the given stream boundary corresponding to the given query from this provider. If the query does not require any data from this provider, returns None. """ assert ( stream_boundary.end_time is not None ), "Cannot return next event for up-to-date stream boundary" next_stream_boundary = data.StreamBoundary( start_time=stream_boundary.end_time, include_start=(not stream_boundary.include_end), end_time=None, include_end=False, ) parsed_filters = self.parse_filters(query, user_subscriptions) if parsed_filters is None: return None maybe_ethereum_transaction = ( self.generate_events_query(db_session, next_stream_boundary, parsed_filters) .order_by(text("block_timestamp asc")) .limit(1) ).one_or_none() if maybe_ethereum_transaction is None: return None return self.events(maybe_ethereum_transaction) def previous_event( self, db_session: Session, bugout_client: Bugout, data_journal_id: str, data_access_token: str, stream_boundary: data.StreamBoundary, query: StreamQuery, user_subscriptions: Dict[str, List[BugoutResource]], ) -> Optional[data.Event]: """ Returns the latest event occuring before the given stream boundary corresponding to the given query from this provider. If the query does not require any data from this provider, returns None. """ assert ( stream_boundary.start_time != 0 ), "Cannot return previous event for stream starting at time 0" previous_stream_boundary = data.StreamBoundary( start_time=0, include_start=True, end_time=stream_boundary.start_time, include_end=(not stream_boundary.include_start), ) parsed_filters = self.parse_filters(query, user_subscriptions) if parsed_filters is None: return None maybe_ethereum_transaction = ( self.generate_events_query( db_session, previous_stream_boundary, parsed_filters ) .order_by(text("block_timestamp desc")) .limit(1) ).one_or_none() if maybe_ethereum_transaction is None: return None return self.events(maybe_ethereum_transaction) EthereumMoonwormProvider = MoonwormProvider( event_type="ethereum_smartcontract", blockchain=AvailableBlockchainType("ethereum"), description="Provider for resiving transactions from Ethereum tables.", streamboaundary_range_limit=2 * 60 * 60, ) PolygonMoonwormProvider = MoonwormProvider( event_type="polygon_smartcontract", blockchain=AvailableBlockchainType("polygon"), description="Provider for resiving transactions from Polygon tables.", streamboaundary_range_limit=2 * 60 * 60, )	328	11,714	111
4fadd427d9e9cb1eb6aa7eccfdde1eb29b0ac329	4,994	py	Python	microscope/monitor/epresolver.py	cilium/microscope	db922b79fb28e500f9a2d1f749620485cfda9dc0	[ "Apache-2.0" ]	16	2018-04-24T16:54:41.000Z	2021-05-13T22:49:19.000Z	microscope/monitor/epresolver.py	cilium/microscope	db922b79fb28e500f9a2d1f749620485cfda9dc0	[ "Apache-2.0" ]	50	2018-02-06T11:32:46.000Z	2021-06-01T21:54:45.000Z	microscope/monitor/epresolver.py	cilium/monitor-mux	db922b79fb28e500f9a2d1f749620485cfda9dc0	[ "Apache-2.0" ]	4	2018-02-13T10:10:34.000Z	2022-02-28T11:50:41.000Z	from typing import Dict, List, Set, Callable # https://github.com/cilium/cilium/blob/master/pkg/identity/numericidentity.go#L33 reserved_identities = { 0: ["reserved:unknown"], 1: ["reserved:host"], 2: ["reserved:world"], 3: ["reserved:cluster"], 4: ["reserved:health"], 5: ["reserved:init"] } class EndpointResolver: """EndpointResolver resolves various fields to the pod-name endpoint_data: a list of lists of endpoint objects obtained from cilium-agent or k8s CEPs """ def resolve_endpoint_ids(self, selectors: List[str], pod_names: List[str], ips: List[str], namespace: str) -> Set[int]: """resolve_endpoint_ids returns endpoint ids that match selectors, pod names and ips provided """ ids = set() ids.update( self.resolve_endpoint_ids_from_pods(pod_names), self.resolve_endpoint_ids_from_selectors(selectors, namespace), self.resolve_endpoint_ids_from_ips(ips) ) return ids	33.972789	82	0.538046	from typing import Dict, List, Set, Callable # https://github.com/cilium/cilium/blob/master/pkg/identity/numericidentity.go#L33 reserved_identities = { 0: ["reserved:unknown"], 1: ["reserved:host"], 2: ["reserved:world"], 3: ["reserved:cluster"], 4: ["reserved:health"], 5: ["reserved:init"] } def get_pod_name(ep): try: podname = ep['status']['external-identifiers']['pod-name'] except KeyError: podname = ep['external-identifiers']['pod-name'] return podname class EndpointResolver: """EndpointResolver resolves various fields to the pod-name endpoint_data: a list of lists of endpoint objects obtained from cilium-agent or k8s CEPs """ def __init__(self, endpoint_data: [Dict]): self.ip_resolutions = {} self.epid_resolutions = {} self.ip_to_epid_resolutions = {} self.endpoint_data = endpoint_data for ep in endpoint_data: podname = get_pod_name(ep) for ip in ep['status']['networking']['addressing']: try: ipv4 = ip['ipv4'] self.ip_resolutions[ipv4] = podname self.ip_to_epid_resolutions[ipv4] = ep['id'] except KeyError: pass try: ipv6 = ip['ipv6'] self.ip_resolutions[ipv6] = podname self.ip_to_epid_resolutions[ipv6] = ep['id'] except KeyError: pass # the str(ep['id']) below is needed because the ID is an # int in json self.epid_resolutions[str(ep['id'])] = podname ep_identities = {id["id"]: id["labels"] for id in [e["status"]["identity"] for e in endpoint_data]} self.identities = {ep_identities, reserved_identities} def resolve_ip(self, ip) -> str: if ip in self.ip_resolutions: return self.ip_resolutions[ip] return "" def resolve_eid(self, eid) -> str: if eid in self.epid_resolutions: return self.epid_resolutions[eid] return "" def resolve_identity(self, id) -> List: if id in self.identities: return self.identities[id] return "" def resolve_id_from_ip(self, ip) -> str: if ip in self.ip_to_epid_resolutions: return self.ip_to_epid_resolutions[ip] return "" def resolve_endpoint_ids(self, selectors: List[str], pod_names: List[str], ips: List[str], namespace: str) -> Set[int]: """resolve_endpoint_ids returns endpoint ids that match selectors, pod names and ips provided """ ids = set() ids.update( self.resolve_endpoint_ids_from_pods(pod_names), self.resolve_endpoint_ids_from_selectors(selectors, namespace), self.resolve_endpoint_ids_from_ips(ips) ) return ids def resolve_endpoint_ids_from_pods(self, pod_names: List[str]): try: namesMatch = { endpoint['id'] for endpoint in self.endpoint_data if get_pod_name(endpoint) in pod_names } except (KeyError, TypeError): # fall back to older API structure namesMatch = {endpoint['id'] for endpoint in self.endpoint_data if endpoint['pod-name'] in pod_names} return namesMatch def resolve_endpoint_ids_from_selectors(self, selectors: List[str], namespace: str): namespace_matcher = f"k8s:io.kubernetes.pod.namespace={namespace}" def labels_match(data, selectors: List[str], labels_getter: Callable[[Dict], List[str]]): return { endpoint['id'] for endpoint in data if any([ any( [selector in label for selector in selectors]) for label in labels_getter(endpoint) ]) and namespace_matcher in labels_getter(endpoint) } getters = [ lambda x: x['status']['labels']['security-relevant'], lambda x: x['labels']['orchestration-identity'], lambda x: x['labels']['security-relevant'] ] labelsMatch = [] for getter in getters: try: labelsMatch = labels_match( self.endpoint_data, selectors, getter) except (KeyError, TypeError): continue break return labelsMatch def resolve_endpoint_ids_from_ips(self, ips: List[str]): return {self.resolve_id_from_ip(ip) for ip in ips} - {''}	3,634	0	238
6f98757d8929b926f6db70c57f06a707280ee1eb	3,229	py	Python	amqp_influxdb/tests/tests.py	cloudify-cosmo/cloudify-amqp-influxdb	60c1f99bcb04876bd6a148f2815d9c900602241b	[ "Apache-2.0" ]	3	2016-08-25T00:34:26.000Z	2017-05-11T09:46:44.000Z	amqp_influxdb/tests/tests.py	cloudify-cosmo/cloudify-amqp-influxdb	60c1f99bcb04876bd6a148f2815d9c900602241b	[ "Apache-2.0" ]	5	2015-03-16T19:53:25.000Z	2018-01-06T11:59:31.000Z	amqp_influxdb/tests/tests.py	cloudify-cosmo/cloudify-amqp-influxdb	60c1f99bcb04876bd6a148f2815d9c900602241b	[ "Apache-2.0" ]	6	2015-01-21T17:09:54.000Z	2017-03-27T02:06:06.000Z	######## # Copyright (c) 2014 GigaSpaces Technologies Ltd. All rights reserved # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. ############ import unittest import threading import json import uuid import time import pika from influxdb.influxdb08 import InfluxDBClient from amqp_influxdb import (InfluxDBPublisher, AMQPTopicConsumer) influx_database = 'influx' amqp_exchange = 'exchange' routing_key = 'routing_key'	29.623853	79	0.584391	######## # Copyright (c) 2014 GigaSpaces Technologies Ltd. All rights reserved # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. ############ import unittest import threading import json import uuid import time import pika from influxdb.influxdb08 import InfluxDBClient from amqp_influxdb import (InfluxDBPublisher, AMQPTopicConsumer) influx_database = 'influx' amqp_exchange = 'exchange' routing_key = 'routing_key' class Test(unittest.TestCase): def test(self): def start(): publisher = InfluxDBPublisher( database=influx_database, host='localhost') # Default conn parameters from __main__, with username and # password specified conn_parameters = { 'host': 'localhost', 'port': 5672, 'connection_attempts': 12, 'retry_delay': 5, 'credentials': { 'username': 'guest', 'password': 'guest', }, 'ssl': False, 'ca_path': '', } consumer = AMQPTopicConsumer( exchange=amqp_exchange, routing_key=routing_key, message_processor=publisher.process, connection_parameters=conn_parameters) consumer.consume() thread = threading.Thread(target=start) thread.daemon = True thread.start() time.sleep(5) event_id = str(uuid.uuid4()) publish_event(event_id) thread.join(3) self.assertTrue(find_event(event_id), 'event not found in influxdb') def publish_event(unique_id): event = { 'node_id': 'node_id', 'node_name': 'node_name', 'deployment_id': unique_id, 'name': 'name', 'path': 'path', 'metric': 100, 'unit': '', 'type': 'type', } connection = pika.BlockingConnection( pika.ConnectionParameters(host='localhost')) channel = connection.channel() channel.exchange_declare(exchange=amqp_exchange, type='topic', durable=False, auto_delete=True, internal=False) channel.basic_publish(exchange=amqp_exchange, routing_key=routing_key, body=json.dumps(event)) channel.close() connection.close() def find_event(unique_id): client = InfluxDBClient('localhost', 8086, 'root', 'root', influx_database) results = client.query('select * from /{0}/ limit 1'.format(unique_id)) return bool(len(results))	2,173	9	96
e6e5d2f55796186a5638dbc834049ae6db8f09e8	486,178	py	Python	script.py	minecraft-design/minecraft-design.github.io	1b07c919e9dbc9a7e8c1833e2541fb5268d49a12	[ "MIT" ]	null	null	null	script.py	minecraft-design/minecraft-design.github.io	1b07c919e9dbc9a7e8c1833e2541fb5268d49a12	[ "MIT" ]	null	null	null	script.py	minecraft-design/minecraft-design.github.io	1b07c919e9dbc9a7e8c1833e2541fb5268d49a12	[ "MIT" ]	null	null	null	print("<!DOCTYPE html><html><body>") # arr =[[0, 152, 17, 252, 146, 88], [1, 260, 335, 63, 44, 17], [2, 53, 72, 130, 24, 80], [3, 352, 178, 32, 30, 287], [4, 80, 24, 17, 77, 28], [5, 85, 79, 276, 158, 63], [6, 376, 85, 16, 251, 382], [7, 17, 378, 16, 376, 384], [8, 79, 180, 183, 362, 85], [9, 80, 28, 17, 11, 36], [10, 33, 3, 25, 53, 152], [11, 28, 77, 80, 25, 85], [12, 6, 17, 378, 376, 16], [13, 210, 160, 356, 168, 63], [14, 362, 85, 125, 97, 118], [15, 25, 78, 353, 53, 43], [16, 251, 376, 382, 85, 6], [17, 80, 297, 152, 373, 75], [18, 360, 246, 377, 20, 347], [19, 104, 85, 362, 116, 125], [20, 347, 28, 374, 160, 53], [21, 14, 160, 35, 80, 28], [22, 85, 382, 258, 251, 79], [23, 24, 53, 78, 80, 28], [24, 80, 53, 130, 64, 72], [25, 160, 53, 74, 28, 130], [26, 371, 63, 88, 279, 145], [27, 30, 325, 37, 25, 210], [28, 25, 160, 14, 356, 8], [29, 371, 362, 118, 104, 125], [30, 61, 3, 32, 51, 76], [31, 181, 21, 294, 241, 43], [32, 76, 52, 3, 61, 30], [33, 53, 68, 130, 25, 24], [34, 89, 29, 246, 54, 48], [35, 371, 362, 125, 85, 14], [36, 28, 297, 14, 80, 16], [37, 90, 25, 368, 42, 48], [38, 63, 217, 44, 211, 39], [39, 45, 63, 61, 44, 46], [40, 17, 80, 25, 260, 152], [41, 63, 44, 276, 208, 61], [42, 368, 104, 22, 362, 48], [43, 25, 42, 54, 48, 89], [44, 63, 61, 276, 173, 335], [45, 39, 63, 44, 6, 386], [46, 63, 39, 61, 176, 276], [47, 347, 87, 95, 342, 80], [48, 54, 354, 368, 355, 34], [49, 80, 24, 75, 130, 53], [50, 63, 386, 83, 171, 192], [51, 30, 25, 352, 325, 160], [52, 32, 76, 337, 61, 63], [53, 130, 24, 25, 72, 80], [54, 48, 34, 89, 362, 368], [55, 178, 348, 3, 287, 352], [56, 80, 17, 75, 258, 8], [57, 42, 368, 158, 371, 116], [58, 118, 16, 22, 251, 297], [59, 80, 53, 130, 24, 363], [60, 67, 348, 287, 242, 55], [61, 63, 30, 335, 32, 52], [62, 297, 364, 6, 16, 251], [63, 44, 61, 39, 276, 371], [64, 24, 80, 53, 130, 78], [65, 382, 79, 258, 85, 22], [66, 71, 61, 260, 17, 81], [67, 60, 348, 242, 287, 178], [68, 53, 24, 130, 78, 80], [69, 85, 14, 77, 362, 97], [70, 80, 17, 49, 56, 130], [71, 343, 6, 45, 386, 376], [72, 53, 130, 2, 24, 80], [73, 6, 92, 343, 365, 105], [74, 25, 160, 28, 53, 80], [75, 258, 362, 80, 359, 17], [76, 32, 52, 61, 30, 63], [77, 80, 345, 85, 342, 22], [78, 80, 53, 24, 130, 68], [79, 85, 276, 125, 180, 153], [80, 24, 53, 130, 17, 78], [81, 28, 25, 160, 15, 11], [82, 168, 8, 210, 152, 160], [83, 79, 8, 276, 90, 356], [84, 25, 160, 28, 362, 61], [85, 79, 125, 382, 22, 276], [86, 80, 28, 347, 85, 297], [87, 80, 77, 342, 25, 47], [88, 17, 160, 350, 152, 278], [89, 256, 34, 189, 25, 368], [90, 25, 37, 53, 83, 28], [91, 22, 114, 128, 79, 258], [92, 376, 6, 73, 292, 229], [93, 80, 24, 53, 130, 78], [94, 364, 44, 17, 215, 297], [95, 80, 347, 20, 47, 28], [96, 25, 89, 42, 116, 368], [97, 362, 14, 371, 85, 104], [98, 25, 368, 104, 362, 116], [99, 107, 85, 341, 6, 297], [100, 16, 297, 17, 264, 315], [101, 20, 160, 25, 3, 34], [102, 145, 17, 88, 279, 371], [103, 25, 134, 43, 85, 320], [104, 118, 79, 116, 362, 180], [105, 112, 376, 16, 79, 251], [106, 241, 34, 22, 42, 294], [107, 123, 99, 386, 376, 85], [108, 195, 160, 328, 249, 123], [109, 364, 125, 294, 355, 241], [110, 28, 85, 160, 297, 11], [111, 29, 371, 104, 362, 355], [105, 112, 376, 16, 79, 251], [113, 158, 77, 83, 85, 256], [114, 79, 85, 125, 252, 8], [115, 34, 368, 246, 54, 161], [116, 118, 104, 362, 371, 180], [117, 211, 351, 22, 285, 336], [118, 125, 180, 116, 79, 104], [119, 85, 79, 125, 382, 22], [120, 17, 58, 376, 16, 384], [121, 160, 158, 362, 63, 347], [122, 153, 191, 79, 272, 125], [123, 107, 167, 160, 124, 290], [124, 63, 44, 123, 158, 276], [125, 79, 85, 276, 118, 333], [126, 377, 162, 160, 89, 256], [127, 290, 302, 124, 90, 295], [128, 91, 252, 79, 180, 328], [129, 297, 85, 16, 22, 376], [130, 53, 24, 80, 72, 25], [131, 63, 125, 85, 44, 158], [188, 132, 282, 246, 8, 372], [133, 284, 155, 252, 374, 247], [134, 34, 54, 246, 48, 25], [135, 251, 307, 6, 297, 77], [136, 299, 8, 114, 79, 83], [137, 85, 371, 251, 297, 382], [138, 125, 22, 79, 382, 85], [139, 374, 231, 160, 79, 166], [140, 63, 377, 44, 276, 215], [141, 42, 368, 241, 43, 89], [142, 79, 85, 276, 125, 153], [143, 114, 160, 337, 299, 252], [144, 44, 354, 127, 310, 63], [145, 160, 180, 371, 79, 25], [146, 359, 114, 351, 344, 289], [147, 114, 85, 382, 160, 133], [148, 158, 77, 161, 295, 106], [149, 46, 89, 63, 195, 82], [150, 44, 63, 371, 85, 158], [151, 63, 276, 44, 211, 176], [152, 17, 160, 297, 28, 130], [153, 79, 125, 85, 180, 276], [154, 263, 45, 44, 173, 171], [155, 133, 252, 166, 160, 139], [156, 63, 61, 44, 151, 217], [157, 345, 313, 85, 297, 382], [158, 79, 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321], [192, 44, 288, 5, 90, 158], [193, 359, 114, 225, 345, 297], [194, 125, 258, 79, 85, 22], [195, 160, 256, 371, 328, 263], [196, 386, 378, 17, 6, 16], [197, 255, 125, 297, 226, 262], [198, 82, 79, 20, 114, 374], [199, 359, 336, 152, 146, 161], [200, 183, 125, 85, 44, 158], [201, 203, 295, 199, 297, 17], [202, 377, 224, 211, 114, 136], [203, 201, 17, 297, 175, 295], [204, 98, 42, 25, 371, 368], [205, 263, 297, 77, 158, 17], [206, 374, 20, 167, 389, 160], [207, 63, 377, 158, 371, 368], [208, 63, 44, 61, 156, 368], [209, 175, 17, 16, 22, 295], [210, 160, 168, 82, 76, 8], [211, 224, 359, 257, 285, 258], [212, 195, 199, 256, 328, 263], [213, 85, 347, 79, 125, 20], [214, 85, 79, 125, 276, 385], [215, 17, 85, 297, 77, 80], [216, 299, 63, 377, 136, 114], [217, 63, 371, 156, 38, 276], [218, 79, 8, 125, 35, 158], [219, 278, 221, 79, 284, 299], [220, 114, 299, 359, 211, 22], [221, 219, 114, 79, 284, 216], [222, 79, 276, 85, 125, 158], [223, 294, 368, 377, 114, 195], [224, 257, 211, 359, 377, 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[2.384185791015625e-07, 0.039878129959106445, 0.04100000858306885, 0.0510176420211792, 0.060056328773498535, 0.06205320358276367]], [[346, 387, 315, 297, 248, 264], [0.0, 0.0, 0.03713566064834595, 0.040827035903930664, 0.04180556535720825, 0.04437363147735596]], [[388, 248, 297, 215, 264, 349], [0.0, 0.03383636474609375, 0.03570961952209473, 0.03682076930999756, 0.03712153434753418, 0.045649588108062744]], [[389, 247, 164, 151, 46, 163], [5.960464477539063e-08, 0.04677700996398926, 0.05047893524169922, 0.05546367168426514, 0.057257115840911865, 0.05798715353012085]]] #1024 with more training # arr = [[[0, 242, 287, 162, 304, 239], [0.0, 0.02417755126953125, 0.027088820934295654, 0.02874159812927246, 0.0384824275970459, 0.04332250356674194]], [[1, 362, 88, 74, 50, 40], [5.960464477539063e-08, 0.33329272270202637, 0.34015023708343506, 0.34056055545806885, 0.34303873777389526, 0.36730706691741943]], [[2, 46, 51, 79, 30, 39], [5.960464477539063e-08, 0.017279505729675293, 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0.06650638580322266, 0.08381253480911255, 0.09024930000305176, 0.09478932619094849, 0.09635621309280396]], [[381, 127, 118, 167, 177, 266], [1.1920928955078125e-07, 0.10467958450317383, 0.11471152305603027, 0.12158674001693726, 0.1332908272743225, 0.13792860507965088]], [[382, 208, 332, 24, 22, 41], [0.0, 0.09446132183074951, 0.1030498743057251, 0.10537409782409668, 0.10602927207946777, 0.10604262351989746]], [[383, 18, 49, 53, 143, 353], [0.0, 0.07739043235778809, 0.08003437519073486, 0.08219456672668457, 0.08422672748565674, 0.08482646942138672]], [[384, 386, 292, 16, 171, 305], [5.960464477539063e-08, 0.04579782485961914, 0.05793106555938721, 0.06560969352722168, 0.06700634956359863, 0.06717205047607422]], [[385, 85, 124, 150, 371, 250], [1.7881393432617188e-07, 0.060361623764038086, 0.07818859815597534, 0.07880616188049316, 0.08771222829818726, 0.0902637243270874]], [[386, 292, 384, 305, 99, 232], [0.0, 0.042023658752441406, 0.04579782485961914, 0.04854476451873779, 0.05754208564758301, 0.06365704536437988]], [[387, 346, 297, 315, 264, 248], [2.980232238769531e-07, 2.980232238769531e-07, 0.04432255029678345, 0.04545408487319946, 0.04711806774139404, 0.047833144664764404]], [[388, 248, 264, 215, 297, 341], [0.0, 0.037600159645080566, 0.03965330123901367, 0.04084932804107666, 0.04194521903991699, 0.047194480895996094]], [[389, 164, 247, 151, 46, 163], [1.7881393432617188e-07, 0.042870163917541504, 0.04697549343109131, 0.05527430772781372, 0.057344913482666016, 0.05813324451446533]]] pred = [2,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 ,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 ,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,1,2,2,2,1,1,1,1,1,1,1,2,1 ,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 ,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 ,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 ,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 ,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 ,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 ,2,2,2,2,2,2,2,2,3,0,0,3,0,3,3,3,3,3,3,3,3,3,0,3,3,3,3,3,3,3,3,3,3,3,3,3,3 ,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3] title = "Nearest neighbors on Model 3 : 3D CNN 2048" print("<h3>"+title+"</h3>"+"<br/><br/>") print("<table style=\"width:100%\">") print("<td>") print("<b>Original</b>") print("</td>") print("<td>") print("<b>Nearest neighbors</b>") print("</td>") for i in range(0, 390): print("</tr>") typ = [] print("<tr id=\"a"+str(i)+"\">") for j in range(0, 5): print("<td>") print("<figure>") print("<a href=\"#a"+str(arr[i][0][j])+"\">") print("<img src=\"./"+ str(arr[i][0][j]+1)+".png\" alt='missing' >") print("</a>") print("<figcaption>") if arr[i][0][j] < 97 : print("Ancient, ") elif arr[i][0][j] < 131: print("Asian,") elif arr[i][0][j] < 341: print("Medieval, ") else: print("Modern,") if pred[arr[i][0][j]] == 0: print("Ancient") if pred[arr[i][0][j]] == 1: print("Asian") if pred[arr[i][0][j]] == 2: print("Medieval") if pred[arr[i][0][j]] == 3: print("Modern") # if pred[i] == 0 : # print("Ancient, Ancient") # elif pred[i] == 1: # print("Asian, Asian") # elif pred[i] == 2: # print("Medieval, Medieval") # else: # print("Modern, Modern") if j!=0: print(", Distance: "+str(arr[i][1][j])) print("</figcaption>") print("</figure>") print("</td>") print("</tr>") print("</table>") print("</body></html>")	5,227.72043	61,586	0.741782	print("<!DOCTYPE html><html><body>") # arr =[[0, 152, 17, 252, 146, 88], [1, 260, 335, 63, 44, 17], [2, 53, 72, 130, 24, 80], [3, 352, 178, 32, 30, 287], [4, 80, 24, 17, 77, 28], [5, 85, 79, 276, 158, 63], [6, 376, 85, 16, 251, 382], [7, 17, 378, 16, 376, 384], [8, 79, 180, 183, 362, 85], [9, 80, 28, 17, 11, 36], [10, 33, 3, 25, 53, 152], [11, 28, 77, 80, 25, 85], [12, 6, 17, 378, 376, 16], [13, 210, 160, 356, 168, 63], [14, 362, 85, 125, 97, 118], [15, 25, 78, 353, 53, 43], [16, 251, 376, 382, 85, 6], [17, 80, 297, 152, 373, 75], [18, 360, 246, 377, 20, 347], [19, 104, 85, 362, 116, 125], [20, 347, 28, 374, 160, 53], [21, 14, 160, 35, 80, 28], [22, 85, 382, 258, 251, 79], [23, 24, 53, 78, 80, 28], [24, 80, 53, 130, 64, 72], [25, 160, 53, 74, 28, 130], [26, 371, 63, 88, 279, 145], [27, 30, 325, 37, 25, 210], [28, 25, 160, 14, 356, 8], [29, 371, 362, 118, 104, 125], [30, 61, 3, 32, 51, 76], [31, 181, 21, 294, 241, 43], [32, 76, 52, 3, 61, 30], [33, 53, 68, 130, 25, 24], [34, 89, 29, 246, 54, 48], [35, 371, 362, 125, 85, 14], [36, 28, 297, 14, 80, 16], [37, 90, 25, 368, 42, 48], [38, 63, 217, 44, 211, 39], [39, 45, 63, 61, 44, 46], [40, 17, 80, 25, 260, 152], [41, 63, 44, 276, 208, 61], [42, 368, 104, 22, 362, 48], [43, 25, 42, 54, 48, 89], [44, 63, 61, 276, 173, 335], [45, 39, 63, 44, 6, 386], [46, 63, 39, 61, 176, 276], [47, 347, 87, 95, 342, 80], [48, 54, 354, 368, 355, 34], [49, 80, 24, 75, 130, 53], [50, 63, 386, 83, 171, 192], [51, 30, 25, 352, 325, 160], [52, 32, 76, 337, 61, 63], [53, 130, 24, 25, 72, 80], [54, 48, 34, 89, 362, 368], [55, 178, 348, 3, 287, 352], [56, 80, 17, 75, 258, 8], [57, 42, 368, 158, 371, 116], [58, 118, 16, 22, 251, 297], [59, 80, 53, 130, 24, 363], [60, 67, 348, 287, 242, 55], [61, 63, 30, 335, 32, 52], [62, 297, 364, 6, 16, 251], [63, 44, 61, 39, 276, 371], [64, 24, 80, 53, 130, 78], [65, 382, 79, 258, 85, 22], [66, 71, 61, 260, 17, 81], [67, 60, 348, 242, 287, 178], [68, 53, 24, 130, 78, 80], [69, 85, 14, 77, 362, 97], [70, 80, 17, 49, 56, 130], [71, 343, 6, 45, 386, 376], [72, 53, 130, 2, 24, 80], [73, 6, 92, 343, 365, 105], [74, 25, 160, 28, 53, 80], [75, 258, 362, 80, 359, 17], [76, 32, 52, 61, 30, 63], [77, 80, 345, 85, 342, 22], [78, 80, 53, 24, 130, 68], [79, 85, 276, 125, 180, 153], [80, 24, 53, 130, 17, 78], [81, 28, 25, 160, 15, 11], [82, 168, 8, 210, 152, 160], [83, 79, 8, 276, 90, 356], [84, 25, 160, 28, 362, 61], [85, 79, 125, 382, 22, 276], [86, 80, 28, 347, 85, 297], [87, 80, 77, 342, 25, 47], [88, 17, 160, 350, 152, 278], [89, 256, 34, 189, 25, 368], [90, 25, 37, 53, 83, 28], [91, 22, 114, 128, 79, 258], [92, 376, 6, 73, 292, 229], [93, 80, 24, 53, 130, 78], [94, 364, 44, 17, 215, 297], [95, 80, 347, 20, 47, 28], [96, 25, 89, 42, 116, 368], [97, 362, 14, 371, 85, 104], [98, 25, 368, 104, 362, 116], [99, 107, 85, 341, 6, 297], [100, 16, 297, 17, 264, 315], [101, 20, 160, 25, 3, 34], [102, 145, 17, 88, 279, 371], [103, 25, 134, 43, 85, 320], [104, 118, 79, 116, 362, 180], [105, 112, 376, 16, 79, 251], [106, 241, 34, 22, 42, 294], [107, 123, 99, 386, 376, 85], [108, 195, 160, 328, 249, 123], [109, 364, 125, 294, 355, 241], [110, 28, 85, 160, 297, 11], [111, 29, 371, 104, 362, 355], [105, 112, 376, 16, 79, 251], [113, 158, 77, 83, 85, 256], [114, 79, 85, 125, 252, 8], [115, 34, 368, 246, 54, 161], [116, 118, 104, 362, 371, 180], [117, 211, 351, 22, 285, 336], [118, 125, 180, 116, 79, 104], [119, 85, 79, 125, 382, 22], [120, 17, 58, 376, 16, 384], [121, 160, 158, 362, 63, 347], [122, 153, 191, 79, 272, 125], [123, 107, 167, 160, 124, 290], [124, 63, 44, 123, 158, 276], [125, 79, 85, 276, 118, 333], [126, 377, 162, 160, 89, 256], [127, 290, 302, 124, 90, 295], [128, 91, 252, 79, 180, 328], [129, 297, 85, 16, 22, 376], [130, 53, 24, 80, 72, 25], [131, 63, 125, 85, 44, 158], [188, 132, 282, 246, 8, 372], [133, 284, 155, 252, 374, 247], [134, 34, 54, 246, 48, 25], [135, 251, 307, 6, 297, 77], [136, 299, 8, 114, 79, 83], [137, 85, 371, 251, 297, 382], [138, 125, 22, 79, 382, 85], [139, 374, 231, 160, 79, 166], [140, 63, 377, 44, 276, 215], [141, 42, 368, 241, 43, 89], [142, 79, 85, 276, 125, 153], [143, 114, 160, 337, 299, 252], [144, 44, 354, 127, 310, 63], [145, 160, 180, 371, 79, 25], [146, 359, 114, 351, 344, 289], [147, 114, 85, 382, 160, 133], [148, 158, 77, 161, 295, 106], [149, 46, 89, 63, 195, 82], [150, 44, 63, 371, 85, 158], [151, 63, 276, 44, 211, 176], [152, 17, 160, 297, 28, 130], [153, 79, 125, 85, 180, 276], [154, 263, 45, 44, 173, 171], [155, 133, 252, 166, 160, 139], [156, 63, 61, 44, 151, 217], [157, 345, 313, 85, 297, 382], [158, 79, 125, 85, 276, 371], [159, 367, 125, 8, 369, 353], [160, 25, 53, 28, 356, 8], [161, 104, 158, 362, 116, 8], [162, 195, 368, 115, 263, 54], [163, 377, 77, 20, 80, 342], [164, 85, 79, 382, 251, 22], [165, 79, 22, 114, 85, 180], [166, 160, 139, 252, 168, 374], [167, 206, 160, 20, 123, 270], [168, 82, 160, 210, 374, 8], [169, 51, 30, 43, 61, 25], [170, 297, 264, 80, 351, 363], [171, 44, 63, 158, 386, 240], [172, 190, 114, 63, 39, 163], [173, 44, 17, 63, 297, 215], [174, 290, 153, 85, 158, 256], [175, 290, 363, 17, 247, 211], [176, 63, 8, 350, 151, 85], [177, 251, 16, 376, 297, 308], [178, 3, 287, 352, 55, 348], [179, 160, 25, 8, 80, 362], [180, 79, 8, 85, 118, 125], [181, 44, 31, 63, 158, 276], [182, 166, 152, 160, 82, 168], [183, 79, 8, 125, 85, 180], [184, 25, 368, 256, 187, 153], [185, 303, 85, 238, 297, 382], [186, 79, 160, 180, 8, 374], [187, 160, 371, 25, 368, 256], [188, 132, 282, 246, 8, 372], [189, 89, 48, 104, 42, 118], [190, 172, 85, 297, 238, 215], [191, 367, 125, 114, 136, 321], [192, 44, 288, 5, 90, 158], [193, 359, 114, 225, 345, 297], [194, 125, 258, 79, 85, 22], [195, 160, 256, 371, 328, 263], [196, 386, 378, 17, 6, 16], [197, 255, 125, 297, 226, 262], [198, 82, 79, 20, 114, 374], [199, 359, 336, 152, 146, 161], [200, 183, 125, 85, 44, 158], [201, 203, 295, 199, 297, 17], [202, 377, 224, 211, 114, 136], [203, 201, 17, 297, 175, 295], [204, 98, 42, 25, 371, 368], [205, 263, 297, 77, 158, 17], [206, 374, 20, 167, 389, 160], [207, 63, 377, 158, 371, 368], [208, 63, 44, 61, 156, 368], [209, 175, 17, 16, 22, 295], [210, 160, 168, 82, 76, 8], [211, 224, 359, 257, 285, 258], [212, 195, 199, 256, 328, 263], [213, 85, 347, 79, 125, 20], [214, 85, 79, 125, 276, 385], [215, 17, 85, 297, 77, 80], [216, 299, 63, 377, 136, 114], [217, 63, 371, 156, 38, 276], [218, 79, 8, 125, 35, 158], [219, 278, 221, 79, 284, 299], [220, 114, 299, 359, 211, 22], [221, 219, 114, 79, 284, 216], [222, 79, 276, 85, 125, 158], [223, 294, 368, 377, 114, 195], [224, 257, 211, 359, 377, 136], [225, 211, 114, 285, 22, 193], [226, 44, 35, 187, 63, 48], [227, 42, 85, 48, 22, 125], [228, 114, 356, 362, 79, 180], [229, 376, 6, 16, 378, 386], [230, 85, 215, 297, 63, 17], [231, 79, 139, 180, 8, 276], [232, 257, 297, 85, 22, 386], [233, 63, 44, 83, 61, 39], [234, 79, 153, 125, 85, 118], [235, 22, 85, 160, 258, 79], [236, 63, 377, 151, 85, 276], [237, 344, 211, 299, 22, 253], [238, 185, 77, 345, 347, 297], [239, 134, 83, 34, 25, 104], [240, 371, 29, 158, 362, 118], [241, 294, 42, 43, 54, 368], [242, 67, 32, 60, 210, 311], [243, 63, 44, 300, 263, 361], [244, 79, 125, 180, 85, 158], [245, 85, 125, 118, 29, 14], [246, 104, 371, 362, 29, 125], [247, 382, 79, 85, 211, 22], [248, 297, 85, 251, 382, 351], [249, 328, 195, 79, 114, 272], [250, 297, 85, 263, 17, 158], [251, 382, 16, 22, 85, 258], [252, 79, 114, 180, 8, 374], [253, 359, 114, 344, 85, 79], [254, 44, 63, 216, 181, 211], [255, 125, 22, 226, 336, 197], [256, 89, 160, 368, 25, 54], [257, 224, 211, 85, 377, 125], [258, 382, 85, 22, 79, 65], [259, 34, 48, 54, 368, 89], [260, 80, 17, 69, 77, 297], [261, 17, 80, 78, 53, 386], [262, 85, 79, 125, 276, 258], [263, 14, 362, 77, 389, 85], [264, 297, 170, 351, 80, 363], [265, 195, 114, 162, 160, 256], [266, 58, 251, 16, 297, 119], [267, 85, 297, 386, 158, 28], [268, 85, 153, 389, 125, 276], [269, 114, 44, 377, 160, 328], [270, 180, 8, 252, 20, 389], [271, 383, 353, 98, 79, 125], [272, 114, 377, 125, 85, 136], [273, 125, 116, 35, 118, 104], [274, 114, 246, 252, 83, 146], [275, 63, 61, 52, 76, 337], [276, 79, 85, 125, 153, 183], [277, 286, 115, 42, 195, 54], [278, 219, 284, 323, 114, 285], [279, 80, 49, 17, 53, 24], [280, 85, 125, 377, 276, 63], [281, 63, 114, 39, 136, 61], [282, 132, 188, 85, 246, 362], [283, 80, 24, 130, 53, 342], [284, 133, 278, 252, 221, 219], [285, 211, 22, 382, 114, 251], [286, 195, 277, 189, 256, 263], [287, 178, 352, 3, 34, 348], [288, 215, 297, 85, 377, 63], [289, 146, 359, 114, 211, 79], [290, 175, 123, 124, 127, 199], [291, 63, 61, 275, 52, 76], [292, 16, 376, 386, 17, 6], [293, 329, 255, 137, 312, 91], [294, 241, 42, 43, 48, 368], [295, 161, 22, 77, 85, 42], [296, 328, 263, 149, 46, 195], [297, 351, 264, 17, 170, 28], [298, 42, 371, 160, 43, 104], [299, 79, 85, 136, 125, 160], [300, 77, 356, 83, 160, 263], [301, 374, 79, 20, 146, 114], [302, 295, 42, 127, 54, 48], [303, 85, 251, 382, 22, 297], [304, 114, 337, 160, 210, 374], [305, 17, 297, 386, 16, 388], [306, 63, 44, 61, 5, 39], [307, 91, 351, 77, 152, 22], [308, 382, 251, 258, 22, 85], [309, 89, 287, 51, 34, 61], [310, 187, 226, 184, 144, 44], [311, 32, 160, 3, 210, 82], [312, 22, 251, 297, 295, 382], [313, 345, 85, 157, 382, 377], [314, 89, 34, 42, 29, 116], [315, 17, 297, 16, 251, 215], [316, 187, 159, 153, 389, 353], [317, 337, 160, 52, 377, 74], [318, 44, 335, 63, 111, 371], [319, 34, 362, 19, 85, 125], [320, 22, 44, 272, 85, 125], [321, 276, 79, 8, 85, 153], [322, 44, 63, 215, 263, 192], [323, 278, 114, 347, 252, 379], [324, 85, 63, 377, 276, 44], [325, 25, 160, 53, 98, 30], [326, 16, 6, 251, 297, 152], [327, 378, 376, 112, 105, 386], [328, 195, 114, 263, 356, 136], [329, 116, 246, 297, 118, 371], [330, 367, 336, 153, 58, 187], [331, 373, 17, 215, 152, 292], [332, 80, 24, 54, 42, 28], [333, 79, 125, 85, 180, 118], [334, 48, 25, 325, 353, 160], [335, 61, 44, 30, 63, 90], [336, 251, 22, 350, 152, 17], [337, 52, 160, 210, 317, 89], [338, 104, 371, 158, 362, 79], [339, 247, 63, 85, 215, 80], [340, 25, 368, 362, 371, 97], [341, 28, 25, 160, 85, 8], [342, 374, 77, 28, 80, 87], [343, 71, 6, 378, 16, 365], [344, 359, 258, 85, 297, 377], [345, 77, 351, 297, 342, 80], [346, 387, 28, 85, 297, 17], [347, 360, 20, 28, 374, 79], [348, 67, 60, 287, 178, 55], [349, 16, 297, 17, 6, 376], [350, 336, 114, 372, 176, 359], [351, 297, 363, 345, 359, 264], [352, 3, 178, 287, 32, 61], [353, 87, 75, 25, 367, 74], [354, 48, 25, 246, 368, 362], [355, 362, 14, 118, 29, 371], [356, 160, 28, 362, 8, 374], [357, 79, 85, 382, 276, 258], [358, 35, 85, 226, 22, 362], [359, 344, 75, 351, 146, 211], [360, 347, 20, 377, 77, 47], [361, 63, 61, 136, 44, 368], [362, 14, 8, 125, 371, 118], [363, 297, 351, 264, 17, 77], [364, 109, 77, 345, 262, 297], [365, 28, 258, 6, 85, 297], [366, 160, 377, 211, 8, 75], [367, 114, 8, 252, 258, 136], [368, 42, 29, 48, 104, 362], [369, 362, 367, 48, 8, 42], [370, 160, 114, 25, 374, 28], [371, 362, 180, 85, 158, 118], [372, 350, 132, 188, 344, 146], [373, 17, 331, 152, 297, 215], [374, 28, 342, 20, 160, 347], [375, 160, 25, 210, 168, 114], [376, 6, 16, 251, 382, 85], [377, 85, 362, 97, 79, 371], [378, 376, 297, 16, 6, 17], [379, 79, 347, 114, 359, 85], [380, 17, 85, 262, 80, 297], [381, 28, 85, 14, 25, 48], [382, 85, 22, 251, 258, 79], [383, 8, 79, 270, 180, 389], [384, 376, 6, 16, 297, 386], [385, 79, 85, 276, 125, 153], [386, 28, 6, 16, 376, 297], [346, 387, 28, 85, 297, 17], [388, 297, 17, 215, 28, 85], [389, 79, 8, 362, 180, 85]] # arr = [[0, 239, 10, 67, 60, 33], [1, 0, 239, 10, 67, 60], [2, 0, 239, 10, 33, 67], [3, 352, 0, 67, 239, 60], [4, 0, 239, 10, 67, 60], [5, 239, 0, 67, 348, 60], [6, 85, 79, 125, 382, 251], [7, 0, 239, 10, 67, 60], [8, 239, 0, 42, 79, 348], [9, 0, 239, 10, 67, 60], [10, 0, 239, 60, 67, 33], [11, 239, 42, 43, 0, 33], [12, 0, 239, 10, 67, 60], [13, 0, 239, 10, 67, 60], [14, 34, 42, 48, 239, 89], [15, 0, 239, 10, 33, 60], [16, 251, 79, 382, 42, 239], [17, 75, 49, 0, 373, 10], [18, 0, 239, 10, 67, 60], [19, 239, 0, 67, 348, 42], [20, 33, 0, 239, 10, 60], [21, 0, 239, 67, 10, 60], [22, 42, 79, 239, 382, 0], [23, 0, 239, 10, 67, 60], [24, 53, 68, 33, 239, 0], [25, 53, 43, 89, 33, 239], [26, 0, 239, 10, 67, 60], [27, 0, 239, 10, 67, 60], [28, 53, 356, 25, 374, 79], [29, 34, 239, 42, 0, 89], [30, 0, 239, 67, 10, 60], [31, 0, 239, 67, 10, 60], [32, 0, 239, 67, 60, 10], [33, 0, 239, 10, 60, 67], [34, 239, 0, 67, 60, 10], [35, 239, 0, 42, 67, 60], [36, 0, 239, 10, 60, 67], [37, 239, 0, 10, 60, 67], [38, 0, 239, 10, 67, 60], [39, 0, 239, 67, 60, 10], [40, 0, 239, 10, 60, 33], [41, 0, 239, 10, 67, 60], [42, 239, 0, 67, 60, 10], [43, 0, 239, 10, 60, 67], [44, 352, 0, 52, 3, 239], [45, 39, 0, 239, 67, 60], [46, 0, 239, 10, 67, 60], [47, 239, 0, 10, 33, 60], [48, 239, 0, 67, 60, 10], [49, 0, 239, 10, 33, 67], [50, 0, 239, 60, 67, 10], [51, 0, 239, 10, 67, 60], [52, 0, 239, 67, 10, 60], [53, 33, 68, 239, 2, 0], [54, 239, 0, 67, 60, 10], [55, 0, 239, 60, 67, 10], [56, 0, 239, 10, 67, 60], [57, 0, 239, 67, 60, 10], [58, 0, 239, 67, 60, 10], [59, 0, 239, 10, 67, 60], [60, 67, 0, 239, 10, 348], [61, 352, 0, 3, 239, 67], [62, 0, 239, 10, 67, 60], [63, 52, 76, 352, 32, 34], [64, 0, 239, 10, 67, 60], [65, 79, 239, 0, 42, 180], [66, 0, 239, 60, 10, 67], [67, 60, 0, 239, 348, 10], [68, 0, 239, 33, 10, 60], [69, 239, 34, 0, 67, 42], [70, 0, 239, 10, 67, 60], [71, 0, 239, 10, 67, 60], [72, 0, 239, 10, 60, 33], [73, 0, 239, 10, 67, 60], [74, 239, 0, 33, 10, 60], [75, 239, 0, 348, 67, 60], [76, 0, 239, 67, 10, 60], [77, 239, 0, 67, 60, 10], [78, 0, 239, 68, 33, 60], [79, 180, 239, 0, 348, 42], [80, 24, 53, 78, 49, 64], [81, 239, 0, 60, 10, 67], [82, 239, 0, 67, 60, 10], [83, 239, 0, 348, 60, 67], [84, 0, 239, 10, 60, 67], [85, 79, 125, 382, 180, 276], [86, 0, 239, 10, 60, 67], [87, 239, 0, 33, 68, 10], [88, 0, 239, 67, 10, 60], [89, 239, 0, 67, 60, 10], [90, 239, 0, 60, 10, 33], [91, 0, 239, 67, 10, 60], [92, 0, 239, 10, 67, 60], [93, 0, 239, 33, 60, 10], [94, 0, 239, 10, 67, 60], [95, 239, 0, 33, 10, 67], [96, 239, 0, 42, 67, 89], [97, 42, 34, 104, 239, 89], [98, 239, 0, 60, 67, 10], [99, 0, 239, 10, 67, 60], [100, 0, 239, 10, 67, 60], [101, 0, 239, 10, 67, 348], [102, 0, 239, 67, 10, 60], [103, 0, 239, 67, 10, 60], [104, 239, 0, 42, 348, 67], [112, 105, 239, 0, 67, 60], [106, 0, 239, 10, 67, 60], [107, 0, 239, 67, 10, 60], [108, 0, 239, 10, 67, 60], [109, 0, 239, 67, 10, 60], [110, 0, 239, 67, 10, 60], [111, 239, 42, 34, 89, 0], [112, 105, 239, 0, 67, 60], [113, 0, 239, 10, 67, 60], [114, 0, 239, 10, 67, 60], [115, 239, 0, 67, 60, 10], [116, 42, 104, 239, 89, 34], [117, 0, 239, 10, 67, 60], [118, 239, 104, 0, 42, 180], [119, 79, 239, 0, 42, 348], [120, 0, 239, 67, 10, 60], [121, 0, 239, 10, 67, 60], [122, 0, 239, 10, 67, 60], [123, 0, 239, 67, 60, 10], [124, 0, 239, 67, 10, 60], [125, 79, 42, 239, 0, 48], [126, 0, 239, 10, 67, 60], [127, 239, 0, 60, 10, 67], [128, 0, 239, 67, 10, 60], [129, 239, 0, 67, 60, 10], [130, 53, 2, 68, 72, 33], [131, 0, 239, 67, 60, 10], [188, 132, 239, 0, 67, 60], [133, 0, 239, 67, 10, 60], [134, 239, 0, 67, 348, 60], [135, 0, 239, 10, 67, 60], [136, 239, 0, 67, 60, 55], [137, 0, 239, 67, 10, 60], [138, 0, 239, 10, 67, 60], [139, 0, 239, 10, 67, 60], [140, 0, 239, 10, 67, 60], [141, 0, 239, 67, 10, 60], [142, 239, 0, 67, 60, 10], [143, 0, 239, 10, 67, 60], [144, 0, 239, 67, 10, 60], [145, 0, 239, 67, 10, 60], [146, 0, 239, 10, 67, 60], [147, 0, 239, 67, 10, 60], [148, 0, 239, 10, 67, 60], [149, 0, 239, 10, 67, 60], [150, 239, 0, 67, 60, 10], [151, 0, 239, 10, 67, 60], [152, 10, 0, 33, 60, 67], [153, 79, 239, 0, 180, 42], [154, 0, 239, 67, 10, 60], [155, 0, 239, 10, 67, 60], [156, 0, 239, 67, 60, 10], [157, 0, 239, 67, 10, 60], [158, 79, 104, 180, 42, 239], [159, 0, 239, 10, 67, 60], [160, 53, 89, 294, 25, 43], [161, 239, 0, 34, 42, 67], [162, 0, 239, 10, 67, 60], [163, 0, 239, 10, 33, 60], [164, 239, 0, 67, 10, 60], [165, 0, 239, 67, 10, 60], [166, 239, 0, 67, 60, 10], [167, 0, 239, 10, 60, 33], [168, 0, 239, 67, 10, 60], [169, 0, 239, 10, 67, 60], [170, 239, 0, 67, 60, 10], [171, 0, 239, 67, 10, 60], [172, 0, 239, 10, 67, 60], [173, 0, 239, 67, 60, 10], [174, 0, 239, 67, 60, 10], [175, 0, 239, 10, 67, 60], [176, 0, 239, 67, 10, 60], [177, 0, 239, 10, 67, 60], [178, 239, 0, 67, 60, 348], [179, 239, 0, 67, 60, 10], [180, 239, 0, 348, 79, 67], [181, 0, 239, 67, 10, 60], [182, 0, 239, 10, 67, 60], [183, 79, 180, 239, 42, 0], [184, 239, 0, 67, 60, 10], [185, 0, 239, 10, 60, 67], [186, 0, 239, 67, 60, 10], [187, 0, 239, 67, 60, 10], [188, 132, 239, 0, 67, 60], [189, 239, 0, 67, 60, 348], [190, 0, 239, 10, 67, 60], [191, 0, 239, 67, 10, 60], [192, 0, 239, 67, 10, 60], [193, 0, 239, 10, 67, 60], [194, 0, 239, 67, 10, 60], [195, 0, 239, 67, 60, 10], [196, 0, 239, 10, 67, 60], [197, 0, 239, 10, 67, 60], [198, 0, 239, 10, 67, 60], [199, 0, 239, 10, 67, 60], [200, 0, 239, 67, 10, 60], [201, 203, 0, 239, 10, 67], [202, 0, 239, 10, 67, 60], [203, 201, 0, 239, 10, 67], [204, 0, 239, 67, 10, 60], [205, 0, 239, 10, 67, 60], [206, 0, 239, 10, 33, 67], [207, 0, 239, 67, 10, 60], [208, 0, 239, 67, 10, 60], [209, 0, 239, 67, 10, 60], [210, 0, 239, 67, 60, 10], [211, 0, 239, 67, 60, 10], [212, 0, 239, 10, 67, 60], [213, 0, 239, 10, 67, 60], [214, 0, 239, 10, 67, 60], [215, 239, 0, 10, 67, 60], [216, 0, 239, 67, 60, 10], [217, 0, 239, 67, 10, 60], [218, 0, 239, 10, 67, 60], [219, 0, 239, 67, 10, 60], [220, 0, 239, 67, 10, 60], [221, 0, 239, 67, 10, 60], [222, 79, 239, 0, 348, 67], [223, 0, 239, 67, 10, 60], [224, 239, 0, 67, 10, 60], [225, 0, 239, 10, 67, 60], [226, 0, 239, 67, 60, 294], [227, 0, 239, 67, 60, 10], [228, 0, 239, 10, 67, 60], [229, 239, 0, 67, 60, 10], [230, 0, 239, 67, 10, 60], [231, 0, 239, 67, 60, 10], [232, 239, 0, 67, 10, 60], [233, 0, 239, 60, 10, 67], [234, 239, 0, 60, 67, 348], [235, 0, 239, 67, 60, 10], [236, 0, 239, 348, 10, 67], [237, 0, 239, 67, 10, 60], [238, 0, 239, 67, 60, 10], [239, 0, 10, 67, 60, 33], [240, 239, 34, 0, 89, 67], [241, 0, 239, 67, 10, 60], [242, 0, 67, 60, 239, 10], [243, 0, 239, 10, 67, 60], [244, 239, 0, 67, 348, 60], [245, 239, 0, 42, 67, 60], [246, 239, 0, 34, 67, 348], [247, 0, 239, 67, 60, 10], [248, 0, 239, 67, 60, 10], [249, 0, 239, 67, 10, 60], [250, 0, 239, 67, 10, 60], [251, 79, 42, 382, 239, 0], [252, 0, 239, 348, 67, 10], [253, 0, 239, 67, 60, 10], [254, 0, 239, 10, 67, 60], [255, 0, 239, 67, 10, 60], [256, 239, 0, 89, 67, 60], [257, 239, 0, 67, 60, 10], [258, 79, 42, 239, 0, 180], [259, 0, 239, 67, 10, 60], [260, 0, 239, 67, 10, 60], [261, 0, 239, 60, 33, 10], [262, 79, 239, 0, 348, 67], [263, 0, 239, 296, 67, 10], [264, 239, 0, 67, 60, 10], [265, 0, 239, 67, 10, 60], [266, 0, 239, 10, 67, 60], [267, 239, 0, 60, 10, 67], [268, 239, 0, 67, 60, 10], [269, 0, 239, 67, 10, 60], [270, 239, 0, 348, 67, 10], [271, 239, 0, 10, 60, 67], [272, 0, 239, 67, 10, 60], [273, 0, 239, 67, 60, 10], [274, 0, 239, 10, 67, 60], [275, 0, 239, 67, 60, 10], [276, 79, 239, 0, 180, 67], [277, 0, 239, 10, 67, 60], [278, 0, 239, 10, 67, 60], [279, 0, 239, 10, 67, 60], [280, 0, 239, 67, 60, 10], [281, 0, 239, 10, 67, 60], [282, 239, 0, 67, 10, 60], [283, 0, 239, 10, 33, 60], [284, 0, 239, 67, 10, 60], [285, 0, 239, 10, 67, 60], [286, 0, 239, 67, 10, 60], [287, 239, 0, 60, 67, 348], [288, 0, 239, 67, 60, 10], [289, 0, 239, 10, 67, 60], [290, 0, 239, 10, 67, 60], [291, 0, 239, 67, 60, 10], [292, 0, 239, 10, 33, 67], [293, 0, 239, 10, 67, 60], [294, 0, 239, 67, 60, 10], [295, 239, 0, 67, 60, 10], [296, 0, 239, 10, 67, 60], [297, 351, 239, 0, 348, 67], [298, 0, 239, 67, 10, 60], [299, 239, 0, 67, 348, 60], [300, 0, 239, 67, 60, 10], [301, 0, 239, 10, 67, 60], [302, 0, 239, 67, 10, 60], [303, 0, 239, 67, 10, 60], [304, 0, 239, 10, 67, 60], [305, 0, 239, 10, 67, 60], [306, 0, 352, 239, 67, 60], [307, 0, 239, 10, 67, 60], [308, 239, 0, 42, 79, 348], [309, 0, 239, 10, 67, 60], [310, 0, 239, 67, 60, 10], [311, 239, 0, 67, 60, 348], [312, 0, 239, 67, 10, 60], [313, 0, 239, 10, 67, 60], [314, 239, 0, 67, 60, 10], [315, 0, 239, 10, 67, 60], [316, 0, 239, 10, 67, 60], [317, 0, 239, 10, 67, 60], [318, 0, 239, 67, 60, 10], [319, 239, 0, 67, 60, 10], [320, 0, 239, 67, 10, 60], [321, 0, 239, 67, 60, 10], [322, 0, 239, 10, 67, 60], [323, 0, 239, 67, 60, 10], [324, 0, 239, 10, 67, 60], [325, 239, 0, 33, 10, 60], [326, 0, 239, 10, 67, 60], [327, 0, 239, 67, 60, 10], [328, 0, 239, 10, 67, 60], [329, 239, 0, 67, 60, 10], [330, 0, 239, 10, 67, 60], [331, 0, 239, 10, 67, 60], [332, 0, 239, 67, 10, 60], [333, 239, 0, 79, 42, 348], [334, 0, 239, 60, 67, 10], [335, 0, 239, 67, 60, 352], [336, 0, 239, 10, 67, 60], [337, 0, 239, 67, 60, 10], [338, 239, 0, 67, 60, 348], [339, 0, 239, 67, 60, 10], [340, 0, 239, 67, 60, 10], [341, 239, 348, 0, 33, 67], [342, 239, 33, 0, 60, 10], [343, 0, 239, 10, 67, 60], [344, 0, 239, 10, 67, 60], [345, 0, 239, 10, 60, 67], [346, 387, 0, 239, 67, 10], [347, 0, 239, 60, 67, 10], [348, 0, 67, 60, 239, 10], [349, 0, 239, 10, 67, 60], [350, 0, 239, 10, 67, 60], [351, 0, 239, 67, 348, 60], [352, 0, 239, 67, 60, 10], [353, 239, 0, 10, 33, 60], [354, 239, 0, 67, 60, 48], [355, 239, 42, 34, 0, 89], [356, 239, 0, 67, 10, 60], [357, 0, 239, 10, 67, 60], [358, 0, 239, 67, 60, 10], [359, 0, 239, 10, 67, 60], [360, 0, 239, 10, 67, 60], [361, 0, 239, 67, 60, 10], [362, 42, 34, 239, 54, 89], [363, 0, 239, 67, 10, 60], [364, 0, 239, 10, 67, 60], [365, 0, 239, 67, 10, 60], [366, 0, 239, 67, 60, 10], [367, 0, 239, 10, 67, 60], [368, 239, 42, 0, 67, 294], [369, 0, 239, 67, 60, 10], [370, 0, 239, 10, 67, 60], [371, 42, 89, 34, 104, 180], [372, 0, 239, 10, 67, 60], [373, 0, 239, 10, 67, 60], [374, 0, 239, 67, 10, 60], [375, 0, 239, 10, 67, 60], [376, 251, 42, 79, 239, 382], [377, 34, 239, 0, 42, 348], [378, 0, 239, 10, 67, 60], [379, 0, 239, 67, 10, 60], [380, 0, 239, 10, 67, 60], [381, 0, 239, 10, 67, 60], [382, 79, 239, 42, 0, 180], [383, 239, 0, 60, 10, 67], [384, 0, 239, 10, 60, 67], [385, 79, 0, 239, 67, 60], [386, 42, 239, 0, 348, 67], [346, 387, 0, 239, 67, 10], [388, 0, 239, 67, 60, 10], [389, 79, 239, 0, 42, 180]] # arr = [[[0, 239, 10, 67, 60, 33], [0.0, 52.86775955154521, 66.90291473471092, 68.49087530467106, 69.39020103732227, 79.13279977354523]], [[1, 0, 239, 10, 67, 60], [0.0, 238.15961034566715, 239.79783151646723, 242.1321952983535, 242.66643772882975, 243.15632831575658]], [[2, 0, 239, 10, 33, 67], [0.0, 135.01111065390137, 136.59795020423988, 141.47791347061914, 142.35167719419397, 142.87407042567241]], [[3, 352, 0, 67, 239, 60], [0.0, 127.34991166074674, 131.33544837552427, 133.65627557282897, 133.9552163971228, 134.0447686409283]], [[4, 0, 239, 10, 67, 60], [0.0, 214.54836284623568, 215.64786110694445, 219.54270655159556, 219.78170988505846, 219.98636321372285]], [[5, 239, 0, 67, 348, 60], [0.0, 282.7914425862282, 284.89296235603996, 287.3969380491031, 287.6890682664185, 287.76900458527496]], [[6, 85, 79, 125, 382, 251], [0.0, 542.9990791889062, 548.0501801842602, 553.0045207771814, 555.3017197884408, 556.0323731582541]], [[7, 0, 239, 10, 67, 60], [0.0, 268.6093818167936, 269.74803057668464, 273.11719096387907, 273.21420168065936, 273.55072655725115]], [[8, 239, 0, 42, 79, 348], [0.0, 253.8936785349332, 256.36107348815653, 256.5248525971704, 257.8100075637096, 258.13949717158744]], [[9, 0, 239, 10, 67, 60], [0.0, 113.66617790706258, 117.0341830406826, 123.58802530989804, 124.63145670335399, 124.64750298341319]], [[10, 0, 239, 60, 67, 33], [0.0, 66.90291473471092, 72.8766080440082, 82.67405880927826, 83.48053665376139, 88.6904729945669]], [[11, 239, 42, 43, 0, 33], [0.0, 368.09373806138024, 368.13041167499324, 368.80618216076584, 368.92817729200357, 370.2998784768907]], [[12, 0, 239, 10, 67, 60], [0.0, 335.6203211964377, 337.6210893886814, 339.6719005157771, 339.7587379303143, 340.32631399878557]], [[13, 0, 239, 10, 67, 60], [0.0, 166.08130538986018, 168.14874367654372, 172.00872070915474, 173.1762108374011, 173.37243148782335]], [[14, 34, 42, 48, 239, 89], [0.0, 306.25479588081555, 306.3217262944305, 308.0405817420815, 308.2369218636859, 308.33585584553737]], [[15, 0, 239, 10, 33, 60], [0.0, 222.56459736445058, 222.58930791931584, 224.7420743875076, 224.98222151983475, 225.4196087300304]], [[16, 251, 79, 382, 42, 239], [0.0, 427.66692647433, 434.8126033131974, 436.8901463754933, 439.70558331683714, 444.68865512850675]], [[17, 75, 49, 0, 373, 10], [0.0, 470.89383092157834, 471.6047073556412, 474.08543533839975, 475.23047040357164, 475.43979639908144]], [[18, 0, 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315, 264, 248], [2.980232238769531e-07, 2.980232238769531e-07, 0.04432255029678345, 0.04545408487319946, 0.04711806774139404, 0.047833144664764404]], [[347, 289, 360, 304, 379, 323], [1.7881393432617188e-07, 0.041539788246154785, 0.047107577323913574, 0.04742884635925293, 0.048440515995025635, 0.050191521644592285]], [[348, 178, 67, 60, 10, 55], [0.0, 0.045823872089385986, 0.04662448167800903, 0.047116994857788086, 0.049902498722076416, 0.050887346267700195]], [[349, 388, 341, 248, 297, 215], [0.0, 0.052068352699279785, 0.06194567680358887, 0.06292980909347534, 0.06334900856018066, 0.06582224369049072]], [[350, 224, 253, 321, 372, 359], [2.384185791015625e-07, 0.039740920066833496, 0.04149752855300903, 0.04431033134460449, 0.04641515016555786, 0.04891777038574219]], [[351, 303, 157, 140, 69, 283], [5.960464477539063e-08, 0.03783857822418213, 0.037863969802856445, 0.038742244243621826, 0.04005134105682373, 0.04178851842880249]], [[352, 10, 178, 348, 67, 60], [0.0, 0.060358524322509766, 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[[359, 344, 224, 253, 366, 211], [0.0, 0.04086506366729736, 0.04346853494644165, 0.043941378593444824, 0.04764068126678467, 0.047681212425231934]], [[360, 347, 20, 289, 281, 304], [5.960464477539063e-08, 0.047107577323913574, 0.048667192459106445, 0.053971827030181885, 0.057216763496398926, 0.05878889560699463]], [[361, 379, 284, 289, 323, 304], [0.0, 0.05255246162414551, 0.05539870262145996, 0.05594289302825928, 0.05623650550842285, 0.05740863084793091]], [[362, 98, 191, 236, 369, 64], [0.0, 0.14328312873840332, 0.15711617469787598, 0.16508632898330688, 0.17009973526000977, 0.17091631889343262]], [[363, 351, 303, 172, 288, 331], [0.0, 0.04253339767456055, 0.04371905326843262, 0.04431450366973877, 0.044401586055755615, 0.0456920862197876]], [[364, 180, 109, 191, 159, 153], [0.0, 0.09463024139404297, 0.1346331238746643, 0.14883947372436523, 0.14951008558273315, 0.15180611610412598]], [[365, 105, 112, 229, 45, 343], [0.0, 0.07727980613708496, 0.07727980613708496, 0.08045876026153564, 0.08407634496688843, 0.0856505036354065]], [[366, 224, 211, 95, 253, 213], [0.0, 0.03657233715057373, 0.04077184200286865, 0.04081171751022339, 0.042626142501831055, 0.04421001672744751]], [[367, 191, 353, 357, 122, 383], [0.0, 0.06222623586654663, 0.08190727233886719, 0.095009446144104, 0.09586310386657715, 0.09700959920883179]], [[368, 347, 289, 304, 20, 361], [5.960464477539063e-08, 0.057599425315856934, 0.05887603759765625, 0.06240040063858032, 0.06439077854156494, 0.06465780735015869]], [[369, 82, 2, 210, 13, 311], [0.0, 0.10376942157745361, 0.11329436302185059, 0.11345469951629639, 0.11726236343383789, 0.11798977851867676]], [[370, 228, 259, 128, 220, 323], [0.0, 0.07302343845367432, 0.10194361209869385, 0.10335290431976318, 0.1067693829536438, 0.112862229347229]], [[371, 331, 263, 385, 150, 260], [0.0, 0.08280110359191895, 0.08405357599258423, 0.08771222829818726, 0.08802986145019531, 0.0894361138343811]], [[372, 321, 313, 151, 176, 224], [0.0, 0.03693962097167969, 0.039354801177978516, 0.03986310958862305, 0.04081320762634277, 0.04128897190093994]], [[373, 331, 288, 25, 363, 69], [0.0, 0.03210270404815674, 0.04745805263519287, 0.049719810485839844, 0.05109107494354248, 0.05379456281661987]], [[374, 139, 231, 281, 304, 13], [0.0, 0.051259756088256836, 0.05210977792739868, 0.052222251892089844, 0.052236199378967285, 0.05283236503601074]], [[375, 76, 84, 30, 309, 210], [2.980232238769531e-07, 0.04639464616775513, 0.05475902557373047, 0.05500936508178711, 0.05542290210723877, 0.058007240295410156]], [[376, 229, 378, 45, 71, 92], [1.1920928955078125e-07, 0.05503499507904053, 0.05789291858673096, 0.0647956132888794, 0.0661664605140686, 0.06734025478363037]], [[377, 202, 163, 151, 176, 313], [0.0, 0.034522414207458496, 0.0456504225730896, 0.05094647407531738, 0.052927613258361816, 0.05370604991912842]], [[378, 229, 154, 96, 45, 71], [0.0, 0.027566850185394287, 0.0352669358253479, 0.03636223077774048, 0.037140846252441406, 0.03851675987243652]], [[379, 213, 304, 323, 289, 347], [0.0, 0.03827625513076782, 0.04258298873901367, 0.04601097106933594, 0.04618537425994873, 0.048440515995025635]], [[380, 262, 305, 100, 36, 226], [1.1920928955078125e-07, 0.06650638580322266, 0.08381253480911255, 0.09024930000305176, 0.09478932619094849, 0.09635621309280396]], [[381, 127, 118, 167, 177, 266], [1.1920928955078125e-07, 0.10467958450317383, 0.11471152305603027, 0.12158674001693726, 0.1332908272743225, 0.13792860507965088]], [[382, 208, 332, 24, 22, 41], [0.0, 0.09446132183074951, 0.1030498743057251, 0.10537409782409668, 0.10602927207946777, 0.10604262351989746]], [[383, 18, 49, 53, 143, 353], [0.0, 0.07739043235778809, 0.08003437519073486, 0.08219456672668457, 0.08422672748565674, 0.08482646942138672]], [[384, 386, 292, 16, 171, 305], [5.960464477539063e-08, 0.04579782485961914, 0.05793106555938721, 0.06560969352722168, 0.06700634956359863, 0.06717205047607422]], [[385, 85, 124, 150, 371, 250], [1.7881393432617188e-07, 0.060361623764038086, 0.07818859815597534, 0.07880616188049316, 0.08771222829818726, 0.0902637243270874]], [[386, 292, 384, 305, 99, 232], [0.0, 0.042023658752441406, 0.04579782485961914, 0.04854476451873779, 0.05754208564758301, 0.06365704536437988]], [[387, 346, 297, 315, 264, 248], [2.980232238769531e-07, 2.980232238769531e-07, 0.04432255029678345, 0.04545408487319946, 0.04711806774139404, 0.047833144664764404]], [[388, 248, 264, 215, 297, 341], [0.0, 0.037600159645080566, 0.03965330123901367, 0.04084932804107666, 0.04194521903991699, 0.047194480895996094]], [[389, 164, 247, 151, 46, 163], [1.7881393432617188e-07, 0.042870163917541504, 0.04697549343109131, 0.05527430772781372, 0.057344913482666016, 0.05813324451446533]]] pred = [2,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 ,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 ,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,1,2,2,2,1,1,1,1,1,1,1,2,1 ,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 ,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 ,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 ,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 ,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 ,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 ,2,2,2,2,2,2,2,2,3,0,0,3,0,3,3,3,3,3,3,3,3,3,0,3,3,3,3,3,3,3,3,3,3,3,3,3,3 ,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3] title = "Nearest neighbors on Model 3 : 3D CNN 2048" print("<h3>"+title+"</h3>"+"<br/><br/>") print("<table style=\"width:100%\">") print("<td>") print("<b>Original</b>") print("</td>") print("<td>") print("<b>Nearest neighbors</b>") print("</td>") for i in range(0, 390): print("</tr>") typ = [] print("<tr id=\"a"+str(i)+"\">") for j in range(0, 5): print("<td>") print("<figure>") print("<a href=\"#a"+str(arr[i][0][j])+"\">") print("<img src=\"./"+ str(arr[i][0][j]+1)+".png\" alt='missing' >") print("</a>") print("<figcaption>") if arr[i][0][j] < 97 : print("Ancient, ") elif arr[i][0][j] < 131: print("Asian,") elif arr[i][0][j] < 341: print("Medieval, ") else: print("Modern,") if pred[arr[i][0][j]] == 0: print("Ancient") if pred[arr[i][0][j]] == 1: print("Asian") if pred[arr[i][0][j]] == 2: print("Medieval") if pred[arr[i][0][j]] == 3: print("Modern") # if pred[i] == 0 : # print("Ancient, Ancient") # elif pred[i] == 1: # print("Asian, Asian") # elif pred[i] == 2: # print("Medieval, Medieval") # else: # print("Modern, Modern") if j!=0: print(", Distance: "+str(arr[i][1][j])) print("</figcaption>") print("</figure>") print("</td>") print("</tr>") print("</table>") print("</body></html>")	0	0	0
14d30ee0c043ae6980a427f35c470ba92110bfd2	1,446	py	Python	past-competitions/2018/src/brett-python/Prob07.py	gideontong/CodeQuest	8da4fe367221094cdf058402a4719ca0dc4bdaac	[ "MIT" ]	2	2021-05-23T01:21:59.000Z	2022-02-17T23:12:48.000Z	past-competitions/2018/src/brett-python/Prob07.py	gideontong/CodeQuest	8da4fe367221094cdf058402a4719ca0dc4bdaac	[ "MIT" ]	null	null	null	past-competitions/2018/src/brett-python/Prob07.py	gideontong/CodeQuest	8da4fe367221094cdf058402a4719ca0dc4bdaac	[ "MIT" ]	null	null	null	# Open the input file with open("Prob07.in.txt", "rt") as inputFile: # Read the number of test cases (trim out the newline) cases = int(inputFile.readline().replace("\n", "")) # For each test case for caseNum in range(cases): # Read the number of words wordCount = int(inputFile.readline().replace("\n", "")) nonPalindromes = [] # For each word for j in range(wordCount): word = inputFile.readline().replace("\n", "") # compare each pair of letters, moving inward for k in range(len(word) // 2): if word[k].upper() != word[-(k + 1)].upper(): # if any are unequal, note the index of the word nonPalindromes.append(j + 1) break # end for k # end for j if len(nonPalindromes) == 0: # all were palindromes print("True") else: # at least one wasn't # specify end to suppress the automatic newline print("False - ", end="") first = True # print each index for index in nonPalindromes: if not first: # add commas as needed print(", ", end="") first = False print(str(index), end="") # now print a newline print("")	36.15	68	0.478562	# Open the input file with open("Prob07.in.txt", "rt") as inputFile: # Read the number of test cases (trim out the newline) cases = int(inputFile.readline().replace("\n", "")) # For each test case for caseNum in range(cases): # Read the number of words wordCount = int(inputFile.readline().replace("\n", "")) nonPalindromes = [] # For each word for j in range(wordCount): word = inputFile.readline().replace("\n", "") # compare each pair of letters, moving inward for k in range(len(word) // 2): if word[k].upper() != word[-(k + 1)].upper(): # if any are unequal, note the index of the word nonPalindromes.append(j + 1) break # end for k # end for j if len(nonPalindromes) == 0: # all were palindromes print("True") else: # at least one wasn't # specify end to suppress the automatic newline print("False - ", end="") first = True # print each index for index in nonPalindromes: if not first: # add commas as needed print(", ", end="") first = False print(str(index), end="") # now print a newline print("")	0	0	0
8e677461788a883eb660d8987193edb44d9015eb	5,801	py	Python	see/context/resources/test/vbox_test.py	security-geeks/see	900472b8b3e45fbb414f3beba4df48e86eaa4b3a	[ "Apache-2.0" ]	851	2015-10-28T09:32:05.000Z	2022-03-31T02:32:28.000Z	see/context/resources/test/vbox_test.py	security-geeks/see	900472b8b3e45fbb414f3beba4df48e86eaa4b3a	[ "Apache-2.0" ]	29	2015-12-21T15:43:28.000Z	2021-05-16T10:57:09.000Z	see/context/resources/test/vbox_test.py	security-geeks/see	900472b8b3e45fbb414f3beba4df48e86eaa4b3a	[ "Apache-2.0" ]	110	2015-10-26T13:05:18.000Z	2021-11-17T18:00:17.000Z	import sys import mock import libvirt import difflib import unittest from see.context.resources import vbox def compare(text1, text2): """Utility function for comparing text and returining differences.""" diff = difflib.ndiff(text1.splitlines(True), text2.splitlines(True)) return '\n' + '\n'.join(diff)	44.968992	109	0.620927	import sys import mock import libvirt import difflib import unittest from see.context.resources import vbox def compare(text1, text2): """Utility function for comparing text and returining differences.""" diff = difflib.ndiff(text1.splitlines(True), text2.splitlines(True)) return '\n' + '\n'.join(diff) class DomainXMLTest(unittest.TestCase): def test_domain_xml(self): """VBOX Domain XML.""" config = """<domain></domain>""" expected = """<domain><name>foo</name><uuid>foo</uuid><devices><disk device="disk" type="file">""" +\ """<source file="/diskpath.vdi" /></disk></devices></domain>""" results = vbox.domain_xml('foo', config, '/diskpath.vdi') self.assertEqual(results, expected, compare(results, expected)) def test_domain_xml_modifies(self): """VBOX Fields are modified if existing.""" config = """<domain><name>bar</name><uuid>bar</uuid><devices><disk device="disk" type="file">""" +\ """<source file="/bar"/></disk></devices></domain>""" expected = """<domain><name>foo</name><uuid>foo</uuid><devices><disk device="disk" type="file">""" +\ """<source file="/diskpath.vdi" /></disk></devices></domain>""" results = vbox.domain_xml('foo', config, '/diskpath.vdi') self.assertEqual(results, expected, compare(results, expected)) class DomainCreateTest(unittest.TestCase): def test_create(self): """VBOX Create domain.""" xml = """<domain></domain>""" expected = """<domain><name>foo</name><uuid>foo</uuid><devices><disk device="disk" type="file">""" +\ """<source file="/diskpath.vdi" /></disk></devices></domain>""" hypervisor = mock.Mock() hypervisor.listNetworks.return_value = [] with mock.patch('see.context.resources.vbox.open', mock.mock_open(read_data=xml), create=True): vbox.domain_create(hypervisor, 'foo', {'configuration': '/foo'}, '/diskpath.vdi') results = hypervisor.defineXML.call_args_list[0][0][0] self.assertEqual(results, expected, compare(results, expected)) class DomainDeleteTest(unittest.TestCase): def test_delete_destroy(self): """VBOX Domain is destroyed if active.""" domain = mock.Mock() logger = mock.Mock() domain.isActive.return_value = True vbox.domain_delete(domain, logger) self.assertTrue(domain.destroy.called) def test_delete_destroy_error(self): """VBOX Domain destroy raises error.""" domain = mock.Mock() logger = mock.Mock() domain.isActive.return_value = True domain.destroy.side_effect = libvirt.libvirtError("BOOM") vbox.domain_delete(domain, logger) self.assertTrue(domain.undefine.called) def test_delete_undefine(self): """VBOX Domain is undefined.""" domain = mock.Mock() logger = mock.Mock() domain.isActive.return_value = False vbox.domain_delete(domain, logger) self.assertTrue(domain.undefine.called) def test_delete_undefine_snapshots(self): """VBOX Domain undefine with snapshots metadata.""" domain = mock.Mock() logger = mock.Mock() domain.isActive.return_value = False domain.undefine.side_effect = libvirt.libvirtError("BOOM") vbox.domain_delete(domain, logger) domain.undefineFlags.assert_called_with(libvirt.VIR_DOMAIN_UNDEFINE_SNAPSHOTS_METADATA) class ResourcesTest(unittest.TestCase): if sys.version_info.major >= 3: builtin_module = 'builtins' else: builtin_module = '__builtin__' @mock.patch('see.context.resources.vbox.libvirt') @mock.patch('see.context.resources.vbox.domain_create') @mock.patch('%s.open' % builtin_module, new_callable=mock.mock_open) def test_allocate_default(self, _, create_mock, libvirt_mock): """VBOX Resources allocater with no extra value.""" resources = vbox.VBoxResources('foo', {'domain': 'bar', 'disk': {'image': '/foo/bar'}}) resources.allocate() libvirt_mock.open.assert_called_with('vbox:///session') create_mock.assert_called_with(resources.hypervisor, 'foo', 'bar', '/foo/bar') @mock.patch('see.context.resources.vbox.libvirt') @mock.patch('see.context.resources.vbox.domain_create') @mock.patch('%s.open' % builtin_module, new_callable=mock.mock_open) def test_allocate_hypervisor(self, _, create_mock, libvirt_mock): """VBOX Resources allocater with hypervisor.""" resources = vbox.VBoxResources('foo', {'domain': 'bar', 'hypervisor': 'baz', 'disk': {'image': '/foo/bar'}}) resources.allocate() libvirt_mock.open.assert_called_with('baz') create_mock.assert_called_with(resources.hypervisor, 'foo', 'bar', '/foo/bar') @mock.patch('see.context.resources.vbox.libvirt') @mock.patch('see.context.resources.vbox.domain_create') @mock.patch('see.context.resources.vbox.domain_delete') def test_deallocate(self, delete_mock, create_mock, libvirt_mock): """VBOX Resources are released on deallocate.""" resources = vbox.VBoxResources('foo', {'domain': 'bar', 'disk': {'image': '/foo/bar'}}) resources._domain = mock.Mock() resources._hypervisor = mock.Mock() resources.deallocate() delete_mock.assert_called_with(resources.domain, mock.ANY) self.assertTrue(resources._hypervisor.close.called)	0	5,386	92
9888e98a07ee556543a1ef4aa21ba395358d4ab3	9,658	py	Python	D3G/main.py	uber-research/D3G	475a1f2491d32da6369846361d77e372908fd1df	[ "Apache-2.0" ]	25	2020-02-25T14:30:11.000Z	2021-07-05T18:42:32.000Z	D3G/main.py	uber-research/D3G	475a1f2491d32da6369846361d77e372908fd1df	[ "Apache-2.0" ]	null	null	null	D3G/main.py	uber-research/D3G	475a1f2491d32da6369846361d77e372908fd1df	[ "Apache-2.0" ]	5	2020-03-17T12:59:43.000Z	2020-10-06T20:34:15.000Z	""" Modifications Copyright (c) 2019 Uber Technologies, Inc. """ import numpy as np import cv2 import torch import gym import argparse import os import utils import TD3 import OurDDPG import D3G import Standard_QSS # Runs policy for X episodes and returns average reward # A fixed seed is used for the eval environment if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument("--policy", default="TD3") # Policy name (TD3, DDPG or OurDDPG) parser.add_argument("--env", default="HalfCheetah-v2") # OpenAI gym environment name parser.add_argument("--save_dir", default=".") # OpenAI gym environment name parser.add_argument("--seed", default=0, type=int) # Sets Gym, PyTorch and Numpy seeds parser.add_argument("--start_timesteps", default=1e4, type=int) # Time steps initial random policy is used parser.add_argument("--train_vae", default=1e4, type=int) # Time steps for training vae parser.add_argument("--eval_freq", default=5e3, type=int) # How often (time steps) we evaluate parser.add_argument("--max_timesteps", default=1e6, type=int) # Max time steps to run environment parser.add_argument("--expl_noise", default=0.1, type=float) # Std of Gaussian exploration noise parser.add_argument("--batch_size", default=256, type=int) # Batch size for both actor and critic parser.add_argument("--discount", default=0.99) # Discount factor parser.add_argument("--tau", default=0.005) # Target network update rate parser.add_argument("--policy_noise", default=0.2) # Noise added to target policy during critic update parser.add_argument("--noise_clip", default=0.5) # Range to clip target policy noise parser.add_argument("--policy_freq", default=2, type=int) # Frequency of delayed policy updates parser.add_argument("--save_model", action="store_true") # Save model and optimizer parameters parser.add_argument("--visualize", action="store_true") # Visualize model predictions parser.add_argument("--is_discrete", action="store_true") # Save model and optimizer parameters parser.add_argument("--load_model", default="") # Model load file name, "" doesn't load, "default" uses file_name args = parser.parse_args() if args.load_model: file_name = f"{args.policy}_{args.env}_{args.seed}" else: file_name = f"{args.policy}_{args.env}_{args.seed}" print("---------------------------------------") print(f"Policy: {args.policy}, Env: {args.env}, Seed: {args.seed}") print("---------------------------------------") results_dir = os.path.join(args.save_dir, "results") models_dir = os.path.join(args.save_dir, "models") if not os.path.exists(results_dir): os.makedirs(results_dir) if args.save_model and not os.path.exists(models_dir): os.makedirs(models_dir) env = make_env(args.env) # Set seeds env.seed(args.seed) torch.manual_seed(args.seed) np.random.seed(args.seed) state_dim = env.observation_space.shape[0] if args.is_discrete: action_dim = env.action_space.n max_action = float(action_dim) else: action_dim = env.action_space.shape[0] max_action = float(env.action_space.high[0]) kwargs = { "state_dim": state_dim, "action_dim": action_dim, "max_action": max_action, "discount": args.discount, "is_discrete": args.is_discrete, "tau": args.tau, } # Initialize policy if args.policy == "TD3": # Target policy smoothing is scaled wrt the action scale kwargs["policy_noise"] = args.policy_noise * max_action kwargs["noise_clip"] = args.noise_clip * max_action kwargs["policy_freq"] = args.policy_freq policy = TD3.TD3(kwargs) elif args.policy == "OurDDPG": policy = OurDDPG.DDPG(kwargs) elif args.policy == "D3G": kwargs["policy_freq"] = args.policy_freq policy = D3G.D3G(kwargs) elif args.policy == "Standard_QSS": kwargs["policy_freq"] = args.policy_freq policy = Standard_QSS.Standard_QSS(kwargs) if args.load_model != "": policy_file = file_name if args.load_model == "default" else args.load_model policy.load(f"{models_dir}/{policy_file}") replay_buffer = utils.ReplayBuffer(state_dim, action_dim, args.is_discrete) # Evaluate untrained policy evaluations = [eval_policy(policy, args.env, args.seed)] state, done = env.reset(), False episode_reward = 0 episode_timesteps = 0 episode_num = 0 for t in range(int(args.max_timesteps)): episode_timesteps += 1 # Select action randomly or according to policy if t < args.start_timesteps: action = env.action_space.sample() elif args.is_discrete: if np.random.uniform(0,1) < .1: action = env.action_space.sample() else: action = policy.select_action(np.array(state)) else: action = ( policy.select_action(np.array(state)) + np.random.normal(0, max_action * args.expl_noise, size=action_dim) ).clip(-max_action, max_action) # Perform action next_state, reward, done, _ = env.step(action) done_bool = float(done) if episode_timesteps < env._max_episode_steps else 0 # Store data in replay buffer replay_buffer.add(state, action, next_state, reward, done_bool) state = next_state episode_reward += reward if t >= args.start_timesteps: policy.train(replay_buffer, args.batch_size) if done: # +1 to account for 0 indexing. +0 on ep_timesteps since it will increment +1 even if done=True print(f"Total T: {t+1} Episode Num: {episode_num+1} Episode T: {episode_timesteps} Reward: {episode_reward:.3f}") # Reset environment state, done = env.reset(), False episode_reward = 0 episode_timesteps = 0 episode_num += 1 # Evaluate episode if (t + 1) % args.eval_freq == 0: evaluation = eval_policy(policy, args.env, args.seed) evaluations.append(evaluation) np.save(f"{results_dir}/{file_name}", evaluations) if args.visualize: visualize(policy, args.env) elif args.save_model: policy.save(f"{models_dir}/{file_name}")	41.273504	171	0.565231	""" Modifications Copyright (c) 2019 Uber Technologies, Inc. """ import numpy as np import cv2 import torch import gym import argparse import os import utils import TD3 import OurDDPG import D3G import Standard_QSS def done_condition(env_name, state): if 'Reacher' in env_name: return (np.abs(np.linalg.norm(state[-3:])) > .02) return (np.abs(state[1]) <= .2) def set_state(eval_env, state): if 'Reacher' in eval_env.unwrapped.spec.id: adjust = (state[0:2] < 0) * np.pi eval_env.set_state(np.concatenate([np.arctan(state[2:4]/state[0:2]) + adjust, eval_env.get_body_com("target")[:2]]), np.concatenate([state[6:8], np.array([0,0])])) state[4:6] = eval_env.get_body_com("target")[:2] # target position state[-3:] = eval_env.get_body_com("fingertip") - eval_env.get_body_com("target") # fingertip - target else: eval_env.set_state(state[0:2], state[2:4]) return state def visualize(policy, env_name): eval_env = gym.make(env_name) state = eval_env.reset() total_reward = 0 for i in range(200): done = not (np.isfinite(state).all() and done_condition(env_name, state)) if done: print(f"Reward {total_reward}") return total_reward else: total_reward += 1 print(i) img = cv2.cvtColor(eval_env.render("rgb_array"), cv2.COLOR_BGR2RGB) cv2.imshow("Model prediction", img) cv2.waitKey(1) state = np.squeeze(policy.select_goal(state)) try: state = set_state(eval_env, state) time.sleep(.01) except: pass return total_reward def make_env(env_name): return gym.make(env_name) # Runs policy for X episodes and returns average reward # A fixed seed is used for the eval environment def eval_policy(policy, env_name, seed, eval_episodes=10): eval_env = make_env(env_name) eval_env.seed(seed + 100) avg_reward = 0. for _ in range(eval_episodes): state, done = eval_env.reset(), False while not done: action = policy.select_action(np.array(state)) state, reward, done, _ = eval_env.step(action) avg_reward += reward avg_reward /= eval_episodes print("---------------------------------------") print(f"Evaluation over {eval_episodes} episodes: {avg_reward:.3f}") print("---------------------------------------") return avg_reward if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument("--policy", default="TD3") # Policy name (TD3, DDPG or OurDDPG) parser.add_argument("--env", default="HalfCheetah-v2") # OpenAI gym environment name parser.add_argument("--save_dir", default=".") # OpenAI gym environment name parser.add_argument("--seed", default=0, type=int) # Sets Gym, PyTorch and Numpy seeds parser.add_argument("--start_timesteps", default=1e4, type=int) # Time steps initial random policy is used parser.add_argument("--train_vae", default=1e4, type=int) # Time steps for training vae parser.add_argument("--eval_freq", default=5e3, type=int) # How often (time steps) we evaluate parser.add_argument("--max_timesteps", default=1e6, type=int) # Max time steps to run environment parser.add_argument("--expl_noise", default=0.1, type=float) # Std of Gaussian exploration noise parser.add_argument("--batch_size", default=256, type=int) # Batch size for both actor and critic parser.add_argument("--discount", default=0.99) # Discount factor parser.add_argument("--tau", default=0.005) # Target network update rate parser.add_argument("--policy_noise", default=0.2) # Noise added to target policy during critic update parser.add_argument("--noise_clip", default=0.5) # Range to clip target policy noise parser.add_argument("--policy_freq", default=2, type=int) # Frequency of delayed policy updates parser.add_argument("--save_model", action="store_true") # Save model and optimizer parameters parser.add_argument("--visualize", action="store_true") # Visualize model predictions parser.add_argument("--is_discrete", action="store_true") # Save model and optimizer parameters parser.add_argument("--load_model", default="") # Model load file name, "" doesn't load, "default" uses file_name args = parser.parse_args() if args.load_model: file_name = f"{args.policy}_{args.env}_{args.seed}" else: file_name = f"{args.policy}_{args.env}_{args.seed}" print("---------------------------------------") print(f"Policy: {args.policy}, Env: {args.env}, Seed: {args.seed}") print("---------------------------------------") results_dir = os.path.join(args.save_dir, "results") models_dir = os.path.join(args.save_dir, "models") if not os.path.exists(results_dir): os.makedirs(results_dir) if args.save_model and not os.path.exists(models_dir): os.makedirs(models_dir) env = make_env(args.env) # Set seeds env.seed(args.seed) torch.manual_seed(args.seed) np.random.seed(args.seed) state_dim = env.observation_space.shape[0] if args.is_discrete: action_dim = env.action_space.n max_action = float(action_dim) else: action_dim = env.action_space.shape[0] max_action = float(env.action_space.high[0]) kwargs = { "state_dim": state_dim, "action_dim": action_dim, "max_action": max_action, "discount": args.discount, "is_discrete": args.is_discrete, "tau": args.tau, } # Initialize policy if args.policy == "TD3": # Target policy smoothing is scaled wrt the action scale kwargs["policy_noise"] = args.policy_noise * max_action kwargs["noise_clip"] = args.noise_clip * max_action kwargs["policy_freq"] = args.policy_freq policy = TD3.TD3(kwargs) elif args.policy == "OurDDPG": policy = OurDDPG.DDPG(kwargs) elif args.policy == "D3G": kwargs["policy_freq"] = args.policy_freq policy = D3G.D3G(kwargs) elif args.policy == "Standard_QSS": kwargs["policy_freq"] = args.policy_freq policy = Standard_QSS.Standard_QSS(kwargs) if args.load_model != "": policy_file = file_name if args.load_model == "default" else args.load_model policy.load(f"{models_dir}/{policy_file}") replay_buffer = utils.ReplayBuffer(state_dim, action_dim, args.is_discrete) # Evaluate untrained policy evaluations = [eval_policy(policy, args.env, args.seed)] state, done = env.reset(), False episode_reward = 0 episode_timesteps = 0 episode_num = 0 for t in range(int(args.max_timesteps)): episode_timesteps += 1 # Select action randomly or according to policy if t < args.start_timesteps: action = env.action_space.sample() elif args.is_discrete: if np.random.uniform(0,1) < .1: action = env.action_space.sample() else: action = policy.select_action(np.array(state)) else: action = ( policy.select_action(np.array(state)) + np.random.normal(0, max_action * args.expl_noise, size=action_dim) ).clip(-max_action, max_action) # Perform action next_state, reward, done, _ = env.step(action) done_bool = float(done) if episode_timesteps < env._max_episode_steps else 0 # Store data in replay buffer replay_buffer.add(state, action, next_state, reward, done_bool) state = next_state episode_reward += reward if t >= args.start_timesteps: policy.train(replay_buffer, args.batch_size) if done: # +1 to account for 0 indexing. +0 on ep_timesteps since it will increment +1 even if done=True print(f"Total T: {t+1} Episode Num: {episode_num+1} Episode T: {episode_timesteps} Reward: {episode_reward:.3f}") # Reset environment state, done = env.reset(), False episode_reward = 0 episode_timesteps = 0 episode_num += 1 # Evaluate episode if (t + 1) % args.eval_freq == 0: evaluation = eval_policy(policy, args.env, args.seed) evaluations.append(evaluation) np.save(f"{results_dir}/{file_name}", evaluations) if args.visualize: visualize(policy, args.env) elif args.save_model: policy.save(f"{models_dir}/{file_name}")	2,054	0	114
3317dfd8291d9c905fca53c341d286e90afbe3ff	342	py	Python	pythonProject/03al88Criar_Ler_escrever_apagar_arquivo/ler_modo_try.py	D-Wolter/PycharmProjects	c8d6144efa30261bff72a3e0414a0d80f6730f9b	[ "MIT" ]	null	null	null	pythonProject/03al88Criar_Ler_escrever_apagar_arquivo/ler_modo_try.py	D-Wolter/PycharmProjects	c8d6144efa30261bff72a3e0414a0d80f6730f9b	[ "MIT" ]	null	null	null	pythonProject/03al88Criar_Ler_escrever_apagar_arquivo/ler_modo_try.py	D-Wolter/PycharmProjects	c8d6144efa30261bff72a3e0414a0d80f6730f9b	[ "MIT" ]	null	null	null	#https://docs.python.org/3/libraty/functions.html#open #costumase usar o bloco try para abrir arquivos try: file = open('abc.txt', 'w+') file.write('Linha')# o arquivo esta vazio entao escrevemos file.seek(0) print(file.read()) finally: #para garantir que o arquivo sera fechado se holver erro file.close()	28.5	78	0.672515	#https://docs.python.org/3/libraty/functions.html#open #costumase usar o bloco try para abrir arquivos try: file = open('abc.txt', 'w+') file.write('Linha')# o arquivo esta vazio entao escrevemos file.seek(0) print(file.read()) finally: #para garantir que o arquivo sera fechado se holver erro file.close()	0	0	0
