repo_name stringlengths 7 90 | path stringlengths 5 191 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 976 581k | license stringclasses 15
values |
|---|---|---|---|---|---|
seaotterman/tensorflow | tensorflow/examples/learn/iris_run_config.py | 86 | 2087 | # Copyright 2016 The TensorFlow 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 appl... | apache-2.0 |
sinhrks/expandas | pandas_ml/skaccessors/test/test_svm.py | 2 | 2995 | #!/usr/bin/env python
import pytest
import numpy as np
import sklearn.datasets as datasets
import sklearn.svm as svm
import pandas_ml as pdml
import pandas_ml.util.testing as tm
class TestSVM(tm.TestCase):
def test_objectmapper(self):
df = pdml.ModelFrame([])
self.assertIs(df.svm... | bsd-3-clause |
arahuja/scikit-learn | examples/linear_model/plot_sgd_separating_hyperplane.py | 260 | 1219 | """
=========================================
SGD: Maximum margin separating hyperplane
=========================================
Plot the maximum margin separating hyperplane within a two-class
separable dataset using a linear Support Vector Machines classifier
trained using SGD.
"""
print(__doc__)
import numpy as n... | bsd-3-clause |
vybstat/scikit-learn | sklearn/decomposition/tests/test_incremental_pca.py | 297 | 8265 | """Tests for Incremental PCA."""
import numpy as np
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_raises
from sklearn import datasets
from sklearn.decomposition import PCA, IncrementalPCA
iris = datasets.load... | bsd-3-clause |
scipy/scipy | scipy/signal/bsplines.py | 12 | 19509 | from numpy import (logical_and, asarray, pi, zeros_like,
piecewise, array, arctan2, tan, zeros, arange, floor)
from numpy.core.umath import (sqrt, exp, greater, less, cos, add, sin,
less_equal, greater_equal)
# From splinemodule.c
from .spline import cspline2d, sepfir2d... | bsd-3-clause |
mmaraya/nd101 | ch02/lesson04/and.perceptron.py | 1 | 1065 | #!/usr/bin/env python
import pandas as pd
# Set weight1, weight2, and bias
weight1 = 0.5
weight2 = 0.5
bias = -1.0
# DON'T CHANGE ANYTHING BELOW
# Inputs and outputs
test_inputs = [(0, 0), (0, 1), (1, 0), (1, 1)]
correct_outputs = [False, False, False, True]
outputs = []
# Generate and check output
for test_input,... | mit |
mahak/spark | python/pyspark/pandas/base.py | 3 | 55960 | #
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not us... | apache-2.0 |
moutai/scikit-learn | examples/model_selection/plot_confusion_matrix.py | 47 | 2495 | """
================
Confusion matrix
================
Example of confusion matrix usage to evaluate the quality
of the output of a classifier on the iris data set. The
diagonal elements represent the number of points for which
the predicted label is equal to the true label, while
off-diagonal elements are those that ... | bsd-3-clause |
sppalkia/weld | python/grizzly/grizzly/seriesweld.py | 3 | 19541 | import pandas as pd
import grizzly_impl
from lazy_op import LazyOpResult, to_weld_type
from weld.weldobject import *
import utils
class SeriesWeld(LazyOpResult):
"""Summary
Attributes:
column_name (TYPE): Description
df (TYPE): Description
dim (int): Description
expr (TYPE): ... | bsd-3-clause |
PMitura/smiles-neural-network | baselines/sicho_svm_uni_feature_sel.py | 1 | 8481 | #! /usr/bin/env python
import db
import math
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from rdkit import Chem
from rdkit.Chem import Descriptors
from sklearn.feature_selection import VarianceThreshold
import pylab
data = db.getTarget_206_1977()
duplicates = {}
for datum in data:
i... | bsd-3-clause |
rs2/pandas | pandas/tests/indexes/multi/test_drop.py | 2 | 4428 | import numpy as np
import pytest
from pandas.errors import PerformanceWarning
import pandas as pd
from pandas import Index, MultiIndex
import pandas._testing as tm
def test_drop(idx):
dropped = idx.drop([("foo", "two"), ("qux", "one")])
index = MultiIndex.from_tuples([("foo", "two"), ("qux", "one")])
d... | bsd-3-clause |
evgchz/scikit-learn | sklearn/neural_network/rbm.py | 15 | 11957 | """Restricted Boltzmann Machine
"""
# Authors: Yann N. Dauphin <dauphiya@iro.umontreal.ca>
# Vlad Niculae
# Gabriel Synnaeve
# Lars Buitinck
# License: BSD 3 clause
import time
import numpy as np
import scipy.sparse as sp
from ..base import BaseEstimator
from ..base import TransformerMixi... | bsd-3-clause |
KeithYue/StockTrading | utility.py | 1 | 4059 | # coding=utf-8
# utility function of stock
import os
import pandas as pd
import numpy as np
import logging
# config the logging system
logging.basicConfig(level=logging.DEBUG)
# define Stock class
class Stock():
'''
the stock class
'''
def __init__(self, code):
self.code=code
# search ... | apache-2.0 |
Sentient07/scikit-learn | examples/ensemble/plot_voting_probas.py | 316 | 2824 | """
===========================================================
Plot class probabilities calculated by the VotingClassifier
===========================================================
Plot the class probabilities of the first sample in a toy dataset
predicted by three different classifiers and averaged by the
`VotingC... | bsd-3-clause |
nkoukou/University_Projects_Year_3 | EDM_Assembly/base_class.py | 1 | 11366 | '''
Defines the base class of an electric potential grid.
