repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
value |
|---|---|---|---|---|---|---|
GalaxyDataset | GalaxyDataset-master/evaluationMetrics.py | 0 | 0 | 0 | py | |
GalaxyDataset | GalaxyDataset-master/preprocess.py | # -*- coding: utf-8 -*-
import torch
import torch.utils.data as Data
import numpy as np
from torchvision import datasets, transforms
import argparse
import os
import random
import yaml
import downloadData
def load_npy(path):
# npy file: [[imgs, label], [imgs, label]...., [imgs, label]]
# when allow_pickle=True... | 1,436 | 29.574468 | 107 | py |
GalaxyDataset | GalaxyDataset-master/digitfive/custom.py |
from PIL import Image, ImageEnhance, ImageOps, ImageFilter
import numpy as np
import random
class GaussianBlur(object):
def __init__(self, sigma=None):
if sigma is None:
sigma = [.1, 2.]
self.sigma = sigma
def __call__(self, x):
sigma = random.uniform(self.sigma[0], sel... | 6,520 | 48.030075 | 138 | py |
GalaxyDataset | GalaxyDataset-master/digitfive/femnist.py | from torchvision.datasets import MNIST, utils
from PIL import Image
import os.path
import torch
class FEMNIST(MNIST):
"""
This dataset is derived from the Leaf repository
(https://github.com/TalwalkarLab/leaf) pre-processing of the Extended MNIST
dataset, grouping examples by writer. Details about Lea... | 3,128 | 36.25 | 110 | py |
GalaxyDataset | GalaxyDataset-master/digitfive/usps.py | import scipy.io as scio
import numpy as np
from PIL import Image
import os
import os.path
import torch
import torchvision
from torchvision import datasets, transforms
from torchvision.datasets import MNIST, utils
from torch.utils.data import DataLoader, Dataset
# dataFile = 'usps_28x28.mat'
# data = scio.loadmat(dataF... | 5,890 | 30.502674 | 215 | py |
GalaxyDataset | GalaxyDataset-master/digitfive/svhn.py | import scipy.io as scio
import numpy as np
from PIL import Image
import os
import os.path
import torch
import torchvision
from torchvision import datasets, transforms
from torchvision.datasets import MNIST, utils
from torch.utils.data import DataLoader, Dataset
# dataFile = 'svhn_train_32x32.mat'
# data = scio.loadmat... | 5,699 | 29.15873 | 215 | py |
GalaxyDataset | GalaxyDataset-master/digitfive/syn.py | import scipy.io as scio
import numpy as np
from PIL import Image
import os
import os.path
import torch
import torchvision
from torchvision import datasets, transforms
from torchvision.datasets import MNIST, utils
from torch.utils.data import DataLoader, Dataset
# dataFile = 'syn_number.mat'
# data = scio.loadmat(dataF... | 5,471 | 30.630058 | 215 | py |
GalaxyDataset | GalaxyDataset-master/digitfive/mnistm.py | import scipy.io as scio
import numpy as np
from PIL import Image
import os
import os.path
import torch
import torchvision
from torchvision import datasets, transforms
from torchvision.datasets import MNIST, utils
from torch.utils.data import DataLoader, Dataset
# dataFile = 'mnistm_with_label.mat'
# data = scio.loadma... | 5,512 | 29.97191 | 215 | py |
GalaxyDataset | GalaxyDataset-master/digitfive/SubPolicy.py | class SubPolicy(object):
def __init__(self, p1, operation1, magnitude_idx1, p2, operation2, magnitude_idx2, fillcolor=(128, 128, 128)):
ranges = {
"shearX": np.linspace(0, 0.3, 10),
"shearY": np.linspace(0, 0.3, 10),
"translateX": np.linspace(0, 150 / 331, 10),
... | 2,048 | 54.378378 | 138 | py |
GalaxyDataset | GalaxyDataset-master/digitfive/mnist.py | import scipy.io as scio
import numpy as np
from PIL import Image
import os
import os.path
import torch
import torchvision
from torchvision import datasets, transforms
from torchvision.datasets import MNIST, utils
from torch.utils.data import DataLoader, Dataset
# dataFile = 'mnist_data.mat'
# data = scio.loadmat(data... | 5,753 | 30.966667 | 215 | py |
skimulator | skimulator-master/setup.py | """
Copyright (C) 2017-2021 OceanDataLab
This file is part of skimulator.
skimulator 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.