a37330d8bd84ef702161d82dfa4cbf7705b5dc92	3,406	py	Python	code.py	Namrata-NM/olympics-data-analysis	7490f33f9335077532f652709fce0301fa3ca67c	[ "MIT" ]	null	null	null	code.py	Namrata-NM/olympics-data-analysis	7490f33f9335077532f652709fce0301fa3ca67c	[ "MIT" ]	null	null	null	code.py	Namrata-NM/olympics-data-analysis	7490f33f9335077532f652709fce0301fa3ca67c	[ "MIT" ]	null	null	null	# -------------- #Importing header files import pandas as pd import numpy as np import matplotlib.pyplot as plt #Path of the file is stored in the variable path #Code starts here # Data Loading data=pd.read_csv(path) data.rename(columns={'Total':'Total_Medals'},inplace=True) data.head(10) # Summer or Winter data['Better_Event'] = np.where(data['Total_Summer'] > data['Total_Winter'] , 'Summer', 'Winter') data['Better_Event'] = np.where(data['Total_Summer'] == data['Total_Winter'] , 'Both',data['Better_Event']) better_event=data['Better_Event'].value_counts().index.values[0] # Top 10 top_countries=data[['Country_Name','Total_Summer', 'Total_Winter','Total_Medals']] top_countries=top_countries[:-1] print(top_countries.head()) # Plotting top 10 # Top Performing Countries top_10_summer=top_ten(top_countries,'Total_Summer') print("Top 10 Summer:\n",top_10_summer, "\n") top_10_winter=top_ten(top_countries,'Total_Winter') print("Top 10 Winter:\n",top_10_winter, "\n") top_10=top_ten(top_countries,'Total_Medals') print("Top 10:\n",top_10, "\n") # Best in the world common=list(set(top_10_summer) & set(top_10_winter) & set(top_10)) print('Common Countries :\n', common, "\n") # Plotting the best summer_df= data[data['Country_Name'].isin(top_10_summer)] winter_df=data[data['Country_Name'].isin(top_10_winter)] top_df=data[data['Country_Name'].isin(top_10)] plt.figure(figsize=(20, 6)) plt.bar(summer_df['Country_Name'], summer_df['Total_Summer']) plt.xlabel('Countries') plt.ylabel('Total') plt.title('Top Summer') plt.figure(figsize=(20, 6)) plt.bar(winter_df['Country_Name'], winter_df['Total_Winter']) plt.xlabel('Countries') plt.ylabel('Total') plt.title('Top Winter') plt.figure(figsize=(20, 6)) plt.bar(top_df['Country_Name'], top_df['Total_Medals']) plt.xlabel('Countries') plt.ylabel('Total') plt.title('Top overall') #Top Performing Countries summer_df['Golden_Ratio']=summer_df['Gold_Summer']/summer_df['Total_Summer'] summer_max_ratio=max(summer_df['Golden_Ratio']) summer_country_gold=summer_df.loc[summer_df['Golden_Ratio'].idxmax(),'Country_Name'] winter_df['Golden_Ratio']=winter_df['Gold_Winter']/winter_df['Total_Winter'] winter_max_ratio=max(winter_df['Golden_Ratio']) winter_country_gold=winter_df.loc[winter_df['Golden_Ratio'].idxmax(),'Country_Name'] top_df['Golden_Ratio']=top_df['Gold_Total']/top_df['Total_Medals'] top_max_ratio=max(top_df['Golden_Ratio']) top_country_gold=top_df.loc[top_df['Golden_Ratio'].idxmax(),'Country_Name'] #Best In World data_1=data[:-1] data_1['Total_Points']= data_1['Gold_Total']3 + data_1['Silver_Total']2 + data_1['Bronze_Total']*1 most_points=max(data_1['Total_Points']) best_country=data_1.loc[data_1['Total_Points'].idxmax(),'Country_Name'] #Plot the best best=data[data['Country_Name']==best_country] best.reset_index(drop = True, inplace = True) best=best[['Gold_Total','Silver_Total','Bronze_Total']] best.plot.bar(stacked=True) plt.xlabel('United States') plt.ylabel('Medals Tally') plt.xticks(rotation=45) l=plt.legend() l.get_texts()[0].set_text('Gold_Total :' + str(best['Gold_Total'].values)) l.get_texts()[1].set_text('Silver_Total :' + str(best['Silver_Total'].values)) l.get_texts()[2].set_text('Bronze_Total :' + str(best['Bronze_Total'].values))	29.617391	107	0.745449	# -------------- #Importing header files import pandas as pd import numpy as np import matplotlib.pyplot as plt #Path of the file is stored in the variable path #Code starts here # Data Loading data=pd.read_csv(path) data.rename(columns={'Total':'Total_Medals'},inplace=True) data.head(10) # Summer or Winter data['Better_Event'] = np.where(data['Total_Summer'] > data['Total_Winter'] , 'Summer', 'Winter') data['Better_Event'] = np.where(data['Total_Summer'] == data['Total_Winter'] , 'Both',data['Better_Event']) better_event=data['Better_Event'].value_counts().index.values[0] # Top 10 top_countries=data[['Country_Name','Total_Summer', 'Total_Winter','Total_Medals']] top_countries=top_countries[:-1] print(top_countries.head()) # Plotting top 10 def top_ten(df,column): country_list=[] top=df.nlargest(10,column) country_list= list(top['Country_Name']) return country_list # Top Performing Countries top_10_summer=top_ten(top_countries,'Total_Summer') print("Top 10 Summer:\n",top_10_summer, "\n") top_10_winter=top_ten(top_countries,'Total_Winter') print("Top 10 Winter:\n",top_10_winter, "\n") top_10=top_ten(top_countries,'Total_Medals') print("Top 10:\n",top_10, "\n") # Best in the world common=list(set(top_10_summer) & set(top_10_winter) & set(top_10)) print('Common Countries :\n', common, "\n") # Plotting the best summer_df= data[data['Country_Name'].isin(top_10_summer)] winter_df=data[data['Country_Name'].isin(top_10_winter)] top_df=data[data['Country_Name'].isin(top_10)] plt.figure(figsize=(20, 6)) plt.bar(summer_df['Country_Name'], summer_df['Total_Summer']) plt.xlabel('Countries') plt.ylabel('Total') plt.title('Top Summer') plt.figure(figsize=(20, 6)) plt.bar(winter_df['Country_Name'], winter_df['Total_Winter']) plt.xlabel('Countries') plt.ylabel('Total') plt.title('Top Winter') plt.figure(figsize=(20, 6)) plt.bar(top_df['Country_Name'], top_df['Total_Medals']) plt.xlabel('Countries') plt.ylabel('Total') plt.title('Top overall') #Top Performing Countries summer_df['Golden_Ratio']=summer_df['Gold_Summer']/summer_df['Total_Summer'] summer_max_ratio=max(summer_df['Golden_Ratio']) summer_country_gold=summer_df.loc[summer_df['Golden_Ratio'].idxmax(),'Country_Name'] winter_df['Golden_Ratio']=winter_df['Gold_Winter']/winter_df['Total_Winter'] winter_max_ratio=max(winter_df['Golden_Ratio']) winter_country_gold=winter_df.loc[winter_df['Golden_Ratio'].idxmax(),'Country_Name'] top_df['Golden_Ratio']=top_df['Gold_Total']/top_df['Total_Medals'] top_max_ratio=max(top_df['Golden_Ratio']) top_country_gold=top_df.loc[top_df['Golden_Ratio'].idxmax(),'Country_Name'] #Best In World data_1=data[:-1] data_1['Total_Points']= data_1['Gold_Total']3 + data_1['Silver_Total']2 + data_1['Bronze_Total']*1 most_points=max(data_1['Total_Points']) best_country=data_1.loc[data_1['Total_Points'].idxmax(),'Country_Name'] #Plot the best best=data[data['Country_Name']==best_country] best.reset_index(drop = True, inplace = True) best=best[['Gold_Total','Silver_Total','Bronze_Total']] best.plot.bar(stacked=True) plt.xlabel('United States') plt.ylabel('Medals Tally') plt.xticks(rotation=45) l=plt.legend() l.get_texts()[0].set_text('Gold_Total :' + str(best['Gold_Total'].values)) l.get_texts()[1].set_text('Silver_Total :' + str(best['Silver_Total'].values)) l.get_texts()[2].set_text('Bronze_Total :' + str(best['Bronze_Total'].values))	121	0	22
b1d982527a36cd045a0ec9f565af25b1ae1a1041	921	py	Python	hw9/task_3.py	DashViolin/gb_python_lvl1	ce4d6e8a717122c4d492b724b249d881c885d30c	[ "Apache-2.0" ]	1	2021-11-01T18:24:38.000Z	2021-11-01T18:24:38.000Z	hw9/task_3.py	DashViolin/gb_python_lvl1	ce4d6e8a717122c4d492b724b249d881c885d30c	[ "Apache-2.0" ]	1	2021-10-04T17:48:29.000Z	2021-10-04T17:48:29.000Z	hw9/task_3.py	DashViolin/gb_python_lvl1	ce4d6e8a717122c4d492b724b249d881c885d30c	[ "Apache-2.0" ]	null	null	null	from typing import Union welder = Position(name='Alex', surname='Murphy', position='welder', wage=120000, bonus=30000) print(welder) print(welder.get_full_name()) miller = Position(name='Anne', surname='Lewis', position='miller', wage=150000, bonus=24000) print(miller) print(miller.get_total_income())	27.909091	114	0.647123	from typing import Union class Worker: def __init__(self, name: str, surname: str, position: str, wage: Union[int, float], bonus: Union[int, float]): self.name = name.capitalize() self.surname = surname.capitalize() self.position = position self._income = { "wage": wage, "bonus": bonus, } def __str__(self): return f'{self.name} {self.surname} ({self.position})' class Position(Worker): def get_full_name(self): return f'{self.name} {self.surname}' def get_total_income(self): return self._income["wage"] + self._income["bonus"] welder = Position(name='Alex', surname='Murphy', position='welder', wage=120000, bonus=30000) print(welder) print(welder.get_full_name()) miller = Position(name='Anne', surname='Lewis', position='miller', wage=150000, bonus=24000) print(miller) print(miller.get_total_income())	467	-6	152
1274d5c5256b405787333273d1e01c0f02bbbaf3	9,903	py	Python	obstacle2osm.py	osmno/obstacle2osm	e45dad160812506f8dd6dddc1c89a75930710fab	[ "CC0-1.0" ]	1	2021-05-27T09:37:01.000Z	2021-05-27T09:37:01.000Z	obstacle2osm.py	osmno/obstacle2osm	e45dad160812506f8dd6dddc1c89a75930710fab	[ "CC0-1.0" ]	null	null	null	obstacle2osm.py	osmno/obstacle2osm	e45dad160812506f8dd6dddc1c89a75930710fab	[ "CC0-1.0" ]	null	null	null	#!/usr/bin/env python3 # -*- coding: utf8 # obstacle2osm # Converts aviation obstacles from Kartverket WFS/GML files for import/update in OSM # Usage: obstacle2.osm [county] # Creates OSM file with name "Luftfartshinder_" + county + ".osm" import html import time import sys import urllib.request import json import zipfile from io import BytesIO from xml.etree import ElementTree import utm # Local library version = "1.0.0" # Tagging per obstacle type tagging_table = { 'Landbruksutstyr': [], 'Telemast': ['man_made=mast', 'tower:type=communication'], 'Bru': ['man_made=tower', 'tower:type=bridge'], 'Bygning': ['building=yes'], 'Gondolbane': ['aerialway=gondola'], u'Kontrolltårn': ['man_made=tower', 'tower:type=airport_control'], u'Kjøletårn': ['man_made=tower', 'tower_type=cooling'], 'Kran': ['man_made=crane'], 'Demning': ['waterway=dam'], 'Kuppel': ['man_made=tower', 'tower:construction=dome'], 'EL_Nettstasjon': ['power=substation', 'power=transformer'], 'Gjerde': ['barrier=fence'], u'Fyrtårn': ['man_made=lighthouse'], 'Monument': ['man_made=tower', 'tower:type=monument'], 'Terrengpunkt': ['natural=peak'], 'Navigasjonshjelpemiddel': ['aeroway=navigationaid'], 'Stolpe': ['man_made=mast'], 'Kraftverk': ['power=plant'], 'Raffineri': ['man_made=tower'], 'Oljerigg': [], 'Skilt': [], 'Pipe': ['man_made=chimney'], 'Tank': ['man_made=storage_tank'], 'Forankret ballong': [], u'Tårn': ['man_made=tower'], 'Kraftledning': [], 'Tre': ['natural=tree'], u'Skogsområde': ['natural=wood'], u'Vanntårn': ['man_made=storage_tank', 'content=water'], u'Vindmølle': ['power=generator', 'generator:source=wind', 'generator:method=wind_turbine', 'generator:type=horizontal_axis'], u'Vindmøllepark': ['type=site', 'power=plant', 'plant:source=wind'], u'Hopptårn': ['man_made=tower', 'piste:type=ski_jump'], u'Vindmåler': ['man_made=mast', 'tower:type=monitoring'], 'Lysmast': ['man_made=mast', 'tower:type=lighting'], 'Flaggstang': ['man_made=flagpole'], 'Petroleumsinnretning': [], 'Silo': ['man_made=silo'], 'Stolheis': ['aerialway=chairlift'], 'Skitrekk': ['aerialway=draglift'], 'Taubane': ['aerialway=cable_car'], u'Fornøyelsesparkinnretning': ['man_made=tower'], 'Annet': [] } # Namespace ns_gml = 'http://www.opengis.net/gml/3.2' ns_xlink = 'http://www.w3.org/1999/xlink' ns_app = 'http://skjema.geonorge.no/SOSI/produktspesifikasjon/Luftfartshindre/20180322' ns = { 'gml': ns_gml, 'xlink': ns_xlink, 'app': ns_app } # Produce a tag for OSM file # Main program if __name__ == '__main__': start_time = time.time() today = time.strftime("%Y-%m-%d", time.localtime()) # Load county id's and names from Kartverket api file = urllib.request.urlopen("https://ws.geonorge.no/kommuneinfo/v1/fylker") county_data = json.load(file) file.close() county = {} for coun in county_data: county[coun['fylkesnummer']] = coun['fylkesnavn'].strip() county['21'] = "Svalbard" county['00'] = "Norge" # Load obstacle gml from GeoNorge if (len(sys.argv) > 1) and (sys.argv[1] in county): county_id = sys.argv[1] county_name = county[county_id].replace(u"Ø", "O").replace(u"ø", "o").replace(" ", "_") if county_id == "21": county_id = "2100" # Svalbard elif county_id == "00": county_id = "0000" # Norway else: sys.exit ("County code not found. Norway is '00'.") print ("Loading %s..." % county_name) url = "https://nedlasting.geonorge.no/geonorge/Samferdsel/Luftfartshindre/GML/Samferdsel_%s_%s_6173_Luftfartshindre_GML.zip" % (county_id, county_name) in_file = urllib.request.urlopen(url) zip_file = zipfile.ZipFile(BytesIO(in_file.read())) filename = zip_file.namelist()[0] file = zip_file.open(filename) tree = ElementTree.parse(file) file.close() root = tree.getroot() feature_collection = root obstacles = [] # Pass 1: # Find all point obstacles (excluding lines) for feature_member in feature_collection.iter('{%s}featureMember' % ns_gml): vertical_object = feature_member.find('app:VertikalObjekt', ns) if vertical_object != None: xlink = vertical_object.find(u'app:bestårAvVertikalobjKompPunkt', ns) status = vertical_object.find('app:status', ns).text valid_date = vertical_object.find('app:gyldigTil', ns) if (xlink != None) and (status in ["E", "P"]) and ((valid_date == None) or (valid_date.text > today)): xlink_ref = xlink.get('{%s}href' % ns_xlink) update_date = vertical_object.find('app:oppdateringsdato', ns).text[:10] name = vertical_object.find('app:vertikalObjektNavn', ns).text object_id = vertical_object.find('app:identifikasjonObjekt/app:IdentifikasjonObjekt/app:lokalId', ns).text object_type = vertical_object.find('app:vertikalObjektType', ns).text obstacle = { 'status': status, 'date_update': update_date, 'type': object_type, 'name': name, 'ref:hinder': object_id, 'xlink': xlink_ref } create_date = vertical_object.find('app:datafangstdato', ns) if create_date != None: obstacle['date_create'] = create_date.text[:10] if valid_date != None: obstacle['date_valid'] = valid_date.text[:10] obstacles.append(obstacle) # Pass 2: # Find obstacle coordinates print ("Matching coordinates for %i obstacles..." % len(obstacles)) for feature_member in feature_collection.iter('{%s}featureMember' % ns_gml): point = feature_member.find('app:VertikalObjektKomponentPunkt', ns) if point != None: point_id = point.get('{%s}id' % ns_gml) for obstacle in obstacles: if obstacle['xlink'] == point_id: coordinates = point.find('app:posisjon/gml:Point/gml:pos', ns).text coordinates_split = coordinates.split(" ") x = float(coordinates_split[0]) y = float(coordinates_split[1]) z = float(coordinates_split[2]) latitude, longitude = utm.UtmToLatLon(x, y, 33, "N") obstacle['latitude'] = latitude obstacle['longitude'] = longitude height = point.find('app:vertikalUtstrekning', ns) if height != None: height = float(height.text) obstacle['height'] = "%.0f" % height z_ref = point.find('app:href', ns).text top_ele = None if z_ref == "TOP": if height != None: z = z - height else: top_ele = z z = None if z: if z == round(z,0): obstacle['ele'] = "%.0f" % z else: obstacle['ele'] = "%.1f" % z elif top_ele: if top_ele == round(top_ele,0): obstacle['top_ele'] = "%.0f" % top_ele else: obstacle['top_ele'] = "%.1f" % top_ele light = point.find('app:lyssetting', ns).text obstacle['light'] = light break # Pass 3: # Output file filename = "Luftfartshindre_" + county_name + ".osm" print ("Writing file '%s'..." % filename) file_out = open(filename, "w") file_out.write ('<?xml version="1.0" encoding="UTF-8"?>\n') file_out.write ('<osm version="0.6" generator="obstacle2osm v%s">\n' % version) node_id = -1000 for obstacle in obstacles: node_id -= 1 file_out.write (' <node id="%i" lat="%f" lon="%f">\n' % (node_id, obstacle['latitude'], obstacle['longitude'])) name = obstacle['name'] if name == obstacle['ref:hinder']: name = "" elif name == name.upper(): name = name.title() make_osm_line ("ref:hinder", obstacle['ref:hinder']) make_osm_line ("description", name) make_osm_line ("OBSTACLE_TYPE", obstacle['type']) make_osm_line ("STATUS", obstacle['status']) if "height" in obstacle: make_osm_line ("height", obstacle['height']) if "ele" in obstacle: make_osm_line ("ele", obstacle['ele']) elif "top_ele" in obstacle: make_osm_line ("top_ele", obstacle['top_ele']) if not("date_create" in obstacle) or (obstacle['date_update'] != obstacle['date_create']): make_osm_line ("DATE_UPDATE", obstacle['date_update']) if "date_create" in obstacle: make_osm_line ("DATE_CREATE", obstacle['date_create']) if "date_valid" in obstacle: make_osm_line ("end_date", obstacle['date_valid']) # Feature tagging (man_made, tower:type etc) tag_found = False for object_type, tags in iter(tagging_table.items()): if object_type == obstacle['type']: for tag in tags: tag_split = tag.split("=") make_osm_line (tag_split[0], tag_split[1]) tag_found = True break if not(tag_found): print ("Object type '%s' not found in tagging table " % obstacle['type']) # Light tagging light = obstacle['light'] if not(light in ['IL', 'UKJ']): colour = "" character = "" intensity = "" icao_type = "" make_osm_line ("aeroway:light", "obstacle") if light in ['BR','FR','LIA','LIB','MIB','MIC']: colour = "red" elif light in ['BH','FH','MIA','HIA','HIB']: colour = "white" make_osm_line ("aeroway:light:colour", colour) if light in ['FR','FH','LIA','LIB','MIC']: character = "fixed" elif light in ['BR','BH','MIA','MIB','HIA','HIB']: character = "flashing" elif light == "FLO": character = "floodlight" make_osm_line ("aeroway:light:character", character) if light in ['LIA','LIB']: intensity = "low" elif light in ['MIA','MIB','MIC']: intensity = "medium" elif light in ['HIA','HIB']: intensity = "high" make_osm_line ("aeroway:light:intensity", intensity) if light in ['LIA','MIA','HIA']: icao_type = "A" elif light in ['LIB','MIB','HIB']: icao_type = "B" elif light == "HIC": icao_type = "C" make_osm_line ("aeroway:light:icao_type", icao_type) file_out.write (' </node>\n') # Wrap up file_out.write ('</osm>\n') file_out.close() print ("Done in %i seconds" % (time.time() - start_time))	28.456897	152	0.647783	#!/usr/bin/env python3 # -*- coding: utf8 # obstacle2osm # Converts aviation obstacles from Kartverket WFS/GML files for import/update in OSM # Usage: obstacle2.osm [county] # Creates OSM file with name "Luftfartshinder_" + county + ".osm" import html import time import sys import urllib.request import json import zipfile from io import BytesIO from xml.etree import ElementTree import utm # Local library version = "1.0.0" # Tagging per obstacle type tagging_table = { 'Landbruksutstyr': [], 'Telemast': ['man_made=mast', 'tower:type=communication'], 'Bru': ['man_made=tower', 'tower:type=bridge'], 'Bygning': ['building=yes'], 'Gondolbane': ['aerialway=gondola'], u'Kontrolltårn': ['man_made=tower', 'tower:type=airport_control'], u'Kjøletårn': ['man_made=tower', 'tower_type=cooling'], 'Kran': ['man_made=crane'], 'Demning': ['waterway=dam'], 'Kuppel': ['man_made=tower', 'tower:construction=dome'], 'EL_Nettstasjon': ['power=substation', 'power=transformer'], 'Gjerde': ['barrier=fence'], u'Fyrtårn': ['man_made=lighthouse'], 'Monument': ['man_made=tower', 'tower:type=monument'], 'Terrengpunkt': ['natural=peak'], 'Navigasjonshjelpemiddel': ['aeroway=navigationaid'], 'Stolpe': ['man_made=mast'], 'Kraftverk': ['power=plant'], 'Raffineri': ['man_made=tower'], 'Oljerigg': [], 'Skilt': [], 'Pipe': ['man_made=chimney'], 'Tank': ['man_made=storage_tank'], 'Forankret ballong': [], u'Tårn': ['man_made=tower'], 'Kraftledning': [], 'Tre': ['natural=tree'], u'Skogsområde': ['natural=wood'], u'Vanntårn': ['man_made=storage_tank', 'content=water'], u'Vindmølle': ['power=generator', 'generator:source=wind', 'generator:method=wind_turbine', 'generator:type=horizontal_axis'], u'Vindmøllepark': ['type=site', 'power=plant', 'plant:source=wind'], u'Hopptårn': ['man_made=tower', 'piste:type=ski_jump'], u'Vindmåler': ['man_made=mast', 'tower:type=monitoring'], 'Lysmast': ['man_made=mast', 'tower:type=lighting'], 'Flaggstang': ['man_made=flagpole'], 'Petroleumsinnretning': [], 'Silo': ['man_made=silo'], 'Stolheis': ['aerialway=chairlift'], 'Skitrekk': ['aerialway=draglift'], 'Taubane': ['aerialway=cable_car'], u'Fornøyelsesparkinnretning': ['man_made=tower'], 'Annet': [] } # Namespace ns_gml = 'http://www.opengis.net/gml/3.2' ns_xlink = 'http://www.w3.org/1999/xlink' ns_app = 'http://skjema.geonorge.no/SOSI/produktspesifikasjon/Luftfartshindre/20180322' ns = { 'gml': ns_gml, 'xlink': ns_xlink, 'app': ns_app } # Produce a tag for OSM file def make_osm_line(key,value): if value: encoded_value = html.escape(value).strip() file_out.write (' <tag k="%s" v="%s" />\n' % (key, encoded_value)) # Main program if __name__ == '__main__': start_time = time.time() today = time.strftime("%Y-%m-%d", time.localtime()) # Load county id's and names from Kartverket api file = urllib.request.urlopen("https://ws.geonorge.no/kommuneinfo/v1/fylker") county_data = json.load(file) file.close() county = {} for coun in county_data: county[coun['fylkesnummer']] = coun['fylkesnavn'].strip() county['21'] = "Svalbard" county['00'] = "Norge" # Load obstacle gml from GeoNorge if (len(sys.argv) > 1) and (sys.argv[1] in county): county_id = sys.argv[1] county_name = county[county_id].replace(u"Ø", "O").replace(u"ø", "o").replace(" ", "_") if county_id == "21": county_id = "2100" # Svalbard elif county_id == "00": county_id = "0000" # Norway else: sys.exit ("County code not found. Norway is '00'.") print ("Loading %s..." % county_name) url = "https://nedlasting.geonorge.no/geonorge/Samferdsel/Luftfartshindre/GML/Samferdsel_%s_%s_6173_Luftfartshindre_GML.zip" % (county_id, county_name) in_file = urllib.request.urlopen(url) zip_file = zipfile.ZipFile(BytesIO(in_file.read())) filename = zip_file.namelist()[0] file = zip_file.open(filename) tree = ElementTree.parse(file) file.close() root = tree.getroot() feature_collection = root obstacles = [] # Pass 1: # Find all point obstacles (excluding lines) for feature_member in feature_collection.iter('{%s}featureMember' % ns_gml): vertical_object = feature_member.find('app:VertikalObjekt', ns) if vertical_object != None: xlink = vertical_object.find(u'app:bestårAvVertikalobjKompPunkt', ns) status = vertical_object.find('app:status', ns).text valid_date = vertical_object.find('app:gyldigTil', ns) if (xlink != None) and (status in ["E", "P"]) and ((valid_date == None) or (valid_date.text > today)): xlink_ref = xlink.get('{%s}href' % ns_xlink) update_date = vertical_object.find('app:oppdateringsdato', ns).text[:10] name = vertical_object.find('app:vertikalObjektNavn', ns).text object_id = vertical_object.find('app:identifikasjonObjekt/app:IdentifikasjonObjekt/app:lokalId', ns).text object_type = vertical_object.find('app:vertikalObjektType', ns).text obstacle = { 'status': status, 'date_update': update_date, 'type': object_type, 'name': name, 'ref:hinder': object_id, 'xlink': xlink_ref } create_date = vertical_object.find('app:datafangstdato', ns) if create_date != None: obstacle['date_create'] = create_date.text[:10] if valid_date != None: obstacle['date_valid'] = valid_date.text[:10] obstacles.append(obstacle) # Pass 2: # Find obstacle coordinates print ("Matching coordinates for %i obstacles..." % len(obstacles)) for feature_member in feature_collection.iter('{%s}featureMember' % ns_gml): point = feature_member.find('app:VertikalObjektKomponentPunkt', ns) if point != None: point_id = point.get('{%s}id' % ns_gml) for obstacle in obstacles: if obstacle['xlink'] == point_id: coordinates = point.find('app:posisjon/gml:Point/gml:pos', ns).text coordinates_split = coordinates.split(" ") x = float(coordinates_split[0]) y = float(coordinates_split[1]) z = float(coordinates_split[2]) latitude, longitude = utm.UtmToLatLon(x, y, 33, "N") obstacle['latitude'] = latitude obstacle['longitude'] = longitude height = point.find('app:vertikalUtstrekning', ns) if height != None: height = float(height.text) obstacle['height'] = "%.0f" % height z_ref = point.find('app:href', ns).text top_ele = None if z_ref == "TOP": if height != None: z = z - height else: top_ele = z z = None if z: if z == round(z,0): obstacle['ele'] = "%.0f" % z else: obstacle['ele'] = "%.1f" % z elif top_ele: if top_ele == round(top_ele,0): obstacle['top_ele'] = "%.0f" % top_ele else: obstacle['top_ele'] = "%.1f" % top_ele light = point.find('app:lyssetting', ns).text obstacle['light'] = light break # Pass 3: # Output file filename = "Luftfartshindre_" + county_name + ".osm" print ("Writing file '%s'..." % filename) file_out = open(filename, "w") file_out.write ('<?xml version="1.0" encoding="UTF-8"?>\n') file_out.write ('<osm version="0.6" generator="obstacle2osm v%s">\n' % version) node_id = -1000 for obstacle in obstacles: node_id -= 1 file_out.write (' <node id="%i" lat="%f" lon="%f">\n' % (node_id, obstacle['latitude'], obstacle['longitude'])) name = obstacle['name'] if name == obstacle['ref:hinder']: name = "" elif name == name.upper(): name = name.title() make_osm_line ("ref:hinder", obstacle['ref:hinder']) make_osm_line ("description", name) make_osm_line ("OBSTACLE_TYPE", obstacle['type']) make_osm_line ("STATUS", obstacle['status']) if "height" in obstacle: make_osm_line ("height", obstacle['height']) if "ele" in obstacle: make_osm_line ("ele", obstacle['ele']) elif "top_ele" in obstacle: make_osm_line ("top_ele", obstacle['top_ele']) if not("date_create" in obstacle) or (obstacle['date_update'] != obstacle['date_create']): make_osm_line ("DATE_UPDATE", obstacle['date_update']) if "date_create" in obstacle: make_osm_line ("DATE_CREATE", obstacle['date_create']) if "date_valid" in obstacle: make_osm_line ("end_date", obstacle['date_valid']) # Feature tagging (man_made, tower:type etc) tag_found = False for object_type, tags in iter(tagging_table.items()): if object_type == obstacle['type']: for tag in tags: tag_split = tag.split("=") make_osm_line (tag_split[0], tag_split[1]) tag_found = True break if not(tag_found): print ("Object type '%s' not found in tagging table " % obstacle['type']) # Light tagging light = obstacle['light'] if not(light in ['IL', 'UKJ']): colour = "" character = "" intensity = "" icao_type = "" make_osm_line ("aeroway:light", "obstacle") if light in ['BR','FR','LIA','LIB','MIB','MIC']: colour = "red" elif light in ['BH','FH','MIA','HIA','HIB']: colour = "white" make_osm_line ("aeroway:light:colour", colour) if light in ['FR','FH','LIA','LIB','MIC']: character = "fixed" elif light in ['BR','BH','MIA','MIB','HIA','HIB']: character = "flashing" elif light == "FLO": character = "floodlight" make_osm_line ("aeroway:light:character", character) if light in ['LIA','LIB']: intensity = "low" elif light in ['MIA','MIB','MIC']: intensity = "medium" elif light in ['HIA','HIB']: intensity = "high" make_osm_line ("aeroway:light:intensity", intensity) if light in ['LIA','MIA','HIA']: icao_type = "A" elif light in ['LIB','MIB','HIB']: icao_type = "B" elif light == "HIC": icao_type = "C" make_osm_line ("aeroway:light:icao_type", icao_type) file_out.write (' </node>\n') # Wrap up file_out.write ('</osm>\n') file_out.close() print ("Done in %i seconds" % (time.time() - start_time))	136	0	23
5c9603f2e0ac2abb46a8160361bd4405030226f9	377	py	Python	calibrate.py	etanzapinsky/voyeur	0b8e6b212dec93a9fee0bbf45e639d63c691cea9	[ "MIT" ]	null	null	null	calibrate.py	etanzapinsky/voyeur	0b8e6b212dec93a9fee0bbf45e639d63c691cea9	[ "MIT" ]	null	null	null	calibrate.py	etanzapinsky/voyeur	0b8e6b212dec93a9fee0bbf45e639d63c691cea9	[ "MIT" ]	null	null	null	import time from blinds import Blinds, NEUTRAL, UP, DOWN # janky way to calibrate blinds to be open/closed to the right amount # edit this file to change UP/DOWN to move blinds in desired direction, # save and then run if __name__ == '__main__': main()	22.176471	71	0.708223	import time from blinds import Blinds, NEUTRAL, UP, DOWN # janky way to calibrate blinds to be open/closed to the right amount # edit this file to change UP/DOWN to move blinds in desired direction, # save and then run def main(): blinds = Blinds() blinds.run_servo(NEUTRAL + UP) time.sleep(1) blinds.run_servo(NEUTRAL) if __name__ == '__main__': main()	95	0	22
d3c9aa8d47bb2a5146cb0aeb909d6c72c15066cf	5,018	py	Python	test/test_compiler.py	timothyrenner/svl	a74c09c49f2e14046acd4b0eeb861f8fef6bca96	[ "MIT" ]	8	2019-03-27T12:49:21.000Z	2020-10-10T11:16:25.000Z	test/test_compiler.py	timothyrenner/svl	a74c09c49f2e14046acd4b0eeb861f8fef6bca96	[ "MIT" ]	65	2018-08-26T14:48:45.000Z	2020-03-17T12:24:42.000Z	test/test_compiler.py	timothyrenner/svl	a74c09c49f2e14046acd4b0eeb861f8fef6bca96	[ "MIT" ]	1	2019-09-13T19:39:07.000Z	2019-09-13T19:39:07.000Z	import pytest import os from jinja2 import Environment, BaseLoader from svl.compiler.compiler import _extract_additional_datasets, svl from svl.compiler.errors import ( SvlSyntaxError, SvlMissingFileError, SvlPlotError, SvlDataLoadError, SvlDataProcessingError, ) CURRENT_DIR = os.path.dirname(os.path.abspath(__file__)) JINJA_ENV = Environment(loader=BaseLoader) @pytest.fixture def svl_source(): """ Self cleaning fixture for rendering an SVL script template into a file to be called from a subprocess. Returns a factory that produces rendered template locations and also renders the template. """ svl_script_template = JINJA_ENV.from_string( """ DATASETS bigfoot "{{ test_dir }}/test_datasets/bigfoot_sightings.csv" HISTOGRAM bigfoot X temperature_mid BINS 25 """ ) return svl_script_template.render(test_dir=CURRENT_DIR) def test_extract_additional_datasets(): """ Tests that the _extract_additional_datasets function returns the correct value. """ datasets = ["bigfoot=datasets/bigfoot.csv", "dogman=datasets/dogman.csv"] truth = { "bigfoot": "datasets/bigfoot.csv", "dogman": "datasets/dogman.csv", } answer = _extract_additional_datasets(datasets) assert truth == answer def test_svl(svl_source): """ Tests that the svl function works when the script is correct. """ svl(svl_source) def test_svl_datasets(svl_source): """ Tests that the svl function works when additional datasets are specified. """ svl( svl_source, datasets=[ "bigfoot={}/test_datasets/bigfoot_sightings.csv".format( CURRENT_DIR ) ], ) def test_svl_debug(svl_source): """ Tests that the svl function works when the debug option is specified. """ answer = svl(svl_source, debug=True) assert "<" not in answer def test_svl_offline_js(svl_source): """ Tests that the svl function works when the offline_js option is specified. """ svl(svl_source, offline_js=True) def test_svl_dataset_error(svl_source): """ Tests that the svl function raises a ValueError when the additional datasets are incorrectly specified. """ with pytest.raises(ValueError, match="name=path"): svl( svl_source, datasets=[ "bigfoot:{}/test_datasets/bigfoot_sightings.csv".format( CURRENT_DIR ) ], ) def test_svl_syntax_error(svl_source): """ Tests that the svl function raises a SvlSyntaxError when there is a syntax error in the source. """ svl_source = """{} LINE bigfoot X X date BY YEAR Y report_number COUNT """.format( svl_source ) with pytest.raises(SvlSyntaxError, match="Syntax error"): svl(svl_source) def test_svl_missing_file_error(svl_source): """ Tests that the svl function raises a SvlMissingFileError when there is a missing file. """ with pytest.raises(SvlMissingFileError, match="File"): svl(svl_source, datasets=["ufos={}/test_datasets/ufo_sightings.csv"]) def test_svl_plot_error(svl_source): """ Tests that the svl function raises a SvlPlotError when there is an error in a plot specification. """ svl_source = """{} LINE bigfoot X date BY YEAR TITLE "Annual Bigfoot Sightings" """.format( svl_source ) with pytest.raises(SvlPlotError, match="Plot error:"): svl(svl_source) def test_svl_data_load_error(): """ Tests that the svl function raises a SvlDataLoadError when there's an incorrectly specified SQL dataset. """ svl_source = """ DATASETS bigfoot "{}/test_datasets/bigfoot_sightings.csv" bigfoot_failure SQL "SELECT date FROM bigfoots" HISTOGRAM bigfoot X temperature_mid BINS 25 """.format( CURRENT_DIR ) with pytest.raises(SvlDataLoadError, match="Error loading data"): svl(svl_source) def test_svl_data_processing_error(): """ Tests that the svl function raises a SvlDataProcessingError when there is an incorrectly specified custom SQL statement in the plot. """ svl_source = """ DATASETS bigfoot "{}/test_datasets/bigfoot_sightings.csv" LINE bigfoot X date by year label "year" Y date count label "number of sightings" SPLIT BY classification FILTER "daet > 1990-01-01" """.format( CURRENT_DIR ) with pytest.raises( SvlDataProcessingError, match="Error processing plot data" ): svl(svl_source) def test_svl_not_implemented_error(svl_source): """ Tests that the svl function raises a NotImplementedError when the selected backend has not been implemented. """ with pytest.raises(NotImplementedError, match="Unable to use"): svl(svl_source, backend="vega")	27.723757	78	0.66381	import pytest import os from jinja2 import Environment, BaseLoader from svl.compiler.compiler import _extract_additional_datasets, svl from svl.compiler.errors import ( SvlSyntaxError, SvlMissingFileError, SvlPlotError, SvlDataLoadError, SvlDataProcessingError, ) CURRENT_DIR = os.path.dirname(os.path.abspath(__file__)) JINJA_ENV = Environment(loader=BaseLoader) @pytest.fixture def svl_source(): """ Self cleaning fixture for rendering an SVL script template into a file to be called from a subprocess. Returns a factory that produces rendered template locations and also renders the template. """ svl_script_template = JINJA_ENV.from_string( """ DATASETS bigfoot "{{ test_dir }}/test_datasets/bigfoot_sightings.csv" HISTOGRAM bigfoot X temperature_mid BINS 25 """ ) return svl_script_template.render(test_dir=CURRENT_DIR) def test_extract_additional_datasets(): """ Tests that the _extract_additional_datasets function returns the correct value. """ datasets = ["bigfoot=datasets/bigfoot.csv", "dogman=datasets/dogman.csv"] truth = { "bigfoot": "datasets/bigfoot.csv", "dogman": "datasets/dogman.csv", } answer = _extract_additional_datasets(datasets) assert truth == answer def test_svl(svl_source): """ Tests that the svl function works when the script is correct. """ svl(svl_source) def test_svl_datasets(svl_source): """ Tests that the svl function works when additional datasets are specified. """ svl( svl_source, datasets=[ "bigfoot={}/test_datasets/bigfoot_sightings.csv".format( CURRENT_DIR ) ], ) def test_svl_debug(svl_source): """ Tests that the svl function works when the debug option is specified. """ answer = svl(svl_source, debug=True) assert "<" not in answer def test_svl_offline_js(svl_source): """ Tests that the svl function works when the offline_js option is specified. """ svl(svl_source, offline_js=True) def test_svl_dataset_error(svl_source): """ Tests that the svl function raises a ValueError when the additional datasets are incorrectly specified. """ with pytest.raises(ValueError, match="name=path"): svl( svl_source, datasets=[ "bigfoot:{}/test_datasets/bigfoot_sightings.csv".format( CURRENT_DIR ) ], ) def test_svl_syntax_error(svl_source): """ Tests that the svl function raises a SvlSyntaxError when there is a syntax error in the source. """ svl_source = """{} LINE bigfoot X X date BY YEAR Y report_number COUNT """.format( svl_source ) with pytest.raises(SvlSyntaxError, match="Syntax error"): svl(svl_source) def test_svl_missing_file_error(svl_source): """ Tests that the svl function raises a SvlMissingFileError when there is a missing file. """ with pytest.raises(SvlMissingFileError, match="File"): svl(svl_source, datasets=["ufos={}/test_datasets/ufo_sightings.csv"]) def test_svl_plot_error(svl_source): """ Tests that the svl function raises a SvlPlotError when there is an error in a plot specification. """ svl_source = """{} LINE bigfoot X date BY YEAR TITLE "Annual Bigfoot Sightings" """.format( svl_source ) with pytest.raises(SvlPlotError, match="Plot error:"): svl(svl_source) def test_svl_data_load_error(): """ Tests that the svl function raises a SvlDataLoadError when there's an incorrectly specified SQL dataset. """ svl_source = """ DATASETS bigfoot "{}/test_datasets/bigfoot_sightings.csv" bigfoot_failure SQL "SELECT date FROM bigfoots" HISTOGRAM bigfoot X temperature_mid BINS 25 """.format( CURRENT_DIR ) with pytest.raises(SvlDataLoadError, match="Error loading data"): svl(svl_source) def test_svl_data_processing_error(): """ Tests that the svl function raises a SvlDataProcessingError when there is an incorrectly specified custom SQL statement in the plot. """ svl_source = """ DATASETS bigfoot "{}/test_datasets/bigfoot_sightings.csv" LINE bigfoot X date by year label "year" Y date count label "number of sightings" SPLIT BY classification FILTER "daet > 1990-01-01" """.format( CURRENT_DIR ) with pytest.raises( SvlDataProcessingError, match="Error processing plot data" ): svl(svl_source) def test_svl_not_implemented_error(svl_source): """ Tests that the svl function raises a NotImplementedError when the selected backend has not been implemented. """ with pytest.raises(NotImplementedError, match="Unable to use"): svl(svl_source, backend="vega")	0	0	0
7dd6e58903392a293ee7778d9cdc919d3feae0dc	285	py	Python	djaveAPI/views/docs.py	dasmith2/djaveAPI	6cece89bb945a4c8ace1534cc007626a35af3c38	[ "MIT" ]	null	null	null	djaveAPI/views/docs.py	dasmith2/djaveAPI	6cece89bb945a4c8ace1534cc007626a35af3c38	[ "MIT" ]	null	null	null	djaveAPI/views/docs.py	dasmith2/djaveAPI	6cece89bb945a4c8ace1534cc007626a35af3c38	[ "MIT" ]	null	null	null	from djaveAPI.docs import docs from djaveURL import protocol_and_host	25.909091	53	0.8	from djaveAPI.docs import docs from djaveURL import protocol_and_host def api_doc_contents(request, model_names): api_root_url = protocol_and_host(request) model_docs = [] for model_name in model_names: model_docs.append(docs(model_name, api_root_url)) return model_docs	191	0	23
3e23295719475515500986c03f81d532318e434d	7,978	py	Python	utils/data_utils.py	Ailln/stock-prediction	9de77de5047446ffceeed83cb610c7edd2cb1ad3	[ "MIT" ]	11	2020-07-11T06:14:29.000Z	2021-12-02T08:48:53.000Z	utils/data_utils.py	HaveTwoBrush/stock-prediction	9de77de5047446ffceeed83cb610c7edd2cb1ad3	[ "MIT" ]	null	null	null	utils/data_utils.py	HaveTwoBrush/stock-prediction	9de77de5047446ffceeed83cb610c7edd2cb1ad3	[ "MIT" ]	8	2020-04-15T14:29:47.000Z	2021-12-19T09:26:53.000Z	from pathlib import Path import numpy as np import pandas as pd from pylab import plt from progressbar import ProgressBar from models import sklearn_model	37.455399	108	0.633116	from pathlib import Path import numpy as np import pandas as pd from pylab import plt from progressbar import ProgressBar from models import sklearn_model class DataUtils(object): def __init__(self, config): self.config = config self.origin_train_path = Path(self.config["datas"]["origin_train_path"]) self.origin_test_path = Path(self.config["datas"]["origin_test_path"]) self.generate_train_path = Path(self.config["datas"]["generate_train_path"]) self.generate_validate_path = Path(self.config["datas"]["generate_validate_path"]) self.generate_test_path = Path(self.config["datas"]["generate_test_path"]) self.is_regenerate_train_data = self.config["datas"]["is_regenerate_train_data"] self.split_validate_size = self.config["datas"]["split_validate_size"] self.is_regenerate_test_data = self.config["datas"]["is_regenerate_test_data"] self.is_debug = self.config["is_debug"] self.is_std = self.config["is_std"] self.is_ntl = self.config["is_ntl"] self.is_remove_extreme = self.config["is_remove_extreme"] self.is_plot = 0 self.progress = ProgressBar() def get_train_data(self): if self.is_regenerate_train_data: df_train_data = self.__generate_train_data() else: df_train_data = pd.read_csv(self.generate_train_path) if self.is_debug: print(f"\n>> train df head:\n\n{df_train_data.head()}") train_header_list = list(df_train_data.columns) train_remove_key_list = ["id", "date", "y"] for remove_key in train_remove_key_list: train_header_list.remove(remove_key) train_input_list = df_train_data[train_header_list].values train_target_list = df_train_data["y"].values return train_input_list, train_target_list def get_test_data(self): if self.is_regenerate_test_data: df_test_data = self.__generate_test_data() else: df_test_data = pd.read_csv(self.generate_test_path) if self.is_debug: print(f"\n>> test df head:\n\n{df_test_data.head()}") df_test_data = df_test_data.fillna(0) test_header_list = list(df_test_data.columns) train_remove_key_list = ["date", "id"] for remove_key in train_remove_key_list: if remove_key in test_header_list: test_header_list.remove(remove_key) test_input_list = df_test_data[test_header_list].values test_id_list = df_test_data["id"].values test_date_list = df_test_data["date"].values return test_input_list, test_id_list, test_date_list def __generate_train_data(self): sorted_train_path = sorted(self.origin_train_path.glob("")) sorted_train_len = len(sorted_train_path) print(f">> all data length: {sorted_train_len}") if self.is_debug: sorted_train_path = sorted_train_path[:10] df_train_data = pd.DataFrame() for index, date_path in enumerate(self.progress(sorted_train_path)): df_train_data = pd.concat([df_train_data, self.__merge_date_data(date_path)], ignore_index=True) print(">> generate all train data success !") if not self.is_debug: df_train_data.to_csv(self.generate_train_path, index=False) print(">> save all data to /datas folder.") return df_train_data def __generate_test_data(self): df_test_data = pd.DataFrame() test_path_list = list(self.origin_test_path.glob("")) for date_path in self.progress(test_path_list): df_test_data = pd.concat([df_test_data, self.__merge_date_data(date_path, "test")], sort=False) print(">> save all data to /datas folder.") df_test_data.to_csv(self.generate_test_path) print(">> generate test data success !") return df_test_data def __merge_date_data(self, date_path, data_type=None): df_non_ts = pd.read_csv(date_path / "non_ts.csv", index_col="id") if self.is_remove_extreme: df_non_ts = self.remove_extreme_value(df_non_ts) if self.is_ntl: df_non_ts = self.neutralization(df_non_ts) if self.is_std: df_non_ts = self.standardization(df_non_ts) if data_type == "test": merge_df = df_non_ts else: df_y = pd.read_csv(date_path / "y.csv") del df_y["date"] merge_df = pd.merge(df_non_ts, df_y, on="id") for ts_path in date_path.glob("ts_.csv"): ts_name = ts_path.name.split(".csv")[0] df_ts = pd.read_csv(ts_path, index_col="id") date = df_ts["date"] del df_ts["date"] if self.is_remove_extreme: df_ts = self.remove_extreme_value(df_ts) if self.is_std: df_ts = self.standardization(df_ts) df_ts_std = self.__get_std(df_ts, ts_name) merge_df = pd.merge(merge_df, df_ts_std, on="id") df_ts_mean_0_5 = self.__get_mean_0_5(df_ts, ts_name) merge_df = pd.merge(merge_df, df_ts_mean_0_5, on="id") df_ts_mean_0_20 = self.__get_mean_0_20(df_ts, ts_name) merge_df = pd.merge(merge_df, df_ts_mean_0_20, on="id") merge_df["date"] = date return merge_df @staticmethod def __get_std(df_input, index_name): df_output = df_input.T[1:].std().to_frame(name=index_name+"_std") return df_output @staticmethod def __get_mean_0_5(df_input, index_name): df_output = df_input.T[1:7].mean().to_frame(name=index_name+"_mean_0_5") return df_output @staticmethod def __get_mean_0_20(df_input, index_name): df_output = df_input.T[1:22].mean().to_frame(name=index_name+"_mean_0_20") return df_output def remove_extreme_value(self, df_input): if self.is_plot: del df_input["date"] del df_input["flag"] fig, (ax0, ax1) = plt.subplots(2, 1, sharey="all") ax0.set_title('BEFORE /20130201/non_ts.csv remove extreme value') df_input.plot(ax=ax0) desc = df_input.describe() mean_add_3std = desc.loc['mean'] + desc.loc['std'] 3 mean_minus_3std = desc.loc['mean'] - desc.loc['std'] * 3 df_input = df_input.where(df_input < mean_add_3std, mean_add_3std, axis=1) df_input = df_input.where(df_input > mean_minus_3std, mean_minus_3std, axis=1) ax1.set_title('AFTER /20130201/non_ts.csv remove extreme value') df_input.plot(ax=ax1) plt.show() else: desc = df_input.describe() mean_add_3std = desc.loc['mean'] + desc.loc['std'] * 3 mean_minus_3std = desc.loc['mean'] - desc.loc['std'] * 3 df_input = df_input.where(df_input < mean_add_3std, mean_add_3std, axis=1) df_input = df_input.where(df_input > mean_minus_3std, mean_minus_3std, axis=1) return df_input # 标准化 @staticmethod def standardization(df_input): df_input = df_input.apply(lambda x: (x - np.min(x)) / (np.max(x) - np.min(x))) df_input = df_input.fillna(0) return df_input # 中性化 @staticmethod def neutralization(df_input): flag_values = [[v] for v in df_input["flag"].values] cols = list(df_input.columns) model = sklearn_model.Model() skm = model.sklearn_model("LinearRegression") cols.remove("date") cols.remove("flag") for col in cols: col_values = [[v] for v in df_input[col].values] skm.fit(flag_values, col_values) col_preds = skm.predict(flag_values) res = [] for x, y in zip(col_values, col_preds): res.append(x[0] - y[0]) df_input[col] = res return df_input	7,361	448	23
a2fa74364a6125d4e4765053cb76ca93208691d6	17,331	py	Python	rules/dr_default.py	00-ab/willows	14754329451b5a11a2ea626ecf939014c2bf4cac	[ "Unlicense" ]	null	null	null	rules/dr_default.py	00-ab/willows	14754329451b5a11a2ea626ecf939014c2bf4cac	[ "Unlicense" ]	null	null	null	rules/dr_default.py	00-ab/willows	14754329451b5a11a2ea626ecf939014c2bf4cac	[ "Unlicense" ]	null	null	null	from __future__ import print_function import math import copy import json dancer = { verbs : {} adjs: {} } # dancer describes the state of a conscious being # relation describes the feeling of one regarding another dancer["adjs"]["lust"] dancer["adjs"]["like"] # define the archetypal relations dancer["relation"]["arch"] = { "lust" : 0, "like" : 0, "respect" : 0, } # define the dancer's abilities ## API: # MODULE SETTINGS: # These values used to calibrate action effects. SMALL_MULTIPLIER = 0.1 MEDIUM_MULTIPLIER = 0.2 LARGE_MULTIPLIER = 0.4 # Key bindings. These are inserted into the game object during _setup_player. keyDict = { "y" : "touch", "t" : "evade", "r" : "jest", "f" : "retreat", "g" : "breathe", "h" : "advance" } # Lists -- these are to be used by the client. # (Mainly so display functions can be dynamic.) # My dance_display.py should work for any moveList that is a list of strings # and any statList that is a list of strings # or a list of lists which contain only strings. # BUT: moveList + statList MUST == the keys of p in _setup_player (-'choice') # (I know that's ugly, sorry.) moveList = [ 'advance', 'retreat', 'touch', 'evade', 'breathe', 'jest' ] statList = [ ['earth', 'will'], ['air', 'calm'], ['fire', 'heat'], ['water', 'balance'] ] playerList = ['0', '1'] # These are some special exceptions. # Probably not necessary. ## BACKEND: # UTILITY FUNCTIONS # These are totally useless ;) # SMALL # MED # LARGE def _setup_player( e0, a0, f0, w0): """ Accepts initial values for eafw, returns a complete player object. """ heat = f0/2 if f0%2 == 1: heat += 1 p = { 'earth' : float(e0), 'will' : float(e0), 'air' : float(a0), 'calm' : float(a0), 'fire' : float(f0), 'heat' :float(heat), 'water' : float(w0), 'balance' : -1.0, 'choice' : None, 'advance' : 1, 'retreat' : 1, 'touch' : 1, 'evade' : 1, 'breathe' : 1, 'jest' : 1 } p.update( keyDict ) return p def _execute( player, choice, game_data0, game_data1 ): """ Reads from gd0 and writes to gd1, according to the move with the same name as the player's choice. """ # In theory, neither of the below exceptions should ever be raised # since the client-side function should test both conditions # before calling a new turn. # First check to see if the move exists. if choice in moveList: pass else: raise NoSuchMove # Second check to see if the move is currently allowed. if game_data0[ str(player) ][ str(choice) ] == 1: pass else: raise IllegalMove # Then perform the move. if player == 0: other = 1 else: other = 0 move = execList[ choice ] game_data1 = move( str(player), str(other), game_data0, game_data1) # Finally, return the modified object. return game_data1 def _val_in( val_0, magnitude ): """ Returns magnitude with the sign such that abs(val_0 + mag2) < abs(val_0) If mag < 0, does the opposite. If abs(mag) > 1, may result in an overshoot. """ if val_0 < 0: pass elif val_0 > 0: magnitude = -magnitude else: # Because one cannot draw closer to 0 if one is already there: if magnitude > 0: magnitude = 0 # And since we don't want d to be always negative: else: magnitude = -magnitude return magnitude def _gameover_check( game_data ): """ Checks to see if gameover should be declared. This function defines the encounter-end conditions. (Maybe it should take some cues from ## MODULE SETTINGS ?) """ if game_data["0"]["will"] <= 0 and game_data["1"]["will"] <= 0: game_data['game']['gameover'] = 1 game_data['game']['gameover_message'] = ( 'SimultaneousExhaustion' ) else: for p in range( 0, 1 ): if game_data[ str(p) ]['will'] <= 0: game_data['game']['gameover'] = 1 game_data['game']['gameover_message'] = ( 'Player ' + str(p) + ' exhaustion.' ) # VERBS SECTION # This section should include callable functions for each move. # Each move must accept actor, target, and distance arguments. # All functions in this section accept a bin for actor or target. # They read only from game_0 and write only to game_1, # returning game_1 def _advance( actor, target, game_0, game_1): """ Signifies a closening, with or without physical contact. A bold statement, a step forward, or a glorious charge. Costs calm; reduces balance. """ # This part is the cost. It will always be the same. game_1[actor]['calm'] -= _small( game_0[actor]["heat"] ) # Advancing does not increase one's balance # if one pushes against the target. # (Though frict may change balance.) if not ( game_0['game']['d'] == 0 and _get_future_d( game_0 ) ): game_1[actor]['balance'] += 1 # If the future distance is 0, a collision occurs. # (As long as the target did not evade.) if _get_future_d( game_0 ) == 0 and game_0[target]['choice'] != 'evade': game_1 = _frict( actor, target, game_0, game_1 ) # If the two players are already grappling, # (ie in the same space, at d=0) # they cannot advance past each other. # Otherwise, the distance will decrease. # (If they are at d1, they will switch positions.) game_1['game']['d'] += _val_in( game_0['game']['d'], 1 ) return game_1 def _retreat( actor, target, game_0, game_1): """ Signifies a distancing, a retreat, a coldness a disreply, a shyness, a step back, or a flight. Costs calm; reduces balance. """ # Reduce calm by small game_1[actor]['calm'] -= _small( game_0[actor]["heat"] ) # Decrease balance by small game_1[actor]['balance'] -= 1 # Open distance by 1 if game_0[target]['choice'] == 'advance' and game_0['game']['d'] == 0: pass else: game_1['game']['d'] += _val_in( game_0['game']['d'], -1 ) return game_1 def _touch( actor, target, game_0, game_1): """ Signifies phsyical contact. A brush, caress, strike, grope, or attempt. """ # This is the cost game_1[actor]['calm'] -= _med( game_0[actor]['heat'] ) # Check to see if the move connects. if abs( _get_future_d( game_0 ) ) <= 1 and game_0[target]['choice'] != 'evade': # Below is a somewhat silly way of saying # that a successful touch is like a frict, # but only affecting the target. save = copy.deepcopy( game_1[actor] ) _frict( actor, target, game_0, game_1 ) game_1[actor] = copy.deepcopy( save ) return game_1 def _evade( actor, target, game_0, game_1): """ A sort of dodge or refusal. Counteracts the effect of a touch or advance. Rather embarassing against a tease. Technically does nothing. Other acts may define exceptions for: if game_0[target]['choice'] == 'evade': """ if _frict_occurs( game_0 ): # In this case, _frict_occurs() is _if_frict_would_occur() # If successful, restores calm. # (Since you look so cool.) game_1[actor]['calm'] += _small( game_0[actor]['air'] ) else: # Otherwise, costs a fair bit. game_1[actor]['calm'] -= _med( game_0[actor]['heat'] ) return game_1 def _breathe( actor, target, game_0, game_1): """ A moment of rest, contemplation, and gathering. Could signify literal breathing, but also meditation or inaction. (Totally restores calm. Slightly reduces heat and restores will.) """ # See above. if not _frict_occurs( game_0 ): game_1[actor]['calm'] = game_0[actor]['air'] game_1[actor]['heat'] -= _small( game_0[actor]['air'] ) game_1[actor]['will'] += _small( game_0[actor]['air'] ) # Closes balance by one. game_1[actor]['balance'] += _val_in( game_1[actor]['balance'], 1 ) # However: breathe is interrupted by a frict. # You'll still get some breath back, but receive no other bonuses. else: game_1[actor]['calm'] += _large( game_0[actor]['air'] ) return game_1 def _jest( actor, target, game_0, game_1): """ A joke or strangeness, encouraging advance and curiosity by inspiring a passion -- for example anger or desire. (Adds heat and negative balance -- more effective if the target is retreating or evading.) """ game_1[actor]['calm'] -= _small( game_0[actor]['heat'] ) if not game_0[target]['choice'] == 'breathe': game_1[target]['heat'] += _small( game_0[actor]['heat'] ) # By reducing balance, tease can force the target to advance or suffer in fricts # It is less useful if the player is already forward-balanced. game_1[target]['balance'] -= 1 if game_0[target]['choice'] == 'retreat' or game_0[target]['choice'] == 'evade': game_1[target]['heat'] += _med( game_0[actor]['heat'] ) return game_1 def _frict( actor, target, game_0, game_1): """ Represents a kind of clash, collision, or rubbing-together. Depends on balances. """ # Both players receive heat. The one with less receives more. game_1[target]['heat'] += _small( game_0[actor]['fire']) game_1[actor]['heat'] += _small( game_0[target]['fire']) if game_0[actor]['heat'] > game_0[target]['heat']: game_1[target]['heat'] += _small( game_0[actor]['heat'] ) elif game_0[actor]['heat'] < game_0[target]['heat']: game_1[actor]['heat'] += _small( game_0[target]['heat'] ) else: game_1[target]['heat'] += _small( game_0[actor]['heat'] ) game_1[actor]['heat'] += _small( game_0[target]['heat'] ) # If one player's will is less than 25% of the other's # that player will be pushed back. if game_0[actor]['will'] > 4 * game_0[target]['will']: game_1[target]['balance'] -= 1 elif 4 * game_0[actor]['will'] < game_0[target]['will']: game_1[actor]['balance'] -= 1 # Adds heat to each player, giving the advantage to the player # whose absolute balance is the smaller percent of their water. # (So if p0.bal = 1/10 and p1.bal = -1/11, then p1 will have the advantage.) a_bal = float( abs(game_0[actor]['balance'] )) / game_0[actor]['water'] t_bal = float( abs(game_0[target]['balance'] )) / game_0[target]['water'] if a_bal == t_bal: game_1[actor]['heat'] += _med( game_0[target]['heat'] ) game_1[target]['heat'] += _med( game_0[actor]['heat'] ) elif a_bal > t_bal: game_1[actor]['heat'] += _large( game_0[target]['heat'] ) game_1[target]['heat'] += _small( game_0[actor]['heat'] ) elif a_bal < t_bal: game_1[actor]['heat'] += _small( game_0[target]['heat'] ) game_1[target]['heat'] += _large( game_0[actor]['heat'] ) else: print( "I think this is impossible, right?" ) return game_1 def _get_future_d( game_0 ): """ This somewhat kludgy function calculates the future distance based on the present distance and the player choices. Used in collision detection. """ d = game_0['game']['d'] if d == 0 and ( game_0['0']['choice'] == 'advance' or game_0['1']['choice'] == 'advance' ): pass else: for p in range( 2 ): choice = game_0[str(p)]['choice'] if choice == 'advance': d -= math.copysign(1, d) elif choice == 'retreat': d += math.copysign(1, d) else: pass d = int(d) return d # The below is used by _execute() to link strings with actions. # This is a little silly, but I don't know a better way. # (For some reason, this list can't be written until after the functions it contains. # Fuck you, Python.) execList = { "advance" : _advance, "retreat" : _retreat, "touch" : _touch, "evade" : _evade, "breathe" : _breathe, "jest" : _jest } # ADJECTIVES SECTION # This section should include rules for checking and correcting element statuses. def _earth_check( game_data ): """ Without will, an individual is unable to continue. """ for p in range(2): if game_data[str(p)]['will'] > game_data[str(p)]['earth']: game_data[str(p)]['will'] = game_data[str(p)]['earth'] if game_data['0']['will'] <= 0 and game_data['1']['will'] <= 0: game_data['game']['gameover'] = 1 game_data['game']['gameover_message'] = 2 else: for p in range( 2 ): if game_data[str(p)]['will'] <= 0: game_data['game']['gameover'] = 1 game_data['game']['gameover_message'] = p return game_data def _air_check( game_data ): """ Below-min breath is called exhaustion. Knowing when to breathe is important. """ for p in range( 2 ): c = game_data[str(p)]['calm'] # Punish will if calm is below zero if c < 0: game_data[str(p)]['calm'] = 0 game_data[str(p)]['will'] += c # Treat Air as maximum Calm if c > game_data[str(p)]['air']: game_data[str(p)]['calm'] = game_data[str(p)]['air'] return game_data def _fire_check( game_data ): """ Above-max heat is called mania, while below-min heat is called depression. High heat will power-up some moves, but it is risky. """ for p in range(2): h = game_data[str(p)]['heat'] f = game_data[str(p)]['fire'] if h < 0: game_data[str(p)]['heat'] = 0 game_data[str(p)]['will'] += h if h > f: game_data[str(p)]['heat'] = f game_data[str(p)]['will'] -= ( h - f ) return game_data def _water_check( game_data ): """ Balance is not a magnitude, but a distance from zero. Zero represents perfect balance, while the positive represents forwardness and the negative backwardness. """ for p in range( 2 ): b = game_data[str(p)]['balance'] w = game_data[str(p)]['water'] if abs( b ) > w: game_data[str(p)]['will'] -= ( abs( b ) - w ) if b < 0: game_data[str(p)]['balance'] = -w elif b > 0: game_data[str(p)]['balance'] = w return game_data # THESE ARE MINOR AND NONMANDATORY API FUNCTIONS, # BUT THEIR USE IS RECOMMENDED def get_stat( dance, player, stat ): """ Accepts a bin representing the player and a string representing the stat and returns the stat's value. """ return dance[ str(player) ][ str(stat) ] # THE TWO FUNCTIONS BELOW # ARE THE ONLY ESSENTIAL API FUNCTIONS def set_stage( p0_e, p0_a, p0_f, p0_w, p1_e, p1_a, p1_f, p1_w, d0, d_max ): """ Accepts initial element values for p0 and p1, as well as initial and maximum distance, then returns a JSON object describing the game-stage. """ game_data = { '0' : _setup_player( p0_e, p0_a, p0_f, p0_w ), '1' : _setup_player( p1_e, p1_a, p1_f, p1_w ), 'game' : { 'd' : d0, 'd_max' : d_max, 'turn' : 0, '0choice' : None, '1choice' : None, 'gameover' : 0, 'gameover_message' : "ERROR" # in 'gameover_message', a bool will symbolize that player, a 2 will symbolize both players } } json_data = json.dumps( game_data ) return json_data def turn( json_data ): """ Accepts a JSON object describing the game-stage, plus a binary representing the active player and a string representing that player's choice. Returns a modified JSON object. """ # Open the game data game_data0 = json.loads( json_data ) # These exceptions should make it easy # to learn if player behavior has violated the rules. if game_data0['game']['gameover'] == 1: raise GameOver for player in playerList: choice = game_data0[player]['choice'] if not choice in moveList: raise NoSuchMove if game_data0[player][choice] == 0: raise IllegalMove # Split the game_data into two branches: 0 for reading and 1 for writing. # For this reason, all action functions must use +/-=, not just = game_data1 = copy.deepcopy( game_data0 ) # Execute the moves of each player game_data1 = _execute( 0, game_data0['0']['choice'], game_data0, game_data1 ) game_data1 = _execute( 1, game_data0['1']['choice'], game_data0, game_data1 ) # Reenable all moves. game_data1 = _enables( game_data1 ) # Disable for next round the moves that were just used. game_data1 = _disables( game_data1 ) # Check to see if any stat is outside legal bounds game_data1 = _adj_check( game_data1 ) # Check to see if the game has ended _gameover_check( game_data1 ) # Finally, increment the turn counter. game_data1['game']['turn'] += 1 # Write the log # Repackage and return the game data new_json_data = json.dumps( game_data1 ) return new_json_data	28.364975	104	0.667878	from __future__ import print_function import math import copy import json dancer = { verbs : {} adjs: {} } # dancer describes the state of a conscious being # relation describes the feeling of one regarding another dancer["adjs"]["lust"] dancer["adjs"]["like"] # define the archetypal relations dancer["relation"]["arch"] = { "lust" : 0, "like" : 0, "respect" : 0, } # define the dancer's abilities ## API: # MODULE SETTINGS: # These values used to calibrate action effects. SMALL_MULTIPLIER = 0.1 MEDIUM_MULTIPLIER = 0.2 LARGE_MULTIPLIER = 0.4 # Key bindings. These are inserted into the game object during _setup_player. keyDict = { "y" : "touch", "t" : "evade", "r" : "jest", "f" : "retreat", "g" : "breathe", "h" : "advance" } # Lists -- these are to be used by the client. # (Mainly so display functions can be dynamic.) # My dance_display.py should work for any moveList that is a list of strings # and any statList that is a list of strings # or a list of lists which contain only strings. # BUT: moveList + statList MUST == the keys of p in _setup_player (-'choice') # (I know that's ugly, sorry.) moveList = [ 'advance', 'retreat', 'touch', 'evade', 'breathe', 'jest' ] statList = [ ['earth', 'will'], ['air', 'calm'], ['fire', 'heat'], ['water', 'balance'] ] playerList = ['0', '1'] # These are some special exceptions. # Probably not necessary. class NoSuchMove( Exception ): pass class NoSuchStat( Exception ): pass class IllegalMove( Exception ): pass class GameOver( Exception ): pass ## BACKEND: # UTILITY FUNCTIONS # These are totally useless ;) # SMALL def _small( mag ): value = ( mag * SMALL_MULTIPLIER ) return (value) # MED def _med( mag ): value = ( mag * MEDIUM_MULTIPLIER ) return (value) # LARGE def _large( mag ): value = ( mag * LARGE_MULTIPLIER ) return (value) def _setup_player( e0, a0, f0, w0): """ Accepts initial values for eafw, returns a complete player object. """ heat = f0/2 if f0%2 == 1: heat += 1 p = { 'earth' : float(e0), 'will' : float(e0), 'air' : float(a0), 'calm' : float(a0), 'fire' : float(f0), 'heat' :float(heat), 'water' : float(w0), 'balance' : -1.0, 'choice' : None, 'advance' : 1, 'retreat' : 1, 'touch' : 1, 'evade' : 1, 'breathe' : 1, 'jest' : 1 } p.update( keyDict ) return p def _execute( player, choice, game_data0, game_data1 ): """ Reads from gd0 and writes to gd1, according to the move with the same name as the player's choice. """ # In theory, neither of the below exceptions should ever be raised # since the client-side function should test both conditions # before calling a new turn. # First check to see if the move exists. if choice in moveList: pass else: raise NoSuchMove # Second check to see if the move is currently allowed. if game_data0[ str(player) ][ str(choice) ] == 1: pass else: raise IllegalMove # Then perform the move. if player == 0: other = 1 else: other = 0 move = execList[ choice ] game_data1 = move( str(player), str(other), game_data0, game_data1) # Finally, return the modified object. return game_data1 def _enables( game_data ): for move in moveList: game_data['0'][move] = 1 game_data['1'][move] = 1 return game_data def _disables( game_data ): # First learn which moves were just used... choice0 = game_data['0']['choice'] choice1 = game_data['1']['choice'] # ... then disable both of them for the next round. game_data['0'][choice0] = 0 game_data['1'][choice1] = 0 return game_data def _val_in( val_0, magnitude ): """ Returns magnitude with the sign such that abs(val_0 + mag2) < abs(val_0) If mag < 0, does the opposite. If abs(mag) > 1, may result in an overshoot. """ if val_0 < 0: pass elif val_0 > 0: magnitude = -magnitude else: # Because one cannot draw closer to 0 if one is already there: if magnitude > 0: magnitude = 0 # And since we don't want d to be always negative: else: magnitude = -magnitude return magnitude def _gameover_check( game_data ): """ Checks to see if gameover should be declared. This function defines the encounter-end conditions. (Maybe it should take some cues from ## MODULE SETTINGS ?) """ if game_data["0"]["will"] <= 0 and game_data["1"]["will"] <= 0: game_data['game']['gameover'] = 1 game_data['game']['gameover_message'] = ( 'SimultaneousExhaustion' ) else: for p in range( 0, 1 ): if game_data[ str(p) ]['will'] <= 0: game_data['game']['gameover'] = 1 game_data['game']['gameover_message'] = ( 'Player ' + str(p) + ' exhaustion.' ) # VERBS SECTION # This section should include callable functions for each move. # Each move must accept actor, target, and distance arguments. # All functions in this section accept a bin for actor or target. # They read only from game_0 and write only to game_1, # returning game_1 def _advance( actor, target, game_0, game_1): """ Signifies a closening, with or without physical contact. A bold statement, a step forward, or a glorious charge. Costs calm; reduces balance. """ # This part is the cost. It will always be the same. game_1[actor]['calm'] -= _small( game_0[actor]["heat"] ) # Advancing does not increase one's balance # if one pushes against the target. # (Though frict may change balance.) if not ( game_0['game']['d'] == 0 and _get_future_d( game_0 ) ): game_1[actor]['balance'] += 1 # If the future distance is 0, a collision occurs. # (As long as the target did not evade.) if _get_future_d( game_0 ) == 0 and game_0[target]['choice'] != 'evade': game_1 = _frict( actor, target, game_0, game_1 ) # If the two players are already grappling, # (ie in the same space, at d=0) # they cannot advance past each other. # Otherwise, the distance will decrease. # (If they are at d1, they will switch positions.) game_1['game']['d'] += _val_in( game_0['game']['d'], 1 ) return game_1 def _retreat( actor, target, game_0, game_1): """ Signifies a distancing, a retreat, a coldness a disreply, a shyness, a step back, or a flight. Costs calm; reduces balance. """ # Reduce calm by small game_1[actor]['calm'] -= _small( game_0[actor]["heat"] ) # Decrease balance by small game_1[actor]['balance'] -= 1 # Open distance by 1 if game_0[target]['choice'] == 'advance' and game_0['game']['d'] == 0: pass else: game_1['game']['d'] += _val_in( game_0['game']['d'], -1 ) return game_1 def _touch( actor, target, game_0, game_1): """ Signifies phsyical contact. A brush, caress, strike, grope, or attempt. """ # This is the cost game_1[actor]['calm'] -= _med( game_0[actor]['heat'] ) # Check to see if the move connects. if abs( _get_future_d( game_0 ) ) <= 1 and game_0[target]['choice'] != 'evade': # Below is a somewhat silly way of saying # that a successful touch is like a frict, # but only affecting the target. save = copy.deepcopy( game_1[actor] ) _frict( actor, target, game_0, game_1 ) game_1[actor] = copy.deepcopy( save ) return game_1 def _evade( actor, target, game_0, game_1): """ A sort of dodge or refusal. Counteracts the effect of a touch or advance. Rather embarassing against a tease. Technically does nothing. Other acts may define exceptions for: if game_0[target]['choice'] == 'evade': """ if _frict_occurs( game_0 ): # In this case, _frict_occurs() is _if_frict_would_occur() # If successful, restores calm. # (Since you look so cool.) game_1[actor]['calm'] += _small( game_0[actor]['air'] ) else: # Otherwise, costs a fair bit. game_1[actor]['calm'] -= _med( game_0[actor]['heat'] ) return game_1 def _breathe( actor, target, game_0, game_1): """ A moment of rest, contemplation, and gathering. Could signify literal breathing, but also meditation or inaction. (Totally restores calm. Slightly reduces heat and restores will.) """ # See above. if not _frict_occurs( game_0 ): game_1[actor]['calm'] = game_0[actor]['air'] game_1[actor]['heat'] -= _small( game_0[actor]['air'] ) game_1[actor]['will'] += _small( game_0[actor]['air'] ) # Closes balance by one. game_1[actor]['balance'] += _val_in( game_1[actor]['balance'], 1 ) # However: breathe is interrupted by a frict. # You'll still get some breath back, but receive no other bonuses. else: game_1[actor]['calm'] += _large( game_0[actor]['air'] ) return game_1 def _jest( actor, target, game_0, game_1): """ A joke or strangeness, encouraging advance and curiosity by inspiring a passion -- for example anger or desire. (Adds heat and negative balance -- more effective if the target is retreating or evading.) """ game_1[actor]['calm'] -= _small( game_0[actor]['heat'] ) if not game_0[target]['choice'] == 'breathe': game_1[target]['heat'] += _small( game_0[actor]['heat'] ) # By reducing balance, tease can force the target to advance or suffer in fricts # It is less useful if the player is already forward-balanced. game_1[target]['balance'] -= 1 if game_0[target]['choice'] == 'retreat' or game_0[target]['choice'] == 'evade': game_1[target]['heat'] += _med( game_0[actor]['heat'] ) return game_1 def _frict_occurs( game_0 ): for p in playerList: if game_0[str(p)]['choice'] == "advance" and _get_future_d( game_0 ) == 0: return 1 elif game_0[str(p)]['choice'] == "touch" and abs(_get_future_d( game_0 )) <= 1: return 1 else: pass return 0 def _frict( actor, target, game_0, game_1): """ Represents a kind of clash, collision, or rubbing-together. Depends on balances. """ # Both players receive heat. The one with less receives more. game_1[target]['heat'] += _small( game_0[actor]['fire']) game_1[actor]['heat'] += _small( game_0[target]['fire']) if game_0[actor]['heat'] > game_0[target]['heat']: game_1[target]['heat'] += _small( game_0[actor]['heat'] ) elif game_0[actor]['heat'] < game_0[target]['heat']: game_1[actor]['heat'] += _small( game_0[target]['heat'] ) else: game_1[target]['heat'] += _small( game_0[actor]['heat'] ) game_1[actor]['heat'] += _small( game_0[target]['heat'] ) # If one player's will is less than 25% of the other's # that player will be pushed back. if game_0[actor]['will'] > 4 * game_0[target]['will']: game_1[target]['balance'] -= 1 elif 4 * game_0[actor]['will'] < game_0[target]['will']: game_1[actor]['balance'] -= 1 # Adds heat to each player, giving the advantage to the player # whose absolute balance is the smaller percent of their water. # (So if p0.bal = 1/10 and p1.bal = -1/11, then p1 will have the advantage.) a_bal = float( abs(game_0[actor]['balance'] )) / game_0[actor]['water'] t_bal = float( abs(game_0[target]['balance'] )) / game_0[target]['water'] if a_bal == t_bal: game_1[actor]['heat'] += _med( game_0[target]['heat'] ) game_1[target]['heat'] += _med( game_0[actor]['heat'] ) elif a_bal > t_bal: game_1[actor]['heat'] += _large( game_0[target]['heat'] ) game_1[target]['heat'] += _small( game_0[actor]['heat'] ) elif a_bal < t_bal: game_1[actor]['heat'] += _small( game_0[target]['heat'] ) game_1[target]['heat'] += _large( game_0[actor]['heat'] ) else: print( "I think this is impossible, right?" ) return game_1 def _get_future_d( game_0 ): """ This somewhat kludgy function calculates the future distance based on the present distance and the player choices. Used in collision detection. """ d = game_0['game']['d'] if d == 0 and ( game_0['0']['choice'] == 'advance' or game_0['1']['choice'] == 'advance' ): pass else: for p in range( 2 ): choice = game_0[str(p)]['choice'] if choice == 'advance': d -= math.copysign(1, d) elif choice == 'retreat': d += math.copysign(1, d) else: pass d = int(d) return d # The below is used by _execute() to link strings with actions. # This is a little silly, but I don't know a better way. # (For some reason, this list can't be written until after the functions it contains. # Fuck you, Python.) execList = { "advance" : _advance, "retreat" : _retreat, "touch" : _touch, "evade" : _evade, "breathe" : _breathe, "jest" : _jest } # ADJECTIVES SECTION # This section should include rules for checking and correcting element statuses. def _adj_check( game_data ): # Checks all play adjective/attributes/stats in sequence. game_data = _air_check( game_data) # ; - ) game_data = _fire_check( game_data) game_data = _water_check( game_data) game_data = _earth_check( game_data) return game_data def _earth_check( game_data ): """ Without will, an individual is unable to continue. """ for p in range(2): if game_data[str(p)]['will'] > game_data[str(p)]['earth']: game_data[str(p)]['will'] = game_data[str(p)]['earth'] if game_data['0']['will'] <= 0 and game_data['1']['will'] <= 0: game_data['game']['gameover'] = 1 game_data['game']['gameover_message'] = 2 else: for p in range( 2 ): if game_data[str(p)]['will'] <= 0: game_data['game']['gameover'] = 1 game_data['game']['gameover_message'] = p return game_data def _air_check( game_data ): """ Below-min breath is called exhaustion. Knowing when to breathe is important. """ for p in range( 2 ): c = game_data[str(p)]['calm'] # Punish will if calm is below zero if c < 0: game_data[str(p)]['calm'] = 0 game_data[str(p)]['will'] += c # Treat Air as maximum Calm if c > game_data[str(p)]['air']: game_data[str(p)]['calm'] = game_data[str(p)]['air'] return game_data def _fire_check( game_data ): """ Above-max heat is called mania, while below-min heat is called depression. High heat will power-up some moves, but it is risky. """ for p in range(2): h = game_data[str(p)]['heat'] f = game_data[str(p)]['fire'] if h < 0: game_data[str(p)]['heat'] = 0 game_data[str(p)]['will'] += h if h > f: game_data[str(p)]['heat'] = f game_data[str(p)]['will'] -= ( h - f ) return game_data def _water_check( game_data ): """ Balance is not a magnitude, but a distance from zero. Zero represents perfect balance, while the positive represents forwardness and the negative backwardness. """ for p in range( 2 ): b = game_data[str(p)]['balance'] w = game_data[str(p)]['water'] if abs( b ) > w: game_data[str(p)]['will'] -= ( abs( b ) - w ) if b < 0: game_data[str(p)]['balance'] = -w elif b > 0: game_data[str(p)]['balance'] = w return game_data # THESE ARE MINOR AND NONMANDATORY API FUNCTIONS, # BUT THEIR USE IS RECOMMENDED def get_stat( dance, player, stat ): """ Accepts a bin representing the player and a string representing the stat and returns the stat's value. """ return dance[ str(player) ][ str(stat) ] def mod_stat( dance, player, stat, magnitude ): dance[ str(player) ][ str(stat) ] += int( magnitude ) return dance def set_stat( dance, player, stat, magnitude ): dance[ str(player) ][ str(stat) ] = int( magnitude ) return dance def get_dist( dance ): return dance[ "game" ][ "d" ] def mod_dist( dance, magnitude ): dance[ "game" ][ "d" ] += int( magnitude ) return dance def set_dist( dance, magnitude ): dance[ "game" ][ "d" ] = int( magnitude ) return dance # THE TWO FUNCTIONS BELOW # ARE THE ONLY ESSENTIAL API FUNCTIONS def set_stage( p0_e, p0_a, p0_f, p0_w, p1_e, p1_a, p1_f, p1_w, d0, d_max ): """ Accepts initial element values for p0 and p1, as well as initial and maximum distance, then returns a JSON object describing the game-stage. """ game_data = { '0' : _setup_player( p0_e, p0_a, p0_f, p0_w ), '1' : _setup_player( p1_e, p1_a, p1_f, p1_w ), 'game' : { 'd' : d0, 'd_max' : d_max, 'turn' : 0, '0choice' : None, '1choice' : None, 'gameover' : 0, 'gameover_message' : "ERROR" # in 'gameover_message', a bool will symbolize that player, a 2 will symbolize both players } } json_data = json.dumps( game_data ) return json_data def turn( json_data ): """ Accepts a JSON object describing the game-stage, plus a binary representing the active player and a string representing that player's choice. Returns a modified JSON object. """ # Open the game data game_data0 = json.loads( json_data ) # These exceptions should make it easy # to learn if player behavior has violated the rules. if game_data0['game']['gameover'] == 1: raise GameOver for player in playerList: choice = game_data0[player]['choice'] if not choice in moveList: raise NoSuchMove if game_data0[player][choice] == 0: raise IllegalMove # Split the game_data into two branches: 0 for reading and 1 for writing. # For this reason, all action functions must use +/-=, not just = game_data1 = copy.deepcopy( game_data0 ) # Execute the moves of each player game_data1 = _execute( 0, game_data0['0']['choice'], game_data0, game_data1 ) game_data1 = _execute( 1, game_data0['1']['choice'], game_data0, game_data1 ) # Reenable all moves. game_data1 = _enables( game_data1 ) # Disable for next round the moves that were just used. game_data1 = _disables( game_data1 ) # Check to see if any stat is outside legal bounds game_data1 = _adj_check( game_data1 ) # Check to see if the game has ended _gameover_check( game_data1 ) # Finally, increment the turn counter. game_data1['game']['turn'] += 1 # Write the log # Repackage and return the game data new_json_data = json.dumps( game_data1 ) return new_json_data	1,342	59	366
29ccba1a2cac835de3bf2e7be861a69f13af32ef	4,653	py	Python	Arbre.py	AmadouSY/Construction-de-mobiles	5c954dc3d5fa99bbdce2bdab395008d863e6178c	[ "MIT" ]	null	null	null	Arbre.py	AmadouSY/Construction-de-mobiles	5c954dc3d5fa99bbdce2bdab395008d863e6178c	[ "MIT" ]	null	null	null	Arbre.py	AmadouSY/Construction-de-mobiles	5c954dc3d5fa99bbdce2bdab395008d863e6178c	[ "MIT" ]	null	null	null	##### CLASSE ARBRE ##### #Initialise l'arbre #Emplacement du sous arbre gauche #Feuille la plus lourde de l'arbre #Liste des feuille de l'arbre #Largeur du noeud #Place les arbres #Largeur de l'arbre pour le dessin #Longueur de l'arbre pour le dessin #Profondeur de l'arbre #Construit le mobile ###### CLASSE FEUILLE #####	26.140449	80	0.566301	##### CLASSE ARBRE ##### class Arbre: #Initialise l'arbre def __init__(self): #Valeur de l'arbre self.valeur = 0 #Fils gauche self.gauche = None #Fils droit self.droit = None #Position de l'arbre self.position = Position() def __str__(self): return "["+str(self.gauche)+","+str(self.droit)+"]" def __len__(self): return len(self.gauche) + len(self.droit) def poid(self): return self.gauche.poid() + self.droit.poid() #Emplacement du sous arbre gauche def equilibre(self): if type(self.gauche) is Arbre: self.gauche.equilibre() if type(self.droit) is Arbre: self.droit.equilibre() self.valeur = self.droit.poid() / (self.gauche.poid()+self.droit.poid()) #Feuille la plus lourde de l'arbre def maximum(self): if self.gauche.maximum() > self.droit.maximum(): return self.gauche.maximum() else: return self.droit.maximum() #Liste des feuille de l'arbre def listeElement(self): l = self.gauche.listeElement() l.extend(self.droit.listeElement()) return l #Largeur du noeud def largeurArbre(self): g = 0 d = 0 if type(self.gauche) is Feuille: g = self.gauche.valeur else: g = self.gauche.largeurArbre() if type(self.droit) is Feuille: d = self.droit.valeur else: d = self.droit.largeurArbre() return g+d #Place les arbres def placerArbre(self): largeur = self.largeurArbre()//2 self.gauche.position.x = -largeur*self.valeur self.gauche.position.y = 0 self.droit.position.x = self.gauche.position.x + largeur self.droit.position.y = 0 if type(self.gauche) is not Feuille: self.gauche.placerArbre() if type(self.droit) is not Feuille: self.droit.placerArbre() #Largeur de l'arbre pour le dessin def largeur(self): g = self.gauche.largeurGauche() + self.gauche.position.x d = self.droit.largeurDroit() + self.droit.position.x return - g + d def largeurGauche(self): return self.gauche.position.x + self.gauche.largeurGauche() def largeurDroit(self): return self.droit.position.x + self.droit.largeurDroit() #Longueur de l'arbre pour le dessin def longueur(self): hauteur = self.maximum() return self.longueurRec(hauteur) def longueurRec(self, hauteur): d = self.droit.position.y + self.droit.longueurRec(hauteur) g = self.gauche.position.y + self.gauche.longueurRec(hauteur) return hauteur + max(d,g) #Profondeur de l'arbre def hauteur(self): if self.gauche.hauteur() > self.droit.hauteur(): return self.gauche.hauteur()+1 return self.droit.hauteur()+1 #Construit le mobile def constructionArbre(self, v): poidG = self.gauche.poid() poidD = self.droit.poid() if v >= (poidG+poidD): A = Arbre() A.gauche = self A.droit = Feuille(v) return A if poidG == poidD: if self.gauche.hauteur() > self.droit.hauteur(): self.droit = self.droit.constructionArbre(v) else: self.gauche = self.gauche.constructionArbre(v) elif poidG > poidD : self.droit = self.droit.constructionArbre(v) else: self.gauche = self.gauche.constructionArbre(v) return self ###### CLASSE FEUILLE ##### class Feuille(Arbre): def __init__(self, v): self.valeur = v self.position = Position() def __str__(self): return str(self.valeur) def __len__(self): return 1 def poid(self): return self.valeur def maximum(self): return self.valeur def listeElement(self): return [self.valeur] def largeurGauche(self): return -self.valeur//2 def largeurDroit(self): return self.valeur//2 def longueur(self): hauteur = self.maximum() return self.longeurRec(hauteur) def longueurRec(self, hauteur): return hauteur + self.valeur//2 def hauteur(self): return 1 def constructionArbre(self, v): p = Arbre() p.gauche = self p.droit = Feuille(v) return p class Position: def __init__(self): self.x = 0 self.y = 0	3,359	-15	897
698ff5d66b57b03332ca7ef940aca00b96b031c8	1,275	py	Python	src/MouseClick.py	radialia/Gestured-Mouse	6c1a41fa552a959ba28453e916709f170142a682	[ "MIT" ]	1	2022-01-31T10:11:05.000Z	2022-01-31T10:11:05.000Z	src/MouseClick.py	radialia/Air-Mouse	6c1a41fa552a959ba28453e916709f170142a682	[ "MIT" ]	null	null	null	src/MouseClick.py	radialia/Air-Mouse	6c1a41fa552a959ba28453e916709f170142a682	[ "MIT" ]	null	null	null	import cv2 import math from pynput.mouse import Button	33.552632	78	0.546667	import cv2 import math from pynput.mouse import Button def MouseClick(frame, landmarkList, mouse): clicked = False if(len(landmarkList) != 0): # Gets landmarks of index and middle finger index_x, index_y = landmarkList[8][1], landmarkList[8][2] middle_x, middle_y = landmarkList[12][1], landmarkList[12][2] cv2.circle(frame, (index_x, index_y), 15, (255, 0, 0), cv2.FILLED) cv2.circle(frame, (middle_x, middle_y), 15, (255, 0, 0), cv2.FILLED) cv2.line(frame, (index_x, index_y), (middle_x, middle_y), (255, 255, 0), 2) # Calculate center center_x, center_y = (index_x+middle_x)//2, (index_y+middle_y)//2 # Get distance distance = math.sqrt( math.pow((index_x-middle_x), 2) + math.pow((index_y-middle_y), 2)) # Detect distance if(distance < 50): cv2.circle(frame, (center_x, center_y), 15, (0, 255, 0), cv2.FILLED) if(clicked != True): mouse.click(Button.left, 1) clicked = True if(distance > 50): cv2.circle(frame, (center_x, center_y), 15, (0, 0, 255), cv2.FILLED) clicked = False	1,196	0	23