'''
import numpy as np
import matplotlib as mpl
import matplotlib.pylab as plt
from numba import jit
# Global dimensions (used for plots)
sqc_x = (2., 'cm') # unit length for SquareCable
sqc_u = (10., 'V') # unit potential for SquareCable
edm_x = (10., 'mm')... | mit |
victor-prado/broker-manager | environment/lib/python3.5/site-packages/pandas/tests/frame/test_mutate_columns.py | 7 | 7831 | # -*- coding: utf-8 -*-
from __future__ import print_function
from pandas.compat import range, lrange
import numpy as np
from pandas import DataFrame, Series, Index
from pandas.util.testing import (assert_series_equal,
assert_frame_equal,
assertRaise... | mit |
bikong2/scikit-learn | sklearn/tests/test_random_projection.py | 79 | 14035 | from __future__ import division
import numpy as np
import scipy.sparse as sp
from sklearn.metrics import euclidean_distances
from sklearn.random_projection import johnson_lindenstrauss_min_dim
from sklearn.random_projection import gaussian_random_matrix
from sklearn.random_projection import sparse_random_matrix
from... | bsd-3-clause |
evidation-health/pymc3 | setup.py | 1 | 2670 | #!/usr/bin/env python
from setuptools import setup
import sys
DISTNAME = 'pymc3'
DESCRIPTION = "PyMC3"
LONG_DESCRIPTION = """Bayesian estimation, particularly using Markov chain Monte Carlo (MCMC), is an increasingly relevant approach to statistical estimation. However, few statistical software packages implement ... | apache-2.0 |
cgrohman/ponies | hypo1.py | 1 | 4172 | import numpy as np
import pandas as pd
from horse import Horse
from race import Race
import pdb
from sklearn.preprocessing import Imputer, StandardScaler, OneHotEncoder
from sklearn.model_selection import train_test_split
#------------------------------------------------------------------------------
def main():
da... | gpl-3.0 |
vberthiaume/vblandr | src/silenceTest.py | 1 | 3381 | import subprocess as sp
import scikits.audiolab
import numpy as np
from scipy.fftpack import fft, ifft
from scipy.io import wavfile
import bisect
import matplotlib.pyplot as plt
import time
plt.rcParams['agg.path.chunksize'] = 10000
#--CONVERT MP3 TO WAV------------------------------------------
#song_path = '/home/g... | apache-2.0 |
joshloyal/scikit-learn | sklearn/linear_model/passive_aggressive.py | 28 | 11542 | # Authors: Rob Zinkov, Mathieu Blondel
# License: BSD 3 clause
from .stochastic_gradient import BaseSGDClassifier
from .stochastic_gradient import BaseSGDRegressor
from .stochastic_gradient import DEFAULT_EPSILON
class PassiveAggressiveClassifier(BaseSGDClassifier):
"""Passive Aggressive Classifier
Read mor... | bsd-3-clause |
QuLogic/burnman | misc/benchmarks/solidsolution_benchmarks.py | 1 | 6797 | # Benchmarks for the solid solution class
import os.path, sys
sys.path.insert(1,os.path.abspath('../..'))
import burnman
from burnman import minerals
from burnman.processchemistry import *
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
atomic_masses=read_masses()
'''
Solvus sha... | gpl-2.0 |
hdmetor/scikit-learn | examples/applications/plot_prediction_latency.py | 234 | 11277 | """
==================
Prediction Latency
==================
This is an example showing the prediction latency of various scikit-learn
estimators.
The goal is to measure the latency one can expect when doing predictions
either in bulk or atomic (i.e. one by one) mode.
The plots represent the distribution of the pred... | bsd-3-clause |
bthirion/scikit-learn | sklearn/feature_extraction/hashing.py | 74 | 6153 | # Author: Lars Buitinck
# License: BSD 3 clause
import numbers
import numpy as np
import scipy.sparse as sp
from . import _hashing
from ..base import BaseEstimator, TransformerMixin
def _iteritems(d):
"""Like d.iteritems, but accepts any collections.Mapping."""