skimul... | 4,810 | 36.007692 | 79 | py |
skimulator | skimulator-master/test/projskim.py | import os
import numpy
import healpy as heal
from numpy import linalg as LA
from netCDF4 import Dataset
import params as p
import skimulator.const as const
import skimulator.rw_data as rw
import matplotlib.pyplot as plt
theta1 = const.theta1
theta0 = const.theta0
gamma0 = const.gamma0
# - In parameter file ## TODO -... | 8,525 | 32.046512 | 108 | py |
skimulator | skimulator-master/test/params2.py | # -----------------------#
# Files and directories
# -----------------------#
## -- Get the user home directory
from os.path import expanduser
import os
import math
home = expanduser("~") + '/src/'
# ------ Directory that contains orbit file:
dir_setup = os.path.join(home, 'skimulator', 'data')
# ------ Directory that ... | 5,776 | 37.771812 | 79 | py |
skimulator | skimulator-master/test/mod_diag.py | import numpy
import netCDF4
import os
import sys
import glob
import pickle
import matplotlib
matplotlib.use('Agg')
from matplotlib import pyplot
import cartopy
import skimulator.rw_data as rw
# Initialize color
listcolor = ['c', 'y', 'b', 'g', 'k', 'r', 'c', 'y']
projection = cartopy.crs.PlateCarree()
transform = car... | 19,253 | 38.374233 | 94 | py |
skimulator | skimulator-master/test/mod_plot.py | import numpy
import netCDF4
import os
import sys
import glob
import matplotlib
matplotlib.use('Agg')
from matplotlib import pyplot
import cartopy
import skimulator.rw_data as rw
# Initialize color
listcolor = ['c', 'y', 'b', 'g', 'k', 'r', 'c', 'y']
projection = cartopy.crs.PlateCarree()
transform = cartopy.crs.Plate... | 6,884 | 35.428571 | 80 | py |
skimulator | skimulator-master/test/plot_grid.py | import mod_plot
import params as p
import numpy
import glob
import os
# Initialize variables
indatadir = p.outdatadir
config = p.config
modelbox = p.modelbox
#modelbox = [-5, 5, 75, 85]
#modelbox = [-65, 55, 40, 45]
modelbox[0] = numpy.mod(modelbox[0] + 180.0, 360.0) - 180.0
modelbox[1] = numpy.mod(modelbox[1] + 180.... | 828 | 26.633333 | 64 | py |
skimulator | skimulator-master/test/diag_l2b.py | import numpy
import mod_diag
import glob
import os
import matplotlib
import json
import sys
if len(sys.argv) < 1:
print('Provide json file for diagnostics')
sys.exit(1)
file_param = sys.argv[1]
with open(file_param, 'r') as f:
params = json.load(f)
modelbox = params['l2b']['modelbox']
config = params['l2b... | 1,499 | 32.333333 | 83 | py |
skimulator | skimulator-master/test/diags_l2d.py | import numpy
from matplotlib import pyplot
import netCDF4
import glob
import os
import scipy.signal
from scipy.fftpack import fft
def cpsd1d(hh1=None, hh2=None, dx=1.,tap=0.05, detrend=True):
hh1 = hh1 - numpy.mean(hh1)
hh2 = hh2 - numpy.mean(hh2)
nx = numpy.shape(hh1)[0]
if detrend:
hh1 =... | 10,114 | 38.666667 | 90 | py |
skimulator | skimulator-master/test/diags_l2c.py | import numpy
from matplotlib import pyplot
import netCDF4
import glob
import os
import sys
import json
import scipy.signal
from scipy.fftpack import fft
def cpsd1d(hh1=None, hh2=None, dx=1.,tap=0.05, detrend=True):
hh1 = hh1 - numpy.mean(hh1)
hh2 = hh2 - numpy.mean(hh2)
nx = numpy.shape(hh1)[0]
if... | 23,170 | 41.282847 | 101 | py |
skimulator | skimulator-master/example/params_example_8beams.py | # -----------------------#
# Files and directories
# -----------------------#
## -- Get the user home directory
from os.path import expanduser
import os
import math
home = expanduser("~")
# ------ Name of the configuration (to build output files names)
# 8 beams, 45 azimuths, 1024 pulses and cycle length of 37 ms
con... | 7,726 | 36.692683 | 80 | py |
skimulator | skimulator-master/example/params_example_6beams.py | # -----------------------#
# Files and directories
# -----------------------#
## -- Get the user home directory
from os.path import expanduser
import os
import math
home = expanduser("~")
# ------ Name of the configuration (to build output files names)
#config="WW3_EQ_metop_2018_6a"
# 6 beams, 60 azimuths, 512 pulses... | 8,115 | 36.229358 | 80 | py |
skimulator | skimulator-master/example/params_example_8beams_ogcm.py | # -----------------------#
# Files and directories
# -----------------------#
## -- Get the user home directory
from os.path import expanduser
import os
import math
home = expanduser("~")
# ------ Name of the configuration (to build output files names)
# 8 beams, 45 azimuths, 1024 pulses and cycle length of 37 ms
conf... | 7,411 | 35.875622 | 80 | py |
skimulator | skimulator-master/example/params_stream.py | # -----------------------#
# Files and directories
# -----------------------#
## -- Get the user home directory
from os.path import expanduser
import os
import math
home = expanduser("~") + '/src/'
# ------ Name of the configuration (to build output files names)
# 8 beams, 45 azimuths, 1024 pulses and cycle length of... | 7,742 | 37.142857 | 80 | py |
skimulator | skimulator-master/skimulator/const.py | """
Copyright (C) 2017-2021 OceanDataLab
This file is part of skimulator.