628e9f8ac0080ab46d87ed0261cbe4bc729e3273	2,003	py	Python	deewr/variables.py	fromz/deewr-tga	bd913d2b70dd83dc7dfa2f2da9cf19f64122ab0e	[ "MIT" ]	null	null	null	deewr/variables.py	fromz/deewr-tga	bd913d2b70dd83dc7dfa2f2da9cf19f64122ab0e	[ "MIT" ]	2	2021-03-31T19:58:26.000Z	2021-12-13T20:41:50.000Z	deewr/variables.py	fromz/deewr-tga	bd913d2b70dd83dc7dfa2f2da9cf19f64122ab0e	[ "MIT" ]	null	null	null	import re def elem2dict(node): """ Convert an lxml.etree node tree into a dict. """ d = {} for e in node.iterchildren(): key = e.tag.split('}')[1] if '}' in e.tag else e.tag value = e.text if e.text else elem2dict(e) d[key] = value return d	30.348485	92	0.624064	import re def elem2dict(node): """ Convert an lxml.etree node tree into a dict. """ d = {} for e in node.iterchildren(): key = e.tag.split('}')[1] if '}' in e.tag else e.tag value = e.text if e.text else elem2dict(e) d[key] = value return d class VariableExtractor: def __init__(self, xmlNodes): self.data = {} for xmlNode in xmlNodes: d = elem2dict(xmlNode) self.data[d['ID']] = d def getbyname(self, name): for id in self.data: data = self.data[id] if "Name" in data and isinstance(data['Name'], str): if data['Name'].upper() == name.upper(): return data class VariableAssignmentExtractor: def __init__(self, xmlNodes): self.data = {} for xmlNode in xmlNodes: d = elem2dict(xmlNode) self.data[d['ID']] = d def resolve_variable_value(variable, variable_assignment): if variable_assignment is None: return variable['Value'] if variable['Type'] == '0': return variable_assignment['Value'] print("dont know how to resolve that variable type", variable) exit(1) def resolve_template_variables(variable_assignment_extractor, variable_extractor, template): regex = r"<.+?>" matches = re.finditer(regex, template, re.MULTILINE) for matchNum, match in enumerate(matches, start=1): templateMatch = match.group() variableName = templateMatch[1:len(templateMatch)-1] codeVariable = variable_extractor.getbyname(variableName) if codeVariable: codeAssignment = None if codeVariable['ID'] in variable_assignment_extractor.data: codeAssignment = variable_assignment_extractor.data[codeVariable['ID']] resolvedVariable = resolve_variable_value(codeVariable, codeAssignment) template = template.replace(templateMatch, resolvedVariable) return template	1,520	16	173
e5deb6e08999615678849e1f02b3b0b5770df613	4,072	py	Python	setup.py	AlexBourassa/nspyre	d254af09c7c8377552e85dba6f60b150fbb8da2e	[ "MIT" ]	8	2019-12-06T14:49:34.000Z	2020-07-03T18:46:45.000Z	setup.py	nspyre-org/nspyre	d254af09c7c8377552e85dba6f60b150fbb8da2e	[ "BSD-3-Clause" ]	31	2020-09-21T21:01:06.000Z	2021-12-10T03:27:26.000Z	setup.py	NSpyre-Dev/nspyre	d254af09c7c8377552e85dba6f60b150fbb8da2e	[ "BSD-3-Clause" ]	4	2020-10-07T23:58:13.000Z	2022-03-01T15:22:34.000Z	from setuptools import setup, find_packages import codecs import pathlib import re here = pathlib.Path(__file__).parent.resolve() def read(parts): """ Build an absolute path from parts* and and return the contents of the resulting file. Assume UTF-8 encoding. """ with codecs.open(pathlib.PurePath(here, parts), "rb", "utf-8") as f: return f.read() def find_version(file_paths): """ Build a path from file_paths and search for a ``__version__`` string inside. """ version_file = read(file_paths) version_match = re.search( r"^__version__ = ['\"]([^'\"])['\"]", version_file, re.M ) if version_match: return version_match.group(1) raise RuntimeError("Unable to find version string.") meta_path = pathlib.PurePath('src', 'nspyre', '__init__.py') version = find_version(meta_path) long_description = (here / 'README.md').read_text(encoding='utf-8') setup( name='nspyre', version=version, license='BSD 3-Clause License', description='Networked Scientific Python Research Environment', long_description=long_description, long_description_content_type='text/markdown', url='https://github.com/nspyre-org/nspyre', author='Alexandre Bourassa', author_email='abourassa@uchicago.edu', maintainer='Michael Solomon', maintainer_email='msolo@uchicago.edu', classifiers=[ 'Development Status :: 4 - Beta', 'Framework :: IPython', 'Framework :: Jupyter', 'Intended Audience :: Developers', 'Intended Audience :: Science/Research', 'License :: OSI Approved :: BSD License', 'Natural Language :: English', 'Operating System :: Microsoft :: Windows', 'Operating System :: POSIX', 'Operating System :: Unix', 'Programming Language :: Python', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.8', 'Programming Language :: Python :: 3 :: Only', 'Programming Language :: Python :: Implementation :: CPython', 'Topic :: Scientific/Engineering', 'Topic :: Scientific/Engineering :: Physics', 'Topic :: Scientific/Engineering :: Visualization', 'Topic :: Software Development :: Libraries', 'Topic :: Software Development :: Libraries :: Application Frameworks', 'Topic :: Software Development :: Libraries :: Python Modules', 'Topic :: Software Development :: User Interfaces', 'Topic :: System :: Distributed Computing', 'Topic :: System :: Logging', ], keywords='nspyre, measurement toolkit, experimentation platform, physics, science, research', package_dir={'': 'src'}, packages=find_packages(where='src'), zip_safe=False, python_requires='>=3.8, <4', install_requires=[ # SciPy 'numpy>=1.19.1', 'scipy>=1.5.2', 'pandas>=1.1.2', # MongoDB 'pymongo>=3.10.1', # Qt 'pyqt5>=5.12.3', 'pyqtgraph>=0.11.0', 'qscintilla>=2.11.2', # VISA 'pyvisa>=1.10.1', # Lantz 'pint>=0.15', 'pimpmyclass>=0.4.3', 'lantzdev>=0.5.2', # Utilities 'parse>=1.18.0', 'tqdm>=4.49.0', 'rpyc>=4.1.5', ], extras_require={ 'dev': [ 'pytest>=6.1.2', 'pytest-cov', 'psutil>=5.7.3', ] }, test_requires=[ 'pytest>=6.1.2', 'pytest-cov', 'psutil>=5.7.3', ], test_suite='tests', entry_points={ 'console_scripts': [ 'nspyre=nspyre.gui:main', 'nspyre-config=nspyre.config.config_cli:main', 'nspyre-mongodb=nspyre.mongodb:main', 'nspyre-inserv=nspyre.inserv:main', ], }, project_urls={ 'Bug Reports': 'https://github.com/nspyre-org/nspyre/issues', 'Source': 'https://github.com/nspyre-org/nspyre/', }, include_package_data=True, options={'bdist_wheel': {'universal': '1'}}, )	31.083969	97	0.585953	from setuptools import setup, find_packages import codecs import pathlib import re here = pathlib.Path(__file__).parent.resolve() def read(parts): """ Build an absolute path from parts* and and return the contents of the resulting file. Assume UTF-8 encoding. """ with codecs.open(pathlib.PurePath(here, parts), "rb", "utf-8") as f: return f.read() def find_version(file_paths): """ Build a path from file_paths and search for a ``__version__`` string inside. """ version_file = read(file_paths) version_match = re.search( r"^__version__ = ['\"]([^'\"])['\"]", version_file, re.M ) if version_match: return version_match.group(1) raise RuntimeError("Unable to find version string.") meta_path = pathlib.PurePath('src', 'nspyre', '__init__.py') version = find_version(meta_path) long_description = (here / 'README.md').read_text(encoding='utf-8') setup( name='nspyre', version=version, license='BSD 3-Clause License', description='Networked Scientific Python Research Environment', long_description=long_description, long_description_content_type='text/markdown', url='https://github.com/nspyre-org/nspyre', author='Alexandre Bourassa', author_email='abourassa@uchicago.edu', maintainer='Michael Solomon', maintainer_email='msolo@uchicago.edu', classifiers=[ 'Development Status :: 4 - Beta', 'Framework :: IPython', 'Framework :: Jupyter', 'Intended Audience :: Developers', 'Intended Audience :: Science/Research', 'License :: OSI Approved :: BSD License', 'Natural Language :: English', 'Operating System :: Microsoft :: Windows', 'Operating System :: POSIX', 'Operating System :: Unix', 'Programming Language :: Python', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.8', 'Programming Language :: Python :: 3 :: Only', 'Programming Language :: Python :: Implementation :: CPython', 'Topic :: Scientific/Engineering', 'Topic :: Scientific/Engineering :: Physics', 'Topic :: Scientific/Engineering :: Visualization', 'Topic :: Software Development :: Libraries', 'Topic :: Software Development :: Libraries :: Application Frameworks', 'Topic :: Software Development :: Libraries :: Python Modules', 'Topic :: Software Development :: User Interfaces', 'Topic :: System :: Distributed Computing', 'Topic :: System :: Logging', ], keywords='nspyre, measurement toolkit, experimentation platform, physics, science, research', package_dir={'': 'src'}, packages=find_packages(where='src'), zip_safe=False, python_requires='>=3.8, <4', install_requires=[ # SciPy 'numpy>=1.19.1', 'scipy>=1.5.2', 'pandas>=1.1.2', # MongoDB 'pymongo>=3.10.1', # Qt 'pyqt5>=5.12.3', 'pyqtgraph>=0.11.0', 'qscintilla>=2.11.2', # VISA 'pyvisa>=1.10.1', # Lantz 'pint>=0.15', 'pimpmyclass>=0.4.3', 'lantzdev>=0.5.2', # Utilities 'parse>=1.18.0', 'tqdm>=4.49.0', 'rpyc>=4.1.5', ], extras_require={ 'dev': [ 'pytest>=6.1.2', 'pytest-cov', 'psutil>=5.7.3', ] }, test_requires=[ 'pytest>=6.1.2', 'pytest-cov', 'psutil>=5.7.3', ], test_suite='tests', entry_points={ 'console_scripts': [ 'nspyre=nspyre.gui:main', 'nspyre-config=nspyre.config.config_cli:main', 'nspyre-mongodb=nspyre.mongodb:main', 'nspyre-inserv=nspyre.inserv:main', ], }, project_urls={ 'Bug Reports': 'https://github.com/nspyre-org/nspyre/issues', 'Source': 'https://github.com/nspyre-org/nspyre/', }, include_package_data=True, options={'bdist_wheel': {'universal': '1'}}, )	0	0	0
ba08a1c3131298618b80139e7d5cc04315de0e4d	2,984	py	Python	code/generate_predictions.py	jpedrocm/jpcm-lista2-codigo	8c1f867e3cc659cd262f8d9cd3521ccc5f1e8fd8	[ "MIT" ]	1	2019-03-15T08:54:08.000Z	2019-03-15T08:54:08.000Z	code/generate_predictions.py	jpedrocm/pool-pruning-experiment	8c1f867e3cc659cd262f8d9cd3521ccc5f1e8fd8	[ "MIT" ]	null	null	null	code/generate_predictions.py	jpedrocm/pool-pruning-experiment	8c1f867e3cc659cd262f8d9cd3521ccc5f1e8fd8	[ "MIT" ]	null	null	null	############################################################################### import numpy as np import random as rn #DO NOT CHANGE THIS np.random.seed(1478) rn.seed(2264) ################### from utils import load_datasets_filenames, load_experiment_configuration from utils import load_dataset, save_predictions from utils import select_validation_set from utils import get_voting_pool_size, calculate_pool_diversity from sklearn.model_selection import StratifiedKFold if __name__ == "__main__": print "Step 1 - Loading configurations" datasets_filenames = load_datasets_filenames() config = load_experiment_configuration() predictions = {} exp = 1 print "Step 2 - Starting experiment" for dataset_filename in datasets_filenames: instances, gold_labels = load_dataset(dataset_filename) skfold = StratifiedKFold(n_splits = config["num_folds"], shuffle = True) gold_labels = (gold_labels["defects"] == 'true').astype(int) predictions[dataset_filename] = {} for fold, division in enumerate(skfold.split(X=instances, y=gold_labels), 1): train_idxs = division[0] test_idxs = division[1] train_instances = instances.iloc[train_idxs].values train_gold_labels = gold_labels.iloc[train_idxs].values.ravel() test_instances = instances.iloc[test_idxs].values test_gold_labels = gold_labels.iloc[test_idxs].values.ravel() predictions[dataset_filename][fold] = {} predictions[dataset_filename][fold]["gold_labels"] = test_gold_labels.tolist() for hardness_type, filter_func in config["validation_hardnesses"]: validation_instances, validation_gold_labels = select_validation_set( train_instances, train_gold_labels, filter_func, config["kdn"]) predictions[dataset_filename][fold][hardness_type] = {} subpredictions = predictions[dataset_filename][fold][hardness_type] base_clf = config["base_classifier"]() clf_pool = config["generation_strategy"](base_clf, config["pool_size"]) clf_pool.fit(train_instances, train_gold_labels) for strategy_name, pruning_strategy in config["pruning_strategies"]: pruned_pool = pruning_strategy(clf_pool, validation_instances, validation_gold_labels) pool_rem_size = get_voting_pool_size(pruned_pool) cur_predictions = pruned_pool.predict(test_instances) data_arr = [cur_predictions.astype(int).tolist(), pool_rem_size] for measure in config["diversity_measures"]: measure_value = calculate_pool_diversity(measure, pruned_pool, validation_instances, validation_gold_labels, pool_rem_size) data_arr.append(measure_value) subpredictions[strategy_name] = data_arr print "Experiment " + str(exp) exp+=1 print "Step 2 - Finished experiment" print "Step 3 - Storing predictions" save_predictions(predictions)	33.52809	81	0.696716	############################################################################### import numpy as np import random as rn #DO NOT CHANGE THIS np.random.seed(1478) rn.seed(2264) ################### from utils import load_datasets_filenames, load_experiment_configuration from utils import load_dataset, save_predictions from utils import select_validation_set from utils import get_voting_pool_size, calculate_pool_diversity from sklearn.model_selection import StratifiedKFold if __name__ == "__main__": print "Step 1 - Loading configurations" datasets_filenames = load_datasets_filenames() config = load_experiment_configuration() predictions = {} exp = 1 print "Step 2 - Starting experiment" for dataset_filename in datasets_filenames: instances, gold_labels = load_dataset(dataset_filename) skfold = StratifiedKFold(n_splits = config["num_folds"], shuffle = True) gold_labels = (gold_labels["defects"] == 'true').astype(int) predictions[dataset_filename] = {} for fold, division in enumerate(skfold.split(X=instances, y=gold_labels), 1): train_idxs = division[0] test_idxs = division[1] train_instances = instances.iloc[train_idxs].values train_gold_labels = gold_labels.iloc[train_idxs].values.ravel() test_instances = instances.iloc[test_idxs].values test_gold_labels = gold_labels.iloc[test_idxs].values.ravel() predictions[dataset_filename][fold] = {} predictions[dataset_filename][fold]["gold_labels"] = test_gold_labels.tolist() for hardness_type, filter_func in config["validation_hardnesses"]: validation_instances, validation_gold_labels = select_validation_set( train_instances, train_gold_labels, filter_func, config["kdn"]) predictions[dataset_filename][fold][hardness_type] = {} subpredictions = predictions[dataset_filename][fold][hardness_type] base_clf = config["base_classifier"]() clf_pool = config["generation_strategy"](base_clf, config["pool_size"]) clf_pool.fit(train_instances, train_gold_labels) for strategy_name, pruning_strategy in config["pruning_strategies"]: pruned_pool = pruning_strategy(clf_pool, validation_instances, validation_gold_labels) pool_rem_size = get_voting_pool_size(pruned_pool) cur_predictions = pruned_pool.predict(test_instances) data_arr = [cur_predictions.astype(int).tolist(), pool_rem_size] for measure in config["diversity_measures"]: measure_value = calculate_pool_diversity(measure, pruned_pool, validation_instances, validation_gold_labels, pool_rem_size) data_arr.append(measure_value) subpredictions[strategy_name] = data_arr print "Experiment " + str(exp) exp+=1 print "Step 2 - Finished experiment" print "Step 3 - Storing predictions" save_predictions(predictions)	0	0	0
f15b72c2d65ffa81c60de9b17f396cd340613c1e	4,350	py	Python	roonremote.py	matteck/roonrest	ce881a0ee89abc40b410f1b88764c4f0983fa3b0	[ "MIT" ]	1	2017-11-13T04:29:44.000Z	2017-11-13T04:29:44.000Z	roonremote.py	matteck/roonrest	ce881a0ee89abc40b410f1b88764c4f0983fa3b0	[ "MIT" ]	null	null	null	roonremote.py	matteck/roonrest	ce881a0ee89abc40b410f1b88764c4f0983fa3b0	[ "MIT" ]	null	null	null	#!/usr/bin/env python3 import evdev import select import requests import subprocess import re from datetime import datetime roon_base_url = "http://greenspeaker:3000/api/v1" harmony_base_url = "http://m1:8282/hubs/harmony-hub/devices/schiit-amp/commands" p = re.compile('"zone_id": "([a-z0-9]+)",\n *"display_name": "Hifi \+ 1"') devices = {} for fn in evdev.list_devices(): print(fn) dev = evdev.InputDevice(fn) if dev.name.find('HBGIC') >= 0: devices[dev.fd] = dev print(devices) last_volume_change = datetime.now() while True: r, w, x = select.select(devices, [], []) for fd in r: for event in devices[fd].read(): url = None cmd = None if event.type == evdev.ecodes.EV_KEY: myzone = None zones = requests.get("%s/zones" % roon_base_url).json() for z in zones: if zones[z]['display_name'] == "Hifi + 1": myzone = zones[z]['zone_id'] break if not myzone: myzone = requests.get('http://greenspeaker:3000/api/v1/default_zone').text if myzone == "undefined": myzone = "default" print("My zone is %s" % myzone) keyev = evdev.categorize(event) code = keyev.keycode[4:] state = keyev.keystate if state == evdev.events.KeyEvent.key_down: state = "DOWN" elif state == evdev.events.KeyEvent.key_up: state = "UP" elif state == evdev.events.KeyEvent.key_hold: state = "HOLD" print(code, state) method = "POST" if state == "DOWN": if code == "PLAYPAUSE": url = "%s/zone/%s/control/playpause" % (roon_base_url, myzone) elif code == "STOP": # url = "%s/zone/all/control/pause" % roon_base_url url = "%s/zone/%s/control/stop" % (roon_base_url, myzone) elif code == "REWIND": url = "%s/zone/%s/control/previous" % (roon_base_url, myzone) elif code == "FASTFORWARD": url = "%s/zone/%s/control/next" % (roon_base_url, myzone) elif code == "INFO": url = "%s/mute" % harmony_base_url if state == "HOLD" or state == "DOWN": # Make sure volume doesn't change too fast if myzone.lower() == "greenspeaker": if code == "UP": url = "%s/zone/%s/volume/relative_step/2" % (roon_base_url, myzone) if code == "DOWN": url = "%s/zone/%s/volume/relative_step/-2" % (roon_base_url, myzone) else: if code == "UP": url = "%s/volume-up" % harmony_base_url if (datetime.now() - last_volume_change).total_seconds() < 0.5: print("Skipped vol change") continue else: last_volume_change = datetime.now() print("Changed volume up") elif code == "DOWN": url = "%s/volume-down" % harmony_base_url if (datetime.now() - last_volume_change).total_seconds() < 0.5: print("Skipped vol change") continue else: last_volume_change = datetime.now() print("Changed volume down") if url: print(method, url) try: if method == "GET": req = requests.get(url) else: req = requests.post(url) except: print("Request to %s failed" % (url)) if cmd: print(" ".join(cmd)) subprocess.call(cmd)	42.647059	116	0.437011	#!/usr/bin/env python3 import evdev import select import requests import subprocess import re from datetime import datetime roon_base_url = "http://greenspeaker:3000/api/v1" harmony_base_url = "http://m1:8282/hubs/harmony-hub/devices/schiit-amp/commands" p = re.compile('"zone_id": "([a-z0-9]+)",\n *"display_name": "Hifi \+ 1"') devices = {} for fn in evdev.list_devices(): print(fn) dev = evdev.InputDevice(fn) if dev.name.find('HBGIC') >= 0: devices[dev.fd] = dev print(devices) last_volume_change = datetime.now() while True: r, w, x = select.select(devices, [], []) for fd in r: for event in devices[fd].read(): url = None cmd = None if event.type == evdev.ecodes.EV_KEY: myzone = None zones = requests.get("%s/zones" % roon_base_url).json() for z in zones: if zones[z]['display_name'] == "Hifi + 1": myzone = zones[z]['zone_id'] break if not myzone: myzone = requests.get('http://greenspeaker:3000/api/v1/default_zone').text if myzone == "undefined": myzone = "default" print("My zone is %s" % myzone) keyev = evdev.categorize(event) code = keyev.keycode[4:] state = keyev.keystate if state == evdev.events.KeyEvent.key_down: state = "DOWN" elif state == evdev.events.KeyEvent.key_up: state = "UP" elif state == evdev.events.KeyEvent.key_hold: state = "HOLD" print(code, state) method = "POST" if state == "DOWN": if code == "PLAYPAUSE": url = "%s/zone/%s/control/playpause" % (roon_base_url, myzone) elif code == "STOP": # url = "%s/zone/all/control/pause" % roon_base_url url = "%s/zone/%s/control/stop" % (roon_base_url, myzone) elif code == "REWIND": url = "%s/zone/%s/control/previous" % (roon_base_url, myzone) elif code == "FASTFORWARD": url = "%s/zone/%s/control/next" % (roon_base_url, myzone) elif code == "INFO": url = "%s/mute" % harmony_base_url if state == "HOLD" or state == "DOWN": # Make sure volume doesn't change too fast if myzone.lower() == "greenspeaker": if code == "UP": url = "%s/zone/%s/volume/relative_step/2" % (roon_base_url, myzone) if code == "DOWN": url = "%s/zone/%s/volume/relative_step/-2" % (roon_base_url, myzone) else: if code == "UP": url = "%s/volume-up" % harmony_base_url if (datetime.now() - last_volume_change).total_seconds() < 0.5: print("Skipped vol change") continue else: last_volume_change = datetime.now() print("Changed volume up") elif code == "DOWN": url = "%s/volume-down" % harmony_base_url if (datetime.now() - last_volume_change).total_seconds() < 0.5: print("Skipped vol change") continue else: last_volume_change = datetime.now() print("Changed volume down") if url: print(method, url) try: if method == "GET": req = requests.get(url) else: req = requests.post(url) except: print("Request to %s failed" % (url)) if cmd: print(" ".join(cmd)) subprocess.call(cmd)	0	0	0
8e4880e0ebce4707e9d80ed91abc80216cb3e5ab	15,179	py	Python	image_manipulation.py	shequin-joshua-9147/cs162-final-project	0edff7170ca0761b38c30774475bfecac2a18f01	[ "MIT" ]	null	null	null	image_manipulation.py	shequin-joshua-9147/cs162-final-project	0edff7170ca0761b38c30774475bfecac2a18f01	[ "MIT" ]	null	null	null	image_manipulation.py	shequin-joshua-9147/cs162-final-project	0edff7170ca0761b38c30774475bfecac2a18f01	[ "MIT" ]	null	null	null	""" Manipulate images in specific ways based on commands used on input. This module is used in order to manipulate images in a number of ways. All of this is done through the ImageO object. The ImageO object reads in a file and allows for manipulations to be done on an image and for that image to be output after the manipulation. All different things this module allows for are: - make an image only all of its red values - make an image only all of its green values - make an image only all of its blue values - zero out all red values of an image - zero out all green values of an image - zero out all blue values of an image - darken an image by moving all values to be in the lower half of 255 - bright an image by moving all values to be in the upper half of 255 - make image in-to a gray-scaled image - invert the colors of an image - block or blur an image, making all pixel of a block the same rgb value All of these option can be called after importing and creating an ImageO object or from calling this module from the command line with the proper options. Joshua Shequin """ import argparse import sys import numpy as np from PIL import Image def common_denominator(number_one, number_two, range_one, range_two): """ Recursion solution to this problem even though it is not the best way of doing it. Base case is when the modulo of both numbers and the second range value is zero, or if they are the same. Parameters ---------- number_one : int the first number of the two numbers to find the common denominator between. number_two : int the second number of the two numbers to find the common denominator between. range_one : int the lowest integer for a range of values to find the common denominator in. range_two : int the highest integer for a range of values to find the common denominator in. Returns ------ Integer the value that the two input have number both have a denominator with, or the lowest int in the range given if no denominator was found. """ if number_one % range_two == 0 and number_two % range_two == 0: return range_two if range_one == range_two: return range_one return common_denominator(number_one, number_two, range_one, range_two-1) class ImageO: """ Object that handles images, allowing for a number of manipulations. Image object that takes an input file as the input and reads that input file and turns that image in to an array. From that array the object allows for a number of manipulations to be done to the image. Every manipulation also by default outputs the file. """ def __init__(self, input_file): """ Initialize the object by taking an input_file and loading the image to an array. Parameter --------- input_file : string string of the file location to be read, relative or full path. """ try: self.infile = np.array(Image.open(input_file)) # read in the file and store as a # numpy array. except FileNotFoundError: # if that file did not exist then we warn the user and close the program. print("Check your infile parameter, I can't find the file you put in!") sys.exit() def clear_red(self, output_file, returnable=False): """ Clear all red in our image. Parameter --------- output_file : string the name of the file we want to output to. Return ------ numpy array Return the numpy array of the image if returnable=True """ for row in self.infile: for column in row: column[0] = 0 if returnable: return self.infile Image.fromarray(self.infile, "RGB").save(output_file) return None def clear_green(self, output_file, returnable=False): """ Clear all green in our image. Parameter --------- output_file : string the name of the file we want to output to. Return ------ numpy array Return the numpy array of the image if returnable=True """ for row in self.infile: for column in row: column[1] = 0 if returnable: return self.infile Image.fromarray(self.infile, "RGB").save(output_file) return None def clear_blue(self, output_file, returnable=False): """ Clear all blue in our image. Parameter --------- output_file : string the name of the file we want to output to. Return ------ numpy array Return the numpy array of the image if returnable=True """ for row in self.infile: for column in row: column[2] = 0 if returnable: return self.infile Image.fromarray(self.infile, "RGB").save(output_file) return None def red_only(self, output_file, returnable=False): """ Clear all green and all blue of our image. Parameter --------- output_file : string the name of the file we want to output to. Return ------ numpy array Return the numpy array of the image if returnable=True """ for row in self.infile: for column in row: column[1] = 0 column[2] = 0 if returnable: return self.infile Image.fromarray(self.infile, "RGB").save(output_file) return None def green_only(self, output_file, returnable=False): """ Clear all red and all blue of our image. Parameter --------- output_file : string the name of the file we want to output to. Return ------ numpy array Return the numpy array of the image if returnable=True """ for row in self.infile: for column in row: column[0] = 0 column[2] = 0 if returnable: return self.infile Image.fromarray(self.infile, "RGB").save(output_file) return None def blue_only(self, output_file, returnable=False): """ Clear all red and all green of our image. Parameter --------- output_file : string the name of the file we want to output to. Return ------ numpy array Return the numpy array of the image if returnable=True """ for row in self.infile: for column in row: column[0] = 0 column[1] = 0 if returnable: return self.infile Image.fromarray(self.infile, "RGB").save(output_file) return None def lower_half(self, output_file, returnable=False): """ Scale all shades to be only in the lower 127 of color ints. Parameter --------- output_file : string the name of the file we want to output to. Return ------ numpy array Return the numpy array of the image if returnable=True """ for row in self.infile: for column in row: column[0] = column[0]/2 column[1] = column[1]/2 column[2] = column[2]/2 if returnable: return self.infile Image.fromarray(self.infile, "RGB").save(output_file) return None def upper_half(self, output_file, returnable=True): """ Scale all shades to be only in the upper 127 of color ints. Parameter --------- output_file : string the name of the file we want to output to. Return ------ numpy array Return the numpy array of the image if returnable=True """ for row in self.infile: for column in row: column[0] = column[0]/2 + 128 column[1] = column[1]/2 + 128 column[2] = column[2]/2 + 128 if returnable: return self.infile Image.fromarray(self.infile, "RGB").save(output_file) return None def gray_scale(self, output_file, returnable=False): """ Convert the image to a grey-scale image. Parameter --------- output_file : string the name of the file we want to output to. Return ------ numpy array Return the numpy array of the image if returnable=True """ for row in self.infile: for column in row: # to transform a pixel to its gray-scale form we find the average of the three # colors. new_value = (column[0](1/3)) + (column[1](1/3)) +\ (column[2](1/3)) column[0] = new_value column[1] = new_value column[2] = new_value if returnable: return self.infile Image.fromarray(self.infile, "RGB").save(output_file) return None def invert_color(self, output_file, returnable=False): """ Invert all rgb values of the image. Parameter --------- output_file : string the name of the file we want to output to. Return ------ numpy array Return the numpy array of the image if returnable=True """ for row in self.infile: for column in row: column[0] = 255 - column[0] column[1] = 255 - column[1] column[2] = 255 - column[2] if returnable: return self.infile Image.fromarray(self.infile, "RGB").save(output_file) return None def block_image(self, output_file, returnable=False): """ Blurs or blocks an image, assigning a block size for an image making all pixels the same. Calls the common_denominator function to find a common denominator within a range of two numbers for two numbers. This will be used to determine the block width and height. Parameter --------- output_file : string the name of the file we want to output to. Return ------ numpy array Return the numpy array of the image if returnable=True """ number_of_blocks = common_denominator(len(self.infile), len(self.infile[0]), 2, 100) block_dimensions = (len(self.infile)//number_of_blocks, len(self.infile[0])//number_of_blocks) for block_row in range(number_of_blocks): for block in range(number_of_blocks): block_rgb = [[], [], []] for row in range((block_row block_dimensions[0]), (block_row * block_dimensions[0]) + block_dimensions[0]): for column in range((block * block_dimensions[1]), (block * block_dimensions[1]) + block_dimensions[1]): # go through every pixel in the block and store the rgb values in their # respective lists. block_rgb[0].append(self.infile[row][column][0]) block_rgb[1].append(self.infile[row][column][1]) block_rgb[2].append(self.infile[row][column][2]) # find the average of the values in our rgb lists avg_of_red = sum(block_rgb[0]) // len(block_rgb[0]) avg_of_green = sum(block_rgb[1]) // len(block_rgb[1]) avg_of_blue = sum(block_rgb[2]) // len(block_rgb[2]) for row in range((block_row * block_dimensions[0]), (block_row * block_dimensions[0]) + block_dimensions[0]): for column in range((block * block_dimensions[1]), (block * block_dimensions[1]) + block_dimensions[1]): # go through every pixel in the block and change its rgb values self.infile[row][column][0] = avg_of_red self.infile[row][column][1] = avg_of_green self.infile[row][column][2] = avg_of_blue if returnable: return self.infile Image.fromarray(self.infile, "RGB").save(output_file) return None if __name__ == "__main__": PARSER = argparse.ArgumentParser(description='Manipulate an Image.') PARSER.add_argument('Infile', metavar='I', type=str, help='The file to have the operation performed on it.') PARSER.add_argument('Outfile', metavar='O', type=str, help="The name of the outfile from the script.") PARSER.add_argument("Operation", metavar="o", type=str, help='Which operation would you like performed? Options:' ' cr - clear all red;' ' cg - clear all green;' ' cb - clear all blue;' ' ro - make the image only shades of red;' ' go - make the image only shades of green;' ' bo - make the image only shades of blue;' ' lh - make colors all be in lower half;' ' uh - make colors all be in upper half;' ' gs - make the image gray-scale;' ' ic - invert the colors of the image;' ' bi - block the image in to same color cubes of pixels') ARGS = PARSER.parse_args() if ARGS.Operation not in ["cr", "cg", "cb", "ro", "go", "bo", "lh", "uh", "gs", "ic", "bi"]: print("Not a valid operation, please use the argument -h for extra help.") sys.exit() if ARGS.Operation == "cr": ImageO(ARGS.Infile).clear_red(ARGS.Outfile) elif ARGS.Operation == "cg": ImageO(ARGS.Infile).clear_green(ARGS.Outfile) elif ARGS.Operation == "cb": ImageO(ARGS.Infile).clear_blue(ARGS.Outfile) elif ARGS.Operation == "ro": ImageO(ARGS.Infile).red_only(ARGS.Outfile) elif ARGS.Operation == "go": ImageO(ARGS.Infile).green_only(ARGS.Outfile) elif ARGS.Operation == "bo": ImageO(ARGS.Infile).blue_only(ARGS.Outfile) elif ARGS.Operation == "lh": ImageO(ARGS.Infile).lower_half(ARGS.Outfile) elif ARGS.Operation == "uh": ImageO(ARGS.Infile).upper_half(ARGS.Outfile) elif ARGS.Operation == "gs": ImageO(ARGS.Infile).gray_scale(ARGS.Outfile) elif ARGS.Operation == "ic": ImageO(ARGS.Infile).invert_color(ARGS.Outfile) elif ARGS.Operation == "bi": ImageO(ARGS.Infile).block_image(ARGS.Outfile)	34.974654	97	0.564332	""" Manipulate images in specific ways based on commands used on input. This module is used in order to manipulate images in a number of ways. All of this is done through the ImageO object. The ImageO object reads in a file and allows for manipulations to be done on an image and for that image to be output after the manipulation. All different things this module allows for are: - make an image only all of its red values - make an image only all of its green values - make an image only all of its blue values - zero out all red values of an image - zero out all green values of an image - zero out all blue values of an image - darken an image by moving all values to be in the lower half of 255 - bright an image by moving all values to be in the upper half of 255 - make image in-to a gray-scaled image - invert the colors of an image - block or blur an image, making all pixel of a block the same rgb value All of these option can be called after importing and creating an ImageO object or from calling this module from the command line with the proper options. Joshua Shequin """ import argparse import sys import numpy as np from PIL import Image def common_denominator(number_one, number_two, range_one, range_two): """ Recursion solution to this problem even though it is not the best way of doing it. Base case is when the modulo of both numbers and the second range value is zero, or if they are the same. Parameters ---------- number_one : int the first number of the two numbers to find the common denominator between. number_two : int the second number of the two numbers to find the common denominator between. range_one : int the lowest integer for a range of values to find the common denominator in. range_two : int the highest integer for a range of values to find the common denominator in. Returns ------ Integer the value that the two input have number both have a denominator with, or the lowest int in the range given if no denominator was found. """ if number_one % range_two == 0 and number_two % range_two == 0: return range_two if range_one == range_two: return range_one return common_denominator(number_one, number_two, range_one, range_two-1) class ImageO: """ Object that handles images, allowing for a number of manipulations. Image object that takes an input file as the input and reads that input file and turns that image in to an array. From that array the object allows for a number of manipulations to be done to the image. Every manipulation also by default outputs the file. """ def __init__(self, input_file): """ Initialize the object by taking an input_file and loading the image to an array. Parameter --------- input_file : string string of the file location to be read, relative or full path. """ try: self.infile = np.array(Image.open(input_file)) # read in the file and store as a # numpy array. except FileNotFoundError: # if that file did not exist then we warn the user and close the program. print("Check your infile parameter, I can't find the file you put in!") sys.exit() def clear_red(self, output_file, returnable=False): """ Clear all red in our image. Parameter --------- output_file : string the name of the file we want to output to. Return ------ numpy array Return the numpy array of the image if returnable=True """ for row in self.infile: for column in row: column[0] = 0 if returnable: return self.infile Image.fromarray(self.infile, "RGB").save(output_file) return None def clear_green(self, output_file, returnable=False): """ Clear all green in our image. Parameter --------- output_file : string the name of the file we want to output to. Return ------ numpy array Return the numpy array of the image if returnable=True """ for row in self.infile: for column in row: column[1] = 0 if returnable: return self.infile Image.fromarray(self.infile, "RGB").save(output_file) return None def clear_blue(self, output_file, returnable=False): """ Clear all blue in our image. Parameter --------- output_file : string the name of the file we want to output to. Return ------ numpy array Return the numpy array of the image if returnable=True """ for row in self.infile: for column in row: column[2] = 0 if returnable: return self.infile Image.fromarray(self.infile, "RGB").save(output_file) return None def red_only(self, output_file, returnable=False): """ Clear all green and all blue of our image. Parameter --------- output_file : string the name of the file we want to output to. Return ------ numpy array Return the numpy array of the image if returnable=True """ for row in self.infile: for column in row: column[1] = 0 column[2] = 0 if returnable: return self.infile Image.fromarray(self.infile, "RGB").save(output_file) return None def green_only(self, output_file, returnable=False): """ Clear all red and all blue of our image. Parameter --------- output_file : string the name of the file we want to output to. Return ------ numpy array Return the numpy array of the image if returnable=True """ for row in self.infile: for column in row: column[0] = 0 column[2] = 0 if returnable: return self.infile Image.fromarray(self.infile, "RGB").save(output_file) return None def blue_only(self, output_file, returnable=False): """ Clear all red and all green of our image. Parameter --------- output_file : string the name of the file we want to output to. Return ------ numpy array Return the numpy array of the image if returnable=True """ for row in self.infile: for column in row: column[0] = 0 column[1] = 0 if returnable: return self.infile Image.fromarray(self.infile, "RGB").save(output_file) return None def lower_half(self, output_file, returnable=False): """ Scale all shades to be only in the lower 127 of color ints. Parameter --------- output_file : string the name of the file we want to output to. Return ------ numpy array Return the numpy array of the image if returnable=True """ for row in self.infile: for column in row: column[0] = column[0]/2 column[1] = column[1]/2 column[2] = column[2]/2 if returnable: return self.infile Image.fromarray(self.infile, "RGB").save(output_file) return None def upper_half(self, output_file, returnable=True): """ Scale all shades to be only in the upper 127 of color ints. Parameter --------- output_file : string the name of the file we want to output to. Return ------ numpy array Return the numpy array of the image if returnable=True """ for row in self.infile: for column in row: column[0] = column[0]/2 + 128 column[1] = column[1]/2 + 128 column[2] = column[2]/2 + 128 if returnable: return self.infile Image.fromarray(self.infile, "RGB").save(output_file) return None def gray_scale(self, output_file, returnable=False): """ Convert the image to a grey-scale image. Parameter --------- output_file : string the name of the file we want to output to. Return ------ numpy array Return the numpy array of the image if returnable=True """ for row in self.infile: for column in row: # to transform a pixel to its gray-scale form we find the average of the three # colors. new_value = (column[0](1/3)) + (column[1](1/3)) +\ (column[2](1/3)) column[0] = new_value column[1] = new_value column[2] = new_value if returnable: return self.infile Image.fromarray(self.infile, "RGB").save(output_file) return None def invert_color(self, output_file, returnable=False): """ Invert all rgb values of the image. Parameter --------- output_file : string the name of the file we want to output to. Return ------ numpy array Return the numpy array of the image if returnable=True """ for row in self.infile: for column in row: column[0] = 255 - column[0] column[1] = 255 - column[1] column[2] = 255 - column[2] if returnable: return self.infile Image.fromarray(self.infile, "RGB").save(output_file) return None def block_image(self, output_file, returnable=False): """ Blurs or blocks an image, assigning a block size for an image making all pixels the same. Calls the common_denominator function to find a common denominator within a range of two numbers for two numbers. This will be used to determine the block width and height. Parameter --------- output_file : string the name of the file we want to output to. Return ------ numpy array Return the numpy array of the image if returnable=True """ number_of_blocks = common_denominator(len(self.infile), len(self.infile[0]), 2, 100) block_dimensions = (len(self.infile)//number_of_blocks, len(self.infile[0])//number_of_blocks) for block_row in range(number_of_blocks): for block in range(number_of_blocks): block_rgb = [[], [], []] for row in range((block_row block_dimensions[0]), (block_row * block_dimensions[0]) + block_dimensions[0]): for column in range((block * block_dimensions[1]), (block * block_dimensions[1]) + block_dimensions[1]): # go through every pixel in the block and store the rgb values in their # respective lists. block_rgb[0].append(self.infile[row][column][0]) block_rgb[1].append(self.infile[row][column][1]) block_rgb[2].append(self.infile[row][column][2]) # find the average of the values in our rgb lists avg_of_red = sum(block_rgb[0]) // len(block_rgb[0]) avg_of_green = sum(block_rgb[1]) // len(block_rgb[1]) avg_of_blue = sum(block_rgb[2]) // len(block_rgb[2]) for row in range((block_row * block_dimensions[0]), (block_row * block_dimensions[0]) + block_dimensions[0]): for column in range((block * block_dimensions[1]), (block * block_dimensions[1]) + block_dimensions[1]): # go through every pixel in the block and change its rgb values self.infile[row][column][0] = avg_of_red self.infile[row][column][1] = avg_of_green self.infile[row][column][2] = avg_of_blue if returnable: return self.infile Image.fromarray(self.infile, "RGB").save(output_file) return None if __name__ == "__main__": PARSER = argparse.ArgumentParser(description='Manipulate an Image.') PARSER.add_argument('Infile', metavar='I', type=str, help='The file to have the operation performed on it.') PARSER.add_argument('Outfile', metavar='O', type=str, help="The name of the outfile from the script.") PARSER.add_argument("Operation", metavar="o", type=str, help='Which operation would you like performed? Options:' ' cr - clear all red;' ' cg - clear all green;' ' cb - clear all blue;' ' ro - make the image only shades of red;' ' go - make the image only shades of green;' ' bo - make the image only shades of blue;' ' lh - make colors all be in lower half;' ' uh - make colors all be in upper half;' ' gs - make the image gray-scale;' ' ic - invert the colors of the image;' ' bi - block the image in to same color cubes of pixels') ARGS = PARSER.parse_args() if ARGS.Operation not in ["cr", "cg", "cb", "ro", "go", "bo", "lh", "uh", "gs", "ic", "bi"]: print("Not a valid operation, please use the argument -h for extra help.") sys.exit() if ARGS.Operation == "cr": ImageO(ARGS.Infile).clear_red(ARGS.Outfile) elif ARGS.Operation == "cg": ImageO(ARGS.Infile).clear_green(ARGS.Outfile) elif ARGS.Operation == "cb": ImageO(ARGS.Infile).clear_blue(ARGS.Outfile) elif ARGS.Operation == "ro": ImageO(ARGS.Infile).red_only(ARGS.Outfile) elif ARGS.Operation == "go": ImageO(ARGS.Infile).green_only(ARGS.Outfile) elif ARGS.Operation == "bo": ImageO(ARGS.Infile).blue_only(ARGS.Outfile) elif ARGS.Operation == "lh": ImageO(ARGS.Infile).lower_half(ARGS.Outfile) elif ARGS.Operation == "uh": ImageO(ARGS.Infile).upper_half(ARGS.Outfile) elif ARGS.Operation == "gs": ImageO(ARGS.Infile).gray_scale(ARGS.Outfile) elif ARGS.Operation == "ic": ImageO(ARGS.Infile).invert_color(ARGS.Outfile) elif ARGS.Operation == "bi": ImageO(ARGS.Infile).block_image(ARGS.Outfile)	0	0	0
7c3bdfb9f4ce43de33608bfbdf36e0f48a3e90c4	1,067	py	Python	CorePython/Networking/TCP/tsTserv.py	AnatoleZho/Python3	3d3d32b5ad0affef76287b89bc87267fc551127d	[ "MIT" ]	null	null	null	CorePython/Networking/TCP/tsTserv.py	AnatoleZho/Python3	3d3d32b5ad0affef76287b89bc87267fc551127d	[ "MIT" ]	null	null	null	CorePython/Networking/TCP/tsTserv.py	AnatoleZho/Python3	3d3d32b5ad0affef76287b89bc87267fc551127d	[ "MIT" ]	null	null	null	# 导入了 time.ctime()和 socket 模块的所有属性 from socket import * from time import ctime HOST = '' # HOST 变量是空白的，这是对 bind()方法的标识，表示它可以使用任何可用的地址 PORT = 21567 # 选择了一个随机的端口号，并且该端口号似乎没有被使用或被系统保留 BZUGSIZ = 1024 # 对于该应用程序，将缓冲区大小设置为 1KB。可以根据网络性能和程序需要改变这个容量 ADDR = (HOST, PORT) tcpSerSock = socket(AF_INET, SOCK_STREAM) # 分配了 TCP 服务器套接字 tcpSerSock.bind(ADDR) # 将套接字绑定到服务器地址以及开启 TCP 监听器的调用 tcpSerSock.listen(5) # listen() 方法的参数是在连接被转接或拒绝之前，传入连接请求的最大数。 ''' # 一旦进入服务器的无限循环之中，就(被动地)等待客户端的连接。当一个连接请求出现时，进入对话循环中， # 在该循环中等待客户端发送的消息。如果消息是空白的，这意味着客户端已经退出，所以此时将跳出对话循环， # 关闭当前客户端连接，然后等待另一个客户端连接。如果确实得到了客户端发送的消息，就将其格式化并返回 # 相同的数据，但是会在这些数据中加上当前时间戳的前缀。最后一行永远不会执行，它只是用来提醒读者， # 如果写了一个处理程序来考虑一个更加优雅的退出方式，正如前面讨论的，那么应该调用 close()方法 ''' while True: print('waiting for connection...') tcpCliSock, addr = tcpSerSock.accept() print('...connected from:', addr) while True: data = tcpCliSock.recv(BZUGSIZ) if not data: break tcpCliSock.send(('[{}] {}'.format(ctime(), data.decode())).encode()) tcpCliSock.close() # tcpSerSock.close()	28.078947	76	0.716963	# 导入了 time.ctime()和 socket 模块的所有属性 from socket import * from time import ctime HOST = '' # HOST 变量是空白的，这是对 bind()方法的标识，表示它可以使用任何可用的地址 PORT = 21567 # 选择了一个随机的端口号，并且该端口号似乎没有被使用或被系统保留 BZUGSIZ = 1024 # 对于该应用程序，将缓冲区大小设置为 1KB。可以根据网络性能和程序需要改变这个容量 ADDR = (HOST, PORT) tcpSerSock = socket(AF_INET, SOCK_STREAM) # 分配了 TCP 服务器套接字 tcpSerSock.bind(ADDR) # 将套接字绑定到服务器地址以及开启 TCP 监听器的调用 tcpSerSock.listen(5) # listen() 方法的参数是在连接被转接或拒绝之前，传入连接请求的最大数。 ''' # 一旦进入服务器的无限循环之中，就(被动地)等待客户端的连接。当一个连接请求出现时，进入对话循环中， # 在该循环中等待客户端发送的消息。如果消息是空白的，这意味着客户端已经退出，所以此时将跳出对话循环， # 关闭当前客户端连接，然后等待另一个客户端连接。如果确实得到了客户端发送的消息，就将其格式化并返回 # 相同的数据，但是会在这些数据中加上当前时间戳的前缀。最后一行永远不会执行，它只是用来提醒读者， # 如果写了一个处理程序来考虑一个更加优雅的退出方式，正如前面讨论的，那么应该调用 close()方法 ''' while True: print('waiting for connection...') tcpCliSock, addr = tcpSerSock.accept() print('...connected from:', addr) while True: data = tcpCliSock.recv(BZUGSIZ) if not data: break tcpCliSock.send(('[{}] {}'.format(ctime(), data.decode())).encode()) tcpCliSock.close() # tcpSerSock.close()	0	0	0
232477d1a2e19b60e70bb78d55802171edcce92e	4,693	py	Python	members/conferences/models.py	ocwc/ocwc-members	3ede8e0ff830e2aaff4ae09f9aaefd3eaa83146b	[ "MIT" ]	null	null	null	members/conferences/models.py	ocwc/ocwc-members	3ede8e0ff830e2aaff4ae09f9aaefd3eaa83146b	[ "MIT" ]	7	2015-11-27T15:59:52.000Z	2022-01-13T00:38:38.000Z	members/conferences/models.py	ocwc/ocwc-members	3ede8e0ff830e2aaff4ae09f9aaefd3eaa83146b	[ "MIT" ]	null	null	null	# -- coding: utf-8 -- import uuid from tinymce import HTMLField from django.db import models from django.urls import reverse from django.core.mail import EmailMessage from django.conf import settings from django.contrib.postgres.fields import JSONField from crm.utils import print_pdf CONFERENCE_REGISTRATION_TYPE = ( ("normal", "Normal registration"), ("presenter", "Presenter registration"), )	32.590278	126	0.698061	# -- coding: utf-8 -- import uuid from tinymce import HTMLField from django.db import models from django.urls import reverse from django.core.mail import EmailMessage from django.conf import settings from django.contrib.postgres.fields import JSONField from crm.utils import print_pdf class ConferenceInterface(models.Model): name = models.CharField(max_length=255) url = models.CharField(max_length=255, default="") api_key = models.CharField(max_length=255, default="") private_key = models.CharField(max_length=255, default="") last_synced = models.DateTimeField(null=True) def __unicode__(self): return self.name class ConferenceRegistration(models.Model): PAYMENT_TYPE = (("paypal", "PayPal"), ("wire", "Wire Transfer")) interface = models.ForeignKey(ConferenceInterface, models.CASCADE) form_id = models.CharField(max_length=255) entry_id = models.CharField(max_length=255) entry_created = models.DateTimeField(null=True) name = models.CharField(max_length=255, default="") email = models.CharField(max_length=255, default="") organization = models.CharField(max_length=255, default="") billing_address = models.TextField(default="", blank=True) ticket_type = models.CharField(max_length=255) dinner_guest = models.CharField(max_length=255, default="", blank=True) dinner_guest_qty = models.IntegerField(default=0) conference_dinner = models.CharField(max_length=255, default="", blank=True) reception_guest = models.CharField(max_length=255, default="", blank=True) reception_guest_qty = models.IntegerField(default=0) total_amount = models.CharField(max_length=255) payment_type = models.CharField(choices=PAYMENT_TYPE, max_length=255) products = JSONField(blank=True, null=True) qbo_id = models.IntegerField(blank=True, null=True) source_url = models.CharField(max_length=255) billing_html = HTMLField(default="") product_html = models.TextField(default="") last_synced = models.DateTimeField(auto_now=True) access_key = models.CharField(max_length=32, blank=True) is_group = models.BooleanField(default=False) def save(self, force_insert=False, force_update=False, using=None): if not self.access_key: self.access_key = uuid.uuid4().hex super(ConferenceRegistration, self).save( force_insert=force_insert, force_update=force_update, using=using ) def get_access_key_url(self): return reverse( "conferences:invoice_preview", kwargs={"pk": self.id, "access_key": self.access_key}, ) def get_absolute_url(self): return "/conferences/#registration-{}".format(self.id) def email_invoice(self): body = """Thank you for registering for Open Education Global Conference 2018 (24-26 April in Delft, the Netherlands). Attached is your invoice. Do not hesitate to contact us at conference@oeglobal.org if you have any questions. We look forward to welcoming you in the Netherlands! Open Education Global Conference 2018 Planning Team. """ message = EmailMessage( subject="Open Education Global Conference 2018 - Invoice", body=body, from_email="conference@oeglobal.org", to=[self.email], # bcc = ['conference@oeglobal.org'] ) url = "%s%s" % (settings.INVOICES_PHANTOM_JS_HOST, self.get_access_key_url()) pdf_file = print_pdf(url) message.attach( filename="OEGlobal-Invoice-%s.pdf" % self.entry_id, content=pdf_file, mimetype="application/pdf", ) message.send() CONFERENCE_REGISTRATION_TYPE = ( ("normal", "Normal registration"), ("presenter", "Presenter registration"), ) class ConferenceEmailTemplate(models.Model): subject = models.CharField(max_length=255) body_text = models.TextField() body_html = models.TextField() email_type = models.CharField( choices=CONFERENCE_REGISTRATION_TYPE, default="normal", max_length=20 ) def __str__(self) -> str: return "{}".format(self.subject) class ConferenceEmailRegistration(models.Model): email = models.CharField(max_length=255) email_type = models.CharField( choices=CONFERENCE_REGISTRATION_TYPE, default="normal", max_length=20 ) def __str__(self) -> str: return "{} - {}".format(self.email, self.email_type) class ConferenceEmailLogs(models.Model): action = models.CharField(max_length=255) pub_date = models.DateTimeField(auto_now_add=True) def __str__(self) -> str: return "{}".format(self.action)	1,595	2,568	115
167b4b86ac839003f6f7230a884abb5014d92fce	9,100	py	Python	tests/test_types.py	krisHans3n/geoalchemy2-mysql	38a44d51c242d867f40d4c5503c91f52a8269ff4	[ "MIT" ]	1	2022-02-01T23:52:06.000Z	2022-02-01T23:52:06.000Z	tests/test_types.py	krisHans3n/geoalchemy2	604c1fcc824d243698ca46227fd05a8cbbb9db2c	[ "MIT" ]	null	null	null	tests/test_types.py	krisHans3n/geoalchemy2	604c1fcc824d243698ca46227fd05a8cbbb9db2c	[ "MIT" ]	null	null	null	import re import pytest from sqlalchemy import Column from sqlalchemy import MetaData from sqlalchemy import Table from sqlalchemy.sql import func from sqlalchemy.sql import insert from sqlalchemy.sql import text from geoalchemy2.exc import ArgumentError from geoalchemy2.types import Geography from geoalchemy2.types import Geometry from geoalchemy2.types import Raster from . import select @pytest.fixture @pytest.fixture @pytest.fixture	33.828996	92	0.661648	import re import pytest from sqlalchemy import Column from sqlalchemy import MetaData from sqlalchemy import Table from sqlalchemy.sql import func from sqlalchemy.sql import insert from sqlalchemy.sql import text from geoalchemy2.exc import ArgumentError from geoalchemy2.types import Geography from geoalchemy2.types import Geometry from geoalchemy2.types import Raster from . import select def eq_sql(a, b): a = re.sub(r'[\n\t]', '', str(a)) assert a == b @pytest.fixture def geometry_table(): table = Table('table', MetaData(), Column('geom', Geometry)) return table @pytest.fixture def geography_table(): table = Table('table', MetaData(), Column('geom', Geography)) return table @pytest.fixture def raster_table(): table = Table('table', MetaData(), Column('rast', Raster)) return table class TestGeometry(): def test_get_col_spec(self): g = Geometry(srid=900913) assert g.get_col_spec() == 'geometry(GEOMETRY,900913)' def test_get_col_spec_no_typmod(self): g = Geometry(geometry_type=None) assert g.get_col_spec() == 'geometry' def test_check_ctor_args_bad_srid(self): with pytest.raises(ArgumentError): Geometry(srid='foo') def test_get_col_spec_geometryzm(self): g = Geometry(geometry_type='GEOMETRYZM', srid=900913) assert g.get_col_spec() == 'geometry(GEOMETRYZM,900913)' def test_get_col_spec_geometryz(self): g = Geometry(geometry_type='GEOMETRYZ', srid=900913) assert g.get_col_spec() == 'geometry(GEOMETRYZ,900913)' def test_get_col_spec_geometrym(self): g = Geometry(geometry_type='GEOMETRYM', srid=900913) assert g.get_col_spec() == 'geometry(GEOMETRYM,900913)' def test_check_ctor_args_management_zm(self): with pytest.raises(ArgumentError): Geometry(geometry_type='POINTZM', management=True) def test_check_ctor_args_management_z(self): with pytest.raises(ArgumentError): Geometry(geometry_type='POINTZ', dimension=2, management=True) def test_check_ctor_args_management_m(self): with pytest.raises(ArgumentError): Geometry(geometry_type='POINTM', dimension=2, management=True) def test_check_ctor_args_incompatible_arguments(self): with pytest.raises(ArgumentError): Geometry(geometry_type=None, management=True) def test_check_ctor_args_srid_not_enforced(self): with pytest.warns(UserWarning): Geometry(geometry_type=None, srid=4326) def test_check_ctor_args_use_typmod_ignored(self): with pytest.warns(UserWarning): Geometry(management=False, use_typmod=True) def test_check_ctor_args_use_typmod_nullable(self): with pytest.warns(UserWarning, match="use_typmod ignored when management is False"): with pytest.raises( ArgumentError, match='The "nullable" and "use_typmod" arguments can not be used together', ): Geometry(use_typmod=True, nullable=False) def test_column_expression(self, geometry_table): s = select([geometry_table.c.geom]) eq_sql(s, 'SELECT ST_AsEWKB("table".geom) AS geom FROM "table"') def test_select_bind_expression(self, geometry_table): s = select([text('foo')]).where(geometry_table.c.geom == 'POINT(1 2)') eq_sql(s, 'SELECT foo FROM "table" WHERE ' '"table".geom = ST_GeomFromEWKT(:geom_1)') assert s.compile().params == {'geom_1': 'POINT(1 2)'} def test_insert_bind_expression(self, geometry_table): i = insert(geometry_table).values(geom='POINT(1 2)') eq_sql(i, 'INSERT INTO "table" (geom) VALUES (ST_GeomFromEWKT(:geom))') assert i.compile().params == {'geom': 'POINT(1 2)'} def test_function_call(self, geometry_table): s = select([geometry_table.c.geom.ST_Buffer(2)]) eq_sql(s, 'SELECT ST_AsEWKB(ST_Buffer("table".geom, :ST_Buffer_2)) ' 'AS "ST_Buffer_1" FROM "table"') def test_non_ST_function_call(self, geometry_table): with pytest.raises(AttributeError): geometry_table.c.geom.Buffer(2) def test_subquery(self, geometry_table): # test for geometry columns not delivered to the result # http://hg.sqlalchemy.org/sqlalchemy/rev/f1efb20c6d61 s = select([geometry_table]).alias('name').select() eq_sql(s, 'SELECT ST_AsEWKB(name.geom) AS geom FROM ' '(SELECT "table".geom AS geom FROM "table") AS name') class TestGeography(): def test_get_col_spec(self): g = Geography(srid=900913) assert g.get_col_spec() == 'geography(GEOMETRY,900913)' def test_get_col_spec_no_typmod(self): g = Geography(geometry_type=None) assert g.get_col_spec() == 'geography' def test_column_expression(self, geography_table): s = select([geography_table.c.geom]) eq_sql(s, 'SELECT ST_AsBinary("table".geom) AS geom FROM "table"') def test_select_bind_expression(self, geography_table): s = select([text('foo')]).where(geography_table.c.geom == 'POINT(1 2)') eq_sql(s, 'SELECT foo FROM "table" WHERE ' '"table".geom = ST_GeogFromText(:geom_1)') assert s.compile().params == {'geom_1': 'POINT(1 2)'} def test_insert_bind_expression(self, geography_table): i = insert(geography_table).values(geom='POINT(1 2)') eq_sql(i, 'INSERT INTO "table" (geom) VALUES (ST_GeogFromText(:geom))') assert i.compile().params == {'geom': 'POINT(1 2)'} def test_function_call(self, geography_table): s = select([geography_table.c.geom.ST_Buffer(2)]) eq_sql(s, 'SELECT ST_AsEWKB(ST_Buffer("table".geom, :ST_Buffer_2)) ' 'AS "ST_Buffer_1" FROM "table"') def test_non_ST_function_call(self, geography_table): with pytest.raises(AttributeError): geography_table.c.geom.Buffer(2) def test_subquery(self, geography_table): # test for geography columns not delivered to the result # http://hg.sqlalchemy.org/sqlalchemy/rev/f1efb20c6d61 s = select([geography_table]).alias('name').select() eq_sql(s, 'SELECT ST_AsBinary(name.geom) AS geom FROM ' '(SELECT "table".geom AS geom FROM "table") AS name') class TestPoint(): def test_get_col_spec(self): g = Geometry(geometry_type='POINT', srid=900913) assert g.get_col_spec() == 'geometry(POINT,900913)' class TestCurve(): def test_get_col_spec(self): g = Geometry(geometry_type='CURVE', srid=900913) assert g.get_col_spec() == 'geometry(CURVE,900913)' class TestLineString(): def test_get_col_spec(self): g = Geometry(geometry_type='LINESTRING', srid=900913) assert g.get_col_spec() == 'geometry(LINESTRING,900913)' class TestPolygon(): def test_get_col_spec(self): g = Geometry(geometry_type='POLYGON', srid=900913) assert g.get_col_spec() == 'geometry(POLYGON,900913)' class TestMultiPoint(): def test_get_col_spec(self): g = Geometry(geometry_type='MULTIPOINT', srid=900913) assert g.get_col_spec() == 'geometry(MULTIPOINT,900913)' class TestMultiLineString(): def test_get_col_spec(self): g = Geometry(geometry_type='MULTILINESTRING', srid=900913) assert g.get_col_spec() == 'geometry(MULTILINESTRING,900913)' class TestMultiPolygon(): def test_get_col_spec(self): g = Geometry(geometry_type='MULTIPOLYGON', srid=900913) assert g.get_col_spec() == 'geometry(MULTIPOLYGON,900913)' class TestGeometryCollection(): def test_get_col_spec(self): g = Geometry(geometry_type='GEOMETRYCOLLECTION', srid=900913) assert g.get_col_spec() == 'geometry(GEOMETRYCOLLECTION,900913)' class TestRaster(): def test_get_col_spec(self): r = Raster() assert r.get_col_spec() == 'raster' def test_column_expression(self, raster_table): s = select([raster_table.c.rast]) eq_sql(s, 'SELECT raster("table".rast) AS rast FROM "table"') def test_insert_bind_expression(self, raster_table): i = insert(raster_table).values(rast=b'\x01\x02') eq_sql(i, 'INSERT INTO "table" (rast) VALUES (raster(:rast))') assert i.compile().params == {'rast': b'\x01\x02'} def test_function_call(self, raster_table): s = select([raster_table.c.rast.ST_Height()]) eq_sql(s, 'SELECT ST_Height("table".rast) ' 'AS "ST_Height_1" FROM "table"') def test_non_ST_function_call(self, raster_table): with pytest.raises(AttributeError): raster_table.c.geom.Height() class TestCompositeType(): def test_ST_Dump(self, geography_table): s = select([func.ST_Dump(geography_table.c.geom).geom.label("geom")]) eq_sql(s, 'SELECT ST_AsEWKB((ST_Dump("table".geom)).geom) AS geom ' 'FROM "table"')	7,144	22	1,472
d1b306d3b99abe243693a2787b9aba3bf7abb9c1	4,187	py	Python	custom_components/googlehome/config_flow.py	Drakulix/googlehome	fb671679b25be51e08bdce066f281b8fb703199a	[ "Apache-2.0" ]	29	2019-09-06T06:15:34.000Z	2021-12-01T13:23:58.000Z	custom_components/googlehome/config_flow.py	Drakulix/googlehome	fb671679b25be51e08bdce066f281b8fb703199a	[ "Apache-2.0" ]	24	2019-09-06T08:37:34.000Z	2021-08-24T15:29:27.000Z	custom_components/googlehome/config_flow.py	Drakulix/googlehome	fb671679b25be51e08bdce066f281b8fb703199a	[ "Apache-2.0" ]	6	2019-09-11T01:41:13.000Z	2022-03-14T10:18:58.000Z	from homeassistant import config_entries from homeassistant.core import callback from collections import OrderedDict from .auth import get_master_token, get_access_token from .const import ( DOMAIN, CONF_USERNAME, CONF_PASSWORD, CONF_MASTER_TOKEN, CONF_DEVICE_TYPES, CONF_RSSI_THRESHOLD, CONF_TRACK_ALARMS, CONF_TRACK_DEVICES, CONF_TRACK_NEW_DEVICES, CONF_CONSIDER_HOME, DEFAULT_DEVICE_TYPES, DEFAULT_RSSI_THRESHOLD, ) from homeassistant.components.device_tracker.const import DEFAULT_CONSIDER_HOME, DEFAULT_TRACK_NEW import homeassistant.helpers.config_validation as cv import voluptuous as vol	40.650485	156	0.609983	from homeassistant import config_entries from homeassistant.core import callback from collections import OrderedDict from .auth import get_master_token, get_access_token from .const import ( DOMAIN, CONF_USERNAME, CONF_PASSWORD, CONF_MASTER_TOKEN, CONF_DEVICE_TYPES, CONF_RSSI_THRESHOLD, CONF_TRACK_ALARMS, CONF_TRACK_DEVICES, CONF_TRACK_NEW_DEVICES, CONF_CONSIDER_HOME, DEFAULT_DEVICE_TYPES, DEFAULT_RSSI_THRESHOLD, ) from homeassistant.components.device_tracker.const import DEFAULT_CONSIDER_HOME, DEFAULT_TRACK_NEW import homeassistant.helpers.config_validation as cv import voluptuous as vol class GoogleHomeConfigFlow(config_entries.ConfigFlow, domain=DOMAIN): VERSION = 1 CONNECTION_CLASS = config_entries.CONN_CLASS_LOCAL_POLL async def async_step_user(self, user_input=None): errors = {} if user_input is not None: if CONF_MASTER_TOKEN in user_input: at = await self.hass.async_add_executor_job( get_access_token, user_input[CONF_USERNAME], user_input[CONF_MASTER_TOKEN] ) if at is not None: return self.async_create_entry( title=user_input[CONF_USERNAME], data={ CONF_USERNAME: user_input[CONF_USERNAME], CONF_MASTER_TOKEN: user_input[CONF_MASTER_TOKEN], }, ) else: errors["base"] = "master_token_incorrect" else: mt = await self.hass.async_add_executor_job( get_master_token, user_input[CONF_USERNAME], user_input[CONF_PASSWORD] ) if mt is not None: return self.async_create_entry( title=user_input[CONF_USERNAME], data={ CONF_USERNAME: user_input[CONF_USERNAME], CONF_MASTER_TOKEN: mt, }, ) else: errors["base"] = "auth_error" data_schema = OrderedDict() data_schema[vol.Required(CONF_USERNAME)] = str data_schema[vol.Required(CONF_PASSWORD)] = str data_schema[vol.Optional(CONF_MASTER_TOKEN)] = str return self.async_show_form( step_id="user", data_schema=vol.Schema(data_schema), errors=errors ) @staticmethod @callback def async_get_options_flow(config_entry): return GoogleHomeOptionsFlow(config_entry) class GoogleHomeOptionsFlow(config_entries.OptionsFlow): def __init__(self, config_entry): self.config_entry = config_entry async def async_step_init(self, user_input=None): """Manage the options.""" if user_input is not None: return self.async_create_entry(title=self.config_entry.data[CONF_USERNAME], data=user_input) return self.async_show_form( step_id="init", data_schema=vol.Schema( { vol.Required(CONF_TRACK_ALARMS, default=self.config_entry.options.get(CONF_TRACK_ALARMS, False)): bool, vol.Required(CONF_TRACK_DEVICES, default=self.config_entry.options.get(CONF_TRACK_DEVICES, True)): bool, #vol.Required(CONF_TRACK_NEW_DEVICES, default=self.config_entry.options.get(CONF_TRACK_NEW_DEVICES, DEFAULT_TRACK_NEW)): bool, vol.Required(CONF_CONSIDER_HOME, default=self.config_entry.options.get(CONF_CONSIDER_HOME, DEFAULT_CONSIDER_HOME.total_seconds())): int, vol.Required( CONF_RSSI_THRESHOLD, default=self.config_entry.options.get(CONF_RSSI_THRESHOLD, DEFAULT_RSSI_THRESHOLD), ): int, #vol.Required( # CONF_DEVICE_TYPES, # default=self.config_entry.data.get(CONF_DEVICE_TYPES, DEFAULT_DEVICE_TYPES), #): [vol.In(DEFAULT_DEVICE_TYPES)], } ), )	1,823	1,672	46
6cafd7462c73dfa3da9224d6445ae29d17212194	5,913	py	Python	mmdet/core/visualization/TensorboardLoggerHookV2.py	flyingTan/QuantMmdetection	6126cd7725dcd0c4d3ad68f016908c500a0adbb9	[ "Apache-2.0" ]	2	2021-08-28T06:43:03.000Z	2022-01-17T00:04:23.000Z	mmdet/core/visualization/TensorboardLoggerHookV2.py	flyingTan/QuantMmdetection	6126cd7725dcd0c4d3ad68f016908c500a0adbb9	[ "Apache-2.0" ]	null	null	null	mmdet/core/visualization/TensorboardLoggerHookV2.py	flyingTan/QuantMmdetection	6126cd7725dcd0c4d3ad68f016908c500a0adbb9	[ "Apache-2.0" ]	null	null	null	import os.path as osp from mmcv.utils import TORCH_VERSION from mmcv.runner.dist_utils import master_only from mmcv.runner import HOOKS from torch.utils.data import DataLoader from mmcv.runner.hooks.logger import LoggerHook import torch import numpy as np from .utils import CompareMultiLayerDist @HOOKS.register_module()	45.137405	141	0.561813	import os.path as osp from mmcv.utils import TORCH_VERSION from mmcv.runner.dist_utils import master_only from mmcv.runner import HOOKS from torch.utils.data import DataLoader from mmcv.runner.hooks.logger import LoggerHook import torch import numpy as np from .utils import CompareMultiLayerDist @HOOKS.register_module() class TensorboardLoggerHookV2(LoggerHook): def __init__(self, log_dir=None, interval=10, ignore_last=True, reset_flag=True, by_epoch=True, weight_vis_interval = 1, by_iter=False, cmp_multilayer_dist = False): super(TensorboardLoggerHookV2, self).__init__(interval, ignore_last, reset_flag, by_epoch) self.log_dir = log_dir self.weight_vis_interval = weight_vis_interval self.by_iter = by_iter self.cmp_multilayer_dist = cmp_multilayer_dist self.drawers = [] if self.cmp_multilayer_dist: self.drawers.append(CompareMultiLayerDist()) @master_only def before_run(self, runner): if TORCH_VERSION < '1.1' or TORCH_VERSION == 'parrots': try: from tensorboardX import SummaryWriter except ImportError: raise ImportError('Please install tensorboardX to use ' 'TensorboardLoggerHook.') else: try: from torch.utils.tensorboard import SummaryWriter except ImportError: raise ImportError( 'Please run "pip install future tensorboard" to install ' 'the dependencies to use torch.utils.tensorboard ' '(applicable to PyTorch 1.1 or higher)') if self.log_dir is None: self.log_dir = osp.join(runner.work_dir, 'tf_logs') self.writer = SummaryWriter(self.log_dir) ## TODO : Show Network Structure #self.writer.add_graph(runner.model, # {'img': torch.rand((1,3,224,224)), # 'gt_label':torch.tensor([1], dtype = torch.int)}) @master_only def log(self, runner): r""" This can be used by: after_train_iter, after_train_epoch This just for record lr, losss, top1, top5, and etc. """ tags = self.get_loggable_tags(runner, allow_text=True) for tag, val in tags.items(): if isinstance(val, str): self.writer.add_text(tag, val, self.get_iter(runner)) else: self.writer.add_scalar(tag, val, self.get_iter(runner)) @master_only def after_train_epoch(self, runner): r""" Fisrt Part: record logger info, such as: lr, losss, top1, top5, and etc. Second Part: staticstic weights distribution or gradient distribution. u can implement anything u want. JUST DO IT! """ if runner.log_buffer.ready: self.log(runner) if self.reset_flag: runner.log_buffer.clear_output() ## Default drawers if runner.mode == 'train' and self.every_n_epochs(runner, self.weight_vis_interval): for name, param in runner.model.named_parameters(): if 'bn' not in name: if not param.numel() == 1: # Tensor self.writer.add_histogram('model_by_epoch/' + name, param, self.get_epoch(runner)) if hasattr(param, "grad") and param.grad is not None: self.writer.add_histogram('model_by_epoch/' + name + "_grad", param.grad, self.get_epoch(runner)) else: self.writer.add_scalar('model_by_epoch/' + name, param, self.get_epoch(runner)) if hasattr(param, "grad") and param.grad is not None: self.writer.add_scalar('model_by_epoch/' + name + "_grad", param.grad, self.get_epoch(runner)) ## Customer Drawers list for draw in self.drawers: draw(self.writer, runner) @master_only def after_run(self, runner): self.writer.close() def after_train_iter(self, runner): def get_global_iter(runner): return runner.epoch * len(runner.data_loader) + runner.inner_iter def every_n_global_iter(runner, n): return (get_global_iter(runner) + 1 ) % n == 0 if n > 0 else False super(TensorboardLoggerHookV2, self).after_train_iter(runner) ### 2. Draw Model Paras: such as weights, bias, and etc parameters distribution. if runner.mode == 'train' and \ self.by_iter and \ hasattr(self, 'writer') and \ every_n_global_iter(runner, self.interval): for name, param in runner.model.named_parameters(): if 'bn' not in name: if not param.numel() == 1: # Tensor self.writer.add_histogram('model_by_iter/' + name, param, get_global_iter(runner) + 1) if hasattr(param, "grad") and param.grad is not None: self.writer.add_histogram('model_by_iter/' + name + "_grad", param.grad, get_global_iter(runner) + 1) else: # Scalar self.writer.add_scalar('model_by_iter/' + name, param.flatten(), get_global_iter(runner) + 1) if hasattr(param, "grad") and param.grad is not None: self.writer.add_scalar('model_by_iter/' + name + "_grad", param.grad.flatten(), get_global_iter(runner) + 1)	3,328	2,241	22
061f629d484ea9933b245faef68b08783aae52d0	594	py	Python	classifier/classes/modules/text/transformer/ModelTransformer.py	canary-for-cognition/multimodal-dl-framework	54ebd3c6dcdfc48ed619316321d9f0e7a5f0fc9c	[ "MIT" ]	2	2021-08-31T08:58:30.000Z	2021-09-02T14:32:30.000Z	classifier/classes/modules/text/transformer/ModelTransformer.py	canary-for-cognition/multimodal-nn-framework	7733376b05840e2b3dead438dd3981db9694b6ae	[ "MIT" ]	5	2020-09-22T04:29:25.000Z	2020-12-20T16:16:47.000Z	classifier/classes/modules/text/transformer/ModelTransformer.py	canary-for-cognition/multimodal-nn-framework	7733376b05840e2b3dead438dd3981db9694b6ae	[ "MIT" ]	1	2021-02-09T18:40:55.000Z	2021-02-09T18:40:55.000Z	from typing import Dict, Tuple import torch from classifier.classes.core.Model import Model from classifier.classes.modules.text.transformer.Transformer import Transformer	31.263158	79	0.727273	from typing import Dict, Tuple import torch from classifier.classes.core.Model import Model from classifier.classes.modules.text.transformer.Transformer import Transformer class ModelTransformer(Model): def __init__(self, network_params: Dict): super().__init__(device=network_params["device"]) self._network = Transformer(network_params).float().to(self._device) def predict(self, x: Tuple, **kwargs) -> torch.Tensor: input_ids = x[0].to(self._device) attention_mask = x[1].to(self._device) return self._network(input_ids, attention_mask)	333	9	77
dc8e765a423050be4a0f0acf7bd19d9cf552b8fa	892	py	Python	src/jvm/io/fsq/twofishes/scripts/fetch_and_fix_flickr.py	jglesner/fsqio	436dd3a7667fd23f638bf96bdcd9ec83266a2319	[ "Apache-2.0" ]	252	2016-01-08T23:12:13.000Z	2022-01-17T16:31:49.000Z	src/jvm/io/fsq/twofishes/scripts/fetch_and_fix_flickr.py	jglesner/fsqio	436dd3a7667fd23f638bf96bdcd9ec83266a2319	[ "Apache-2.0" ]	67	2016-01-13T17:34:12.000Z	2021-08-04T18:50:24.000Z	src/jvm/io/fsq/twofishes/scripts/fetch_and_fix_flickr.py	jglesner/fsqio	436dd3a7667fd23f638bf96bdcd9ec83266a2319	[ "Apache-2.0" ]	59	2016-03-25T20:49:03.000Z	2021-08-04T05:36:38.000Z	#!/usr/bin/env python import tarfile import urllib import re import StringIO import os basedir = 'src/jvm/io/fsq/twofishes/indexer/data/downloaded' flickr_shapes_file_name = os.path.join(basedir, 'flickr_shapes_public_dataset_2.0.tar.gz') try: open(flickr_shapes_file_name) except IOError as e: print 'Downloading Flickr Shapes File to %s' % flickr_shapes_file_name urllib.urlretrieve ('http://www.flickr.com/services/shapefiles/2.0/', flickr_shapes_file_name) print 'done downloading' old_tar = tarfile.open(flickr_shapes_file_name) for file_info in old_tar: print 'Processing %s' % file_info.name old_data = old_tar.extractfile(file_info.name).read() p = re.compile(',(\s+})') new_data = p.sub('\\1', old_data) print 'Writing updated %s' % file_info.name new_file = open(os.path.join(basedir, file_info.name), "w") new_file.write(new_data) new_file.close()	24.777778	96	0.751121	#!/usr/bin/env python import tarfile import urllib import re import StringIO import os basedir = 'src/jvm/io/fsq/twofishes/indexer/data/downloaded' flickr_shapes_file_name = os.path.join(basedir, 'flickr_shapes_public_dataset_2.0.tar.gz') try: open(flickr_shapes_file_name) except IOError as e: print 'Downloading Flickr Shapes File to %s' % flickr_shapes_file_name urllib.urlretrieve ('http://www.flickr.com/services/shapefiles/2.0/', flickr_shapes_file_name) print 'done downloading' old_tar = tarfile.open(flickr_shapes_file_name) for file_info in old_tar: print 'Processing %s' % file_info.name old_data = old_tar.extractfile(file_info.name).read() p = re.compile(',(\s+})') new_data = p.sub('\\1', old_data) print 'Writing updated %s' % file_info.name new_file = open(os.path.join(basedir, file_info.name), "w") new_file.write(new_data) new_file.close()	0	0	0
6ea13b23e201409046ac5f8b79ed0cf75e2bf2f7	559	py	Python	src/db/storage.py	BernarBerdikul/Async_API_part_1	0f218f38d099909fad629f6f9443fea4a29be3f8	[ "BSD-3-Clause" ]	null	null	null	src/db/storage.py	BernarBerdikul/Async_API_part_1	0f218f38d099909fad629f6f9443fea4a29be3f8	[ "BSD-3-Clause" ]	null	null	null	src/db/storage.py	BernarBerdikul/Async_API_part_1	0f218f38d099909fad629f6f9443fea4a29be3f8	[ "BSD-3-Clause" ]	null	null	null	from abc import ABC, abstractmethod from typing import Optional storage: Optional[AbstractStorage] = None # Функция понадобится при внедрении зависимостей	19.964286	54	0.697674	from abc import ABC, abstractmethod from typing import Optional class AbstractStorage(ABC): def __init__(self, storage_instance): self.storage = storage_instance @abstractmethod def get(self, index: str, target_id: str): pass @abstractmethod def search(self, index: str, _source, body, sort): pass @abstractmethod def close(self): pass storage: Optional[AbstractStorage] = None # Функция понадобится при внедрении зависимостей async def get_storage() -> AbstractStorage: return storage	181	173	45