return d.iteritems() if hasattr(d, "iteritems... | bsd-3-clause |
madengr/usrp_rf_tests | apps/b200_two_tone_tx_test.py | 1 | 5934 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Created on Sat Jul 26 20:28:23 2014
USRP generates two tones with swept gain and frequency
Tone and IMD powers measured with spectrum analyzer
@author: madengr
"""
import instruments
import numpy as np
import time
from gnuradio import gr
from gnuradio import uhd
from gn... | gpl-3.0 |
libAtoms/matscipy | examples/electrochemistry/samples_pb_c2d.py | 1 | 63342 | # -*- coding: utf-8 -*-
# ---
# jupyter:
# jupytext:
# formats: ipynb,py:percent
# text_representation:
# extension: .py
# format_name: percent
# format_version: '1.3'
# jupytext_version: 1.6.0
# kernelspec:
# display_name: Python 3
# language: python
# name: python3
# --... | gpl-2.0 |
DangoMelon0701/PyRemote-Sensing | Scatter Plot/np_scatter_plot.py | 1 | 7491 | # -*- coding: utf-8 -*-
"""
Created on Tue Dec 06 13:17:45 2016
@author: gerar
"""
# Este archivo toma como datos de entrada un ASCII
# con 5 Columnas
# Date_MODIS Time_MODIS AOD_MODIS Time_AERONET AOD_AERONET
# Se puede usar en conjunto con el codigo llamado
# pd_match_data.py
import os
import numpy as n... | mit |
Eksmo/calibre | setup/installer/linux/freeze.py | 2 | 11661 | #!/usr/bin/env python
from __future__ import with_statement
__license__ = 'GPL v3'
__copyright__ = '2008, Kovid Goyal kovid@kovidgoyal.net'
__docformat__ = 'restructuredtext en'
'''
Create linux binary.
'''
from setup import Command, __version__, __appname__
class LinuxFreeze(Command):
description = 'Create ... | gpl-3.0 |
emetsger/osf.io | scripts/analytics/addons.py | 18 | 2173 | # -*- coding: utf-8 -*-
import os
import re
import matplotlib.pyplot as plt
from framework.mongo import database
from website import settings
from website.app import init_app
from .utils import plot_dates, oid_to_datetime, mkdirp
log_collection = database['nodelog']
FIG_PATH = os.path.join(settings.ANALYTICS_PATH... | apache-2.0 |
maheshakya/scikit-learn | examples/linear_model/plot_iris_logistic.py | 283 | 1678 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Logistic Regression 3-class Classifier
=========================================================
Show below is a logistic-regression classifiers decision boundaries on the
`iris <http://en.wikipedia.org/wiki/Iris_f... | bsd-3-clause |
zuku1985/scikit-learn | sklearn/exceptions.py | 50 | 5276 | """
The :mod:`sklearn.exceptions` module includes all custom warnings and error
classes used across scikit-learn.
"""
__all__ = ['NotFittedError',
'ChangedBehaviorWarning',
'ConvergenceWarning',
'DataConversionWarning',
'DataDimensionalityWarning',
'EfficiencyWarn... | bsd-3-clause |
dgwakeman/mne-python | examples/realtime/ftclient_rt_compute_psd.py | 17 | 2460 | """
==============================================================
Compute real-time power spectrum density with FieldTrip client
==============================================================
Please refer to `ftclient_rt_average.py` for instructions on
how to get the FieldTrip connector working in MNE-Python.
This e... | bsd-3-clause |
effigies/mne-python | examples/stats/plot_spatio_temporal_cluster_stats_sensor.py | 1 | 5435 | """
=====================================================
Spatiotemporal permutation F-test on full sensor data
=====================================================
Tests for differential evoked responses in at least
one condition using a permutation clustering test.
The FieldTrip neighbor templates will be used to d... | bsd-3-clause |
stylianos-kampakis/scikit-learn | examples/model_selection/plot_train_error_vs_test_error.py | 349 | 2577 | """
=========================
Train error vs Test error
=========================
Illustration of how the performance of an estimator on unseen data (test data)
is not the same as the performance on training data. As the regularization
increases the performance on train decreases while the performance on test
is optim... | bsd-3-clause |
marcoantoniooliveira/labweb | oscar/lib/python2.7/site-packages/IPython/external/qt_for_kernel.py | 9 | 2379 | """ Import Qt in a manner suitable for an IPython kernel.
This is the import used for the `gui=qt` or `matplotlib=qt` initialization.
Import Priority:
if Qt4 has been imported anywhere else:
use that
if matplotlib has been imported and doesn't support v2 (<= 1.0.1):
use PyQt4 @v1
Next, ask ETS' QT_API env v... | bsd-3-clause |
nicholsn/ncanda-data-integration | scripts/redcap/scoring/psqi/__init__.py | 2 | 2693 | #!/usr/bin/env python
##
## See COPYING file distributed along with the ncanda-data-integration package
## for the copyright and license terms
##
import re
import pandas
import RwrapperNew
#
# Variables from surveys needed for PSQI
#
# LimeSurvey field names
lime_fields = [ "psqi1", "psqi2", "psqi3", "psqi4", "... | bsd-3-clause |
heidi-ann/ocaml-raft-data | plotting_funct.py | 1 | 3255 | from matplotlib import rc
import matplotlib.pyplot as plt
import matplotlib.pylab as pyl
import numpy as np
import csv
from itertools import cycle
from utils import *
figs = ['org','expo','combo','fixed']
graph_a = ['12-24','25-50','50-100','100-200','150-300']
graph_b = ['150-151','150-155','150-175','150-200','150-3... | mit |
russel1237/scikit-learn | sklearn/ensemble/gradient_boosting.py | 12 | 69795 | """Gradient Boosted Regression Trees
This module contains methods for fitting gradient boosted regression trees for
both classification and regression.