skimulator 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.
skimul... | 1,840 | 29.683333 | 75 | py |
skimulator | skimulator-master/skimulator/mod_parallel.py | """
Copyright (C) 2017-2021 OceanDataLab
This file is part of skimulator.
skimulator 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.
skimul... | 7,515 | 31.257511 | 79 | py |
skimulator | skimulator-master/skimulator/fitspline2d.py | """
Copyright (C) 2017-2021 OceanDataLab
This file is part of skimulator.
skimulator 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.
skimul... | 6,754 | 37.6 | 106 | py |
skimulator | skimulator-master/skimulator/build_swath.py | """
Copyright (C) 2017-2021 OceanDataLab
This file is part of skimulator.
skimulator 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.
skimul... | 21,162 | 42.455852 | 83 | py |
skimulator | skimulator-master/skimulator/run_simulator.py | '''Main program:
Usage: run_simulator(file_param) \n
If no param file is specified, the default one is exemple/params_exemple.txt \n
In the first part of the program, model coordinates are read and the
SKIM swath is computing accordingly. \n
The SKIM grid parameters are saved in netcdf files, if you don't want to
reco... | 15,674 | 39.29563 | 79 | py |
skimulator | skimulator-master/skimulator/cli.py | """
Copyright (C) 2017-2021 OceanDataLab
This file is part of skimulator.
skimulator 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.
skimul... | 5,891 | 31.196721 | 77 | py |
skimulator | skimulator-master/skimulator/regridding_l2d.py | """
Copyright (C) 2017-2021 OceanDataLab
This file is part of skimulator.
skimulator 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.
skimul... | 29,349 | 38.715832 | 87 | py |
skimulator | skimulator-master/skimulator/regridding.py | """
Copyright (C) 2017-2021 OceanDataLab
This file is part of skimulator.
skimulator 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.
skimul... | 26,773 | 41.633758 | 109 | py |
skimulator | skimulator-master/skimulator/mod_run.py | '''Module to create one beam data:
\n
\n
Copyright (C) 2017-2021 OceanDataLab
This file is part of skimulator.
skimulator 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 ... | 20,831 | 43.8 | 79 | py |
skimulator | skimulator-master/skimulator/grid_check.py | """
Copyright (C) 2017-2021 OceanDataLab
This file is part of skimulator.
skimulator 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.
skimul... | 7,140 | 30.879464 | 116 | py |
skimulator | skimulator-master/skimulator/__init__.py | # =======================================================================
# General Documentation
"""Utilities for SKIM Science Simulator for the ocean
Some useful online help commands for the package:
* help(skimulator): Help for the package. A list of all modules in
this package ... | 3,814 | 31.887931 | 78 | py |
skimulator | skimulator-master/skimulator/spline.py | """
Copyright (C) 2017-2021 OceanDataLab
This file is part of skimulator.
skimulator 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.
skimul... | 6,038 | 25.603524 | 74 | py |
skimulator | skimulator-master/skimulator/rw_data.py | """
Copyright (C) 2017-2021 OceanDataLab
This file is part of skimulator.
skimulator 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.
skimul... | 48,046 | 42.246625 | 83 | py |
skimulator | skimulator-master/skimulator/mod_tools.py | """
Copyright (C) 2017-2021 OceanDataLab
This file is part of skimulator.
skimulator 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.
skimul... | 11,664 | 36.149682 | 134 | py |
skimulator | skimulator-master/skimulator/error/wet_troposphere.py | # Copyright (c) 2020 CNES/JPL
#
# All rights reserved. Use of this source code is governed by a
# BSD-style license that can be found in the LICENSE file.
"""
Copyright (C) 2017-2021 OceanDataLab
This file is part of skimulator.
skimulator is free software: you can redistribute it and/or modify
it under the terms of t... | 12,414 | 41.958478 | 79 | py |
skimulator | skimulator-master/skimulator/error/rain.py | """
Copyright (C) 2017-2021 OceanDataLab
This file is part of skimulator.
skimulator 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.
skimul... | 4,964 | 38.094488 | 79 | py |
skimulator | skimulator-master/skimulator/error/instrument.py | """
Copyright (C) 2017-2021 OceanDataLab
This file is part of skimulator.