55c7798fee43dcc97a6cfd5cbe15725d9078c8d0	8,714	py	Python	convnet3d/bin/train.py	yecharlie/convnet3d	0b2771eec149b196ef59b58d09eef71c9b201d40	[ "MIT" ]	6	2020-03-12T10:28:41.000Z	2021-11-18T16:17:20.000Z	convnet3d/bin/train.py	yecharlie/convnet3d	0b2771eec149b196ef59b58d09eef71c9b201d40	[ "MIT" ]	null	null	null	convnet3d/bin/train.py	yecharlie/convnet3d	0b2771eec149b196ef59b58d09eef71c9b201d40	[ "MIT" ]	1	2019-08-01T02:50:05.000Z	2019-08-01T02:50:05.000Z	import argparse import os import sys import keras import tensorflow as tf # print(__name__,'__package__:',__package__) if __name__ == "__main__" and __package__ is None: sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..')) import convnet3d.bin # noqa: F401 __package__ = "convnet3d.bin" from .. import models from .. import losses from ..preprocessing.generator import Generator from ..preprocessing.val_generator import ValidationGenerator from ..utils.transform import randomTransformGenerator from ..callbacks import (RedirectModel, Evaluate) def get_session(): '''Construct a modified tf session ''' # config = tf.ConfigProto(allow_soft_placement=True, log_device_placement=True) config = tf.ConfigProto() config.gpu_options.allow_growth = True return tf.Session(config=config) def parse_args(args): '''Parse the arguments ''' parser = argparse.ArgumentParser(description='Simple training script for training the candidate screening model & false positive reduction model.') subparsers = parser.add_subparsers(help='Specitic the model type: cs/fpr.', dest='model_type') subparsers.required = True cs_parser = subparsers.add_parser('cs') # noqa: F841 fpr_parser = subparsers.add_parser('fpr') fpr_parser.add_argument('--val-cs-model', help='Path to candidate screening model, then the two model are combined to biuld a convnet3d model for validation.') group = parser.add_mutually_exclusive_group() group.add_argument('--snapshot') group.add_argument('--no-weights', dest='val_cs_weights', action='store_const', const=False) group.add_argument('--val-cs-weights', action='store_true') parser.add_argument('annotations') parser.add_argument('classes') parser.add_argument('--val-annotations') parser.add_argument('--batch-size', type=int, default=32) parser.add_argument('--epochs', type=int, default=50) parser.add_argument('--gpu', metavar='GPUs', type=devices, default=None) parser.add_argument('--snapshot-path', default='./snapshots') parser.add_argument('--tensorboard-dir', default='./logs') parser.add_argument('--no-snapshots', dest='snapshots', action='store_false') parser.add_argument('--random-transform', action='store_true') parser.add_argument('--data-channels', default=1, type=int) return check_args(parser.parse_args(args)) if __name__ == '__main__': main()	34.039063	163	0.641726	import argparse import os import sys import keras import tensorflow as tf # print(__name__,'__package__:',__package__) if __name__ == "__main__" and __package__ is None: sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..')) import convnet3d.bin # noqa: F401 __package__ = "convnet3d.bin" from .. import models from .. import losses from ..preprocessing.generator import Generator from ..preprocessing.val_generator import ValidationGenerator from ..utils.transform import randomTransformGenerator from ..callbacks import (RedirectModel, Evaluate) def get_session(): '''Construct a modified tf session ''' # config = tf.ConfigProto(allow_soft_placement=True, log_device_placement=True) config = tf.ConfigProto() config.gpu_options.allow_growth = True return tf.Session(config=config) def create_generators(args): if args.random_transform: transform_generator = randomTransformGenerator( min_scaling = (0.9, 0.9, 0.9), max_scaling = (1.1, 1.1, 1.1), min_horizontal_rotation = -0.1, max_horizontal_rotation = 0.1, flip_x_chance = 0.5, flip_y_chance = 0.5, min_translation = (-0.1, -0.1, -0.1), max_translation = (0.1, 0.1, 0.1) ) else: transform_generator = None train_generator = Generator( args.annotations, args.classes, batch_size = args.batch_size, transform_generator=transform_generator ) if args.val_annotations and getattr(args, 'val_cs_model', None): validation_generator = ValidationGenerator( args.val_annotations, args.classes ) elif args.val_annotations: validation_generator = Generator( args.val_annotations, args.classes, batch_size = args.batch_size ) else: validation_generator = None return train_generator, validation_generator def create_models(num_classes, args): if args.model_type == 'cs': model = models.detectionModel(num_classes = num_classes, input_feature_size = args.data_channels) detections = model.outputs[0] reshaped = keras.layers.Reshape((num_classes,), name='classification' )(detections) training_model = keras.models.Model(inputs=model.inputs, outputs=reshaped) prediction_model = training_model training_model.compile( loss={'classification' : losses.detectionLossOHEM()}, optimizer=keras.optimizers.adam(lr=1e-5, clipnorm=0.001) ) elif args.model_type == 'fpr': if args.val_cs_weights: # initiate fpr model with cs model weights model = models.reductionModel1b(num_classes = num_classes, input_feature_size = args.data_channels, cs_model_path=args.val_cs_model) else: model = models.reductionModel1b(num_classes = num_classes, input_feature_size = args.data_channels) training_model = model # prediction_model = model if args.val_cs_model and args.val_annotations: cs_model = models.loadModel(args.val_cs_model) prediction_model = models.convnet3dModel1b(model, cs_model) else: prediction_model = model training_model.compile( loss={ 'classification' : keras.losses.sparse_categorical_crossentropy }, optimizer=keras.optimizers.adam(lr=1e-5, clipnorm=0.001) ) return model, training_model, prediction_model def create_callbacks(model, training_model, prediction_model, validation_generator, args): callbacks = [] if args.snapshots: os.makedirs(args.snapshot_path, exist_ok=True) checkpoint = keras.callbacks.ModelCheckpoint( os.path.join( args.snapshot_path, '{model_type}_{{epoch:02d}}.h5'.format(model_type=args.model_type) ), verbose=1 ) checkpoint = RedirectModel(checkpoint, model) callbacks.append(checkpoint) tensorboard_callback = None if args.tensorboard_dir: tensorboard_callback = keras.callbacks.TensorBoard( log_dir = args.tensorboard_dir, histogram_freq = 0, batch_size = args.batch_size, write_graph = True, write_grads = False, write_images = False, embeddings_freq = 0, embeddings_layer_names = None, embeddings_metadata = None ) callbacks.append(tensorboard_callback) if args.val_annotations: if args.model_type == 'cs': evaluation = Evaluate(validation_generator, mode='recall', tensorboard=tensorboard_callback) elif args.val_cs_model: evaluation = Evaluate( validation_generator, mode='mAP', tensorboard=tensorboard_callback, window_size = (25, 60, 60), sliding_strides = (13, 30, 30), nms=True ) else: evaluation = Evaluate(validation_generator, mode='accuracy', tensorboard=tensorboard_callback) evaluation = RedirectModel(evaluation, prediction_model) callbacks.append(evaluation) callbacks.append(keras.callbacks.ReduceLROnPlateau( monitor = 'loss', factor = 0.1, patience = 2, verbose = 1, mode = 'auto', epsilon = 0.0001, cooldown = 0, min_lr = 0 )) return callbacks def parse_args(args): '''Parse the arguments ''' parser = argparse.ArgumentParser(description='Simple training script for training the candidate screening model & false positive reduction model.') subparsers = parser.add_subparsers(help='Specitic the model type: cs/fpr.', dest='model_type') subparsers.required = True cs_parser = subparsers.add_parser('cs') # noqa: F841 fpr_parser = subparsers.add_parser('fpr') fpr_parser.add_argument('--val-cs-model', help='Path to candidate screening model, then the two model are combined to biuld a convnet3d model for validation.') group = parser.add_mutually_exclusive_group() group.add_argument('--snapshot') group.add_argument('--no-weights', dest='val_cs_weights', action='store_const', const=False) group.add_argument('--val-cs-weights', action='store_true') parser.add_argument('annotations') parser.add_argument('classes') parser.add_argument('--val-annotations') parser.add_argument('--batch-size', type=int, default=32) parser.add_argument('--epochs', type=int, default=50) def devices(string): return string.split(',') parser.add_argument('--gpu', metavar='GPUs', type=devices, default=None) parser.add_argument('--snapshot-path', default='./snapshots') parser.add_argument('--tensorboard-dir', default='./logs') parser.add_argument('--no-snapshots', dest='snapshots', action='store_false') parser.add_argument('--random-transform', action='store_true') parser.add_argument('--data-channels', default=1, type=int) return check_args(parser.parse_args(args)) def check_args(parsed_args): if parsed_args.val_cs_weights: if parsed_args.model_type == 'cs': raise ValueError( '"--val-cs-model" is an option for fpr model only. ') elif not parsed_args.val_cs_model: raise ValueError( 'Validation cs model has not benn set yet. (See "--val-cs-model")') return parsed_args def main(args=None): if args is None: args = sys.argv[1:] args = parse_args(args) if args.gpu: os.environ['CUDA_VISIBLE_DEVICES'] = args.gpu[0] keras.backend.tensorflow_backend.set_session(get_session()) train_generator, validation_generator = create_generators(args) if args.snapshot is not None: raise NotImplementedError('Snapshot option is unsupported now.') else: print('Creating model, this may take a second...') model, training_model, prediction_model = create_models( num_classes = train_generator.numClasses(), args = args ) print(model.summary()) callbacks = create_callbacks( model, training_model, prediction_model, validation_generator, args ) # training training_model.fit_generator( generator=train_generator, epochs=args.epochs, verbose=1, callbacks=callbacks ) if __name__ == '__main__': main()	6,119	0	142
373d0db4da6950d1bc8a4dabb4dea5dbcd544cf5	1,587	py	Python	pipeline_win.py	AndresRubianoM/DataScrapping	2523cd848939992ac4c01534fd0e45ad2ff7f179	[ "MIT" ]	null	null	null	pipeline_win.py	AndresRubianoM/DataScrapping	2523cd848939992ac4c01534fd0e45ad2ff7f179	[ "MIT" ]	null	null	null	pipeline_win.py	AndresRubianoM/DataScrapping	2523cd848939992ac4c01534fd0e45ad2ff7f179	[ "MIT" ]	null	null	null	import logging import subprocess logging.basicConfig(level = logging.INFO) logger = logging.getLogger(__name__) news_sites_uid = ['elpais'] if __name__ == '__main__': main()	32.387755	142	0.676118	import logging import subprocess logging.basicConfig(level = logging.INFO) logger = logging.getLogger(__name__) news_sites_uid = ['elpais'] def main(): _extract() _tranform() _load() def _extract(): logger.info('Beginning the extract process') for new_site_uid in news_sites_uid: #Commands to automatizate the cmd operations subprocess.run(['python', 'main.py', new_site_uid], cwd = '.\extract') #execute main.py to extract the data subprocess.run(['move', '.\extract\*.csv', '.\Transform\{}_.csv'.format(new_site_uid)], shell = True) #Find all the files and move it def _tranform(): logger.info('Starting transform process') for new_site_uid in news_sites_uid: dirty_data_filename = '{}_.csv'.format(new_site_uid) clean_data_filename = 'clean_{}'.format(dirty_data_filename) subprocess.run(['python', 'newspaper_recipe.py', dirty_data_filename], cwd = '.\Transform') #execute the newspaper_recipe.py subprocess.run(['del', '.\Transform\{}'.format(dirty_data_filename)], shell = True) subprocess.run(['move', '.\Transform\{}'.format(clean_data_filename), '.\load\{}.csv'.format(new_site_uid)], shell = True) def _load(): logger.info('Starting load process') for new_site_uid in news_sites_uid: clean_data_filename = '{}.csv'.format(new_site_uid) subprocess.run(['python', 'save_data.py', clean_data_filename], cwd = '.\load') subprocess.run(['del', '.\load\{}'.format(clean_data_filename)], shell = True) if __name__ == '__main__': main()	1,308	0	92
b32bd4bfe56139d124371a82bdf53c931c3b5161	15,332	py	Python	vlc-ios-3.0.3/Tools/update_strings.py	qq644531343/vlc-ios	c12421e1d9842f268e3cb64518dd0e0dca32db3c	[ "Apache-2.0" ]	null	null	null	vlc-ios-3.0.3/Tools/update_strings.py	qq644531343/vlc-ios	c12421e1d9842f268e3cb64518dd0e0dca32db3c	[ "Apache-2.0" ]	null	null	null	vlc-ios-3.0.3/Tools/update_strings.py	qq644531343/vlc-ios	c12421e1d9842f268e3cb64518dd0e0dca32db3c	[ "Apache-2.0" ]	null	null	null	#!/usr/bin/env python # -- coding: utf-8 -- ''' Update or create an Apple XCode project localization strings file. TODO: handle localization domains ''' from __future__ import with_statement import sys import os import os.path import re import tempfile import subprocess import codecs import unittest import optparse import shutil import logging ENCODINGS = ['utf16', 'utf8'] class LocalizedString(object): ''' A localized string from a strings file ''' COMMENT_EXPR = re.compile( # Line start '^\w' # Comment '/\ (?P<comment>.+) \/' # End of line '\w$' ) LOCALIZED_STRING_EXPR = re.compile( # Line start '^' # Key '"(?P<key>.+)"' # Equals ' ?= ?' # Value '"(?P<value>.+)"' # Whitespace ';' # Comment '(?: /\* (?P<comment>.+) \/)?' # End of line '$' ) @classmethod def parse_comment(cls, comment): ''' Extract the content of a comment line from a strings file. Returns the comment string or None if the line doesn't match. ''' result = cls.COMMENT_EXPR.match(comment) if result != None: return result.group('comment') else: return None @classmethod def from_line(cls, line): ''' Extract the content of a string line from a strings file. Returns a LocalizedString instance or None if the line doesn't match. TODO: handle whitespace restore ''' result = cls.LOCALIZED_STRING_EXPR.match(line) if result != None: return cls( result.group('key'), result.group('value'), result.group('comment') ) else: return None def is_raw(self): ''' Return True if the localized string has not been translated. ''' return self.value == self.key def strings_from_folder(folder_path, extensions=None, exclude=None): ''' Recursively scan folder_path for files containing localizable strings. Run genstrings on these files and extract the strings. Returns a dictionnary of LocalizedString instances, indexed by key. ''' localized_strings = {} code_file_paths = [] if extensions == None: extensions = frozenset(['m', 'mm']) if exclude == None: exclude = frozenset(['ImportedSources','Pods']) logging.debug('Scanning for source files in %s', folder_path) for dir_path, dir_names, file_names in os.walk(folder_path): dir_names[:] = [d for d in dir_names if d not in exclude] for file_name in file_names: extension = file_name.rpartition('.')[2] if extension in extensions: code_file_path = os.path.join(dir_path, file_name) code_file_paths.append(code_file_path) logging.debug('Found %d files', len(code_file_paths)) logging.debug('Running genstrings') temp_folder_path = tempfile.mkdtemp() arguments = ['genstrings', '-u', '-o', temp_folder_path] arguments.extend(code_file_paths) logging.debug('Here are the argumengts %s', arguments) subprocess.call(arguments) temp_file_path = os.path.join(temp_folder_path, 'Localizable.strings') if os.path.exists(temp_file_path): logging.debug('Analysing genstrings content') localized_strings = strings_from_file(temp_file_path) os.remove(temp_file_path) else: logging.debug('No translations found') shutil.rmtree(temp_folder_path) return localized_strings def strings_from_file(file_path): ''' Try to autodetect file encoding and call strings_from_encoded_file on the file at file_path. Returns a dictionnary of LocalizedString instances, indexed by key. Returns an empty dictionnary if the encoding is wrong. ''' for current_encoding in ENCODINGS: try: return strings_from_encoded_file(file_path, current_encoding) except UnicodeError: pass logging.error( 'Cannot determine encoding for file %s among %s', file_path, ', '.join(ENCODINGS) ) return {} def strings_from_encoded_file(file_path, encoding): ''' Extract the strings from the file at file_path. Returns a dictionnary of LocalizedString instances, indexed by key. ''' localized_strings = {} with codecs.open(file_path, 'r', encoding) as content: comment = None for line in content: line = line.strip() if not line: comment = None continue current_comment = LocalizedString.parse_comment(line) if current_comment: if current_comment != 'No comment provided by engineer.': comment = current_comment continue localized_string = LocalizedString.from_line(line) if localized_string: if not localized_string.comment: localized_string.comment = comment localized_strings[localized_string.key] = localized_string else: logging.error('Could not parse: %s', line.strip()) return localized_strings def strings_to_file(localized_strings, file_path, encoding='utf16'): ''' Write a strings file at file_path containing string in the localized_strings dictionnary. The strings are alphabetically sorted. ''' with codecs.open(file_path, 'w', encoding) as output: for localized_string in sorted_strings_from_dict(localized_strings): output.write('%s\n' % localized_string) def update_file_with_strings(file_path, localized_strings): ''' Try to autodetect file encoding and call update_encoded_file_with_strings on the file at file_path. The file at file_path must exist or this function will raise an exception. ''' for current_encoding in ENCODINGS: try: return update_encoded_file_with_strings( file_path, localized_strings, current_encoding ) except UnicodeError: pass logging.error( 'Cannot determine encoding for file %s among %s', file_path, ', '.join(ENCODINGS) ) return {} def update_encoded_file_with_strings( file_path, localized_strings, encoding='utf16' ): ''' Update file at file_path with translations from localized_strings, trying to preserve the initial formatting by only removing the old translations, updating the current ones and adding the new translations at the end of the file. The file at file_path must exist or this function will raise an exception. ''' output_strings = [] keys = set() with codecs.open(file_path, 'r', encoding) as content: for line in content: current_string = LocalizedString.from_line(line.strip()) if current_string: key = current_string.key localized_string = localized_strings.get(key, None) if localized_string: keys.add(key) output_strings.append(unicode(localized_string)) else: output_strings.append(line[:-1]) new_strings = [] for value in localized_strings.itervalues(): if value.key not in keys: new_strings.append(unicode(value)) if len(new_strings) != 0: output_strings.append('') output_strings.append('/ New strings /') new_strings.sort() output_strings.extend(new_strings) with codecs.open(file_path, 'w', encoding) as output: output.write('\n'.join(output_strings)) # Always add a new line at the end of the file output.write('\n') def match_strings(scanned_strings, reference_strings): ''' Complete scanned_strings with translations from reference_strings. Return the completed scanned_strings dictionnary. scanned_strings is not affected. Strings in reference_strings and not in scanned_strings are not copied. ''' final_strings = {} for key, value in scanned_strings.iteritems(): reference_value = reference_strings.get(key, None) if reference_value: if reference_value.is_raw(): # Mark non-translated strings logging.debug('[raw] %s', key) final_strings[key] = value else: # Reference comment comes from the code reference_value.comment = value.comment final_strings[key] = reference_value else: logging.debug('[new] %s', key) final_strings[key] = value final_keys = set(final_strings.keys()) for key in reference_strings.iterkeys(): if key not in final_keys: logging.debug('[deleted] %s', key) return final_strings def merge_dictionaries(reference_dict, import_dict): ''' Return a dictionnary containing key/values from reference_dict and import_dict. In case of conflict, the value from reference_dict is chosen. ''' final_dict = reference_dict.copy() reference_dict_keys = set(reference_dict.keys()) for key, value in import_dict.iteritems(): if key not in reference_dict_keys: final_dict[key] = value return final_dict def sorted_strings_from_dict(strings): ''' Return an array containing the string objects sorted alphabetically. ''' keys = strings.keys() keys.sort() values = [] for key in keys: values.append(strings[key]) return values class Tests(unittest.TestCase): ''' Unit Tests ''' def test_comment(self): ''' Test comment pattern ''' result = LocalizedString.COMMENT_EXPR.match('/ Testing Comments /') self.assertNotEqual(result, None, 'Pattern not recognized') self.assertEqual(result.group('comment'), 'Testing Comments', 'Incorrect pattern content: [%s]' % result.group('comment') ) def test_localized_string(self): ''' Test localized string pattern ''' result = LocalizedString.LOCALIZED_STRING_EXPR.match( '"KEY" = "VALUE";' ) self.assertNotEqual(result, None, 'Pattern not recognized') self.assertEqual(result.group('key'), 'KEY', 'Incorrect comment content: [%s]' % result.group('key') ) self.assertEqual(result.group('value'), 'VALUE', 'Incorrect comment content: [%s]' % result.group('value') ) self.assertEqual(result.group('comment'), None, 'Incorrect comment content: [%s]' % result.group('comment') ) def test_localized_comment_string(self): ''' Test localized string with comment pattern ''' result = LocalizedString.LOCALIZED_STRING_EXPR.match( '"KEY" = "VALUE"; / COMMENT */' ) self.assertNotEqual(result, None, 'Pattern not recognized') self.assertEqual(result.group('key'), 'KEY', 'Incorrect comment content: [%s]' % result.group('key') ) self.assertEqual(result.group('value'), 'VALUE', 'Incorrect comment content: [%s]' % result.group('value') ) self.assertEqual(result.group('comment'), 'COMMENT', 'Incorrect comment content: [%s]' % result.group('comment') ) def main(): ''' Parse the command line and do what it is telled to do ''' parser = optparse.OptionParser( 'usage: %prog [options] Localizable.strings [source folders]' ) parser.add_option( '-v', '--verbose', action='store_true', dest='verbose', default=False, help='Show debug messages' ) parser.add_option( '', '--dry-run', action='store_true', dest='dry_run', default=False, help='Do not write to the strings file' ) parser.add_option( '', '--import', dest='import_file', help='Import strings from FILENAME' ) parser.add_option( '', '--overwrite', action='store_true', dest='overwrite', default=False, help='Overwrite the strings file, ignores original formatting' ) parser.add_option( '', '--unittests', action='store_true', dest='unittests', default=False, help='Run unit tests (debug)' ) (options, args) = parser.parse_args() logging.basicConfig( format='%(message)s', level=options.verbose and logging.DEBUG or logging.INFO ) if options.unittests: suite = unittest.TestLoader().loadTestsFromTestCase(Tests) return unittest.TextTestRunner(verbosity=2).run(suite) if len(args) == 0: parser.error('Please specify a strings file') strings_file = args[0] input_folders = ['.'] if len(args) > 1: input_folders = args[1:] scanned_strings = {} for input_folder in input_folders: if not os.path.isdir(input_folder): logging.error('Input path is not a folder: %s', input_folder) return 1 # TODO: allow to specify file extensions to scan scanned_strings = merge_dictionaries( scanned_strings, strings_from_folder(input_folder) ) if options.import_file: logging.debug( 'Reading import file: %s', options.import_file ) reference_strings = strings_from_file(options.import_file) scanned_strings = match_strings( scanned_strings, reference_strings ) if os.path.isfile(strings_file): logging.debug( 'Reading strings file: %s', strings_file ) reference_strings = strings_from_file( strings_file ) scanned_strings = match_strings( scanned_strings, reference_strings ) if options.dry_run: logging.info( 'Dry run: the strings file has not been updated' ) else: try: if os.path.exists(strings_file) and not options.overwrite: update_file_with_strings(strings_file, scanned_strings) else: strings_to_file(scanned_strings, strings_file) except IOError, exc: logging.error('Error writing to file %s: %s', strings_file, exc) return 1 logging.info( 'Strings were generated in %s', strings_file ) return 0 if __name__ == '__main__': sys.exit(main())	29.828794	78	0.604031	#!/usr/bin/env python # -- coding: utf-8 -- ''' Update or create an Apple XCode project localization strings file. TODO: handle localization domains ''' from __future__ import with_statement import sys import os import os.path import re import tempfile import subprocess import codecs import unittest import optparse import shutil import logging ENCODINGS = ['utf16', 'utf8'] class LocalizedString(object): ''' A localized string from a strings file ''' COMMENT_EXPR = re.compile( # Line start '^\w' # Comment '/\ (?P<comment>.+) \/' # End of line '\w$' ) LOCALIZED_STRING_EXPR = re.compile( # Line start '^' # Key '"(?P<key>.+)"' # Equals ' ?= ?' # Value '"(?P<value>.+)"' # Whitespace ';' # Comment '(?: /\* (?P<comment>.+) \/)?' # End of line '$' ) @classmethod def parse_comment(cls, comment): ''' Extract the content of a comment line from a strings file. Returns the comment string or None if the line doesn't match. ''' result = cls.COMMENT_EXPR.match(comment) if result != None: return result.group('comment') else: return None @classmethod def from_line(cls, line): ''' Extract the content of a string line from a strings file. Returns a LocalizedString instance or None if the line doesn't match. TODO: handle whitespace restore ''' result = cls.LOCALIZED_STRING_EXPR.match(line) if result != None: return cls( result.group('key'), result.group('value'), result.group('comment') ) else: return None def __init__(self, key, value=None, comment=None): super(LocalizedString, self).__init__() self.key = key self.value = value self.comment = comment def is_raw(self): ''' Return True if the localized string has not been translated. ''' return self.value == self.key def __str__(self): if self.comment: return '"%s" = "%s"; / %s /' % ( self.key or '', self.value or '', self.comment ) else: return '"%s" = "%s";' % (self.key or '', self.value or '') def strings_from_folder(folder_path, extensions=None, exclude=None): ''' Recursively scan folder_path for files containing localizable strings. Run genstrings on these files and extract the strings. Returns a dictionnary of LocalizedString instances, indexed by key. ''' localized_strings = {} code_file_paths = [] if extensions == None: extensions = frozenset(['m', 'mm']) if exclude == None: exclude = frozenset(['ImportedSources','Pods']) logging.debug('Scanning for source files in %s', folder_path) for dir_path, dir_names, file_names in os.walk(folder_path): dir_names[:] = [d for d in dir_names if d not in exclude] for file_name in file_names: extension = file_name.rpartition('.')[2] if extension in extensions: code_file_path = os.path.join(dir_path, file_name) code_file_paths.append(code_file_path) logging.debug('Found %d files', len(code_file_paths)) logging.debug('Running genstrings') temp_folder_path = tempfile.mkdtemp() arguments = ['genstrings', '-u', '-o', temp_folder_path] arguments.extend(code_file_paths) logging.debug('Here are the argumengts %s', arguments) subprocess.call(arguments) temp_file_path = os.path.join(temp_folder_path, 'Localizable.strings') if os.path.exists(temp_file_path): logging.debug('Analysing genstrings content') localized_strings = strings_from_file(temp_file_path) os.remove(temp_file_path) else: logging.debug('No translations found') shutil.rmtree(temp_folder_path) return localized_strings def strings_from_file(file_path): ''' Try to autodetect file encoding and call strings_from_encoded_file on the file at file_path. Returns a dictionnary of LocalizedString instances, indexed by key. Returns an empty dictionnary if the encoding is wrong. ''' for current_encoding in ENCODINGS: try: return strings_from_encoded_file(file_path, current_encoding) except UnicodeError: pass logging.error( 'Cannot determine encoding for file %s among %s', file_path, ', '.join(ENCODINGS) ) return {} def strings_from_encoded_file(file_path, encoding): ''' Extract the strings from the file at file_path. Returns a dictionnary of LocalizedString instances, indexed by key. ''' localized_strings = {} with codecs.open(file_path, 'r', encoding) as content: comment = None for line in content: line = line.strip() if not line: comment = None continue current_comment = LocalizedString.parse_comment(line) if current_comment: if current_comment != 'No comment provided by engineer.': comment = current_comment continue localized_string = LocalizedString.from_line(line) if localized_string: if not localized_string.comment: localized_string.comment = comment localized_strings[localized_string.key] = localized_string else: logging.error('Could not parse: %s', line.strip()) return localized_strings def strings_to_file(localized_strings, file_path, encoding='utf16'): ''' Write a strings file at file_path containing string in the localized_strings dictionnary. The strings are alphabetically sorted. ''' with codecs.open(file_path, 'w', encoding) as output: for localized_string in sorted_strings_from_dict(localized_strings): output.write('%s\n' % localized_string) def update_file_with_strings(file_path, localized_strings): ''' Try to autodetect file encoding and call update_encoded_file_with_strings on the file at file_path. The file at file_path must exist or this function will raise an exception. ''' for current_encoding in ENCODINGS: try: return update_encoded_file_with_strings( file_path, localized_strings, current_encoding ) except UnicodeError: pass logging.error( 'Cannot determine encoding for file %s among %s', file_path, ', '.join(ENCODINGS) ) return {} def update_encoded_file_with_strings( file_path, localized_strings, encoding='utf16' ): ''' Update file at file_path with translations from localized_strings, trying to preserve the initial formatting by only removing the old translations, updating the current ones and adding the new translations at the end of the file. The file at file_path must exist or this function will raise an exception. ''' output_strings = [] keys = set() with codecs.open(file_path, 'r', encoding) as content: for line in content: current_string = LocalizedString.from_line(line.strip()) if current_string: key = current_string.key localized_string = localized_strings.get(key, None) if localized_string: keys.add(key) output_strings.append(unicode(localized_string)) else: output_strings.append(line[:-1]) new_strings = [] for value in localized_strings.itervalues(): if value.key not in keys: new_strings.append(unicode(value)) if len(new_strings) != 0: output_strings.append('') output_strings.append('/ New strings /') new_strings.sort() output_strings.extend(new_strings) with codecs.open(file_path, 'w', encoding) as output: output.write('\n'.join(output_strings)) # Always add a new line at the end of the file output.write('\n') def match_strings(scanned_strings, reference_strings): ''' Complete scanned_strings with translations from reference_strings. Return the completed scanned_strings dictionnary. scanned_strings is not affected. Strings in reference_strings and not in scanned_strings are not copied. ''' final_strings = {} for key, value in scanned_strings.iteritems(): reference_value = reference_strings.get(key, None) if reference_value: if reference_value.is_raw(): # Mark non-translated strings logging.debug('[raw] %s', key) final_strings[key] = value else: # Reference comment comes from the code reference_value.comment = value.comment final_strings[key] = reference_value else: logging.debug('[new] %s', key) final_strings[key] = value final_keys = set(final_strings.keys()) for key in reference_strings.iterkeys(): if key not in final_keys: logging.debug('[deleted] %s', key) return final_strings def merge_dictionaries(reference_dict, import_dict): ''' Return a dictionnary containing key/values from reference_dict and import_dict. In case of conflict, the value from reference_dict is chosen. ''' final_dict = reference_dict.copy() reference_dict_keys = set(reference_dict.keys()) for key, value in import_dict.iteritems(): if key not in reference_dict_keys: final_dict[key] = value return final_dict def sorted_strings_from_dict(strings): ''' Return an array containing the string objects sorted alphabetically. ''' keys = strings.keys() keys.sort() values = [] for key in keys: values.append(strings[key]) return values class Tests(unittest.TestCase): ''' Unit Tests ''' def test_comment(self): ''' Test comment pattern ''' result = LocalizedString.COMMENT_EXPR.match('/ Testing Comments /') self.assertNotEqual(result, None, 'Pattern not recognized') self.assertEqual(result.group('comment'), 'Testing Comments', 'Incorrect pattern content: [%s]' % result.group('comment') ) def test_localized_string(self): ''' Test localized string pattern ''' result = LocalizedString.LOCALIZED_STRING_EXPR.match( '"KEY" = "VALUE";' ) self.assertNotEqual(result, None, 'Pattern not recognized') self.assertEqual(result.group('key'), 'KEY', 'Incorrect comment content: [%s]' % result.group('key') ) self.assertEqual(result.group('value'), 'VALUE', 'Incorrect comment content: [%s]' % result.group('value') ) self.assertEqual(result.group('comment'), None, 'Incorrect comment content: [%s]' % result.group('comment') ) def test_localized_comment_string(self): ''' Test localized string with comment pattern ''' result = LocalizedString.LOCALIZED_STRING_EXPR.match( '"KEY" = "VALUE"; / COMMENT */' ) self.assertNotEqual(result, None, 'Pattern not recognized') self.assertEqual(result.group('key'), 'KEY', 'Incorrect comment content: [%s]' % result.group('key') ) self.assertEqual(result.group('value'), 'VALUE', 'Incorrect comment content: [%s]' % result.group('value') ) self.assertEqual(result.group('comment'), 'COMMENT', 'Incorrect comment content: [%s]' % result.group('comment') ) def main(): ''' Parse the command line and do what it is telled to do ''' parser = optparse.OptionParser( 'usage: %prog [options] Localizable.strings [source folders]' ) parser.add_option( '-v', '--verbose', action='store_true', dest='verbose', default=False, help='Show debug messages' ) parser.add_option( '', '--dry-run', action='store_true', dest='dry_run', default=False, help='Do not write to the strings file' ) parser.add_option( '', '--import', dest='import_file', help='Import strings from FILENAME' ) parser.add_option( '', '--overwrite', action='store_true', dest='overwrite', default=False, help='Overwrite the strings file, ignores original formatting' ) parser.add_option( '', '--unittests', action='store_true', dest='unittests', default=False, help='Run unit tests (debug)' ) (options, args) = parser.parse_args() logging.basicConfig( format='%(message)s', level=options.verbose and logging.DEBUG or logging.INFO ) if options.unittests: suite = unittest.TestLoader().loadTestsFromTestCase(Tests) return unittest.TextTestRunner(verbosity=2).run(suite) if len(args) == 0: parser.error('Please specify a strings file') strings_file = args[0] input_folders = ['.'] if len(args) > 1: input_folders = args[1:] scanned_strings = {} for input_folder in input_folders: if not os.path.isdir(input_folder): logging.error('Input path is not a folder: %s', input_folder) return 1 # TODO: allow to specify file extensions to scan scanned_strings = merge_dictionaries( scanned_strings, strings_from_folder(input_folder) ) if options.import_file: logging.debug( 'Reading import file: %s', options.import_file ) reference_strings = strings_from_file(options.import_file) scanned_strings = match_strings( scanned_strings, reference_strings ) if os.path.isfile(strings_file): logging.debug( 'Reading strings file: %s', strings_file ) reference_strings = strings_from_file( strings_file ) scanned_strings = match_strings( scanned_strings, reference_strings ) if options.dry_run: logging.info( 'Dry run: the strings file has not been updated' ) else: try: if os.path.exists(strings_file) and not options.overwrite: update_file_with_strings(strings_file, scanned_strings) else: strings_to_file(scanned_strings, strings_file) except IOError, exc: logging.error('Error writing to file %s: %s', strings_file, exc) return 1 logging.info( 'Strings were generated in %s', strings_file ) return 0 if __name__ == '__main__': sys.exit(main())	389	0	54
86dfc395ff5ab6ef9c14be7ee4df1e0ab24a57c0	85	py	Python	mayday_control/scripts/side.py	LasseBoerresen/Lumos	2447adc7795ae07cb0a1df409d3b1a6178c2cd8b	[ "MIT" ]	null	null	null	mayday_control/scripts/side.py	LasseBoerresen/Lumos	2447adc7795ae07cb0a1df409d3b1a6178c2cd8b	[ "MIT" ]	null	null	null	mayday_control/scripts/side.py	LasseBoerresen/Lumos	2447adc7795ae07cb0a1df409d3b1a6178c2cd8b	[ "MIT" ]	null	null	null	from enum import Enum, auto	12.142857	27	0.611765	from enum import Enum, auto class Side(Enum): LEFT = auto() RIGHT = auto()	0	33	23
46f3c5c10009f79e8f58863d6137c6c1d59ef457	1,212	py	Python	examples/hlapi/v3arch/asyncore/sync/agent/ntforg/send-notification-with-additional-varbinds.py	fabriziovanni/pysnmp	eef4cc03b4da199e9c131ddd18ccb7501f1f2c40	[ "BSD-2-Clause" ]	null	null	null	examples/hlapi/v3arch/asyncore/sync/agent/ntforg/send-notification-with-additional-varbinds.py	fabriziovanni/pysnmp	eef4cc03b4da199e9c131ddd18ccb7501f1f2c40	[ "BSD-2-Clause" ]	null	null	null	examples/hlapi/v3arch/asyncore/sync/agent/ntforg/send-notification-with-additional-varbinds.py	fabriziovanni/pysnmp	eef4cc03b4da199e9c131ddd18ccb7501f1f2c40	[ "BSD-2-Clause" ]	null	null	null	""" Sending additional var-binds ++++++++++++++++++++++++++++ Send SNMP notification using the following options: * SNMPv2c * with community name 'public' * over IPv4/UDP * send INFORM notification * with TRAP ID 'coldStart' specified as a MIB symbol * include managed object information specified as a MIB symbol Functionally similar to: \| $ snmpinform -v2c -c public demo.snmplabs.com 12345 1.3.6.1.6.3.1.1.5.1 1.3.6.1.2.1.1.1.0 s "my system" """# from pysnmp.hlapi import * errorIndication, errorStatus, errorIndex, varBinds = next( sendNotification( SnmpEngine(), CommunityData('public'), UdpTransportTarget(('demo.snmplabs.com', 162)), ContextData(), 'inform', NotificationType( ObjectIdentity('SNMPv2-MIB', 'coldStart') ).addVarBinds( ObjectType(ObjectIdentity('SNMPv2-MIB', 'sysName', 0), 'my system') ) ) ) if errorIndication: print(errorIndication) elif errorStatus: print('%s at %s' % (errorStatus.prettyPrint(), errorIndex and varBinds[int(errorIndex) - 1][0] or '?')) else: for varBind in varBinds: print(' = '.join([x.prettyPrint() for x in varBind]))	27.545455	105	0.632838	""" Sending additional var-binds ++++++++++++++++++++++++++++ Send SNMP notification using the following options: * SNMPv2c * with community name 'public' * over IPv4/UDP * send INFORM notification * with TRAP ID 'coldStart' specified as a MIB symbol * include managed object information specified as a MIB symbol Functionally similar to: \| $ snmpinform -v2c -c public demo.snmplabs.com 12345 1.3.6.1.6.3.1.1.5.1 1.3.6.1.2.1.1.1.0 s "my system" """# from pysnmp.hlapi import * errorIndication, errorStatus, errorIndex, varBinds = next( sendNotification( SnmpEngine(), CommunityData('public'), UdpTransportTarget(('demo.snmplabs.com', 162)), ContextData(), 'inform', NotificationType( ObjectIdentity('SNMPv2-MIB', 'coldStart') ).addVarBinds( ObjectType(ObjectIdentity('SNMPv2-MIB', 'sysName', 0), 'my system') ) ) ) if errorIndication: print(errorIndication) elif errorStatus: print('%s at %s' % (errorStatus.prettyPrint(), errorIndex and varBinds[int(errorIndex) - 1][0] or '?')) else: for varBind in varBinds: print(' = '.join([x.prettyPrint() for x in varBind]))	0	0	0
8769954b2a2c6814333a757790542af24afd9ca2	16,490	py	Python	smt/surrogate_models/krg_mgp.py	joshuauk1026/smt	ec6aa20643b1e4fa772c6f470281c58df113c3a6	[ "BSD-3-Clause" ]	3	2017-09-08T21:32:16.000Z	2021-04-20T20:52:30.000Z	smt/surrogate_models/krg_mgp.py	joshuauk1026/smt	ec6aa20643b1e4fa772c6f470281c58df113c3a6	[ "BSD-3-Clause" ]	null	null	null	smt/surrogate_models/krg_mgp.py	joshuauk1026/smt	ec6aa20643b1e4fa772c6f470281c58df113c3a6	[ "BSD-3-Clause" ]	null	null	null	""" Author: Remy Priem (remy.priem@onera.fr) This package is distributed under New BSD license. """ from __future__ import division import numpy as np from scipy import linalg from smt.utils.kriging_utils import differences from smt.surrogate_models.krg_based import KrgBased from smt.utils.kriging_utils import componentwise_distance """ The Active kriging class. """	31.833977	93	0.546574	""" Author: Remy Priem (remy.priem@onera.fr) This package is distributed under New BSD license. """ from __future__ import division import numpy as np from scipy import linalg from smt.utils.kriging_utils import differences from smt.surrogate_models.krg_based import KrgBased from smt.utils.kriging_utils import componentwise_distance """ The Active kriging class. """ class MGP(KrgBased): def _initialize(self): """ Initialized MGP """ super(MGP, self)._initialize() declare = self.options.declare declare("n_comp", 1, types=int, desc="Number of active dimensions") declare( "prior", {"mean": [0.0], "var": 5.0 / 4.0}, types=dict, desc="Parameters for Gaussian prior of the Hyperparameters", ) self.options["hyper_opt"] = "TNC" self.options["corr"] = "act_exp" self.name = "MGP" def _componentwise_distance(self, dx, small=False, opt=0): """ Compute the componentwise distance with respect to the correlation kernel Parameters ---------- dx : numpy.ndarray Distance matrix. small : bool, optional Compute the componentwise distance in small (n_components) dimension or in initial dimension. The default is False. opt : int, optional useless for MGP Returns ------- d : numpy.ndarray Component wise distance. """ if small: d = componentwise_distance(dx, self.options["corr"], self.options["n_comp"]) else: d = componentwise_distance(dx, self.options["corr"], self.nx) return d def predict_variances(self, x, both=False): """ Predict the variance of a specific point Parameters ---------- x : numpy.ndarray Point to compute. both : bool, optional True if MSE and MGP-MSE wanted. The default is False. Raises ------ ValueError The number fo dimension is not good. Returns ------- numpy.nd array MSE or (MSE, MGP-MSE). """ n_eval, n_features = x.shape if n_features < self.nx: if n_features != self.options["n_comp"]: raise ValueError( "dim(u) should be equal to %i" % self.options["n_comp"] ) u = x x = self.get_x_from_u(u) u = u * self.embedding["norm"] - self.U_mean x = (x - self.X_offset) / self.X_scale else: if n_features != self.nx: raise ValueError("dim(x) should be equal to %i" % self.X_scale.shape[0]) u = None x = (x - self.X_offset) / self.X_scale dy = self._predict_value_derivatives_hyper(x, u) dMSE, MSE = self._predict_variance_derivatives_hyper(x, u) arg_1 = np.einsum("ij,ij->i", dy.T, linalg.solve(self.inv_sigma_R, dy).T) arg_2 = np.einsum("ij,ij->i", dMSE.T, linalg.solve(self.inv_sigma_R, dMSE).T) MGPMSE = np.zeros(x.shape[0]) MGPMSE[MSE != 0] = ( (4.0 / 3.0) * MSE[MSE != 0] + arg_1[MSE != 0] + (1.0 / (3.0 * MSE[MSE != 0])) * arg_2[MSE != 0] ) MGPMSE[MGPMSE < 0.0] = 0.0 if both: return MGPMSE, MSE else: return MGPMSE def predict_values(self, x): """ Predict the value of the MGP for a given point Parameters ---------- x : numpy.ndarray Point to compute. Raises ------ ValueError The number fo dimension is not good. Returns ------- y : numpy.ndarray Value of the MGP at the given point x. """ n_eval, n_features = x.shape if n_features < self.nx: if n_features != self.options["n_comp"]: raise ValueError( "dim(u) should be equal to %i" % self.options["n_comp"] ) theta = np.eye(self.options["n_comp"]).reshape( (self.options["n_comp"] ** 2,) ) # Get pairwise componentwise L1-distances to the input training set u = x x = self.get_x_from_u(u) u = u * self.embedding["norm"] - self.U_mean du = differences(u, Y=self.U_norma.copy()) d = self._componentwise_distance(du, small=True) # Get an approximation of x x = (x - self.X_offset) / self.X_scale dx = differences(x, Y=self.X_norma.copy()) d_x = self._componentwise_distance(dx) else: if n_features != self.nx: raise ValueError("dim(x) should be equal to %i" % self.X_scale.shape[0]) theta = self.optimal_theta # Get pairwise componentwise L1-distances to the input training set x = (x - self.X_offset) / self.X_scale dx = differences(x, Y=self.X_norma.copy()) d = self._componentwise_distance(dx) d_x = None # Compute the correlation function r = self._correlation_types[self.options["corr"]](theta, d, d_x=d_x).reshape( n_eval, self.nt ) f = self._regression_types[self.options["poly"]](x) # Scaled predictor y_ = np.dot(f, self.optimal_par["beta"]) + np.dot(r, self.optimal_par["gamma"]) # Predictor y = (self.y_mean + self.y_std * y_).ravel() return y def _reduced_log_prior(self, theta, grad=False, hessian=False): """ Compute the reduced log prior at given hyperparameters Parameters ---------- theta : numpy.ndarray Hyperparameters. grad : bool, optional True to compuyte gradient. The default is False. hessian : bool, optional True to compute hessian. The default is False. Returns ------- res : numpy.ndarray Value, gradient, hessian of the reduced log prior. """ nb_theta = len(theta) if theta.ndim < 2: theta = np.atleast_2d(theta).T mean = np.ones((nb_theta, 1)) * self.options["prior"]["mean"] sig_inv = np.eye(nb_theta) / self.options["prior"]["var"] if grad: sig_inv_m = np.atleast_2d(np.sum(sig_inv, axis=0)).T res = -2.0 * (theta - mean) * sig_inv_m elif hessian: res = -2.0 * np.atleast_2d(np.sum(sig_inv, axis=0)).T else: res = -np.dot((theta - mean).T, sig_inv.dot(theta - mean)) return res def _predict_value_derivatives_hyper(self, x, u=None): """ Compute the derivatives of the mean of the GP with respect to the hyperparameters Parameters ---------- x : numpy.ndarray Point to compute in initial dimension. u : numpy.ndarray, optional Point to compute in small dimension. The default is None. Returns ------- dy : numpy.ndarray Derivatives of the mean of the GP with respect to the hyperparameters. """ # Initialization n_eval, _ = x.shape # Get pairwise componentwise L1-distances to the input training set dx = differences(x, Y=self.X_norma.copy()) d_x = self._componentwise_distance(dx) if u is not None: theta = np.eye(self.options["n_comp"]).reshape( (self.options["n_comp"] 2,) ) # Get pairwise componentwise L1-distances to the input training set du = differences(u, Y=self.U_norma.copy()) d = self._componentwise_distance(du, small=True) else: theta = self.optimal_theta # Get pairwise componentwise L1-distances to the input training set d = d_x d_x = None # Compute the correlation function r = self._correlation_types[self.options["corr"]](theta, d, d_x=d_x).reshape( n_eval, self.nt ) # Compute the regression function f = self._regression_types[self.options["poly"]](x) dy = np.zeros((len(self.optimal_theta), n_eval)) gamma = self.optimal_par["gamma"] Rinv_dR_gamma = self.optimal_par["Rinv_dR_gamma"] Rinv_dmu = self.optimal_par["Rinv_dmu"] for omega in range(len(self.optimal_theta)): drdomega = self._correlation_types[self.options["corr"]]( theta, d, grad_ind=omega, d_x=d_x ).reshape(n_eval, self.nt) dbetadomega = self.optimal_par["dbeta_all"][omega] dy_omega = ( f.dot(dbetadomega) + drdomega.dot(gamma) - r.dot(Rinv_dR_gamma[omega] + Rinv_dmu[omega]) ) dy[omega, :] = dy_omega[:, 0] return dy def _predict_variance_derivatives_hyper(self, x, u=None): """ Compute the derivatives of the variance of the GP with respect to the hyperparameters Parameters ---------- x : numpy.ndarray Point to compute in initial dimension. u : numpy.ndarray, optional Point to compute in small dimension. The default is None. Returns ------- dMSE : numpy.ndarrray derivatives of the variance of the GP with respect to the hyperparameters. MSE : TYPE Variance of the GP. """ # Initialization n_eval, n_features_x = x.shape # Get pairwise componentwise L1-distances to the input training set dx = differences(x, Y=self.X_norma.copy()) d_x = self._componentwise_distance(dx) if u is not None: theta = np.eye(self.options["n_comp"]).reshape( (self.options["n_comp"] 2,) ) # Get pairwise componentwise L1-distances to the input training set du = differences(u, Y=self.U_norma.copy()) d = self._componentwise_distance(du, small=True) else: theta = self.optimal_theta # Get pairwise componentwise L1-distances to the input training set d = d_x d_x = None # Compute the correlation function r = ( self._correlation_types[self.options["corr"]](theta, d, d_x=d_x) .reshape(n_eval, self.nt) .T ) f = self._regression_types[self.options["poly"]](x).T C = self.optimal_par["C"] G = self.optimal_par["G"] Ft = self.optimal_par["Ft"] sigma2 = self.optimal_par["sigma2"] rt = linalg.solve_triangular(C, r, lower=True) F_Rinv_r = np.dot(Ft.T, rt) u_ = linalg.solve_triangular(G.T, f - F_Rinv_r) MSE = self.optimal_par["sigma2"] * ( 1.0 - (rt 2.0).sum(axis=0) + (u_ 2.0).sum(axis=0) ) # Mean Squared Error might be slightly negative depending on # machine precision: force to zero! MSE[MSE < 0.0] = 0.0 Ginv_u = linalg.solve_triangular(G, u_, lower=False) Rinv_F = linalg.solve_triangular(C.T, Ft, lower=False) Rinv_r = linalg.solve_triangular(C.T, rt, lower=False) Rinv_F_Ginv_u = Rinv_F.dot(Ginv_u) dMSE = np.zeros((len(self.optimal_theta), n_eval)) dr_all = self.optimal_par["dr"] dsigma = self.optimal_par["dsigma"] for omega in range(len(self.optimal_theta)): drdomega = ( self._correlation_types[self.options["corr"]]( theta, d, grad_ind=omega, d_x=d_x ) .reshape(n_eval, self.nt) .T ) dRdomega = np.zeros((self.nt, self.nt)) dRdomega[self.ij[:, 0], self.ij[:, 1]] = dr_all[omega][:, 0] dRdomega[self.ij[:, 1], self.ij[:, 0]] = dr_all[omega][:, 0] # Compute du2dtheta dRdomega_Rinv_F_Ginv_u = dRdomega.dot(Rinv_F_Ginv_u) r_Rinv_dRdomega_Rinv_F_Ginv_u = np.einsum( "ij,ij->i", Rinv_r.T, dRdomega_Rinv_F_Ginv_u.T ) drdomega_Rinv_F_Ginv_u = np.einsum("ij,ij->i", drdomega.T, Rinv_F_Ginv_u.T) u_Ginv_F_Rinv_dRdomega_Rinv_F_Ginv_u = np.einsum( "ij,ij->i", Rinv_F_Ginv_u.T, dRdomega_Rinv_F_Ginv_u.T ) du2domega = ( 2.0 * r_Rinv_dRdomega_Rinv_F_Ginv_u - 2.0 * drdomega_Rinv_F_Ginv_u + u_Ginv_F_Rinv_dRdomega_Rinv_F_Ginv_u ) du2domega = np.atleast_2d(du2domega) # Compute drt2dtheta drdomega_Rinv_r = np.einsum("ij,ij->i", drdomega.T, Rinv_r.T) r_Rinv_dRdomega_Rinv_r = np.einsum( "ij,ij->i", Rinv_r.T, dRdomega.dot(Rinv_r).T ) drt2domega = 2.0 * drdomega_Rinv_r - r_Rinv_dRdomega_Rinv_r drt2domega = np.atleast_2d(drt2domega) dMSE[omega] = dsigma[omega] * MSE / sigma2 + sigma2 * ( -drt2domega + du2domega ) return dMSE, MSE def get_x_from_u(self, u): """ Compute the point in initial dimension from a point in low dimension Parameters ---------- u : numpy.ndarray Point in low dimension. Returns ------- res : numpy.ndarray point in initial dimension. """ u = np.atleast_2d(u) self.embedding["Q_C"], self.embedding["R_C"] x_temp = np.dot( self.embedding["Q_C"], linalg.solve_triangular(self.embedding["R_C"].T, u.T, lower=True), ).T res = np.atleast_2d(x_temp) return res def get_u_from_x(self, x): """ Compute the point in low dimension from a point in initial dimension Parameters ---------- x : numpy.ndarray Point in initial dimension. Returns ------- u : numpy.ndarray Point in low dimension. """ u = x.dot(self.embedding["C"]) return u def _specific_train(self): """ Compute the specific training values necessary for MGP (Hessian) """ # Compute covariance matrix of hyperparameters var_R = np.zeros((len(self.optimal_theta), len(self.optimal_theta))) r, r_ij, par = self._reduced_likelihood_hessian(self.optimal_theta) var_R[r_ij[:, 0], r_ij[:, 1]] = r[:, 0] var_R[r_ij[:, 1], r_ij[:, 0]] = r[:, 0] self.inv_sigma_R = -var_R # Compute normalise embedding self.optimal_par = par A = np.reshape(self.optimal_theta, (self.options["n_comp"], self.nx)).T B = (A.T / self.X_scale).T norm_B = np.linalg.norm(B) C = B / norm_B self.embedding = {} self.embedding["A"] = A self.embedding["C"] = C self.embedding["norm"] = norm_B self.embedding["Q_C"], self.embedding["R_C"] = linalg.qr(C, mode="economic") # Compute normalisation in embeding base self.U_norma = self.X_norma.dot(A) self.U_mean = self.X_offset.dot(C) * norm_B # Compute best number of Components for Active Kriging svd = linalg.svd(A) svd_cumsum = np.cumsum(svd[1]) svd_sum = np.sum(svd[1]) self.best_ncomp = min(np.argwhere(svd_cumsum > 0.99 * svd_sum)) + 1 def _check_param(self): """ Overrides KrgBased implementation This function checks some parameters of the model. """ d = self.options["n_comp"] * self.nx if self.options["corr"] != "act_exp": raise ValueError("MGP must be used with act_exp correlation function") if self.options["hyper_opt"] != "TNC": raise ValueError("MGP must be used with TNC hyperparameters optimizer") if len(self.options["theta0"]) != d: if len(self.options["theta0"]) == 1: self.options["theta0"] *= np.ones(d) else: raise ValueError( "the number of dim %s should be equal to the length of theta0 %s." % (d, len(self.options["theta0"])) )	0	16,093	23
5239e00a83e4cff0b9a0629d3941b9bf6db58e7f	1,470	py	Python	L1Trigger/TrackerTFP/python/Producer_cfi.py	Jingyan95/cmssw	f78d843f0837f269ee6811b0e0f4c0432928c190	[ "Apache-2.0" ]	5	2020-07-02T19:05:26.000Z	2022-02-25T14:37:09.000Z	L1Trigger/TrackerTFP/python/Producer_cfi.py	Jingyan95/cmssw	f78d843f0837f269ee6811b0e0f4c0432928c190	[ "Apache-2.0" ]	61	2020-07-14T17:22:52.000Z	2022-03-16T11:11:12.000Z	L1Trigger/TrackerTFP/python/Producer_cfi.py	dally96/cmssw	c37b9bfa391850cb349c71190b0bbb2d04224cc8	[ "Apache-2.0" ]	8	2020-06-08T16:28:54.000Z	2021-11-16T14:40:00.000Z	import FWCore.ParameterSet.Config as cms TrackerTFPProducer_params = cms.PSet ( LabelDTC = cms.string( "TrackerDTCProducer" ), # LabelGP = cms.string( "TrackerTFPProducerGP" ), # LabelHT = cms.string( "TrackerTFPProducerHT" ), # LabelMHT = cms.string( "TrackerTFPProducerMHT" ), # LabelZHT = cms.string( "TrackerTFPProducerZHT" ), # LabelZHTout = cms.string( "TrackerTFPProducerZHTout" ), # LabelKFin = cms.string( "TrackerTFPProducerKFin" ), # LabelKF = cms.string( "TrackerTFPProducerKF" ), # LabelDR = cms.string( "TrackerTFPProducerDR" ), # LabelTT = cms.string( "TrackerTFPProducerTT" ), # LabelAS = cms.string( "TrackerTFPProducerAS" ), # BranchAcceptedStubs = cms.string( "StubAccepted" ), # branch for prodcut with passed stubs BranchAcceptedTracks = cms.string( "TrackAccepted" ), # branch for prodcut with passed tracks BranchLostStubs = cms.string( "StubLost" ), # branch for prodcut with lost stubs BranchLostTracks = cms.string( "TracksLost" ), # branch for prodcut with lost tracks CheckHistory = cms.bool ( False ), # checks if input sample production is configured as current process EnableTruncation = cms.bool ( True ) # enable emulation of truncation, lost stubs are filled in BranchLost )	63.913043	132	0.621769	import FWCore.ParameterSet.Config as cms TrackerTFPProducer_params = cms.PSet ( LabelDTC = cms.string( "TrackerDTCProducer" ), # LabelGP = cms.string( "TrackerTFPProducerGP" ), # LabelHT = cms.string( "TrackerTFPProducerHT" ), # LabelMHT = cms.string( "TrackerTFPProducerMHT" ), # LabelZHT = cms.string( "TrackerTFPProducerZHT" ), # LabelZHTout = cms.string( "TrackerTFPProducerZHTout" ), # LabelKFin = cms.string( "TrackerTFPProducerKFin" ), # LabelKF = cms.string( "TrackerTFPProducerKF" ), # LabelDR = cms.string( "TrackerTFPProducerDR" ), # LabelTT = cms.string( "TrackerTFPProducerTT" ), # LabelAS = cms.string( "TrackerTFPProducerAS" ), # BranchAcceptedStubs = cms.string( "StubAccepted" ), # branch for prodcut with passed stubs BranchAcceptedTracks = cms.string( "TrackAccepted" ), # branch for prodcut with passed tracks BranchLostStubs = cms.string( "StubLost" ), # branch for prodcut with lost stubs BranchLostTracks = cms.string( "TracksLost" ), # branch for prodcut with lost tracks CheckHistory = cms.bool ( False ), # checks if input sample production is configured as current process EnableTruncation = cms.bool ( True ) # enable emulation of truncation, lost stubs are filled in BranchLost )	0	0	0
e85d58a5f33f7110024d64347a8d77eba76faad1	1,012	py	Python	MyMxOnline/apps/organization/urls.py	xgq07/Django	a3bfa4fa0ebfc3cdcbc59bcaa810507889050d3b	[ "MIT" ]	null	null	null	MyMxOnline/apps/organization/urls.py	xgq07/Django	a3bfa4fa0ebfc3cdcbc59bcaa810507889050d3b	[ "MIT" ]	null	null	null	MyMxOnline/apps/organization/urls.py	xgq07/Django	a3bfa4fa0ebfc3cdcbc59bcaa810507889050d3b	[ "MIT" ]	null	null	null	from organization.views import OrgView,AddUserAskView,OrgHomeView,OrgCourseView,OrgDescView,\ OrgTeacherView,AddFavView,TeacherListView,TeacherDetailView from django.conf.urls import url,include #from django.urls import path,re_path # 要写上app的名字 app_name = "organization" urlpatterns = [ #课程机构列表页 url(r'^list/$', OrgView.as_view(), name="org_list"), url(r'^add_ask/$', AddUserAskView.as_view(), name="add_ask"), url(r'^home/(?P<org_id>\d+)/$', OrgHomeView.as_view(), name="org_home"), url(r'^course/(?P<org_id>\d+)/$', OrgCourseView.as_view(), name="org_course"), url(r'^desc/(?P<org_id>\d+)/', OrgDescView.as_view(), name="org_desc"), url(r'^teacher/(?P<org_id>\d+)/', OrgTeacherView.as_view(), name="org_teacher"), url(r'^add_fav/$', AddFavView.as_view(), name="add_fav"), # 讲师列表 url(r'^teacher/list/', TeacherListView.as_view(), name="teacher_list"), # 讲师详情 url(r'teacher/detail/(?P<teacher_id>\d+)/', TeacherDetailView.as_view(), name="teacher_detail"), ]	46	100	0.689723	from organization.views import OrgView,AddUserAskView,OrgHomeView,OrgCourseView,OrgDescView,\ OrgTeacherView,AddFavView,TeacherListView,TeacherDetailView from django.conf.urls import url,include #from django.urls import path,re_path # 要写上app的名字 app_name = "organization" urlpatterns = [ #课程机构列表页 url(r'^list/$', OrgView.as_view(), name="org_list"), url(r'^add_ask/$', AddUserAskView.as_view(), name="add_ask"), url(r'^home/(?P<org_id>\d+)/$', OrgHomeView.as_view(), name="org_home"), url(r'^course/(?P<org_id>\d+)/$', OrgCourseView.as_view(), name="org_course"), url(r'^desc/(?P<org_id>\d+)/', OrgDescView.as_view(), name="org_desc"), url(r'^teacher/(?P<org_id>\d+)/', OrgTeacherView.as_view(), name="org_teacher"), url(r'^add_fav/$', AddFavView.as_view(), name="add_fav"), # 讲师列表 url(r'^teacher/list/', TeacherListView.as_view(), name="teacher_list"), # 讲师详情 url(r'teacher/detail/(?P<teacher_id>\d+)/', TeacherDetailView.as_view(), name="teacher_detail"), ]	0	0	0
9f97f311276aac0c7752ed83fb0ee1d286767ec5	684	py	Python	tests/test_wake.py	rotdrop/rhasspy-hermes	ab822ad954da6da90368b65d72ed7e53694f085f	[ "MIT" ]	1	2020-07-11T19:25:32.000Z	2020-07-11T19:25:32.000Z	tests/test_wake.py	rotdrop/rhasspy-hermes	ab822ad954da6da90368b65d72ed7e53694f085f	[ "MIT" ]	15	2019-12-31T13:19:25.000Z	2022-01-17T17:40:13.000Z	tests/test_wake.py	rotdrop/rhasspy-hermes	ab822ad954da6da90368b65d72ed7e53694f085f	[ "MIT" ]	8	2019-12-31T10:40:53.000Z	2020-12-04T18:48:08.000Z	"""Tests for rhasspyhermes.wake""" from rhasspyhermes.wake import HotwordDetected, HotwordToggleOff, HotwordToggleOn wakeword_id = "testWakeWord" def test_hotword_detected(): """Test HotwordDetected.""" assert HotwordDetected.is_topic(HotwordDetected.topic(wakeword_id=wakeword_id)) assert ( HotwordDetected.get_wakeword_id(HotwordDetected.topic(wakeword_id=wakeword_id)) == wakeword_id ) def test_hotword_toggle_on(): """Test HotwordToggleOn.""" assert HotwordToggleOn.topic() == "hermes/hotword/toggleOn" def test_hotword_toggle_off(): """Test HotwordToggleOff.""" assert HotwordToggleOff.topic() == "hermes/hotword/toggleOff"	28.5	87	0.745614	"""Tests for rhasspyhermes.wake""" from rhasspyhermes.wake import HotwordDetected, HotwordToggleOff, HotwordToggleOn wakeword_id = "testWakeWord" def test_hotword_detected(): """Test HotwordDetected.""" assert HotwordDetected.is_topic(HotwordDetected.topic(wakeword_id=wakeword_id)) assert ( HotwordDetected.get_wakeword_id(HotwordDetected.topic(wakeword_id=wakeword_id)) == wakeword_id ) def test_hotword_toggle_on(): """Test HotwordToggleOn.""" assert HotwordToggleOn.topic() == "hermes/hotword/toggleOn" def test_hotword_toggle_off(): """Test HotwordToggleOff.""" assert HotwordToggleOff.topic() == "hermes/hotword/toggleOff"	0	0	0
1d8d5603276e76c3b2ea3734f7c017edeca526fb	2,267	py	Python	geography/management/commands/bootstrap/fixtures/_nation.py	The-Politico/politico-civic-geography	032b3ee773b50b65cfe672f230dda772df0f89e0	[ "MIT" ]	1	2018-07-31T13:54:38.000Z	2018-07-31T13:54:38.000Z	geography/management/commands/bootstrap/fixtures/_nation.py	The-Politico/politico-civic-geography	032b3ee773b50b65cfe672f230dda772df0f89e0	[ "MIT" ]	7	2018-04-18T20:57:40.000Z	2021-06-10T20:50:40.000Z	geography/management/commands/bootstrap/fixtures/_nation.py	The-Politico/politico-civic-geography	032b3ee773b50b65cfe672f230dda772df0f89e0	[ "MIT" ]	1	2018-12-15T20:17:52.000Z	2018-12-15T20:17:52.000Z	import json import os from tqdm import tqdm import geojson import shapefile from geography.models import Geometry	31.486111	71	0.521394	import json import os from tqdm import tqdm import geojson import shapefile from geography.models import Geometry class NationFixtures(object): def create_nation_fixtures(self): """ Create national US and State Map """ SHP_SLUG = "cb_{}_us_state_500k".format(self.YEAR) DOWNLOAD_PATH = os.path.join(self.DOWNLOAD_DIRECTORY, SHP_SLUG) shape = shapefile.Reader( os.path.join(DOWNLOAD_PATH, "{}.shp".format(SHP_SLUG)) ) fields = shape.fields[1:] field_names = [f[0] for f in fields] features = [] for shp in shape.shapeRecords(): state = dict(zip(field_names, shp.record)) geodata = { "type": "Feature", "geometry": shp.shape.__geo_interface__, "properties": { "state": state["STATEFP"], "name": state["NAME"], }, } features.append(geodata) Geometry.objects.update_or_create( division=self.NATION, subdivision_level=self.STATE_LEVEL, simplification=self.THRESHOLDS["nation"], source=os.path.join( self.SHP_SOURCE_BASE.format(self.YEAR), SHP_SLUG ) + ".zip", series=self.YEAR, defaults={ "topojson": self.toposimplify( geojson.FeatureCollection(features), self.THRESHOLDS["nation"], ) }, ) geo, created = Geometry.objects.update_or_create( division=self.NATION, subdivision_level=self.COUNTY_LEVEL, simplification=self.THRESHOLDS["nation"], source=os.path.join( self.SHP_SOURCE_BASE.format(self.YEAR), SHP_SLUG ) + ".zip", series=self.YEAR, defaults={"topojson": self.get_state_county_shps("00")}, ) tqdm.write("Nation\n") tqdm.write( self.TQDM_PREFIX + "> FIPS {} @ ~{}kb ".format( "00", round(len(json.dumps(geo.topojson)) / 1000) ) ) tqdm.write(self.style.SUCCESS("Done.\n"))	0	2,127	23
11d5c86e0a8bc126cada2f724bb16ebccefa8607	1,602	py	Python	test/models/test_value.py	firstof9/python-openzwave-mqtt	25f9f90ba586e33fee7b7a444743966371268787	[ "Apache-2.0" ]	63	2019-11-06T19:30:45.000Z	2022-02-04T22:19:07.000Z	test/models/test_value.py	firstof9/python-openzwave-mqtt	25f9f90ba586e33fee7b7a444743966371268787	[ "Apache-2.0" ]	66	2021-01-18T06:52:17.000Z	2022-03-28T08:04:22.000Z	test/models/test_value.py	firstof9/python-openzwave-mqtt	25f9f90ba586e33fee7b7a444743966371268787	[ "Apache-2.0" ]	12	2020-01-03T13:35:06.000Z	2020-10-10T20:50:20.000Z	"""Provide tests for the node value.""" from openzwavemqtt.const import ( EVENT_VALUE_ADDED, EVENT_VALUE_CHANGED, EVENT_VALUE_REMOVED, ) def test_value_events(mgr): """Test value events.""" events = [] # Fill parent data. mgr.mock_receive_json("OpenZWave/1/node/2", {}) mgr.mock_receive_json("OpenZWave/1/node/2/instance/1", {}) mgr.mock_receive_json("OpenZWave/1/node/2/instance/1/commandclass/4", {}) # Listen for value added mgr.options.listen(EVENT_VALUE_ADDED, events.append) mgr.mock_receive_json( "OpenZWave/1/node/2/instance/1/commandclass/4/value/3", {"Value": "yo"} ) assert len(events) == 1 assert events[0].id == 3 assert events[0].value == "yo" assert events[0].parent.id == 4 # Test OZWNode.values shortcut assert list(mgr.get_instance(1).get_node(2).values())[0].id == 3 # Listen for value changed mgr.options.listen(EVENT_VALUE_CHANGED, events.append) mgr.mock_receive_json( "OpenZWave/1/node/2/instance/1/commandclass/4/value/3", {"Value": "yo2"} ) assert len(events) == 2 assert events[0].id == 3 assert events[0].value == "yo2" # Show how to use collection helpers assert ( list(mgr.get_instance(1).get_node(2).get_instance(1).commandclasses())[0] .get_value(3) .value == "yo2" ) # Listen for value removed mgr.options.listen(EVENT_VALUE_REMOVED, events.append) mgr.receive_message("OpenZWave/1/node/2/instance/1/commandclass/4/value/3", "") assert len(events) == 3 assert events[0].id == 3	30.226415	83	0.65231	"""Provide tests for the node value.""" from openzwavemqtt.const import ( EVENT_VALUE_ADDED, EVENT_VALUE_CHANGED, EVENT_VALUE_REMOVED, ) def test_value_events(mgr): """Test value events.""" events = [] # Fill parent data. mgr.mock_receive_json("OpenZWave/1/node/2", {}) mgr.mock_receive_json("OpenZWave/1/node/2/instance/1", {}) mgr.mock_receive_json("OpenZWave/1/node/2/instance/1/commandclass/4", {}) # Listen for value added mgr.options.listen(EVENT_VALUE_ADDED, events.append) mgr.mock_receive_json( "OpenZWave/1/node/2/instance/1/commandclass/4/value/3", {"Value": "yo"} ) assert len(events) == 1 assert events[0].id == 3 assert events[0].value == "yo" assert events[0].parent.id == 4 # Test OZWNode.values shortcut assert list(mgr.get_instance(1).get_node(2).values())[0].id == 3 # Listen for value changed mgr.options.listen(EVENT_VALUE_CHANGED, events.append) mgr.mock_receive_json( "OpenZWave/1/node/2/instance/1/commandclass/4/value/3", {"Value": "yo2"} ) assert len(events) == 2 assert events[0].id == 3 assert events[0].value == "yo2" # Show how to use collection helpers assert ( list(mgr.get_instance(1).get_node(2).get_instance(1).commandclasses())[0] .get_value(3) .value == "yo2" ) # Listen for value removed mgr.options.listen(EVENT_VALUE_REMOVED, events.append) mgr.receive_message("OpenZWave/1/node/2/instance/1/commandclass/4/value/3", "") assert len(events) == 3 assert events[0].id == 3	0	0	0
7dc0816d12478814ffed3ae145d96cfd99595450	5,753	py	Python	hand_servo/JO_tester.py	JohnOmernik/pimeup	c68f84d699f67af71bb5561eb6c5885ccd8b4ac8	[ "Apache-2.0" ]	1	2017-10-21T16:52:21.000Z	2017-10-21T16:52:21.000Z	hand_servo/JO_tester.py	JohnOmernik/pimeup	c68f84d699f67af71bb5561eb6c5885ccd8b4ac8	[ "Apache-2.0" ]	null	null	null	hand_servo/JO_tester.py	JohnOmernik/pimeup	c68f84d699f67af71bb5561eb6c5885ccd8b4ac8	[ "Apache-2.0" ]	null	null	null	#!/usr/bin/python # Import the PCA9685 module. import Adafruit_PCA9685 import time import random import sys import json # Initialise the PCA9685 using the default address (0x40). pwm = Adafruit_PCA9685.PCA9685(0x40) pwm.set_pwm_freq(60) SRV_OPTIONS = [] ACTIONS = {} STATUS="" thingfile = "/home/pi/pimeup/thingbox/thing.json" thingactionfile = "/home/pi/pimeup/thingbox/thingactions.json" if __name__ == "__main__": main()	26.75814	158	0.460108	#!/usr/bin/python # Import the PCA9685 module. import Adafruit_PCA9685 import time import random import sys import json # Initialise the PCA9685 using the default address (0x40). pwm = Adafruit_PCA9685.PCA9685(0x40) pwm.set_pwm_freq(60) SRV_OPTIONS = [] ACTIONS = {} STATUS="" thingfile = "/home/pi/pimeup/thingbox/thing.json" thingactionfile = "/home/pi/pimeup/thingbox/thingactions.json" def main(): global SRV_OPTIONS global ACTIONS global STATUS SRV_OPTIONS = loadfile(thingfile) ACTIONS = loadfile(thingactionfile) cur_finger = -1 ACT_SHORT = [] upact = "" downact = "" for x in ACTIONS: if x['KEY'] == "U": upact = x['ACTION'] if x['KEY'] == "P": downact = x['ACTION'] ACT_SHORT.append(x['KEY']) # processAction(upact) while True: if cur_finger == -1: print("Current Status: %s" % STATUS) printServos() printAction() print("") srv_sel = raw_input("Servo to move or action: ") int_srv = -1 if srv_sel == "e": print("Exiting!") break if srv_sel in ACT_SHORT: processAction(srv_sel) else: try: int_srv = int(srv_sel) except: print("Selected Servors must be an integer or action in this list:") printServos() printAction() continue for y in SRV_OPTIONS: if int_srv == y['IDX']: cur_finger = int_srv break if cur_finger == int_srv: continue else: print("Servo provided (%s) not in the following List: Please try again") printServos() else: for y in SRV_OPTIONS: if cur_finger == y['IDX']: mysrv = y break print("Currently working with Servo: %s - Press q to quit this" % cur_finger) printServo(mysrv) while True: mv = raw_input("Enter Servo Value: ") if mv == 'q': cur_finger = -1 break else: try: myval = int(mv) except: print("You must enter a integer") continue pwm.set_pwm(cur_finger, 0, myval) processAction(downact) time.sleep(2) pwm.set_pwm(0, 4096, 0) pwm.set_pwm(1, 4096, 0) pwm.set_pwm(2, 4096, 0) pwm.set_pwm(3, 4096, 0) pwm.set_pwm(4, 4096, 0) pwm.set_pwm(5, 4096, 0) pwm.set_pwm(6, 4096, 0) pwm.set_pwm(7, 4096, 0) pwm.set_pwm(8, 4096, 0) sys.exit(0) def printServos(): print("") print ("All Available Servos: ") print("==============================") for x in SRV_OPTIONS: printServo(x) print("") def printServo(s): print("Servo Number: %s - Desc: %s - Min Movement: %s - Max Movement: %s - Notes: %s" % (s['IDX'], s['DESC'], s['RANGE_MIN'], s['RANGE_MAX'], s['NOTES'])) def printAction(): print("") print("Available Actions: ") print("==============================") for x in ACTIONS: print("\t%s - %s - %s" % (x['KEY'], x['NAME'], x['DESC'])) print("") def loadfile(f): o = open(f, "rb") tj = o.read() o.close() pj = "" for line in tj.split("\n"): if line.strip() == "" or line.strip().find("#") == 0: pass else: pj += line.strip() + "\n" print(pj) return json.loads(pj) def processAction(actKey): global STATUS act = {} bfound = False for x in ACTIONS: if actKey == x['KEY']: act = x bfound = True if bfound == True: new_status = act['STATUS'] req_status = act['REQ_STATUS'] actStr = act['ACTION'] if req_status != "": if STATUS.find(req_status) < 0: print("Can't do it") print("STATUS: %s" % STATUS) print("req_status: %s" % req_status) return print("Running Action: %s" % act['NAME']) for action in actStr.split(","): tval = action.split(":") act = tval[0] val = tval[1] if act == "P": val = float(val) time.sleep(val) elif act == "A": shutdown = False try: val = int(val) if val == 0: shutdown = True except: shutdown = False if shutdown == True: for x in range(len(SRV_OPTIONS) - 1): pwm.set_pwm(x, 4096, 0) else: processAction(val) else: act = int(act) val = int(val) if val >= 0: pwm.set_pwm(act, 0, val) else: pwm.set_pwm(act, 4096, 0) if new_status != "": STATUS = new_status def setServoPulse(channel, pulse): pulseLength = 1000000 # 1,000,000 us per second pulseLength /= 60 # 60 Hz print "%d us per period" % pulseLength pulseLength /= 4096 # 12 bits of resolution print "%d us per bit" % pulseLength pulse *= 1000 pulse /= pulseLength pwm.set_pwm(channel, 0, pulse) if __name__ == "__main__": main()	5,147	0	161
e0ffbfca22a90ed69e2f3f3cd411e0e7e7d7c239	13,384	py	Python	PyFlow/Core/GraphManager.py	luzpaz/PyFlow	e00642794051b1d9b7b2665eee38567e9763558d	[ "Apache-2.0" ]	1,463	2019-07-29T15:45:22.000Z	2022-03-31T23:32:13.000Z	PyFlow/Core/GraphManager.py	luzpaz/PyFlow	e00642794051b1d9b7b2665eee38567e9763558d	[ "Apache-2.0" ]	58	2019-07-31T07:58:57.000Z	2022-02-23T05:46:08.000Z	PyFlow/Core/GraphManager.py	luzpaz/PyFlow	e00642794051b1d9b7b2665eee38567e9763558d	[ "Apache-2.0" ]	169	2019-08-03T16:38:57.000Z	2022-03-31T14:20:12.000Z	## Copyright 2015-2019 Ilgar Lunin, Pedro Cabrera ## Licensed under the Apache License, Version 2.0 (the "License"); ## you may not use this file except in compliance with the License. ## You may obtain a copy of the License at ## http://www.apache.org/licenses/LICENSE-2.0 ## Unless required by applicable law or agreed to in writing, software ## distributed under the License is distributed on an "AS IS" BASIS, ## WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. ## See the License for the specific language governing permissions and ## limitations under the License. from nine import str from blinker import Signal from PyFlow.Core.GraphBase import GraphBase from PyFlow.Core.Common import * from PyFlow.Core import version ROOT_GRAPH_NAME = str('root') class GraphManager(object): """Data structure that holds graph tree This class switches active graph. Can insert or remove graphs to tree, can search nodes and variables across all graphs. Also this class responsible for giving unique names. """ def findRootGraph(self): """Returns top level root graph :rtype: :class:`~PyFlow.Core.GraphBase.GraphBase` """ roots = [] for graph in self.getAllGraphs(): if graph.isRoot(): roots.append(graph) assert(len(roots) == 1), "Fatal! Multiple roots!" return roots[0] def selectRootGraph(self): """Selects root graph """ self.selectGraph(self.findRootGraph()) def serialize(self): """Serializes itself to json. All child graphs will be serialized. :rtype: dict """ rootGraph = self.findRootGraph() saved = rootGraph.serialize() saved["fileVersion"] = str(version.currentVersion()) saved["activeGraph"] = self.activeGraph().name return saved def removeGraphByName(self, name): """Removes graph by :attr:`~PyFlow.Core.GraphBase.GraphBase.name` :param name: name of graph to be removed :type name: str """ graph = self.findGraph(name) if graph is not None: graph.clear() self._graphs.pop(graph.uid) if graph.parentGraph is not None: if graph in graph.parentGraph.childGraphs: graph.parentGraph.childGraphs.remove(graph) del graph def removeGraph(self, graph): """Removes supplied graph :param graph: Graph to be removed :type graph: :class:`~PyFlow.Core.GraphBase.GraphBase` """ if graph.uid in self._graphs: graph.clear() self._graphs.pop(graph.uid) if graph.parentGraph is not None: if graph in graph.parentGraph.childGraphs: graph.parentGraph.childGraphs.remove(graph) del graph def deserialize(self, data): """Populates itself from serialized data :param data: Serialized data :type data: dict """ if "fileVersion" in data: fileVersion = version.Version.fromString(data["fileVersion"]) else: # handle older version pass self.clear(keepRoot=False) self._activeGraph = GraphBase(str('root'), self) self._activeGraph.populateFromJson(data) self._activeGraph.setIsRoot(True) self.selectGraph(self._activeGraph) def clear(self, keepRoot=True, args, *kwargs): """Wipes everything. :param keepRoot: Whether to remove root graph or not :type keepRoot: bool """ self.selectGraphByName(ROOT_GRAPH_NAME) self.removeGraphByName(ROOT_GRAPH_NAME) self._graphs.clear() self._graphs = {} del self._activeGraph self._activeGraph = None if keepRoot: self._activeGraph = GraphBase(ROOT_GRAPH_NAME, self) self.selectGraph(self._activeGraph) self._activeGraph.setIsRoot(True) def Tick(self, deltaTime): """Periodically calls :meth:`~PyFlow.Core.GraphBase.GraphBase.Tick` on all graphs :param deltaTime: Elapsed time from last call :type deltaTime: float """ for graph in self._graphs.values(): graph.Tick(deltaTime) def findVariableRefs(self, variable): """Returns a list of variable accessors spawned across all graphs :param variable: Variable to search accessors for :type variable: :class:`~PyFlow.Core.Variable.Variable` :rtype: list(:class:`~PyFlow.Core.NodeBase.NodeBase`) """ result = [] for node in self.getAllNodes(classNameFilters=['getVar', 'setVar']): if node.variableUid() == variable.uid: result.append(node) return result def findGraph(self, name): """Tries to find graph by :attr:`~PyFlow.Core.GraphBase.GraphBase.name` :param name: Name of target graph :type name: str :rtype: :class:`~PyFlow.Core.GraphBase.GraphBase` or None """ graphs = self.getGraphsDict() if name in graphs: return graphs[name] return None def findPinByName(self, pinFullName): """Tries to find pin by name across all graphs :param pinFullName: Full name of pin including node namespace :type pinFullName: str :rtype: :class:`~PyFlow.Core.PinBase.PinBase` or None """ result = None for graph in self.getAllGraphs(): result = graph.findPin(pinFullName) if result is not None: break return result def findNode(self, name): """Finds a node across all graphs :param name: Node name to search by :type name: str :rtype: :class:`~PyFlow.Core.NodeBase.NodeBase` """ result = None for graph in self.getAllGraphs(): result = graph.findNode(name) if result is not None: break return result def findVariableByUid(self, uuid): """Finds a variable across all graphs :param uuid: Variable unique identifier :type uuid: :class:`~uuid.UUID` :rtype: :class:`~PyFlow.Core.Variable.Variable` or None """ result = None for graph in self._graphs.values(): if uuid in graph.getVars(): result = graph.getVars()[uuid] break return result def findVariableByName(self, name): """Finds a variable across all graphs :param name: Variable name :type name: str :rtype: :class:`~PyFlow.Core.Variable.Variable` or None """ for graph in self._graphs.values(): for var in graph.getVars().values(): if var.name == name: return var return None def location(self): """Returns location of active graph .. seealso :: :meth:`PyFlow.Core.GraphBase.GraphBase.location` """ return self.activeGraph().location() def getGraphsDict(self): """Creates and returns dictionary where graph name associated with graph :rtype: dict(str, :class:`~PyFlow.Core.GraphBase.GraphBase`) """ result = {} for graph in self.getAllGraphs(): result[graph.name] = graph return result def add(self, graph): """Adds graph to storage and ensures that graph name is unique :param graph: Graph to add :type graph: :class:`~PyFlow.Core.GraphBase.GraphBase` """ graph.name = self.getUniqGraphName(graph.name) self._graphs[graph.uid] = graph def activeGraph(self): """Returns active graph :rtype: :class:`~PyFlow.Core.GraphBase.GraphBase` """ return self._activeGraph def selectGraphByName(self, name): """Sets active graph by graph name and fires event :param name: Name of target graph :type name: str """ graphs = self.getGraphsDict() if name in graphs: if name != self.activeGraph().name: oldGraph = self.activeGraph() newGraph = graphs[name] self._activeGraph = newGraph self.graphChanged.send(self.activeGraph()) def selectGraph(self, graph): """Sets supplied graph as active and fires event :param graph: Target graph :type graph: :class:`~PyFlow.Core.GraphBase.GraphBase` """ for newGraph in self.getAllGraphs(): if newGraph.name == graph.name: if newGraph.name != self.activeGraph().name: oldGraph = self.activeGraph() self._activeGraph = newGraph self.graphChanged.send(self.activeGraph()) break def getAllGraphs(self): """Returns all graphs :rtype: list(:class:`~PyFlow.Core.GraphBase.GraphBase`) """ return [g for g in self._graphs.values()] def getAllNodes(self, classNameFilters=[]): """Returns all nodes across all graphs :param classNameFilters: If class name filters specified, only those node classes will be considered :type classNameFilters: list(str) :rtype: list(:class:`~PyFlow.Core.NodeBase.NodeBase`) """ allNodes = [] for graph in self.getAllGraphs(): if len(classNameFilters) == 0: allNodes.extend(list(graph.getNodes().values())) else: allNodes.extend([node for node in graph.getNodes().values() if node.__class__.__name__ in classNameFilters]) return allNodes def getAllVariables(self): """Returns a list of all variables :rtype: list(:class:`~PyFlow.Core.Variable.Variable`) """ result = [] for graph in self.getAllGraphs(): result.extend(list(graph.getVars().values())) return result def getUniqGraphPinName(self, graph, name): """Returns unique pin name for graph Used by compound node and graphInputs graphOutputs nodes. To make all exposed to compound pins names unique. :param graph: Target graph :type graph: :class:`~PyFlow.Core.GraphBase.GraphBase` :param name: Target pin name :type name: str :rtype: str """ existingNames = [] for node in graph.getNodesList(classNameFilters=['graphInputs', 'graphOutputs']): existingNames.extend([pin.name for pin in node.pins]) return getUniqNameFromList(existingNames, name) def getAllNames(self): """Returns list of all registered names Includes graphs, nodes, pins, variables names :rtype: list(str) """ existingNames = [g.name for g in self.getAllGraphs()] existingNames.extend([n.name for n in self.getAllNodes()]) existingNames.extend([var.name for var in self.getAllVariables()]) for node in self.getAllNodes(): existingNames.extend([pin.name for pin in node.pins]) return existingNames def getUniqName(self, name): """Returns unique name :param name: Source name :type name: str :rtype: str """ existingNames = self.getAllNames() return getUniqNameFromList(existingNames, name) def getUniqGraphName(self, name): """Returns unique graph name :param name: Source name :type name: str :rtype: str """ existingNames = [g.name for g in self.getAllGraphs()] return getUniqNameFromList(existingNames, name) def getUniqNodeName(self, name): """Returns unique node name :param name: Source name :type name: str :rtype: str """ existingNames = [n.name for n in self.getAllNodes()] return getUniqNameFromList(existingNames, name) def getUniqVariableName(self, name): """Returns unique variable name :param name: Source name :type name: str :rtype: str """ existingNames = [var.name for var in self.getAllVariables()] return getUniqNameFromList(existingNames, name) def plot(self): """Prints all data to console. May be useful for debugging """ root = self.findRootGraph() print("Active graph: {0}".format(str(self.activeGraph().name)), "All graphs:", [g.name for g in self._graphs.values()]) root.plot() @SingletonDecorator class GraphManagerSingleton(object): """Singleton class that holds graph manager instance inside. Used by app as main graph manager """ def get(self): """Returns graph manager instance :rtype: :class:`~PyFlow.Core.GraphManager.GraphManager` """ return self.man	32.485437	127	0.605424	## Copyright 2015-2019 Ilgar Lunin, Pedro Cabrera ## Licensed under the Apache License, Version 2.0 (the "License"); ## you may not use this file except in compliance with the License. ## You may obtain a copy of the License at ## http://www.apache.org/licenses/LICENSE-2.0 ## Unless required by applicable law or agreed to in writing, software ## distributed under the License is distributed on an "AS IS" BASIS, ## WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. ## See the License for the specific language governing permissions and ## limitations under the License. from nine import str from blinker import Signal from PyFlow.Core.GraphBase import GraphBase from PyFlow.Core.Common import * from PyFlow.Core import version ROOT_GRAPH_NAME = str('root') class GraphManager(object): """Data structure that holds graph tree This class switches active graph. Can insert or remove graphs to tree, can search nodes and variables across all graphs. Also this class responsible for giving unique names. """ def __init__(self): super(GraphManager, self).__init__() self.terminationRequested = False #: used by cli only self.graphChanged = Signal(object) self._graphs = {} self._activeGraph = None self._activeGraph = GraphBase(ROOT_GRAPH_NAME, self) self._activeGraph.setIsRoot(True) def findRootGraph(self): """Returns top level root graph :rtype: :class:`~PyFlow.Core.GraphBase.GraphBase` """ roots = [] for graph in self.getAllGraphs(): if graph.isRoot(): roots.append(graph) assert(len(roots) == 1), "Fatal! Multiple roots!" return roots[0] def selectRootGraph(self): """Selects root graph """ self.selectGraph(self.findRootGraph()) def serialize(self): """Serializes itself to json. All child graphs will be serialized. :rtype: dict """ rootGraph = self.findRootGraph() saved = rootGraph.serialize() saved["fileVersion"] = str(version.currentVersion()) saved["activeGraph"] = self.activeGraph().name return saved def removeGraphByName(self, name): """Removes graph by :attr:`~PyFlow.Core.GraphBase.GraphBase.name` :param name: name of graph to be removed :type name: str """ graph = self.findGraph(name) if graph is not None: graph.clear() self._graphs.pop(graph.uid) if graph.parentGraph is not None: if graph in graph.parentGraph.childGraphs: graph.parentGraph.childGraphs.remove(graph) del graph def removeGraph(self, graph): """Removes supplied graph :param graph: Graph to be removed :type graph: :class:`~PyFlow.Core.GraphBase.GraphBase` """ if graph.uid in self._graphs: graph.clear() self._graphs.pop(graph.uid) if graph.parentGraph is not None: if graph in graph.parentGraph.childGraphs: graph.parentGraph.childGraphs.remove(graph) del graph def deserialize(self, data): """Populates itself from serialized data :param data: Serialized data :type data: dict """ if "fileVersion" in data: fileVersion = version.Version.fromString(data["fileVersion"]) else: # handle older version pass self.clear(keepRoot=False) self._activeGraph = GraphBase(str('root'), self) self._activeGraph.populateFromJson(data) self._activeGraph.setIsRoot(True) self.selectGraph(self._activeGraph) def clear(self, keepRoot=True, args, *kwargs): """Wipes everything. :param keepRoot: Whether to remove root graph or not :type keepRoot: bool """ self.selectGraphByName(ROOT_GRAPH_NAME) self.removeGraphByName(ROOT_GRAPH_NAME) self._graphs.clear() self._graphs = {} del self._activeGraph self._activeGraph = None if keepRoot: self._activeGraph = GraphBase(ROOT_GRAPH_NAME, self) self.selectGraph(self._activeGraph) self._activeGraph.setIsRoot(True) def Tick(self, deltaTime): """Periodically calls :meth:`~PyFlow.Core.GraphBase.GraphBase.Tick` on all graphs :param deltaTime: Elapsed time from last call :type deltaTime: float """ for graph in self._graphs.values(): graph.Tick(deltaTime) def findVariableRefs(self, variable): """Returns a list of variable accessors spawned across all graphs :param variable: Variable to search accessors for :type variable: :class:`~PyFlow.Core.Variable.Variable` :rtype: list(:class:`~PyFlow.Core.NodeBase.NodeBase`) """ result = [] for node in self.getAllNodes(classNameFilters=['getVar', 'setVar']): if node.variableUid() == variable.uid: result.append(node) return result def findGraph(self, name): """Tries to find graph by :attr:`~PyFlow.Core.GraphBase.GraphBase.name` :param name: Name of target graph :type name: str :rtype: :class:`~PyFlow.Core.GraphBase.GraphBase` or None """ graphs = self.getGraphsDict() if name in graphs: return graphs[name] return None def findPinByName(self, pinFullName): """Tries to find pin by name across all graphs :param pinFullName: Full name of pin including node namespace :type pinFullName: str :rtype: :class:`~PyFlow.Core.PinBase.PinBase` or None """ result = None for graph in self.getAllGraphs(): result = graph.findPin(pinFullName) if result is not None: break return result def findNode(self, name): """Finds a node across all graphs :param name: Node name to search by :type name: str :rtype: :class:`~PyFlow.Core.NodeBase.NodeBase` """ result = None for graph in self.getAllGraphs(): result = graph.findNode(name) if result is not None: break return result def findVariableByUid(self, uuid): """Finds a variable across all graphs :param uuid: Variable unique identifier :type uuid: :class:`~uuid.UUID` :rtype: :class:`~PyFlow.Core.Variable.Variable` or None """ result = None for graph in self._graphs.values(): if uuid in graph.getVars(): result = graph.getVars()[uuid] break return result def findVariableByName(self, name): """Finds a variable across all graphs :param name: Variable name :type name: str :rtype: :class:`~PyFlow.Core.Variable.Variable` or None """ for graph in self._graphs.values(): for var in graph.getVars().values(): if var.name == name: return var return None def location(self): """Returns location of active graph .. seealso :: :meth:`PyFlow.Core.GraphBase.GraphBase.location` """ return self.activeGraph().location() def getGraphsDict(self): """Creates and returns dictionary where graph name associated with graph :rtype: dict(str, :class:`~PyFlow.Core.GraphBase.GraphBase`) """ result = {} for graph in self.getAllGraphs(): result[graph.name] = graph return result def add(self, graph): """Adds graph to storage and ensures that graph name is unique :param graph: Graph to add :type graph: :class:`~PyFlow.Core.GraphBase.GraphBase` """ graph.name = self.getUniqGraphName(graph.name) self._graphs[graph.uid] = graph def activeGraph(self): """Returns active graph :rtype: :class:`~PyFlow.Core.GraphBase.GraphBase` """ return self._activeGraph def selectGraphByName(self, name): """Sets active graph by graph name and fires event :param name: Name of target graph :type name: str """ graphs = self.getGraphsDict() if name in graphs: if name != self.activeGraph().name: oldGraph = self.activeGraph() newGraph = graphs[name] self._activeGraph = newGraph self.graphChanged.send(self.activeGraph()) def selectGraph(self, graph): """Sets supplied graph as active and fires event :param graph: Target graph :type graph: :class:`~PyFlow.Core.GraphBase.GraphBase` """ for newGraph in self.getAllGraphs(): if newGraph.name == graph.name: if newGraph.name != self.activeGraph().name: oldGraph = self.activeGraph() self._activeGraph = newGraph self.graphChanged.send(self.activeGraph()) break def getAllGraphs(self): """Returns all graphs :rtype: list(:class:`~PyFlow.Core.GraphBase.GraphBase`) """ return [g for g in self._graphs.values()] def getAllNodes(self, classNameFilters=[]): """Returns all nodes across all graphs :param classNameFilters: If class name filters specified, only those node classes will be considered :type classNameFilters: list(str) :rtype: list(:class:`~PyFlow.Core.NodeBase.NodeBase`) """ allNodes = [] for graph in self.getAllGraphs(): if len(classNameFilters) == 0: allNodes.extend(list(graph.getNodes().values())) else: allNodes.extend([node for node in graph.getNodes().values() if node.__class__.__name__ in classNameFilters]) return allNodes def getAllVariables(self): """Returns a list of all variables :rtype: list(:class:`~PyFlow.Core.Variable.Variable`) """ result = [] for graph in self.getAllGraphs(): result.extend(list(graph.getVars().values())) return result def getUniqGraphPinName(self, graph, name): """Returns unique pin name for graph Used by compound node and graphInputs graphOutputs nodes. To make all exposed to compound pins names unique. :param graph: Target graph :type graph: :class:`~PyFlow.Core.GraphBase.GraphBase` :param name: Target pin name :type name: str :rtype: str """ existingNames = [] for node in graph.getNodesList(classNameFilters=['graphInputs', 'graphOutputs']): existingNames.extend([pin.name for pin in node.pins]) return getUniqNameFromList(existingNames, name) def getAllNames(self): """Returns list of all registered names Includes graphs, nodes, pins, variables names :rtype: list(str) """ existingNames = [g.name for g in self.getAllGraphs()] existingNames.extend([n.name for n in self.getAllNodes()]) existingNames.extend([var.name for var in self.getAllVariables()]) for node in self.getAllNodes(): existingNames.extend([pin.name for pin in node.pins]) return existingNames def getUniqName(self, name): """Returns unique name :param name: Source name :type name: str :rtype: str """ existingNames = self.getAllNames() return getUniqNameFromList(existingNames, name) def getUniqGraphName(self, name): """Returns unique graph name :param name: Source name :type name: str :rtype: str """ existingNames = [g.name for g in self.getAllGraphs()] return getUniqNameFromList(existingNames, name) def getUniqNodeName(self, name): """Returns unique node name :param name: Source name :type name: str :rtype: str """ existingNames = [n.name for n in self.getAllNodes()] return getUniqNameFromList(existingNames, name) def getUniqVariableName(self, name): """Returns unique variable name :param name: Source name :type name: str :rtype: str """ existingNames = [var.name for var in self.getAllVariables()] return getUniqNameFromList(existingNames, name) def plot(self): """Prints all data to console. May be useful for debugging """ root = self.findRootGraph() print("Active graph: {0}".format(str(self.activeGraph().name)), "All graphs:", [g.name for g in self._graphs.values()]) root.plot() @SingletonDecorator class GraphManagerSingleton(object): """Singleton class that holds graph manager instance inside. Used by app as main graph manager """ def __init__(self): self.man = GraphManager() def get(self): """Returns graph manager instance :rtype: :class:`~PyFlow.Core.GraphManager.GraphManager` """ return self.man	343	0	52