The module structure is the following:
- The ``BaseGradientBoosting`` base class implements a common ``fit`` method
for all the estimators in the module. Regressio... | bsd-3-clause |
webmasterraj/GaSiProMo | flask/lib/python2.7/site-packages/pandas/tools/tests/test_merge.py | 3 | 98825 | # pylint: disable=E1103
import nose
from datetime import datetime
from numpy.random import randn
from numpy import nan
import numpy as np
import random
import pandas as pd
from pandas.compat import range, lrange, lzip, zip, StringIO
from pandas import compat
from pandas.tseries.index import DatetimeIndex
from pandas... | gpl-2.0 |
chrsrds/scikit-learn | sklearn/tests/test_isotonic.py | 1 | 16117 | import warnings
import numpy as np
import pickle
import copy
from sklearn.isotonic import (check_increasing, isotonic_regression,
IsotonicRegression, _make_unique)
from sklearn.utils.validation import check_array
from sklearn.utils.testing import (assert_raises, assert_array_equal,
... | bsd-3-clause |
AlfredNeverKog/BrainCarya | src/my/kadenze/lesson4/inception_graph.py | 1 | 2023 | import numpy as np
import tensorflow as tf
from PIL import Image
from scipy import misc
from tensorflow.python.platform import gfile
import matplotlib.pyplot as plt
from src.my.lib.utils import montage_filters,montage
model, labels = ('./inception5h/tensorflow_inception_graph.pb',
'./inception5h/imagen... | mit |
pypot/scikit-learn | examples/semi_supervised/plot_label_propagation_structure.py | 247 | 2432 | """
==============================================
Label Propagation learning a complex structure
==============================================
Example of LabelPropagation learning a complex internal structure
to demonstrate "manifold learning". The outer circle should be
labeled "red" and the inner circle "blue". Be... | bsd-3-clause |
kevin-intel/scikit-learn | sklearn/inspection/tests/test_permutation_importance.py | 5 | 19332 | import pytest
import numpy as np
from numpy.testing import assert_allclose
from sklearn.compose import ColumnTransformer
from sklearn.datasets import load_diabetes
from sklearn.datasets import load_iris
from sklearn.datasets import make_classification
from sklearn.datasets import make_regression
from sklearn.dummy im... | bsd-3-clause |
ishanic/scikit-learn | sklearn/utils/arpack.py | 265 | 64837 | """
This contains a copy of the future version of
scipy.sparse.linalg.eigen.arpack.eigsh
It's an upgraded wrapper of the ARPACK library which
allows the use of shift-invert mode for symmetric matrices.
Find a few eigenvectors and eigenvalues of a matrix.
Uses ARPACK: http://www.caam.rice.edu/software/ARPACK/
"""
#... | bsd-3-clause |
manns/pyspread | pyspread/model/model.py | 1 | 51023 | # -*- coding: utf-8 -*-
# Copyright Martin Manns
# Distributed under the terms of the GNU General Public License
# --------------------------------------------------------------------
# pyspread is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published... | gpl-3.0 |
cbertinato/pandas | pandas/tests/frame/test_timezones.py | 1 | 7854 | """
Tests for DataFrame timezone-related methods
"""
from datetime import datetime
import numpy as np
import pytest
import pytz
from pandas.core.dtypes.dtypes import DatetimeTZDtype
import pandas as pd
from pandas import DataFrame, Series
from pandas.core.indexes.datetimes import date_range
import pandas.util.testin... | bsd-3-clause |
cassinius/right-to-forget-data | src/multi_class/linear_svc.py | 1 | 1024 | from sklearn.multiclass import OneVsRestClassifier
from sklearn.svm import LinearSVC
from src.multi_class import input_preproc
from src.multi_class import calculate_metrics
def runClassifier(X_train, X_test, y_train, y_test):
# print y_train
predictions = OneVsRestClassifier(LinearSVC(), n_jobs=-1)\
... | apache-2.0 |
barentsen/dave | milesplay/productionPCA.py | 1 | 16265 |
"""
Created on Tue Aug 2 09:55:43 2016
@author: Miles
"""
import numpy as np
import matplotlib.pyplot as plt
import dave.fileio.mastio as mastio
import dave.fileio.tpf as tpf
import dave.fileio.kplrfits as kplrfits
import dave.misc.noise as noise
import gapfill
def getData(epic, campaign):
"""Obtains the data ... | mit |
cohortfsllc/cohort-cocl2-sandbox | buildbot/buildbot_selector.py | 2 | 19580 | #!/usr/bin/python
# Copyright (c) 2012 The Native Client Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
import json
import os
import subprocess
import sys
import tempfile
sys.path.append(os.path.join(os.path.dirname(__file__), '..'))... | bsd-3-clause |
Srisai85/scikit-learn | examples/mixture/plot_gmm.py | 248 | 2817 | """
=================================
Gaussian Mixture Model Ellipsoids
=================================
Plot the confidence ellipsoids of a mixture of two Gaussians with EM
and variational Dirichlet process.
