metadata dict | text stringlengths 0 40.6M | id stringlengths 14 255 |
|---|---|---|
{
"filename": "test_pyramids.py",
"repo_name": "scikit-image/scikit-image",
"repo_path": "scikit-image_extracted/scikit-image-main/skimage/transform/tests/test_pyramids.py",
"type": "Python"
} | import math
import warnings
import pytest
import numpy as np
from numpy.testing import assert_almost_equal, assert_array_equal, assert_equal
from skimage import data
from skimage._shared.utils import _supported_float_type
from skimage.transform import pyramids
image = data.astronaut()
image_gray = image[..., 0]
@... | scikit-imageREPO_NAMEscikit-imagePATH_START.@scikit-image_extracted@scikit-image-main@skimage@transform@tests@test_pyramids.py@.PATH_END.py |
{
"filename": "tfcas.py",
"repo_name": "maxmahlke/classy",
"repo_path": "classy_extracted/classy-main/classy/sources/pds/tfcas.py",
"type": "Python"
} | import numpy as np
import pandas as pd
import rocks
from classy import config
from classy import index
# ------
# Module definitions
REFERENCES = {
"CHAPMAN1972": ["1972PhDT.........5C", "Chapman 1972"],
"CHAPMAN&GAFFEY1979A": ["1979aste.book..655C", "Chapman and Gaffey 1979"],
1: ["1979aste.book.1064C", ... | maxmahlkeREPO_NAMEclassyPATH_START.@classy_extracted@classy-main@classy@sources@pds@tfcas.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/waterfall/insidetextfont/__init__.py",
"type": "Python"
} | import sys
from typing import TYPE_CHECKING
if sys.version_info < (3, 7) or TYPE_CHECKING:
from ._weightsrc import WeightsrcValidator
from ._weight import WeightValidator
from ._variantsrc import VariantsrcValidator
from ._variant import VariantValidator
from ._textcasesrc import TextcasesrcValidat... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@waterfall@insidetextfont@__init__.py@.PATH_END.py |
{
"filename": "_parentssrc.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/treemap/_parentssrc.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class ParentssrcValidator(_plotly_utils.basevalidators.SrcValidator):
def __init__(self, plotly_name="parentssrc", parent_name="treemap", **kwargs):
super(ParentssrcValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@treemap@_parentssrc.py@.PATH_END.py |
{
"filename": "test_calculations.py",
"repo_name": "macrocosme/shwirl",
"repo_path": "shwirl_extracted/shwirl-master/shwirl/extern/vispy/geometry/tests/test_calculations.py",
"type": "Python"
} | # -*- coding: utf-8 -*-
# Copyright (c) 2015, Vispy Development Team.
# Distributed under the (new) BSD License. See LICENSE.txt for more info.
import numpy as np
from numpy.testing import assert_allclose
from vispy.testing import assert_raises
from vispy.geometry import resize
def test_resize():
"""Test image r... | macrocosmeREPO_NAMEshwirlPATH_START.@shwirl_extracted@shwirl-master@shwirl@extern@vispy@geometry@tests@test_calculations.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "bek0s/gbkfit",
"repo_path": "gbkfit_extracted/gbkfit-master/src/gbkfit/driver/native/__init__.py",
"type": "Python"
} | bek0sREPO_NAMEgbkfitPATH_START.@gbkfit_extracted@gbkfit-master@src@gbkfit@driver@native@__init__.py@.PATH_END.py | |
{
"filename": "reduction_metrics_test.py",
"repo_name": "fchollet/keras",
"repo_path": "keras_extracted/keras-master/keras/src/metrics/reduction_metrics_test.py",
"type": "Python"
} | import numpy as np
from keras.src import backend
from keras.src import testing
from keras.src.backend.common.keras_tensor import KerasTensor
from keras.src.metrics import reduction_metrics
from keras.src.saving import register_keras_serializable
class SumTest(testing.TestCase):
def test_config(self):
sum... | fcholletREPO_NAMEkerasPATH_START.@keras_extracted@keras-master@keras@src@metrics@reduction_metrics_test.py@.PATH_END.py |
{
"filename": "alpha_dropout.py",
"repo_name": "keras-team/keras",
"repo_path": "keras_extracted/keras-master/keras/src/layers/regularization/alpha_dropout.py",
"type": "Python"
} | from keras.src import backend
from keras.src import ops
from keras.src.api_export import keras_export
from keras.src.layers.layer import Layer
@keras_export("keras.layers.AlphaDropout")
class AlphaDropout(Layer):
"""Applies Alpha Dropout to the input.
Alpha Dropout is a `Dropout` that keeps mean and variance... | keras-teamREPO_NAMEkerasPATH_START.@keras_extracted@keras-master@keras@src@layers@regularization@alpha_dropout.py@.PATH_END.py |
{
"filename": "_orientation.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/histogram/_orientation.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class OrientationValidator(_plotly_utils.basevalidators.EnumeratedValidator):
def __init__(self, plotly_name="orientation", parent_name="histogram", **kwargs):
super(OrientationValidator, self).__init__(
plotly_name=plotly_name,
parent_name=paren... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@histogram@_orientation.py@.PATH_END.py |
{
"filename": "custom_call.filecheck.py",
"repo_name": "jax-ml/jax",
"repo_path": "jax_extracted/jax-main/tests/filecheck/custom_call.filecheck.py",
"type": "Python"
} | # Copyright 2023 The JAX Authors.