e00d9fd40434cd4d86af85a211851d99b4589f1a	9,011	py	Python	rethinkdb/tests/common.py	mchelen-gov/integrations-core	81281600b3cc7025a7a32148c59620c9592a564f	[ "BSD-3-Clause" ]	663	2016-08-23T05:23:45.000Z	2022-03-29T00:37:23.000Z	rethinkdb/tests/common.py	mchelen-gov/integrations-core	81281600b3cc7025a7a32148c59620c9592a564f	[ "BSD-3-Clause" ]	6,642	2016-06-09T16:29:20.000Z	2022-03-31T22:24:09.000Z	rethinkdb/tests/common.py	mchelen-gov/integrations-core	81281600b3cc7025a7a32148c59620c9592a564f	[ "BSD-3-Clause" ]	1,222	2017-01-27T15:51:38.000Z	2022-03-31T18:17:51.000Z	# (C) Datadog, Inc. 2020-present # All rights reserved # Licensed under a 3-clause BSD style license (see LICENSE) import os from typing import Callable, Dict, List, Set, Tuple, Union import pytest from datadog_checks.base.stubs.aggregator import AggregatorStub from datadog_checks.dev import get_docker_hostname, get_here from .types import ServerName HERE = get_here() IMAGE = os.environ.get('RETHINKDB_IMAGE', '') RAW_VERSION = os.environ.get('RETHINKDB_RAW_VERSION', '') IS_RETHINKDB_2_3 = RAW_VERSION.startswith('2.3.') HOST = get_docker_hostname() TAGS = ['rethinkdb_env:testing'] # Servers. # NOTE: server information is tightly coupled to the Docker Compose setup. SERVERS = {'server0', 'server1', 'server2'} # type: Set[ServerName] BOOTSTRAP_SERVER = 'server0' # type: ServerName SERVER_PORTS = {'server0': 28015, 'server1': 28016, 'server2': 28017, 'proxy': 28018} # type: Dict[ServerName, int] FORMATTED_SERVER_TAGS = { 'server0': ['server_tag:default', 'server_tag:us'], 'server1': ['server_tag:default', 'server_tag:us', 'server_tag:primary'], 'server2': ['server_tag:default', 'server_tag:eu'], } # type: Dict[ServerName, List[str]] # Users. if IS_RETHINKDB_2_3: # In RethinkDB 2.3.x, granting permissions onto `rethinkdb` database to non-admin users is not supported. # So we must use the admin account. # See: https://github.com/rethinkdb/rethinkdb/issues/5692 AGENT_USER = 'admin' AGENT_PASSWORD = '' else: # Use a dedicated user for metric collection. AGENT_USER = 'datadog-agent' AGENT_PASSWORD = 'r3th1nK' CLIENT_USER = 'doggo' # TLS. TLS_SERVER = 'server1' # type: ServerName TLS_DRIVER_KEY = os.path.join(HERE, 'data', 'tls', 'server.key') TLS_DRIVER_CERT = os.path.join(HERE, 'data', 'tls', 'server.pem') TLS_CLIENT_CERT = os.path.join(HERE, 'data', 'tls', 'client.pem') # Database content. DATABASE = 'doghouse' HEROES_TABLE = 'heroes' HEROES_TABLE_CONFIG = { 'shards': 1, 'replicas': {'primary': 1, 'eu': 1}, 'primary_replica_tag': 'primary', } HEROES_TABLE_SERVERS = {'server1', 'server2'} # type: Set[ServerName] HEROES_TABLE_PRIMARY_REPLICA = 'server1' # type: ServerName HEROES_TABLE_REPLICAS_BY_SHARD = {0: HEROES_TABLE_SERVERS} HEROES_TABLE_DOCUMENTS = [ { "hero": "Magneto", "name": "Max Eisenhardt", "aka": ["Magnus", "Erik Lehnsherr", "Lehnsherr"], "magazine_titles": ["Alpha Flight", "Avengers", "Avengers West Coast"], "appearances_count": 42, }, { "hero": "Professor Xavier", "name": "Charles Francis Xavier", "magazine_titles": ["Alpha Flight", "Avengers", "Bishop", "Defenders"], "appearances_count": 72, }, { "hero": "Storm", "name": "Ororo Monroe", "magazine_titles": ["Amazing Spider-Man vs. Wolverine", "Excalibur", "Fantastic Four", "Iron Fist"], "appearances_count": 72, }, ] HEROES_TABLE_INDEX_FIELD = 'appearances_count' # Metrics lists. # NOTE: jobs metrics are not listed here as they're hard to trigger, so they're covered by unit tests instead. CONFIG_METRICS = ( ( 'rethinkdb.config.servers', AggregatorStub.GAUGE, lambda disconnected_servers: len(SERVERS) - len(disconnected_servers), [], ), ('rethinkdb.config.databases', AggregatorStub.GAUGE, 1, []), ('rethinkdb.config.tables_per_database', AggregatorStub.GAUGE, 1, ['database:{}'.format(DATABASE)]), ('rethinkdb.config.secondary_indexes_per_table', AggregatorStub.GAUGE, 1, ['table:{}'.format(HEROES_TABLE)]), ) # type: Tuple[Tuple[str, int, Union[int, Callable[[set], int]], List[str]], ...] CLUSTER_STATISTICS_METRICS = ( ('rethinkdb.stats.cluster.query_engine.queries_per_sec', AggregatorStub.GAUGE), ('rethinkdb.stats.cluster.query_engine.read_docs_per_sec', AggregatorStub.GAUGE), ('rethinkdb.stats.cluster.query_engine.written_docs_per_sec', AggregatorStub.GAUGE), ) # type: Tuple[Tuple[str, int], ...] SERVER_STATISTICS_METRICS = ( ('rethinkdb.stats.server.query_engine.queries_per_sec', AggregatorStub.GAUGE), ('rethinkdb.stats.server.query_engine.queries_total', AggregatorStub.MONOTONIC_COUNT), ('rethinkdb.stats.server.query_engine.read_docs_per_sec', AggregatorStub.GAUGE), ('rethinkdb.stats.server.query_engine.read_docs_total', AggregatorStub.MONOTONIC_COUNT), ('rethinkdb.stats.server.query_engine.written_docs_per_sec', AggregatorStub.GAUGE), ('rethinkdb.stats.server.query_engine.written_docs_total', AggregatorStub.MONOTONIC_COUNT), ('rethinkdb.stats.server.query_engine.client_connections', AggregatorStub.GAUGE), ( # NOTE: submitted but not documented on the RethinkDB website. 'rethinkdb.stats.server.query_engine.clients_active', AggregatorStub.GAUGE, ), ) # type: Tuple[Tuple[str, int], ...] TABLE_STATISTICS_METRICS = ( ('rethinkdb.stats.table.query_engine.read_docs_per_sec', AggregatorStub.GAUGE), ('rethinkdb.stats.table.query_engine.written_docs_per_sec', AggregatorStub.GAUGE), ) # type: Tuple[Tuple[str, int], ...] REPLICA_STATISTICS_METRICS = ( ('rethinkdb.stats.table_server.query_engine.read_docs_per_sec', AggregatorStub.GAUGE), ('rethinkdb.stats.table_server.query_engine.read_docs_total', AggregatorStub.MONOTONIC_COUNT), ('rethinkdb.stats.table_server.query_engine.written_docs_per_sec', AggregatorStub.GAUGE), ('rethinkdb.stats.table_server.query_engine.written_docs_total', AggregatorStub.MONOTONIC_COUNT), ('rethinkdb.stats.table_server.storage_engine.cache.in_use_bytes', AggregatorStub.GAUGE), ('rethinkdb.stats.table_server.storage_engine.disk.read_bytes_per_sec', AggregatorStub.GAUGE), ('rethinkdb.stats.table_server.storage_engine.disk.read_bytes_total', AggregatorStub.MONOTONIC_COUNT), ('rethinkdb.stats.table_server.storage_engine.disk.written_bytes_per_sec', AggregatorStub.GAUGE), ('rethinkdb.stats.table_server.storage_engine.disk.written_bytes_total', AggregatorStub.MONOTONIC_COUNT), ('rethinkdb.stats.table_server.storage_engine.disk.space_usage.metadata_bytes', AggregatorStub.GAUGE), ('rethinkdb.stats.table_server.storage_engine.disk.space_usage.data_bytes', AggregatorStub.GAUGE), ('rethinkdb.stats.table_server.storage_engine.disk.space_usage.garbage_bytes', AggregatorStub.GAUGE), ('rethinkdb.stats.table_server.storage_engine.disk.space_usage.preallocated_bytes', AggregatorStub.GAUGE), ) # type: Tuple[Tuple[str, int], ...] TABLE_STATUS_SERVICE_CHECKS = ( 'rethinkdb.table_status.status.ready_for_outdated_reads', 'rethinkdb.table_status.status.ready_for_reads', 'rethinkdb.table_status.status.ready_for_writes', 'rethinkdb.table_status.status.all_replicas_ready', ) TABLE_STATUS_METRICS = (('rethinkdb.table_status.shards', AggregatorStub.GAUGE),) # type: Tuple[Tuple[str, int], ...] TABLE_STATUS_SHARDS_METRICS = ( ('rethinkdb.table_status.shards.replicas', AggregatorStub.GAUGE), ('rethinkdb.table_status.shards.primary_replicas', AggregatorStub.GAUGE), ) # type: Tuple[Tuple[str, int], ...] SERVER_STATUS_METRICS = ( ('rethinkdb.server_status.network.time_connected', AggregatorStub.GAUGE), ('rethinkdb.server_status.network.connected_to', AggregatorStub.GAUGE), ('rethinkdb.server_status.process.time_started', AggregatorStub.GAUGE), ) # type: Tuple[Tuple[str, int], ...] JOBS_METRICS = ( ( 'rethinkdb.system_jobs.jobs', AggregatorStub.GAUGE, 1, ['job_type:query'], ), ) # type: Tuple[Tuple[str, int, int, List[str]], ...] CURRENT_ISSUES_METRICS = ( ('rethinkdb.current_issues.issues', AggregatorStub.GAUGE), ('rethinkdb.current_issues.critical_issues', AggregatorStub.GAUGE), ) # type: Tuple[Tuple[str, int], ...] CURRENT_ISSUE_TYPES_SUBMITTED_IF_DISCONNECTED_SERVERS = ['table_availability'] E2E_METRICS = ( tuple((name, typ) for name, typ, _, _ in CONFIG_METRICS) + CLUSTER_STATISTICS_METRICS + SERVER_STATISTICS_METRICS + TABLE_STATISTICS_METRICS + REPLICA_STATISTICS_METRICS + TABLE_STATUS_METRICS + TABLE_STATUS_SHARDS_METRICS + SERVER_STATUS_METRICS + tuple((name, typ) for name, typ, _, _ in JOBS_METRICS) ) # type: Tuple[Tuple[str, int], ...] # Docker Compose configuration. COMPOSE_FILE = os.path.join(HERE, 'compose', 'docker-compose.yaml') COMPOSE_ENV_VARS = env_vars = { 'RETHINKDB_IMAGE': IMAGE, 'RETHINKDB_PORT_SERVER0': str(SERVER_PORTS['server0']), 'RETHINKDB_PORT_SERVER1': str(SERVER_PORTS['server1']), 'RETHINKDB_PORT_SERVER2': str(SERVER_PORTS['server2']), 'RETHINKDB_PORT_PROXY': str(SERVER_PORTS['proxy']), 'RETHINKDB_TLS_DRIVER_KEY': TLS_DRIVER_KEY, 'RETHINKDB_TLS_DRIVER_CERT': TLS_DRIVER_CERT, } # Pytest common test data. MALFORMED_VERSION_STRING_PARAMS = [ pytest.param('rethinkdb (GCC 4.9.2)', id='no-version'), pytest.param('rethinkdb', id='prefix-only'), pytest.param('abc 2.4.0~0bionic (GCC 4.9.2)', id='wrong-prefix'), ]	40.959091	118	0.724559	# (C) Datadog, Inc. 2020-present # All rights reserved # Licensed under a 3-clause BSD style license (see LICENSE) import os from typing import Callable, Dict, List, Set, Tuple, Union import pytest from datadog_checks.base.stubs.aggregator import AggregatorStub from datadog_checks.dev import get_docker_hostname, get_here from .types import ServerName HERE = get_here() IMAGE = os.environ.get('RETHINKDB_IMAGE', '') RAW_VERSION = os.environ.get('RETHINKDB_RAW_VERSION', '') IS_RETHINKDB_2_3 = RAW_VERSION.startswith('2.3.') HOST = get_docker_hostname() TAGS = ['rethinkdb_env:testing'] # Servers. # NOTE: server information is tightly coupled to the Docker Compose setup. SERVERS = {'server0', 'server1', 'server2'} # type: Set[ServerName] BOOTSTRAP_SERVER = 'server0' # type: ServerName SERVER_PORTS = {'server0': 28015, 'server1': 28016, 'server2': 28017, 'proxy': 28018} # type: Dict[ServerName, int] FORMATTED_SERVER_TAGS = { 'server0': ['server_tag:default', 'server_tag:us'], 'server1': ['server_tag:default', 'server_tag:us', 'server_tag:primary'], 'server2': ['server_tag:default', 'server_tag:eu'], } # type: Dict[ServerName, List[str]] # Users. if IS_RETHINKDB_2_3: # In RethinkDB 2.3.x, granting permissions onto `rethinkdb` database to non-admin users is not supported. # So we must use the admin account. # See: https://github.com/rethinkdb/rethinkdb/issues/5692 AGENT_USER = 'admin' AGENT_PASSWORD = '' else: # Use a dedicated user for metric collection. AGENT_USER = 'datadog-agent' AGENT_PASSWORD = 'r3th1nK' CLIENT_USER = 'doggo' # TLS. TLS_SERVER = 'server1' # type: ServerName TLS_DRIVER_KEY = os.path.join(HERE, 'data', 'tls', 'server.key') TLS_DRIVER_CERT = os.path.join(HERE, 'data', 'tls', 'server.pem') TLS_CLIENT_CERT = os.path.join(HERE, 'data', 'tls', 'client.pem') # Database content. DATABASE = 'doghouse' HEROES_TABLE = 'heroes' HEROES_TABLE_CONFIG = { 'shards': 1, 'replicas': {'primary': 1, 'eu': 1}, 'primary_replica_tag': 'primary', } HEROES_TABLE_SERVERS = {'server1', 'server2'} # type: Set[ServerName] HEROES_TABLE_PRIMARY_REPLICA = 'server1' # type: ServerName HEROES_TABLE_REPLICAS_BY_SHARD = {0: HEROES_TABLE_SERVERS} HEROES_TABLE_DOCUMENTS = [ { "hero": "Magneto", "name": "Max Eisenhardt", "aka": ["Magnus", "Erik Lehnsherr", "Lehnsherr"], "magazine_titles": ["Alpha Flight", "Avengers", "Avengers West Coast"], "appearances_count": 42, }, { "hero": "Professor Xavier", "name": "Charles Francis Xavier", "magazine_titles": ["Alpha Flight", "Avengers", "Bishop", "Defenders"], "appearances_count": 72, }, { "hero": "Storm", "name": "Ororo Monroe", "magazine_titles": ["Amazing Spider-Man vs. Wolverine", "Excalibur", "Fantastic Four", "Iron Fist"], "appearances_count": 72, }, ] HEROES_TABLE_INDEX_FIELD = 'appearances_count' # Metrics lists. # NOTE: jobs metrics are not listed here as they're hard to trigger, so they're covered by unit tests instead. CONFIG_METRICS = ( ( 'rethinkdb.config.servers', AggregatorStub.GAUGE, lambda disconnected_servers: len(SERVERS) - len(disconnected_servers), [], ), ('rethinkdb.config.databases', AggregatorStub.GAUGE, 1, []), ('rethinkdb.config.tables_per_database', AggregatorStub.GAUGE, 1, ['database:{}'.format(DATABASE)]), ('rethinkdb.config.secondary_indexes_per_table', AggregatorStub.GAUGE, 1, ['table:{}'.format(HEROES_TABLE)]), ) # type: Tuple[Tuple[str, int, Union[int, Callable[[set], int]], List[str]], ...] CLUSTER_STATISTICS_METRICS = ( ('rethinkdb.stats.cluster.query_engine.queries_per_sec', AggregatorStub.GAUGE), ('rethinkdb.stats.cluster.query_engine.read_docs_per_sec', AggregatorStub.GAUGE), ('rethinkdb.stats.cluster.query_engine.written_docs_per_sec', AggregatorStub.GAUGE), ) # type: Tuple[Tuple[str, int], ...] SERVER_STATISTICS_METRICS = ( ('rethinkdb.stats.server.query_engine.queries_per_sec', AggregatorStub.GAUGE), ('rethinkdb.stats.server.query_engine.queries_total', AggregatorStub.MONOTONIC_COUNT), ('rethinkdb.stats.server.query_engine.read_docs_per_sec', AggregatorStub.GAUGE), ('rethinkdb.stats.server.query_engine.read_docs_total', AggregatorStub.MONOTONIC_COUNT), ('rethinkdb.stats.server.query_engine.written_docs_per_sec', AggregatorStub.GAUGE), ('rethinkdb.stats.server.query_engine.written_docs_total', AggregatorStub.MONOTONIC_COUNT), ('rethinkdb.stats.server.query_engine.client_connections', AggregatorStub.GAUGE), ( # NOTE: submitted but not documented on the RethinkDB website. 'rethinkdb.stats.server.query_engine.clients_active', AggregatorStub.GAUGE, ), ) # type: Tuple[Tuple[str, int], ...] TABLE_STATISTICS_METRICS = ( ('rethinkdb.stats.table.query_engine.read_docs_per_sec', AggregatorStub.GAUGE), ('rethinkdb.stats.table.query_engine.written_docs_per_sec', AggregatorStub.GAUGE), ) # type: Tuple[Tuple[str, int], ...] REPLICA_STATISTICS_METRICS = ( ('rethinkdb.stats.table_server.query_engine.read_docs_per_sec', AggregatorStub.GAUGE), ('rethinkdb.stats.table_server.query_engine.read_docs_total', AggregatorStub.MONOTONIC_COUNT), ('rethinkdb.stats.table_server.query_engine.written_docs_per_sec', AggregatorStub.GAUGE), ('rethinkdb.stats.table_server.query_engine.written_docs_total', AggregatorStub.MONOTONIC_COUNT), ('rethinkdb.stats.table_server.storage_engine.cache.in_use_bytes', AggregatorStub.GAUGE), ('rethinkdb.stats.table_server.storage_engine.disk.read_bytes_per_sec', AggregatorStub.GAUGE), ('rethinkdb.stats.table_server.storage_engine.disk.read_bytes_total', AggregatorStub.MONOTONIC_COUNT), ('rethinkdb.stats.table_server.storage_engine.disk.written_bytes_per_sec', AggregatorStub.GAUGE), ('rethinkdb.stats.table_server.storage_engine.disk.written_bytes_total', AggregatorStub.MONOTONIC_COUNT), ('rethinkdb.stats.table_server.storage_engine.disk.space_usage.metadata_bytes', AggregatorStub.GAUGE), ('rethinkdb.stats.table_server.storage_engine.disk.space_usage.data_bytes', AggregatorStub.GAUGE), ('rethinkdb.stats.table_server.storage_engine.disk.space_usage.garbage_bytes', AggregatorStub.GAUGE), ('rethinkdb.stats.table_server.storage_engine.disk.space_usage.preallocated_bytes', AggregatorStub.GAUGE), ) # type: Tuple[Tuple[str, int], ...] TABLE_STATUS_SERVICE_CHECKS = ( 'rethinkdb.table_status.status.ready_for_outdated_reads', 'rethinkdb.table_status.status.ready_for_reads', 'rethinkdb.table_status.status.ready_for_writes', 'rethinkdb.table_status.status.all_replicas_ready', ) TABLE_STATUS_METRICS = (('rethinkdb.table_status.shards', AggregatorStub.GAUGE),) # type: Tuple[Tuple[str, int], ...] TABLE_STATUS_SHARDS_METRICS = ( ('rethinkdb.table_status.shards.replicas', AggregatorStub.GAUGE), ('rethinkdb.table_status.shards.primary_replicas', AggregatorStub.GAUGE), ) # type: Tuple[Tuple[str, int], ...] SERVER_STATUS_METRICS = ( ('rethinkdb.server_status.network.time_connected', AggregatorStub.GAUGE), ('rethinkdb.server_status.network.connected_to', AggregatorStub.GAUGE), ('rethinkdb.server_status.process.time_started', AggregatorStub.GAUGE), ) # type: Tuple[Tuple[str, int], ...] JOBS_METRICS = ( ( 'rethinkdb.system_jobs.jobs', AggregatorStub.GAUGE, 1, ['job_type:query'], ), ) # type: Tuple[Tuple[str, int, int, List[str]], ...] CURRENT_ISSUES_METRICS = ( ('rethinkdb.current_issues.issues', AggregatorStub.GAUGE), ('rethinkdb.current_issues.critical_issues', AggregatorStub.GAUGE), ) # type: Tuple[Tuple[str, int], ...] CURRENT_ISSUE_TYPES_SUBMITTED_IF_DISCONNECTED_SERVERS = ['table_availability'] E2E_METRICS = ( tuple((name, typ) for name, typ, _, _ in CONFIG_METRICS) + CLUSTER_STATISTICS_METRICS + SERVER_STATISTICS_METRICS + TABLE_STATISTICS_METRICS + REPLICA_STATISTICS_METRICS + TABLE_STATUS_METRICS + TABLE_STATUS_SHARDS_METRICS + SERVER_STATUS_METRICS + tuple((name, typ) for name, typ, _, _ in JOBS_METRICS) ) # type: Tuple[Tuple[str, int], ...] # Docker Compose configuration. COMPOSE_FILE = os.path.join(HERE, 'compose', 'docker-compose.yaml') COMPOSE_ENV_VARS = env_vars = { 'RETHINKDB_IMAGE': IMAGE, 'RETHINKDB_PORT_SERVER0': str(SERVER_PORTS['server0']), 'RETHINKDB_PORT_SERVER1': str(SERVER_PORTS['server1']), 'RETHINKDB_PORT_SERVER2': str(SERVER_PORTS['server2']), 'RETHINKDB_PORT_PROXY': str(SERVER_PORTS['proxy']), 'RETHINKDB_TLS_DRIVER_KEY': TLS_DRIVER_KEY, 'RETHINKDB_TLS_DRIVER_CERT': TLS_DRIVER_CERT, } # Pytest common test data. MALFORMED_VERSION_STRING_PARAMS = [ pytest.param('rethinkdb (GCC 4.9.2)', id='no-version'), pytest.param('rethinkdb', id='prefix-only'), pytest.param('abc 2.4.0~0bionic (GCC 4.9.2)', id='wrong-prefix'), ]	0	0	0
2c0645b579d4039d3fb0936a880573ee5a707aa0	396	py	Python	janitor/package/chef/__init__.py	nilesh-naik/lambda-functions	5daa2828914d23851538d5c3cb11f36b0f4bac52	[ "MIT" ]	77	2016-03-15T21:51:11.000Z	2021-09-15T18:40:25.000Z	janitor/package/chef/__init__.py	nilesh-naik/lambda-functions	5daa2828914d23851538d5c3cb11f36b0f4bac52	[ "MIT" ]	20	2016-04-15T18:40:57.000Z	2021-06-01T18:59:56.000Z	lambda/chef/__init__.py	novu/lambda-chef-node-cleanup	6659db950a3ab6b88ff608a6324f36a75fecebf2	[ "Apache-2.0" ]	53	2016-04-07T07:35:04.000Z	2022-01-25T18:48:10.000Z	# Copyright (c) 2010 Noah Kantrowitz <noah@coderanger.net> __version__ = (0, 3, 0) from chef.api import ChefAPI, autoconfigure from chef.client import Client from chef.data_bag import DataBag, DataBagItem from chef.exceptions import ChefError from chef.node import Node from chef.role import Role from chef.environment import Environment from chef.search import Search from chef.acl import Acl	28.285714	58	0.810606	# Copyright (c) 2010 Noah Kantrowitz <noah@coderanger.net> __version__ = (0, 3, 0) from chef.api import ChefAPI, autoconfigure from chef.client import Client from chef.data_bag import DataBag, DataBagItem from chef.exceptions import ChefError from chef.node import Node from chef.role import Role from chef.environment import Environment from chef.search import Search from chef.acl import Acl	0	0	0
ac828b22a576f4b7bb7ccd120bfa1776b6a53295	10,290	py	Python	pyspeckit/spectrum/models/nh2d.py	glangsto/pyspeckit	346b24fb828d1d33c7891cdde7609723e51af34c	[ "MIT" ]	null	null	null	pyspeckit/spectrum/models/nh2d.py	glangsto/pyspeckit	346b24fb828d1d33c7891cdde7609723e51af34c	[ "MIT" ]	1	2021-05-14T19:17:41.000Z	2021-05-14T19:17:41.000Z	pyspeckit/spectrum/models/nh2d.py	glangsto/pyspeckit	346b24fb828d1d33c7891cdde7609723e51af34c	[ "MIT" ]	1	2020-04-23T17:04:09.000Z	2020-04-23T17:04:09.000Z	""" =========== NH2D fitter: ortho- and para- in the same file, but not modeled together =========== Reference for line params: F. Daniel et al. (2016) line frequencies and line strengths. It includes HFS due to D http://adsabs.harvard.edu/abs/2016A%26A...586L...4D """ from . import hyperfine import astropy.units as u freq_dict_cen ={ 'o-1_01-1_11': 85.926263e9, 'p-1_01-1_11': 110.153599e9, 'o-1_01-0_00': 332.82251e9, 'p-1_01-0_00': 332.78189e9, } freq_dict={ ####### ortho-NH2D J=1_01-1_11 'o-1_01-1_11_01': 85.924691e9, 'o-1_01-1_11_02': 85.924749e9, 'o-1_01-1_11_03': 85.924781e9, 'o-1_01-1_11_04': 85.925273e9, 'o-1_01-1_11_05': 85.925370e9, 'o-1_01-1_11_06': 85.925644e9, 'o-1_01-1_11_07': 85.925662e9, 'o-1_01-1_11_08': 85.925688e9, 'o-1_01-1_11_09': 85.925694e9, 'o-1_01-1_11_10': 85.925702e9, 'o-1_01-1_11_11': 85.925734e9, 'o-1_01-1_11_12': 85.926186e9, 'o-1_01-1_11_13': 85.926191e9, 'o-1_01-1_11_14': 85.926212e9, 'o-1_01-1_11_15': 85.926225e9, 'o-1_01-1_11_16': 85.926243e9, 'o-1_01-1_11_17': 85.926244e9, 'o-1_01-1_11_18': 85.926270e9, 'o-1_01-1_11_19': 85.926282e9, 'o-1_01-1_11_20': 85.926284e9, 'o-1_01-1_11_21': 85.926288e9, 'o-1_01-1_11_22': 85.926301e9, 'o-1_01-1_11_23': 85.926314e9, 'o-1_01-1_11_24': 85.926323e9, 'o-1_01-1_11_25': 85.926333e9, 'o-1_01-1_11_26': 85.926806e9, 'o-1_01-1_11_27': 85.926825e9, 'o-1_01-1_11_28': 85.926864e9, 'o-1_01-1_11_29': 85.926877e9, 'o-1_01-1_11_30': 85.926904e9, 'o-1_01-1_11_31': 85.926922e9, 'o-1_01-1_11_32': 85.927104e9, 'o-1_01-1_11_33': 85.927143e9, 'o-1_01-1_11_34': 85.927698e9, 'o-1_01-1_11_35': 85.927724e9, 'o-1_01-1_11_36': 85.927743e9, ####### ortho-NH2D J=1_01-0_00 'o-1_01-0_00_01': 332.780875e9, 'o-1_01-0_00_02': 332.780875e9, 'o-1_01-0_00_03': 332.780875e9, 'o-1_01-0_00_04': 332.781695e9, 'o-1_01-0_00_05': 332.781695e9, 'o-1_01-0_00_06': 332.781695e9, 'o-1_01-0_00_07': 332.781735e9, 'o-1_01-0_00_08': 332.781793e9, 'o-1_01-0_00_09': 332.781793e9, 'o-1_01-0_00_10': 332.782285e9, 'o-1_01-0_00_11': 332.782285e9, 'o-1_01-0_00_12': 332.782285e9, 'o-1_01-0_00_13': 332.782317e9, 'o-1_01-0_00_14': 332.782317e9, 'o-1_01-0_00_15': 332.782375e9, ####### para-NH2D J=1_01-1_11 'p-1_01-1_11_01': 110.151982e9, 'p-1_01-1_11_02': 110.152040e9, 'p-1_01-1_11_03': 110.152072e9, 'p-1_01-1_11_04': 110.152565e9, 'p-1_01-1_11_05': 110.152662e9, 'p-1_01-1_11_06': 110.152935e9, 'p-1_01-1_11_07': 110.152954e9, 'p-1_01-1_11_08': 110.152980e9, 'p-1_01-1_11_09': 110.152986e9, 'p-1_01-1_11_10': 110.152993e9, 'p-1_01-1_11_11': 110.153025e9, 'p-1_01-1_11_12': 110.153478e9, 'p-1_01-1_11_13': 110.153484e9, 'p-1_01-1_11_14': 110.153504e9, 'p-1_01-1_11_15': 110.153517e9, 'p-1_01-1_11_16': 110.153534e9, 'p-1_01-1_11_17': 110.153536e9, 'p-1_01-1_11_18': 110.153562e9, 'p-1_01-1_11_19': 110.153574e9, 'p-1_01-1_11_20': 110.153576e9, 'p-1_01-1_11_21': 110.153580e9, 'p-1_01-1_11_22': 110.153592e9, 'p-1_01-1_11_23': 110.153606e9, 'p-1_01-1_11_24': 110.153615e9, 'p-1_01-1_11_25': 110.153625e9, 'p-1_01-1_11_26': 110.154098e9, 'p-1_01-1_11_27': 110.154117e9, 'p-1_01-1_11_28': 110.154156e9, 'p-1_01-1_11_29': 110.154170e9, 'p-1_01-1_11_30': 110.154196e9, 'p-1_01-1_11_31': 110.154215e9, 'p-1_01-1_11_32': 110.154397e9, 'p-1_01-1_11_33': 110.154437e9, 'p-1_01-1_11_34': 110.154991e9, 'p-1_01-1_11_35': 110.155017e9, 'p-1_01-1_11_36': 110.155036e9, ####### para-NH2D J=1_01-0_00 'p-1_01-0_00_01': 332.821618e9, 'p-1_01-0_00_02': 332.821618e9, 'p-1_01-0_00_03': 332.821618e9, 'p-1_01-0_00_04': 332.822439e9, 'p-1_01-0_00_05': 332.822439e9, 'p-1_01-0_00_06': 332.822439e9, 'p-1_01-0_00_07': 332.822479e9, 'p-1_01-0_00_08': 332.822537e9, 'p-1_01-0_00_09': 332.822537e9, 'p-1_01-0_00_10': 332.823029e9, 'p-1_01-0_00_11': 332.823029e9, 'p-1_01-0_00_12': 332.823029e9, 'p-1_01-0_00_13': 332.823062e9, 'p-1_01-0_00_14': 332.823062e9, 'p-1_01-0_00_15': 332.823120e9 } line_strength_dict = { ####### ortho-NH2D J=1_01-1_11 'o-1_01-1_11_01': 0.01310, 'o-1_01-1_11_02': 0.06187, 'o-1_01-1_11_03': 0.03562, 'o-1_01-1_11_04': 0.00016, 'o-1_01-1_11_05': 0.00035, 'o-1_01-1_11_06': 0.01595, 'o-1_01-1_11_07': 0.01758, 'o-1_01-1_11_08': 0.05965, 'o-1_01-1_11_09': 0.04054, 'o-1_01-1_11_10': 0.00064, 'o-1_01-1_11_11': 0.00556, 'o-1_01-1_11_12': 0.09296, 'o-1_01-1_11_13': 0.00000, 'o-1_01-1_11_14': 0.02677, 'o-1_01-1_11_15': 0.02341, 'o-1_01-1_11_16': 0.00798, 'o-1_01-1_11_17': 0.01984, 'o-1_01-1_11_18': 0.17288, 'o-1_01-1_11_19': 0.03609, 'o-1_01-1_11_20': 0.01423, 'o-1_01-1_11_21': 0.01265, 'o-1_01-1_11_22': 0.00934, 'o-1_01-1_11_23': 0.01131, 'o-1_01-1_11_24': 0.06547, 'o-1_01-1_11_25': 0.00541, 'o-1_01-1_11_26': 0.00769, 'o-1_01-1_11_27': 0.03419, 'o-1_01-1_11_28': 0.06657, 'o-1_01-1_11_29': 0.01395, 'o-1_01-1_11_30': 0.00325, 'o-1_01-1_11_31': 0.01385, 'o-1_01-1_11_32': 0.00002, 'o-1_01-1_11_33': 0.00006, 'o-1_01-1_11_34': 0.01043, 'o-1_01-1_11_35': 0.06026, 'o-1_01-1_11_36': 0.04034, ####### ortho-NH2D J=1_01-0_00 'o-1_01-0_00_01': 0.06298, 'o-1_01-0_00_02': 0.03129, 'o-1_01-0_00_03': 0.01683, 'o-1_01-0_00_04': 0.00007, 'o-1_01-0_00_05': 0.04185, 'o-1_01-0_00_06': 0.06918, 'o-1_01-0_00_07': 0.25920, 'o-1_01-0_00_08': 0.05735, 'o-1_01-0_00_09': 0.12788, 'o-1_01-0_00_10': 0.03796, 'o-1_01-0_00_11': 0.04805, 'o-1_01-0_00_12': 0.02509, 'o-1_01-0_00_13': 0.05735, 'o-1_01-0_00_14': 0.12788, 'o-1_01-0_00_15': 0.03703, ####### para-NH2D J=1_01-1_11 'p-1_01-1_11_01': 0.01310, 'p-1_01-1_11_02': 0.06188, 'p-1_01-1_11_03': 0.03562, 'p-1_01-1_11_04': 0.00016, 'p-1_01-1_11_05': 0.00035, 'p-1_01-1_11_06': 0.01595, 'p-1_01-1_11_07': 0.01758, 'p-1_01-1_11_08': 0.05965, 'p-1_01-1_11_09': 0.04054, 'p-1_01-1_11_10': 0.00064, 'p-1_01-1_11_11': 0.00556, 'p-1_01-1_11_12': 0.09296, 'p-1_01-1_11_13': 0.00000, 'p-1_01-1_11_14': 0.02675, 'p-1_01-1_11_15': 0.02341, 'p-1_01-1_11_16': 0.00798, 'p-1_01-1_11_17': 0.01984, 'p-1_01-1_11_18': 0.17288, 'p-1_01-1_11_19': 0.03609, 'p-1_01-1_11_20': 0.01424, 'p-1_01-1_11_21': 0.01266, 'p-1_01-1_11_22': 0.00934, 'p-1_01-1_11_23': 0.01131, 'p-1_01-1_11_24': 0.06546, 'p-1_01-1_11_25': 0.00541, 'p-1_01-1_11_26': 0.00769, 'p-1_01-1_11_27': 0.03419, 'p-1_01-1_11_28': 0.06658, 'p-1_01-1_11_29': 0.01395, 'p-1_01-1_11_30': 0.00325, 'p-1_01-1_11_31': 0.01385, 'p-1_01-1_11_32': 0.00002, 'p-1_01-1_11_33': 0.00006, 'p-1_01-1_11_34': 0.01043, 'p-1_01-1_11_35': 0.06026, 'p-1_01-1_11_36': 0.04034, ####### para-NH2D J=1_01-0_00 'p-1_01-0_00_01': 0.06298, 'p-1_01-0_00_02': 0.03130, 'p-1_01-0_00_03': 0.01683, 'p-1_01-0_00_04': 0.00007, 'p-1_01-0_00_05': 0.04185, 'p-1_01-0_00_06': 0.06918, 'p-1_01-0_00_07': 0.25920, 'p-1_01-0_00_08': 0.05734, 'p-1_01-0_00_09': 0.12788, 'p-1_01-0_00_10': 0.03795, 'p-1_01-0_00_11': 0.04805, 'p-1_01-0_00_12': 0.02510, 'p-1_01-0_00_13': 0.05734, 'p-1_01-0_00_14': 0.12788, 'p-1_01-0_00_15': 0.03703, } # Get offset velocity dictionary in km/s based on the lines frequencies and rest frequency conv_o1_1=u.doppler_radio(freq_dict_cen['o-1_01-1_11']u.Hz) conv_p1_1=u.doppler_radio(freq_dict_cen['p-1_01-1_11']u.Hz) conv_o1_0=u.doppler_radio(freq_dict_cen['o-1_01-0_00']u.Hz) conv_p1_0=u.doppler_radio(freq_dict_cen['p-1_01-0_00']u.Hz) voff_lines_dict = { name: ((freq_dict[name]u.Hz).to(u.km/u.s, equivalencies=conv_o1_1).value) for name in freq_dict.keys() if "o-1_01-1_11" in name } voff_lines_dict.update({ name: ((freq_dict[name]u.Hz).to(u.km/u.s, equivalencies=conv_p1_1).value) for name in freq_dict.keys() if "p-1_01-1_11" in name }) voff_lines_dict.update({ name: ((freq_dict[name]u.Hz).to(u.km/u.s, equivalencies=conv_o1_0).value) for name in freq_dict.keys() if "o-1_01-0_00" in name }) voff_lines_dict.update({ name: ((freq_dict[name]u.Hz).to(u.km/u.s, equivalencies=conv_p1_0).value) for name in freq_dict.keys() if "p-1_01-0_00" in name }) # I don't know yet how to use this parameter... in CLASS it does not exist # Note to Jaime: this is the sum of the degeneracy values for all hyperfines # for a given line; it gives the relative weights between the J=2-1 and J=3-2 # lines, for example (the hyperfine weights are treated as normalized within # one rotational transition) wo1_1 = sum(val for name,val in line_strength_dict.items() if 'o-1_01-1_11' in name) wp1_1 = sum(val for name,val in line_strength_dict.items() if 'p-1_01-1_11' in name) wo1_0 = sum(val for name,val in line_strength_dict.items() if 'o-1_01-0_00' in name) wp1_0 = sum(val for name,val in line_strength_dict.items() if 'p-1_01-0_00' in name) relative_strength_total_degeneracy = { name : wo1_1 for name in line_strength_dict.keys() if "o-1_01-1_11" in name } relative_strength_total_degeneracy.update({ name : wp1_1 for name in line_strength_dict.keys() if "p-1_01-1_11" in name }) relative_strength_total_degeneracy.update({ name : wo1_0 for name in line_strength_dict.keys() if "o-1_01-0_00" in name }) relative_strength_total_degeneracy.update({ name : wp1_0 for name in line_strength_dict.keys() if "p-1_01-0_00" in name }) # Get the list of line names from the previous lists line_names = [name for name in voff_lines_dict.keys()] nh2d_vtau = hyperfine.hyperfinemodel(line_names, voff_lines_dict, freq_dict, line_strength_dict, relative_strength_total_degeneracy) nh2d_vtau_fitter = nh2d_vtau.fitter nh2d_vtau_vheight_fitter = nh2d_vtau.vheight_fitter nh2d_vtau_tbg_fitter = nh2d_vtau.background_fitter	35.482759	132	0.636929	""" =========== NH2D fitter: ortho- and para- in the same file, but not modeled together =========== Reference for line params: F. Daniel et al. (2016) line frequencies and line strengths. It includes HFS due to D http://adsabs.harvard.edu/abs/2016A%26A...586L...4D """ from . import hyperfine import astropy.units as u freq_dict_cen ={ 'o-1_01-1_11': 85.926263e9, 'p-1_01-1_11': 110.153599e9, 'o-1_01-0_00': 332.82251e9, 'p-1_01-0_00': 332.78189e9, } freq_dict={ ####### ortho-NH2D J=1_01-1_11 'o-1_01-1_11_01': 85.924691e9, 'o-1_01-1_11_02': 85.924749e9, 'o-1_01-1_11_03': 85.924781e9, 'o-1_01-1_11_04': 85.925273e9, 'o-1_01-1_11_05': 85.925370e9, 'o-1_01-1_11_06': 85.925644e9, 'o-1_01-1_11_07': 85.925662e9, 'o-1_01-1_11_08': 85.925688e9, 'o-1_01-1_11_09': 85.925694e9, 'o-1_01-1_11_10': 85.925702e9, 'o-1_01-1_11_11': 85.925734e9, 'o-1_01-1_11_12': 85.926186e9, 'o-1_01-1_11_13': 85.926191e9, 'o-1_01-1_11_14': 85.926212e9, 'o-1_01-1_11_15': 85.926225e9, 'o-1_01-1_11_16': 85.926243e9, 'o-1_01-1_11_17': 85.926244e9, 'o-1_01-1_11_18': 85.926270e9, 'o-1_01-1_11_19': 85.926282e9, 'o-1_01-1_11_20': 85.926284e9, 'o-1_01-1_11_21': 85.926288e9, 'o-1_01-1_11_22': 85.926301e9, 'o-1_01-1_11_23': 85.926314e9, 'o-1_01-1_11_24': 85.926323e9, 'o-1_01-1_11_25': 85.926333e9, 'o-1_01-1_11_26': 85.926806e9, 'o-1_01-1_11_27': 85.926825e9, 'o-1_01-1_11_28': 85.926864e9, 'o-1_01-1_11_29': 85.926877e9, 'o-1_01-1_11_30': 85.926904e9, 'o-1_01-1_11_31': 85.926922e9, 'o-1_01-1_11_32': 85.927104e9, 'o-1_01-1_11_33': 85.927143e9, 'o-1_01-1_11_34': 85.927698e9, 'o-1_01-1_11_35': 85.927724e9, 'o-1_01-1_11_36': 85.927743e9, ####### ortho-NH2D J=1_01-0_00 'o-1_01-0_00_01': 332.780875e9, 'o-1_01-0_00_02': 332.780875e9, 'o-1_01-0_00_03': 332.780875e9, 'o-1_01-0_00_04': 332.781695e9, 'o-1_01-0_00_05': 332.781695e9, 'o-1_01-0_00_06': 332.781695e9, 'o-1_01-0_00_07': 332.781735e9, 'o-1_01-0_00_08': 332.781793e9, 'o-1_01-0_00_09': 332.781793e9, 'o-1_01-0_00_10': 332.782285e9, 'o-1_01-0_00_11': 332.782285e9, 'o-1_01-0_00_12': 332.782285e9, 'o-1_01-0_00_13': 332.782317e9, 'o-1_01-0_00_14': 332.782317e9, 'o-1_01-0_00_15': 332.782375e9, ####### para-NH2D J=1_01-1_11 'p-1_01-1_11_01': 110.151982e9, 'p-1_01-1_11_02': 110.152040e9, 'p-1_01-1_11_03': 110.152072e9, 'p-1_01-1_11_04': 110.152565e9, 'p-1_01-1_11_05': 110.152662e9, 'p-1_01-1_11_06': 110.152935e9, 'p-1_01-1_11_07': 110.152954e9, 'p-1_01-1_11_08': 110.152980e9, 'p-1_01-1_11_09': 110.152986e9, 'p-1_01-1_11_10': 110.152993e9, 'p-1_01-1_11_11': 110.153025e9, 'p-1_01-1_11_12': 110.153478e9, 'p-1_01-1_11_13': 110.153484e9, 'p-1_01-1_11_14': 110.153504e9, 'p-1_01-1_11_15': 110.153517e9, 'p-1_01-1_11_16': 110.153534e9, 'p-1_01-1_11_17': 110.153536e9, 'p-1_01-1_11_18': 110.153562e9, 'p-1_01-1_11_19': 110.153574e9, 'p-1_01-1_11_20': 110.153576e9, 'p-1_01-1_11_21': 110.153580e9, 'p-1_01-1_11_22': 110.153592e9, 'p-1_01-1_11_23': 110.153606e9, 'p-1_01-1_11_24': 110.153615e9, 'p-1_01-1_11_25': 110.153625e9, 'p-1_01-1_11_26': 110.154098e9, 'p-1_01-1_11_27': 110.154117e9, 'p-1_01-1_11_28': 110.154156e9, 'p-1_01-1_11_29': 110.154170e9, 'p-1_01-1_11_30': 110.154196e9, 'p-1_01-1_11_31': 110.154215e9, 'p-1_01-1_11_32': 110.154397e9, 'p-1_01-1_11_33': 110.154437e9, 'p-1_01-1_11_34': 110.154991e9, 'p-1_01-1_11_35': 110.155017e9, 'p-1_01-1_11_36': 110.155036e9, ####### para-NH2D J=1_01-0_00 'p-1_01-0_00_01': 332.821618e9, 'p-1_01-0_00_02': 332.821618e9, 'p-1_01-0_00_03': 332.821618e9, 'p-1_01-0_00_04': 332.822439e9, 'p-1_01-0_00_05': 332.822439e9, 'p-1_01-0_00_06': 332.822439e9, 'p-1_01-0_00_07': 332.822479e9, 'p-1_01-0_00_08': 332.822537e9, 'p-1_01-0_00_09': 332.822537e9, 'p-1_01-0_00_10': 332.823029e9, 'p-1_01-0_00_11': 332.823029e9, 'p-1_01-0_00_12': 332.823029e9, 'p-1_01-0_00_13': 332.823062e9, 'p-1_01-0_00_14': 332.823062e9, 'p-1_01-0_00_15': 332.823120e9 } line_strength_dict = { ####### ortho-NH2D J=1_01-1_11 'o-1_01-1_11_01': 0.01310, 'o-1_01-1_11_02': 0.06187, 'o-1_01-1_11_03': 0.03562, 'o-1_01-1_11_04': 0.00016, 'o-1_01-1_11_05': 0.00035, 'o-1_01-1_11_06': 0.01595, 'o-1_01-1_11_07': 0.01758, 'o-1_01-1_11_08': 0.05965, 'o-1_01-1_11_09': 0.04054, 'o-1_01-1_11_10': 0.00064, 'o-1_01-1_11_11': 0.00556, 'o-1_01-1_11_12': 0.09296, 'o-1_01-1_11_13': 0.00000, 'o-1_01-1_11_14': 0.02677, 'o-1_01-1_11_15': 0.02341, 'o-1_01-1_11_16': 0.00798, 'o-1_01-1_11_17': 0.01984, 'o-1_01-1_11_18': 0.17288, 'o-1_01-1_11_19': 0.03609, 'o-1_01-1_11_20': 0.01423, 'o-1_01-1_11_21': 0.01265, 'o-1_01-1_11_22': 0.00934, 'o-1_01-1_11_23': 0.01131, 'o-1_01-1_11_24': 0.06547, 'o-1_01-1_11_25': 0.00541, 'o-1_01-1_11_26': 0.00769, 'o-1_01-1_11_27': 0.03419, 'o-1_01-1_11_28': 0.06657, 'o-1_01-1_11_29': 0.01395, 'o-1_01-1_11_30': 0.00325, 'o-1_01-1_11_31': 0.01385, 'o-1_01-1_11_32': 0.00002, 'o-1_01-1_11_33': 0.00006, 'o-1_01-1_11_34': 0.01043, 'o-1_01-1_11_35': 0.06026, 'o-1_01-1_11_36': 0.04034, ####### ortho-NH2D J=1_01-0_00 'o-1_01-0_00_01': 0.06298, 'o-1_01-0_00_02': 0.03129, 'o-1_01-0_00_03': 0.01683, 'o-1_01-0_00_04': 0.00007, 'o-1_01-0_00_05': 0.04185, 'o-1_01-0_00_06': 0.06918, 'o-1_01-0_00_07': 0.25920, 'o-1_01-0_00_08': 0.05735, 'o-1_01-0_00_09': 0.12788, 'o-1_01-0_00_10': 0.03796, 'o-1_01-0_00_11': 0.04805, 'o-1_01-0_00_12': 0.02509, 'o-1_01-0_00_13': 0.05735, 'o-1_01-0_00_14': 0.12788, 'o-1_01-0_00_15': 0.03703, ####### para-NH2D J=1_01-1_11 'p-1_01-1_11_01': 0.01310, 'p-1_01-1_11_02': 0.06188, 'p-1_01-1_11_03': 0.03562, 'p-1_01-1_11_04': 0.00016, 'p-1_01-1_11_05': 0.00035, 'p-1_01-1_11_06': 0.01595, 'p-1_01-1_11_07': 0.01758, 'p-1_01-1_11_08': 0.05965, 'p-1_01-1_11_09': 0.04054, 'p-1_01-1_11_10': 0.00064, 'p-1_01-1_11_11': 0.00556, 'p-1_01-1_11_12': 0.09296, 'p-1_01-1_11_13': 0.00000, 'p-1_01-1_11_14': 0.02675, 'p-1_01-1_11_15': 0.02341, 'p-1_01-1_11_16': 0.00798, 'p-1_01-1_11_17': 0.01984, 'p-1_01-1_11_18': 0.17288, 'p-1_01-1_11_19': 0.03609, 'p-1_01-1_11_20': 0.01424, 'p-1_01-1_11_21': 0.01266, 'p-1_01-1_11_22': 0.00934, 'p-1_01-1_11_23': 0.01131, 'p-1_01-1_11_24': 0.06546, 'p-1_01-1_11_25': 0.00541, 'p-1_01-1_11_26': 0.00769, 'p-1_01-1_11_27': 0.03419, 'p-1_01-1_11_28': 0.06658, 'p-1_01-1_11_29': 0.01395, 'p-1_01-1_11_30': 0.00325, 'p-1_01-1_11_31': 0.01385, 'p-1_01-1_11_32': 0.00002, 'p-1_01-1_11_33': 0.00006, 'p-1_01-1_11_34': 0.01043, 'p-1_01-1_11_35': 0.06026, 'p-1_01-1_11_36': 0.04034, ####### para-NH2D J=1_01-0_00 'p-1_01-0_00_01': 0.06298, 'p-1_01-0_00_02': 0.03130, 'p-1_01-0_00_03': 0.01683, 'p-1_01-0_00_04': 0.00007, 'p-1_01-0_00_05': 0.04185, 'p-1_01-0_00_06': 0.06918, 'p-1_01-0_00_07': 0.25920, 'p-1_01-0_00_08': 0.05734, 'p-1_01-0_00_09': 0.12788, 'p-1_01-0_00_10': 0.03795, 'p-1_01-0_00_11': 0.04805, 'p-1_01-0_00_12': 0.02510, 'p-1_01-0_00_13': 0.05734, 'p-1_01-0_00_14': 0.12788, 'p-1_01-0_00_15': 0.03703, } # Get offset velocity dictionary in km/s based on the lines frequencies and rest frequency conv_o1_1=u.doppler_radio(freq_dict_cen['o-1_01-1_11']u.Hz) conv_p1_1=u.doppler_radio(freq_dict_cen['p-1_01-1_11']u.Hz) conv_o1_0=u.doppler_radio(freq_dict_cen['o-1_01-0_00']u.Hz) conv_p1_0=u.doppler_radio(freq_dict_cen['p-1_01-0_00']u.Hz) voff_lines_dict = { name: ((freq_dict[name]u.Hz).to(u.km/u.s, equivalencies=conv_o1_1).value) for name in freq_dict.keys() if "o-1_01-1_11" in name } voff_lines_dict.update({ name: ((freq_dict[name]u.Hz).to(u.km/u.s, equivalencies=conv_p1_1).value) for name in freq_dict.keys() if "p-1_01-1_11" in name }) voff_lines_dict.update({ name: ((freq_dict[name]u.Hz).to(u.km/u.s, equivalencies=conv_o1_0).value) for name in freq_dict.keys() if "o-1_01-0_00" in name }) voff_lines_dict.update({ name: ((freq_dict[name]u.Hz).to(u.km/u.s, equivalencies=conv_p1_0).value) for name in freq_dict.keys() if "p-1_01-0_00" in name }) # I don't know yet how to use this parameter... in CLASS it does not exist # Note to Jaime: this is the sum of the degeneracy values for all hyperfines # for a given line; it gives the relative weights between the J=2-1 and J=3-2 # lines, for example (the hyperfine weights are treated as normalized within # one rotational transition) wo1_1 = sum(val for name,val in line_strength_dict.items() if 'o-1_01-1_11' in name) wp1_1 = sum(val for name,val in line_strength_dict.items() if 'p-1_01-1_11' in name) wo1_0 = sum(val for name,val in line_strength_dict.items() if 'o-1_01-0_00' in name) wp1_0 = sum(val for name,val in line_strength_dict.items() if 'p-1_01-0_00' in name) relative_strength_total_degeneracy = { name : wo1_1 for name in line_strength_dict.keys() if "o-1_01-1_11" in name } relative_strength_total_degeneracy.update({ name : wp1_1 for name in line_strength_dict.keys() if "p-1_01-1_11" in name }) relative_strength_total_degeneracy.update({ name : wo1_0 for name in line_strength_dict.keys() if "o-1_01-0_00" in name }) relative_strength_total_degeneracy.update({ name : wp1_0 for name in line_strength_dict.keys() if "p-1_01-0_00" in name }) # Get the list of line names from the previous lists line_names = [name for name in voff_lines_dict.keys()] nh2d_vtau = hyperfine.hyperfinemodel(line_names, voff_lines_dict, freq_dict, line_strength_dict, relative_strength_total_degeneracy) nh2d_vtau_fitter = nh2d_vtau.fitter nh2d_vtau_vheight_fitter = nh2d_vtau.vheight_fitter nh2d_vtau_tbg_fitter = nh2d_vtau.background_fitter	0	0	0
5f8095707304f334fc478e2b1d6cdfd9581bb80b	44	py	Python	parameters_443.py	amonmoce/ElectionsStats	647fbd5ebc0aa25a027355e0cc851220328fec06	[ "BSD-3-Clause" ]	null	null	null	parameters_443.py	amonmoce/ElectionsStats	647fbd5ebc0aa25a027355e0cc851220328fec06	[ "BSD-3-Clause" ]	null	null	null	parameters_443.py	amonmoce/ElectionsStats	647fbd5ebc0aa25a027355e0cc851220328fec06	[ "BSD-3-Clause" ]	null	null	null	password="4bd9270216a6d2e7bc330cf396f7c8f2"	22	43	0.909091	password="4bd9270216a6d2e7bc330cf396f7c8f2"	0	0	0
5885938e77707f880d8da482e0285130b6697045	593	py	Python	src/utils/train/training_utils.py	chris4540/StudyMaskedLMForQG	2bf477b7b8cfb5d195c028db6d63aadf06af8fc5	[ "MIT" ]	6	2020-12-09T11:30:37.000Z	2022-03-03T12:06:44.000Z	src/utils/train/training_utils.py	chris4540/StudyMaskedLMForQG	2bf477b7b8cfb5d195c028db6d63aadf06af8fc5	[ "MIT" ]	null	null	null	src/utils/train/training_utils.py	chris4540/StudyMaskedLMForQG	2bf477b7b8cfb5d195c028db6d63aadf06af8fc5	[ "MIT" ]	3	2021-03-23T04:56:48.000Z	2022-02-02T19:31:46.000Z	from typing import List from typing import Dict from typing import NamedTuple # from typing import Optional	25.782609	66	0.627319	from typing import List from typing import Dict from typing import NamedTuple # from typing import Optional def build_generated_text(refs: List[str], hyps: List[str]) -> str: ret = "" linesep = " \n" # Tensorboard text uses format of markdown for i, (ref, hyp) in enumerate(zip(refs, hyps)): ret += f"{i}" + linesep ret += f"ref: {ref}" + linesep ret += f"hyp: {hyp}" + linesep ret += "-" * 100 + linesep return ret class TextGenerationOutput(NamedTuple): references: List[str] hypotheses: List[str] metrics: Dict[str, float]	337	100	46
6fb14605bf869967b78c62d65e4c34bd50dca9b2	884	py	Python	online/client/char-client.py	jas-dzied/quiz	39d19c952af8b71c8e407f7a650361ab49653bf3	[ "MIT" ]	null	null	null	online/client/char-client.py	jas-dzied/quiz	39d19c952af8b71c8e407f7a650361ab49653bf3	[ "MIT" ]	null	null	null	online/client/char-client.py	jas-dzied/quiz	39d19c952af8b71c8e407f7a650361ab49653bf3	[ "MIT" ]	null	null	null	#!/usr/bin/env python3 import asyncio import websockets import threading import queue import secrets asyncio.run(main())	24.555556	75	0.700226	#!/usr/bin/env python3 import asyncio import websockets import threading import queue import secrets async def worker(uid, q): async with websockets.connect("ws://localhost:8003") as websocket: await websocket.send(f'0:{uid}') async def receiver(uid, q): async with websockets.connect("ws://localhost:8003") as websocket: await websocket.send(f'1:{uid}') def watcher_starter(args): asyncio.run(worker(args)) def sender_starter(args): asyncio.run(receiver(args)) async def main(): uid = secrets.token_urlsafe(16) print(f'My uid: {uid}') q = queue.Queue() watcher_thread = threading.Thread(target=watcher_starter, args=(uid,q)) sender_thread = threading.Thread(target=sender_starter, args=(uid,q)) watcher_thread.start() sender_thread.start() watcher_thread.join() sender_thread.join() asyncio.run(main())	647	0	114
30261c9941c84f4da118943a0ab2701b46dde7d5	663	py	Python	ns/demux/flow_demux.py	lunarss/ns.py	9298c850290fb2ee98b047dfc757f4687763c2f8	[ "Apache-2.0" ]	null	null	null	ns/demux/flow_demux.py	lunarss/ns.py	9298c850290fb2ee98b047dfc757f4687763c2f8	[ "Apache-2.0" ]	1	2021-07-20T02:48:41.000Z	2021-07-20T02:48:41.000Z	ns/demux/flow_demux.py	JinJinGuang/ns.py	90415c4c83dd775cc50976c609ecbf551191cdf0	[ "Apache-2.0" ]	null	null	null	""" A demultiplexing element that splits packet streams by flow_id. """ class FlowDemux: """ The constructor takes a list of downstream elements for the corresponding output ports as its input. """ def put(self, packet): """ Sends a packet to this element. """ self.packets_received += 1 flow_id = packet.flow_id if flow_id < len(self.outs): self.outs[flow_id].put(packet) else: if self.default: self.default.put(packet)	26.52	63	0.603318	""" A demultiplexing element that splits packet streams by flow_id. """ class FlowDemux: """ The constructor takes a list of downstream elements for the corresponding output ports as its input. """ def __init__(self, outs=None, default=None): self.outs = outs self.default = default self.packets_received = 0 def put(self, packet): """ Sends a packet to this element. """ self.packets_received += 1 flow_id = packet.flow_id if flow_id < len(self.outs): self.outs[flow_id].put(packet) else: if self.default: self.default.put(packet)	113	0	26
fcbf29f197cc47590cb289066bc6f4f0276442d6	4,621	py	Python	python-advanced/chapter1.py	Rokon-Uz-Zaman/thinkdiff_python_django	5010c5f1dd8a028fb9e5235319bb6bb434831e6c	[ "MIT" ]	92	2018-04-03T20:53:07.000Z	2022-03-04T05:53:10.000Z	python-language/python-advanced/chapter1.py	mostafijur-rahman299/thinkdiff	b0e0c01fe38c406f4dfa8cc80b2f0c5654017079	[ "MIT" ]	11	2018-10-01T15:35:33.000Z	2021-09-01T04:59:56.000Z	python-language/python-advanced/chapter1.py	mostafijur-rahman299/thinkdiff	b0e0c01fe38c406f4dfa8cc80b2f0c5654017079	[ "MIT" ]	98	2018-03-13T08:03:54.000Z	2022-03-22T08:11:44.000Z	# author: Mahmud Ahsan # code: https://github.com/mahmudahsan/thinkdiff # blog: http://thinkdiff.net # http://pythonbangla.com # MIT License # -------------------------- # Files # -------------------------- ## Reading full contents of a text file ''' Encouraged way with keyword close the file automatically ''' try: with open('data/article.txt') as fobj: contents = fobj.read() print (contents) except Exception as e: print ("File Error: " , e) print() ### Another way ''' In this way, file need to close manually ''' try: fobj = open('data/article.txt') except Exception as e: print ("File Error: " , e) else: contents = fobj.read() print (contents) finally: fobj.close() print() ''' MacOS and Linux Relative path: data/article.txt Absolute path: /user/mahmud/python/data/article.txt ''' # Windows: # data\article.txt # C:\Users\mahmud\python\data\article.txt ### Reading line by line and make uppercase with open("data/article.txt") as fobj: for num, line in enumerate(fobj): print ( num+1, line.upper() ) print() ### Reading list of lines with open("data/names.txt") as fobj: lines = fobj.readlines() print (lines) ## Write text in a file ''' w = write # erase existing content if any a = append r = read # default OR wt = write at = append rt = read t is for text mode which is set by default ''' with open ('data/number.txt', 'w') as fobj: fobj.write('1') fobj.write('\n') fobj.write('28484') ## Append text in an existing file ''' # uncomment to run this program with open ('data/message.txt', 'a') as fobj: fobj.write("life is good \n") ''' ## Encoding during writing file # latin-1 other encoding with open ('data/bangla.txt', 'w', encoding='UTF-8') as fobj: fobj.write('আমার দেশ বাংলাদেশ') fobj.write('\n') fobj.write('আমি আমার দেশকে ভালবাসি') ## Redirect print output to file with open ('data/print.txt', 'w') as fobj: print ("Nothing goes unpaid", file=fobj) ## Write a binary data to a file with open ('data/binary', 'wb') as fobj: fobj.write(b'Life is good') ## Read a binary data file with open ('data/binary', 'rb') as fobj: binary_data = fobj.read() decoded_data = binary_data.decode('utf-8') print ( decoded_data ) ## File existence checking import os if os.path.exists('data/article.txt'): print ("Yes, file exist") ## Temporary file ''' w+ = reading and writing same time With auto destroyed when file closed ''' from tempfile import TemporaryFile with TemporaryFile('w+') as fobj: fobj.write("Life is cool.\n") fobj.seek(0) # seek to the beginning data = fobj.read() print (data) ## pyserial serial port access library ''' Controlling hardware device like robot, sensor by using serial port https://github.com/pyserial/pyserial ''' ## Serialize python object to a byte stream import pickle dict_data = {'name':'Ahsan', 'country':'Bangladesh'} # serialize_data = pickle.dumps(dict_data) with open ('data/serialize', 'wb') as fobj: pickle.dump(dict_data, fobj) with open ('data/serialize', 'rb') as fobj: dict_data = pickle.load(fobj) print ( dict_data ) print() ## CSV file read import csv with open('data/expense.csv', 'r') as fobj: fcsv = csv.reader(fobj) sum = 0 for i, row in enumerate(fcsv): print (i, row[0], row[1]) sum += int(row[1]) if i > 0 else 0 print ("Total Cost: ", sum) ''' https://docs.python.org/3/library/csv.html http://pandas.pydata.org Pandas has pandas.read_csv() function to load CSV data to a DataFrame object. ''' ## CSV file write list_items = [["name", 'age', 'country'], ['Bill Gates', 55, 'US'], ['Mark Zuckerberg', 34, 'US'], ['Swift', 35, 'Canada'] ] import csv with open('data/people.csv', 'w') as fobj: fcsv = csv.writer(fobj) fcsv.writerows(list_items) print() ## JSON Data Encode and Decode ''' JSON (JavaScript Object Notation) is a common standard to exchange data between server and client in web application. ''' import json data = { 'name' : 'Bill Gates', 'age' : 55, 'country' : 'US', 'is_retired': True } json_encoded_str = json.dumps(data) print(json_encoded_str) json_decode = json.loads(json_encoded_str) print(json_decode) ### Dumping data in file and load from file with open('data/json_data.json', 'w') as fobj: json.dump(data, fobj) with open('data/json_data.json', 'r') as fobj: json_data = json.load(fobj) print (json_data)	21.79717	118	0.628003	# author: Mahmud Ahsan # code: https://github.com/mahmudahsan/thinkdiff # blog: http://thinkdiff.net # http://pythonbangla.com # MIT License # -------------------------- # Files # -------------------------- ## Reading full contents of a text file ''' Encouraged way with keyword close the file automatically ''' try: with open('data/article.txt') as fobj: contents = fobj.read() print (contents) except Exception as e: print ("File Error: " , e) print() ### Another way ''' In this way, file need to close manually ''' try: fobj = open('data/article.txt') except Exception as e: print ("File Error: " , e) else: contents = fobj.read() print (contents) finally: fobj.close() print() ''' MacOS and Linux Relative path: data/article.txt Absolute path: /user/mahmud/python/data/article.txt ''' # Windows: # data\article.txt # C:\Users\mahmud\python\data\article.txt ### Reading line by line and make uppercase with open("data/article.txt") as fobj: for num, line in enumerate(fobj): print ( num+1, line.upper() ) print() ### Reading list of lines with open("data/names.txt") as fobj: lines = fobj.readlines() print (lines) ## Write text in a file ''' w = write # erase existing content if any a = append r = read # default OR wt = write at = append rt = read t is for text mode which is set by default ''' with open ('data/number.txt', 'w') as fobj: fobj.write('1') fobj.write('\n') fobj.write('28484') ## Append text in an existing file ''' # uncomment to run this program with open ('data/message.txt', 'a') as fobj: fobj.write("life is good \n") ''' ## Encoding during writing file # latin-1 other encoding with open ('data/bangla.txt', 'w', encoding='UTF-8') as fobj: fobj.write('আমার দেশ বাংলাদেশ') fobj.write('\n') fobj.write('আমি আমার দেশকে ভালবাসি') ## Redirect print output to file with open ('data/print.txt', 'w') as fobj: print ("Nothing goes unpaid", file=fobj) ## Write a binary data to a file with open ('data/binary', 'wb') as fobj: fobj.write(b'Life is good') ## Read a binary data file with open ('data/binary', 'rb') as fobj: binary_data = fobj.read() decoded_data = binary_data.decode('utf-8') print ( decoded_data ) ## File existence checking import os if os.path.exists('data/article.txt'): print ("Yes, file exist") ## Temporary file ''' w+ = reading and writing same time With auto destroyed when file closed ''' from tempfile import TemporaryFile with TemporaryFile('w+') as fobj: fobj.write("Life is cool.\n") fobj.seek(0) # seek to the beginning data = fobj.read() print (data) ## pyserial serial port access library ''' Controlling hardware device like robot, sensor by using serial port https://github.com/pyserial/pyserial ''' ## Serialize python object to a byte stream import pickle dict_data = {'name':'Ahsan', 'country':'Bangladesh'} # serialize_data = pickle.dumps(dict_data) with open ('data/serialize', 'wb') as fobj: pickle.dump(dict_data, fobj) with open ('data/serialize', 'rb') as fobj: dict_data = pickle.load(fobj) print ( dict_data ) print() ## CSV file read import csv with open('data/expense.csv', 'r') as fobj: fcsv = csv.reader(fobj) sum = 0 for i, row in enumerate(fcsv): print (i, row[0], row[1]) sum += int(row[1]) if i > 0 else 0 print ("Total Cost: ", sum) ''' https://docs.python.org/3/library/csv.html http://pandas.pydata.org Pandas has pandas.read_csv() function to load CSV data to a DataFrame object. ''' ## CSV file write list_items = [["name", 'age', 'country'], ['Bill Gates', 55, 'US'], ['Mark Zuckerberg', 34, 'US'], ['Swift', 35, 'Canada'] ] import csv with open('data/people.csv', 'w') as fobj: fcsv = csv.writer(fobj) fcsv.writerows(list_items) print() ## JSON Data Encode and Decode ''' JSON (JavaScript Object Notation) is a common standard to exchange data between server and client in web application. ''' import json data = { 'name' : 'Bill Gates', 'age' : 55, 'country' : 'US', 'is_retired': True } json_encoded_str = json.dumps(data) print(json_encoded_str) json_decode = json.loads(json_encoded_str) print(json_decode) ### Dumping data in file and load from file with open('data/json_data.json', 'w') as fobj: json.dump(data, fobj) with open('data/json_data.json', 'r') as fobj: json_data = json.load(fobj) print (json_data)	0	0	0
3e3c54cdb703d3ef42b7087e51bdaa42632a5cbb	360	py	Python	src/services/ThresholdController/TestingServices/FakeSchedule.py	IAPark/PITherm	a334cb0843b1961997aa90e45671d556be91380f	[ "MIT" ]	null	null	null	src/services/ThresholdController/TestingServices/FakeSchedule.py	IAPark/PITherm	a334cb0843b1961997aa90e45671d556be91380f	[ "MIT" ]	null	null	null	src/services/ThresholdController/TestingServices/FakeSchedule.py	IAPark/PITherm	a334cb0843b1961997aa90e45671d556be91380f	[ "MIT" ]	null	null	null	from flask import Flask from flask import json from multiprocessing import Queue responses_ = Queue() port = 4001 app = Flask(__name__) @app.route("/state/<int:time>")	17.142857	41	0.716667	from flask import Flask from flask import json from multiprocessing import Queue responses_ = Queue() port = 4001 app = Flask(__name__) @app.route("/state/<int:time>") def state(time: int): global responses_ return json.jsonify(responses_.get()) def run(responses: Queue,): global responses_ responses_ = responses app.run(port=port)	142	0	45
d1fc830663f4626f0851f21db7dea2f0175a03fc	15,819	py	Python	portable_spreadsheet/cell_slice.py	david-salac/Portable-spreadsheet-generator	ca31b1e77f26b77ab2ca4d328b12e3cf14c8a029	[ "MIT" ]	28	2020-05-17T18:42:07.000Z	2021-06-01T14:58:22.000Z	portable_spreadsheet/cell_slice.py	david-salac/Portable-spreadsheet-generator	ca31b1e77f26b77ab2ca4d328b12e3cf14c8a029	[ "MIT" ]	3	2020-08-19T21:28:17.000Z	2021-01-10T20:00:56.000Z	portable_spreadsheet/cell_slice.py	david-salac/Portable-spreadsheet-generator	ca31b1e77f26b77ab2ca4d328b12e3cf14c8a029	[ "MIT" ]	4	2020-10-10T12:15:40.000Z	2021-11-08T02:08:34.000Z	from numbers import Number from typing import Iterable, Tuple, Union, List, Optional import copy import numpy as np from .cell import Cell from .cell_indices import CellIndices from .serialization import Serialization # Acceptable values for the slice T_slice = Union[np.ndarray, List[Number], List[str], List[Cell], str, Number, Cell] class CellSlice(Serialization): """Encapsulate aggregating functionality and setting of the slices. Attributes: start_idx (Tuple[int, int]): Integer position of the starting cell inside the spreadsheet. Top left cell of the slice. end_idx (Tuple[int, int]): Integer position of the ending cell inside the spreadsheet. Bottom right cell of the slice. start_cell (Cell): Top left cell of the slice. end_cell (Cell): Bottom right cell of the slice. cell_subset (Iterable[Cell]): The list of all cells in the slice. driving_sheet (Sheet): Reference to the spreadsheet. """ def __init__(self, start_idx: Tuple[int, int], end_idx: Tuple[int, int], cell_subset: Iterable[Cell], driving_sheet ): """Create a cell slice from the spreadsheet. Args: start_idx (Tuple[int, int]): Integer position of the starting cell inside the spreadsheet. Top left cell of the slice. end_idx (Tuple[int, int]): Integer position of the ending cell inside the spreadsheet. Bottom right cell of the slice. cell_subset (Iterable[Cell]): The list of all cells in the slice. driving_sheet (Sheet): Reference to the spreadsheet. """ # Initialise functionality for serialization: super().__init__(export_offset=start_idx, warning_logger=driving_sheet.warning_logger, export_subset=True) self.start_idx: Tuple[int, int] = start_idx self.end_idx: Tuple[int, int] = end_idx self.start_cell: Cell = driving_sheet.iloc[start_idx] self.end_cell: Cell = driving_sheet.iloc[end_idx] self.cell_subset: Iterable[Cell] = cell_subset self.driving_sheet = driving_sheet def sum(self, skip_none_cell: bool = True) -> Cell: """Compute the sum of the aggregate. Args: skip_none_cell (bool): If true, skips all the cells with None as a value (and does not raise exception). Returns: Cell: a new cell with the result. """ if skip_none_cell: cell_subset = [nn_cell for nn_cell in self.cell_subset if nn_cell.value is not None] else: cell_subset = self.cell_subset return Cell.sum(self.start_cell, self.end_cell, cell_subset) def product(self, skip_none_cell: bool = True) -> Cell: """Compute the product of the aggregate. Args: skip_none_cell (bool): If true, skips all the cells with None as a value (and does not raise exception). Returns: Cell: a new cell with the result. """ if skip_none_cell: cell_subset = [nn_cell for nn_cell in self.cell_subset if nn_cell.value is not None] else: cell_subset = self.cell_subset return Cell.product(self.start_cell, self.end_cell, cell_subset) def min(self, skip_none_cell: bool = True) -> Cell: """Find the minimum of the aggregate. Args: skip_none_cell (bool): If true, skips all the cells with None as a value (and does not raise exception). Returns: Cell: a new cell with the result. """ if skip_none_cell: cell_subset = [nn_cell for nn_cell in self.cell_subset if nn_cell.value is not None] else: cell_subset = self.cell_subset return Cell.min(self.start_cell, self.end_cell, cell_subset) def max(self, skip_none_cell: bool = True) -> Cell: """Find the maximum of the aggregate. Args: skip_none_cell (bool): If true, skips all the cells with None as a value (and does not raise exception). Returns: Cell: a new cell with the result. """ if skip_none_cell: cell_subset = [nn_cell for nn_cell in self.cell_subset if nn_cell.value is not None] else: cell_subset = self.cell_subset return Cell.max(self.start_cell, self.end_cell, cell_subset) def mean(self, skip_none_cell: bool = True) -> Cell: """Compute the mean-average of the aggregate. Args: skip_none_cell (bool): If true, skips all the cells with None as a value (and does not raise exception). Returns: Cell: a new cell with the result. """ if skip_none_cell: cell_subset = [nn_cell for nn_cell in self.cell_subset if nn_cell.value is not None] else: cell_subset = self.cell_subset return Cell.mean(self.start_cell, self.end_cell, cell_subset) def average(self, skip_none_cell: bool = True) -> Cell: """Compute the mean-average of the aggregate. Args: skip_none_cell (bool): If true, skips all the cells with None as a value (and does not raise exception). Returns: Cell: a new cell with the result. """ return self.mean(skip_none_cell=skip_none_cell) def stdev(self, skip_none_cell: bool = True) -> Cell: """Compute the standard deviation of the aggregate. Args: skip_none_cell (bool): If true, skips all the cells with None as a value (and does not raise exception). Returns: Cell: a new cell with the result. """ if skip_none_cell: cell_subset = [nn_cell for nn_cell in self.cell_subset if nn_cell.value is not None] else: cell_subset = self.cell_subset return Cell.stdev(self.start_cell, self.end_cell, cell_subset) def median(self, skip_none_cell: bool = True) -> Cell: """Compute the median of the aggregate. Args: skip_none_cell (bool): If true, skips all the cells with None as a value (and does not raise exception). Returns: Cell: a new cell with the result. """ if skip_none_cell: cell_subset = [nn_cell for nn_cell in self.cell_subset if nn_cell.value is not None] else: cell_subset = self.cell_subset return Cell.median(self.start_cell, self.end_cell, cell_subset) def count(self, skip_none_cell: bool = True) -> Cell: """Compute the number of items in the aggregate. Args: skip_none_cell (bool): If true, skips all the cells with None as a value (and does not raise exception). Returns: Cell: a new cell with the result. """ if skip_none_cell: cell_subset = [nn_cell for nn_cell in self.cell_subset if nn_cell.value is not None] else: cell_subset = self.cell_subset return Cell.count(self.start_cell, self.end_cell, cell_subset) def irr(self, skip_none_cell: bool = True) -> Cell: """Compute the Internal Rate of Return (IRR) of items in the aggregate. Args: skip_none_cell (bool): If true, skips all the cells with None as a value (and does not raise exception). Returns: Cell: a new cell with the result. """ if skip_none_cell: cell_subset = [nn_cell for nn_cell in self.cell_subset if nn_cell.value is not None] else: cell_subset = self.cell_subset return Cell.irr(self.start_cell, self.end_cell, cell_subset) def match_negative_before_positive(self, skip_none_cell: bool = True) -> Cell: """Find the position of the last negative number in the series that is located just before the first non-negative number. Args: skip_none_cell (bool): If true, skips all the cells with None as a value (and does not raise exception). Returns: Cell: Return the position of the negative number in a series that is located just before the first positive number (or zero). """ if skip_none_cell: cell_subset = [nn_cell for nn_cell in self.cell_subset if nn_cell.value is not None] else: cell_subset = self.cell_subset return Cell.match_negative_before_positive(self.start_cell, self.end_cell, cell_subset) @property def excel_format(self): """Should not be accessible for slides.""" raise NotImplementedError @excel_format.setter def excel_format(self, new_format: dict): """Set the Excel cell format/style. Read the documentation: https://xlsxwriter.readthedocs.io/format.html Args: new_format (dict): New format definition. """ if not isinstance(new_format, dict): raise ValueError("New format has to be a dictionary!") for row in range(self.start_idx[0], self.end_idx[0] + 1): for col in range(self.start_idx[1], self.end_idx[1] + 1): self.driving_sheet.iloc[row, col].excel_format = new_format @property def description(self) -> Optional[str]: """Not implementable. """ raise NotImplementedError @description.setter def description(self, new_description: Optional[str]): """Set the cell description. Args: new_description (Optional[str]): description of the cell. """ if (new_description is not None and not isinstance(new_description, str)): raise ValueError("Cell description has to be a string value!") for row in range(self.start_idx[0], self.end_idx[0] + 1): for col in range(self.start_idx[1], self.end_idx[1] + 1): self.driving_sheet.iloc[row, col].description = new_description def _set_value_on_position(self, other: Union[Cell, Number], row: int, col: int) -> None: """Set the cell on given position in the spreadsheet to the value 'other'. Args: other (Union[Cell, Number]): new value to be set. row (int): the row integer position in the spreadsheet (indexed from 0). col (int): the column integer position in the spreadsheet (indexed from 0). """ if isinstance(other, Cell): if other.anchored: _value = Cell.reference(other) elif other.is_variable: # Set value _value = Cell.variable(other) # Anchor it: _value.coordinates = (row, col) else: # Create a deep copy _value = copy.deepcopy(other) # Anchor it: _value.coordinates = (row, col) self.driving_sheet.iloc[row, col] = _value else: # Call the external logic to manage the same self.driving_sheet.iloc[row, col] = other # Set to scalar / Other cells: def set(self, other: T_slice) -> None: """Set all the values in the slice to the new one (or the list of values). Args: other: Union[np.ndarray, List[Number], List[Cell], Number, Cell]: Some value or list (or numpy array) of values that should be set for all the cells inside slice. """ if isinstance(other, (np.ndarray, list, tuple)): dim_match = True is_list = True is_1d = False by_row = self.shape[0] > self.shape[1] if hasattr(other, "shape"): dim_match = other.shape == self.shape is_list = False is_1d = len(other.shape) == 1 if is_1d: dim_match = max(other.shape) == max(self.shape) else: is_list = True if min(self.shape) == 1: dim_match = len(other) == max(self.shape) is_1d = True if not dim_match: raise ValueError("Shape of the input does not match to the " "shape of the slice!") if is_1d: col = self.start_idx[1] row = self.start_idx[0] for val in other: self._set_value_on_position(val, row, col) if by_row: row += 1 else: col += 1 else: # If is N-dimensional for row in range(self.start_idx[0], self.end_idx[0] + 1): for col in range(self.start_idx[1], self.end_idx[1] + 1): if is_list: val = other[row - self.start_idx[0]][ col - self.start_idx[1] ] else: val = other[ row - self.start_idx[0], col - self.start_idx[1] ] self._set_value_on_position(val, row, col) else: for row in range(self.start_idx[0], self.end_idx[0] + 1): for col in range(self.start_idx[1], self.end_idx[1] + 1): # Set the right values self._set_value_on_position(other, row, col) def __ilshift__(self, other: T_slice): """Overrides operator <<= to do a set functionality. """ self.set(other) # ==== OVERRIDE ABSTRACT METHODS AND PROPERTIES OF SERIALIZATION CLASS ==== @Serialization.shape.getter def shape(self) -> Tuple[int, int]: """Return the shape of the sheet in the NumPy logic. Returns: Tuple[int]: Number of rows, Number of columns """ return (self.end_idx[0] - self.start_idx[0] + 1, self.end_idx[1] - self.start_idx[1] + 1) @Serialization.cell_indices.getter def cell_indices(self) -> CellIndices: """Get the cell indices. Returns: CellIndices: Cell indices of the spreadsheet. """ return self.driving_sheet._cell_indices def _get_cell_at(self, row: int, column: int) -> 'Cell': """Get the particular cell on the (row, column) position. Returns: Cell: The call on given position. """ return self.driving_sheet.iloc[self.start_idx[0] + row, self.start_idx[1] + column] def _get_variables(self): """Return the sheet variables as _SheetVariables object. Returns: _SheetVariables: Sheet variables. """ return self.driving_sheet.var # =========================================================================	37.935252	79	0.554081	from numbers import Number from typing import Iterable, Tuple, Union, List, Optional import copy import numpy as np from .cell import Cell from .cell_indices import CellIndices from .serialization import Serialization # Acceptable values for the slice T_slice = Union[np.ndarray, List[Number], List[str], List[Cell], str, Number, Cell] class CellSlice(Serialization): """Encapsulate aggregating functionality and setting of the slices. Attributes: start_idx (Tuple[int, int]): Integer position of the starting cell inside the spreadsheet. Top left cell of the slice. end_idx (Tuple[int, int]): Integer position of the ending cell inside the spreadsheet. Bottom right cell of the slice. start_cell (Cell): Top left cell of the slice. end_cell (Cell): Bottom right cell of the slice. cell_subset (Iterable[Cell]): The list of all cells in the slice. driving_sheet (Sheet): Reference to the spreadsheet. """ def __init__(self, start_idx: Tuple[int, int], end_idx: Tuple[int, int], cell_subset: Iterable[Cell], driving_sheet ): """Create a cell slice from the spreadsheet. Args: start_idx (Tuple[int, int]): Integer position of the starting cell inside the spreadsheet. Top left cell of the slice. end_idx (Tuple[int, int]): Integer position of the ending cell inside the spreadsheet. Bottom right cell of the slice. cell_subset (Iterable[Cell]): The list of all cells in the slice. driving_sheet (Sheet): Reference to the spreadsheet. """ # Initialise functionality for serialization: super().__init__(export_offset=start_idx, warning_logger=driving_sheet.warning_logger, export_subset=True) self.start_idx: Tuple[int, int] = start_idx self.end_idx: Tuple[int, int] = end_idx self.start_cell: Cell = driving_sheet.iloc[start_idx] self.end_cell: Cell = driving_sheet.iloc[end_idx] self.cell_subset: Iterable[Cell] = cell_subset self.driving_sheet = driving_sheet def sum(self, skip_none_cell: bool = True) -> Cell: """Compute the sum of the aggregate. Args: skip_none_cell (bool): If true, skips all the cells with None as a value (and does not raise exception). Returns: Cell: a new cell with the result. """ if skip_none_cell: cell_subset = [nn_cell for nn_cell in self.cell_subset if nn_cell.value is not None] else: cell_subset = self.cell_subset return Cell.sum(self.start_cell, self.end_cell, cell_subset) def product(self, skip_none_cell: bool = True) -> Cell: """Compute the product of the aggregate. Args: skip_none_cell (bool): If true, skips all the cells with None as a value (and does not raise exception). Returns: Cell: a new cell with the result. """ if skip_none_cell: cell_subset = [nn_cell for nn_cell in self.cell_subset if nn_cell.value is not None] else: cell_subset = self.cell_subset return Cell.product(self.start_cell, self.end_cell, cell_subset) def min(self, skip_none_cell: bool = True) -> Cell: """Find the minimum of the aggregate. Args: skip_none_cell (bool): If true, skips all the cells with None as a value (and does not raise exception). Returns: Cell: a new cell with the result. """ if skip_none_cell: cell_subset = [nn_cell for nn_cell in self.cell_subset if nn_cell.value is not None] else: cell_subset = self.cell_subset return Cell.min(self.start_cell, self.end_cell, cell_subset) def max(self, skip_none_cell: bool = True) -> Cell: """Find the maximum of the aggregate. Args: skip_none_cell (bool): If true, skips all the cells with None as a value (and does not raise exception). Returns: Cell: a new cell with the result. """ if skip_none_cell: cell_subset = [nn_cell for nn_cell in self.cell_subset if nn_cell.value is not None] else: cell_subset = self.cell_subset return Cell.max(self.start_cell, self.end_cell, cell_subset) def mean(self, skip_none_cell: bool = True) -> Cell: """Compute the mean-average of the aggregate. Args: skip_none_cell (bool): If true, skips all the cells with None as a value (and does not raise exception). Returns: Cell: a new cell with the result. """ if skip_none_cell: cell_subset = [nn_cell for nn_cell in self.cell_subset if nn_cell.value is not None] else: cell_subset = self.cell_subset return Cell.mean(self.start_cell, self.end_cell, cell_subset) def average(self, skip_none_cell: bool = True) -> Cell: """Compute the mean-average of the aggregate. Args: skip_none_cell (bool): If true, skips all the cells with None as a value (and does not raise exception). Returns: Cell: a new cell with the result. """ return self.mean(skip_none_cell=skip_none_cell) def stdev(self, skip_none_cell: bool = True) -> Cell: """Compute the standard deviation of the aggregate. Args: skip_none_cell (bool): If true, skips all the cells with None as a value (and does not raise exception). Returns: Cell: a new cell with the result. """ if skip_none_cell: cell_subset = [nn_cell for nn_cell in self.cell_subset if nn_cell.value is not None] else: cell_subset = self.cell_subset return Cell.stdev(self.start_cell, self.end_cell, cell_subset) def median(self, skip_none_cell: bool = True) -> Cell: """Compute the median of the aggregate. Args: skip_none_cell (bool): If true, skips all the cells with None as a value (and does not raise exception). Returns: Cell: a new cell with the result. """ if skip_none_cell: cell_subset = [nn_cell for nn_cell in self.cell_subset if nn_cell.value is not None] else: cell_subset = self.cell_subset return Cell.median(self.start_cell, self.end_cell, cell_subset) def count(self, skip_none_cell: bool = True) -> Cell: """Compute the number of items in the aggregate. Args: skip_none_cell (bool): If true, skips all the cells with None as a value (and does not raise exception). Returns: Cell: a new cell with the result. """ if skip_none_cell: cell_subset = [nn_cell for nn_cell in self.cell_subset if nn_cell.value is not None] else: cell_subset = self.cell_subset return Cell.count(self.start_cell, self.end_cell, cell_subset) def irr(self, skip_none_cell: bool = True) -> Cell: """Compute the Internal Rate of Return (IRR) of items in the aggregate. Args: skip_none_cell (bool): If true, skips all the cells with None as a value (and does not raise exception). Returns: Cell: a new cell with the result. """ if skip_none_cell: cell_subset = [nn_cell for nn_cell in self.cell_subset if nn_cell.value is not None] else: cell_subset = self.cell_subset return Cell.irr(self.start_cell, self.end_cell, cell_subset) def match_negative_before_positive(self, skip_none_cell: bool = True) -> Cell: """Find the position of the last negative number in the series that is located just before the first non-negative number. Args: skip_none_cell (bool): If true, skips all the cells with None as a value (and does not raise exception). Returns: Cell: Return the position of the negative number in a series that is located just before the first positive number (or zero). """ if skip_none_cell: cell_subset = [nn_cell for nn_cell in self.cell_subset if nn_cell.value is not None] else: cell_subset = self.cell_subset return Cell.match_negative_before_positive(self.start_cell, self.end_cell, cell_subset) @property def excel_format(self): """Should not be accessible for slides.""" raise NotImplementedError @excel_format.setter def excel_format(self, new_format: dict): """Set the Excel cell format/style. Read the documentation: https://xlsxwriter.readthedocs.io/format.html Args: new_format (dict): New format definition. """ if not isinstance(new_format, dict): raise ValueError("New format has to be a dictionary!") for row in range(self.start_idx[0], self.end_idx[0] + 1): for col in range(self.start_idx[1], self.end_idx[1] + 1): self.driving_sheet.iloc[row, col].excel_format = new_format @property def description(self) -> Optional[str]: """Not implementable. """ raise NotImplementedError @description.setter def description(self, new_description: Optional[str]): """Set the cell description. Args: new_description (Optional[str]): description of the cell. """ if (new_description is not None and not isinstance(new_description, str)): raise ValueError("Cell description has to be a string value!") for row in range(self.start_idx[0], self.end_idx[0] + 1): for col in range(self.start_idx[1], self.end_idx[1] + 1): self.driving_sheet.iloc[row, col].description = new_description def _set_value_on_position(self, other: Union[Cell, Number], row: int, col: int) -> None: """Set the cell on given position in the spreadsheet to the value 'other'. Args: other (Union[Cell, Number]): new value to be set. row (int): the row integer position in the spreadsheet (indexed from 0). col (int): the column integer position in the spreadsheet (indexed from 0). """ if isinstance(other, Cell): if other.anchored: _value = Cell.reference(other) elif other.is_variable: # Set value _value = Cell.variable(other) # Anchor it: _value.coordinates = (row, col) else: # Create a deep copy _value = copy.deepcopy(other) # Anchor it: _value.coordinates = (row, col) self.driving_sheet.iloc[row, col] = _value else: # Call the external logic to manage the same self.driving_sheet.iloc[row, col] = other # Set to scalar / Other cells: def set(self, other: T_slice) -> None: """Set all the values in the slice to the new one (or the list of values). Args: other: Union[np.ndarray, List[Number], List[Cell], Number, Cell]: Some value or list (or numpy array) of values that should be set for all the cells inside slice. """ if isinstance(other, (np.ndarray, list, tuple)): dim_match = True is_list = True is_1d = False by_row = self.shape[0] > self.shape[1] if hasattr(other, "shape"): dim_match = other.shape == self.shape is_list = False is_1d = len(other.shape) == 1 if is_1d: dim_match = max(other.shape) == max(self.shape) else: is_list = True if min(self.shape) == 1: dim_match = len(other) == max(self.shape) is_1d = True if not dim_match: raise ValueError("Shape of the input does not match to the " "shape of the slice!") if is_1d: col = self.start_idx[1] row = self.start_idx[0] for val in other: self._set_value_on_position(val, row, col) if by_row: row += 1 else: col += 1 else: # If is N-dimensional for row in range(self.start_idx[0], self.end_idx[0] + 1): for col in range(self.start_idx[1], self.end_idx[1] + 1): if is_list: val = other[row - self.start_idx[0]][ col - self.start_idx[1] ] else: val = other[ row - self.start_idx[0], col - self.start_idx[1] ] self._set_value_on_position(val, row, col) else: for row in range(self.start_idx[0], self.end_idx[0] + 1): for col in range(self.start_idx[1], self.end_idx[1] + 1): # Set the right values self._set_value_on_position(other, row, col) def __ilshift__(self, other: T_slice): """Overrides operator <<= to do a set functionality. """ self.set(other) # ==== OVERRIDE ABSTRACT METHODS AND PROPERTIES OF SERIALIZATION CLASS ==== @Serialization.shape.getter def shape(self) -> Tuple[int, int]: """Return the shape of the sheet in the NumPy logic. Returns: Tuple[int]: Number of rows, Number of columns """ return (self.end_idx[0] - self.start_idx[0] + 1, self.end_idx[1] - self.start_idx[1] + 1) @Serialization.cell_indices.getter def cell_indices(self) -> CellIndices: """Get the cell indices. Returns: CellIndices: Cell indices of the spreadsheet. """ return self.driving_sheet._cell_indices def _get_cell_at(self, row: int, column: int) -> 'Cell': """Get the particular cell on the (row, column) position. Returns: Cell: The call on given position. """ return self.driving_sheet.iloc[self.start_idx[0] + row, self.start_idx[1] + column] def _get_variables(self): """Return the sheet variables as _SheetVariables object. Returns: _SheetVariables: Sheet variables. """ return self.driving_sheet.var # =========================================================================	0	0	0