skimulator 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.
skimul... | 6,800 | 39.96988 | 79 | py |
skimulator | skimulator-master/skimulator/error/dsigma.py | """
Copyright (C) 2017-2021 OceanDataLab
This file is part of skimulator.
skimulator 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.
skimul... | 4,605 | 36.754098 | 80 | py |
skimulator | skimulator-master/skimulator/error/utils.py | # Copyright (c) 2020 CNES/JPL
#
# All rights reserved. Use of this source code is governed by a
# BSD-style license that can be found in the LICENSE file.
"""
Copyright (C) 2017-2021 OceanDataLab
This file is part of skimulator.
skimulator is free software: you can redistribute it and/or modify
it under the terms of t... | 7,169 | 34.147059 | 76 | py |
skimulator | skimulator-master/skimulator/error/altimeter.py | # Copyright (c) 2020 CNES/JPL
#
# All rights reserved. Use of this source code is governed by a
# BSD-style license that can be found in the LICENSE file.
"""
Copyright (C) 2017-2021 OceanDataLab
This file is part of skimulator.
skimulator is free software: you can redistribute it and/or modify
it under the terms of t... | 2,323 | 33.686567 | 79 | py |
skimulator | skimulator-master/skimulator/error/simulate_spectrum.py | """
Copyright (C) 2017-2021 OceanDataLab
This file is part of skimulator.
skimulator 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.
skimul... | 13,999 | 43.444444 | 105 | py |
skimulator | skimulator-master/skimulator/error/wave_doppler.py | """
Copyright (C) 2017-2021 OceanDataLab
This file is part of skimulator.
skimulator 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.
skimul... | 10,280 | 38.694981 | 79 | py |
skimulator | skimulator-master/skimulator/error/__init__.py | """
Copyright (C) 2017-2021 OceanDataLab
This file is part of skimulator.
skimulator 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.
skimul... | 917 | 35.72 | 68 | py |
skimulator | skimulator-master/skimulator/error/attitude.py | """
Copyright (C) 2017-2021 OceanDataLab
This file is part of skiMulator.
skimulator 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.
skimul... | 6,582 | 38.419162 | 80 | py |
skimulator | skimulator-master/skimulator/error/generator.py | # Copyright (c) 2020 CNES/JPL
#
# All rights reserved. Use of this source code is governed by a
# BSD-style license that can be found in the LICENSE file.
"""
Copyright (C) 2017-2021 OceanDataLab
This file is part of skimulator.
skimulator is free software: you can redistribute it and/or modify
it under the terms of t... | 9,631 | 42.981735 | 80 | py |
skimulator | skimulator-master/doc/source/conf.py | # -*- coding: utf-8 -*-
#
# S4 documentation build configuration file, created by
# sphinx-quickstart on Thu Jul 10 16:54:19 2014.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All co... | 10,718 | 30.342105 | 80 | py |
skimulator | skimulator-master/doc/source/params.py | # -----------------------#
# Files and directories
# -----------------------#
## -- Get the user home directory
from os.path import expanduser
import os
import math
home = expanduser("~")
# ------ Name of the configuration (to build output files names)
config = [yourconfig]
# ------ Directory that contains orbit file... | 7,779 | 38.492386 | 89 | py |
skimulator | skimulator-master/doc/images/code_image/Fig4.py | '''
FIG. 4: Radial currents and instrumental noise.
'''
import netCDF4
import numpy
import matplotlib
matplotlib.use('Agg')
from matplotlib import pyplot
import skimulator.rw_data as rw
import glob
import cartopy
import os
# Initialize color
listcolor = ['c', 'y', 'b', 'g', 'k', 'r', 'c', 'y']
# List files
indata... | 2,193 | 30.797101 | 74 | py |
skimulator | skimulator-master/doc/images/code_image/Fig6.py | '''
FIG. 4: Radial currents and instrumental noise.
'''
import netCDF4
import numpy
import matplotlib
matplotlib.use('Agg')
from matplotlib import pyplot
import skimulator.rw_data as rw
import glob
import cartopy
import os
# Initialize color
listcolor = ['c', 'y', 'b', 'g', 'k', 'r', 'c', 'y']
# List files
indata... | 2,216 | 31.130435 | 74 | py |
skimulator | skimulator-master/doc/images/code_image/Fig2.py | '''
FIG. 2: scheme of the SKIM geometry with 4 beams at 12 degrees and 1 beam at 6 degree and 5 beams at 12 degrees and 2 beams at 6 degree.