Both models have access to five components with which to fit the
data. Note that the EM model will necessari... | bsd-3-clause |
jgomezc1/FEM-Notes | scripts/1DELEMENT.py | 1 | 1170 | # -*- coding: utf-8 -*-
"""
--------1D Lagramge interpolation problem---------------
"""
from __future__ import division
import lagrange as la
import matplotlib.pyplot as plt
import numpy as np
from sympy import *
from sympy import init_printing
init_printing()
#
fx = lambda x: x**3 + 4*x**2 - 10.0;
#
# Assign symbols
... | mit |
aayushidwivedi01/spark-tk | python/sparktk/frame/constructors/import_pandas.py | 12 | 8940 | # vim: set encoding=utf-8
# Copyright (c) 2016 Intel Corporation
#
# 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 require... | apache-2.0 |
mne-tools/mne-tools.github.io | 0.22/_downloads/68dbe405ac02c372b6167f7e86b7e3e0/plot_background_filtering.py | 4 | 49916 | # -*- coding: utf-8 -*-
r"""
.. _disc-filtering:
===================================
Background information on filtering
===================================
Here we give some background information on filtering in general, and
how it is done in MNE-Python in particular.
Recommended reading for practical applications ... | bsd-3-clause |
bilgili/nest-simulator | extras/ConnPlotter/examples/connplotter_tutorial.py | 13 | 26833 | # -*- coding: utf-8 -*-
#
# connplotter_tutorial.py
#
# This file is part of NEST.
#
# Copyright (C) 2004 The NEST Initiative
#
# NEST 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 2 of the Li... | gpl-2.0 |
xubenben/scikit-learn | examples/linear_model/plot_logistic.py | 312 | 1426 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Logit function
=========================================================
Show in the plot is how the logistic regression would, in this
synthetic dataset, classify values as either 0 or 1,
i.e. class one or two, u... | bsd-3-clause |
dialounke/pylayers | pylayers/location/geometric/util/cdf2.py | 2 | 3799 | # -*- coding:Utf-8 -*-
import numpy as np
import scipy as sp
import os
import matplotlib.pyplot as plt
import pdb
try:
import mplrc.ieee.transaction
except:
pass
from matplotlib import rcParams
rcParams['text.usetex'] = True
rcParams['text.latex.unicode'] = True
class CDF(object):
def __init__(self, ld, ... | mit |
yanlend/scikit-learn | sklearn/metrics/tests/test_pairwise.py | 13 | 25520 | import numpy as np
from numpy import linalg
from scipy.sparse import dok_matrix, csr_matrix, issparse
from scipy.spatial.distance import cosine, cityblock, minkowski, wminkowski
from sklearn.utils.testing import assert_greater
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing impo... | bsd-3-clause |
hobson/pug-invest | pug/invest/bin/thresh-test.py | 1 | 2097 | from pug.invest.util import clipped_area
# from scipy.optimize import minimize
import pandas as pd
from matplotlib import pyplot as plt
np = pd.np
t = ['2014-12-09T00:00', '2014-12-09T00:15', '2014-12-09T00:30', '2014-12-09T00:45', '2014-12-09T01:00', '2014-12-09T01:15', '2014-12-09T01:30', '2014-12-09T01:45']
ts = p... | mit |
xiaozhuchacha/OpenBottle | grammar_induction/earley_parser/nltk/tbl/demo.py | 7 | 14715 | # -*- coding: utf-8 -*-
# Natural Language Toolkit: Transformation-based learning
#
# Copyright (C) 2001-2017 NLTK Project
# Author: Marcus Uneson <marcus.uneson@gmail.com>
# based on previous (nltk2) version by
# Christopher Maloof, Edward Loper, Steven Bird
# URL: <http://nltk.org/>
# For license information, see... | mit |
bthirion/scikit-learn | examples/classification/plot_classifier_comparison.py | 26 | 5236 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=====================
Classifier comparison
=====================
A comparison of a several classifiers in scikit-learn on synthetic datasets.
The point of this example is to illustrate the nature of decision boundaries
of different classifiers.
This should be taken with ... | bsd-3-clause |
bnaul/scikit-learn | examples/linear_model/plot_lasso_model_selection.py | 15 | 5402 | """
===================================================
Lasso model selection: Cross-Validation / AIC / BIC
===================================================
Use the Akaike information criterion (AIC), the Bayes Information
criterion (BIC) and cross-validation to select an optimal value
of the regularization paramet... | bsd-3-clause |
shivamvats/graphSearch | main_mha.py | 1 | 2271 | from heuristicSearch.planners.mhastar import MHAstar
from heuristicSearch.envs.env import GridEnvironment
from heuristicSearch.envs.occupancy_grid import OccupancyGrid
from heuristicSearch.graph.node import Node
from heuristicSearch.utils.visualizer import ImageVisualizer
from heuristicSearch.utils.utils import *
from... | mit |
alfonsokim/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/path.py | 69 | 20263 | """
Contains a class for managing paths (polylines).