03afcc1023649b896ec4f37fc2b3a99fcc1a2bca	2,546	py	Python	radiaTest-worker/worker/utils/bash.py	openeuler-mirror/radiaTest	4a067511d6ab69f76b8dc08667b8a1f8c1c73d23	[ "MulanPSL-1.0" ]	null	null	null	radiaTest-worker/worker/utils/bash.py	openeuler-mirror/radiaTest	4a067511d6ab69f76b8dc08667b8a1f8c1c73d23	[ "MulanPSL-1.0" ]	1	2022-03-23T06:53:25.000Z	2022-03-23T06:53:25.000Z	radiaTest-worker/worker/utils/bash.py	openeuler-mirror/radiaTest	4a067511d6ab69f76b8dc08667b8a1f8c1c73d23	[ "MulanPSL-1.0" ]	null	null	null	from shlex import quote from subprocess import getoutput, getstatusoutput # from flask import current_app	31.04878	154	0.516104	from shlex import quote from subprocess import getoutput, getstatusoutput # from flask import current_app def install_base(body, storage_pool): fixed_mac = "" if body.get("mac"): fixed_mac = ",mac={}".format(quote(body.get("mac"))) controller = "" if body.get("frame") == "aarch64": controller = "--controller type=pci,model=pcie-root-port,index=50" cmd = ( "virt-install --os-type generic --name {} --memory {} --vcpus {},sockets={},cores={},threads={} --cpu={} --disk path={}/{}.qcow2,bus={} ".format( quote(body.get("name")), quote(str(body.get("memory"))), quote( str( int(body.get("sockets")) * int(body.get("cores")) * int(body.get("threads")) ) ), quote(str(body.get("sockets"))), quote(str(body.get("cores"))), quote(str(body.get("threads"))), quote(body.get("cpu_mode")), quote(storage_pool.replace("/$", "")), quote(body.get("name")), quote(body.get("disk_bus")), ) + " --network {}={},model={}".format( quote(body.get("net_mode")), getoutput(" virsh iface-list \| sed '1,2d' \| awk '{print $1}' \| head -1"), quote(body.get("net_bus")), ) + fixed_mac + " --video={} --noautoconsole --graphics vnc,listen={} --check path_in_use=1 --os-variant unknown {} ".format( quote(body.get("video_bus")), quote(body.get("host")), controller, ) ) return cmd def get_bridge_source(): return "virsh iface-list \| sed '1,2d;/^$/d' \| grep -v '^ lo' \| awk '{print $1}' \| shuf -n1" def get_network_source(): return "virsh net-list \| sed '1,2d;/^$/d' \| awk '{print $1}' \| shuf -n 1" def rm_disk_image(name, storage_pool): return getoutput( "rm -rf {}/{}.qcow2".format( quote(storage_pool), quote(name), ) ) def domain_cli(act, name): return getstatusoutput("virsh {} {}".format(quote(act), quote(name))) def domain_state(name): return getstatusoutput( "export LANG=en_US.UTF-8 && virsh list --all \| grep {} \| awk -F '{}' ".format( quote(name), quote(name) ) + " '{print $NF}' \| sed 's/^ //;s/ $//' " ) def undefine_domain(name): return getstatusoutput( "virsh undefine --nvram --remove-all-storage {}".format(quote(name)) )	2,273	0	161
0eff813d270b63670413294208f76ac98ecc73aa	2,025	py	Python	pyutilib/misc/twzzle.py	PyUtilib/PyUtilib	d99406f2af1fb62268c34453a2fbe6bd4a7348f0	[ "BSD-3-Clause" ]	24	2016-04-02T10:00:02.000Z	2021-03-02T16:40:18.000Z	pyutilib/misc/twzzle.py	PyUtilib/PyUtilib	d99406f2af1fb62268c34453a2fbe6bd4a7348f0	[ "BSD-3-Clause" ]	105	2015-10-29T03:29:58.000Z	2021-12-30T22:00:45.000Z	pyutilib/misc/twzzle.py	PyUtilib/PyUtilib	d99406f2af1fb62268c34453a2fbe6bd4a7348f0	[ "BSD-3-Clause" ]	22	2016-01-21T15:35:25.000Z	2021-05-15T20:17:44.000Z	# _________________________________________________________________________ # # PyUtilib: A Python utility library. # Copyright (c) 2008 Sandia Corporation. # This software is distributed under the BSD License. # Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation, # the U.S. Government retains certain rights in this software. # _________________________________________________________________________ # # Class to encapsulate a progress indicator __all__ = ['progress'] import sys import time import unittest class progressException(Exception): 'Error to raise for any recursive problem.' if __name__ == '__main__': widgetTestSuite = unittest.TestSuite() widgetTestSuite.addTest(TestCase("testProgress")) runner = unittest.TextTestRunner() runner.run(widgetTestSuite)	26.298701	76	0.607407	# _________________________________________________________________________ # # PyUtilib: A Python utility library. # Copyright (c) 2008 Sandia Corporation. # This software is distributed under the BSD License. # Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation, # the U.S. Government retains certain rights in this software. # _________________________________________________________________________ # # Class to encapsulate a progress indicator __all__ = ['progress'] import sys import time import unittest class progressException(Exception): 'Error to raise for any recursive problem.' class progress: def __init__(self, period=1): self._twissler = ["\|", "/", "-", "\\", "\|"] self._state = 0 self._period = period self._ctr = period def getStart(self): sys.stdout.write('\t[ ') # include 2 spaces for the twissler sys.stdout.flush() def getStart(self, text): sys.stdout.write('\t %s [ ' % (text)) # include 2 spaces for the twissler sys.stdout.flush() def moveOn(self): try: self._ctr += 1 if self._ctr <= self._period: return self._ctr = 1 self._state += 1 if self._state >= 5: self._state = 1 sys.stdout.write( chr(8) + chr(8) + self._twissler[self._state] + ']') sys.stdout.flush() except: raise progressException('failed to progress') class TestCase(unittest.TestCase): def setUp(self): pass def tearDown(self): pass def testProgress(self): p = progress() p.getStart("HERE") for a in range(0, 10, 1): p.moveOn() time.sleep(0.2) if __name__ == '__main__': widgetTestSuite = unittest.TestSuite() widgetTestSuite.addTest(TestCase("testProgress")) runner = unittest.TextTestRunner() runner.run(widgetTestSuite)	958	7	235
980e573908e89dde46aaea141c146ea143777822	827	py	Python	performance-storage-service/pss_project/api/serializers/rest/metrics/IncrementalMetricsSerializer.py	cmu-db/noisepage-stats	d61a0e143904748b3f7f43628a5b29769a5c9cf8	[ "MIT" ]	23	2020-12-22T20:19:51.000Z	2021-11-24T06:11:01.000Z	performance-storage-service/pss_project/api/serializers/rest/metrics/IncrementalMetricsSerializer.py	cmu-db/noisepage-test	d61a0e143904748b3f7f43628a5b29769a5c9cf8	[ "MIT" ]	13	2020-06-05T22:36:49.000Z	2020-11-10T16:25:04.000Z	performance-storage-service/pss_project/api/serializers/rest/metrics/IncrementalMetricsSerializer.py	cmu-db/noisepage-test	d61a0e143904748b3f7f43628a5b29769a5c9cf8	[ "MIT" ]	2	2020-06-08T18:03:34.000Z	2020-10-06T18:01:35.000Z	from rest_framework.serializers import Serializer, DecimalField, IntegerField from pss_project.api.serializers.rest.metrics.LatencyMetricsSerializer \ import LatencyMetricsSerializer from pss_project.api.models.rest.metrics.IncrementalMetrics \ import IncrementalMetrics from pss_project.api.serializers.rest.metrics.MemoryMetricsSerializer \ import MemoryMetricsSerializer	39.380952	77	0.754534	from rest_framework.serializers import Serializer, DecimalField, IntegerField from pss_project.api.serializers.rest.metrics.LatencyMetricsSerializer \ import LatencyMetricsSerializer from pss_project.api.models.rest.metrics.IncrementalMetrics \ import IncrementalMetrics from pss_project.api.serializers.rest.metrics.MemoryMetricsSerializer \ import MemoryMetricsSerializer class IncrementalMetricsSerializer(Serializer): # Fields time = IntegerField() throughput = DecimalField(max_digits=24, decimal_places=15, coerce_to_string=False) latency = LatencyMetricsSerializer(required=False) memory_info = MemoryMetricsSerializer(required=False) def create(self, validated_data): return IncrementalMetrics(**validated_data)	64	353	23
c59a57fdb4853653342c36c7a372a1ad6827770f	2,673	py	Python	fsttest/_test_case.py	eddieantonio/fsttest	8ff71a9aa41a70a30832fa219b72e7478872c16f	[ "MIT" ]	null	null	null	fsttest/_test_case.py	eddieantonio/fsttest	8ff71a9aa41a70a30832fa219b72e7478872c16f	[ "MIT" ]	1	2020-01-27T21:43:04.000Z	2020-01-28T15:57:05.000Z	fsttest/_test_case.py	eddieantonio/fsttest	8ff71a9aa41a70a30832fa219b72e7478872c16f	[ "MIT" ]	1	2021-04-26T17:46:19.000Z	2021-04-26T17:46:19.000Z	#!/usr/bin/env python3 # -- coding: UTF-8 -- from pathlib import Path from typing import Any, Dict, List, Optional, Union from ._fst import FST from ._results import FailedTestResult, PassedTestResult from .exceptions import TestCaseDefinitionError class TestCase: """ An executable test case. """ @staticmethod def from_description( raw_test_case: Dict[str, Any], location: Optional[Path] = None ) -> "TestCase": """ Given a dictionary, parses and returns an executable test case. """ # Parse a few things if "expect" not in raw_test_case: raise TestCaseDefinitionError('Missing "expect" in test case') raw_expected = raw_test_case["expect"] if isinstance(raw_expected, str): expected = [raw_expected] elif isinstance(raw_expected, list): if len(raw_expected) == 0: raise TestCaseDefinitionError( "Must provide at least one expected transduction" ) expected = raw_expected else: raise TestCaseDefinitionError( '"expect" MUST be either a single string or a list of strings;' f"instead got {raw_expected!r}" ) if "upper" in raw_test_case: direction = "down" fst_input = raw_test_case["upper"] elif "lower" in raw_test_case: direction = "up" fst_input = raw_test_case["lower"] else: raise TestCaseDefinitionError('Missing "upper" or "lower" in test case') return TestCase(fst_input, expected, direction, location)	33.835443	88	0.606061	#!/usr/bin/env python3 # -- coding: UTF-8 -- from pathlib import Path from typing import Any, Dict, List, Optional, Union from ._fst import FST from ._results import FailedTestResult, PassedTestResult from .exceptions import TestCaseDefinitionError class TestCase: """ An executable test case. """ def __init__( self, input_: str, expected: List[str], direction: str, location: Optional[Path] ): self.input = input_ self.expected = expected self.direction = direction self.location = location def execute(self, fst: FST) -> Union[PassedTestResult, FailedTestResult]: transductions = fst.apply([self.input], direction=self.direction) assert ( self.input in transductions ), f"Expected to find {self.input} in {transductions}" actual_transductions = transductions[self.input] assert len(self.expected) >= 1, "Must have at least on expected output" if set(self.expected) <= set(actual_transductions): return PassedTestResult(location=self.location) else: return FailedTestResult( given=self.input, expected=self.expected, actual=actual_transductions, location=self.location, ) @staticmethod def from_description( raw_test_case: Dict[str, Any], location: Optional[Path] = None ) -> "TestCase": """ Given a dictionary, parses and returns an executable test case. """ # Parse a few things if "expect" not in raw_test_case: raise TestCaseDefinitionError('Missing "expect" in test case') raw_expected = raw_test_case["expect"] if isinstance(raw_expected, str): expected = [raw_expected] elif isinstance(raw_expected, list): if len(raw_expected) == 0: raise TestCaseDefinitionError( "Must provide at least one expected transduction" ) expected = raw_expected else: raise TestCaseDefinitionError( '"expect" MUST be either a single string or a list of strings;' f"instead got {raw_expected!r}" ) if "upper" in raw_test_case: direction = "down" fst_input = raw_test_case["upper"] elif "lower" in raw_test_case: direction = "up" fst_input = raw_test_case["lower"] else: raise TestCaseDefinitionError('Missing "upper" or "lower" in test case') return TestCase(fst_input, expected, direction, location)	946	0	54
84a25250ddea53d73b4571ee50268f072bd9f331	1,073	py	Python	2019/d19.py	max-f/advent-of-code	3c0ee995f7c0691418ecb86cbfa201b3d03131b8	[ "MIT" ]	null	null	null	2019/d19.py	max-f/advent-of-code	3c0ee995f7c0691418ecb86cbfa201b3d03131b8	[ "MIT" ]	null	null	null	2019/d19.py	max-f/advent-of-code	3c0ee995f7c0691418ecb86cbfa201b3d03131b8	[ "MIT" ]	null	null	null	#!/usr/bin/env python import copy from collections import deque, defaultdict from utils.intcode import Machine from utils.utils import get_input, ints if __name__ == "__main__": main()	21.897959	60	0.615098	#!/usr/bin/env python import copy from collections import deque, defaultdict from utils.intcode import Machine from utils.utils import get_input, ints def part1(intcode) -> int: total_affected = 0 for y in range(50): for x in range(50): pos_in = position_in_beam(intcode, x, y) total_affected += pos_in return total_affected def part2(intcode, n=100) -> int: x = 100 y = 100 while not position_in_beam(intcode, x + (n - 1), y): y += 1 while not position_in_beam(intcode, x, y + (n - 1)): x += 1 return x * 10000 + y def position_in_beam(intcode, x, y): machine = Machine(0, copy.copy(intcode), deque(), 0) machine.inputs.append(x) machine.inputs.append(y) return bool(machine.run()[-1][0]) def main(): input_txt = get_input(19) int_code_list = ints(input_txt) code = defaultdict(int, enumerate(int_code_list)) p1 = part1(code) print(f"Part 1: {p1}") p2 = part2(code) print(f"Part 2: {p2}") if __name__ == "__main__": main()	784	0	92
fe04686535636400f725184e167933f807600954	13,763	py	Python	src/core/task.py	gaotuan/Yearning-1.2.0_me	8b4a1a443abc39a638931907599b9306fc92531c	[ "Apache-2.0" ]	1	2020-06-05T06:17:48.000Z	2020-06-05T06:17:48.000Z	src/core/task.py	gaotuan/Yearning-1.2.0_me	8b4a1a443abc39a638931907599b9306fc92531c	[ "Apache-2.0" ]	5	2020-04-17T03:38:08.000Z	2020-04-17T03:39:26.000Z	src/core/task.py	gaotuan/SQL-Manager	8b4a1a443abc39a638931907599b9306fc92531c	[ "Apache-2.0" ]	null	null	null	from __future__ import absolute_import, unicode_literals import logging import functools import threading import time from django.http import HttpResponse from libs import send_email, util from libs import call_inception from .models import ( Usermessage, DatabaseList, Account, globalpermissions, SqlOrder, SqlRecord, grained ) from core.models import Account from core.utils.send_feishu_mess import send_msg as fs_send_msg CUSTOM_ERROR = logging.getLogger('Yearning.core.views') def grained_permissions(func): ''' :argument 装饰器函数,校验细化权限。非法请求直接返回401交由前端判断状态码 ''' @functools.wraps(func) return wrapper class order_push_message(threading.Thread): ''' :argument 同意执行工单调用该方法异步处理数据 ''' def execute(self): ''' :argument 将获得的sql语句提交给inception执行并将返回结果写入SqlRecord表,最后更改该工单SqlOrder表中的status :param self.order self.id :return: none ''' time.sleep(self.order.delay * 60) try: detail = DatabaseList.objects.filter(id=self.order.bundle_id).first() with call_inception.Inception( LoginDic={ 'host': detail.ip, 'user': detail.username, 'password': detail.password, 'db': self.order.basename, 'port': detail.port } ) as f: res = f.Execute(sql=self.order.sql, backup=self.order.backup) for i in res: if i['errlevel'] != 0: SqlOrder.objects.filter(work_id=self.order.work_id).update(status=4) SqlRecord.objects.get_or_create( state=i['stagestatus'], sql=i['sql'], error=i['errormessage'], workid=self.order.work_id, affectrow=i['affected_rows'], sequence=i['sequence'], execute_time=i['execute_time'], SQLSHA1=i['SQLSHA1'], backup_dbname=i['backup_dbname'] ) except Exception as e: CUSTOM_ERROR.error(f'{e.__class__.__name__}--邮箱推送失败: {e}') finally: status = SqlOrder.objects.filter(work_id=self.order.work_id).first() if status.status != 4: SqlOrder.objects.filter(id=self.id).update(status=1) def agreed(self): ''' :argument 将执行的结果通过站内信,email,dingding 发送 :param self.from_user self.to_user self.title self.order self.addr_ip :return: none ''' t = threading.Thread(target=order_push_message.con_close, args=(self,)) t.start() t.join() class rejected_push_messages(threading.Thread): ''' :argument 驳回工单调用该方法异步处理数据 ''' def execute(self): ''' :argument 更改该工单SqlOrder表中的status :param self._tmpData self.addr_ip self.text self.to_user :return: none ''' content = DatabaseList.objects.filter(id=self._tmpData['bundle_id']).first() mail = Account.objects.filter(username=self.to_user).first() tag = globalpermissions.objects.filter(authorization='global').first() if tag.message['ding']: try: if content.url: util.dingding( content='工单驳回通知\n工单编号:%s\n发起人:%s\n操作人:%s\n地址:%s\n驳回说明:%s\n状态:驳回' % (self._tmpData['work_id'], self.to_user,self.from_user, self.addr_ip, self.text), url=content.url) except Exception as e: CUSTOM_ERROR.error(f'{e.__class__.__name__}--钉钉推送失败: {e}') if tag.message['feishu']: try: user_mail = Account.objects.filter(username=self.to_user).values('email').first() user = {'mail': user_mail.get('email')} fs_send_msg( msg='工单驳回通知\n工单编号:%s\n发起人:%s\n操作人:%s\n地址:%s\n驳回说明:%s\n状态:驳回' % (self._tmpData['work_id'], self.to_user,self.from_user, self.addr_ip, self.text),user=user) except Exception as e: CUSTOM_ERROR.error(f'{e.__class__.__name__}--飞书推送失败: {e}') if tag.message['mail']: try: if mail.email: mess_info = { 'workid': self._tmpData['work_id'], 'to_user': self.to_user, 'addr': self.addr_ip, 'rejected': self.text} put_mess = send_email.send_email(to_addr=mail.email) put_mess.send_mail(mail_data=mess_info, type=1) except Exception as e: CUSTOM_ERROR.error(f'{e.__class__.__name__}--邮箱推送失败: {e}') class submit_push_messages(threading.Thread): ''' :argument 提交工单调用该方法异步处理数据 ''' def submit(self): ''' :argument 更改该工单SqlOrder表中的status :param self.workId self.user self.addr_ip self.text self.assigned self.id :return: none ''' content = DatabaseList.objects.filter(id=self.id).first() mail = Account.objects.filter(username=self.assigned).first() tag = globalpermissions.objects.filter(authorization='global').first() if tag.message['ding']: if content.url: try: util.dingding( content='工单提交通知\n工单编号:%s\n发起人:%s\n审批人:%s\n地址:%s\n工单说明:%s\n状态:已提交\n备注:%s' % (self.workId, self.user,self.assigned, self.addr_ip, self.text, content.before), url=content.url) except Exception as e: CUSTOM_ERROR.error(f'{e.__class__.__name__}--钉钉推送失败: {e}') if tag.message['feishu']: try: user_mail = Account.objects.filter(username=self.assigned).values('email').first() user = {'mail': user_mail.get('email')} fs_send_msg( msg='工单提交通知\n工单编号:%s\n发起人:%s\n审批人:%s\n地址:%s\n工单说明:%s\n状态:已提交\n备注:%s' % (self.workId, self.user,self.assigned, self.addr_ip, self.text, content.before),user=user) except Exception as e: CUSTOM_ERROR.error(f'{e.__class__.__name__}--飞书推送失败: {e}') if tag.message['mail']: if mail.email: mess_info = { 'workid': self.workId, 'to_user': self.user, 'addr': self.addr_ip, 'text': self.text, 'note': content.before} try: put_mess = send_email.send_email(to_addr=mail.email) put_mess.send_mail(mail_data=mess_info, type=99) except Exception as e: CUSTOM_ERROR.error(f'{e.__class__.__name__}--邮箱推送失败: {e}') class forward_push_messages(threading.Thread): ''' :argument 提交工单调用该方法异步处理数据 ''' def submit(self): ''' :argument 更改该工单SqlOrder表中的status :param self.workId self.user self.addr_ip self.text self.assigned self.id :return: none ''' content = DatabaseList.objects.filter(id=self.id).first() mail = Account.objects.filter(username=self.assigned).first() tag = globalpermissions.objects.filter(authorization='global').first() if tag.message['ding']: if content.url: try: util.dingding( content='工单转发通知\n工单编号:%s\n发起人:%s\n当前审批人:%s\n地址:%s\n工单说明:%s\n状态:已提交\n备注:%s' % (self.workId, self.user,self.assigned, self.addr_ip, self.text, content.before), url=content.url) except Exception as e: CUSTOM_ERROR.error(f'{e.__class__.__name__}--钉钉推送失败: {e}') if tag.message['feishu']: try: user_mail = Account.objects.filter(username=self.assigned).values('email').first() user = {'mail': user_mail.get('email')} fs_send_msg( msg='工单转发通知\n工单编号:%s\n发起人:%s\n当前审批人:%s\n地址:%s\n工单说明:%s\n状态:已提交\n备注:%s' % (self.workId, self.user,self.assigned, self.addr_ip, self.text, content.before),user=user) except Exception as e: CUSTOM_ERROR.error(f'{e.__class__.__name__}--飞书推送失败: {e}') if tag.message['mail']: if mail.email: mess_info = { 'workid': self.workId, 'to_user': self.user, 'addr': self.addr_ip, 'text': self.text, 'note': content.before} try: put_mess = send_email.send_email(to_addr=mail.email) put_mess.send_mail(mail_data=mess_info, type=99) except Exception as e: CUSTOM_ERROR.error(f'{e.__class__.__name__}--邮箱推送失败: {e}')	35.65544	152	0.525612	from __future__ import absolute_import, unicode_literals import logging import functools import threading import time from django.http import HttpResponse from libs import send_email, util from libs import call_inception from .models import ( Usermessage, DatabaseList, Account, globalpermissions, SqlOrder, SqlRecord, grained ) from core.models import Account from core.utils.send_feishu_mess import send_msg as fs_send_msg CUSTOM_ERROR = logging.getLogger('Yearning.core.views') def grained_permissions(func): ''' :argument 装饰器函数,校验细化权限。非法请求直接返回401交由前端判断状态码 ''' @functools.wraps(func) def wrapper(self, request, args=None): if request.method == "PUT" and args != 'connection': return func(self, request, args) else: if request.method == "GET": permissions_type = request.GET.get('permissions_type') else: permissions_type = request.data['permissions_type'] if permissions_type == 'own_space' or permissions_type == 'query': return func(self, request, args) else: user = grained.objects.filter(username=request.user).first() if user is not None and user.permissions[permissions_type] == '1': return func(self, request, args) else: return HttpResponse(status=401) return wrapper class order_push_message(threading.Thread): ''' :argument 同意执行工单调用该方法异步处理数据 ''' def __init__(self, addr_ip, id, from_user, to_user): super().__init__() self.id = id self.addr_ip = addr_ip self.order = SqlOrder.objects.filter(id=id).first() self.from_user = from_user self.to_user = to_user self.title = f'工单:{self.order.work_id}审核通过通知' def run(self): self.execute() self.agreed() def execute(self): ''' :argument 将获得的sql语句提交给inception执行并将返回结果写入SqlRecord表,最后更改该工单SqlOrder表中的status :param self.order self.id :return: none ''' time.sleep(self.order.delay * 60) try: detail = DatabaseList.objects.filter(id=self.order.bundle_id).first() with call_inception.Inception( LoginDic={ 'host': detail.ip, 'user': detail.username, 'password': detail.password, 'db': self.order.basename, 'port': detail.port } ) as f: res = f.Execute(sql=self.order.sql, backup=self.order.backup) for i in res: if i['errlevel'] != 0: SqlOrder.objects.filter(work_id=self.order.work_id).update(status=4) SqlRecord.objects.get_or_create( state=i['stagestatus'], sql=i['sql'], error=i['errormessage'], workid=self.order.work_id, affectrow=i['affected_rows'], sequence=i['sequence'], execute_time=i['execute_time'], SQLSHA1=i['SQLSHA1'], backup_dbname=i['backup_dbname'] ) except Exception as e: CUSTOM_ERROR.error(f'{e.__class__.__name__}--邮箱推送失败: {e}') finally: status = SqlOrder.objects.filter(work_id=self.order.work_id).first() if status.status != 4: SqlOrder.objects.filter(id=self.id).update(status=1) def agreed(self): ''' :argument 将执行的结果通过站内信,email,dingding 发送 :param self.from_user self.to_user self.title self.order self.addr_ip :return: none ''' t = threading.Thread(target=order_push_message.con_close, args=(self,)) t.start() t.join() def con_close(self): Usermessage.objects.get_or_create( from_user=self.from_user, time=util.date(), title=self.title, content='该工单已审核通过!', to_user=self.to_user, state='unread' ) content = DatabaseList.objects.filter(id=self.order.bundle_id).first() mail = Account.objects.filter(username=self.to_user).first() tag = globalpermissions.objects.filter(authorization='global').first() if tag.message['ding']: try: if content.url: util.dingding( content='工单执行通知\n工单编号:%s\n发起人:%s\n审核人:%s\n地址:%s\n工单备注:%s\n状态:已执行\n备注:%s' % ( self.order.work_id, self.order.username,self.order.assigned, self.addr_ip, self.order.text, content.after), url=content.url) except Exception as e: CUSTOM_ERROR.error(f'{e.__class__.__name__}--钉钉推送失败: {e}') if tag.message['feishu']: try: user_mail = Account.objects.filter(username=self.order.username).values('email').first() user = {'mail': user_mail.get('email')} fs_send_msg( msg='工单执行通知\n工单编号:%s\n发起人:%s\n审核人:%s\n地址:%s\n工单备注:%s\n状态:已执行\n备注:%s' % (self.order.work_id, self.order.username,self.order.assigned, self.addr_ip, self.order.text, content.after),user=user) except Exception as e: CUSTOM_ERROR.error(f'{e.__class__.__name__}--飞书推送失败: {e}') if tag.message['mail']: try: if mail.email: mess_info = { 'workid': self.order.work_id, 'to_user': self.order.username, 'addr': self.addr_ip, 'text': self.order.text, 'note': content.after} put_mess = send_email.send_email(to_addr=mail.email) put_mess.send_mail(mail_data=mess_info, type=0) except Exception as e: CUSTOM_ERROR.error(f'{e.__class__.__name__}--邮箱推送失败: {e}') class rejected_push_messages(threading.Thread): ''' :argument 驳回工单调用该方法异步处理数据 ''' def __init__(self, _tmpData, to_user,from_user, addr_ip, text): super().__init__() self.to_user = to_user self._tmpData = _tmpData self.addr_ip = addr_ip self.text = text self.from_user = from_user def run(self): self.execute() def execute(self): ''' :argument 更改该工单SqlOrder表中的status :param self._tmpData self.addr_ip self.text self.to_user :return: none ''' content = DatabaseList.objects.filter(id=self._tmpData['bundle_id']).first() mail = Account.objects.filter(username=self.to_user).first() tag = globalpermissions.objects.filter(authorization='global').first() if tag.message['ding']: try: if content.url: util.dingding( content='工单驳回通知\n工单编号:%s\n发起人:%s\n操作人:%s\n地址:%s\n驳回说明:%s\n状态:驳回' % (self._tmpData['work_id'], self.to_user,self.from_user, self.addr_ip, self.text), url=content.url) except Exception as e: CUSTOM_ERROR.error(f'{e.__class__.__name__}--钉钉推送失败: {e}') if tag.message['feishu']: try: user_mail = Account.objects.filter(username=self.to_user).values('email').first() user = {'mail': user_mail.get('email')} fs_send_msg( msg='工单驳回通知\n工单编号:%s\n发起人:%s\n操作人:%s\n地址:%s\n驳回说明:%s\n状态:驳回' % (self._tmpData['work_id'], self.to_user,self.from_user, self.addr_ip, self.text),user=user) except Exception as e: CUSTOM_ERROR.error(f'{e.__class__.__name__}--飞书推送失败: {e}') if tag.message['mail']: try: if mail.email: mess_info = { 'workid': self._tmpData['work_id'], 'to_user': self.to_user, 'addr': self.addr_ip, 'rejected': self.text} put_mess = send_email.send_email(to_addr=mail.email) put_mess.send_mail(mail_data=mess_info, type=1) except Exception as e: CUSTOM_ERROR.error(f'{e.__class__.__name__}--邮箱推送失败: {e}') class submit_push_messages(threading.Thread): ''' :argument 提交工单调用该方法异步处理数据 ''' def __init__(self, workId, user, addr_ip, text, assigned, id): super().__init__() self.workId = workId self.user = user self.addr_ip = addr_ip self.text = text self.assigned = assigned self.id = id def run(self): self.submit() def submit(self): ''' :argument 更改该工单SqlOrder表中的status :param self.workId self.user self.addr_ip self.text self.assigned self.id :return: none ''' content = DatabaseList.objects.filter(id=self.id).first() mail = Account.objects.filter(username=self.assigned).first() tag = globalpermissions.objects.filter(authorization='global').first() if tag.message['ding']: if content.url: try: util.dingding( content='工单提交通知\n工单编号:%s\n发起人:%s\n审批人:%s\n地址:%s\n工单说明:%s\n状态:已提交\n备注:%s' % (self.workId, self.user,self.assigned, self.addr_ip, self.text, content.before), url=content.url) except Exception as e: CUSTOM_ERROR.error(f'{e.__class__.__name__}--钉钉推送失败: {e}') if tag.message['feishu']: try: user_mail = Account.objects.filter(username=self.assigned).values('email').first() user = {'mail': user_mail.get('email')} fs_send_msg( msg='工单提交通知\n工单编号:%s\n发起人:%s\n审批人:%s\n地址:%s\n工单说明:%s\n状态:已提交\n备注:%s' % (self.workId, self.user,self.assigned, self.addr_ip, self.text, content.before),user=user) except Exception as e: CUSTOM_ERROR.error(f'{e.__class__.__name__}--飞书推送失败: {e}') if tag.message['mail']: if mail.email: mess_info = { 'workid': self.workId, 'to_user': self.user, 'addr': self.addr_ip, 'text': self.text, 'note': content.before} try: put_mess = send_email.send_email(to_addr=mail.email) put_mess.send_mail(mail_data=mess_info, type=99) except Exception as e: CUSTOM_ERROR.error(f'{e.__class__.__name__}--邮箱推送失败: {e}') class forward_push_messages(threading.Thread): ''' :argument 提交工单调用该方法异步处理数据 ''' def __init__(self, workId, user, addr_ip, text, assigned, id): super().__init__() self.workId = workId self.user = user self.addr_ip = addr_ip self.text = text self.assigned = assigned self.id = id def run(self): self.submit() def submit(self): ''' :argument 更改该工单SqlOrder表中的status :param self.workId self.user self.addr_ip self.text self.assigned self.id :return: none ''' content = DatabaseList.objects.filter(id=self.id).first() mail = Account.objects.filter(username=self.assigned).first() tag = globalpermissions.objects.filter(authorization='global').first() if tag.message['ding']: if content.url: try: util.dingding( content='工单转发通知\n工单编号:%s\n发起人:%s\n当前审批人:%s\n地址:%s\n工单说明:%s\n状态:已提交\n备注:%s' % (self.workId, self.user,self.assigned, self.addr_ip, self.text, content.before), url=content.url) except Exception as e: CUSTOM_ERROR.error(f'{e.__class__.__name__}--钉钉推送失败: {e}') if tag.message['feishu']: try: user_mail = Account.objects.filter(username=self.assigned).values('email').first() user = {'mail': user_mail.get('email')} fs_send_msg( msg='工单转发通知\n工单编号:%s\n发起人:%s\n当前审批人:%s\n地址:%s\n工单说明:%s\n状态:已提交\n备注:%s' % (self.workId, self.user,self.assigned, self.addr_ip, self.text, content.before),user=user) except Exception as e: CUSTOM_ERROR.error(f'{e.__class__.__name__}--飞书推送失败: {e}') if tag.message['mail']: if mail.email: mess_info = { 'workid': self.workId, 'to_user': self.user, 'addr': self.addr_ip, 'text': self.text, 'note': content.before} try: put_mess = send_email.send_email(to_addr=mail.email) put_mess.send_mail(mail_data=mess_info, type=99) except Exception as e: CUSTOM_ERROR.error(f'{e.__class__.__name__}--邮箱推送失败: {e}')	4,202	0	269
eac6a981fadd003fa43c9af833b6effbf17649fc	2,000	py	Python	snapshotcleanup/snapshotcleanup.py	meredith-digops/awsops	d3e4dc3d16866a95550602b924f97dc5c0c77642	[ "MIT" ]	4	2017-11-29T08:15:45.000Z	2020-03-23T18:43:10.000Z	snapshotcleanup/snapshotcleanup.py	meredith-digops/awsops	d3e4dc3d16866a95550602b924f97dc5c0c77642	[ "MIT" ]	6	2016-09-26T21:01:14.000Z	2021-05-03T13:33:31.000Z	snapshotcleanup/snapshotcleanup.py	meredith-digops/awsops	d3e4dc3d16866a95550602b924f97dc5c0c77642	[ "MIT" ]	5	2016-09-26T14:26:22.000Z	2018-01-26T00:38:01.000Z	#!/usr/bin/env python from __future__ import print_function from datetime import datetime, timedelta, tzinfo import boto3 from botocore.exceptions import ClientError DEFAULT_RETENTION_DAYS = None """If None, no default retention is applied""" ZERO = timedelta(0) class UTC(tzinfo): """ Implements UTC timezone for datetime interaction """ def get_snapshots(ec2, filters, retention): """ Generator of snapshots that exceed retention policy. """ for snapshot in ec2.snapshots.filter(Filters=filters): # If the retention is specified in a tag override the default if snapshot.tags: for tag in snapshot.tags: if tag['Key'] == 'ops:retention': retention = int(tag['Value']) utc = UTC() if retention and \ snapshot.start_time < (datetime.now(utc) - timedelta(days=retention)): yield snapshot def lambda_handler(event, context): """ Delete EBS snapshots that exceed retention policy. """ if not 'DryRun' in event: event['DryRun'] = False if not 'Filters' in event: event['Filters'] = [{ 'Name': 'tag-key', 'Values': [ 'ops:retention' ] }] # Set the default retention period if none was provided to the lambda # invocation if not 'Retention' in event: event['Retention'] = DEFAULT_RETENTION_DAYS ec2 = boto3.resource('ec2') snapshots = get_snapshots(ec2, filters=event['Filters'], retention=event['Retention']) for snapshot in snapshots: print('Deleting: %s' % snapshot) try: snapshot.delete(DryRun=event['DryRun']) except ClientError as e: if e.response['Error']['Code'] == 'DryRunOperation': pass	25.316456	86	0.595	#!/usr/bin/env python from __future__ import print_function from datetime import datetime, timedelta, tzinfo import boto3 from botocore.exceptions import ClientError DEFAULT_RETENTION_DAYS = None """If None, no default retention is applied""" ZERO = timedelta(0) class UTC(tzinfo): """ Implements UTC timezone for datetime interaction """ def utcoffset(self, dt): return ZERO def tzname(self, dt): return "UTC" def dst(self, dt): return ZERO def get_snapshots(ec2, filters, retention): """ Generator of snapshots that exceed retention policy. """ for snapshot in ec2.snapshots.filter(Filters=filters): # If the retention is specified in a tag override the default if snapshot.tags: for tag in snapshot.tags: if tag['Key'] == 'ops:retention': retention = int(tag['Value']) utc = UTC() if retention and \ snapshot.start_time < (datetime.now(utc) - timedelta(days=retention)): yield snapshot def lambda_handler(event, context): """ Delete EBS snapshots that exceed retention policy. """ if not 'DryRun' in event: event['DryRun'] = False if not 'Filters' in event: event['Filters'] = [{ 'Name': 'tag-key', 'Values': [ 'ops:retention' ] }] # Set the default retention period if none was provided to the lambda # invocation if not 'Retention' in event: event['Retention'] = DEFAULT_RETENTION_DAYS ec2 = boto3.resource('ec2') snapshots = get_snapshots(ec2, filters=event['Filters'], retention=event['Retention']) for snapshot in snapshots: print('Deleting: %s' % snapshot) try: snapshot.delete(DryRun=event['DryRun']) except ClientError as e: if e.response['Error']['Code'] == 'DryRunOperation': pass	61	0	80
1b7a12539a5910e5b2156704a5c7a96622ee4933	6,698	py	Python	lib/threatminer.py	macdaliot/exist	65244f79c602c5a00c3ea6a7eef512ce9c21e60a	[ "MIT" ]	159	2019-03-15T10:46:19.000Z	2022-03-12T09:19:31.000Z	lib/threatminer.py	macdaliot/exist	65244f79c602c5a00c3ea6a7eef512ce9c21e60a	[ "MIT" ]	6	2019-03-16T12:51:24.000Z	2020-07-09T02:25:42.000Z	lib/threatminer.py	macdaliot/exist	65244f79c602c5a00c3ea6a7eef512ce9c21e60a	[ "MIT" ]	36	2019-03-16T10:37:14.000Z	2021-11-14T21:04:18.000Z	#!/usr/bin/env python import argparse import requests try: import simplejson as json except ImportError: import json version = '%(prog)s 20180912' ### From Domain ### From IP address ### From Sample ### From AV ### From Report ### Search APINotes if __name__ == '__main__': if ArgParse().type == 'domain': print(json.dumps(ThreatMiner().getURIFromDomain(ArgParse().resource))) print(json.dumps(ThreatMiner().getSamplesFromDomain(ArgParse().resource))) print(json.dumps(ThreatMiner().getSubdomainsFromDomain(ArgParse().resource))) print(json.dumps(ThreatMiner().getReportFromDomain(ArgParse().resource))) elif ArgParse().type == 'ip': print(json.dumps(ThreatMiner().getURIFromIP(ArgParse().resource))) print(json.dumps(ThreatMiner().getSamplesFromIP(ArgParse().resource))) print(json.dumps(ThreatMiner().getReportFromIP(ArgParse().resource))) elif ArgParse().type == 'hash': print(json.dumps(ThreatMiner().getMetaFromSample(ArgParse().resource))) print(json.dumps(ThreatMiner().getHttpFromSample(ArgParse().resource))) print(json.dumps(ThreatMiner().getHostsFromSample(ArgParse().resource))) print(json.dumps(ThreatMiner().getMutantsFromSample(ArgParse().resource))) print(json.dumps(ThreatMiner().getRegistryFromSample(ArgParse().resource))) print(json.dumps(ThreatMiner().getAVFromSample(ArgParse().resource))) print(json.dumps(ThreatMiner().getReportFromSample(ArgParse().resource))) elif ArgParse().type == 'av': print(json.dumps(ThreatMiner().getSamplesFromAV(ArgParse().resource))) print(json.dumps(ThreatMiner().getReportFromAV(ArgParse().resource))) elif ArgParse().type == 'report': print(json.dumps(ThreatMiner().getDomainFromReport(ArgParse().resource))) print(json.dumps(ThreatMiner().getHostsFromReport(ArgParse().resource))) print(json.dumps(ThreatMiner().getEmailFromReport(ArgParse().resource))) print(json.dumps(ThreatMiner().getSamplesFromReport(ArgParse().resource))) elif ArgParse().type == 'keyword': print(json.dumps(ThreatMiner().getReportFromKeyword(ArgParse().resource))) elif ArgParse().type == 'year': print(json.dumps(ThreatMiner().getReportFromYear(ArgParse().resource)))	31.744076	115	0.615557	#!/usr/bin/env python import argparse import requests try: import simplejson as json except ImportError: import json version = '%(prog)s 20180912' class ThreatMiner(): def __init__(self): self.__baseURL = "https://api.threatminer.org/v2/" def sendQuery(self, endpoint, rt, q): params = { 'rt': rt, 'q': q, } url = self.__baseURL + endpoint try: res = requests.get(url, params=params) except Exception as e: return e res_dict = json.loads(res.text) return res_dict ### From Domain def getURIFromDomain(self, q): rt = 3 endpoint = "domain.php" result = self.sendQuery(endpoint, rt, q) return result def getSamplesFromDomain(self, q): rt = 4 endpoint = "domain.php" result = self.sendQuery(endpoint, rt, q) return result def getSubdomainsFromDomain(self, q): rt = 5 endpoint = "domain.php" result = self.sendQuery(endpoint, rt, q) return result def getReportFromDomain(self, q): rt = 6 endpoint = "domain.php" result = self.sendQuery(endpoint, rt, q) return result ### From IP address def getURIFromIP(self, q): rt = 3 endpoint = "host.php" result = self.sendQuery(endpoint, rt, q) return result def getSamplesFromIP(self, q): rt = 4 endpoint = "host.php" result = self.sendQuery(endpoint, rt, q) return result def getReportFromIP(self, q): rt = 6 endpoint = "host.php" result = self.sendQuery(endpoint, rt, q) return result ### From Sample def getMetaFromSample(self, q): rt = 1 endpoint = "sample.php" result = self.sendQuery(endpoint, rt, q) return result def getHttpFromSample(self, q): rt = 2 endpoint = "sample.php" result = self.sendQuery(endpoint, rt, q) return result def getHostsFromSample(self, q): rt = 3 endpoint = "sample.php" result = self.sendQuery(endpoint, rt, q) return result def getMutantsFromSample(self, q): rt = 4 endpoint = "sample.php" result = self.sendQuery(endpoint, rt, q) return result def getRegistryFromSample(self, q): rt = 5 endpoint = "sample.php" result = self.sendQuery(endpoint, rt, q) return result def getAVFromSample(self, q): rt = 6 endpoint = "sample.php" result = self.sendQuery(endpoint, rt, q) return result def getReportFromSample(self, q): rt = 7 endpoint = "sample.php" result = self.sendQuery(endpoint, rt, q) return result ### From AV def getSamplesFromAV(self, q): rt = 1 endpoint = "av.php" result = self.sendQuery(endpoint, rt, q) return result def getReportFromAV(self, q): rt = 2 endpoint = "av.php" result = self.sendQuery(endpoint, rt, q) return result ### From Report def getDomainFromReport(self, q): rt = 1 endpoint = "report.php" result = self.sendQuery(endpoint, rt, q) return result def getHostsFromReport(self, q): rt = 2 endpoint = "report.php" result = self.sendQuery(endpoint, rt, q) return result def getEmailFromReport(self, q): rt = 3 endpoint = "report.php" result = self.sendQuery(endpoint, rt, q) return result def getSamplesFromReport(self, q): rt = 4 endpoint = "report.php" result = self.sendQuery(endpoint, rt, q) return result ### Search APINotes def getReportFromKeyword(self, q): rt = 1 endpoint = "reports.php" result = self.sendQuery(endpoint, rt, q) return result def getReportFromYear(self, q): rt = 2 endpoint = "reports.php" result = self.sendQuery(endpoint, rt, q) return result def ArgParse(): parser = argparse.ArgumentParser(description= '''This script get report from ThreatMiner. ''', formatter_class=argparse.RawDescriptionHelpFormatter) parser.add_argument('type', action='store', type=str, help='domain / ip / hash / av / report / keyword / year') parser.add_argument('resource', action='store', type=str, help='resource') parser.add_argument('-v', '--version', action='version', version=version) args = parser.parse_args() return args if __name__ == '__main__': if ArgParse().type == 'domain': print(json.dumps(ThreatMiner().getURIFromDomain(ArgParse().resource))) print(json.dumps(ThreatMiner().getSamplesFromDomain(ArgParse().resource))) print(json.dumps(ThreatMiner().getSubdomainsFromDomain(ArgParse().resource))) print(json.dumps(ThreatMiner().getReportFromDomain(ArgParse().resource))) elif ArgParse().type == 'ip': print(json.dumps(ThreatMiner().getURIFromIP(ArgParse().resource))) print(json.dumps(ThreatMiner().getSamplesFromIP(ArgParse().resource))) print(json.dumps(ThreatMiner().getReportFromIP(ArgParse().resource))) elif ArgParse().type == 'hash': print(json.dumps(ThreatMiner().getMetaFromSample(ArgParse().resource))) print(json.dumps(ThreatMiner().getHttpFromSample(ArgParse().resource))) print(json.dumps(ThreatMiner().getHostsFromSample(ArgParse().resource))) print(json.dumps(ThreatMiner().getMutantsFromSample(ArgParse().resource))) print(json.dumps(ThreatMiner().getRegistryFromSample(ArgParse().resource))) print(json.dumps(ThreatMiner().getAVFromSample(ArgParse().resource))) print(json.dumps(ThreatMiner().getReportFromSample(ArgParse().resource))) elif ArgParse().type == 'av': print(json.dumps(ThreatMiner().getSamplesFromAV(ArgParse().resource))) print(json.dumps(ThreatMiner().getReportFromAV(ArgParse().resource))) elif ArgParse().type == 'report': print(json.dumps(ThreatMiner().getDomainFromReport(ArgParse().resource))) print(json.dumps(ThreatMiner().getHostsFromReport(ArgParse().resource))) print(json.dumps(ThreatMiner().getEmailFromReport(ArgParse().resource))) print(json.dumps(ThreatMiner().getSamplesFromReport(ArgParse().resource))) elif ArgParse().type == 'keyword': print(json.dumps(ThreatMiner().getReportFromKeyword(ArgParse().resource))) elif ArgParse().type == 'year': print(json.dumps(ThreatMiner().getReportFromYear(ArgParse().resource)))	3,665	-1	687
da4b158d8c736ac7723e882f97e8bcedc90b1567	3,541	py	Python	sym_api_client_python/clients/connections_client.py	symphony-thibault/symphony-api-client-python	628cbf3aa857d3bc66a98a3ec009ce1c82295d05	[ "MIT" ]	null	null	null	sym_api_client_python/clients/connections_client.py	symphony-thibault/symphony-api-client-python	628cbf3aa857d3bc66a98a3ec009ce1c82295d05	[ "MIT" ]	null	null	null	sym_api_client_python/clients/connections_client.py	symphony-thibault/symphony-api-client-python	628cbf3aa857d3bc66a98a3ec009ce1c82295d05	[ "MIT" ]	null	null	null	import logging from .api_client import APIClient # child class of APIClient --> Extends error handling functionality # ConnectionsClient class contains a series of functions corresponding to all # pod admin endpoints on the REST API.	42.154762	80	0.674386	import logging from .api_client import APIClient # child class of APIClient --> Extends error handling functionality # ConnectionsClient class contains a series of functions corresponding to all # pod admin endpoints on the REST API. class ConnectionsClient(APIClient): def __init__(self, bot_client): self.bot_client = bot_client def create_connection(self, user_id): """ Pods from all users involved need to have crossPod enabled between them. Users who belong to the same private pod are implicitly connected. If you attempt to connect with an internal user, this endpoint will return the corresponding connection object with a status of accepted """ logging.debug('ConnectionsClient/create_connection()') url = '/pod/v1/connection/create' data = {'userId': user_id} return self.bot_client.execute_rest_call('POST', url, json=data) def get_connection(self, user_id): """ When calling this as an OBO-enabled endpoint, use the OBO User Authenticate token for sessionToken """ logging.debug('ConnectionsClient/get_connection()') url = '/pod/v1/connection/user/{0}/info'.format(user_id) return self.bot_client.execute_rest_call('GET', url) def list_connections(self, status, **kwargs): """ This retrieves all connections of the requesting user. (i.e. both connections in which the requesting user is the sender and those in which the requesting user is the inivtee). By default, if you haven't specified the connection status to filter on, this call will only return results for both "pending_incoming" and "pending_outgoing". """ logging.debug('ConnectionsClient/list_connections()') url = '/pod/v1/connection/list' params = {'status' : status} return self.bot_client.execute_rest_call('GET', url, params=params) def accept_connection(self, user_id): """ This allows the user to accept a specific connection request. For users of the same private pod who are implicitly connected, this endpoint returns the connection with status of "Accepted". """ logging.debug('ConnectionsClient/accept_connection()') url = '/pod/v1/connection/accept' data = {'userId': user_id} return self.bot_client.execute_rest_call('POST', url, json=data) def reject_connection(self, user_id): """ This allows the user to reject a specific connection request. Reject the connection between the requesting user and request sender. If both users are in the same private pod, an error will be returned because both users have an implicit connection which cannot be rejected. """ logging.debug('ConnectionsClient/reject_connection()') url = '/pod/v1/connection/reject' data = {'userId': user_id} return self.bot_client.execute_rest_call('POST', url, json=data) def remove_connection(self, user_id): """ Removes a connection with a user. This endpoint returns 400 Bad Request when the users aren't connected. For example, when a user hasn’t yet accepted a connection request from another user. """ logging.debug('ConnectionsClient/remove_connection()') url = '/pod/v1/connection/user/{0}/remove'.format(user_id) return self.bot_client.execute_rest_call('POST', url)	47	3,236	22
16b08766cb370edf52b3d39c46180b630ddb5f0e	1,405	py	Python	server/services/weather.py	vipul0104/logistics-wizard-controller	bd2470a5847310fe0c7bccadf6179dd7bb866de0	[ "Apache-2.0" ]	null	null	null	server/services/weather.py	vipul0104/logistics-wizard-controller	bd2470a5847310fe0c7bccadf6179dd7bb866de0	[ "Apache-2.0" ]	5	2018-06-25T16:12:07.000Z	2019-11-08T21:47:47.000Z	server/services/weather.py	vipul0104/logistics-wizard-controller	bd2470a5847310fe0c7bccadf6179dd7bb866de0	[ "Apache-2.0" ]	1	2019-11-03T20:40:02.000Z	2019-11-03T20:40:02.000Z	""" Handle all actions on the weather resource. """ import json import requests from server.utils import call_openwhisk from server.exceptions import ResourceDoesNotExistException, APIException def get_recommendations(demoGuid): """ Get recommendations """ try: payload = dict() payload['demoGuid'] = demoGuid response = call_openwhisk('retrieve', payload) except Exception as e: raise APIException('KO', internal_details=str(e)) return response def acknowledge_recommendation(demoGuid, recommendationId): """ Acknowledge the given recommendation """ try: payload = dict() payload['demoGuid'] = demoGuid payload['recommendationId'] = recommendationId response = call_openwhisk('acknowledge', payload) except Exception as e: raise APIException('KO', internal_details=str(e)) return response def trigger_simulation(demoGuid): """ Trigger a simulation in the given demo Creates a Snow Storm in the DC area """ try: payload = dict() payload['demoGuid'] = demoGuid event = dict() event = json.loads(open('./sample_event.json').read()) payload['event'] = event response = call_openwhisk('recommend', payload) except Exception as e: raise APIException('KO', internal_details=str(e)) return response	25.545455	73	0.659786	""" Handle all actions on the weather resource. """ import json import requests from server.utils import call_openwhisk from server.exceptions import ResourceDoesNotExistException, APIException def get_recommendations(demoGuid): """ Get recommendations """ try: payload = dict() payload['demoGuid'] = demoGuid response = call_openwhisk('retrieve', payload) except Exception as e: raise APIException('KO', internal_details=str(e)) return response def acknowledge_recommendation(demoGuid, recommendationId): """ Acknowledge the given recommendation """ try: payload = dict() payload['demoGuid'] = demoGuid payload['recommendationId'] = recommendationId response = call_openwhisk('acknowledge', payload) except Exception as e: raise APIException('KO', internal_details=str(e)) return response def trigger_simulation(demoGuid): """ Trigger a simulation in the given demo Creates a Snow Storm in the DC area """ try: payload = dict() payload['demoGuid'] = demoGuid event = dict() event = json.loads(open('./sample_event.json').read()) payload['event'] = event response = call_openwhisk('recommend', payload) except Exception as e: raise APIException('KO', internal_details=str(e)) return response	0	0	0
d351744e79c3ee2c12d9ec03d2736c0dbd0359f3	7,788	py	Python	utils/gdb-printers/csd.py	kjcamann/csd-mirror	e0808cdb084404fc7319c76186c05eba0a56b056	[ "BSD-2-Clause" ]	null	null	null	utils/gdb-printers/csd.py	kjcamann/csd-mirror	e0808cdb084404fc7319c76186c05eba0a56b056	[ "BSD-2-Clause" ]	null	null	null	utils/gdb-printers/csd.py	kjcamann/csd-mirror	e0808cdb084404fc7319c76186c05eba0a56b056	[ "BSD-2-Clause" ]	null	null	null	"""GDB pretty-printers for CSD. """ import enum import gdb import gdb.xmethod import re _csd_printer_name = 'csd_pretty_printer' _csd_xmethod_name = 'csd_xmethods' _nttpIntegralSuffix = { 'long' : 'l', 'long long' : 'll', 'unsigned int' : 'u', 'unsigned long' : 'ul', 'unsigned long long' : 'ull' } def _get_entry_extractor_typename(ty): """Return the adjusted typename of an entry extractor for the purpose of performing symbol lookups. offset_extractor takes, as its third argument, a non-type template parameter of type `std::size_t`. When gcc prints the NTTP argument, it prints it as just a number, e.g., "8". In the symbol name, however, it must appear as something like "8ul" (unsigned long) because the symbol must encode the type according to the ABI rules. """ templateName = _remove_generics(ty.strip_typedefs().name) if templateName != 'csg::offset_extractor': return ty.strip_typedefs().name offset = ty.template_argument(2) assert type(offset) is gdb.Value, 'offset_extractor template arg 2 not an NTTP?' suffix = _nttpIntegralSuffix.get(offset.type.name, None) fixedOffset = f'{offset}{suffix}' if suffix else str(offset) return f'csg::offset_extractor<{ty.template_argument(0)}, ' \ f'{ty.template_argument(1)}, {fixedOffset}>' def _lookup_entry_ref_codec_functions(elementTy, entryTy, entryExTy, entryRefUnionTy): """To iterate over CSD lists in the debugger, we need access to the functions entry_ref_codec<...>::get_entry and entry_ref_codec<...>::get_value, which are looked up using this helper. """ entryExTyName = _get_entry_extractor_typename(entryExTy) entryRefCodecClassName = \ f'csg::detail::entry_ref_codec<{entryTy}, {elementTy}, {entryExTyName}>' def lookupEntryRefCodecSymbol(fnName): """Look up symbol for entry_ref_codec<...> static member functions.""" symName = f'{entryRefCodecClassName}::{fnName}' sym, _ = gdb.lookup_symbol(symName) if not sym or not sym.is_function: raise Exception(f'required symbol {symName} does not exist or is not a function') return sym getEntryFnName = f'get_entry({entryExTyName} &, {entryRefUnionTy})' getEntrySym = lookupEntryRefCodecSymbol(getEntryFnName) getValueFnName = f'get_value({entryRefUnionTy})' getValueSym = lookupEntryRefCodecSymbol(getValueFnName) return getEntrySym.value(), getValueSym.value() class EntryRefPrinter: """Printer for csg::entry_ref_union<EntryType, T>""" class ListPrinter: """Printer for all CSD list types.""" def register_csd_pretty_printers(): """Register event handlers to load csd pretty-printers.""" gdb.events.new_objfile.connect(_register_csd_printers) gdb.events.clear_objfiles.connect(_unregister_csd_printers)	35.081081	87	0.699666	"""GDB pretty-printers for CSD. """ import enum import gdb import gdb.xmethod import re _csd_printer_name = 'csd_pretty_printer' _csd_xmethod_name = 'csd_xmethods' def _remove_generics(typename): if type(typename) is gdb.Type: typename = typename.name or typename.tag or str(typename) match = re.match('^([^<]+)', typename) return match.group(1) _nttpIntegralSuffix = { 'long' : 'l', 'long long' : 'll', 'unsigned int' : 'u', 'unsigned long' : 'ul', 'unsigned long long' : 'ull' } def _get_entry_extractor_typename(ty): """Return the adjusted typename of an entry extractor for the purpose of performing symbol lookups. offset_extractor takes, as its third argument, a non-type template parameter of type `std::size_t`. When gcc prints the NTTP argument, it prints it as just a number, e.g., "8". In the symbol name, however, it must appear as something like "8ul" (unsigned long) because the symbol must encode the type according to the ABI rules. """ templateName = _remove_generics(ty.strip_typedefs().name) if templateName != 'csg::offset_extractor': return ty.strip_typedefs().name offset = ty.template_argument(2) assert type(offset) is gdb.Value, 'offset_extractor template arg 2 not an NTTP?' suffix = _nttpIntegralSuffix.get(offset.type.name, None) fixedOffset = f'{offset}{suffix}' if suffix else str(offset) return f'csg::offset_extractor<{ty.template_argument(0)}, ' \ f'{ty.template_argument(1)}, {fixedOffset}>' def _lookup_entry_ref_codec_functions(elementTy, entryTy, entryExTy, entryRefUnionTy): """To iterate over CSD lists in the debugger, we need access to the functions entry_ref_codec<...>::get_entry and entry_ref_codec<...>::get_value, which are looked up using this helper. """ entryExTyName = _get_entry_extractor_typename(entryExTy) entryRefCodecClassName = \ f'csg::detail::entry_ref_codec<{entryTy}, {elementTy}, {entryExTyName}>' def lookupEntryRefCodecSymbol(fnName): """Look up symbol for entry_ref_codec<...> static member functions.""" symName = f'{entryRefCodecClassName}::{fnName}' sym, _ = gdb.lookup_symbol(symName) if not sym or not sym.is_function: raise Exception(f'required symbol {symName} does not exist or is not a function') return sym getEntryFnName = f'get_entry({entryExTyName} &, {entryRefUnionTy})' getEntrySym = lookupEntryRefCodecSymbol(getEntryFnName) getValueFnName = f'get_value({entryRefUnionTy})' getValueSym = lookupEntryRefCodecSymbol(getValueFnName) return getEntrySym.value(), getValueSym.value() class EntryRefPrinter: """Printer for csg::entry_ref_union<EntryType, T>""" def __init__(self, value): self.value = value self.addrVal = self.value['offset']['m_address'] if int(self.addrVal) & 0x1: # A tagged address; this means we're pointing at a T value. ptrType = self.value.type.template_argument(1).pointer() self.childValue = (self.addrVal - 1).cast(ptrType) self.label = str(ptrType) else: # An untagged address; this means we're pointing directly an entry_type<T> ptrType = self.value.type.template_argument(0).pointer() self.childValue = self.addrVal.cast(ptrType) self.label = str(ptrType) def children(self): yield self.label, self.childValue class ListPrinter: """Printer for all CSD list types.""" class ListIterator: def __init__(self, nextEntryRef, entryEx, getEntryFn, getValueFn, stopEntryRefValue): self.nextEntryRef = nextEntryRef self.entryEx = entryEx self.getEntryFn = getEntryFn self.getValueFn = getValueFn self.count = 0 self.stopEntryRefValue = stopEntryRefValue def __iter__(self): return self def __next__(self): self.count += 1 if self.isFinished(): raise StopIteration item = self.getValueFn(self.nextEntryRef).referenced_value() curEntry = self.getEntryFn(self.entryEx, self.nextEntryRef).dereference() self.nextEntryRef = curEntry['next'] return f'[{self.count}]', item def isFinished(self): return int(self.nextEntryRef['offset']['m_address']) == self.stopEntryRefValue def __init__(self, value): self.value = value self.entryEx = self.value['m_entryExtractor'] qualListTyName = _remove_generics(value.type.strip_typedefs()) assert qualListTyName.startswith('csg::') self.listTyName = qualListTyName[5:] self.isProxy = self.listTyName.endswith('_proxy') self.isTailQ = self.listTyName.startswith('tailq_') self.fwdHead = self.value['m_head'] if self.isProxy: self.fwdHead = self.fwdHead.referenced_value() listHeadEntry = self.fwdHead['m_endEntry'] if self.isTailQ else \ self.fwdHead['m_headEntry'] stopEntryRefValue = int(listHeadEntry.address) if self.isTailQ else 0 firstEntryRef = listHeadEntry['next'] baseCls = self.value.type.fields()[0].type entryRefUnionTy = firstEntryRef.type self.elementTy = baseCls.template_argument(0) self.entryTy = entryRefUnionTy.template_argument(0) self.entryExTy = self.entryEx.type.strip_typedefs() getEntryFn, getValueFn = \ _lookup_entry_ref_codec_functions(self.elementTy, self.entryTy, self.entryExTy, entryRefUnionTy) self.iterator = self.ListIterator(firstEntryRef, self.entryEx, getEntryFn, getValueFn, stopEntryRefValue) def to_string(self): desc = f'csg::{self.listTyName} of {self.elementTy}' size = self.fwdHead['m_sz'] if size.type.code == gdb.TYPE_CODE_INT: desc += f', size = {size}' elif self.iterator.isFinished(): desc += " (empty)" if self.entryEx.type.fields(): entryExTyName = self.entryEx.type.strip_typedefs() desc += f', extractor {entryExTyName} = {self.entryEx}' return desc def children(self): return self.iterator def display_hint(self): return 'array' class CSDPrettyPrinter: def __init__(self, name): self.name = name self.enabled = True self.lookup = { 'slist_head' : ListPrinter, 'slist_proxy' : ListPrinter, 'stailq_head' : ListPrinter, 'stailq_proxy' : ListPrinter, 'tailq_head' : ListPrinter, 'tailq_proxy' : ListPrinter, 'entry_ref_union' : EntryRefPrinter, } def __call__(self, value): """Return the pretty printer for a gdb.Value""" canonType = value.type.strip_typedefs() if canonType.code not in (gdb.TYPE_CODE_STRUCT, gdb.TYPE_CODE_UNION): return None typename = canonType.name or canonType.tag or str(canonType) if not typename.startswith('csg::'): return None baseName = _remove_generics(typename[5:]) printer = self.lookup.get(baseName, None) return printer(value) if printer else None def _register_csd_printers(event): progspace = event.new_objfile.progspace if not getattr(progspace, _csd_printer_name, False): print("Loading csd pretty-printers") gdb.printing.register_pretty_printer(progspace, CSDPrettyPrinter(_csd_printer_name)) setattr(progspace, _csd_printer_name, True) def _unregister_csd_printers(event): progspace = event.progspace if getattr(progspace, _csd_printer_name, False): for printer in progspace.pretty_printers: if getattr(printer, "name", "none") == _csd_printer_name: progspace.pretty_printers.remove(printer) setattr(progspace, _csd_printer_name, False) break def register_csd_pretty_printers(): """Register event handlers to load csd pretty-printers.""" gdb.events.new_objfile.connect(_register_csd_printers) gdb.events.clear_objfiles.connect(_unregister_csd_printers)	4,118	508	372
a6c66342d24401cf2bf73506e53eb58aa58133e0	1,222	py	Python	nets/attention/position_encoding.py	megvii-research/CREStereo	fce504591fbb0eb29642235544f1aaecd1198526	[ "Apache-2.0" ]	80	2022-03-22T06:32:47.000Z	2022-03-31T21:53:07.000Z	nets/attention/position_encoding.py	megvii-research/CREStereo	fce504591fbb0eb29642235544f1aaecd1198526	[ "Apache-2.0" ]	3	2022-03-24T06:10:27.000Z	2022-03-31T06:03:51.000Z	nets/attention/position_encoding.py	megvii-research/CREStereo	fce504591fbb0eb29642235544f1aaecd1198526	[ "Apache-2.0" ]	6	2022-03-23T08:15:58.000Z	2022-03-29T12:07:52.000Z	import math import megengine.module as M import megengine.functional as F class PositionEncodingSine(M.Module): """ This is a sinusoidal position encoding that generalized to 2-dimensional images """ def __init__(self, d_model, max_shape=(256, 256)): """ Args: max_shape (tuple): for 1/8 featmap, the max length of 256 corresponds to 2048 pixels """ super().__init__() pe = F.zeros((d_model, max_shape)) y_position = F.expand_dims(F.cumsum(F.ones(max_shape), 0), 0) x_position = F.expand_dims(F.cumsum(F.ones(max_shape), 1), 0) div_term = F.exp( F.arange(0, d_model // 2, 2) (-math.log(10000.0) / d_model // 2) ) div_term = F.expand_dims(div_term, (1, 2)) # [C//4, 1, 1] pe[0::4, :, :] = F.sin(x_position * div_term) pe[1::4, :, :] = F.cos(x_position * div_term) pe[2::4, :, :] = F.sin(y_position * div_term) pe[3::4, :, :] = F.cos(y_position * div_term) self.pe = F.expand_dims(pe, 0) def forward(self, x): """ Args: x: [N, C, H, W] """ return x + self.pe[:, :, : x.shape[2], : x.shape[3]].to(x.device)	32.157895	96	0.54419	import math import megengine.module as M import megengine.functional as F class PositionEncodingSine(M.Module): """ This is a sinusoidal position encoding that generalized to 2-dimensional images """ def __init__(self, d_model, max_shape=(256, 256)): """ Args: max_shape (tuple): for 1/8 featmap, the max length of 256 corresponds to 2048 pixels """ super().__init__() pe = F.zeros((d_model, max_shape)) y_position = F.expand_dims(F.cumsum(F.ones(max_shape), 0), 0) x_position = F.expand_dims(F.cumsum(F.ones(max_shape), 1), 0) div_term = F.exp( F.arange(0, d_model // 2, 2) (-math.log(10000.0) / d_model // 2) ) div_term = F.expand_dims(div_term, (1, 2)) # [C//4, 1, 1] pe[0::4, :, :] = F.sin(x_position * div_term) pe[1::4, :, :] = F.cos(x_position * div_term) pe[2::4, :, :] = F.sin(y_position * div_term) pe[3::4, :, :] = F.cos(y_position * div_term) self.pe = F.expand_dims(pe, 0) def forward(self, x): """ Args: x: [N, C, H, W] """ return x + self.pe[:, :, : x.shape[2], : x.shape[3]].to(x.device)	0	0	0
4a7bae05fad6d3a7ae3e34b5e332150a92ca6ee7	3,744	py	Python	data-science-not/weeks/m03_sequences/p0/stack.py	nurseiit/comm-unist	e7a122c910bf12eddf5c0ffc2c666995b4989408	[ "MIT" ]	4	2019-07-03T00:57:01.000Z	2020-12-11T23:06:11.000Z	data-science-not/weeks/m03_sequences/p0/stack.py	nurseiit/comm-unist	e7a122c910bf12eddf5c0ffc2c666995b4989408	[ "MIT" ]	1	2019-10-19T17:42:42.000Z	2019-10-19T17:42:42.000Z	data-science-not/weeks/m03_sequences/p0/stack.py	nurseiit/comm-unist	e7a122c910bf12eddf5c0ffc2c666995b4989408	[ "MIT" ]	1	2019-11-05T04:14:08.000Z	2019-11-05T04:14:08.000Z	# Copyright 2013, Michael H. Goldwasser # # Developed for use with the book: # # Data Structures and Algorithms in Python # Michael T. Goodrich, Roberto Tamassia, and Michael H. Goldwasser # John Wiley & Sons, 2013 # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program. If not, see <http://www.gnu.org/licenses/>. """Basic example of an adapter class to provide a stack interface to Python's list.""" class ArrayStack: """LIFO Stack implementation using a Python list as underlying storage.""" def __init__(self): """Create an empty stack.""" self._data = [] # nonpublic list instance def __len__(self): """Return the number of elements in the stack.""" return len(self._data) def is_empty(self): """Return True if the stack is empty.""" return len(self._data) == 0 def push(self, e): """Add element e to the top of the stack.""" self._data.append(e) # new item stored at end of list def top(self): """Return (but do not remove) the element at the top of the stack. Raise Empty exception if the stack is empty. """ if self.is_empty(): raise AssertionError('Stack is empty') return self._data[-1] # the last item in the list def pop(self): """Remove and return the element from the top of the stack (i.e., LIFO). Raise Empty exception if the stack is empty. """ if self.is_empty(): raise AssertionError('Stack is empty') return self._data.pop() # remove last item from list if __name__ == '__main__': S = ArrayStack() # contents: [ ] S.push(5) # contents: [5] S.push(3) # contents: [5, 3] print(len(S)) # contents: [5, 3]; outputs 2 print(S.pop()) # contents: [5]; outputs 3 print(S.is_empty()) # contents: [5]; outputs False print(S.pop()) # contents: [ ]; outputs 5 print(S.is_empty()) # contents: [ ]; outputs True S.push(7) # contents: [7] S.push(9) # contents: [7, 9] print(S.top()) # contents: [7, 9]; outputs 9 S.print_contents() S.push(4) # contents: [7, 9, 4] print(len(S)) # contents: [7, 9, 4]; outputs 3 print(S.pop()) # contents: [7, 9]; outputs 4 S.push(6) # contents: [7, 9, 6] S.push(8) # contents: [7, 9, 6, 8] S.print_contents() print(S.pop()) # contents: [7, 9, 6]; outputs 8 #you can push anything in a stack, for instance you can push strings... S1 = ArrayStack() S1.push("John") S1.push("Doe") S1.print_contents() #...or an array! S2 = ArrayStack() S2.push(["Basic English", 60, 'B+']) S2.push(["ADSA", 95, 'A+']) S2.print_contents()	39.410526	86	0.554754	# Copyright 2013, Michael H. Goldwasser # # Developed for use with the book: # # Data Structures and Algorithms in Python # Michael T. Goodrich, Roberto Tamassia, and Michael H. Goldwasser # John Wiley & Sons, 2013 # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program. If not, see <http://www.gnu.org/licenses/>. """Basic example of an adapter class to provide a stack interface to Python's list.""" class ArrayStack: """LIFO Stack implementation using a Python list as underlying storage.""" def __init__(self): """Create an empty stack.""" self._data = [] # nonpublic list instance def __len__(self): """Return the number of elements in the stack.""" return len(self._data) def is_empty(self): """Return True if the stack is empty.""" return len(self._data) == 0 def push(self, e): """Add element e to the top of the stack.""" self._data.append(e) # new item stored at end of list def top(self): """Return (but do not remove) the element at the top of the stack. Raise Empty exception if the stack is empty. """ if self.is_empty(): raise AssertionError('Stack is empty') return self._data[-1] # the last item in the list def pop(self): """Remove and return the element from the top of the stack (i.e., LIFO). Raise Empty exception if the stack is empty. """ if self.is_empty(): raise AssertionError('Stack is empty') return self._data.pop() # remove last item from list def print_contents(self): print("Stack content: {0}".format(self._data)) if __name__ == '__main__': S = ArrayStack() # contents: [ ] S.push(5) # contents: [5] S.push(3) # contents: [5, 3] print(len(S)) # contents: [5, 3]; outputs 2 print(S.pop()) # contents: [5]; outputs 3 print(S.is_empty()) # contents: [5]; outputs False print(S.pop()) # contents: [ ]; outputs 5 print(S.is_empty()) # contents: [ ]; outputs True S.push(7) # contents: [7] S.push(9) # contents: [7, 9] print(S.top()) # contents: [7, 9]; outputs 9 S.print_contents() S.push(4) # contents: [7, 9, 4] print(len(S)) # contents: [7, 9, 4]; outputs 3 print(S.pop()) # contents: [7, 9]; outputs 4 S.push(6) # contents: [7, 9, 6] S.push(8) # contents: [7, 9, 6, 8] S.print_contents() print(S.pop()) # contents: [7, 9, 6]; outputs 8 #you can push anything in a stack, for instance you can push strings... S1 = ArrayStack() S1.push("John") S1.push("Doe") S1.print_contents() #...or an array! S2 = ArrayStack() S2.push(["Basic English", 60, 'B+']) S2.push(["ADSA", 95, 'A+']) S2.print_contents()	59	0	27
fefc73a6ccd7110962995b4002d9d6080e706454	254	py	Python	preprocessing/smri/utils/features.py	GalBenZvi/BrainPrint	8dda22f130f60bac66fe05f0f5163ee3680616f5	[ "Apache-2.0" ]	null	null	null	preprocessing/smri/utils/features.py	GalBenZvi/BrainPrint	8dda22f130f60bac66fe05f0f5163ee3680616f5	[ "Apache-2.0" ]	1	2021-08-12T07:54:37.000Z	2021-08-12T07:54:37.000Z	preprocessing/dwi/utils/features.py	GalBenZvi/BrainPrint	8dda22f130f60bac66fe05f0f5163ee3680616f5	[ "Apache-2.0" ]	1	2021-08-08T11:56:19.000Z	2021-08-08T11:56:19.000Z	FEATURES = { "DWI": [ "MD", "FA", "AD", "RD", "EigenValue", "EigenVector", "CS", "CP", "CL", ], "SMRI": [ "Thickness", "Volume", "Sulc", ], }	13.368421	22	0.271654	FEATURES = { "DWI": [ "MD", "FA", "AD", "RD", "EigenValue", "EigenVector", "CS", "CP", "CL", ], "SMRI": [ "Thickness", "Volume", "Sulc", ], }	0	0	0
4e01f94c8ce0771d637f22aa24a5caf4396746e5	1,240	py	Python	tests/test_https_middleware.py	alxpy/aiohttp-middlewares	377740d21cdaf3142523eb81b0cee4c6dd01f6b5	[ "BSD-3-Clause" ]	34	2017-05-14T11:31:41.000Z	2022-03-24T06:07:31.000Z	tests/test_https_middleware.py	alxpy/aiohttp-middlewares	377740d21cdaf3142523eb81b0cee4c6dd01f6b5	[ "BSD-3-Clause" ]	77	2017-10-20T19:40:59.000Z	2022-03-01T05:07:36.000Z	tests/test_https_middleware.py	alxpy/aiohttp-middlewares	377740d21cdaf3142523eb81b0cee4c6dd01f6b5	[ "BSD-3-Clause" ]	2	2019-11-06T12:45:33.000Z	2021-11-24T14:55:28.000Z	import pytest from aiohttp import web from aiohttp_middlewares import https_middleware @pytest.mark.parametrize( "match_headers, request_headers, expected", [ (None, None, "http"), (None, {"X-Forwarded-Proto": "http"}, "http"), (None, {"X-Forwarded-Proto": "https"}, "https"), ({}, None, "http"), ({}, {"X-Forwarded-Proto": "http"}, "http"), ({"Forwarded": "https"}, None, "http"), ({"Forwarded": "https"}, {"X-Forwarded-Proto": "http"}, "http"), ({"Forwarded": "https"}, {"X-Forwarded-Proto": "https"}, "http"), ({"Forwarded": "https"}, {"Forwarded": "http"}, "http"), ({"Forwarded": "https"}, {"Forwarded": "https"}, "https"), ], )	32.631579	73	0.625806	import pytest from aiohttp import web from aiohttp_middlewares import https_middleware def create_app(match_headers): app = web.Application(middlewares=[https_middleware(match_headers)]) app.router.add_route("GET", "/", handler) return app async def handler(request): return web.json_response(request.url.scheme) @pytest.mark.parametrize( "match_headers, request_headers, expected", [ (None, None, "http"), (None, {"X-Forwarded-Proto": "http"}, "http"), (None, {"X-Forwarded-Proto": "https"}, "https"), ({}, None, "http"), ({}, {"X-Forwarded-Proto": "http"}, "http"), ({"Forwarded": "https"}, None, "http"), ({"Forwarded": "https"}, {"X-Forwarded-Proto": "http"}, "http"), ({"Forwarded": "https"}, {"X-Forwarded-Proto": "https"}, "http"), ({"Forwarded": "https"}, {"Forwarded": "http"}, "http"), ({"Forwarded": "https"}, {"Forwarded": "https"}, "https"), ], ) async def test_https_middleware( aiohttp_client, match_headers, request_headers, expected ): client = await aiohttp_client(create_app(match_headers)) response = await client.get("/", headers=request_headers) assert await response.json() == expected	441	0	68
2159bbd87ad1a044357a5af7ed39b624367234cb	1,066	py	Python	m2core/data_schemes/redis_system_scheme.py	mdutkin/m2core	1e08acbc99e9e6c60a03d63110e2fcec96a35ec0	[ "MIT" ]	18	2017-11-02T16:06:41.000Z	2019-04-16T08:11:37.000Z	m2core/data_schemes/redis_system_scheme.py	mdutkin/m2core	1e08acbc99e9e6c60a03d63110e2fcec96a35ec0	[ "MIT" ]	4	2018-06-19T08:45:26.000Z	2019-02-08T04:28:28.000Z	m2core/data_schemes/redis_system_scheme.py	mdutkin/m2core	1e08acbc99e9e6c60a03d63110e2fcec96a35ec0	[ "MIT" ]	2	2017-11-10T07:27:22.000Z	2018-06-27T12:16:27.000Z	# holds mapping between human key prefixes and real Redis prefixes minute = 60 hour = 60 * minute day = 24 * hour week = 7 * day month = 31 * day redis_scheme = { # # human-readable table name # \| # \| prefix for key in Redis + # \| key placeholder # \| \| # \| \| # \| \| # \| \| # \| \| # \| \| # \| \| # \| \| # \| \| key TTL in Redis (sec), None - never expire # V V V # mapping between token (key) and user id (value) 'ACCESS_TOKENS_BY_HASH': {'prefix': 'at:%s', 'ttl': None}, # mapping of user id and his roles 'USER_ROLES': {'prefix': 'ur:%s', 'ttl': -1}, # mapping between role id and its permissions 'ROLE_PERMISSIONS': {'prefix': 'rp:%s', 'ttl': -1}, }	34.387097	87	0.366792	# holds mapping between human key prefixes and real Redis prefixes minute = 60 hour = 60 * minute day = 24 * hour week = 7 * day month = 31 * day redis_scheme = { # # human-readable table name # \| # \| prefix for key in Redis + # \| key placeholder # \| \| # \| \| # \| \| # \| \| # \| \| # \| \| # \| \| # \| \| # \| \| key TTL in Redis (sec), None - never expire # V V V # mapping between token (key) and user id (value) 'ACCESS_TOKENS_BY_HASH': {'prefix': 'at:%s', 'ttl': None}, # mapping of user id and his roles 'USER_ROLES': {'prefix': 'ur:%s', 'ttl': -1}, # mapping between role id and its permissions 'ROLE_PERMISSIONS': {'prefix': 'rp:%s', 'ttl': -1}, }	0	0	0
83fef8c29fe6d4a012071d9b3885e0118d9aecd4	4,535	py	Python	python/paddle/fluid/tests/unittests/test_allclose_op.py	Steffy-zxf/Paddle	82b23b8fcf6f171ad72e1453c8a2b337e95ee8a9	[ "Apache-2.0" ]	null	null	null	python/paddle/fluid/tests/unittests/test_allclose_op.py	Steffy-zxf/Paddle	82b23b8fcf6f171ad72e1453c8a2b337e95ee8a9	[ "Apache-2.0" ]	null	null	null	python/paddle/fluid/tests/unittests/test_allclose_op.py	Steffy-zxf/Paddle	82b23b8fcf6f171ad72e1453c8a2b337e95ee8a9	[ "Apache-2.0" ]	null	null	null	# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import unittest import numpy as np from op_test import OpTest import paddle if __name__ == "__main__": unittest.main()	33.592593	80	0.592944	# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import unittest import numpy as np from op_test import OpTest import paddle class TestAllcloseOp(OpTest): def set_args(self): self.input = np.array([10000., 1e-07]).astype("float32") self.other = np.array([10000.1, 1e-08]).astype("float32") self.rtol = 1e-05 self.atol = 1e-08 self.equal_nan = False def setUp(self): self.set_args() self.op_type = "allclose" self.inputs = {'Input': self.input, 'Other': self.other} self.attrs = { 'rtol': self.rtol, 'atol': self.atol, 'equal_nan': self.equal_nan } self.outputs = { 'Out': np.array([ np.allclose( self.inputs['Input'], self.inputs['Other'], rtol=self.rtol, atol=self.atol, equal_nan=self.equal_nan) ]) } def test_check_output(self): self.check_output() class TestAllcloseOpSmallNum(TestAllcloseOp): def set_args(self): self.input = np.array([10000., 1e-08]).astype("float32") self.other = np.array([10000.1, 1e-09]).astype("float32") self.rtol = 1e-05 self.atol = 1e-08 self.equal_nan = False class TestAllcloseOpNanFalse(TestAllcloseOp): def set_args(self): self.input = np.array([1.0, float('nan')]).astype("float32") self.other = np.array([1.0, float('nan')]).astype("float32") self.rtol = 1e-05 self.atol = 1e-08 self.equal_nan = False class TestAllcloseOpNanTrue(TestAllcloseOp): def set_args(self): self.input = np.array([1.0, float('nan')]).astype("float32") self.other = np.array([1.0, float('nan')]).astype("float32") self.rtol = 1e-05 self.atol = 1e-08 self.equal_nan = True class TestAllcloseDygraph(unittest.TestCase): def test_api_case(self): paddle.disable_static() x_data = np.random.rand(10, 10) y_data = np.random.rand(10, 10) x = paddle.to_tensor(x_data) y = paddle.to_tensor(y_data) out = paddle.allclose(x, y, rtol=1e-05, atol=1e-08) expected_out = np.allclose(x_data, y_data, rtol=1e-05, atol=1e-08) self.assertTrue((out.numpy() == expected_out).all(), True) paddle.enable_static() class TestAllcloseError(unittest.TestCase): def test_input_dtype(self): def test_x_dtype(): with paddle.static.program_guard(paddle.static.Program(), paddle.static.Program()): x = paddle.fluid.data(name='x', shape=[10, 10], dtype='float16') y = paddle.fluid.data(name='y', shape=[10, 10], dtype='float64') result = paddle.allclose(x, y) self.assertRaises(TypeError, test_x_dtype) def test_y_dtype(): with paddle.static.program_guard(paddle.static.Program(), paddle.static.Program()): x = paddle.fluid.data(name='x', shape=[10, 10], dtype='float64') y = paddle.fluid.data(name='y', shape=[10, 10], dtype='int32') result = paddle.allclose(x, y) self.assertRaises(TypeError, test_y_dtype) def test_attr(self): x = paddle.fluid.data(name='x', shape=[10, 10], dtype='float64') y = paddle.fluid.data(name='y', shape=[10, 10], dtype='float64') def test_rtol(): result = paddle.allclose(x, y, rtol=True) self.assertRaises(TypeError, test_rtol) def test_atol(): result = paddle.allclose(x, y, rtol=True) self.assertRaises(TypeError, test_atol) def test_equal_nan(): result = paddle.allclose(x, y, equal_nan=1) self.assertRaises(TypeError, test_equal_nan) if __name__ == "__main__": unittest.main()	3,291	125	375