'''
import netCDF4
import numpy
import matplotlib
matplotlib.use('Agg')
from matplotlib import pyplot
import skimulator.rw_data as rw
import glob
import cartopy
import os
# I... | 3,290 | 35.164835 | 139 | py |
skimulator | skimulator-master/doc/images/code_image/Fig3.py | '''
FIG. 3: Model interpolated currents and the corresponding radial currents.
'''
import netCDF4
import numpy
import matplotlib
matplotlib.use('Agg')
from matplotlib import pyplot
import skimulator.rw_data as rw
import glob
import cartopy
import os
# Initialize color
listcolor = ['c', 'y', 'b', 'g', 'k', 'r', 'c'... | 3,784 | 32.794643 | 78 | py |
skimulator | skimulator-master/doc/images/code_image/Fig1.py | '''
FIG. 1: 5-day worth of SKIM simulated data in a global configuration with the science orbit.
'''
import netCDF4
import numpy
import matplotlib
matplotlib.use('Agg')
from matplotlib import pyplot
import skimulator.rw_data as rw
import glob
import cartopy
import os
# List files
outdatadir = '/tmp/key'
outdatadir = ... | 1,647 | 31.96 | 92 | py |
skimulator | skimulator-master/doc/images/code_image/Fig5.py | '''
FIG. 4: Radial currents and instrumental noise.
'''
import netCDF4
import numpy
import matplotlib
matplotlib.use('Agg')
from matplotlib import pyplot
import skimulator.rw_data as rw
import glob
import cartopy
import os
# Initialize color
listcolor = ['c', 'y', 'b', 'g', 'k', 'r', 'c', 'y']
# List files
indata... | 2,199 | 30.884058 | 74 | py |
CompositionSpaceNFDI | CompositionSpaceNFDI-main/setup.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
compositionspace : add licence and such
"""
from setuptools import setup, find_packages, Extension
with open('README.md') as readme_file:
readme = readme_file.read()
setup_requirements = ['pytest-runner', ]
test_requirements = ['pytest>=3', ]
setup(
author=... | 1,643 | 29.444444 | 80 | py |
CompositionSpaceNFDI | CompositionSpaceNFDI-main/compositionspace/datautils.py |
import pandas as pd
import re
import os
import yaml
from tqdm.notebook import tqdm
import matplotlib.pyplot as plt
import numpy as np
import pickle
import time
import h5py
import warnings
import compositionspace.paraprobe_transcoder as paraprobe_transcoder
#really check this!
pd.options.mode.chained_assignment = None... | 19,133 | 34.108257 | 151 | py |
CompositionSpaceNFDI | CompositionSpaceNFDI-main/compositionspace/segmentation.py | from compositionspace.datautils import DataPreparation
from compositionspace.models import get_model
from sklearn.decomposition import PCA
from sklearn.mixture import GaussianMixture
import json
import h5py
import numpy as np
import pandas as pd
import matplotlib.pylab as plt
from tqdm.notebook import tqdm
import os
f... | 10,121 | 35.541516 | 106 | py |
CompositionSpaceNFDI | CompositionSpaceNFDI-main/compositionspace/paraprobe_transcoder.py | # -*- coding: utf-8 -*-
"""
Reader for the APSuite6/IVAS4 *.APT file format
MK::GPLV3, 03/09/2020, Markus K\"uhbach, m.kuehbach@mpie.de
"""
import numpy as np
#https://www.python-kurs.eu/numpy_dtype.php
class APTFileBranches():
def __init__(self):
self.dict_kwnsect = { 1: 'tof', 2: 'pulse', 3: 'freq', 4... | 26,191 | 50.66075 | 161 | py |
CompositionSpaceNFDI | CompositionSpaceNFDI-main/compositionspace/models.py | from ast import Raise
from sklearn.ensemble import RandomForestClassifier
from sklearn.mixture import GaussianMixture
from sklearn.cluster import DBSCAN
def get_model(ml_params):
"""
get machine learning model for clustering
"""
model_name = ml_params["name"]
model_params = ml_params[model_name]
... | 1,067 | 37.142857 | 144 | py |
CompositionSpaceNFDI | CompositionSpaceNFDI-main/compositionspace/__init__.py | 0 | 0 | 0 | py | |
CompositionSpaceNFDI | CompositionSpaceNFDI-main/compositionspace/postprocessing.py | import pandas as pd
import os
from tqdm.notebook import tqdm
import matplotlib.pyplot as plt
import numpy as np
import h5py
from sklearn.cluster import DBSCAN
from pyevtk.hl import pointsToVTK
from pyevtk.hl import gridToVTK
import yaml
class DataPostprocess:
def __init__(self, inputfile):
if isin... | 5,481 | 38.157143 | 126 | py |
CompositionSpaceNFDI | CompositionSpaceNFDI-main/tests/test_read_files.py | import pytest
import numpy as np
import os
import sys
from compositionspace.datautils import DataPreparation
def test_file_rrng():
data = DataPreparation("tests/experiment_params.yaml")
datarrng = data.get_rrng("tests/data/R31_06365-v02.rrng")
assert datarrng[0]["name"].values[0] == "C"
def test_file_p... | 1,213 | 31.810811 | 61 | py |
CompositionSpaceNFDI | CompositionSpaceNFDI-main/docs/source/conf.py | # Configuration file for the Sphinx documentation builder.