"""
import math
from weakref import WeakValueDictionary
import numpy as np
from numpy import ma
from matplotlib._path import point_in_path, get_path_extents, \
point_in_path_collection, get_path_collection_extents, \
path_in_path, path_intersects_path, con... | agpl-3.0 |
kipohl/ncanda-data-integration | scripts/redcap/scoring/pgd/__init__.py | 2 | 2426 | #!/usr/bin/env python
##
## See COPYING file distributed along with the ncanda-data-integration package
## for the copyright and license terms
##
import pandas
import RwrapperNew
#
# Variables from surveys needed for PGD
#
# LimeSurvey field names
lime_fields = [ "PGD_sec1 [pgd1]", "PGD_sec1 [pgd2]", "PGD_sec1 ... | bsd-3-clause |
chrisburr/scikit-learn | examples/linear_model/plot_ard.py | 18 | 2827 | """
==================================================
Automatic Relevance Determination Regression (ARD)
==================================================
Fit regression model with Bayesian Ridge Regression.
See :ref:`bayesian_ridge_regression` for more information on the regressor.
Compared to the OLS (ordinary l... | bsd-3-clause |
CVML/scikit-learn | benchmarks/bench_glmnet.py | 297 | 3848 | """
To run this, you'll need to have installed.
* glmnet-python
* scikit-learn (of course)
Does two benchmarks
First, we fix a training set and increase the number of
samples. Then we plot the computation time as function of
the number of samples.
In the second benchmark, we increase the number of dimensions of... | bsd-3-clause |
ai-se/XTREE | src/Planners/XTREE/Prediction.py | 1 | 8693 | from __future__ import division
from pdb import set_trace
from os import environ, getcwd
from os import walk
from os.path import expanduser
from pdb import set_trace
import sys
# Update PYTHONPATH
HOME = expanduser('~')
axe = HOME + '/git/axe/axe/' # AXE
pystat = HOME + '/git/pystats/' # PySTAT
cwd = getcwd() # Cur... | mit |
jviada/QuantEcon.py | examples/lqramsey.py | 4 | 9949 | """
Filename: lqramsey.py
Authors: Thomas Sargent, Doc-Jin Jang, Jeong-hun Choi, John Stachurski
This module provides code to compute Ramsey equilibria in a LQ economy with
distortionary taxation. The program computes allocations (consumption,
leisure), tax rates, revenues, the net present value of the debt and other... | bsd-3-clause |
EachenKuang/PythonRepository | MedicineSCI/document_word.py | 1 | 3290 | # -*- encoding: utf-8 -*-
import numpy as np
import pandas as pd
def generate_documents_words_matrix():
f1 = open('TF.txt', 'r') # Documents
f2 = open('termList.txt', 'r') # Words
# 词表
words_list = []
for line in f2.readlines():
words_list.append(line.strip())
documents_words_ma... | apache-2.0 |
fabioticconi/scikit-learn | examples/decomposition/plot_kernel_pca.py | 353 | 2011 | """
==========
Kernel PCA
==========
This example shows that Kernel PCA is able to find a projection of the data
that makes data linearly separable.
"""
print(__doc__)
# Authors: Mathieu Blondel
# Andreas Mueller
# License: BSD 3 clause
import numpy as np
import matplotlib.pyplot as plt
from sklearn.decomp... | bsd-3-clause |
dimroc/tensorflow-mnist-tutorial | lib/python3.6/site-packages/matplotlib/streamplot.py | 10 | 20629 | """
Streamline plotting for 2D vector fields.
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from six.moves import xrange
import numpy as np
import matplotlib
import matplotlib.cm as cm
import matplotlib.colors as mcolors
import matplotlib.... | apache-2.0 |
jakobworldpeace/scikit-learn | examples/model_selection/plot_underfitting_overfitting.py | 41 | 2672 | """
============================
Underfitting vs. Overfitting
============================
This example demonstrates the problems of underfitting and overfitting and
how we can use linear regression with polynomial features to approximate
nonlinear functions. The plot shows the function that we want to approximate,
wh... | bsd-3-clause |
kevin-coder/tensorflow-fork | tensorflow/contrib/learn/python/learn/estimators/kmeans_test.py | 39 | 20233 | # Copyright 2016 The TensorFlow 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 applica... | apache-2.0 |
samzhang111/scikit-learn | sklearn/feature_extraction/dict_vectorizer.py | 234 | 12267 | # Authors: Lars Buitinck
# Dan Blanchard <dblanchard@ets.org>
# License: BSD 3 clause
from array import array
from collections import Mapping
from operator import itemgetter
import numpy as np
import scipy.sparse as sp
from ..base import BaseEstimator, TransformerMixin
from ..externals import six
from ..ext... | bsd-3-clause |
thekerrlab/netpyne | netpyne/analysis/lfp.py | 1 | 16820 | """
analysis/lfp.py
Functions to plot and analyze LFP-related results
Contributors: salvadordura@gmail.com
"""
from __future__ import print_function
from __future__ import division
from __future__ import unicode_literals
from __future__ import absolute_import
from builtins import range
from builtins import round
fro... | mit |
peraktong/Cannon-Experiment | 0228_opt_simultaneously_1_data.py | 1 | 4384 | import os
import numpy as np
from astropy.table import Table
from astropy.io import fits
import matplotlib.pyplot as plt
import matplotlib
import pickle
import astropy.io.fits as ts
import AnniesLasso_2 as tc
import math
def get_pixmask(flux, err):
bad_flux = ~np.isfinite(flux)
bad_err = (~np.isfinite(err))... | mit |
shikhardb/scikit-learn | sklearn/linear_model/coordinate_descent.py | 13 | 73434 | # Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Fabian Pedregosa <fabian.pedregosa@inria.fr>
# Olivier Grisel <olivier.grisel@ensta.org>
# Gael Varoquaux <gael.varoquaux@inria.fr>
#
# License: BSD 3 clause
import sys
import warnings
from abc import ABCMeta, abstractmethod
import n... | bsd-3-clause |
gbcolborne/TALN_2016 | exp_AD.py | 1 | 5248 | #! -*- coding:utf-8 -*-
""" Evaluate count-based distributional semantic models. """
import sys, os, codecs, argparse
from sklearn.metrics.pairwise import pairwise_distances
import Corpus, CoocTensor, eval_utils
def join_strings_and_append_to_file(strings, filename):
"""
Join strings in list using comma as de... | mit |
lbeltrame/bcbio-nextgen | bcbio/heterogeneity/loh.py | 2 | 15786 | """Summarize amplification and loss of heterozygosity (LOH) from heterogeneity callers.