bbe11f64ed969361559c9c408832f964831eb078	174	py	Python	flask_swag/extractor/__init__.py	Hardtack/Flask-Swag	84555d1b88434ed8813a7045f08a98398197e90a	[ "MIT" ]	10	2016-02-08T14:08:20.000Z	2019-07-21T02:25:02.000Z	flask_swag/extractor/__init__.py	Hardtack/Flask-Swag	84555d1b88434ed8813a7045f08a98398197e90a	[ "MIT" ]	2	2016-02-11T08:59:00.000Z	2017-05-08T06:49:28.000Z	flask_swag/extractor/__init__.py	Hardtack/Flask-Swag	84555d1b88434ed8813a7045f08a98398197e90a	[ "MIT" ]	null	null	null	""" extractor ========= Extract path info from flask application. """ from .base import Extractor from .mark import MarkExtractor __all__ = ['Extractor', 'MarkExtractor']	14.5	41	0.706897	""" extractor ========= Extract path info from flask application. """ from .base import Extractor from .mark import MarkExtractor __all__ = ['Extractor', 'MarkExtractor']	0	0	0
ab256a8a46bd4d6a36a50cb2513e20b4a1200245	1,676	py	Python	lib/process_util.py	hustwei/chromite	10eb79abeb64e859362546214b7e039096ac9830	[ "BSD-3-Clause" ]	null	null	null	lib/process_util.py	hustwei/chromite	10eb79abeb64e859362546214b7e039096ac9830	[ "BSD-3-Clause" ]	null	null	null	lib/process_util.py	hustwei/chromite	10eb79abeb64e859362546214b7e039096ac9830	[ "BSD-3-Clause" ]	null	null	null	# Copyright 2014 The Chromium OS Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. """Process related utilities.""" from __future__ import print_function import errno import os import signal import sys import time def GetExitStatus(status): """Get the exit status of a child from an os.waitpid call. Args: status: The return value of os.waitpid(pid, 0)[1] Returns: The exit status of the process. If the process exited with a signal, the return value will be 128 plus the signal number. """ if os.WIFSIGNALED(status): return 128 + os.WTERMSIG(status) else: assert os.WIFEXITED(status), 'Unexpected exit status %r' % status return os.WEXITSTATUS(status) def ExitAsStatus(status): """Exit the same way as \|status\|. If the status field says it was killed by a signal, then we'll do that to ourselves. Otherwise we'll exit with the exit code. See http://www.cons.org/cracauer/sigint.html for more details. Args: status: A status as returned by os.wait type funcs. """ exit_status = os.WEXITSTATUS(status) if os.WIFSIGNALED(status): # Kill ourselves with the same signal. sig_status = os.WTERMSIG(status) pid = os.getpid() os.kill(pid, sig_status) time.sleep(0.1) # Still here? Maybe the signal was masked. try: signal.signal(sig_status, signal.SIG_DFL) except RuntimeError as e: if e.args[0] != errno.EINVAL: raise os.kill(pid, sig_status) time.sleep(0.1) # Still here? Just exit. exit_status = 127 # Exit with the code we want. sys.exit(exit_status)	25.014925	75	0.693914	# Copyright 2014 The Chromium OS Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. """Process related utilities.""" from __future__ import print_function import errno import os import signal import sys import time def GetExitStatus(status): """Get the exit status of a child from an os.waitpid call. Args: status: The return value of os.waitpid(pid, 0)[1] Returns: The exit status of the process. If the process exited with a signal, the return value will be 128 plus the signal number. """ if os.WIFSIGNALED(status): return 128 + os.WTERMSIG(status) else: assert os.WIFEXITED(status), 'Unexpected exit status %r' % status return os.WEXITSTATUS(status) def ExitAsStatus(status): """Exit the same way as \|status\|. If the status field says it was killed by a signal, then we'll do that to ourselves. Otherwise we'll exit with the exit code. See http://www.cons.org/cracauer/sigint.html for more details. Args: status: A status as returned by os.wait type funcs. """ exit_status = os.WEXITSTATUS(status) if os.WIFSIGNALED(status): # Kill ourselves with the same signal. sig_status = os.WTERMSIG(status) pid = os.getpid() os.kill(pid, sig_status) time.sleep(0.1) # Still here? Maybe the signal was masked. try: signal.signal(sig_status, signal.SIG_DFL) except RuntimeError as e: if e.args[0] != errno.EINVAL: raise os.kill(pid, sig_status) time.sleep(0.1) # Still here? Just exit. exit_status = 127 # Exit with the code we want. sys.exit(exit_status)	0	0	0
b6f9b268179e914aa4660fb6210f0fd47b82d044	7,204	py	Python	function_testing/test_pointcorr.py	simonsobs/soaculib	db829e74f9feba06b3b90e2b0fc997a4c86ae683	[ "BSD-2-Clause" ]	1	2022-02-16T22:33:46.000Z	2022-02-16T22:33:46.000Z	function_testing/test_pointcorr.py	simonsobs/soaculib	db829e74f9feba06b3b90e2b0fc997a4c86ae683	[ "BSD-2-Clause" ]	null	null	null	function_testing/test_pointcorr.py	simonsobs/soaculib	db829e74f9feba06b3b90e2b0fc997a4c86ae683	[ "BSD-2-Clause" ]	null	null	null	import soaculib import test_helpers as th import time import numpy as np import pickle # Locals. import spem_model import util parser = util.get_parser() parser.add_argument('mode', default='passive', nargs='?') args = parser.parse_args() SPEM_KEYS = [ 'IA', 'IE', 'TF', 'TFS', 'TFC', 'AN', 'AW', # 'AN2', 'AW2', 'NPAE', 'CA', # 'AES', 'AEC', 'AES2', 'AEC2', #'EES' ... no elevation ellipticity. ] IGNORE_WRITEBACK = [] #'AN2', 'AW2'] class SpemHelper: """This works with simple parameter names (IA, etc) and values in degrees (rather than ACU internal mdeg). """ DSET = 'DataSets.CmdSPEMParameter' GLOBAL_EN = ('DataSets.CmdPointingCorrection', 'Systematic error model (SPEM) on') MDEG = 0.001 keep_going = True acu = soaculib.AcuControl(args.config) banner('Check Datasets Present') for dset in [ 'DataSets.StatusSATPDetailed8100', 'DataSets.StatusPointingCorrection', 'DataSets.CmdSPEMParameter', ]: try: v1 = acu.Values(dset) print(' Retrieved %-40s - %i keys' % (dset, len(v1))) except soaculib.http.HttpError as e: print(' ! Failed to retrieve %s' % dset) keep_going = False check_ok() banner('Check SPEM Against Schema') spemh = SpemHelper(acu) excess_keys = spemh.get().keys() missing_keys = [k for k in SPEM_KEYS] print(' Read %i keys (expecting %i)' % (len(excess_keys), len(missing_keys))) both = set(missing_keys).intersection(excess_keys) missing_keys = list(set(missing_keys).difference(both)) excess_keys = list(set(excess_keys).difference(both)) if len(missing_keys): print(' Expected but did not find these keys:') print(' ' + ', '.join(missing_keys)) keep_going = False if len(excess_keys): print(' Found but did not expect these keys:') print(' ' + ', '.join(excess_keys)) #keep_going = False check_ok() banner('Check write-back all SPEM parameters') if not th.check_remote(acu): print('ACU is not in remote mode!') keep_going = False check_ok() for k, v in spemh.get().items(): try: spemh.set({k: v}) except: print(' Failed to write %s!' % k) if k not in IGNORE_WRITEBACK: keep_going = False continue print(' Write-back test complete.') check_ok() banner('Confirm ACU in Stop') if acu.mode() != 'Stop': print(' Any further testing requires ACU to be in stop.') keep_going = False else: print(' ACU is in stop.') check_ok() banner('Check SPEM responsiveness') pos0 = th.get_positions(acu) print('Current position:', pos0) # Test basic offsets. for param in ['IA', 'IE']: val = 0.1 # deg print('Set %s=%f deg' % (param, val)) spemh.set({param: val}) print(' new position:', th.get_positions(acu)) spemh.set({param: 0}) banner('Check global enable') spemh.clear(ignore=IGNORE_WRITEBACK) pos0 = th.get_positions(acu) print(' Starting position is az=%8.4f, el=%8.4f' % tuple(pos0)) spemh.set({'IA': 0.3, 'IE': -0.4}) pos1 = th.get_positions(acu) print(' After SPEM model az=%8.4f, el=%8.4f' % tuple(pos1)) spemh.global_enable(False) pos2 = th.get_positions(acu) print(' After SPEM disable az=%8.4f, el=%8.4f' % tuple(pos2)) spemh.global_enable(True) pos3 = th.get_positions(acu) print(' After SPEM enable az=%8.4f, el=%8.4f' % tuple(pos3)) spemh.clear(ignore=IGNORE_WRITEBACK) pos4 = th.get_positions(acu) print(' After SPEM clear az=%8.4f, el=%8.4f' % tuple(pos4)) if args.mode == 'singles': # A good mode for debugging individual parameter equations. banner('Test response to each parameter.') spemh.clear(ignore=IGNORE_WRITEBACK) model0 = spemh.get() pos0 = th.get_positions(acu) print(' Starting position is az=%8.4f, el=%8.4f' % tuple(pos0)) for k in SPEM_KEYS: if k in IGNORE_WRITEBACK: continue D = 0.4 spemh.set({k: D}) model = dict(model0) model[k] = D time.sleep(.2) pos1 = th.get_positions(acu) spemh.set({k: 0}) expected = spem_model.delta(pos0, model) print(' For %-4s = %4.2f only: ' % (k, D) + 'expect [%+7.4f,%+7.4f] ' % tuple(expected) + 'and measure [%+7.4f,%+7.4f]' % tuple(pos1 - pos0), end='') if (abs(expected - (pos1-pos0)).sum() > 1e-4): print(' ! Mismatch.') else: print(' * ok') if args.mode == 'survey': # A good mode for checking that model makes sense across the sky. banner('Make a survey of corrections over many pointings.') model = {'IA': .1, 'IE': .2, 'TF': .3, #'TFC': .4, 'TFS': .5, 'AN': -.1, 'AW': -.2, } # Move through various positions, apply the model at each and # measure the offsets. data = [] # [cmd, meas0, meas1] for el in [40, 45, 55]: for az in [160, 180, 200]: print('Moving to az=%.2f el=%.2f' % (az, el)) acu.go_to(az, el) spemh.clear(ignore=IGNORE_WRITEBACK) while not th.check_positions(acu, az, el): time.sleep(.5) print(' setting stop mode.') acu.stop() time.sleep(.2) pos0 = th.get_positions(acu) spemh.set(model) time.sleep(.2) pos1 = th.get_positions(acu) print(' delta pos is ', pos1-pos0) data.append([np.array([az, el]), pos0, pos1]) data = np.array(data) print(data.shape) # Write out model and params. filename = 'spem_survey_%i.pik' % int(time.time()) with open(filename, 'wb') as fout: pickle.dump({'model': model, 'data': data}, fout)	27.601533	92	0.575236	import soaculib import test_helpers as th import time import numpy as np import pickle # Locals. import spem_model import util parser = util.get_parser() parser.add_argument('mode', default='passive', nargs='?') args = parser.parse_args() SPEM_KEYS = [ 'IA', 'IE', 'TF', 'TFS', 'TFC', 'AN', 'AW', # 'AN2', 'AW2', 'NPAE', 'CA', # 'AES', 'AEC', 'AES2', 'AEC2', #'EES' ... no elevation ellipticity. ] IGNORE_WRITEBACK = [] #'AN2', 'AW2'] class SpemHelper: """This works with simple parameter names (IA, etc) and values in degrees (rather than ACU internal mdeg). """ DSET = 'DataSets.CmdSPEMParameter' GLOBAL_EN = ('DataSets.CmdPointingCorrection', 'Systematic error model (SPEM) on') MDEG = 0.001 def __init__(self, acu): self.acu = acu def global_enable(self, enable=None): if enable is None: return self.acu.Values(self.GLOBAL_EN[0])[self.GLOBAL_EN[1]] self.acu.Command(self.GLOBAL_EN[0], 'Set %s' % self.GLOBAL_EN[1], int(bool(enable))) def clear(self, ignore=[]): vals = self.get(ignore=ignore) self.set({k: 0 for k in vals.keys()}) return not any(self.get().values()) def get(self, ignore=[]): # Strip "Parameter " from start of each key. raw = self.acu.Values(self.DSET) cleaned = {k.split()[-1]: float(v) * self.MDEG for k, v in raw.items()} return {k: v for k, v in cleaned.items() if k not in ignore} def set(self, dict_arg=None, *kwargs): all_args = {} if dict_arg is not None: all_args.update(dict_arg) all_args.update(kwargs) for k, v in all_args.items(): ret_val = self.acu.Command(self.DSET, 'Set Spem_%s' % k, '%f' % (v / self.MDEG)) if ret_val != 'OK, Command send.': raise RuntimeError('Failed to set parameter: %s' % k) keep_going = True def check_ok(): if not keep_going: parser.exit("Exiting.") def banner(title): print() print('' * 60) print(' ' + title) print('' 60) acu = soaculib.AcuControl(args.config) banner('Check Datasets Present') for dset in [ 'DataSets.StatusSATPDetailed8100', 'DataSets.StatusPointingCorrection', 'DataSets.CmdSPEMParameter', ]: try: v1 = acu.Values(dset) print(' Retrieved %-40s - %i keys' % (dset, len(v1))) except soaculib.http.HttpError as e: print(' ! Failed to retrieve %s' % dset) keep_going = False check_ok() banner('Check SPEM Against Schema') spemh = SpemHelper(acu) excess_keys = spemh.get().keys() missing_keys = [k for k in SPEM_KEYS] print(' Read %i keys (expecting %i)' % (len(excess_keys), len(missing_keys))) both = set(missing_keys).intersection(excess_keys) missing_keys = list(set(missing_keys).difference(both)) excess_keys = list(set(excess_keys).difference(both)) if len(missing_keys): print(' Expected but did not find these keys:') print(' ' + ', '.join(missing_keys)) keep_going = False if len(excess_keys): print(' Found but did not expect these keys:') print(' ' + ', '.join(excess_keys)) #keep_going = False check_ok() banner('Check write-back all SPEM parameters') if not th.check_remote(acu): print('ACU is not in remote mode!') keep_going = False check_ok() for k, v in spemh.get().items(): try: spemh.set({k: v}) except: print(' Failed to write %s!' % k) if k not in IGNORE_WRITEBACK: keep_going = False continue print(' Write-back test complete.') check_ok() banner('Confirm ACU in Stop') if acu.mode() != 'Stop': print(' Any further testing requires ACU to be in stop.') keep_going = False else: print(' ACU is in stop.') check_ok() banner('Check SPEM responsiveness') pos0 = th.get_positions(acu) print('Current position:', pos0) # Test basic offsets. for param in ['IA', 'IE']: val = 0.1 # deg print('Set %s=%f deg' % (param, val)) spemh.set({param: val}) print(' new position:', th.get_positions(acu)) spemh.set({param: 0}) banner('Check global enable') spemh.clear(ignore=IGNORE_WRITEBACK) pos0 = th.get_positions(acu) print(' Starting position is az=%8.4f, el=%8.4f' % tuple(pos0)) spemh.set({'IA': 0.3, 'IE': -0.4}) pos1 = th.get_positions(acu) print(' After SPEM model az=%8.4f, el=%8.4f' % tuple(pos1)) spemh.global_enable(False) pos2 = th.get_positions(acu) print(' After SPEM disable az=%8.4f, el=%8.4f' % tuple(pos2)) spemh.global_enable(True) pos3 = th.get_positions(acu) print(' After SPEM enable az=%8.4f, el=%8.4f' % tuple(pos3)) spemh.clear(ignore=IGNORE_WRITEBACK) pos4 = th.get_positions(acu) print(' After SPEM clear az=%8.4f, el=%8.4f' % tuple(pos4)) if args.mode == 'singles': # A good mode for debugging individual parameter equations. banner('Test response to each parameter.') spemh.clear(ignore=IGNORE_WRITEBACK) model0 = spemh.get() pos0 = th.get_positions(acu) print(' Starting position is az=%8.4f, el=%8.4f' % tuple(pos0)) for k in SPEM_KEYS: if k in IGNORE_WRITEBACK: continue D = 0.4 spemh.set({k: D}) model = dict(model0) model[k] = D time.sleep(.2) pos1 = th.get_positions(acu) spemh.set({k: 0}) expected = spem_model.delta(pos0, model) print(' For %-4s = %4.2f only: ' % (k, D) + 'expect [%+7.4f,%+7.4f] ' % tuple(expected) + 'and measure [%+7.4f,%+7.4f]' % tuple(pos1 - pos0), end='') if (abs(expected - (pos1-pos0)).sum() > 1e-4): print(' ! Mismatch.') else: print(' * ok') if args.mode == 'survey': # A good mode for checking that model makes sense across the sky. banner('Make a survey of corrections over many pointings.') model = {'IA': .1, 'IE': .2, 'TF': .3, #'TFC': .4, 'TFS': .5, 'AN': -.1, 'AW': -.2, } # Move through various positions, apply the model at each and # measure the offsets. data = [] # [cmd, meas0, meas1] for el in [40, 45, 55]: for az in [160, 180, 200]: print('Moving to az=%.2f el=%.2f' % (az, el)) acu.go_to(az, el) spemh.clear(ignore=IGNORE_WRITEBACK) while not th.check_positions(acu, az, el): time.sleep(.5) print(' setting stop mode.') acu.stop() time.sleep(.2) pos0 = th.get_positions(acu) spemh.set(model) time.sleep(.2) pos1 = th.get_positions(acu) print(' delta pos is ', pos1-pos0) data.append([np.array([az, el]), pos0, pos1]) data = np.array(data) print(data.shape) # Write out model and params. filename = 'spem_survey_%i.pik' % int(time.time()) with open(filename, 'wb') as fout: pickle.dump({'model': model, 'data': data}, fout)	1,172	0	192
f8a8ba1c09a54c0a8400ac2ff929242b3d0ee342	995	py	Python	django/ledger_base/backend.py	phantomhieve/cashcenter	642a496c5e60847f4c4a6cc2c80b957ae2d6285b	[ "MIT" ]	null	null	null	django/ledger_base/backend.py	phantomhieve/cashcenter	642a496c5e60847f4c4a6cc2c80b957ae2d6285b	[ "MIT" ]	4	2021-04-08T22:00:11.000Z	2021-09-22T19:42:08.000Z	django/ledger_base/backend.py	phantomhieve/cashcenter	642a496c5e60847f4c4a6cc2c80b957ae2d6285b	[ "MIT" ]	null	null	null	from ledger.models import LedgerData	39.8	49	0.527638	from ledger.models import LedgerData def makeInstance(instance, request): new_instance = LedgerData( user = request.user, l_r_no = instance.l_r_no, l_r_date = instance.l_r_date, bale_no = instance.bale_no, supplier = instance.supplier, location = instance.location, item = instance.item, pcs_mtr = instance.pcs_mtr, price = instance.price, weight = instance.weight, frieght = instance.frieght, transport = instance.transport, delivery = instance.delivery, reciept = instance.reciept, remark = instance.remark, status = instance.status, hsn_code = instance.hsn_code, bill_ammount = instance.bill_ammount, no_of_bale = instance.no_of_bale ) return new_instance	936	0	22
61379b4f083f9f81ebc303758aee285ce2476135	13,529	py	Python	tests/test_of_mangle.py	cloudysunny14/faucet	7e4414028f7696e67385b811518ae41d01fc830c	[ "Apache-2.0" ]	1	2016-12-28T15:14:51.000Z	2016-12-28T15:14:51.000Z	tests/test_of_mangle.py	cloudysunny14/of_mangle	78fbf4ca897da2995a6ecba6330519b8680ebadb	[ "Apache-2.0" ]	null	null	null	tests/test_of_mangle.py	cloudysunny14/of_mangle	78fbf4ca897da2995a6ecba6330519b8680ebadb	[ "Apache-2.0" ]	null	null	null	#!/usr/bin/env python # # Copyright 2014 cloudysunny14. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or # implied. # See the License for the specific language governing permissions and # limitations under the License. """ How to run this test edit linc config file. LINC-Switch/rel/linc/releases/1.0/sys.config You can find the sample config I used for the test below: [ {linc, [ {of_config, enabled}, {capable_switch_ports, [ {port, 1, [{interface, "tap0"}]}, {port, 2, [{interface, "tap1"}]} ]}, {capable_switch_queues, [ {queue, 1, [{min_rate, 100}, {max_rate, 100}]}, {queue, 2, [{min_rate, 100}, {max_rate, 100}]} ]}, {logical_switches, [ {switch, 0, [ {backend, linc_us4}, {controllers, [ {"Switch0-DefaultController", "localhost", 6633, tcp} ]}, {queues_status, enabled}, {ports, [ {port, 1, {queues, [1,2]}}, {port, 2, {queues, [1,2]}} ]} ]} ]} ]}, {enetconf, [ {capabilities, [{base, {1, 1}}, {startup, {1, 0}}, {'writable-running', {1, 0}}]}, {callback_module, linc_ofconfig}, {sshd_ip, any}, {sshd_port, 1830}, {sshd_user_passwords, [ {"linc", "linc"} ]} ]}, {lager, [ {handlers, [ {lager_console_backend, info}, {lager_file_backend, [ {"log/error.log", error, 10485760, "$D0", 5}, {"log/console.log", info, 10485760, "$D0", 5} ]} ]} ]}, {sasl, [ {sasl_error_logger, {file, "log/sasl-error.log"}}, {errlog_type, error}, {error_logger_mf_dir, "log/sasl"}, % Log directory {error_logger_mf_maxbytes, 10485760}, % 10 MB max file size {error_logger_mf_maxfiles, 5} % 5 files max ]}, {sync, [ {excluded_modules, [procket]} ]} ]. Then run linc # sudo rel/linc/bin/linc console Then run ryu # cd of_mangle # export RYUHOME=$HOME/ryu # PYTHONPATH=$RYUHOME:. $RYUHOME/bin/ryu-manager --verbose\ tests/test_of_mangle.py """ import logging from ryu.base import app_manager from ryu.controller import dpset from ryu.controller.handler import set_ev_cls from ryu.exception import OFPUnknownVersion from ryu.lib import ofctl_v1_0 from ryu.lib import ofctl_v1_2 from ryu.lib import ofctl_v1_3 from ryu.lib import hub from ryu.lib.of_config import capable_switch from ryu.controller import ofp_event from ryu.controller import dpset from ryu.controller.handler import MAIN_DISPATCHER from ryu.ofproto import ofproto_v1_0 from ryu.ofproto import ofproto_v1_2 from ryu.ofproto import ofproto_v1_3 from app import qoslib LOG = logging.getLogger(__name__) LOG_TEST_FINISH = 'TEST_FINISHED: Tests=[%s] (OK=%s NG=%s SKIP=%s)'	35.69657	83	0.572326	#!/usr/bin/env python # # Copyright 2014 cloudysunny14. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or # implied. # See the License for the specific language governing permissions and # limitations under the License. """ How to run this test edit linc config file. LINC-Switch/rel/linc/releases/1.0/sys.config You can find the sample config I used for the test below: [ {linc, [ {of_config, enabled}, {capable_switch_ports, [ {port, 1, [{interface, "tap0"}]}, {port, 2, [{interface, "tap1"}]} ]}, {capable_switch_queues, [ {queue, 1, [{min_rate, 100}, {max_rate, 100}]}, {queue, 2, [{min_rate, 100}, {max_rate, 100}]} ]}, {logical_switches, [ {switch, 0, [ {backend, linc_us4}, {controllers, [ {"Switch0-DefaultController", "localhost", 6633, tcp} ]}, {queues_status, enabled}, {ports, [ {port, 1, {queues, [1,2]}}, {port, 2, {queues, [1,2]}} ]} ]} ]} ]}, {enetconf, [ {capabilities, [{base, {1, 1}}, {startup, {1, 0}}, {'writable-running', {1, 0}}]}, {callback_module, linc_ofconfig}, {sshd_ip, any}, {sshd_port, 1830}, {sshd_user_passwords, [ {"linc", "linc"} ]} ]}, {lager, [ {handlers, [ {lager_console_backend, info}, {lager_file_backend, [ {"log/error.log", error, 10485760, "$D0", 5}, {"log/console.log", info, 10485760, "$D0", 5} ]} ]} ]}, {sasl, [ {sasl_error_logger, {file, "log/sasl-error.log"}}, {errlog_type, error}, {error_logger_mf_dir, "log/sasl"}, % Log directory {error_logger_mf_maxbytes, 10485760}, % 10 MB max file size {error_logger_mf_maxfiles, 5} % 5 files max ]}, {sync, [ {excluded_modules, [procket]} ]} ]. Then run linc # sudo rel/linc/bin/linc console Then run ryu # cd of_mangle # export RYUHOME=$HOME/ryu # PYTHONPATH=$RYUHOME:. $RYUHOME/bin/ryu-manager --verbose\ tests/test_of_mangle.py """ import logging from ryu.base import app_manager from ryu.controller import dpset from ryu.controller.handler import set_ev_cls from ryu.exception import OFPUnknownVersion from ryu.lib import ofctl_v1_0 from ryu.lib import ofctl_v1_2 from ryu.lib import ofctl_v1_3 from ryu.lib import hub from ryu.lib.of_config import capable_switch from ryu.controller import ofp_event from ryu.controller import dpset from ryu.controller.handler import MAIN_DISPATCHER from ryu.ofproto import ofproto_v1_0 from ryu.ofproto import ofproto_v1_2 from ryu.ofproto import ofproto_v1_3 from app import qoslib LOG = logging.getLogger(__name__) LOG_TEST_FINISH = 'TEST_FINISHED: Tests=[%s] (OK=%s NG=%s SKIP=%s)' def get_flow_stats(dp, waiters, ofctl): table_id = dp.ofproto.OFPTT_ALL flags = 0 out_port = dp.ofproto.OFPP_ANY out_group = dp.ofproto.OFPG_ANY cookie = 0 cookie_mask = 0 match = dp.ofproto_parser.OFPMatch() stats = dp.ofproto_parser.OFPFlowStatsRequest( dp, flags, table_id, out_port, out_group, cookie, cookie_mask, match) msgs = [] ofctl.send_stats_request(dp, stats, waiters, msgs) flows = [] for msg in msgs: for stats in msg.body: actions = ofctl.actions_to_str(stats.instructions) match = ofctl.match_to_str(stats.match) s = {'priority': stats.priority, 'cookie': stats.cookie, 'idle_timeout': stats.idle_timeout, 'hard_timeout': stats.hard_timeout, 'actions': actions, 'match': match, 'table_id': stats.table_id} flows.append(s) flows = {str(dp.id): flows} return flows def delete_all_flows(dp): match = dp.ofproto_parser.OFPMatch() m = dp.ofproto_parser.OFPFlowMod(dp, 0, 0, dp.ofproto.OFPTT_ALL, dp.ofproto.OFPFC_DELETE, 0, 0, 0, 0xffffffff, dp.ofproto.OFPP_ANY, dp.ofproto.OFPG_ANY, 0, match, []) dp.send_msg(m) class OFMangleTester(app_manager.RyuApp): OFP_VERSIONS = [ofproto_v1_3.OFP_VERSION] _CONTEXTS = {'dpset': dpset.DPSet, 'qoslib': qoslib.QoSLib} _OFCTL = {ofproto_v1_0.OFP_VERSION: ofctl_v1_0, ofproto_v1_2.OFP_VERSION: ofctl_v1_2, ofproto_v1_3.OFP_VERSION: ofctl_v1_3} def __init__(self, args, kwargs): super(OFMangleTester, self).__init__(args, **kwargs) self.dpset = kwargs['dpset'] self.qoslib = kwargs['qoslib'] self.qoslib.use_switch_flow = False self.waiters = {} self.pending = [] self.results = {} self.capable_switch = capable_switch.OFCapableSwitch( host='localhost', port=1830, username='linc', password='linc', unknown_host_cb=lambda host, fingeprint: True) for t in dir(self): if t.startswith("test_"): self.pending.append(t) self.pending.sort(reverse=True) def stats_reply_handler(self, ev): msg = ev.msg dp = msg.datapath if dp.id not in self.waiters: return if msg.xid not in self.waiters[dp.id]: return lock, msgs = self.waiters[dp.id][msg.xid] msgs.append(msg) flags = 0 if dp.ofproto.OFP_VERSION == ofproto_v1_0.OFP_VERSION or \ dp.ofproto.OFP_VERSION == ofproto_v1_2.OFP_VERSION: flags = dp.ofproto.OFPSF_REPLY_MORE elif dp.ofproto.OFP_VERSION == ofproto_v1_3.OFP_VERSION: flags = dp.ofproto.OFPMPF_REPLY_MORE if msg.flags & flags: return del self.waiters[dp.id][msg.xid] lock.set() # for OpenFlow version1.0 @set_ev_cls(ofp_event.EventOFPFlowStatsReply, MAIN_DISPATCHER) def stats_reply_handler_v1_0(self, ev): self.stats_reply_handler(ev) # for OpenFlow version1.2 or later @set_ev_cls(ofp_event.EventOFPStatsReply, MAIN_DISPATCHER) def stats_reply_handler_v1_2(self, ev): self.stats_reply_handler(ev) @set_ev_cls(dpset.EventDP, dpset.DPSET_EV_DISPATCHER) def datapath_handler(self, ev): # Target switch datapath self.dp = ev.dp version = self.dp.ofproto.OFP_VERSION if version not in self._OFCTL: raise OFPUnknownVersion(version=version) self.ofctl = self._OFCTL[version] hub.spawn(self._do_test) def test_action_accept(self): mangle = qoslib.QoSLib.mangle(self.dp) mangle.add_property('action', 'accept').\ add_property('dst-address', '10.0.0.2').\ add_property('chain', 'forward') self.qoslib.add_mangle(mangle) msg = get_flow_stats(self.dp, self.waiters, self.ofctl) flow = msg[msg.keys()[0]][0] return ({'hard_timeout': 0, 'actions': ['GOTO_TABLE:3'], 'priority': 0, 'idle_timeout': 0, 'cookie': 0, 'table_id': 2, 'match': {'dl_type': 2048, 'nw_dst': '10.0.0.2'}} == flow) def test_action_list(self): mangle = qoslib.QoSLib.mangle(self.dp) mangle.address_list('first', ['10.0.0.2', '10.0.0.3']) mangle.add_property('action', 'accept').\ add_property('dst-address-list', 'first').\ add_property('chain', 'forward') self.qoslib.add_mangle(mangle) msg = get_flow_stats(self.dp, self.waiters, self.ofctl) flow = msg[msg.keys()[0]] LOG.info(flow) return ([{'hard_timeout': 0, 'actions': ['GOTO_TABLE:3'], 'priority': 0, 'idle_timeout': 0, 'cookie': 2113536, 'table_id': 2, 'match': {'dl_type': 2048, 'nw_dst': '10.0.0.3'}}, {'hard_timeout': 0, 'actions': ['GOTO_TABLE:3'], 'priority': 0, 'idle_timeout': 0, 'cookie': 2113536, 'table_id': 2, 'match': {'dl_type': 2048, 'nw_dst': '10.0.0.2'}}] == flow) def test_add_address_list(self): mangle = qoslib.QoSLib.mangle(self.dp) mangle.address_list('add_telnet', ['10.0.2.1', '10.0.3.1']) mangle.add_property('action', 'add-dst-to-address-list').\ add_property('address-list', 'add_telnet').\ add_property('dst-port', 5001).\ add_property('chain', 'input').\ add_property('priority', 100) self.qoslib.add_mangle(mangle) mangle = qoslib.QoSLib.mangle(self.dp) mangle.add_property('action', 'mark-packet').\ add_property('src-address-list', 'add_telnet').\ add_property('new-packet-mark', 'drop').\ add_property('chain', 'preforward') self.qoslib.add_mangle(mangle) mangle = qoslib.QoSLib.mangle(self.dp) mangle.add_property('action', 'accept').\ add_property('chain', 'input').\ add_property('priority', 0) self.qoslib.add_mangle(mangle) msg = get_flow_stats(self.dp, self.waiters, self.ofctl) flow = msg[msg.keys()[0]] LOG.info(flow) return ([{'hard_timeout': 0, 'actions': ['OUTPUT:4294967293'], 'priority': 100, 'idle_timeout': 0, 'cookie': 1048576, 'table_id': 0, 'match': {'dl_type': 2048, 'nw_proto': 6, 'tp_dst': 5001}}, {'hard_timeout': 0, 'actions': ['GOTO_TABLE:3'], 'priority': 0, 'idle_timeout': 0, 'cookie': 0, 'table_id': 0, 'match': {}}, {'hard_timeout': 0, 'actions': ['SET_FIELD: {ip_dscp:2}', 'GOTO_TABLE:2'], 'priority': 0, 'idle_timeout': 0, 'cookie': 1056768, 'table_id': 1, 'match': {'dl_type': 2048, 'nw_src': '10.0.3.1'}}, {'hard_timeout': 0, 'actions': ['SET_FIELD: {ip_dscp:2}', 'GOTO_TABLE:2'], 'priority': 0, 'idle_timeout': 0, 'cookie': 1056768, 'table_id': 1, 'match': {'dl_type': 2048, 'nw_src': '10.0.2.1'}}] == flow) def test_match_mac(self): mangle = qoslib.QoSLib.mangle(self.dp) mangle.add_property('action', 'accept').\ add_property('dst-mac-address', '11:11:11:11:11:11').\ add_property('chain', 'forward') self.qoslib.add_mangle(mangle) msg = get_flow_stats(self.dp, self.waiters, self.ofctl) flow = msg[msg.keys()[0]] return ([{'hard_timeout': 0, 'actions': ['GOTO_TABLE:3'], 'priority': 0, 'idle_timeout': 0, 'cookie': 0, 'table_id': 2, 'match': {'dl_dst': '11:11:11:11:11:11'}}] == flow) def test_add_queue(self): queue = qoslib.QoSLib.queue_tree(self.capable_switch, self.dp) queue.queue('high-priority', '500', '500') self.qoslib.register_queue(queue) return True def test_queue_configuration(self): queue = qoslib.QoSLib.queue_tree(self.capable_switch, self.dp) queue.queue('best-effort-queue', '100', '100') self.qoslib.register_queue(queue) mangle = qoslib.QoSLib.mangle(self.dp) mangle.add_property('action', 'mark-packet').\ add_property('new-packet-mark', 'best-effort').\ add_property('src-address', '10.0.1.0/24').\ add_property('jump', 'forward') self.qoslib.add_mangle(mangle) mangle = qoslib.QoSLib.mangle(self.dp) mangle.add_property('action', 'accept').\ add_property('queue', 'best-effort-queue').\ add_property('packet-mark', 'best-effort').\ add_property('chain', 'forward') self.qoslib.add_mangle(mangle) msg = get_flow_stats(self.dp, self.waiters, self.ofctl) flow = msg[msg.keys()[0]] LOG.info(flow) return ([{'hard_timeout': 0, 'actions': ['SET_FIELD: {ip_dscp:1}', 'GOTO_TABLE:2'], 'priority': 0, 'idle_timeout': 0, 'cookie': 0, 'table_id': 0, 'match': {'dl_type': 2048, 'nw_src': '10.0.1.0/24'}}, {'hard_timeout': 0, 'actions': ['SET_QUEUE:2', 'GOTO_TABLE:3'], 'priority': 0, 'idle_timeout': 0, 'cookie': 0, 'table_id': 2, 'match': {'dl_type': 2048, 'ip_dscp': 1}}] == flow) def _print_results(self): LOG.info("TEST_RESULTS:") ok = 0 ng = 0 skip = 0 for t in sorted(self.results.keys()): if self.results[t] is True: ok += 1 else: ng += 1 LOG.info(" %s: %s", t, self.results[t]) LOG.info(LOG_TEST_FINISH, len(self.pending), ok, ng, skip) def _do_test(self): """""" for test in self.pending: delete_all_flows(self.dp) self.results[test] = getattr(self, test)() self._print_results()	9,184	1,110	74
e644729f9f477affc4780f5fb80a7494502e4463	1,708	py	Python	orchestra/contrib/domains/utils.py	RubenPX/django-orchestra	5ab4779e1ae12ec99569d682601b7810587ed381	[ "Unlicense" ]	68	2015-02-09T10:28:44.000Z	2022-03-12T11:08:36.000Z	orchestra/contrib/domains/utils.py	RubenPX/django-orchestra	5ab4779e1ae12ec99569d682601b7810587ed381	[ "Unlicense" ]	17	2015-05-01T18:10:03.000Z	2021-03-19T21:52:55.000Z	orchestra/contrib/domains/utils.py	RubenPX/django-orchestra	5ab4779e1ae12ec99569d682601b7810587ed381	[ "Unlicense" ]	29	2015-03-31T04:51:03.000Z	2022-02-17T02:58:50.000Z	from collections import defaultdict from django.utils import timezone class RecordStorage(object): """ list-dict implementation for fast lookups of record types """ def format_hostmaster(hostmaster): """ The DNS encodes the <local-part> as a single label, and encodes the <mail-domain> as a domain name. The single label from the <local-part> is prefaced to the domain name from <mail-domain> to form the domain name corresponding to the mailbox. Thus the mailbox HOSTMASTER@SRI- NIC.ARPA is mapped into the domain name HOSTMASTER.SRI-NIC.ARPA. If the <local-part> contains dots or other special characters, its representation in a master file will require the use of backslash quoting to ensure that the domain name is properly encoded. For example, the mailbox Action.domains@ISI.EDU would be represented as Action\.domains.ISI.EDU. http://www.ietf.org/rfc/rfc1035.txt """ name, domain = hostmaster.split('@') if '.' in name: name = name.replace('.', '\.') return "%s.%s." % (name, domain)	32.226415	76	0.659251	from collections import defaultdict from django.utils import timezone class RecordStorage(object): """ list-dict implementation for fast lookups of record types """ def __init__(self, args): self.records = list(args) self.type = defaultdict(list) def __iter__(self): return iter(self.records) def append(self, record): self.records.append(record) self.type[record['type']].append(record) def insert(self, ix, record): self.records.insert(ix, record) self.type[record['type']].insert(ix, record) def by_type(self, type): return self.type[type] def generate_zone_serial(): today = timezone.now() return int("%.4d%.2d%.2d%.2d" % (today.year, today.month, today.day, 0)) def format_hostmaster(hostmaster): """ The DNS encodes the <local-part> as a single label, and encodes the <mail-domain> as a domain name. The single label from the <local-part> is prefaced to the domain name from <mail-domain> to form the domain name corresponding to the mailbox. Thus the mailbox HOSTMASTER@SRI- NIC.ARPA is mapped into the domain name HOSTMASTER.SRI-NIC.ARPA. If the <local-part> contains dots or other special characters, its representation in a master file will require the use of backslash quoting to ensure that the domain name is properly encoded. For example, the mailbox Action.domains@ISI.EDU would be represented as Action\.domains.ISI.EDU. http://www.ietf.org/rfc/rfc1035.txt """ name, domain = hostmaster.split('@') if '.' in name: name = name.replace('.', '\.') return "%s.%s." % (name, domain)	444	0	178
edae5c03b18bc54c2307cfc6aff9c4173371eb1c	5,398	py	Python	dbinit/dump.py	mrdepth/libdgmpp	2721f7f905a2c015383868db5043c382fe682ab0	[ "MIT" ]	13	2016-04-30T17:14:59.000Z	2021-08-19T01:52:38.000Z	dbinit/dump.py	mrdepth/eufe	2721f7f905a2c015383868db5043c382fe682ab0	[ "MIT" ]	7	2017-12-19T23:13:35.000Z	2018-08-02T14:14:15.000Z	dbinit/dump.py	mrdepth/eufe	2721f7f905a2c015383868db5043c382fe682ab0	[ "MIT" ]	8	2016-01-26T16:52:37.000Z	2021-10-15T08:29:48.000Z	import yaml import json import sqlite3 from functools import reduce import operator import time f=open('./tmp/sde/typeIDs.json', 'r', encoding='utf-8') j=json.load(f) #y=load("./tmp/sde/fsd/typeIDs.yaml") #f=open('./tmp/sde/typeIDs.json', 'w', encoding='utf-8') #json.dump(y, f) #f.write(json.dump(y)) #f.close() #db = sqlite3.connect(':memory:') db = sqlite3.connect("./tmp/db.sqlite") c = db.cursor() c.execute(''' CREATE TABLE invCategories ( "categoryID" tinyint(3) NOT NULL, "categoryName" TEXT(100), "published" tinyint(1), PRIMARY KEY ("categoryID") ); ''') c.execute(''' CREATE TABLE invGroups ( "groupID" smallint(6) NOT NULL, "groupName" varchar(100) DEFAULT NULL, "categoryID" tinyint(3) default NULL, "published" tinyint(1), PRIMARY KEY ("groupID") ); ''') c.execute(''' CREATE TABLE invTypes ( "typeID" int(11) NOT NULL, "groupID" smallint(6) default NULL, "typeName" varchar(100) default NULL, "radius" double default NULL, "mass" double default NULL, "volume" double default NULL, "capacity" double default NULL, "portionSize" int(11) default NULL, "raceID" tinyint(3) default NULL, "published" tinyint(1) default NULL, "metaGroupID" integer default NULL, "parentTypeID" integer default NULL, PRIMARY KEY ("typeID") ); ''') c.execute(''' CREATE TABLE dgmAttributeTypes ( "attributeID" smallint(6) NOT NULL, "attributeName" varchar(100) default NULL, "displayName" varchar(100) default NULL, "maxAttributeID" smallint(6) default NULL, "defaultValue" double default NULL, "stackable" tinyint(1) default NULL, "highIsGood" tinyint(1) default NULL, "categoryID" tinyint(3) default NULL, PRIMARY KEY ("attributeID") ); ''') c.execute(''' CREATE TABLE dgmTypeAttributes ( "typeID" smallint(6) NOT NULL, "attributeID" smallint(6) NOT NULL, "value" double default NULL, PRIMARY KEY ("typeID","attributeID") ); ''') c.execute(''' CREATE TABLE dgmTypeEffects ( "typeID" smallint(6) NOT NULL, "effectID" smallint(6) NOT NULL, "isDefault" tinyint(1) default NULL, PRIMARY KEY ("typeID","effectID") ); ''') c.execute(''' CREATE TABLE dgmEffects ( "effectID" smallint(6), "effectName" TEXT(400), "effectCategory" TEXT(100), "isOffensive" INTEGER, "isAssistance" INTEGER, "modifierInfo" TEXT, PRIMARY KEY ("effectID") ); ''') c.execute(''' CREATE TABLE planetSchematics ( "schematicID" smallint(6) NOT NULL, "schematicName" varchar(255) DEFAULT NULL, "cycleTime" integer DEFAULT NULL, PRIMARY KEY ("schematicID") ); ''') c.execute(''' CREATE TABLE planetSchematicsPinMap ( "schematicID" smallint(6) NOT NULL, "pinTypeID" integer NOT NULL, PRIMARY KEY ("schematicID","pinTypeID") ); ''') c.execute(''' CREATE TABLE planetSchematicsTypeMap ( "schematicID" smallint(6) NOT NULL, "typeID" integer NOT NULL, "quantity" integer DEFAULT NULL, "isInput" integer DEFAULT NULL, PRIMARY KEY ("schematicID","typeID") ); ''') for id, row in load("./tmp/sde/fsd/categoryIDs.yaml"): insert('invCategories', id, ['name.en', 'published'], row) for id, row in load("./tmp/sde/fsd/groupIDs.yaml"): insert('invGroups', id, ['name.en', 'categoryID', 'published'], row) for id, row in load("./tmp/sde/fsd/dogmaAttributes.yaml"): insert('dgmAttributeTypes', id, ['name', 'displayNameID.en', 'maxAttributeID', 'defaultValue', 'stackable', 'highIsGood', 'categoryID'], row) for id, row in load("./tmp/sde/fsd/dogmaEffects.yaml"): modifierInfo = find('modifierInfo', row) if modifierInfo: row['modifierInfo'] = yaml.dump(modifierInfo) insert('dgmEffects', id, ['effectName', 'effectCategory', 'isOffensive', 'isAssistance', 'modifierInfo'], row) for id, row in load("./tmp/sde/fsd/typeIDs.yaml"): insert('invTypes', id, ['groupID', 'name.en', 'radius', 'mass', 'valume', 'capacity', 'portionSize', 'raceID', 'published', 'metaGroupID', 'variationParentTypeID'], row) for id, type in load("./tmp/sde/fsd/typeDogma.yaml"): try: for row in find("dogmaAttributes", type): insert('dgmTypeAttributes', id, ['attributeID', 'value'], row) except: pass try: for row in find("dogmaEffects", type): insert('dgmTypeEffects', id, ['effectID', 'isDefault'], row) except: pass for row in load("./tmp/sde/bsd/planetSchematics.yaml"): insert('planetSchematics', row['schematicID'], ['schematicName', 'cycleTime'], row) for row in load("./tmp/sde/bsd/planetSchematicsPinMap.yaml"): insert('planetSchematicsPinMap', row['schematicID'], ['pinTypeID'], row) for row in load("./tmp/sde/bsd/planetSchematicsTypeMap.yaml"): insert('planetSchematicsTypeMap', row['schematicID'], ['typeID', 'quantity', 'isInput'], row) db.commit() db.close()	27.682051	173	0.667469	import yaml import json import sqlite3 from functools import reduce import operator import time def f(): return None def load(path): t0 = time.time() s=open(path, "r", encoding="utf-8").read() result = yaml.load(s, yaml.CLoader) if isinstance(result, dict): result = result#.items() t1 = time.time() print('yaml: {} {}s'.format(path, int((t1 - t0)))) return result f=open('./tmp/sde/typeIDs.json', 'r', encoding='utf-8') j=json.load(f) #y=load("./tmp/sde/fsd/typeIDs.yaml") #f=open('./tmp/sde/typeIDs.json', 'w', encoding='utf-8') #json.dump(y, f) #f.write(json.dump(y)) #f.close() #db = sqlite3.connect(':memory:') db = sqlite3.connect("./tmp/db.sqlite") c = db.cursor() c.execute(''' CREATE TABLE invCategories ( "categoryID" tinyint(3) NOT NULL, "categoryName" TEXT(100), "published" tinyint(1), PRIMARY KEY ("categoryID") ); ''') c.execute(''' CREATE TABLE invGroups ( "groupID" smallint(6) NOT NULL, "groupName" varchar(100) DEFAULT NULL, "categoryID" tinyint(3) default NULL, "published" tinyint(1), PRIMARY KEY ("groupID") ); ''') c.execute(''' CREATE TABLE invTypes ( "typeID" int(11) NOT NULL, "groupID" smallint(6) default NULL, "typeName" varchar(100) default NULL, "radius" double default NULL, "mass" double default NULL, "volume" double default NULL, "capacity" double default NULL, "portionSize" int(11) default NULL, "raceID" tinyint(3) default NULL, "published" tinyint(1) default NULL, "metaGroupID" integer default NULL, "parentTypeID" integer default NULL, PRIMARY KEY ("typeID") ); ''') c.execute(''' CREATE TABLE dgmAttributeTypes ( "attributeID" smallint(6) NOT NULL, "attributeName" varchar(100) default NULL, "displayName" varchar(100) default NULL, "maxAttributeID" smallint(6) default NULL, "defaultValue" double default NULL, "stackable" tinyint(1) default NULL, "highIsGood" tinyint(1) default NULL, "categoryID" tinyint(3) default NULL, PRIMARY KEY ("attributeID") ); ''') c.execute(''' CREATE TABLE dgmTypeAttributes ( "typeID" smallint(6) NOT NULL, "attributeID" smallint(6) NOT NULL, "value" double default NULL, PRIMARY KEY ("typeID","attributeID") ); ''') c.execute(''' CREATE TABLE dgmTypeEffects ( "typeID" smallint(6) NOT NULL, "effectID" smallint(6) NOT NULL, "isDefault" tinyint(1) default NULL, PRIMARY KEY ("typeID","effectID") ); ''') c.execute(''' CREATE TABLE dgmEffects ( "effectID" smallint(6), "effectName" TEXT(400), "effectCategory" TEXT(100), "isOffensive" INTEGER, "isAssistance" INTEGER, "modifierInfo" TEXT, PRIMARY KEY ("effectID") ); ''') c.execute(''' CREATE TABLE planetSchematics ( "schematicID" smallint(6) NOT NULL, "schematicName" varchar(255) DEFAULT NULL, "cycleTime" integer DEFAULT NULL, PRIMARY KEY ("schematicID") ); ''') c.execute(''' CREATE TABLE planetSchematicsPinMap ( "schematicID" smallint(6) NOT NULL, "pinTypeID" integer NOT NULL, PRIMARY KEY ("schematicID","pinTypeID") ); ''') c.execute(''' CREATE TABLE planetSchematicsTypeMap ( "schematicID" smallint(6) NOT NULL, "typeID" integer NOT NULL, "quantity" integer DEFAULT NULL, "isInput" integer DEFAULT NULL, PRIMARY KEY ("schematicID","typeID") ); ''') def find(element, json): try: return reduce(operator.getitem, element.split('.'), json) except: return None def insert(table, id, keys, row): values=[id] + [find(x, row) for x in keys] marks = ','.join(['?' for x in values]) sql='INSERT INTO {} VALUES ({})'.format(table, marks) c.execute(sql, tuple(values)) for id, row in load("./tmp/sde/fsd/categoryIDs.yaml"): insert('invCategories', id, ['name.en', 'published'], row) for id, row in load("./tmp/sde/fsd/groupIDs.yaml"): insert('invGroups', id, ['name.en', 'categoryID', 'published'], row) for id, row in load("./tmp/sde/fsd/dogmaAttributes.yaml"): insert('dgmAttributeTypes', id, ['name', 'displayNameID.en', 'maxAttributeID', 'defaultValue', 'stackable', 'highIsGood', 'categoryID'], row) for id, row in load("./tmp/sde/fsd/dogmaEffects.yaml"): modifierInfo = find('modifierInfo', row) if modifierInfo: row['modifierInfo'] = yaml.dump(modifierInfo) insert('dgmEffects', id, ['effectName', 'effectCategory', 'isOffensive', 'isAssistance', 'modifierInfo'], row) for id, row in load("./tmp/sde/fsd/typeIDs.yaml"): insert('invTypes', id, ['groupID', 'name.en', 'radius', 'mass', 'valume', 'capacity', 'portionSize', 'raceID', 'published', 'metaGroupID', 'variationParentTypeID'], row) for id, type in load("./tmp/sde/fsd/typeDogma.yaml"): try: for row in find("dogmaAttributes", type): insert('dgmTypeAttributes', id, ['attributeID', 'value'], row) except: pass try: for row in find("dogmaEffects", type): insert('dgmTypeEffects', id, ['effectID', 'isDefault'], row) except: pass for row in load("./tmp/sde/bsd/planetSchematics.yaml"): insert('planetSchematics', row['schematicID'], ['schematicName', 'cycleTime'], row) for row in load("./tmp/sde/bsd/planetSchematicsPinMap.yaml"): insert('planetSchematicsPinMap', row['schematicID'], ['pinTypeID'], row) for row in load("./tmp/sde/bsd/planetSchematicsTypeMap.yaml"): insert('planetSchematicsTypeMap', row['schematicID'], ['typeID', 'quantity', 'isInput'], row) db.commit() db.close()	570	0	91
35dca39e0121540a436f6da96d93d03e4d00edc2	689	py	Python	tests/theano/__init__.py	brandonwillard/symbolic-pymc	84e8d612c714f502f8d188c1766498f4ff7beecf	[ "Apache-2.0" ]	59	2019-02-16T21:07:48.000Z	2022-03-09T01:01:45.000Z	tests/theano/__init__.py	brandonwillard/symbolic-pymc	84e8d612c714f502f8d188c1766498f4ff7beecf	[ "Apache-2.0" ]	56	2019-02-20T09:06:04.000Z	2021-01-08T21:22:23.000Z	tests/theano/__init__.py	brandonwillard/symbolic-pymc	84e8d612c714f502f8d188c1766498f4ff7beecf	[ "Apache-2.0" ]	9	2019-02-22T06:22:31.000Z	2021-07-05T10:05:35.000Z	import warnings with warnings.catch_warnings(): warnings.filterwarnings("ignore", category=DeprecationWarning) import theano import pymc3 as pm from functools import wraps theano.config.compute_test_value = "ignore" theano.config.on_opt_error = "raise" theano.config.mode = "FAST_COMPILE" theano.config.cxx = ""	19.685714	66	0.676343	import warnings with warnings.catch_warnings(): warnings.filterwarnings("ignore", category=DeprecationWarning) import theano import pymc3 as pm from functools import wraps theano.config.compute_test_value = "ignore" theano.config.on_opt_error = "raise" theano.config.mode = "FAST_COMPILE" theano.config.cxx = "" def requires_test_values(f): @wraps(f) def _f(args, kwargs): import theano last_value = theano.config.compute_test_value theano.config.compute_test_value = "raise" try: res = f(args, **kwargs) finally: theano.config.compute_test_value = last_value return res return _f	340	0	23
70778d96d5999b4ef52cb4dde6e9df7135bb617c	13,904	py	Python	Segmentation/eval_performance.py	atomized1/MRI_Segmentation_Radiomics	3998dd26b60972f41d3b397cecdad16563df4189	[ "Apache-2.0" ]	12	2020-02-14T05:33:24.000Z	2022-01-13T16:37:44.000Z	Segmentation/eval_performance.py	atomized1/MRI_Segmentation_Radiomics	3998dd26b60972f41d3b397cecdad16563df4189	[ "Apache-2.0" ]	3	2020-01-28T22:20:08.000Z	2022-02-09T23:33:30.000Z	Segmentation/eval_performance.py	atomized1/MRI_Segmentation_Radiomics	3998dd26b60972f41d3b397cecdad16563df4189	[ "Apache-2.0" ]	4	2020-06-12T02:59:55.000Z	2021-08-20T05:42:34.000Z	import os from MachineLearning.load_datasets import load_filenames_2nd, load_data, keep_t2 from glob2 import glob import nibabel as nib import numpy as np import keras from Segmentation.model_keras import * from sklearn.metrics import precision_recall_curve, precision_score, \ recall_score, roc_auc_score, f1_score, \ precision_recall_fscore_support, matthews_corrcoef, jaccard_similarity_score, accuracy_score import pandas as pd from pylab import rcParams import seaborn as sns # Set up plotting properties sns.set(style='ticks', palette='Spectral', font_scale=1.5) rcParams['figure.figsize'] = 6, 4 RAND_SEED = 42 def load_models(paths): """ Loads a list of models Args: paths (list): list of paths to models (not including the filename) Returns: """ model = [] for path in paths: model_path = os.path.join(path, 'Trained_model.h5') model.append(keras.models.load_model(model_path, custom_objects={'dice_loss': dice_loss, 'dice_metric': dice_metric})) return model def score_pred(Y_lab, Y_prob, threshold): """ Calculate a set of scores for the predictions Args: Y_lab (numpy array): labels Y_prob (numpy array): predictions as probablilities threshold (float): threshold for predictions Returns: (float): precision (float): recall (float): f1 score (Dice) (float): support (float): volume overlap error (float): binary accuracy """ Y_thresh = Y_prob >= threshold precision = [] recall = [] fbeta_score = [] support = [] voe = [] acc = [] Y_lab = Y_lab.reshape(-1) Y_thresh = Y_thresh.reshape(-1) # Compute precision/recall scores scores = precision_recall_fscore_support(y_true=Y_lab, y_pred=Y_thresh) precision.append(scores[0][1]) recall.append(scores[1][1]) fbeta_score.append(scores[2][1]) support.append(scores[3][1]/(scores[3][0] + scores[3][1])) # percent of volume occupied by tumor voe.append(jaccard_similarity_score(y_true=Y_lab, y_pred=Y_thresh)) acc.append(accuracy_score(y_true=Y_lab, y_pred=Y_thresh, normalize=True)) return precision, recall, fbeta_score, support, voe, acc def main(paths, spath): """ Args: paths (list of str): path to t2_only and all_contrast models thresholds (list of float): training thresholds Returns: """ # Set up data constants block_size = [18, 142, 142] oversamp_test = 1.0 lab_trun = 2 test_split = 0.1 # Load models models = load_models(paths) # Set up data generator gen_t2 = load_test_volumes(only_t2=True) gen = load_test_volumes() nsets = next(gen) nsets = next(gen_t2) print('Testing using {} sets'.format(nsets)) # Set up metric lists df = pd.DataFrame(columns=['Loss', 'Data', 'Precision', 'Recall', 'Dice', 'Support', 'VOE', 'Accuracy']) df_cat = pd.DataFrame(columns=['Loss', 'Data', 'Metric', 'Value']) # Concatenated dataframe contrasts = ['Multi-modal', 'T2 only'] con_lab = ['t2', 'all'] # Process clear_vol_stats() thresholds = [] flag = True z = 0 while flag: try: print('\tVolume %d' % (z + 1)) print('Loading test batch') [xall, yall, szall] = next(gen) [xt2, yt2, szt2] = next(gen_t2) for model, path in zip(models, paths): # Load model threshold file = os.path.join(path, 'metrics2.txt') with open(file, 'r') as f: dat = f.readlines() thr_ind = -7 tmp = [i for i in dat[thr_ind] if i.isdigit() or i == '.'] threshold = float(''.join(tmp)) thresholds.append(threshold) # Get model loss if 'dice' in path.lower(): loss = 'Dice' else: loss = 'Xentropy' # Get skip status if 'skip' in path.lower(): skip = 'Yes' else: skip = 'No' # Get number of model inputs mod_input_ch = model.input_shape[-1] # Get correct contrast if mod_input_ch == 1: x, y, sz = xt2, yt2, szt2 contrast = contrasts[1] else: x, y, sz = xall, yall, szall contrast = contrasts[0] # Predict using model print('Making predictions') y_pred = model.predict(x) # Compute metrics print('Evaluating predictions') res = score_pred(y, y_pred, threshold) # Concatenate metrics df = df.append(pd.DataFrame({'Loss': loss, 'Data': contrast, 'Skip': skip, 'Precision': res[0], 'Recall': res[1], 'Dice': res[2], 'Support': res[3], 'VOE': res[4], 'Accuracy': res[5] })) for ii in range(6): df_cat = df_cat.append(pd.DataFrame({'Loss': loss, 'Data': contrast, 'Metric': df.keys()[ii+3], 'Value': res[ii] })) # Reconstruct images # _, y = recon_test_3D(X=x, Y=y, orig_size=sz, block_size=block_size, oversamp=oversamp_test, # lab_trun=lab_trun) # x, y_pred = recon_test_3D(X=x, Y=y_pred, orig_size=sz, block_size=block_size, oversamp=oversamp_test, # lab_trun=lab_trun) # # # Swap axes # x = np.rollaxis(x, 0, 2).swapaxes(1, 2) # y = np.rollaxis(y, 0, 2).swapaxes(1, 2) # y_pred = np.rollaxis(y_pred, 0, 2).swapaxes(1, 2) # Threshold segmentation y_thresh = y_pred > threshold # Record volume measurements write_volumes(y, y_thresh, spath) z += 1 except StopIteration: print('Exhausted generator') flag = False # Plot results # print('Saving plots') # plot_results_cat(df_cat, spath) # plot_results(df, spath) # Write statistics write_stats(df, thresholds, spath) # Update dataframes to include stds losses = df['Loss'].unique().tolist() datas = df['Data'].unique().tolist() skips = df['Skip'].unique().tolist() metrics = ['Accuracy', 'Dice', 'Precision', 'Recall', 'Support', 'VOE'] df_out = {i: [] for i in df.keys()} for loss in losses: ind1 = df['Loss'] == loss for data in datas: ind2 = df['Data'] == data for skip in skips: ind3 = df['Skip'] == skip # Create output df df_out['Loss'].append(loss) df_out['Data'].append(data) df_out['Skip'].append(skip) for metric in metrics: # Get measurements vals = df.loc[ind1 & ind2 & ind3, metric] df_out[metric].append('{:0.3f} \xb1 {:0.3f}'.format(vals.mean(), vals.std())) # std_metric = metric + '_std' # df_out[std_metric].append(vals.std()) df_out = pd.DataFrame.from_dict(df_out) # Save dataframes print('Saving data') save_df(df_out, spath, descriptor='metrics') save_df(df_cat, spath, descriptor='cat') if __name__ == '__main__': """ Example of how to test train networks. """ paths = ['/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_08_14-36-46_cnn_model_3D_3lyr_relu_dice', '/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_08_21-50-21_cnn_model_3D_3lyr_do_relu_dice_skip', '/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_09_06-49-45_cnn_model_3D_3lyr_do_relu_xentropy', '/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_09_14-12-47_cnn_model_3D_3lyr_do_relu_xentropy_skip', '/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_09_23-04-28_t2_cnn_model_3D_3lyr_relu_dice', '/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_10_04-50-05_t2_cnn_model_3D_3lyr_do_relu_dice_skip', '/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_10_12-28-23_t2_cnn_model_3D_3lyr_do_relu_xentropy', '/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_10_18-43-24_t2_cnn_model_3D_3lyr_do_relu_xentropy_skip'] spath = '/media/matt/Seagate Expansion Drive/b7TData_19/b7TData/Results/Analysis/Segmentation_images' main(paths, spath)	30.897778	133	0.562572	import os from MachineLearning.load_datasets import load_filenames_2nd, load_data, keep_t2 from glob2 import glob import nibabel as nib import numpy as np import keras from Segmentation.model_keras import * from sklearn.metrics import precision_recall_curve, precision_score, \ recall_score, roc_auc_score, f1_score, \ precision_recall_fscore_support, matthews_corrcoef, jaccard_similarity_score, accuracy_score import pandas as pd from pylab import rcParams import seaborn as sns # Set up plotting properties sns.set(style='ticks', palette='Spectral', font_scale=1.5) rcParams['figure.figsize'] = 6, 4 RAND_SEED = 42 def load_test_volumes(only_t2=False, adaptive_hist=False): # Set up image path image_base_path = '/media/matt/Seagate Expansion Drive/MR Data/MR_Images_Sarcoma' # Set up data constants block_size = [18, 142, 142] oversamp_test = 1.0 lab_trun = 2 test_split = 0.1 # Get filenames filenames = load_filenames_2nd(base_path=image_base_path) nfiles = len(filenames) if only_t2: filenames = keep_t2(filenames) # Remove validation and test set inds = np.array((range(nfiles)), dtype=int) np.random.seed(RAND_SEED) np.random.shuffle(inds) # Test data test_inds = inds[-round(test_splitnfiles):] test_files = [filenames[i] for i in test_inds] # Yield the number of sets in the generator yield test_files for test_file in test_files: X_test, Y_test, orig_size_test = load_data([test_file], block_size, oversamp_test, lab_trun, adaptive_hist) yield [X_test, Y_test, orig_size_test] def load_models(paths): """ Loads a list of models Args: paths (list): list of paths to models (not including the filename) Returns: """ model = [] for path in paths: model_path = os.path.join(path, 'Trained_model.h5') model.append(keras.models.load_model(model_path, custom_objects={'dice_loss': dice_loss, 'dice_metric': dice_metric})) return model def score_pred(Y_lab, Y_prob, threshold): """ Calculate a set of scores for the predictions Args: Y_lab (numpy array): labels Y_prob (numpy array): predictions as probablilities threshold (float): threshold for predictions Returns: (float): precision (float): recall (float): f1 score (Dice) (float): support (float): volume overlap error (float): binary accuracy """ Y_thresh = Y_prob >= threshold precision = [] recall = [] fbeta_score = [] support = [] voe = [] acc = [] Y_lab = Y_lab.reshape(-1) Y_thresh = Y_thresh.reshape(-1) # Compute precision/recall scores scores = precision_recall_fscore_support(y_true=Y_lab, y_pred=Y_thresh) precision.append(scores[0][1]) recall.append(scores[1][1]) fbeta_score.append(scores[2][1]) support.append(scores[3][1]/(scores[3][0] + scores[3][1])) # percent of volume occupied by tumor voe.append(jaccard_similarity_score(y_true=Y_lab, y_pred=Y_thresh)) acc.append(accuracy_score(y_true=Y_lab, y_pred=Y_thresh, normalize=True)) return precision, recall, fbeta_score, support, voe, acc def plot_results_cat(df, spath): # Remove support and accuracy df = df.loc[df['Metric'] !='Accuracy'] df = df.loc[df['Metric'] !='Support'] # Plot results plt.figure(1) sns.swarmplot(x='Metric', y='Value', hue='Data', data=df, size=10, dodge=True) # plt.grid() plt.ylabel('Coefficient') plt.tight_layout() plt.savefig(os.path.join(spath, 'cat_plot_1901.svg'), dpi=300) plt.show() def plot_results(df, spath): plt.figure(11) sns.swarmplot(x='Data', y='Precision', data=df, size=10) plt.grid() plt.ylabel('Precision Coefficient') plt.tight_layout() plt.savefig(os.path.join(spath, 'prec_1901.svg'), dpi=300) plt.figure(12) sns.swarmplot(x='Data', y='Recall', data=df, size=10) plt.grid() plt.ylabel('Recall Coefficient') plt.tight_layout() plt.savefig(os.path.join(spath, 'rec_1901.svg'), dpi=300) plt.figure(13) sns.swarmplot(x='Data', y='dice', data=df, size=10) plt.grid() plt.ylabel('DICE Coefficient') plt.tight_layout() plt.savefig(os.path.join(spath, 'dice_1901.svg'), dpi=300) plt.figure(14) sns.swarmplot(x='Data', y='Support', data=df, size=10) plt.grid() plt.ylabel('Support Coefficient') plt.tight_layout() plt.savefig(os.path.join(spath, 'support_1901.svg'), dpi=300) plt.figure(15) sns.swarmplot(x='Data', y='VOE', data=df, size=10) plt.grid() plt.ylabel('VOE Coefficient') plt.tight_layout() plt.savefig(os.path.join(spath, 'VOE_1901.svg'), dpi=300) plt.figure(16) sns.swarmplot(x='Data', y='Accuracy', data=df, size=10) plt.grid() plt.ylabel('Accuracy') plt.tight_layout() plt.savefig(os.path.join(spath, 'accuracy_1901.svg'), dpi=300) plt.show() def write_stats(df, thresholds, spath): f = open(os.path.join(spath, 'stats.txt'), 'w') f.write('T2\n') f.write(20'-' + '\n') f.write('Threshold: %0.3f\n' % thresholds[0]) f.write('Mean:\n') a = df.loc[df['Data'] == 'T2'] f.write(a.mean().to_string()) f.write('\n\nStd:\n') f.write(a.std().to_string()) f.write(3'\n') a = df.loc[df['Data'] == 'T1, T1C, T2'] f.write('T1, T1C, T2\n') f.write(20'-' + '\n') f.write('Threshold: %0.3f\n' % thresholds[1]) f.write('Mean:\n') f.write(a.mean().to_string()) f.write('\n\nStd:\n') f.write(a.std().to_string()) f.close() def clear_vol_stats(): f = open(os.path.join(spath, 'volumes.txt'), 'w') f.close() def write_volumes(Y, Y_pred, spath): y_vol = Y.sum() pred_vol = Y_pred.sum() f = open(os.path.join(spath, 'volumes.txt'), 'a') f.write('Label: %d\tPrediction: %d\tPercent:\%0.3f\n' % (y_vol, pred_vol, 100y_vol/pred_vol)) f.close() def save_df(df, spath, descriptor): df.to_csv(os.path.join(spath, 'data_%s.csv' % descriptor)) def run_from_df(spath): # Load concatenated dataframe template = 'cat.csv' file = glob(os.path.join(spath, template)) df_cat = pd.DataFrame.from_csv(file) # Load metrics dataframe template = '*metrics.csv' file = glob(os.path.join(spath, template)) df = pd.DataFrame.from_csv(file) # Write statistics write_stats(df, spath) # Plot results plot_results(df, spath) plot_results_cat(df_cat, spath) def main(paths, spath): """ Args: paths (list of str): path to t2_only and all_contrast models thresholds (list of float): training thresholds Returns: """ # Set up data constants block_size = [18, 142, 142] oversamp_test = 1.0 lab_trun = 2 test_split = 0.1 # Load models models = load_models(paths) # Set up data generator gen_t2 = load_test_volumes(only_t2=True) gen = load_test_volumes() nsets = next(gen) nsets = next(gen_t2) print('Testing using {} sets'.format(nsets)) # Set up metric lists df = pd.DataFrame(columns=['Loss', 'Data', 'Precision', 'Recall', 'Dice', 'Support', 'VOE', 'Accuracy']) df_cat = pd.DataFrame(columns=['Loss', 'Data', 'Metric', 'Value']) # Concatenated dataframe contrasts = ['Multi-modal', 'T2 only'] con_lab = ['t2', 'all'] # Process clear_vol_stats() thresholds = [] flag = True z = 0 while flag: try: print('\tVolume %d' % (z + 1)) print('Loading test batch') [xall, yall, szall] = next(gen) [xt2, yt2, szt2] = next(gen_t2) for model, path in zip(models, paths): # Load model threshold file = os.path.join(path, 'metrics2.txt') with open(file, 'r') as f: dat = f.readlines() thr_ind = -7 tmp = [i for i in dat[thr_ind] if i.isdigit() or i == '.'] threshold = float(''.join(tmp)) thresholds.append(threshold) # Get model loss if 'dice' in path.lower(): loss = 'Dice' else: loss = 'Xentropy' # Get skip status if 'skip' in path.lower(): skip = 'Yes' else: skip = 'No' # Get number of model inputs mod_input_ch = model.input_shape[-1] # Get correct contrast if mod_input_ch == 1: x, y, sz = xt2, yt2, szt2 contrast = contrasts[1] else: x, y, sz = xall, yall, szall contrast = contrasts[0] # Predict using model print('Making predictions') y_pred = model.predict(x) # Compute metrics print('Evaluating predictions') res = score_pred(y, y_pred, threshold) # Concatenate metrics df = df.append(pd.DataFrame({'Loss': loss, 'Data': contrast, 'Skip': skip, 'Precision': res[0], 'Recall': res[1], 'Dice': res[2], 'Support': res[3], 'VOE': res[4], 'Accuracy': res[5] })) for ii in range(6): df_cat = df_cat.append(pd.DataFrame({'Loss': loss, 'Data': contrast, 'Metric': df.keys()[ii+3], 'Value': res[ii] })) # Reconstruct images # _, y = recon_test_3D(X=x, Y=y, orig_size=sz, block_size=block_size, oversamp=oversamp_test, # lab_trun=lab_trun) # x, y_pred = recon_test_3D(X=x, Y=y_pred, orig_size=sz, block_size=block_size, oversamp=oversamp_test, # lab_trun=lab_trun) # # # Swap axes # x = np.rollaxis(x, 0, 2).swapaxes(1, 2) # y = np.rollaxis(y, 0, 2).swapaxes(1, 2) # y_pred = np.rollaxis(y_pred, 0, 2).swapaxes(1, 2) # Threshold segmentation y_thresh = y_pred > threshold # Record volume measurements write_volumes(y, y_thresh, spath) z += 1 except StopIteration: print('Exhausted generator') flag = False # Plot results # print('Saving plots') # plot_results_cat(df_cat, spath) # plot_results(df, spath) # Write statistics write_stats(df, thresholds, spath) # Update dataframes to include stds losses = df['Loss'].unique().tolist() datas = df['Data'].unique().tolist() skips = df['Skip'].unique().tolist() metrics = ['Accuracy', 'Dice', 'Precision', 'Recall', 'Support', 'VOE'] df_out = {i: [] for i in df.keys()} for loss in losses: ind1 = df['Loss'] == loss for data in datas: ind2 = df['Data'] == data for skip in skips: ind3 = df['Skip'] == skip # Create output df df_out['Loss'].append(loss) df_out['Data'].append(data) df_out['Skip'].append(skip) for metric in metrics: # Get measurements vals = df.loc[ind1 & ind2 & ind3, metric] df_out[metric].append('{:0.3f} \xb1 {:0.3f}'.format(vals.mean(), vals.std())) # std_metric = metric + '_std' # df_out[std_metric].append(vals.std()) df_out = pd.DataFrame.from_dict(df_out) # Save dataframes print('Saving data') save_df(df_out, spath, descriptor='metrics') save_df(df_cat, spath, descriptor='cat') if __name__ == '__main__': """ Example of how to test train networks. """ paths = ['/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_08_14-36-46_cnn_model_3D_3lyr_relu_dice', '/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_08_21-50-21_cnn_model_3D_3lyr_do_relu_dice_skip', '/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_09_06-49-45_cnn_model_3D_3lyr_do_relu_xentropy', '/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_09_14-12-47_cnn_model_3D_3lyr_do_relu_xentropy_skip', '/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_09_23-04-28_t2_cnn_model_3D_3lyr_relu_dice', '/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_10_04-50-05_t2_cnn_model_3D_3lyr_do_relu_dice_skip', '/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_10_12-28-23_t2_cnn_model_3D_3lyr_do_relu_xentropy', '/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_10_18-43-24_t2_cnn_model_3D_3lyr_do_relu_xentropy_skip'] spath = '/media/matt/Seagate Expansion Drive/b7TData_19/b7TData/Results/Analysis/Segmentation_images' main(paths, spath)	4,222	0	184
e1aab230d47c97b07e835f65d3a577d40d2af698	9,585	py	Python	fixed_stack_in_order_models.py	ekayen/rnng-pytorch	4cdfcb62f18a214011a8ea4c034fbf9041ac6012	[ "MIT" ]	null	null	null	fixed_stack_in_order_models.py	ekayen/rnng-pytorch	4cdfcb62f18a214011a8ea4c034fbf9041ac6012	[ "MIT" ]	null	null	null	fixed_stack_in_order_models.py	ekayen/rnng-pytorch	4cdfcb62f18a214011a8ea4c034fbf9041ac6012	[ "MIT" ]	null	null	null	import torch from torch import nn import torch.nn.functional as F from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence import numpy as np from fixed_stack_models import BeamItems, FixedStack, FixedStackRNNG, StackState	49.407216	121	0.676474	import torch from torch import nn import torch.nn.functional as F from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence import numpy as np from fixed_stack_models import BeamItems, FixedStack, FixedStackRNNG, StackState class FixedInOrderStack(FixedStack): def __init__(self, initial_hidden, stack_size, input_size, beam_size = 1): super(FixedInOrderStack, self).__init__(initial_hidden, stack_size, input_size, beam_size) # An extra storage necessary to achieve correct in-order implementation for subwords. self.last_subword_begin_idx = self.nt_index_pos.new_zeros(self.nt_index_pos.size()) self.attrs += ['last_subword_begin_idx'] def do_shift(self, shift_batches, shifted_embs, subword_end_mask): super().do_shift(shift_batches, shifted_embs, subword_end_mask) # Extra operations to update last_subword_begin_idx. is_begin_subword = ( subword_end_mask[(shift_batches[0], self.pointer[shift_batches]-2,)] + (self.pointer[shift_batches] == 1) # pointer==1 after shift means this is first shifted token ) # (shifted_batch_size,) begin_subword_shift_batches = tuple([item[is_begin_subword] for item in shift_batches]) self.last_subword_begin_idx[begin_subword_shift_batches] \ = self.top_position[begin_subword_shift_batches] def do_nt(self, nt_batches, nt_embs, nt_ids): subword_begin_idx = self.last_subword_begin_idx[nt_batches] subword_span_length = self.top_position[nt_batches]+1 - subword_begin_idx max_span_length = subword_span_length.max() span_idx_order = (torch.arange(max_span_length, device=subword_begin_idx.device) .unsqueeze(0).repeat(subword_begin_idx.size(0), 1)) span_idx_mask = (span_idx_order < subword_span_length.unsqueeze(-1)).view(-1) span_idx = (subword_begin_idx.unsqueeze(-1) + span_idx_order).view(-1)[span_idx_mask] - 1 nt_batches_for_move = () for nt_batch in nt_batches: nt_batches_for_move += ( nt_batch.unsqueeze(-1).expand(-1, max_span_length).reshape(-1)[span_idx_mask], ) nt_batches_for_move += (span_idx,) # reason why not +1 here is due to offset of self.trees relative to self.hiddens. nt_batches_for_move_tgt = nt_batches_for_move[:-1] + (nt_batches_for_move[-1] + 1,) self.trees[nt_batches_for_move_tgt] = self.trees[nt_batches_for_move] self.trees[nt_batches + (subword_begin_idx-1,)] = nt_embs self.nt_index_pos[nt_batches] = self.nt_index_pos[nt_batches] + 1 self.nt_ids[nt_batches + (self.nt_index_pos[nt_batches],)] = nt_ids self.top_position[nt_batches] = self.top_position[nt_batches] + 1 self.nt_index[nt_batches + (self.nt_index_pos[nt_batches],)] = subword_begin_idx def do_reduce(self, reduce_batches, new_child): super().do_reduce(reduce_batches, new_child) self.last_subword_begin_idx[reduce_batches] = self.top_position[reduce_batches] class InOrderStackState(StackState): def __init__(self, batch_size, beam_size, device): super(InOrderStackState, self).__init__(batch_size, beam_size, device) def update_nt_counts(self, actions, action_dict, action_path): shift_idxs = (actions == action_dict.a2i['SHIFT']).nonzero(as_tuple=True) nt_idxs = (actions >= action_dict.nt_begin_id()).nonzero(as_tuple=True) reduce_idxs = (actions == action_dict.a2i['REDUCE']).nonzero(as_tuple=True) prev_is_not_nt = (action_path.prev_actions() < action_dict.nt_begin_id()) self.ncons_nts[shift_idxs] = 0 self.nopen_parens[nt_idxs] += 1 self.ncons_nts[nt_idxs] += 1 self.nopen_parens[reduce_idxs] -= 1 # To regard repetitive nt->reduce->nt->reduce ... as cons nts, # we don't reset ncons_nts if previous action is nt. reset_ncons_reduce_mask = (actions == action_dict.a2i['REDUCE']) * (prev_is_not_nt) self.ncons_nts[reset_ncons_reduce_mask] = 0 class FixedStackInOrderRNNG(FixedStackRNNG): def __init__(self, action_dict, vocab = 100, padding_idx = 0, w_dim = 20, h_dim = 20, num_layers = 1, dropout = 0, attention_composition = False, max_open_nts = 100, max_cons_nts = 3, speech_feat_types = None, tok_frame_len=100, token_lookahead = False, back_context = 0, for_context = 0 ): super(FixedStackInOrderRNNG, self).__init__( action_dict, vocab, padding_idx, w_dim, h_dim, num_layers, dropout, attention_composition, max_open_nts, max_cons_nts, speech_feat_types,tok_frame_len,token_lookahead, back_context,for_context) print(f'token lookahead in in order model init: {token_lookahead}') def build_stack(self, x, batch_size = None): stack_size = max(150, x.size(1) + 10) initial_hidden = self.rnng.get_initial_hidden(x) return FixedInOrderStack(initial_hidden, stack_size, self.input_size) def new_beam_stack_with_state(self, initial_hidden, stack_size, beam_size): stack = FixedInOrderStack(initial_hidden, stack_size, self.input_size, beam_size) stack_state = InOrderStackState(initial_hidden[0].size(0), beam_size, initial_hidden[0].device) return stack, stack_state def invalid_action_mask(self, beam, sent_lengths, subword_end_mask): action_order = torch.arange(self.num_actions, device=beam.nopen_parens.device) nopen_parens = beam.nopen_parens ncons_nts = beam.ncons_nts pointer = beam.stack.pointer top_position = beam.stack.top_position prev_actions = beam.prev_actions() sent_lengths = sent_lengths.unsqueeze(-1) # add beam dim # For in-order, cons_nts is accumuated by the loop of nt->reduce. # Except sentence final, we prohibit reduce to break this loop. Otherwise, # we fall into the state of one element in the stack, which prohibits following # shift (-> no way to escape). # # We instead prohibit nt for sentence final, because we need to close all # incomplete brackets. # This mask is a precondition used both for reduce_mask and reduce_nt # (depending on sentence final or not). pre_nt_reduce_mask = ((nopen_parens > self.max_open_nts-1) + (ncons_nts > self.max_cons_nts-1)) prev_pointer = beam.stack.pointer - 1 prev_prev_pointer = beam.stack.pointer - 2 prev_pointer[prev_pointer < 0] = 0 prev_prev_pointer[prev_prev_pointer < 0] = 0 prev_is_subword_mask = (beam.stack.pointer > 0) * (subword_end_mask.gather(1, prev_pointer) == 0) prev_is_subword_end_mask = ((beam.stack.pointer > 0) * subword_end_mask.gather(1, prev_pointer)) # reduce_mask[i,j,k]=True means k is a not allowed reduce action for (i,j). reduce_mask = (action_order == self.action_dict.a2i['REDUCE']).view(1, 1, -1) reduce_mask = (((nopen_parens == 0) + (pre_nt_reduce_mask * (pointer < sent_lengths)) + # reduce is only allowed when prev is not subword prev_is_subword_mask).unsqueeze(-1) * reduce_mask) finish_mask = (action_order == self.action_dict.finish_action()).view(1, 1, -1) finish_mask = (((pointer != sent_lengths) + (nopen_parens != 0) + (top_position != 1)).unsqueeze(-1) * finish_mask) shift_mask = (action_order == self.action_dict.a2i['SHIFT']).view(1, 1, -1) shift_mask = (((pointer == sent_lengths) + ((pointer > 0) * (nopen_parens == 0) * prev_is_subword_end_mask) + # when nopen=0, shift accompanies nt, thus requires two. ((nopen_parens == 0) * (top_position >= beam.stack.stack_size-2)) + # otherwise, requires one room. ((nopen_parens > 0) * (top_position >= beam.stack.stack_size-1))).unsqueeze(-1) * shift_mask) nt_mask = (action_order >= self.action_dict.nt_begin_id()).view(1, 1, -1) prev_is_nt = prev_actions >= self.action_dict.nt_begin_id() nt_mask = ((prev_is_nt + (top_position == 0) + # prohibit nt version of pre_nt_reduce_mask (reduce is prohibited except empty buffer) (pre_nt_reduce_mask * (pointer == sent_lengths)) + # reduce is allowed after nt, so minimal room for stack is 1. (top_position >= beam.stack.stack_size-1) + # +3 for the same reason as top-down parser; +1 for final finish. (beam.actions.size(2) - beam.actions_pos < ( sent_lengths - beam.stack.pointer + beam.nopen_parens + 4)) + # shift->nt is prohibited when shifted token is an (unfinished) subword (prev_is_subword_mask * (prev_actions == self.action_dict.a2i['SHIFT']))).unsqueeze(-1) * nt_mask) pad_mask = (action_order == self.action_dict.padding_idx).view(1, 1, -1) finished_mask = ((prev_actions == self.action_dict.finish_action()) + (prev_actions == self.action_dict.padding_idx)).unsqueeze(-1) beam_width_mask = (torch.arange(beam.beam_size, device=reduce_mask.device).unsqueeze(0) >= beam.beam_widths.unsqueeze(1)).unsqueeze(-1) return (reduce_mask + finish_mask + shift_mask + nt_mask + pad_mask + finished_mask + beam_width_mask) def _parse_finish_mask(self, beam, action_id, beam_id): return action_id == self.action_dict.finish_action()	8,951	53	340
9be6fb310c07fcd88eaec8696898000d5997cbdc	1,510	py	Python	linear_models/perceptron.py	lkk7/ml-library	bf338eb0d0f566ccb0fc51f27e04fafa1215ef93	[ "MIT" ]	null	null	null	linear_models/perceptron.py	lkk7/ml-library	bf338eb0d0f566ccb0fc51f27e04fafa1215ef93	[ "MIT" ]	null	null	null	linear_models/perceptron.py	lkk7/ml-library	bf338eb0d0f566ccb0fc51f27e04fafa1215ef93	[ "MIT" ]	null	null	null	import numpy as np from linear_models.logistic_regression import LogisticRegression class Perceptron(LogisticRegression): """A simple (binary classification) perceptron. Uses binary cross-entropy loss for updating weights. >>NOTE: it inherits most of the code from logistic regression for simplicity.<< Parameters ---------- learning_rate : float, default = 0.2 The learning rate for gradient descent or SGD. method : str, default = 'gradient' Method of fitting the model. 'gradient' for gradient descent, 'sgd' for stochastic gradient descent. reg : str, default = None Regularization method. For L1 or L2, use 'l1' or 'l2' respectively. For elastic net method, use 'elastic'. None for no regularization. alpha : float, default = 0 Alpha parameter controlling the 'strength' of regularization. l1_ratio : float, default = 0 Defines the ratio of L1 regularization. Only for elastic regularization option. The penalty added to cost is l1_ratio * L1 + 0.5 * (1 - l1_ratio) * L2. """ def predict(self, x): """Predict the class for given input. Parameters ---------- x : array-like Input array. """ return np.heaviside(np.dot(x, self.coef) + self.intercept, 1)	37.75	104	0.652318	import numpy as np from linear_models.logistic_regression import LogisticRegression class Perceptron(LogisticRegression): """A simple (binary classification) perceptron. Uses binary cross-entropy loss for updating weights. >>NOTE: it inherits most of the code from logistic regression for simplicity.<< Parameters ---------- learning_rate : float, default = 0.2 The learning rate for gradient descent or SGD. method : str, default = 'gradient' Method of fitting the model. 'gradient' for gradient descent, 'sgd' for stochastic gradient descent. reg : str, default = None Regularization method. For L1 or L2, use 'l1' or 'l2' respectively. For elastic net method, use 'elastic'. None for no regularization. alpha : float, default = 0 Alpha parameter controlling the 'strength' of regularization. l1_ratio : float, default = 0 Defines the ratio of L1 regularization. Only for elastic regularization option. The penalty added to cost is l1_ratio * L1 + 0.5 * (1 - l1_ratio) * L2. """ def __init__(self, learning_rate=0.2, method='gradient', reg=None, alpha=0, l1_ratio=0): super().__init__(learning_rate, method, reg, alpha, l1_ratio) def predict(self, x): """Predict the class for given input. Parameters ---------- x : array-like Input array. """ return np.heaviside(np.dot(x, self.coef) + self.intercept, 1)	137	0	27
e465039836c2865c9891dbb3920bc30d8a2a4018	2,178	py	Python	Algo/004 (Contest)/F_test.py	abel1502/mipt_1s	f97974075ad82b4f1df4df1beee6ad895c363691	[ "MIT" ]	3	2020-10-01T17:21:49.000Z	2020-10-16T10:57:53.000Z	Algo/004 (Contest)/F_test.py	abel1502/mipt_1s	f97974075ad82b4f1df4df1beee6ad895c363691	[ "MIT" ]	2	2020-10-07T15:53:14.000Z	2020-10-07T16:26:02.000Z	Algo/004 (Contest)/F_test.py	abel1502/mipt_1s	f97974075ad82b4f1df4df1beee6ad895c363691	[ "MIT" ]	null	null	null	import subprocess import io import random INF = 10 ** 20 stress(100) exit() data = (16, 8, [8, 10, 15, 16, 4, 11]) """ 16 6 8 8 10 15 16 4 11 """ ans = solve(data) print(test(data, ans)) print(data, ans) """ [Error] (18, 3, [18, 8, 11, 2, 17, 10, 15, 5, 16]) (0, 1, 6) [Error] (80, 5, [61, 2]) (0, 1, 16) [Error] (9, 3, [9, 1]) (0, 1, 3) [Error] (2, 2, [1, 2]) (0, 1, 1) [Error] (8, 8, [3, 6]) (1, 1, 1) [Error] (24, 3, [4, 5, 17, 23, 7, 24, 12, 10, 8, 2, 9]) (2, 3, 1) """	20.942308	101	0.495868	import subprocess import io import random INF = 10 ** 20 def test(l, k, cells, ans): inData = "{l} {n} {k}\n{cells}\n".format(n=len(cells), l=l, k=k, cells=' '.join(map(str, cells))) result = subprocess.run("F.exe", input=inData.encode(), stdout=subprocess.PIPE) d, c, s = map(int, result.stdout.decode().split()) res = result.returncode == 0 and d == ans[0] and c == ans[1] # and s == ans[1] if not res: print("!", d, c, s) return res def solve(l, k, cells): cells = set(cells) buf = [int((i % l + 1) in cells) for i in range(3 * l)] blkSize = l // k minDelta = INF minStart = 0 minCnt = 0 for offset in range(blkSize): minBlk = INF maxBlk = -INF for blk in range(k): curBlk = sum(buf[blk * blkSize + offset:(blk + 1) * blkSize + offset]) minBlk = min(minBlk, curBlk) maxBlk = max(maxBlk, curBlk) curDelta = maxBlk - minBlk if curDelta < minDelta: minDelta = curDelta minStart = offset minCnt = 0 if curDelta == minDelta: minCnt += 1 return (minDelta, minCnt * k, minStart + 1) def genTest(bndN=(1, 20), bndK=(1,10), bndL=(1,10)): n = random.randrange(bndN) k = random.randrange(bndK) l = k * random.randrange(bndL) cells = list(range(1, l + 1)) random.shuffle(cells) cells = cells[:n] ans = solve(l, k, cells) return (l, k, cells), ans def stress(count): for i in range(count): data, ans = genTest() if not test(data, ans): print("[Error]", data, ans) #break stress(100) exit() data = (16, 8, [8, 10, 15, 16, 4, 11]) """ 16 6 8 8 10 15 16 4 11 """ ans = solve(data) print(test(data, ans)) print(data, ans) """ [Error] (18, 3, [18, 8, 11, 2, 17, 10, 15, 5, 16]) (0, 1, 6) [Error] (80, 5, [61, 2]) (0, 1, 16) [Error] (9, 3, [9, 1]) (0, 1, 3) [Error] (2, 2, [1, 2]) (0, 1, 1) [Error] (8, 8, [3, 6]) (1, 1, 1) [Error] (24, 3, [4, 5, 17, 23, 7, 24, 12, 10, 8, 2, 9]) (2, 3, 1) """	1,580	0	92