#
# For the full list of built-in configuration values, see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Project information -----------------------------------------------------
# https://www.sphinx-doc.org/en/master... | 1,349 | 23.545455 | 83 | py |
fuzzyJoiner | fuzzyJoiner-master/build_model.py | from random import shuffle
import pickle
import numpy as np
# import pandas
import tensorflow as tf
import random as random
import json
from keras import backend as K
from keras.preprocessing.text import Tokenizer
from keras.preprocessing.sequence import pad_sequences
from keras.layers import Dense, Input, Flatten, ... | 25,195 | 37.118003 | 249 | py |
fuzzyJoiner | fuzzyJoiner-master/preloaded_runner.py | import pickle
import numpy as np
import tensorflow as tf
import random as random
import json
from keras import backend as K
#from keras.preprocessing.text import Tokenizer
from keras.preprocessing.sequence import pad_sequences
from keras.layers import Input, Lambda, GRU
from keras.layers import Embedding
from kera... | 17,465 | 35.848101 | 139 | py |
fuzzyJoiner | fuzzyJoiner-master/parse_additive.py | 0 | 0 | 0 | py | |
fuzzyJoiner | fuzzyJoiner-master/Levenstien_Rule_Based.py | from sys import argv
import string
import Levenshtein
import statistics
from names_cleanser import NameDataCleanser, CompanyDataCleanser
def read_entities(filepath):
entities = []
with open(filepath, 'r', encoding='utf8') as fl:
for line in fl:
entities.append(line)
return entities
... | 8,910 | 37.409483 | 120 | py |
fuzzyJoiner | fuzzyJoiner-master/names_cleanser.py | import re
import argparse
import Levenshtein
from nltk import bigrams
from os import listdir
from os.path import isfile, join
from difflib import SequenceMatcher
# from sklearn.metrics import jaccard_similarity_score
class GenericDataCleanser(object):
name_reject_set = frozenset(['father of', '(', 'author of', '... | 15,807 | 37.462287 | 188 | py |
fuzzyJoiner | fuzzyJoiner-master/random_test_selecter.py | from sys import argv
from random import shuffle
input_file = open(argv[1], 'r')
output_file = open(argv[2], 'w')
lines = input_file.readlines()
shuffle(lines)
lines = lines[-int(argv[3]):]
for line in lines:
output_file.write(line)
input_file.close()
output_file.close()
| 272 | 21.75 | 32 | py |
fuzzyJoiner | fuzzyJoiner-master/old/TripletLossFacenetLSTM.py | import numpy as np
import random as random
# """
# The below is necessary in Python 3.2.3 onwards to
# have reproducible behavior for certain hash-based operations.
# See these references for further details:
# https://docs.python.org/3.4/using/cmdline.html#envvar-PYTHONHASHSEED
# https://github.com/keras-team/keras/is... | 21,712 | 37.227113 | 167 | py |
fuzzyJoiner | fuzzyJoiner-master/old/matcher_functions.py | import sqlalchemy
from sqlalchemy.sql import select
from sqlalchemy import Table, Column, Integer, String, MetaData, ForeignKey
def connect(user, password, db, host='localhost', port=5432):
'''Returns a connection and a metadata object'''
# We connect with the help of the PostgreSQL URL
# postgresql://feder... | 8,149 | 37.809524 | 114 | py |
fuzzyJoiner | fuzzyJoiner-master/old/TripletLossFacenetLSTM-8.20.18.py | import numpy as np
import pandas
import tensorflow as tf
import random as random
import json
from keras import backend as K
from keras.preprocessing.text import Tokenizer
from keras.preprocessing.sequence import pad_sequences
from keras.layers import Dense, Input, Flatten, Dropout, Lambda, GRU, Activation
from keras... | 21,235 | 36.061082 | 163 | py |
fuzzyJoiner | fuzzyJoiner-master/old/ANNBasedSampleSelection.py | import Named_Entity_Recognition_Modified
from keras.preprocessing.text import Tokenizer
from keras.preprocessing.sequence import pad_sequences
from embeddings import KazumaCharEmbedding
from annoy import AnnoyIndex
from matcher_functions import connect
import argparse
import numpy as np
from keras.layers import Embeddi... | 6,038 | 32.181319 | 138 | py |
fuzzyJoiner | fuzzyJoiner-master/old/TripletLossFacenetLSTM-angular.py | import numpy as np