Provides high level summaries of calls in regions of interest.
"""
import csv
import collections
import os
import decimal
import uuid
import pandas as pd
import six
from six import StringIO
import toolz as tz
import yaml
from bcb... | mit |
vivekmishra1991/scikit-learn | examples/cluster/plot_affinity_propagation.py | 349 | 2304 | """
=================================================
Demo of affinity propagation clustering algorithm
=================================================
Reference:
Brendan J. Frey and Delbert Dueck, "Clustering by Passing Messages
Between Data Points", Science Feb. 2007
"""
print(__doc__)
from sklearn.cluster impor... | bsd-3-clause |
ProkopHapala/SimpleSimulationEngine | cpp/sketches_SDL/Molecular/python/eFF_terms.py | 1 | 12181 | #!/usr/bin/python
import numpy as np
import matplotlib.pyplot as plt
import scipy.special as spc
'''
Note: It seems that H2 Molecule cannot be sable without varying Kinetic Energy
see:
[1] https://link.aps.org/doi/10.1103/PhysRevLett.99.185003
Excited Electron Dynamics Modeling of Warm Dense Matter
Julius T. Su... | mit |
imperial-genomics-facility/data-management-python | igf_data/process/metadata_reformat/reformat_samplesheet_file.py | 1 | 8902 | import re
import pandas as pd
from igf_data.illumina.samplesheet import SampleSheet
from igf_data.utils.sequtils import rev_comp
from igf_data.process.metadata_reformat.reformat_metadata_file import Reformat_metadata_file
SAMPLESHEET_COLUMNS = [
'Lane',
'Sample_ID',
'Sample_Name',
'Sample_Plate',
'Sample_Wel... | apache-2.0 |
stwunsch/gnuradio | gr-filter/examples/resampler.py | 58 | 4454 | #!/usr/bin/env python
#
# Copyright 2009,2012,2013 Free Software Foundation, Inc.
#
# This file is part of GNU Radio
#
# GNU Radio 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, or (at your ... | gpl-3.0 |
liberatorqjw/scikit-learn | examples/svm/plot_svm_nonlinear.py | 61 | 1089 | """
==============
Non-linear SVM
==============
Perform binary classification using non-linear SVC
with RBF kernel. The target to predict is a XOR of the
inputs.
The color map illustrates the decision function learn by the SVC.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from sklearn impor... | bsd-3-clause |
jreback/pandas | pandas/compat/pickle_compat.py | 1 | 7903 | """
Support pre-0.12 series pickle compatibility.
"""
import contextlib
import copy
import io
import pickle as pkl
from typing import TYPE_CHECKING, Optional
import warnings
from pandas._libs.tslibs import BaseOffset
from pandas import Index
if TYPE_CHECKING:
from pandas import DataFrame, Series
def load_redu... | bsd-3-clause |
yorkerlin/shogun | examples/undocumented/python_modular/graphical/interactive_clustering_demo.py | 10 | 11280 | """
Shogun demo, based on PyQT Demo by Eli Bendersky
Christian Widmer
Soeren Sonnenburg
License: GPLv3
"""
import numpy
import sys, os, csv
from PyQt4.QtCore import *
from PyQt4.QtGui import *
import matplotlib
from matplotlib.colorbar import make_axes, Colorbar
from matplotlib.backends.backend_qt4agg import FigureCa... | gpl-3.0 |
barentsen/dave | detrendThis/martinsff.py | 1 | 8302 | import sys, os
import scipy
from pylab import *
from matplotlib import *
from scipy.stats import *
from numpy import *
from scipy import *
import kepfit
import kepmsg
"""
This code is based on the PyKE routine kepsff
found at keplerscience.arc.nasa.gov
The kepsff code is based on Vanderberg and Johnson 2014.