0c88c092702f2372af93159b4d7525bfd1fe0502	2,820	py	Python	meta_policy_search/envs/mujoco_envs/half_cheetah_rand_direc.py	Zhiwei-Z/SeqPromp	d973b8564d500d95477624cfb992fb5a96e096ca	[ "MIT" ]	null	null	null	meta_policy_search/envs/mujoco_envs/half_cheetah_rand_direc.py	Zhiwei-Z/SeqPromp	d973b8564d500d95477624cfb992fb5a96e096ca	[ "MIT" ]	null	null	null	meta_policy_search/envs/mujoco_envs/half_cheetah_rand_direc.py	Zhiwei-Z/SeqPromp	d973b8564d500d95477624cfb992fb5a96e096ca	[ "MIT" ]	null	null	null	import numpy as np from meta_policy_search.envs.base import MetaEnv from meta_policy_search.utils import logger import gym from gym.envs.mujoco.mujoco_env import MujocoEnv IterationBound1 = 200 IterationBound2 = 600	37.105263	92	0.634752	import numpy as np from meta_policy_search.envs.base import MetaEnv from meta_policy_search.utils import logger import gym from gym.envs.mujoco.mujoco_env import MujocoEnv IterationBound1 = 200 IterationBound2 = 600 class HalfCheetahRandDirecEnv(MetaEnv, MujocoEnv, gym.utils.EzPickle): def __init__(self, goal_direction=None): self.goal_direction = goal_direction if goal_direction else 1.0 MujocoEnv.__init__(self, 'half_cheetah.xml', 5) gym.utils.EzPickle.__init__(self, goal_direction) self.counter = 0 def sample_tasks(self, n_tasks): # for fwd/bwd env, goal direc is backwards if - 1.0, forwards if + 1.0 self.counter += 1 if self.counter < IterationBound1: return np.random.choice((-1.0, -0.5), (n_tasks, )) if self.counter < IterationBound2: return np.random.choice((-1.0, -0.5, 0.5), (n_tasks, )) return np.random.choice((-1.0, -0.5, 0.5, 1.0), (n_tasks, )) def set_task(self, task): """ Args: task: task of the meta-learning environment """ self.goal_direction = task def get_task(self): """ Returns: task: task of the meta-learning environment """ return self.goal_direction def step(self, action): xposbefore = self.sim.data.qpos[0] self.do_simulation(action, self.frame_skip) xposafter = self.sim.data.qpos[0] ob = self._get_obs() reward_ctrl = - 0.5 * 0.1 * np.square(action).sum() reward_run = self.goal_direction * (xposafter - xposbefore) / self.dt reward = reward_ctrl + reward_run done = False return ob, reward, done, dict(reward_run=reward_run, reward_ctrl=reward_ctrl) def _get_obs(self): return np.concatenate([ self.sim.data.qpos.flat[1:], self.sim.data.qvel.flat, ]) def reset_model(self): qpos = self.init_qpos + self.np_random.uniform(low=-.1, high=.1, size=self.model.nq) qvel = self.init_qvel + self.np_random.randn(self.model.nv) * .1 self.set_state(qpos, qvel) return self._get_obs() def viewer_setup(self): self.viewer.cam.distance = self.model.stat.extent * 0.5 def log_diagnostics(self, paths, prefix=''): fwrd_vel = [path["env_infos"]['reward_run'] for path in paths] final_fwrd_vel = [path["env_infos"]['reward_run'][-1] for path in paths] ctrl_cost = [-path["env_infos"]['reward_ctrl'] for path in paths] logger.logkv(prefix + 'AvgForwardVel', np.mean(fwrd_vel)) logger.logkv(prefix + 'AvgFinalForwardVel', np.mean(final_fwrd_vel)) logger.logkv(prefix + 'AvgCtrlCost', np.std(ctrl_cost)) def __str__(self): return 'HalfCheetahRandDirecEnv'	2,000	581	23
d9c30762e931c64e2c9bdf14b9468c8796124944	42,572	py	Python	pydia/cuda_functions_dp.py	koconnor4/pyDIA	7c0c2c21f039ae28bcda4af821f16dbafb27ceb5	[ "MIT" ]	2	2019-04-18T09:58:12.000Z	2020-03-03T09:27:25.000Z	pydia/cuda_functions_dp.py	koconnor4/pyDIA	7c0c2c21f039ae28bcda4af821f16dbafb27ceb5	[ "MIT" ]	null	null	null	pydia/cuda_functions_dp.py	koconnor4/pyDIA	7c0c2c21f039ae28bcda4af821f16dbafb27ceb5	[ "MIT" ]	1	2019-03-13T02:09:29.000Z	2019-03-13T02:09:29.000Z	import pycuda.autoinit from pycuda.compiler import SourceModule cu_matrix_kernel = SourceModule(""" #include <math.h> #include <stdio.h> #include "texture_fetch_functions.h" #include "texture_types.h" #define THREADS_PER_BLOCK 256 #define FIT_RADIUS 6 texture<float, cudaTextureType2DLayered, cudaReadModeElementType> tex; __device__ void deconvolve3_columns(int width,int height,int rowstride, double data,double buffer,double a,double b) { double row; double q; int i, j; / // if (( height < 2) \|\| (rowstride > width)) { // printf("Failure in deconvolve3_rows: height, rowstride, width, a, b = %//d %d %d %f %f\n",height, rowstride, width, a, b ); // return; // } / if (!height \|\| !width) return; if (height == 1) { q = a + 2.0b; for (j = 0; j < width; j++) data[j] /= q; return; } if (height == 2) { q = a(a + 2.0b); for (j = 0; j < width; j++) { buffer[0] = (a + b)/qdata[j] - b/qdata[rowstride + j]; data[rowstride + j] = (a + b)/qdata[rowstride + j] - b/qdata[j]; data[j] = buffer[0]; } return; } /* Special-case first row / buffer[0] = a + b; / Inner rows / for (i = 1; i < height-1; i++) { q = b/buffer[i-1]; buffer[i] = a - qb; row = data + (i - 1)rowstride; for (j = 0; j < width; j++) row[rowstride + j] -= qrow[j]; } /* Special-case last row / q = b/buffer[i-1]; buffer[i] = a + b(1.0 - q); row = data + (i - 1)rowstride; for (j = 0; j < width; j++) row[rowstride + j] -= qrow[j]; /* Go back / row += rowstride; for (j = 0; j < width; j++) row[j] /= buffer[i]; do { i--; row = data + irowstride; for (j = 0; j < width; j++) row[j] = (row[j] - brow[rowstride + j])/buffer[i]; } while (i > 0); } __device__ void deconvolve3_rows(int width,int height,int rowstride,double data, double buffer,double a,double b) { double row; double q; int i, j; /* // if (( height < 2) \|\| (rowstride > width)) { // printf("Failure in deconvolve3_rows\n"); // return; // } / if (!height \|\| !width) return; if (width == 1) { q = a + 2.0b; for (i = 0; i < height; i++) data[irowstride] /= q; return; } if (width == 2) { q = a(a + 2.0b); for (i = 0; i < height; i++) { row = data + irowstride; buffer[0] = (a + b)/qrow[0] - b/qrow[1]; row[1] = (a + b)/qrow[1] - b/qrow[0]; row[0] = buffer[0]; } return; } /* Special-case first item / buffer[0] = a + b; / Inner items / for (j = 1; j < width-1; j++) { q = b/buffer[j-1]; buffer[j] = a - qb; data[j] -= qdata[j-1]; } / Special-case last item / q = b/buffer[j-1]; buffer[j] = a + b(1.0 - q); data[j] -= qdata[j-1]; / Go back / data[j] /= buffer[j]; do { j--; data[j] = (data[j] - bdata[j+1])/buffer[j]; } while (j > 0); /* Remaining rows / for (i = 1; i < height; i++) { row = data + irowstride; /* Forward / for (j = 1; j < width-1; j++) row[j] -= brow[j-1]/buffer[j-1]; row[j] -= brow[j-1]/buffer[j-1]; / Back / row[j] /= buffer[j]; do { j--; row[j] = (row[j] - brow[j+1])/buffer[j]; } while (j > 0); } } __device__ void resolve_coeffs_2d(int width, int height, int rowstride, double data) { double buffer; int max; max = width > height ? width : height; buffer = (double )malloc(maxsizeof(double)); deconvolve3_rows(width, height, rowstride, data, buffer, 13.0/21.0, 4.0/21.0); deconvolve3_columns(width, height, rowstride, data, buffer, 13.0/21.0, 4.0/21.0); free(buffer); } __device__ double interpolate_2d(double x,double y,int rowstride,double coeff) { double wx[4], wy[4]; int i, j; double v, vx; / // if (x < 0.0 \|\| x > 1.0 \|\| y < 0.0 \|\| y > 1.0) { // printf("interpolate_2d: x or y out of bounds %f %f\n",x,y); // return(-1.0); // } / wx[0] = 4.0/21.0 + (-11.0/21.0 + (0.5 - x/6.0)x)x; wx[1] = 13.0/21.0 + (1.0/14.0 + (-1.0 + x/2.0)x)x; wx[2] = 4.0/21.0 + (3.0/7.0 + (0.5 - x/2.0)x)x; wx[3] = (1.0/42.0 + xx/6.0)x; wy[0] = 4.0/21.0 + (-11.0/21.0 + (0.5 - y/6.0)y)y; wy[1] = 13.0/21.0 + (1.0/14.0 + (-1.0 + y/2.0)y)y; wy[2] = 4.0/21.0 + (3.0/7.0 + (0.5 - y/2.0)y)y; wy[3] = (1.0/42.0 + yy/6.0)y; v = 0.0; for (i = 0; i < 4; i++) { vx = 0.0; for (j = 0; j < 4; j++) vx += coeff[irowstride + j]wx[j]; v += wy[i]vx; } return v; } __device__ float integrated_profile(int profile_type, int idx, int idy, float xpos, float ypos, float psf_parameters, float lut_0, float lut_xd, float lut_yd) { int psf_size; float psf_height, psf_sigma_x, psf_sigma_y, psf_xpos, psf_ypos; float p0; int ip, jp; double pi=3.14159265,fwtosig=0.8493218; psf_size = (int) psf_parameters[0]; psf_height = psf_parameters[1]; psf_sigma_x = psf_parameters[2]; psf_sigma_y = psf_parameters[3]; psf_ypos = psf_parameters[4]; psf_xpos = psf_parameters[5]; if (profile_type == 0) { // gaussian // PSF at location (Idx,Idy). PSF is centred at (7.5,7.5) // Analytic part p0 = 0.5psf_heightpifwtosigfwtosig* (erf((idx-7.5+0.5)/(1.41421356psf_sigma_x)) - erf((idx-7.5-0.5)/(1.41421356psf_sigma_x))) * (erf((idy-7.5+0.5)/(1.41421356psf_sigma_y)) - erf((idy-7.5-0.5)/(1.41421356psf_sigma_y))); // Index into the lookup table ip = psf_size/2 + 2idx - 15; jp = psf_size/2 + 2idy - 15; if ((ip>=0) && (ip<=psf_size-1) && (jp>=0) && (jp<=psf_size-1)) { p0 += lut_0[ip+psf_sizejp] + lut_xd[ip+psf_sizejp](xpos-psf_xpos) + lut_yd[ip+psf_sizejp](ypos-psf_ypos); } return p0; } else if (profile_type == 1) { // moffat25 // From iraf/noao/digiphot/daophot/daolib/profile.x float d[4][4] = {{ 0.0, 0.0, 0.0, 0.0}, {-0.28867513, 0.28867513, 0.0, 0.0}, {-0.38729833, 0.0, 0.38729833, 0.0}, {-0.43056816, -0.16999052, 0.16999052, 0.43056816}}; float w[4][4] = {{1.0, 0.0, 0.0, 0.0}, {0.5, 0.5, 0.0, 0.0}, {0.27777778, 0.44444444, 0.27777778, 0.0}, {0.17392742, 0.32607258, 0.32607258, 0.17392742}}; double alpha = 0.3195079; float p1sq, p2sq, p1p2, dx, dy, xy, denom, func, x[4], xsq[4], p1xsq[4]; float y, ysq, p2ysq, wt, p4fod, wp4fod, wf; int npt, ix, iy; p1sq = psf_parameters[2]psf_parameters[2]; p2sq = psf_parameters[3]psf_parameters[3]; p1p2 = psf_parameters[2]psf_parameters[3]; dx = idx-7.5+0.5; dy = idy-7.5+0.5; xy = dx * dy; denom = 1.0 + alpha * (dxdx/p1sq + dydy/p2sq + xypsf_parameters[4]); if (denom > 1.0e4) { return 0.0; } p0 = 0.0; func = 1.0 / (p1p2pow(double(denom),double(2.5))); if (func >= 0.046) { npt = 4; } else if (func >= 0.0022) { npt = 3; } else if (func >= 0.0001) { npt = 2; } else if (func >= 1.0e-10) { p0 = (2.5 - 1.0) * func; } if (func >= 0.0001) { for (ix=0; ix<npt; ix++) { x[ix] = dx + d[npt][ix]; xsq[ix] = x[ix]x[ix]; p1xsq[ix] = xsq[ix]/p1sq; } for (iy=0; iy<npt; iy++) { y = dy + d[npt][iy]; ysq = yy; p2ysq = ysq/p2sq; for (ix=0; ix<npt; ix++) { wt = w[npt][iy] * w[npt][ix]; xy = x[ix] * y; denom = 1.0 + alpha * (p1xsq[ix] + p2ysq + xypsf_parameters[4]); func = (2.5 - 1.0) / (p1p2 pow(double(denom),double(2.5)) ); p4fod = 2.5 * alpha * func / denom; wp4fod = wt * p4fod; wf = wt * func; p0 += wf; } } } p0 = psf_parameters[1]; // Index into the lookup table ip = psf_size/2 + 2idx - 15; jp = psf_size/2 + 2idy - 15; if ((ip>=0) && (ip<=psf_size-1) && (jp>=0) && (jp<=psf_size-1)) { p0 += lut_0[ip+psf_sizejp] + lut_xd[ip+psf_sizejp](xpos-psf_xpos) + lut_yd[ip+psf_sizejp](ypos-psf_ypos); } return p0; } else { return 0.0; } } __global__ void convolve_image_psf(int profile_type, int nx, int ny, int dx, int dy, int dp, int ds, int n_coeff, int nkernel, int kernel_radius,int kxindex, int kyindex, int* ext_basis, float psf_parameters, float psf_0, float psf_xd, float psf_yd, float coeff,float cim1, float* cim2) { int id, txa, tyb, txag, tybg; int np, ns, i, j, ii, ip, jp, ic, ki, a, b; int d1, sidx, l, m, l1, m1, ig, jg; int psf_size, ix, jx; float x, y, p0, p1, p1g, cpsf_pixel, xpos, ypos; float psf_height, psf_sigma_x, psf_sigma_y, psf_sigma_xy, psf_xpos, psf_ypos; float gain,psf_rad,psf_rad2, px, py; float sx2, sy2, sxy2, sx2msy2, sx2psy2; double psf_norm,dd; double pi=3.14159265,fwtosig=0.8493218; __shared__ double psf_sum[256]; __shared__ double cpsf[256]; __shared__ double cpix1[256]; __shared__ double cpix2[256]; // initialise memory id = threadIdx.x+threadIdx.y16; cpsf[id] = 0.0; // star position in normalised units xpos = blockIdx.xdx + dx/2; ypos = blockIdx.ydy + dy/2; x = (xpos - 0.5(nx-1))/(nx-1); y = (ypos - 0.5(ny-1))/(ny-1); // number of polynomial coefficients per basis function np = (dp+1)(dp+2)/2; ns = (ds+1)(ds+2)/2; // PSF parameters psf_size = (int) psf_parameters[0]; psf_height = psf_parameters[1]; psf_sigma_x = psf_parameters[2]; psf_sigma_y = psf_parameters[3]; psf_ypos = psf_parameters[4]; psf_xpos = psf_parameters[5]; psf_rad = psf_parameters[6]; gain = psf_parameters[7]; if (psf_rad > 5.0) { psf_rad = 5.0; } psf_rad2 = psf_radpsf_rad; // PSF integral __syncthreads(); psf_sum[id] = 0.0; for (i=threadIdx.x+1; i<psf_size-1; i+=blockDim.x) { for (j=threadIdx.y+1; j<psf_size-1; j+=blockDim.y) { psf_sum[id] += psf_0[i+jpsf_size]; } } __syncthreads(); i = 128; while (i != 0) { if (id < i) { psf_sum[id] += psf_sum[id + i]; } __syncthreads(); i /= 2; } __syncthreads(); if (profile_type == 0) { // gaussian psf_norm = 0.25psf_sum[0] + psf_height2pifwtosigfwtosig; } else if (profile_type == 1) { // moffat25 psf_sigma_xy = psf_parameters[8]; sx2 = psf_sigma_xpsf_sigma_x; sy2 = psf_sigma_ypsf_sigma_y; sxy2 = psf_sigma_xypsf_sigma_xy; sx2msy2 = 1.0/sx2 - 1.0/sy2; sx2psy2 = 1.0/sx2 + 1.0/sy2; px = 1.0/sqrt( sx2psy2 + sqrt(sx2msy2sx2msy2 + sxy2) ); py = 1.0/sqrt( sx2psy2 - sqrt(sx2msy2sx2msy2 + sxy2) ); psf_norm = 0.25psf_sum[0] + psf_heightpi(pxpy)/(psf_sigma_xpsf_sigma_y); } // Construct the convolved PSF // PSF at location (Idx,Idy). PSF is centred at (7.5,7.5) // Analytic part p0 = integrated_profile(profile_type, threadIdx.x, threadIdx.y, xpos, ypos, psf_parameters, psf_0, psf_xd, psf_yd); __syncthreads(); cpsf_pixel = 0.0; // Iterate over coefficients for (ic=0; ic<n_coeff; ic++) { // basis function position ki = ic < np ? 0 : (ic-np)/ns + 1; if (ki<nkernel) { a = kxindex[ki]; b = kyindex[ki]; // Set the polynomial degree for the subvector and the // index within the subvector if (ki == 0) { d1 = dp; sidx = ic; } else { d1 = ds; sidx = ic - np - (ki-1)ns; } // Compute the polynomial index (l,m) values corresponding // to the index within the subvector l1 = m1 = 0; if (d1 > 0) { i = 0; for (l=0; l<=d1; l++) { for (m=0; m<=d1-l; m++) { if (i == sidx) { l1 = l; m1 = m; } i++; } } } // Indices into the PSF if (ki > 0) { txa = threadIdx.x + a; tyb = threadIdx.y + b; p1 = integrated_profile(profile_type, txa, tyb, xpos, ypos, psf_parameters, psf_0, psf_xd, psf_yd); __syncthreads(); // If we have an extended basis function, we need to // average the PSF over a 3x3 grid if (ext_basis[ki]) { p1 = 0.0; for (ig=-1; ig<2; ig++) { for (jg=-1; jg<2; jg++) { txag = txa + ig; tybg = tyb + jg; p1g = integrated_profile(profile_type, txag, tybg, xpos, ypos, psf_parameters, psf_0, psf_xd, psf_yd); __syncthreads(); p1 += p1g; } } p1 /= 9.0; } cpsf_pixel += coeff[ic](p1-p0)pow(x,l1)pow(y,m1); } else { cpsf_pixel += coeff[ic]p0pow(x,l1)pow(y,m1); } } } //end ic loop __syncthreads(); cpsf[id] = cpsf_pixel/psf_norm; __syncthreads(); // Now convolve the image section with the convolved PSF for (i=xpos-dx/2; i<xpos+dx/2; i++) { for (j=ypos-dy/2; j<ypos+dy/2; j++) { ix = (int)floor(i+0.5)+threadIdx.x-8.0; jx = (int)floor(j+0.5)+threadIdx.y-8.0; cpix1[id] = cpsf[id]tex2DLayered(tex,ix,jx,0); cpix2[id] = cpsf[id]tex2DLayered(tex,ix,jx,1); __syncthreads(); // Parallel sum ii = 128; while (ii != 0) { if (id < ii) { cpix1[id] += cpix1[id + ii]; cpix2[id] += cpix2[id + ii]; } __syncthreads(); ii /= 2; } if (id == 0) { cim1[i+jnx] = cpix1[0]; cim2[i+jnx] = cpix2[0]; } __syncthreads(); } } return; } __global__ void cu_photom(int profile_type, int nx, int ny, int dp, int ds, int n_coeff, int nkernel, int kernel_radius,int kxindex, int kyindex, int ext_basis, float psf_parameters, float psf_0, float psf_xd, float psf_yd, float posx, float posy, float coeff, float flux, float dflux, float star_sky) { int id, txa, tyb, txag, tybg; int np, ns, i, j, ip, jp, ic, ki, a, b; int d1, sidx, l, m, l1, m1, ig, jg; int psf_size, ix, jx; float x, y, p0, p1, p1g, cpsf_pixel, xpos, ypos, dd; float psf_height, psf_sigma_x, psf_sigma_y, psf_sigma_xy, psf_xpos, psf_ypos; float psf_rad, psf_rad2, gain, fl, inv_var, px, py; float sx2, sy2, sxy2, sx2msy2, sx2psy2; double subx, suby, psf_norm, bgnd; double pi=3.14159265, fwtosig=0.8493218, RON=5.0; __shared__ double psf_sum[256]; __shared__ double cpsf[256]; __shared__ float mpsf[256]; __shared__ float fsum1[256]; __shared__ float fsum2[256]; __shared__ float fsum3[256]; __shared__ float fsum4[256]; __shared__ float fsum5[256]; // initialise memory id = threadIdx.x+threadIdx.y16; cpsf[id] = 0.0; mpsf[id] = 0.0; // star position in normalised units xpos = posx[blockIdx.x]; ypos = posy[blockIdx.x]; x = (xpos - 0.5(nx-1))/(nx-1); y = (ypos - 0.5(ny-1))/(ny-1); // number of polynomial coefficients per basis function np = (dp+1)(dp+2)/2; ns = (ds+1)(ds+2)/2; // PSF parameters psf_size = (int) psf_parameters[0]; psf_height = psf_parameters[1]; psf_sigma_x = psf_parameters[2]; psf_sigma_y = psf_parameters[3]; psf_ypos = psf_parameters[4]; psf_xpos = psf_parameters[5]; psf_rad = psf_parameters[6]; gain = psf_parameters[7]; if (psf_rad > 7.0) { psf_rad = 7.0; } psf_rad2 = psf_radpsf_rad; // PSF integral __syncthreads(); psf_sum[id] = 0.0; for (i=threadIdx.x; i<psf_size; i+=blockDim.x) { for (j=threadIdx.y; j<psf_size; j+=blockDim.y) { psf_sum[id] += psf_0[i+jpsf_size]; //if (blockIdx.x == 120) { // printf("i, j, id, psf_0: %d %d %d %f\\n",i,j,id,psf_0[i+jpsf_size]); //} } } __syncthreads(); i = 128; while (i != 0) { if (id < i) { psf_sum[id] += psf_sum[id + i]; } __syncthreads(); i /= 2; } __syncthreads(); if (profile_type == 0) { // gaussian psf_norm = 0.25psf_sum[0] + psf_height2pifwtosigfwtosig; //if ((id == 0) && (blockIdx.x==120)){ // printf("psf_sum0, psf_height, psf_norm: %f %f %f\\n",psf_sum[0],psf_height,psf_norm); //} } else if (profile_type == 1) { // moffat25 psf_sigma_xy = psf_parameters[8]; sx2 = psf_sigma_xpsf_sigma_x; sy2 = psf_sigma_ypsf_sigma_y; sxy2 = psf_sigma_xypsf_sigma_xy; sx2msy2 = 1.0/sx2 - 1.0/sy2; sx2psy2 = 1.0/sx2 + 1.0/sy2; px = 1.0/sqrt( sx2psy2 + sqrt(sx2msy2sx2msy2 + sxy2) ); py = 1.0/sqrt( sx2psy2 - sqrt(sx2msy2sx2msy2 + sxy2) ); psf_norm = 0.25psf_sum[0] + psf_heightpi(pxpy)/(psf_sigma_xpsf_sigma_y); //if ((id == 0) && (blockIdx.x==120)){ // printf("psf_sum0, psf_height, psf_norm: %f %f %f\\n",psf_sum[0],psf_height, psf_norm); //} } // Construct the convolved PSF // PSF at location (Idx,Idy). PSF is centred at (7.5,7.5) // Analytic part p0 = integrated_profile(profile_type, threadIdx.x, threadIdx.y, xpos, ypos, psf_parameters, psf_0, psf_xd, psf_yd); __syncthreads(); // Spatially variable part // // + // psf_xd[ipsf+psf_sizejpsf](xpos-psf_xpos) + // psf_yd[ipsf+psf_sizejpsf](ypos-psf_ypos); // } // cpsf_pixel = 0.0; // Iterate over coefficients for (ic=0; ic<n_coeff; ic++) { // basis function position ki = ic < np ? 0 : (ic-np)/ns + 1; if (ki<nkernel) { a = kxindex[ki]; b = kyindex[ki]; // Set the polynomial degree for the subvector and the // index within the subvector if (ki == 0) { d1 = dp; sidx = ic; } else { d1 = ds; sidx = ic - np - (ki-1)ns; } // Compute the polynomial index (l,m) values corresponding // to the index within the subvector l1 = m1 = 0; if (d1 > 0) { i = 0; for (l=0; l<=d1; l++) { for (m=0; m<=d1-l; m++) { if (i == sidx) { l1 = l; m1 = m; } i++; } } } // Indices into the PSF if (ki > 0) { txa = threadIdx.x + a; tyb = threadIdx.y + b; p1 = integrated_profile(profile_type, txa, tyb, xpos, ypos, psf_parameters, psf_0, psf_xd, psf_yd); __syncthreads(); // // + // psf_xd[ipsf+psf_sizejpsf](xpos-psf_xpos) + // psf_yd[ipsf+psf_sizejpsf](ypos-psf_ypos); // } // // If we have an extended basis function, we need to // average the PSF over a 3x3 grid if (ext_basis[ki]) { p1 = 0.0; for (ig=-1; ig<2; ig++) { for (jg=-1; jg<2; jg++) { txag = txa + ig; tybg = tyb + jg; p1g = integrated_profile(profile_type, txag, tybg, xpos, ypos, psf_parameters, psf_0, psf_xd, psf_yd); __syncthreads(); // // + // psf_xd[ipsf+psf_sizejpsf](xpos-psf_xpos) + // psf_yd[ipsf+psf_sizejpsf](ypos-psf_ypos); // } // p1 += p1g; } } p1 /= 9.0; } cpsf_pixel += coeff[ic](p1-p0)pow(x,l1)pow(y,m1); } else { cpsf_pixel += coeff[ic]p0pow(x,l1)pow(y,m1); } } } //end ic loop __syncthreads(); cpsf[id] = cpsf_pixel/psf_norm; __syncthreads(); /* Uncomment to print convolved PSF if ((id == 0) && (blockIdx.x==14)){ txa = 7; tyb = 7; ip = psf_size/2 + 2txa - 15; jp = psf_size/2 + 2tyb - 15; if (profile_type == 0) { printf("psf_test: %lf %lf %lf %lf\\n", 0.5psf_heightpifwtosigfwtosig* (erf((txa-7.5+0.5)/(1.41421356psf_sigma_x)) - erf((txa-7.5-0.5)/(1.41421356psf_sigma_x))) * (erf((tyb-7.5+0.5)/(1.41421356psf_sigma_y)) - erf((tyb-7.5-0.5)/(1.41421356psf_sigma_y))), psf_0[ip+psf_sizejp], psf_xd[ip+psf_sizejp](xpos-psf_xpos), psf_yd[ip+psf_sizejp](ypos-psf_ypos)); } dd = 0.0; printf("cpsf\\n"); for (j=15; j>=0; j--) { printf("%2d ",j); for (i=0; i<16; i++) { printf("%6.4f ",cpsf[i+j16]); dd += cpsf[i+j16]; } printf("\\n"); } printf("sum = %f\\n",dd); printf("psf lookup table fraction: %f\\n",psf_sum[0]/psf_norm); } / __syncthreads(); // Map the convolved PSF to the subpixel star coordinates if (id == 0) { resolve_coeffs_2d(16,16,16,cpsf); } __syncthreads(); mpsf[id] = 0.0; subx = ceil(xpos+0.5+0.0000000001) - (xpos+0.5); suby = ceil(ypos+0.5+0.0000000001) - (ypos+0.5); if ((threadIdx.x > 1) && (threadIdx.x < 14) && (threadIdx.y > 1) && (threadIdx.y < 14)) { mpsf[id] = (float)interpolate_2d(subx,suby,16,&cpsf[threadIdx.x-2+(threadIdx.y-2)16]); } __syncthreads(); // force negative pixels to zero mpsf[id] = mpsf[id] > 0.0 ? mpsf[id] : 0.0; __syncthreads(); // // Normalise mapped PSF // (No - the convolved PSF contains the phot scale) / cpsf[id] = mpsf[id]; __syncthreads(); i = 128; while (i != 0) { if (id < i) { cpsf[id] += cpsf[id + i]; } __syncthreads(); i /= 2; } mpsf[id] /= cpsf[0]; / / Uncomment to print mapped PSF / if ((id == 0) && (blockIdx.x==14)){ printf("xpos, ypos: %f %f\\n",xpos,ypos); printf("subx, suby: %f %f\\n",subx,suby); printf("mpsf\\n"); dd = 0.0; for (j=15; j>=0; j--) { printf("%2d ",j); for (i=0; i<16; i++) { printf("%6.4f ",mpsf[i+j16]); dd += mpsf[i+j16]; } printf("\\n"); } printf("sum = %f\\n",dd); } __syncthreads(); // Fit the mapped PSF to the difference image to compute an // optimal flux estimate. // Assume the difference image is in tex(:,:,0) // and the inverse variance in tex(:,:,1). // We need to iterate to get the variance correct // fl = 0.0; for (j=0; j<3; j++) { fsum1[id] = 0.0; fsum2[id] = 0.0; fsum3[id] = 0.0; __syncthreads(); / if ((id == 0) && (blockIdx.x==14)){ printf("photom, j=%d\\n",j); } / if (pow(threadIdx.x-8.0,2)+pow(threadIdx.y-8.0,2) < psf_rad2) { ix = (int)floor(xpos+0.5)+threadIdx.x-8.0; jx = (int)floor(ypos+0.5)+threadIdx.y-8.0; inv_var = 1.0/(1.0/tex2DLayered(tex,ix,jx,1) + flmpsf[id]/gain); fsum1[id] = mpsf[id]tex2DLayered(tex,ix,jx,0)inv_var; fsum2[id] = mpsf[id]mpsf[id]inv_var; fsum3[id] = mpsf[id]; /* if ((blockIdx.x==14)){ printf("ix jx mpsf im: %03d %03d %6.5f %12.2f\\n",ix,jx,mpsf[id],tex2DLayered(tex,ix,jx,0)); } / } __syncthreads(); // Parallel sum i = 128; while (i != 0) { if (id < i) { fsum1[id] += fsum1[id + i]; fsum2[id] += fsum2[id + i]; fsum3[id] += fsum3[id + i]; } __syncthreads(); i /= 2; } fl = fsum1[0]/fsum2[0]; } if (id == 0) { flux[blockIdx.x] = fl; dflux[blockIdx.x] = sqrt(fsum3[0]fsum3[0]/fsum2[0]); } /* Uncomment for debug info / / __syncthreads(); i = 128; while (i != 0) { if (id < i) { mpsf[id] += mpsf[id + i]; } __syncthreads(); i /= 2; } __syncthreads(); if (id == 0) { if (blockIdx.x == 120) { printf("result: %f %f %f %f %f %f %f %f %f %f %f %f\\n",fsum1[0],fsum2[0],fsum3[0],mpsf[0],psf_norm,psf_sum[0],bgnd,flux[blockIdx.x],flux[blockIdx.x]fsum3[0],flux[blockIdx.x]mpsf[0],fsum4[0],dflux[blockIdx.x]); } } / __syncthreads(); return; } __global__ void cu_compute_model(int dp, int ds, int db, int kxindex, int kyindex, int ext_basis, int nkernel, float coefficient, float M) { int np, ns, nb, hs, idx, ki, a, b, d1, sidx, l, m, l1, m1, i; double x, y, Bi; __shared__ double count[THREADS_PER_BLOCK]; // Calculate number of terms in subvectors np = (dp+1)(dp+2)/2; ns = (ds+1)(ds+2)/2; nb = (db+1)(db+2)/2; hs = (nkernel-1)ns+np+nb; x = (blockIdx.x - 0.5(gridDim.x-1))/(gridDim.x-1); y = (blockIdx.y - 0.5(gridDim.y-1))/(gridDim.y-1); count[threadIdx.x] = 0.0; for (idx = threadIdx.x; idx < hs; idx += blockDim.x) { // This is the index of the subvector and its kernel offsets ki = idx < np ? 0 : (idx-np)/ns + 1; a = b = 0; if (ki<nkernel) { a = kxindex[ki]; b = kyindex[ki]; } // Set the polynomial degree for the subvector and the // index within the subvector if (ki == 0) { d1 = dp; sidx = idx; } else if (ki < nkernel) { d1 = ds; sidx = idx - np - (ki-1)ns; } else { d1 = db; sidx = idx - np - (ki-1)ns; } // Compute the (l,m) values corresponding to the index within // the subvector l1 = m1 = 0; if (d1 > 0) { i = 0; for (l=0; l<=d1; l++) { for (m=0; m<=d1-l; m++) { if (i == sidx) { l1 = l; m1 = m; } i++; } } } if (ki == 0) { Bi = tex2DLayered(tex,blockIdx.x,blockIdx.y,0); } else if (ki < nkernel) { if (ext_basis[ki]) { Bi = tex2DLayered(tex,blockIdx.x+a,blockIdx.y+b,1)- tex2DLayered(tex,blockIdx.x,blockIdx.y,0); } else { Bi = tex2DLayered(tex,blockIdx.x+a,blockIdx.y+b,0)- tex2DLayered(tex,blockIdx.x,blockIdx.y,0); } } else { Bi = 1.0; } count[threadIdx.x] += coefficient[idx]pow(x,l1)pow(y,m1)Bi; } __syncthreads(); // Then parallel-sum the results i = blockDim.x/2; while (i != 0) { if (threadIdx.x < i) { count[threadIdx.x] += count[threadIdx.x + i]; } __syncthreads(); i /= 2; } if (threadIdx.x == 0) { M[blockIdx.x+gridDim.xblockIdx.y] = count[0]; } } __global__ void cu_compute_vector(int dp, int ds, int db, int nx, int ny, int kxindex, int kyindex, int ext_basis, int nkernel, int kernelRadius,float V) { int idx; int np, ns, ki, a, b, d1, i, j; int l, m, l1, m1; float py, x, y, Bi; double temp; __shared__ double count[THREADS_PER_BLOCK]; // Calculate number of terms in subvectors np = (dp+1)(dp+2)/2; ns = (ds+1)(ds+2)/2; // This is the index of the subvector and its kernel offsets ki = blockIdx.x < np ? 0 : (blockIdx.x-np)/ns + 1; a = b = 0; if (ki<nkernel) { a = kxindex[ki]; b = kyindex[ki]; } // Set the polynomial degrees for the submatrix and the // indices within the submatrix if (ki == 0) { d1 = dp; idx = blockIdx.x; } else if (ki < nkernel) { d1 = ds; idx = blockIdx.x - np - (ki-1)ns; } else { d1 = db; idx = blockIdx.x - np - (ki-1)ns; } // Compute the (l,m) values corresponding to the index within // the subvector i = 0; for (l=0; l<=d1; l++) { for (m=0; m<=d1-l; m++) { if (i == idx) { l1 = l; m1 = m; } i++; } } // Compute the contribution to V from each image location. // Use individual threads to sum over columns. // tex[:,:,0] is the reference image, // tex[:,:,1] is the blurred reference image, // tex[:,:,2] is the target image, // tex[:,:,3] is the inverse variance, // tex[:,:,4] is the mask. // Bi is the basis image value. temp = 0.0; Bi = 1.0; __syncthreads(); for (j=kernelRadius; j<ny-kernelRadius; j++) { y = (j - 0.5(ny-1))/(ny-1); py = pow(y,m1); for (i=threadIdx.x+kernelRadius; i<nx-kernelRadius; i+=blockDim.x) { x = (i - 0.5(nx-1))/(nx-1); if (ki == 0) { Bi = tex2DLayered(tex,i,j,0); } else if (ki < nkernel) { if (ext_basis[ki]) { Bi = tex2DLayered(tex,i+a,j+b,1)-tex2DLayered(tex,i,j,0); } else { Bi = tex2DLayered(tex,i+a,j+b,0)-tex2DLayered(tex,i,j,0); } } else { Bi = 1.0; } temp += pow(x,l1)pyBitex2DLayered(tex,i,j,2)tex2DLayered(tex,i,j,3)* tex2DLayered(tex,i,j,4); } } count[threadIdx.x] = temp; __syncthreads(); // Then parallel-sum the rows i = blockDim.x/2; while (i != 0) { if (threadIdx.x < i) { count[threadIdx.x] += count[threadIdx.x + i]; } __syncthreads(); i /= 2; } if (threadIdx.x == 0) { V[blockIdx.x] = count[0]; } } __global__ void cu_compute_vector_stamps(int dp, int ds, int db, int nx, int ny, int nstamps, int stamp_half_width, float stamp_xpos, float stamp_ypos, int kxindex, int kyindex, int ext_basis, int nkernel, int kernelRadius,float V) { int idx; int np, ns, ki, a, b, d1, i, j, i1, i2, j1, j2; int l, m, l1, m1; float py, x, y, Bi; double temp; __shared__ double count[THREADS_PER_BLOCK]; // Calculate number of terms in subvectors np = (dp+1)(dp+2)/2; ns = (ds+1)(ds+2)/2; // This is the index of the subvector and its kernel offsets ki = blockIdx.x < np ? 0 : (blockIdx.x-np)/ns + 1; a = b = 0; if (ki<nkernel) { a = kxindex[ki]; b = kyindex[ki]; } // Set the polynomial degrees for the submatrix and the // indices within the submatrix if (ki == 0) { d1 = dp; idx = blockIdx.x; } else if (ki < nkernel) { d1 = ds; idx = blockIdx.x - np - (ki-1)ns; } else { d1 = db; idx = blockIdx.x - np - (ki-1)ns; } // Compute the (l,m) values corresponding to the index within // the subvector i = 0; for (l=0; l<=d1; l++) { for (m=0; m<=d1-l; m++) { if (i == idx) { l1 = l; m1 = m; } i++; } } // Compute the contribution to V from each image location. // Use individual threads to sum over columns. // tex[:,:,0] is the reference image, // tex[:,:,1] is the blurred reference image, // tex[:,:,2] is the target image, // tex[:,:,3] is the inverse variance, // tex[:,:,4] is the mask. // Bi is the basis image value. temp = 0.0; Bi = 1.0; __syncthreads(); for (idx = threadIdx.x; idx<nstamps; idx += blockDim.x) { j1 = max(0,(int)stamp_ypos[idx]-stamp_half_width); j2 = min(ny,(int)stamp_ypos[idx]+stamp_half_width); for (j=j1; j<j2; j++) { y = (j - 0.5(ny-1))/(ny-1); py = pow(y,m1); i1 = max(0,(int)stamp_xpos[idx]-stamp_half_width); i2 = min(nx,(int)stamp_xpos[idx]+stamp_half_width); for (i=i1; i<i2; i++) { x = (i - 0.5(nx-1))/(nx-1); if (ki == 0) { Bi = tex2DLayered(tex,i,j,0); } else if (ki < nkernel) { if (ext_basis[ki]) { Bi = tex2DLayered(tex,i+a,j+b,1)-tex2DLayered(tex,i,j,0); } else { Bi = tex2DLayered(tex,i+a,j+b,0)-tex2DLayered(tex,i,j,0); } } else { Bi = 1.0; } temp += pow(x,l1)pyBitex2DLayered(tex,i,j,2)tex2DLayered(tex,i,j,3)* tex2DLayered(tex,i,j,4); } } } count[threadIdx.x] = temp; __syncthreads(); // Then parallel-sum the rows i = blockDim.x/2; while (i != 0) { if (threadIdx.x < i) { count[threadIdx.x] += count[threadIdx.x + i]; } __syncthreads(); i /= 2; } if (threadIdx.x == 0) { V[blockIdx.x] = count[0]; } } __global__ void cu_compute_matrix(int dp, int ds, int db, int nx, int ny, int kxindex, int kyindex, int ext_basis, int nkernel, int kernelRadius,float H) { int idx, idy, idx0, idy0, idx1, idy1; int np, ns, ki, kj, a, b, c, d, d1, d2, i, j; int l, m, l1, m1, l2, m2; float py, x, y, Bi, Bj; double temp; __shared__ double count[THREADS_PER_BLOCK]; // Terminate if we are not in the lower triangle if (blockIdx.x > blockIdx.y) { return; } // Calculate number of terms in submatrices np = (dp+1)(dp+2)/2; ns = (ds+1)(ds+2)/2; // These are indices of the submatrix and their kernel offsets ki = blockIdx.x < np ? 0 : (blockIdx.x-np)/ns + 1; kj = blockIdx.y < np ? 0 : (blockIdx.y-np)/ns + 1; a = b = 0; if (ki<nkernel) { a = kxindex[ki]; b = kyindex[ki]; } if (kj<nkernel) { c = kxindex[kj]; d = kyindex[kj]; } // Set the polynomial degrees for the submatrix and the // indices within the submatrix if (ki == 0) { d1 = dp; idx = blockIdx.x; } else if (ki < nkernel) { d1 = ds; idx = blockIdx.x - np - (ki-1)ns; } else { d1 = db; idx = blockIdx.x - np - (ki-1)ns; } if (kj == 0) { d2 = dp; idy = blockIdx.y; } else if (kj < nkernel) { d2 = ds; idy = blockIdx.y - np - (kj-1)ns; } else { d2 = db; idy = blockIdx.y - np - (kj-1)ns; } if ((ki>0) && (ki<nkernel) && (kj>0) && (kj<nkernel) && (idx > idy)) { return; } idx0 = idx; idy0 = idy; // Compute the (l,m) values corresponding to the indices within // the submatrix i = 0; for (l=0; l<=d1; l++) { for (m=0; m<=d1-l; m++) { if (i == idx) { l1 = l; m1 = m; } i++; } } i = 0; for (l=0; l<=d2; l++) { for (m=0; m<=d2-l; m++) { if (i == idy) { l2 = l; m2 = m; } i++; } } // Compute the contribution to H from each image location. // Use individual threads to sum over columns. // tex[:,:,0] is the reference image, // tex[:,:,1] is the blurred reference image, // tex[:,:,2] is the target image, // tex[:,:,3] is the inverse variance, // tex[:,:,4] is the mask. // Bi and Bj are the basis image values. temp = 0.0; Bi = Bj = 1.0; __syncthreads(); for (j=kernelRadius; j<ny-kernelRadius; j++) { y = (j - 0.5(ny-1))/(ny-1); py = pow(y,m1+m2); for (i=threadIdx.x+kernelRadius; i<nx-kernelRadius; i+=blockDim.x) { x = (i - 0.5(nx-1))/(nx-1); if (ki == 0) { Bi = tex2DLayered(tex,i,j,0); } else if (ki < nkernel) { if (ext_basis[ki]) { Bi = tex2DLayered(tex,i+a,j+b,1)-tex2DLayered(tex,i,j,0); } else { Bi = tex2DLayered(tex,i+a,j+b,0)-tex2DLayered(tex,i,j,0); } } else { Bi = 1.0; } if (kj == 0) { Bj = tex2DLayered(tex,i,j,0); } else if (kj < nkernel) { if (ext_basis[kj]) { Bj = tex2DLayered(tex,i+c,j+d,1)-tex2DLayered(tex,i,j,0); } else { Bj = tex2DLayered(tex,i+c,j+d,0)-tex2DLayered(tex,i,j,0); } } else { Bj = 1.0; } temp += pow(x,l1+l2)pyBiBjtex2DLayered(tex,i,j,3)tex2DLayered(tex,i,j,4); } } count[threadIdx.x] = temp; __syncthreads(); // Then parallel-sum the rows i = blockDim.x/2; while (i != 0) { if (threadIdx.x < i) { count[threadIdx.x] += count[threadIdx.x + i]; } __syncthreads(); i /= 2; } if (threadIdx.x == 0) { H[blockIdx.x+gridDim.xblockIdx.y] = count[0]; H[blockIdx.y+gridDim.xblockIdx.x] = count[0]; if ((ki>0) && (ki<nkernel) && (kj>0) && (kj<nkernel)) { idx1 = np + (ki-1)ns; idy1 = np + (kj-1)ns; H[(idx1+idy0)+gridDim.x(idy1+idx0)] = count[0]; H[(idy1+idx0)+gridDim.x(idx1+idy0)] = count[0]; } } } __global__ void cu_compute_matrix_stamps(int dp, int ds, int db, int nx, int ny, int nstamps, int stamp_half_width, float stamp_xpos, float* stamp_ypos, int kxindex, int kyindex, int ext_basis, int nkernel, int kernelRadius,float H) { int idx, idy, idx0, idy0, idx1, idy1; int np, ns, ki, kj, a, b, c, d, d1, d2, i, j, i1, i2, j1, j2; int l, m, l1, m1, l2, m2; float px, py, x, y, Bi, Bj; double temp; __shared__ double count[THREADS_PER_BLOCK]; // Terminate if we are not in the lower triangle if (blockIdx.x > blockIdx.y) { return; } // Calculate number of terms in submatrices np = (dp+1)(dp+2)/2; ns = (ds+1)(ds+2)/2; // These are indices of the submatrix and their kernel offsets ki = blockIdx.x < np ? 0 : (blockIdx.x-np)/ns + 1; kj = blockIdx.y < np ? 0 : (blockIdx.y-np)/ns + 1; a = b = 0; if (ki<nkernel) { a = kxindex[ki]; b = kyindex[ki]; } if (kj<nkernel) { c = kxindex[kj]; d = kyindex[kj]; } // Set the polynomial degrees for the submatrix and the // indices within the submatrix if (ki == 0) { d1 = dp; idx = blockIdx.x; } else if (ki < nkernel) { d1 = ds; idx = blockIdx.x - np - (ki-1)ns; } else { d1 = db; idx = blockIdx.x - np - (ki-1)ns; } if (kj == 0) { d2 = dp; idy = blockIdx.y; } else if (kj < nkernel) { d2 = ds; idy = blockIdx.y - np - (kj-1)ns; } else { d2 = db; idy = blockIdx.y - np - (kj-1)ns; } if ((ki>0) && (ki<nkernel) && (kj>0) && (kj<nkernel) && (idx > idy)) { return; } idx0 = idx; idy0 = idy; // Compute the (l,m) values corresponding to the indices within // the submatrix i = 0; for (l=0; l<=d1; l++) { for (m=0; m<=d1-l; m++) { if (i == idx) { l1 = l; m1 = m; } i++; } } i = 0; for (l=0; l<=d2; l++) { for (m=0; m<=d2-l; m++) { if (i == idy) { l2 = l; m2 = m; } i++; } } // Compute the contribution to H from each image location. // Use individual threads to sum over stamps. // tex[:,:,0] is the reference image, // tex[:,:,1] is the blurred reference image, // tex[:,:,2] is the target image, // tex[:,:,3] is the inverse variance, // tex[:,:,4] is the mask. // Bi and Bj are the basis image values. temp = 0.0; Bi = Bj = 1.0; __syncthreads(); for (idx = threadIdx.x; idx<nstamps; idx += blockDim.x) { i1 = max(0,(int)stamp_xpos[idx]-stamp_half_width); i2 = min(nx,(int)stamp_xpos[idx]+stamp_half_width); for (i=i1; i<i2; i++) { x = (i - 0.5(nx-1))/(nx-1); px = pow(x,l1+l2); j1 = max(0,(int)stamp_ypos[idx]-stamp_half_width); j2 = min(ny,(int)stamp_ypos[idx]+stamp_half_width); for (j=j1; j<j2; j++) { y = (j - 0.5(ny-1))/(ny-1); py = pow(y,m1+m2); if (ki == 0) { Bi = tex2DLayered(tex,i,j,0); } else if (ki < nkernel) { if (ext_basis[ki]) { Bi = tex2DLayered(tex,i+a,j+b,1)-tex2DLayered(tex,i,j,0); } else { Bi = tex2DLayered(tex,i+a,j+b,0)-tex2DLayered(tex,i,j,0); } } else { Bi = 1.0; } if (kj == 0) { Bj = tex2DLayered(tex,i,j,0); } else if (kj < nkernel) { if (ext_basis[kj]) { Bj = tex2DLayered(tex,i+c,j+d,1)-tex2DLayered(tex,i,j,0); } else { Bj = tex2DLayered(tex,i+c,j+d,0)-tex2DLayered(tex,i,j,0); } } else { Bj = 1.0; } temp += pxpyBiBjtex2DLayered(tex,i,j,3)tex2DLayered(tex,i,j,4); } } } count[threadIdx.x] = temp; __syncthreads(); // Then parallel-sum the rows i = blockDim.x/2; while (i != 0) { if (threadIdx.x < i) { count[threadIdx.x] += count[threadIdx.x + i]; } __syncthreads(); i /= 2; } if (threadIdx.x == 0) { H[blockIdx.x+gridDim.xblockIdx.y] = count[0]; H[blockIdx.y+gridDim.xblockIdx.x] = count[0]; if ((ki>0) && (ki<nkernel) && (kj>0) && (kj<nkernel)) { idx1 = np + (ki-1)ns; idy1 = np + (kj-1)ns; H[(idx1+idy0)+gridDim.x(idy1+idx0)] = count[0]; H[(idy1+idx0)+gridDim.x*(idx1+idy0)] = count[0]; } } } """)	25.895377	219	0.485272	import pycuda.autoinit from pycuda.compiler import SourceModule cu_matrix_kernel = SourceModule(""" #include <math.h> #include <stdio.h> #include "texture_fetch_functions.h" #include "texture_types.h" #define THREADS_PER_BLOCK 256 #define FIT_RADIUS 6 texture<float, cudaTextureType2DLayered, cudaReadModeElementType> tex; __device__ void deconvolve3_columns(int width,int height,int rowstride, double data,double buffer,double a,double b) { double row; double q; int i, j; / // if (( height < 2) \|\| (rowstride > width)) { // printf("Failure in deconvolve3_rows: height, rowstride, width, a, b = %//d %d %d %f %f\n",height, rowstride, width, a, b ); // return; // } / if (!height \|\| !width) return; if (height == 1) { q = a + 2.0b; for (j = 0; j < width; j++) data[j] /= q; return; } if (height == 2) { q = a(a + 2.0b); for (j = 0; j < width; j++) { buffer[0] = (a + b)/qdata[j] - b/qdata[rowstride + j]; data[rowstride + j] = (a + b)/qdata[rowstride + j] - b/qdata[j]; data[j] = buffer[0]; } return; } /* Special-case first row / buffer[0] = a + b; / Inner rows / for (i = 1; i < height-1; i++) { q = b/buffer[i-1]; buffer[i] = a - qb; row = data + (i - 1)rowstride; for (j = 0; j < width; j++) row[rowstride + j] -= qrow[j]; } /* Special-case last row / q = b/buffer[i-1]; buffer[i] = a + b(1.0 - q); row = data + (i - 1)rowstride; for (j = 0; j < width; j++) row[rowstride + j] -= qrow[j]; /* Go back / row += rowstride; for (j = 0; j < width; j++) row[j] /= buffer[i]; do { i--; row = data + irowstride; for (j = 0; j < width; j++) row[j] = (row[j] - brow[rowstride + j])/buffer[i]; } while (i > 0); } __device__ void deconvolve3_rows(int width,int height,int rowstride,double data, double buffer,double a,double b) { double row; double q; int i, j; /* // if (( height < 2) \|\| (rowstride > width)) { // printf("Failure in deconvolve3_rows\n"); // return; // } / if (!height \|\| !width) return; if (width == 1) { q = a + 2.0b; for (i = 0; i < height; i++) data[irowstride] /= q; return; } if (width == 2) { q = a(a + 2.0b); for (i = 0; i < height; i++) { row = data + irowstride; buffer[0] = (a + b)/qrow[0] - b/qrow[1]; row[1] = (a + b)/qrow[1] - b/qrow[0]; row[0] = buffer[0]; } return; } /* Special-case first item / buffer[0] = a + b; / Inner items / for (j = 1; j < width-1; j++) { q = b/buffer[j-1]; buffer[j] = a - qb; data[j] -= qdata[j-1]; } / Special-case last item / q = b/buffer[j-1]; buffer[j] = a + b(1.0 - q); data[j] -= qdata[j-1]; / Go back / data[j] /= buffer[j]; do { j--; data[j] = (data[j] - bdata[j+1])/buffer[j]; } while (j > 0); /* Remaining rows / for (i = 1; i < height; i++) { row = data + irowstride; /* Forward / for (j = 1; j < width-1; j++) row[j] -= brow[j-1]/buffer[j-1]; row[j] -= brow[j-1]/buffer[j-1]; / Back / row[j] /= buffer[j]; do { j--; row[j] = (row[j] - brow[j+1])/buffer[j]; } while (j > 0); } } __device__ void resolve_coeffs_2d(int width, int height, int rowstride, double data) { double buffer; int max; max = width > height ? width : height; buffer = (double )malloc(maxsizeof(double)); deconvolve3_rows(width, height, rowstride, data, buffer, 13.0/21.0, 4.0/21.0); deconvolve3_columns(width, height, rowstride, data, buffer, 13.0/21.0, 4.0/21.0); free(buffer); } __device__ double interpolate_2d(double x,double y,int rowstride,double coeff) { double wx[4], wy[4]; int i, j; double v, vx; / // if (x < 0.0 \|\| x > 1.0 \|\| y < 0.0 \|\| y > 1.0) { // printf("interpolate_2d: x or y out of bounds %f %f\n",x,y); // return(-1.0); // } / wx[0] = 4.0/21.0 + (-11.0/21.0 + (0.5 - x/6.0)x)x; wx[1] = 13.0/21.0 + (1.0/14.0 + (-1.0 + x/2.0)x)x; wx[2] = 4.0/21.0 + (3.0/7.0 + (0.5 - x/2.0)x)x; wx[3] = (1.0/42.0 + xx/6.0)x; wy[0] = 4.0/21.0 + (-11.0/21.0 + (0.5 - y/6.0)y)y; wy[1] = 13.0/21.0 + (1.0/14.0 + (-1.0 + y/2.0)y)y; wy[2] = 4.0/21.0 + (3.0/7.0 + (0.5 - y/2.0)y)y; wy[3] = (1.0/42.0 + yy/6.0)y; v = 0.0; for (i = 0; i < 4; i++) { vx = 0.0; for (j = 0; j < 4; j++) vx += coeff[irowstride + j]wx[j]; v += wy[i]vx; } return v; } __device__ float integrated_profile(int profile_type, int idx, int idy, float xpos, float ypos, float psf_parameters, float lut_0, float lut_xd, float lut_yd) { int psf_size; float psf_height, psf_sigma_x, psf_sigma_y, psf_xpos, psf_ypos; float p0; int ip, jp; double pi=3.14159265,fwtosig=0.8493218; psf_size = (int) psf_parameters[0]; psf_height = psf_parameters[1]; psf_sigma_x = psf_parameters[2]; psf_sigma_y = psf_parameters[3]; psf_ypos = psf_parameters[4]; psf_xpos = psf_parameters[5]; if (profile_type == 0) { // gaussian // PSF at location (Idx,Idy). PSF is centred at (7.5,7.5) // Analytic part p0 = 0.5psf_heightpifwtosigfwtosig* (erf((idx-7.5+0.5)/(1.41421356psf_sigma_x)) - erf((idx-7.5-0.5)/(1.41421356psf_sigma_x))) * (erf((idy-7.5+0.5)/(1.41421356psf_sigma_y)) - erf((idy-7.5-0.5)/(1.41421356psf_sigma_y))); // Index into the lookup table ip = psf_size/2 + 2idx - 15; jp = psf_size/2 + 2idy - 15; if ((ip>=0) && (ip<=psf_size-1) && (jp>=0) && (jp<=psf_size-1)) { p0 += lut_0[ip+psf_sizejp] + lut_xd[ip+psf_sizejp](xpos-psf_xpos) + lut_yd[ip+psf_sizejp](ypos-psf_ypos); } return p0; } else if (profile_type == 1) { // moffat25 // From iraf/noao/digiphot/daophot/daolib/profile.x float d[4][4] = {{ 0.0, 0.0, 0.0, 0.0}, {-0.28867513, 0.28867513, 0.0, 0.0}, {-0.38729833, 0.0, 0.38729833, 0.0}, {-0.43056816, -0.16999052, 0.16999052, 0.43056816}}; float w[4][4] = {{1.0, 0.0, 0.0, 0.0}, {0.5, 0.5, 0.0, 0.0}, {0.27777778, 0.44444444, 0.27777778, 0.0}, {0.17392742, 0.32607258, 0.32607258, 0.17392742}}; double alpha = 0.3195079; float p1sq, p2sq, p1p2, dx, dy, xy, denom, func, x[4], xsq[4], p1xsq[4]; float y, ysq, p2ysq, wt, p4fod, wp4fod, wf; int npt, ix, iy; p1sq = psf_parameters[2]psf_parameters[2]; p2sq = psf_parameters[3]psf_parameters[3]; p1p2 = psf_parameters[2]psf_parameters[3]; dx = idx-7.5+0.5; dy = idy-7.5+0.5; xy = dx * dy; denom = 1.0 + alpha * (dxdx/p1sq + dydy/p2sq + xypsf_parameters[4]); if (denom > 1.0e4) { return 0.0; } p0 = 0.0; func = 1.0 / (p1p2pow(double(denom),double(2.5))); if (func >= 0.046) { npt = 4; } else if (func >= 0.0022) { npt = 3; } else if (func >= 0.0001) { npt = 2; } else if (func >= 1.0e-10) { p0 = (2.5 - 1.0) * func; } if (func >= 0.0001) { for (ix=0; ix<npt; ix++) { x[ix] = dx + d[npt][ix]; xsq[ix] = x[ix]x[ix]; p1xsq[ix] = xsq[ix]/p1sq; } for (iy=0; iy<npt; iy++) { y = dy + d[npt][iy]; ysq = yy; p2ysq = ysq/p2sq; for (ix=0; ix<npt; ix++) { wt = w[npt][iy] * w[npt][ix]; xy = x[ix] * y; denom = 1.0 + alpha * (p1xsq[ix] + p2ysq + xypsf_parameters[4]); func = (2.5 - 1.0) / (p1p2 pow(double(denom),double(2.5)) ); p4fod = 2.5 * alpha * func / denom; wp4fod = wt * p4fod; wf = wt * func; p0 += wf; } } } p0 = psf_parameters[1]; // Index into the lookup table ip = psf_size/2 + 2idx - 15; jp = psf_size/2 + 2idy - 15; if ((ip>=0) && (ip<=psf_size-1) && (jp>=0) && (jp<=psf_size-1)) { p0 += lut_0[ip+psf_sizejp] + lut_xd[ip+psf_sizejp](xpos-psf_xpos) + lut_yd[ip+psf_sizejp](ypos-psf_ypos); } return p0; } else { return 0.0; } } __global__ void convolve_image_psf(int profile_type, int nx, int ny, int dx, int dy, int dp, int ds, int n_coeff, int nkernel, int kernel_radius,int kxindex, int kyindex, int* ext_basis, float psf_parameters, float psf_0, float psf_xd, float psf_yd, float coeff,float cim1, float* cim2) { int id, txa, tyb, txag, tybg; int np, ns, i, j, ii, ip, jp, ic, ki, a, b; int d1, sidx, l, m, l1, m1, ig, jg; int psf_size, ix, jx; float x, y, p0, p1, p1g, cpsf_pixel, xpos, ypos; float psf_height, psf_sigma_x, psf_sigma_y, psf_sigma_xy, psf_xpos, psf_ypos; float gain,psf_rad,psf_rad2, px, py; float sx2, sy2, sxy2, sx2msy2, sx2psy2; double psf_norm,dd; double pi=3.14159265,fwtosig=0.8493218; __shared__ double psf_sum[256]; __shared__ double cpsf[256]; __shared__ double cpix1[256]; __shared__ double cpix2[256]; // initialise memory id = threadIdx.x+threadIdx.y16; cpsf[id] = 0.0; // star position in normalised units xpos = blockIdx.xdx + dx/2; ypos = blockIdx.ydy + dy/2; x = (xpos - 0.5(nx-1))/(nx-1); y = (ypos - 0.5(ny-1))/(ny-1); // number of polynomial coefficients per basis function np = (dp+1)(dp+2)/2; ns = (ds+1)(ds+2)/2; // PSF parameters psf_size = (int) psf_parameters[0]; psf_height = psf_parameters[1]; psf_sigma_x = psf_parameters[2]; psf_sigma_y = psf_parameters[3]; psf_ypos = psf_parameters[4]; psf_xpos = psf_parameters[5]; psf_rad = psf_parameters[6]; gain = psf_parameters[7]; if (psf_rad > 5.0) { psf_rad = 5.0; } psf_rad2 = psf_radpsf_rad; // PSF integral __syncthreads(); psf_sum[id] = 0.0; for (i=threadIdx.x+1; i<psf_size-1; i+=blockDim.x) { for (j=threadIdx.y+1; j<psf_size-1; j+=blockDim.y) { psf_sum[id] += psf_0[i+jpsf_size]; } } __syncthreads(); i = 128; while (i != 0) { if (id < i) { psf_sum[id] += psf_sum[id + i]; } __syncthreads(); i /= 2; } __syncthreads(); if (profile_type == 0) { // gaussian psf_norm = 0.25psf_sum[0] + psf_height2pifwtosigfwtosig; } else if (profile_type == 1) { // moffat25 psf_sigma_xy = psf_parameters[8]; sx2 = psf_sigma_xpsf_sigma_x; sy2 = psf_sigma_ypsf_sigma_y; sxy2 = psf_sigma_xypsf_sigma_xy; sx2msy2 = 1.0/sx2 - 1.0/sy2; sx2psy2 = 1.0/sx2 + 1.0/sy2; px = 1.0/sqrt( sx2psy2 + sqrt(sx2msy2sx2msy2 + sxy2) ); py = 1.0/sqrt( sx2psy2 - sqrt(sx2msy2sx2msy2 + sxy2) ); psf_norm = 0.25psf_sum[0] + psf_heightpi(pxpy)/(psf_sigma_xpsf_sigma_y); } // Construct the convolved PSF // PSF at location (Idx,Idy). PSF is centred at (7.5,7.5) // Analytic part p0 = integrated_profile(profile_type, threadIdx.x, threadIdx.y, xpos, ypos, psf_parameters, psf_0, psf_xd, psf_yd); __syncthreads(); cpsf_pixel = 0.0; // Iterate over coefficients for (ic=0; ic<n_coeff; ic++) { // basis function position ki = ic < np ? 0 : (ic-np)/ns + 1; if (ki<nkernel) { a = kxindex[ki]; b = kyindex[ki]; // Set the polynomial degree for the subvector and the // index within the subvector if (ki == 0) { d1 = dp; sidx = ic; } else { d1 = ds; sidx = ic - np - (ki-1)ns; } // Compute the polynomial index (l,m) values corresponding // to the index within the subvector l1 = m1 = 0; if (d1 > 0) { i = 0; for (l=0; l<=d1; l++) { for (m=0; m<=d1-l; m++) { if (i == sidx) { l1 = l; m1 = m; } i++; } } } // Indices into the PSF if (ki > 0) { txa = threadIdx.x + a; tyb = threadIdx.y + b; p1 = integrated_profile(profile_type, txa, tyb, xpos, ypos, psf_parameters, psf_0, psf_xd, psf_yd); __syncthreads(); // If we have an extended basis function, we need to // average the PSF over a 3x3 grid if (ext_basis[ki]) { p1 = 0.0; for (ig=-1; ig<2; ig++) { for (jg=-1; jg<2; jg++) { txag = txa + ig; tybg = tyb + jg; p1g = integrated_profile(profile_type, txag, tybg, xpos, ypos, psf_parameters, psf_0, psf_xd, psf_yd); __syncthreads(); p1 += p1g; } } p1 /= 9.0; } cpsf_pixel += coeff[ic](p1-p0)pow(x,l1)pow(y,m1); } else { cpsf_pixel += coeff[ic]p0pow(x,l1)pow(y,m1); } } } //end ic loop __syncthreads(); cpsf[id] = cpsf_pixel/psf_norm; __syncthreads(); // Now convolve the image section with the convolved PSF for (i=xpos-dx/2; i<xpos+dx/2; i++) { for (j=ypos-dy/2; j<ypos+dy/2; j++) { ix = (int)floor(i+0.5)+threadIdx.x-8.0; jx = (int)floor(j+0.5)+threadIdx.y-8.0; cpix1[id] = cpsf[id]tex2DLayered(tex,ix,jx,0); cpix2[id] = cpsf[id]tex2DLayered(tex,ix,jx,1); __syncthreads(); // Parallel sum ii = 128; while (ii != 0) { if (id < ii) { cpix1[id] += cpix1[id + ii]; cpix2[id] += cpix2[id + ii]; } __syncthreads(); ii /= 2; } if (id == 0) { cim1[i+jnx] = cpix1[0]; cim2[i+jnx] = cpix2[0]; } __syncthreads(); } } return; } __global__ void cu_photom(int profile_type, int nx, int ny, int dp, int ds, int n_coeff, int nkernel, int kernel_radius,int kxindex, int kyindex, int ext_basis, float psf_parameters, float psf_0, float psf_xd, float psf_yd, float posx, float posy, float coeff, float flux, float dflux, float star_sky) { int id, txa, tyb, txag, tybg; int np, ns, i, j, ip, jp, ic, ki, a, b; int d1, sidx, l, m, l1, m1, ig, jg; int psf_size, ix, jx; float x, y, p0, p1, p1g, cpsf_pixel, xpos, ypos, dd; float psf_height, psf_sigma_x, psf_sigma_y, psf_sigma_xy, psf_xpos, psf_ypos; float psf_rad, psf_rad2, gain, fl, inv_var, px, py; float sx2, sy2, sxy2, sx2msy2, sx2psy2; double subx, suby, psf_norm, bgnd; double pi=3.14159265, fwtosig=0.8493218, RON=5.0; __shared__ double psf_sum[256]; __shared__ double cpsf[256]; __shared__ float mpsf[256]; __shared__ float fsum1[256]; __shared__ float fsum2[256]; __shared__ float fsum3[256]; __shared__ float fsum4[256]; __shared__ float fsum5[256]; // initialise memory id = threadIdx.x+threadIdx.y16; cpsf[id] = 0.0; mpsf[id] = 0.0; // star position in normalised units xpos = posx[blockIdx.x]; ypos = posy[blockIdx.x]; x = (xpos - 0.5(nx-1))/(nx-1); y = (ypos - 0.5(ny-1))/(ny-1); // number of polynomial coefficients per basis function np = (dp+1)(dp+2)/2; ns = (ds+1)(ds+2)/2; // PSF parameters psf_size = (int) psf_parameters[0]; psf_height = psf_parameters[1]; psf_sigma_x = psf_parameters[2]; psf_sigma_y = psf_parameters[3]; psf_ypos = psf_parameters[4]; psf_xpos = psf_parameters[5]; psf_rad = psf_parameters[6]; gain = psf_parameters[7]; if (psf_rad > 7.0) { psf_rad = 7.0; } psf_rad2 = psf_radpsf_rad; // PSF integral __syncthreads(); psf_sum[id] = 0.0; for (i=threadIdx.x; i<psf_size; i+=blockDim.x) { for (j=threadIdx.y; j<psf_size; j+=blockDim.y) { psf_sum[id] += psf_0[i+jpsf_size]; //if (blockIdx.x == 120) { // printf("i, j, id, psf_0: %d %d %d %f\\n",i,j,id,psf_0[i+jpsf_size]); //} } } __syncthreads(); i = 128; while (i != 0) { if (id < i) { psf_sum[id] += psf_sum[id + i]; } __syncthreads(); i /= 2; } __syncthreads(); if (profile_type == 0) { // gaussian psf_norm = 0.25psf_sum[0] + psf_height2pifwtosigfwtosig; //if ((id == 0) && (blockIdx.x==120)){ // printf("psf_sum0, psf_height, psf_norm: %f %f %f\\n",psf_sum[0],psf_height,psf_norm); //} } else if (profile_type == 1) { // moffat25 psf_sigma_xy = psf_parameters[8]; sx2 = psf_sigma_xpsf_sigma_x; sy2 = psf_sigma_ypsf_sigma_y; sxy2 = psf_sigma_xypsf_sigma_xy; sx2msy2 = 1.0/sx2 - 1.0/sy2; sx2psy2 = 1.0/sx2 + 1.0/sy2; px = 1.0/sqrt( sx2psy2 + sqrt(sx2msy2sx2msy2 + sxy2) ); py = 1.0/sqrt( sx2psy2 - sqrt(sx2msy2sx2msy2 + sxy2) ); psf_norm = 0.25psf_sum[0] + psf_heightpi(pxpy)/(psf_sigma_xpsf_sigma_y); //if ((id == 0) && (blockIdx.x==120)){ // printf("psf_sum0, psf_height, psf_norm: %f %f %f\\n",psf_sum[0],psf_height, psf_norm); //} } // Construct the convolved PSF // PSF at location (Idx,Idy). PSF is centred at (7.5,7.5) // Analytic part p0 = integrated_profile(profile_type, threadIdx.x, threadIdx.y, xpos, ypos, psf_parameters, psf_0, psf_xd, psf_yd); __syncthreads(); // Spatially variable part // // + // psf_xd[ipsf+psf_sizejpsf](xpos-psf_xpos) + // psf_yd[ipsf+psf_sizejpsf](ypos-psf_ypos); // } // cpsf_pixel = 0.0; // Iterate over coefficients for (ic=0; ic<n_coeff; ic++) { // basis function position ki = ic < np ? 0 : (ic-np)/ns + 1; if (ki<nkernel) { a = kxindex[ki]; b = kyindex[ki]; // Set the polynomial degree for the subvector and the // index within the subvector if (ki == 0) { d1 = dp; sidx = ic; } else { d1 = ds; sidx = ic - np - (ki-1)ns; } // Compute the polynomial index (l,m) values corresponding // to the index within the subvector l1 = m1 = 0; if (d1 > 0) { i = 0; for (l=0; l<=d1; l++) { for (m=0; m<=d1-l; m++) { if (i == sidx) { l1 = l; m1 = m; } i++; } } } // Indices into the PSF if (ki > 0) { txa = threadIdx.x + a; tyb = threadIdx.y + b; p1 = integrated_profile(profile_type, txa, tyb, xpos, ypos, psf_parameters, psf_0, psf_xd, psf_yd); __syncthreads(); // // + // psf_xd[ipsf+psf_sizejpsf](xpos-psf_xpos) + // psf_yd[ipsf+psf_sizejpsf](ypos-psf_ypos); // } // // If we have an extended basis function, we need to // average the PSF over a 3x3 grid if (ext_basis[ki]) { p1 = 0.0; for (ig=-1; ig<2; ig++) { for (jg=-1; jg<2; jg++) { txag = txa + ig; tybg = tyb + jg; p1g = integrated_profile(profile_type, txag, tybg, xpos, ypos, psf_parameters, psf_0, psf_xd, psf_yd); __syncthreads(); // // + // psf_xd[ipsf+psf_sizejpsf](xpos-psf_xpos) + // psf_yd[ipsf+psf_sizejpsf](ypos-psf_ypos); // } // p1 += p1g; } } p1 /= 9.0; } cpsf_pixel += coeff[ic](p1-p0)pow(x,l1)pow(y,m1); } else { cpsf_pixel += coeff[ic]p0pow(x,l1)pow(y,m1); } } } //end ic loop __syncthreads(); cpsf[id] = cpsf_pixel/psf_norm; __syncthreads(); /* Uncomment to print convolved PSF if ((id == 0) && (blockIdx.x==14)){ txa = 7; tyb = 7; ip = psf_size/2 + 2txa - 15; jp = psf_size/2 + 2tyb - 15; if (profile_type == 0) { printf("psf_test: %lf %lf %lf %lf\\n", 0.5psf_heightpifwtosigfwtosig* (erf((txa-7.5+0.5)/(1.41421356psf_sigma_x)) - erf((txa-7.5-0.5)/(1.41421356psf_sigma_x))) * (erf((tyb-7.5+0.5)/(1.41421356psf_sigma_y)) - erf((tyb-7.5-0.5)/(1.41421356psf_sigma_y))), psf_0[ip+psf_sizejp], psf_xd[ip+psf_sizejp](xpos-psf_xpos), psf_yd[ip+psf_sizejp](ypos-psf_ypos)); } dd = 0.0; printf("cpsf\\n"); for (j=15; j>=0; j--) { printf("%2d ",j); for (i=0; i<16; i++) { printf("%6.4f ",cpsf[i+j16]); dd += cpsf[i+j16]; } printf("\\n"); } printf("sum = %f\\n",dd); printf("psf lookup table fraction: %f\\n",psf_sum[0]/psf_norm); } / __syncthreads(); // Map the convolved PSF to the subpixel star coordinates if (id == 0) { resolve_coeffs_2d(16,16,16,cpsf); } __syncthreads(); mpsf[id] = 0.0; subx = ceil(xpos+0.5+0.0000000001) - (xpos+0.5); suby = ceil(ypos+0.5+0.0000000001) - (ypos+0.5); if ((threadIdx.x > 1) && (threadIdx.x < 14) && (threadIdx.y > 1) && (threadIdx.y < 14)) { mpsf[id] = (float)interpolate_2d(subx,suby,16,&cpsf[threadIdx.x-2+(threadIdx.y-2)16]); } __syncthreads(); // force negative pixels to zero mpsf[id] = mpsf[id] > 0.0 ? mpsf[id] : 0.0; __syncthreads(); // // Normalise mapped PSF // (No - the convolved PSF contains the phot scale) / cpsf[id] = mpsf[id]; __syncthreads(); i = 128; while (i != 0) { if (id < i) { cpsf[id] += cpsf[id + i]; } __syncthreads(); i /= 2; } mpsf[id] /= cpsf[0]; / / Uncomment to print mapped PSF / if ((id == 0) && (blockIdx.x==14)){ printf("xpos, ypos: %f %f\\n",xpos,ypos); printf("subx, suby: %f %f\\n",subx,suby); printf("mpsf\\n"); dd = 0.0; for (j=15; j>=0; j--) { printf("%2d ",j); for (i=0; i<16; i++) { printf("%6.4f ",mpsf[i+j16]); dd += mpsf[i+j16]; } printf("\\n"); } printf("sum = %f\\n",dd); } __syncthreads(); // Fit the mapped PSF to the difference image to compute an // optimal flux estimate. // Assume the difference image is in tex(:,:,0) // and the inverse variance in tex(:,:,1). // We need to iterate to get the variance correct // fl = 0.0; for (j=0; j<3; j++) { fsum1[id] = 0.0; fsum2[id] = 0.0; fsum3[id] = 0.0; __syncthreads(); / if ((id == 0) && (blockIdx.x==14)){ printf("photom, j=%d\\n",j); } / if (pow(threadIdx.x-8.0,2)+pow(threadIdx.y-8.0,2) < psf_rad2) { ix = (int)floor(xpos+0.5)+threadIdx.x-8.0; jx = (int)floor(ypos+0.5)+threadIdx.y-8.0; inv_var = 1.0/(1.0/tex2DLayered(tex,ix,jx,1) + flmpsf[id]/gain); fsum1[id] = mpsf[id]tex2DLayered(tex,ix,jx,0)inv_var; fsum2[id] = mpsf[id]mpsf[id]inv_var; fsum3[id] = mpsf[id]; /* if ((blockIdx.x==14)){ printf("ix jx mpsf im: %03d %03d %6.5f %12.2f\\n",ix,jx,mpsf[id],tex2DLayered(tex,ix,jx,0)); } / } __syncthreads(); // Parallel sum i = 128; while (i != 0) { if (id < i) { fsum1[id] += fsum1[id + i]; fsum2[id] += fsum2[id + i]; fsum3[id] += fsum3[id + i]; } __syncthreads(); i /= 2; } fl = fsum1[0]/fsum2[0]; } if (id == 0) { flux[blockIdx.x] = fl; dflux[blockIdx.x] = sqrt(fsum3[0]fsum3[0]/fsum2[0]); } /* Uncomment for debug info / / __syncthreads(); i = 128; while (i != 0) { if (id < i) { mpsf[id] += mpsf[id + i]; } __syncthreads(); i /= 2; } __syncthreads(); if (id == 0) { if (blockIdx.x == 120) { printf("result: %f %f %f %f %f %f %f %f %f %f %f %f\\n",fsum1[0],fsum2[0],fsum3[0],mpsf[0],psf_norm,psf_sum[0],bgnd,flux[blockIdx.x],flux[blockIdx.x]fsum3[0],flux[blockIdx.x]mpsf[0],fsum4[0],dflux[blockIdx.x]); } } / __syncthreads(); return; } __global__ void cu_compute_model(int dp, int ds, int db, int kxindex, int kyindex, int ext_basis, int nkernel, float coefficient, float M) { int np, ns, nb, hs, idx, ki, a, b, d1, sidx, l, m, l1, m1, i; double x, y, Bi; __shared__ double count[THREADS_PER_BLOCK]; // Calculate number of terms in subvectors np = (dp+1)(dp+2)/2; ns = (ds+1)(ds+2)/2; nb = (db+1)(db+2)/2; hs = (nkernel-1)ns+np+nb; x = (blockIdx.x - 0.5(gridDim.x-1))/(gridDim.x-1); y = (blockIdx.y - 0.5(gridDim.y-1))/(gridDim.y-1); count[threadIdx.x] = 0.0; for (idx = threadIdx.x; idx < hs; idx += blockDim.x) { // This is the index of the subvector and its kernel offsets ki = idx < np ? 0 : (idx-np)/ns + 1; a = b = 0; if (ki<nkernel) { a = kxindex[ki]; b = kyindex[ki]; } // Set the polynomial degree for the subvector and the // index within the subvector if (ki == 0) { d1 = dp; sidx = idx; } else if (ki < nkernel) { d1 = ds; sidx = idx - np - (ki-1)ns; } else { d1 = db; sidx = idx - np - (ki-1)ns; } // Compute the (l,m) values corresponding to the index within // the subvector l1 = m1 = 0; if (d1 > 0) { i = 0; for (l=0; l<=d1; l++) { for (m=0; m<=d1-l; m++) { if (i == sidx) { l1 = l; m1 = m; } i++; } } } if (ki == 0) { Bi = tex2DLayered(tex,blockIdx.x,blockIdx.y,0); } else if (ki < nkernel) { if (ext_basis[ki]) { Bi = tex2DLayered(tex,blockIdx.x+a,blockIdx.y+b,1)- tex2DLayered(tex,blockIdx.x,blockIdx.y,0); } else { Bi = tex2DLayered(tex,blockIdx.x+a,blockIdx.y+b,0)- tex2DLayered(tex,blockIdx.x,blockIdx.y,0); } } else { Bi = 1.0; } count[threadIdx.x] += coefficient[idx]pow(x,l1)pow(y,m1)Bi; } __syncthreads(); // Then parallel-sum the results i = blockDim.x/2; while (i != 0) { if (threadIdx.x < i) { count[threadIdx.x] += count[threadIdx.x + i]; } __syncthreads(); i /= 2; } if (threadIdx.x == 0) { M[blockIdx.x+gridDim.xblockIdx.y] = count[0]; } } __global__ void cu_compute_vector(int dp, int ds, int db, int nx, int ny, int kxindex, int kyindex, int ext_basis, int nkernel, int kernelRadius,float V) { int idx; int np, ns, ki, a, b, d1, i, j; int l, m, l1, m1; float py, x, y, Bi; double temp; __shared__ double count[THREADS_PER_BLOCK]; // Calculate number of terms in subvectors np = (dp+1)(dp+2)/2; ns = (ds+1)(ds+2)/2; // This is the index of the subvector and its kernel offsets ki = blockIdx.x < np ? 0 : (blockIdx.x-np)/ns + 1; a = b = 0; if (ki<nkernel) { a = kxindex[ki]; b = kyindex[ki]; } // Set the polynomial degrees for the submatrix and the // indices within the submatrix if (ki == 0) { d1 = dp; idx = blockIdx.x; } else if (ki < nkernel) { d1 = ds; idx = blockIdx.x - np - (ki-1)ns; } else { d1 = db; idx = blockIdx.x - np - (ki-1)ns; } // Compute the (l,m) values corresponding to the index within // the subvector i = 0; for (l=0; l<=d1; l++) { for (m=0; m<=d1-l; m++) { if (i == idx) { l1 = l; m1 = m; } i++; } } // Compute the contribution to V from each image location. // Use individual threads to sum over columns. // tex[:,:,0] is the reference image, // tex[:,:,1] is the blurred reference image, // tex[:,:,2] is the target image, // tex[:,:,3] is the inverse variance, // tex[:,:,4] is the mask. // Bi is the basis image value. temp = 0.0; Bi = 1.0; __syncthreads(); for (j=kernelRadius; j<ny-kernelRadius; j++) { y = (j - 0.5(ny-1))/(ny-1); py = pow(y,m1); for (i=threadIdx.x+kernelRadius; i<nx-kernelRadius; i+=blockDim.x) { x = (i - 0.5(nx-1))/(nx-1); if (ki == 0) { Bi = tex2DLayered(tex,i,j,0); } else if (ki < nkernel) { if (ext_basis[ki]) { Bi = tex2DLayered(tex,i+a,j+b,1)-tex2DLayered(tex,i,j,0); } else { Bi = tex2DLayered(tex,i+a,j+b,0)-tex2DLayered(tex,i,j,0); } } else { Bi = 1.0; } temp += pow(x,l1)pyBitex2DLayered(tex,i,j,2)tex2DLayered(tex,i,j,3)* tex2DLayered(tex,i,j,4); } } count[threadIdx.x] = temp; __syncthreads(); // Then parallel-sum the rows i = blockDim.x/2; while (i != 0) { if (threadIdx.x < i) { count[threadIdx.x] += count[threadIdx.x + i]; } __syncthreads(); i /= 2; } if (threadIdx.x == 0) { V[blockIdx.x] = count[0]; } } __global__ void cu_compute_vector_stamps(int dp, int ds, int db, int nx, int ny, int nstamps, int stamp_half_width, float stamp_xpos, float stamp_ypos, int kxindex, int kyindex, int ext_basis, int nkernel, int kernelRadius,float V) { int idx; int np, ns, ki, a, b, d1, i, j, i1, i2, j1, j2; int l, m, l1, m1; float py, x, y, Bi; double temp; __shared__ double count[THREADS_PER_BLOCK]; // Calculate number of terms in subvectors np = (dp+1)(dp+2)/2; ns = (ds+1)(ds+2)/2; // This is the index of the subvector and its kernel offsets ki = blockIdx.x < np ? 0 : (blockIdx.x-np)/ns + 1; a = b = 0; if (ki<nkernel) { a = kxindex[ki]; b = kyindex[ki]; } // Set the polynomial degrees for the submatrix and the // indices within the submatrix if (ki == 0) { d1 = dp; idx = blockIdx.x; } else if (ki < nkernel) { d1 = ds; idx = blockIdx.x - np - (ki-1)ns; } else { d1 = db; idx = blockIdx.x - np - (ki-1)ns; } // Compute the (l,m) values corresponding to the index within // the subvector i = 0; for (l=0; l<=d1; l++) { for (m=0; m<=d1-l; m++) { if (i == idx) { l1 = l; m1 = m; } i++; } } // Compute the contribution to V from each image location. // Use individual threads to sum over columns. // tex[:,:,0] is the reference image, // tex[:,:,1] is the blurred reference image, // tex[:,:,2] is the target image, // tex[:,:,3] is the inverse variance, // tex[:,:,4] is the mask. // Bi is the basis image value. temp = 0.0; Bi = 1.0; __syncthreads(); for (idx = threadIdx.x; idx<nstamps; idx += blockDim.x) { j1 = max(0,(int)stamp_ypos[idx]-stamp_half_width); j2 = min(ny,(int)stamp_ypos[idx]+stamp_half_width); for (j=j1; j<j2; j++) { y = (j - 0.5(ny-1))/(ny-1); py = pow(y,m1); i1 = max(0,(int)stamp_xpos[idx]-stamp_half_width); i2 = min(nx,(int)stamp_xpos[idx]+stamp_half_width); for (i=i1; i<i2; i++) { x = (i - 0.5(nx-1))/(nx-1); if (ki == 0) { Bi = tex2DLayered(tex,i,j,0); } else if (ki < nkernel) { if (ext_basis[ki]) { Bi = tex2DLayered(tex,i+a,j+b,1)-tex2DLayered(tex,i,j,0); } else { Bi = tex2DLayered(tex,i+a,j+b,0)-tex2DLayered(tex,i,j,0); } } else { Bi = 1.0; } temp += pow(x,l1)pyBitex2DLayered(tex,i,j,2)tex2DLayered(tex,i,j,3)* tex2DLayered(tex,i,j,4); } } } count[threadIdx.x] = temp; __syncthreads(); // Then parallel-sum the rows i = blockDim.x/2; while (i != 0) { if (threadIdx.x < i) { count[threadIdx.x] += count[threadIdx.x + i]; } __syncthreads(); i /= 2; } if (threadIdx.x == 0) { V[blockIdx.x] = count[0]; } } __global__ void cu_compute_matrix(int dp, int ds, int db, int nx, int ny, int kxindex, int kyindex, int ext_basis, int nkernel, int kernelRadius,float H) { int idx, idy, idx0, idy0, idx1, idy1; int np, ns, ki, kj, a, b, c, d, d1, d2, i, j; int l, m, l1, m1, l2, m2; float py, x, y, Bi, Bj; double temp; __shared__ double count[THREADS_PER_BLOCK]; // Terminate if we are not in the lower triangle if (blockIdx.x > blockIdx.y) { return; } // Calculate number of terms in submatrices np = (dp+1)(dp+2)/2; ns = (ds+1)(ds+2)/2; // These are indices of the submatrix and their kernel offsets ki = blockIdx.x < np ? 0 : (blockIdx.x-np)/ns + 1; kj = blockIdx.y < np ? 0 : (blockIdx.y-np)/ns + 1; a = b = 0; if (ki<nkernel) { a = kxindex[ki]; b = kyindex[ki]; } if (kj<nkernel) { c = kxindex[kj]; d = kyindex[kj]; } // Set the polynomial degrees for the submatrix and the // indices within the submatrix if (ki == 0) { d1 = dp; idx = blockIdx.x; } else if (ki < nkernel) { d1 = ds; idx = blockIdx.x - np - (ki-1)ns; } else { d1 = db; idx = blockIdx.x - np - (ki-1)ns; } if (kj == 0) { d2 = dp; idy = blockIdx.y; } else if (kj < nkernel) { d2 = ds; idy = blockIdx.y - np - (kj-1)ns; } else { d2 = db; idy = blockIdx.y - np - (kj-1)ns; } if ((ki>0) && (ki<nkernel) && (kj>0) && (kj<nkernel) && (idx > idy)) { return; } idx0 = idx; idy0 = idy; // Compute the (l,m) values corresponding to the indices within // the submatrix i = 0; for (l=0; l<=d1; l++) { for (m=0; m<=d1-l; m++) { if (i == idx) { l1 = l; m1 = m; } i++; } } i = 0; for (l=0; l<=d2; l++) { for (m=0; m<=d2-l; m++) { if (i == idy) { l2 = l; m2 = m; } i++; } } // Compute the contribution to H from each image location. // Use individual threads to sum over columns. // tex[:,:,0] is the reference image, // tex[:,:,1] is the blurred reference image, // tex[:,:,2] is the target image, // tex[:,:,3] is the inverse variance, // tex[:,:,4] is the mask. // Bi and Bj are the basis image values. temp = 0.0; Bi = Bj = 1.0; __syncthreads(); for (j=kernelRadius; j<ny-kernelRadius; j++) { y = (j - 0.5(ny-1))/(ny-1); py = pow(y,m1+m2); for (i=threadIdx.x+kernelRadius; i<nx-kernelRadius; i+=blockDim.x) { x = (i - 0.5(nx-1))/(nx-1); if (ki == 0) { Bi = tex2DLayered(tex,i,j,0); } else if (ki < nkernel) { if (ext_basis[ki]) { Bi = tex2DLayered(tex,i+a,j+b,1)-tex2DLayered(tex,i,j,0); } else { Bi = tex2DLayered(tex,i+a,j+b,0)-tex2DLayered(tex,i,j,0); } } else { Bi = 1.0; } if (kj == 0) { Bj = tex2DLayered(tex,i,j,0); } else if (kj < nkernel) { if (ext_basis[kj]) { Bj = tex2DLayered(tex,i+c,j+d,1)-tex2DLayered(tex,i,j,0); } else { Bj = tex2DLayered(tex,i+c,j+d,0)-tex2DLayered(tex,i,j,0); } } else { Bj = 1.0; } temp += pow(x,l1+l2)pyBiBjtex2DLayered(tex,i,j,3)tex2DLayered(tex,i,j,4); } } count[threadIdx.x] = temp; __syncthreads(); // Then parallel-sum the rows i = blockDim.x/2; while (i != 0) { if (threadIdx.x < i) { count[threadIdx.x] += count[threadIdx.x + i]; } __syncthreads(); i /= 2; } if (threadIdx.x == 0) { H[blockIdx.x+gridDim.xblockIdx.y] = count[0]; H[blockIdx.y+gridDim.xblockIdx.x] = count[0]; if ((ki>0) && (ki<nkernel) && (kj>0) && (kj<nkernel)) { idx1 = np + (ki-1)ns; idy1 = np + (kj-1)ns; H[(idx1+idy0)+gridDim.x(idy1+idx0)] = count[0]; H[(idy1+idx0)+gridDim.x(idx1+idy0)] = count[0]; } } } __global__ void cu_compute_matrix_stamps(int dp, int ds, int db, int nx, int ny, int nstamps, int stamp_half_width, float stamp_xpos, float* stamp_ypos, int kxindex, int kyindex, int ext_basis, int nkernel, int kernelRadius,float H) { int idx, idy, idx0, idy0, idx1, idy1; int np, ns, ki, kj, a, b, c, d, d1, d2, i, j, i1, i2, j1, j2; int l, m, l1, m1, l2, m2; float px, py, x, y, Bi, Bj; double temp; __shared__ double count[THREADS_PER_BLOCK]; // Terminate if we are not in the lower triangle if (blockIdx.x > blockIdx.y) { return; } // Calculate number of terms in submatrices np = (dp+1)(dp+2)/2; ns = (ds+1)(ds+2)/2; // These are indices of the submatrix and their kernel offsets ki = blockIdx.x < np ? 0 : (blockIdx.x-np)/ns + 1; kj = blockIdx.y < np ? 0 : (blockIdx.y-np)/ns + 1; a = b = 0; if (ki<nkernel) { a = kxindex[ki]; b = kyindex[ki]; } if (kj<nkernel) { c = kxindex[kj]; d = kyindex[kj]; } // Set the polynomial degrees for the submatrix and the // indices within the submatrix if (ki == 0) { d1 = dp; idx = blockIdx.x; } else if (ki < nkernel) { d1 = ds; idx = blockIdx.x - np - (ki-1)ns; } else { d1 = db; idx = blockIdx.x - np - (ki-1)ns; } if (kj == 0) { d2 = dp; idy = blockIdx.y; } else if (kj < nkernel) { d2 = ds; idy = blockIdx.y - np - (kj-1)ns; } else { d2 = db; idy = blockIdx.y - np - (kj-1)ns; } if ((ki>0) && (ki<nkernel) && (kj>0) && (kj<nkernel) && (idx > idy)) { return; } idx0 = idx; idy0 = idy; // Compute the (l,m) values corresponding to the indices within // the submatrix i = 0; for (l=0; l<=d1; l++) { for (m=0; m<=d1-l; m++) { if (i == idx) { l1 = l; m1 = m; } i++; } } i = 0; for (l=0; l<=d2; l++) { for (m=0; m<=d2-l; m++) { if (i == idy) { l2 = l; m2 = m; } i++; } } // Compute the contribution to H from each image location. // Use individual threads to sum over stamps. // tex[:,:,0] is the reference image, // tex[:,:,1] is the blurred reference image, // tex[:,:,2] is the target image, // tex[:,:,3] is the inverse variance, // tex[:,:,4] is the mask. // Bi and Bj are the basis image values. temp = 0.0; Bi = Bj = 1.0; __syncthreads(); for (idx = threadIdx.x; idx<nstamps; idx += blockDim.x) { i1 = max(0,(int)stamp_xpos[idx]-stamp_half_width); i2 = min(nx,(int)stamp_xpos[idx]+stamp_half_width); for (i=i1; i<i2; i++) { x = (i - 0.5(nx-1))/(nx-1); px = pow(x,l1+l2); j1 = max(0,(int)stamp_ypos[idx]-stamp_half_width); j2 = min(ny,(int)stamp_ypos[idx]+stamp_half_width); for (j=j1; j<j2; j++) { y = (j - 0.5(ny-1))/(ny-1); py = pow(y,m1+m2); if (ki == 0) { Bi = tex2DLayered(tex,i,j,0); } else if (ki < nkernel) { if (ext_basis[ki]) { Bi = tex2DLayered(tex,i+a,j+b,1)-tex2DLayered(tex,i,j,0); } else { Bi = tex2DLayered(tex,i+a,j+b,0)-tex2DLayered(tex,i,j,0); } } else { Bi = 1.0; } if (kj == 0) { Bj = tex2DLayered(tex,i,j,0); } else if (kj < nkernel) { if (ext_basis[kj]) { Bj = tex2DLayered(tex,i+c,j+d,1)-tex2DLayered(tex,i,j,0); } else { Bj = tex2DLayered(tex,i+c,j+d,0)-tex2DLayered(tex,i,j,0); } } else { Bj = 1.0; } temp += pxpyBiBjtex2DLayered(tex,i,j,3)tex2DLayered(tex,i,j,4); } } } count[threadIdx.x] = temp; __syncthreads(); // Then parallel-sum the rows i = blockDim.x/2; while (i != 0) { if (threadIdx.x < i) { count[threadIdx.x] += count[threadIdx.x + i]; } __syncthreads(); i /= 2; } if (threadIdx.x == 0) { H[blockIdx.x+gridDim.xblockIdx.y] = count[0]; H[blockIdx.y+gridDim.xblockIdx.x] = count[0]; if ((ki>0) && (ki<nkernel) && (kj>0) && (kj<nkernel)) { idx1 = np + (ki-1)ns; idy1 = np + (kj-1)ns; H[(idx1+idy0)+gridDim.x(idy1+idx0)] = count[0]; H[(idy1+idx0)+gridDim.x*(idx1+idy0)] = count[0]; } } } """)	0	0	0
127f75e4af1c5b7ee4fe6000ac7878906b35420f	5,466	py	Python	taro/jobs/job.py	taro-suite/taro	baa76e75706bc824a799928d9b7548431b898338	[ "MIT" ]	null	null	null	taro/jobs/job.py	taro-suite/taro	baa76e75706bc824a799928d9b7548431b898338	[ "MIT" ]	26	2021-04-05T12:32:21.000Z	2022-03-22T12:53:44.000Z	taro/jobs/job.py	taro-suite/taro	baa76e75706bc824a799928d9b7548431b898338	[ "MIT" ]	1	2021-04-16T21:04:53.000Z	2021-04-16T21:04:53.000Z	""" Job framework defines components used for job submission and management. It is built upon :mod:`execution` framework. It provides constructs for: 1. Creating of job definition 2. Implementing of job instance 3. Implementing of job observer There are two type of clients of the framework: 1. Job users 2. Job management implementation """ import abc from collections import namedtuple from fnmatch import fnmatch from taro.jobs.execution import ExecutionError class JobInfo: """ Immutable snapshot of job instance state """ @property @property @property @property @property @property @property DisabledJob = namedtuple('DisabledJob', 'job_id regex created expires') Warn = namedtuple('Warn', 'name params') WarnEventCtx = namedtuple('WarnEventCtx', 'count')	24.079295	115	0.643981	""" Job framework defines components used for job submission and management. It is built upon :mod:`execution` framework. It provides constructs for: 1. Creating of job definition 2. Implementing of job instance 3. Implementing of job observer There are two type of clients of the framework: 1. Job users 2. Job management implementation """ import abc from collections import namedtuple from fnmatch import fnmatch from taro.jobs.execution import ExecutionError class JobInstance(abc.ABC): @property @abc.abstractmethod def job_id(self) -> str: """Identifier of the job of this instance""" @property @abc.abstractmethod def instance_id(self) -> str: """Identifier of this instance""" @property @abc.abstractmethod def lifecycle(self): """Execution lifecycle of this instance""" @property @abc.abstractmethod def status(self): """Current status of the job or None if not supported""" @property @abc.abstractmethod def last_output(self): """Last lines of output or None if not supported""" @property @abc.abstractmethod def warnings(self): """ Return dictionary of {alarm_name: occurrence_count} :return: warnings """ @abc.abstractmethod def add_warning(self, warning): """ Add warning to the instance :param warning warning to add """ @property @abc.abstractmethod def exec_error(self) -> ExecutionError: """Job execution error if occurred otherwise None""" @abc.abstractmethod def create_info(self): """ Create consistent (thread-safe) snapshot of job instance state :return job (instance) info """ @abc.abstractmethod def stop(self): """ Stop running execution gracefully """ @abc.abstractmethod def interrupt(self): """ Stop running execution immediately """ @abc.abstractmethod def add_state_observer(self, observer): """ Register execution state observer Observer can be: 1. An instance of ExecutionStateObserver 2. Callable object with single parameter of JobInfo type :param observer observer to register """ @abc.abstractmethod def remove_state_observer(self, observer): """ De-register execution state observer :param observer observer to de-register """ @abc.abstractmethod def add_warning_observer(self, observer): """ Register warning observer :param observer observer to register """ @abc.abstractmethod def remove_warning_observer(self, observer): """ De-register warning observer :param observer observer to de-register """ @abc.abstractmethod def add_output_observer(self, observer): """ Register output observer :param observer observer to register """ @abc.abstractmethod def remove_output_observer(self, observer): """ De-register output observer :param observer observer to de-register """ class JobInfo: """ Immutable snapshot of job instance state """ def __init__(self, job_id: str, instance_id: str, lifecycle, status, warnings, exec_error: ExecutionError): self._job_id = job_id self._instance_id = instance_id self._lifecycle = lifecycle self._status = status self._warnings = warnings self._exec_error = exec_error @property def job_id(self) -> str: return self._job_id @property def instance_id(self) -> str: return self._instance_id @property def lifecycle(self): return self._lifecycle @property def state(self): return self._lifecycle.state() @property def status(self): return self._status @property def warnings(self): return self._warnings @property def exec_error(self) -> ExecutionError: return self._exec_error def matches(self, instance, job_matching_strategy=fnmatch): return job_matching_strategy(self.job_id, instance) or fnmatch(self.instance_id, instance) def __repr__(self) -> str: return "{}({!r}, {!r}, {!r}, {!r}, {!r}, {!r})".format( self.__class__.__name__, self._job_id, self.instance_id, self._lifecycle, self._status, self._warnings, self._exec_error) class JobInfoCollection: def __init__(self, *jobs): self._jobs = jobs @property def jobs(self): return list(self._jobs) class ExecutionStateObserver(abc.ABC): @abc.abstractmethod def state_update(self, job_info: JobInfo): """This method is called when job instance execution state is changed.""" DisabledJob = namedtuple('DisabledJob', 'job_id regex created expires') Warn = namedtuple('Warn', 'name params') WarnEventCtx = namedtuple('WarnEventCtx', 'count') class WarningObserver(abc.ABC): @abc.abstractmethod def new_warning(self, job_info: JobInfo, warning: Warn, event_ctx: WarnEventCtx): """This method is called when there is a new warning event.""" class JobOutputObserver(abc.ABC): @abc.abstractmethod def output_update(self, job_info: JobInfo, output): """Executed when new output line is available."""	941	3,316	378
7e126c872bc77ec31b05758c5eda86b8368ea35a	305	py	Python	plugins/test/main.py	StyXman/pbt	83dac5b896e9037fac17453f21a4d14faa25c09e	[ "Apache-2.0" ]	1	2015-07-16T19:14:50.000Z	2015-07-16T19:14:50.000Z	plugins/test/main.py	StyXman/pbt	83dac5b896e9037fac17453f21a4d14faa25c09e	[ "Apache-2.0" ]	null	null	null	plugins/test/main.py	StyXman/pbt	83dac5b896e9037fac17453f21a4d14faa25c09e	[ "Apache-2.0" ]	null	null	null	import pbt import sys import unittest @pbt.command(name="test")	23.461538	53	0.704918	import pbt import sys import unittest @pbt.command(name="test") def run(ctx, args, project): loader = unittest.TestLoader() for test_dir in project.settings.test_paths: tests = loader.discover(test_dir) testRunner = unittest.runner.TextTestRunner() testRunner.run(tests)	217	0	22
258df39239a3f809e93d6348ebe51ed653b9433d	285	py	Python	test/api/test_nvgli.py	lonagi/pynvg	a7b28952960184509eba8060e10ddd824913b08e	[ "MIT" ]	null	null	null	test/api/test_nvgli.py	lonagi/pynvg	a7b28952960184509eba8060e10ddd824913b08e	[ "MIT" ]	null	null	null	test/api/test_nvgli.py	lonagi/pynvg	a7b28952960184509eba8060e10ddd824913b08e	[ "MIT" ]	null	null	null	import unittest from pynvg.api import nvgli if(__name__=="main"): unittest.main()	20.357143	39	0.642105	import unittest from pynvg.api import nvgli class NVGLiTestCase(unittest.TestCase): def test_nvgli(self): url = "nvg-grou.com"; result="https://nvg.li/nvg"; test=nvgli(url); self.assertEqual(test,result) if(__name__=="main"): unittest.main()	131	18	50
2a6533ef8ebb5fa457b07048f4ff5f7a4f159684	400	py	Python	hlwtadmin/migrations/0024_concertannouncement_seen_count.py	Kunstenpunt/havelovewilltravel	6a27824b4d3d8b1bf19e0bc0d0648f0f4e8abc83	[ "Apache-2.0" ]	1	2020-10-16T16:29:01.000Z	2020-10-16T16:29:01.000Z	hlwtadmin/migrations/0024_concertannouncement_seen_count.py	Kunstenpunt/havelovewilltravel	6a27824b4d3d8b1bf19e0bc0d0648f0f4e8abc83	[ "Apache-2.0" ]	365	2020-02-03T12:46:53.000Z	2022-02-27T17:20:46.000Z	hlwtadmin/migrations/0024_concertannouncement_seen_count.py	Kunstenpunt/havelovewilltravel	6a27824b4d3d8b1bf19e0bc0d0648f0f4e8abc83	[ "Apache-2.0" ]	null	null	null	# Generated by Django 3.0 on 2020-03-25 09:09 from django.db import migrations, models	21.052632	49	0.615	# Generated by Django 3.0 on 2020-03-25 09:09 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('hlwtadmin', '0023_auto_20200323_1239'), ] operations = [ migrations.AddField( model_name='concertannouncement', name='seen_count', field=models.IntegerField(default=1), ), ]	0	288	23
13c657a63c4bc6f64117453622ae0d605cc4d139	735	py	Python	uptee/lib/template_loader.py	teeworldsCNFun/upTee	1c04b7421f4834f83bbb9f59f43dfebac08e56b0	[ "BSD-3-Clause" ]	2	2018-12-26T18:48:58.000Z	2021-07-20T23:41:14.000Z	uptee/lib/template_loader.py	teeworldsCNFun/upTee	1c04b7421f4834f83bbb9f59f43dfebac08e56b0	[ "BSD-3-Clause" ]	13	2015-01-20T19:18:10.000Z	2022-03-07T21:35:55.000Z	uptee/lib/template_loader.py	teeworldsCNFun/upTee	1c04b7421f4834f83bbb9f59f43dfebac08e56b0	[ "BSD-3-Clause" ]	3	2015-12-04T20:10:50.000Z	2022-01-24T12:31:09.000Z	import os from django.template.loaders.filesystem import Loader as FileSystemLoader from accounts.models import get_template import settings	38.684211	85	0.711565	import os from django.template.loaders.filesystem import Loader as FileSystemLoader from accounts.models import get_template import settings class Loader(FileSystemLoader): def get_template_sources(self, template_name, template_dirs=None): if not template_dirs: template = settings.DEFAULT_TEMPLATE request = getattr(settings, 'request_handler', None) template_dirs = settings.TEMPLATE_DIRS if request: template = get_template(request) template_dirs = [os.path.join(path, template) for path in template_dirs] template_dirs = tuple(template_dirs) return super(Loader, self).get_template_sources(template_name, template_dirs)	533	10	50
a7dbb1c47342dbe9ec25e6f02175caff451286c8	910	py	Python	oop/class_ipaddress.py	levs72/pyneng-examples	d6288292dcf9d1ebc5a9db4a0d620bd11b4a2df9	[ "MIT" ]	11	2021-04-05T09:30:23.000Z	2022-03-09T13:27:56.000Z	oop/class_ipaddress.py	levs72/pyneng-examples	d6288292dcf9d1ebc5a9db4a0d620bd11b4a2df9	[ "MIT" ]	null	null	null	oop/class_ipaddress.py	levs72/pyneng-examples	d6288292dcf9d1ebc5a9db4a0d620bd11b4a2df9	[ "MIT" ]	11	2021-04-06T03:44:35.000Z	2022-03-04T21:20:40.000Z	import ipaddress if __name__ == "__main__": ip1 = IPAddress("10.1.1.1/25") print(ip1 + 5) print(5 + ip1) print(ip1.__radd__(5))	26	62	0.579121	import ipaddress class IPAddress: def __init__(self, ip): address, mask = ip.split("/") self.address = address self.mask = int(mask) def __str__(self): return f"{self.address}/{self.mask}" def __repr__(self): return f"IPAddress('{self.address}/{self.mask}')" def __add__(self, second): if not isinstance(second, int): raise TypeError( f"unsupported operand type(s) for +: " f"'IPAddress' and '{type(second).__name__}'" ) ip_int = int(ipaddress.ip_address(self.address)) result_ip = str(ipaddress.ip_address(ip_int + second)) return IPAddress(f"{result_ip}/{self.mask}") def __radd__(self, number): return self + number if __name__ == "__main__": ip1 = IPAddress("10.1.1.1/25") print(ip1 + 5) print(5 + ip1) print(ip1.__radd__(5))	611	-5	157