import tensorflow as tf
import random as random
# import cntk as C
# """
# The below is necessary in Python 3.2.3 onwards to
# have reproducible behavior for certain hash-based operations.
# See these references for further details:
# https://docs.python.org/3.4/using/cmdline.html#envvar-PYTHONHASHSE... | 21,847 | 37.329825 | 167 | py |
fuzzyJoiner | fuzzyJoiner-master/old/Triplet_Iteration.py | from sys import argv
from keras import backend as K
from keras.preprocessing.text import Tokenizer
from keras.preprocessing.sequence import pad_sequences
from keras.layers import Dense, Input, Flatten, Dropout, Lambda
from keras.layers import Conv1D, MaxPooling1D, Embedding
from keras.models import Model, model_fr... | 14,236 | 37.374663 | 199 | py |
fuzzyJoiner | fuzzyJoiner-master/old/ContrastiveLossLSTM-8.20.18.py | import numpy as np
import pandas
import tensorflow as tf
import random as random
import json
from keras import backend as K
from keras.preprocessing.text import Tokenizer
from keras.preprocessing.sequence import pad_sequences
from keras.layers import Dense, Input, Flatten, Dropout, Lambda, GRU, Activation
from keras... | 19,575 | 35.86629 | 163 | py |
fuzzyJoiner | fuzzyJoiner-master/old/seq2seq.py | '''Sequence to sequence example in Keras (character-level).
This script demonstrates how to implement a basic character-level
sequence-to-sequence model. We apply it to translating
short English sentences into short French sentences,
character-by-character. Note that it is fairly unusual to
do character-level machine t... | 9,104 | 40.013514 | 79 | py |
fuzzyJoiner | fuzzyJoiner-master/old/matcher.py | #using tutorial https://suhas.org/sqlalchemy-tutorial/
from sys import argv
from matcher_functions import *
#establish connection to database
con, meta = connect(argv[1], argv[2], argv[3])
#load pairs from database
aliases = get_aliases(con, meta)
#create dictionaries assingning serial numbers to names and names from s... | 1,840 | 62.482759 | 152 | py |
fuzzyJoiner | fuzzyJoiner-master/old/cleanser.py | from sys import argv
from os import listdir
from os.path import isfile, join
if __name__ == '__main__':
parser = argparse.ArgumentParser(
description=__doc__,
formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument('-f', dest="input_file or directory", help="file to cleanse ... | 1,994 | 38.9 | 130 | py |
fuzzyJoiner | fuzzyJoiner-master/old/image_join3.py | 0 | 0 | 0 | py | |
fuzzyJoiner | fuzzyJoiner-master/old/matcher_class.py | from matcher_functions import load_good_buckets, create_double_num_dicts, connect, get_aliases
class matcher(object):
def __init__(self, user, password, database, test_pairs, bucket_number):
con, meta = connect(user, password, database)
num_to_word, word_to_num = create_double_num_dicts(get_aliases(... | 1,366 | 46.137931 | 105 | py |
fuzzyJoiner | fuzzyJoiner-master/old/Named_Entity_Recognition_Modified.py | """
This code is modified from
https://github.com/fchollet/keras/blob/master/examples/pretrained_word_embeddings.py
and ttps://github.com/fchollet/keras/blob/master/examples/
for our own purposes
"""
from __future__ import absolute_import
from __future__ import print_function
import numpy as np
from matcher_functio... | 23,976 | 36.289269 | 258 | py |
fuzzyJoiner | fuzzyJoiner-master/old/Named_Entity_Recognition.py | """
This code is modified from
https://github.com/fchollet/keras/blob/master/examples/pretrained_word_embeddings.py
and ttps://github.com/fchollet/keras/blob/master/examples/
for our own purposes
"""
from __future__ import absolute_import
from __future__ import print_function
import numpy as np
from matcher_functio... | 19,852 | 31.176661 | 254 | py |
fuzzyJoiner | fuzzyJoiner-master/old/face_vgg.py | 0 | 0 | 0 | py | |
fuzzyJoiner | fuzzyJoiner-master/old/TripletLossFacenetLSTM-modified.py | import numpy as np