If you ... | mit |
beepee14/scikit-learn | sklearn/manifold/isomap.py | 229 | 7169 | """Isomap for manifold learning"""
# Author: Jake Vanderplas -- <vanderplas@astro.washington.edu>
# License: BSD 3 clause (C) 2011
import numpy as np
from ..base import BaseEstimator, TransformerMixin
from ..neighbors import NearestNeighbors, kneighbors_graph
from ..utils import check_array
from ..utils.graph import... | bsd-3-clause |
jakevdp/megaman | megaman/utils/covar_plotter.py | 4 | 2672 | # LICENSE: Simplified BSD https://github.com/mmp2/megaman/blob/master/LICENSE
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Ellipse
def plot_point_cov(points, nstd=2, ax=None, **kwargs):
"""
Plots an `nstd` sigma ellipse based on the mean and covariance of a point
"clo... | bsd-2-clause |
stevenzhang18/Indeed-Flask | lib/pandas/core/nanops.py | 9 | 23144 | import itertools
import functools
import numpy as np
try:
import bottleneck as bn
_USE_BOTTLENECK = True
except ImportError: # pragma: no cover
_USE_BOTTLENECK = False
import pandas.hashtable as _hash
from pandas import compat, lib, algos, tslib
from pandas.compat import builtins
from pandas.core.common ... | apache-2.0 |
zrhans/pythonanywhere | .virtualenvs/django19/lib/python3.4/site-packages/matplotlib/tests/test_basic.py | 7 | 1290 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
from matplotlib.externals import six
from nose.tools import assert_equal
from matplotlib.testing.decorators import knownfailureif
from pylab import *
def test_simple():
assert_equal(1 + 1, 2)
@knownfa... | apache-2.0 |
OshynSong/scikit-learn | sklearn/tests/test_kernel_ridge.py | 342 | 3027 | import numpy as np
import scipy.sparse as sp
from sklearn.datasets import make_regression
from sklearn.linear_model import Ridge
from sklearn.kernel_ridge import KernelRidge
from sklearn.metrics.pairwise import pairwise_kernels
from sklearn.utils.testing import ignore_warnings
from sklearn.utils.testing import assert... | bsd-3-clause |
pratapvardhan/pandas | pandas/io/formats/printing.py | 6 | 13133 | """
printing tools
"""
import sys
from pandas.core.dtypes.inference import is_sequence
from pandas import compat
from pandas.compat import u
from pandas.core.config import get_option
def adjoin(space, *lists, **kwargs):
"""
Glues together two sets of strings using the amount of space requested.
The idea ... | bsd-3-clause |
chaluemwut/fbserver | venv/lib/python2.7/site-packages/sklearn/feature_selection/rfe.py | 1 | 14237 | # Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Vincent Michel <vincent.michel@inria.fr>
# Gilles Louppe <g.louppe@gmail.com>
#
# License: BSD 3 clause
"""Recursive feature elimination for feature ranking"""
import numpy as np
from ..utils import check_arrays, safe_sqr
from ..base impo... | apache-2.0 |
lihongchun2007/SeeNN | heatmap/class_hot.py | 1 | 4056 | #!/usr/bin/env python2
import os
import sys
import pickle
import argparse
import tensorflow as tf
import numpy as np
from scipy.misc import imread, imresize
from matplotlib import pyplot as plt
def download_vgg16():
from six.moves import urllib
model_files = ['https://www.cs.toronto.edu/~frossard/vgg16/vgg16... | gpl-3.0 |
andrewfullard/python-meet | exercise8.py | 1 | 2207 | # -*- coding: utf-8 -*-
"""
Created on Wed Nov 20 09:10:22 2013
@author: c0918140
"""
import numpy as np
import matplotlib.pyplot as plt
import scipy.interpolate as interpolate
def f(x):
y = -np.exp(x)*(-2. + 2.*x + 5.*x**2. + x**3.)
return y
def R(r):
y = -r**2./(1 + r**6)
return y... | mit |
rubydatasystems/seniority_list | seniority_list/interactive_plotting.py | 1 | 9185 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
'''
.. module:: interactive_plotting
:synopsis: The bokeh module contains interactive plotting functions.
.. moduleauthor:: Bob Davison <rubydatasystems@fastmail.net>
'''
from bokeh.plotting import figure, ColumnDataSource
# from bokeh.models import (HoverTool, Box... | gpl-3.0 |
piersy/theano-machine-learning | 2_logistic_regression.py | 1 | 1696 | import matplotlib.pyplot as plt
import theano
from theano import tensor as T
import numpy as np
from load import mnist
def floatX(X):
return np.asarray(X, dtype=theano.config.floatX)
def init_weights(shape):
return theano.shared(floatX(np.random.randn(*shape) * 0.01))
def model(X, w):
return T.nnet.softm... | mit |
manterd/myPhyloDB | functions/analysis/pca_graphs.py | 1 | 28862 | import datetime
from django.http import HttpResponse
import logging
import numpy as np
import pandas as pd
from pyper import *
import json
import functions
LOG_FILENAME = 'error_log.txt'
pd.set_option('display.max_colwidth', -1)
def getPCA(request, stops, RID, PID):
try:
while True:
if requ... | gpl-3.0 |
tdgoodrich/mase | python101/code/zipf.py | 14 | 1453 | """This module contains code from
Think Python by Allen B. Downey
http://thinkpython.com
Copyright 2012 Allen B. Downey
License: GNU GPLv3 http://www.gnu.org/licenses/gpl.html
"""
import sys
import string
import matplotlib.pyplot as pyplot
from analyze_book import *
def rank_freq(hist):
"""Returns a list of ... | unlicense |
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