import tensorflow as tf
import random as random
# import cntk as C
# """
# The below is necessary in Python 3.2.3 onwards to
# have reproducible behavior for certain hash-based operations.
# See these references for further details:
# https://docs.python.org/3.4/using/cmdline.html#envvar-PYTHONHASHSE... | 21,841 | 37.319298 | 167 | py |
fuzzyJoiner | fuzzyJoiner-master/old/ANNCharacteristics.py | import numpy as np
import pandas
import tensorflow as tf
import random as random
import json
from keras import backend as K
from keras.preprocessing.text import Tokenizer
from keras.preprocessing.sequence import pad_sequences
from keras.layers import Dense, Input, Flatten, Dropout, Lambda, GRU, Activation
from keras... | 19,558 | 35.355019 | 134 | py |
fuzzyJoiner | fuzzyJoiner-master/old/TripletLossFacenet.py | from sys import argv
from keras import backend as K
from keras.preprocessing.text import Tokenizer
from keras.preprocessing.sequence import pad_sequences
from keras.layers import Dense, Input, Flatten, Dropout, Lambda, LSTM
from keras.layers import Conv1D, MaxPooling1D, Embedding
from keras.models import Model, mo... | 12,095 | 37.893891 | 199 | py |
fuzzyJoiner | fuzzyJoiner-master/old/TripletLossFacenetLSTM-8.31.18.py | from random import shuffle
import numpy as np
import pandas
import tensorflow as tf
import random as random
import json
from keras import backend as K
from keras.preprocessing.text import Tokenizer
from keras.preprocessing.sequence import pad_sequences
from keras.layers import Dense, Input, Flatten, Dropout, Lambda... | 22,999 | 35.624204 | 163 | py |
fuzzyJoiner | fuzzyJoiner-master/old/image_join2.py | 0 | 0 | 0 | py | |
fuzzyJoiner | fuzzyJoiner-master/old/seq2seqTriplet.py | '''Sequence to sequence example in Keras (character-level).
This script demonstrates how to implement a basic character-level
sequence-to-sequence model. We apply it to translating
short English sentences into short French sentences,
character-by-character. Note that it is fairly unusual to
do character-level machine t... | 9,670 | 39.634454 | 106 | py |
fuzzyJoiner | fuzzyJoiner-master/old/image_join.py | 0 | 0 | 0 | py | |
fuzzyJoiner | fuzzyJoiner-master/old/TripletLossFacenetLSTM_hpo.py | import numpy as np
import pandas
import tensorflow as tf
import random as random
import json
from keras import backend as K
from keras.preprocessing.text import Tokenizer
from keras.preprocessing.sequence import pad_sequences
from keras.layers import Dense, Input, Flatten, Dropout, Lambda, GRU, Activation
from keras... | 19,474 | 35.88447 | 163 | py |
fuzzyJoiner | fuzzyJoiner-master/old/TripletLossFacenetLSTM-schroffloss.py | import numpy as np
import tensorflow as tf
import random as random
# import cntk as C
# """
# The below is necessary in Python 3.2.3 onwards to
# have reproducible behavior for certain hash-based operations.
# See these references for further details:
# https://docs.python.org/3.4/using/cmdline.html#envvar-PYTHONHASHSE... | 21,846 | 37.463028 | 167 | py |
fuzzyJoiner | fuzzyJoiner-master/old/file_parser.py | from sys import argv
onlyfiles = [f for f in listdir(args[1]) if isfile(join(args[1], f))]
for file_path in onlyfiles:
input_file = open(args[1] + "/" + file_path, encoding='utf-8')
output_file = open(argv[2] + "/" + file_path, "w", encoding='utf-8')
write_line = False
for line in input_file:
if write_line:
it... | 460 | 31.928571 | 69 | py |
fuzzyJoiner | fuzzyJoiner-master/old/TripletLossFacenetLSTM-8.29.18.py | import numpy as np
import pandas
import tensorflow as tf
import random as random
import json
from keras import backend as K
from keras.preprocessing.text import Tokenizer
from keras.preprocessing.sequence import pad_sequences
from keras.layers import Dense, Input, Flatten, Dropout, Lambda, GRU, Activation
from keras... | 21,235 | 36.061082 | 163 | py |
smt | smt-master/setup.py | """
Author: Dr. John T. Hwang <hwangjt@umich.edu>
Dr. Mohamed A. Bouhlel <mbouhlel@umich.edu>
Remi Lafage <remi.lafage@onera.fr>
Lucas Alber <lucasd.alber@gmail.com>
This package is distributed under New BSD license.
"""
from setuptools import setup, Extension
import sys
import numpy as np
from... | 3,762 | 29.346774 | 87 | py |
smt | smt-master/smt/__init__.py | __version__ = "2.0"
| 20 | 9.5 | 19 | py |
smt | smt-master/smt/examples/run_examples.py | """
Author: Dr. Mohamed A. Bouhlel <mbouhlel@umich>
Dr. John T. Hwang <hwangjt@umich.edu>
This package is distributed under New BSD license.
"""
import numpy as np
from scipy import linalg
from smt.utils import compute_rms_error
from smt.problems import Sphere, NdimRobotArm
from smt.sampling_methods import L... | 21,474 | 30.259098 | 173 | py |
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