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in wri... | jax-mlREPO_NAMEjaxPATH_START.@jax_extracted@jax-main@tests@filecheck@custom_call.filecheck.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "b-thorne/PySM_public",
"repo_path": "PySM_public_extracted/PySM_public-master/pysm/test/__init__.py",
"type": "Python"
} | import os
import os.path
def get_testdata(*filename):
import pysm
# if a test data dir is set by run-tests.py, use it.
# otherwise fall back to the test data in source (e.g. if ran directly with py.test)
reldir = os.path.join(os.path.abspath(os.path.join(os.path.dirname(pysm.__file__), '..')), "test_da... | b-thorneREPO_NAMEPySM_publicPATH_START.@PySM_public_extracted@PySM_public-master@pysm@test@__init__.py@.PATH_END.py |
{
"filename": "core.py",
"repo_name": "D-arioSpace/astroquery",
"repo_path": "astroquery_extracted/astroquery-main/astroquery/splatalogue/core.py",
"type": "Python"
} | # Licensed under a 3-clause BSD style license - see LICENSE.rst
# -*- coding: utf-8 -*-
"""
Module to search Splatalogue.net via splat, modeled loosely on
ftp://ftp.cv.nrao.edu/NRAO-staff/bkent/slap/idl/
:author: Adam Ginsburg <adam.g.ginsburg@gmail.com>
"""
import json
from astropy.table import Table
from astropy imp... | D-arioSpaceREPO_NAMEastroqueryPATH_START.@astroquery_extracted@astroquery-main@astroquery@splatalogue@core.py@.PATH_END.py |
{
"filename": "CHANGELOG.md",
"repo_name": "dmentipl/plonk",
"repo_path": "plonk_extracted/plonk-main/CHANGELOG.md",
"type": "Markdown"
} | # Changelog
All notable changes to this project will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
Types of changes:
- `Added` for new features.
- `Changed` for chan... | dmentiplREPO_NAMEplonkPATH_START.@plonk_extracted@plonk-main@CHANGELOG.md@.PATH_END.py |
{
"filename": "readme.md",
"repo_name": "tomasoshea/chameleon",
"repo_path": "chameleon_extracted/chameleon-main/readme.md",
"type": "Markdown"
} | # solar chameleon production
Code to calculate the solar Primakoff production of light scalars / chameleons.
- *filter.py* reads solar model from AGSS09 files in data folder and outputs easy to use .dat files
- *solarcham.cpp* contains all the code needed to calculate spectra, energy loss, profiles etc in the form of... | tomasosheaREPO_NAMEchameleonPATH_START.@chameleon_extracted@chameleon-main@readme.md@.PATH_END.py |
{
"filename": "enumerate_ops.py",
"repo_name": "tensorflow/tensorflow",
"repo_path": "tensorflow_extracted/tensorflow-master/tensorflow/python/data/experimental/ops/enumerate_ops.py",
"type": "Python"
} | # Copyright 2017 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... | tensorflowREPO_NAMEtensorflowPATH_START.@tensorflow_extracted@tensorflow-master@tensorflow@python@data@experimental@ops@enumerate_ops.py@.PATH_END.py |
{
"filename": "test_numpy_network.py",
"repo_name": "pynucastro/pynucastro",
"repo_path": "pynucastro_extracted/pynucastro-main/pynucastro/networks/tests/test_numpy_network.py",
"type": "Python"
} | import pytest
from numpy.testing import assert_allclose
import pynucastro as pyna
class TestNumpyNetwork:
"""Make sure the vectorized methods give the same results."""
@pytest.fixture(scope="class")
def net(self, reaclib_library):
rate_names = ["c12(p,g)n13",
"c13(p,g)n14",... | pynucastroREPO_NAMEpynucastroPATH_START.@pynucastro_extracted@pynucastro-main@pynucastro@networks@tests@test_numpy_network.py@.PATH_END.py |
{
"filename": "independent_sample.py",
"repo_name": "POSYDON-code/POSYDON",
"repo_path": "POSYDON_extracted/POSYDON-main/posydon/popsyn/independent_sample.py",
"type": "Python"
} | """Generate the initial parameters for a binary population."""
__authors__ = [
"Devina Misra <devina.misra@unige.ch>",
"Jeffrey Andrews <jeffrey.andrews@northwestern.edu>",
"Kyle Akira Rocha <kylerocha2024@u.northwestern.edu>",
"Konstantinos Kovlakas <Konstantinos.Kovlakas@unige.ch>",
"Simone Bave... | POSYDON-codeREPO_NAMEPOSYDONPATH_START.@POSYDON_extracted@POSYDON-main@posydon@popsyn@independent_sample.py@.PATH_END.py |
{
"filename": "_discretization.py",
"repo_name": "rapidsai/cuml",
"repo_path": "cuml_extracted/cuml-main/python/cuml/cuml/_thirdparty/sklearn/preprocessing/_discretization.py",
"type": "Python"
} | # Original authors from Sckit-Learn:
# Henry Lin <hlin117@gmail.com>
# Tom Dupré la Tour
# License: BSD
# This code originates from the Scikit-Learn library,
# it was since modified to allow GPU acceleration.
# This code is under BSD 3 clause license.
# Authors mentioned above do not endorse or promo... | rapidsaiREPO_NAMEcumlPATH_START.@cuml_extracted@cuml-main@python@cuml@cuml@_thirdparty@sklearn@preprocessing@_discretization.py@.PATH_END.py |
{
"filename": "monitoring_test.py",
"repo_name": "google/jax",
"repo_path": "jax_extracted/jax-main/tests/monitoring_test.py",
"type": "Python"
} | # Copyright 2022 The JAX Authors.
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in wri... | googleREPO_NAMEjaxPATH_START.@jax_extracted@jax-main@tests@monitoring_test.py@.PATH_END.py |
{
"filename": "_stream.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/choropleth/_stream.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class StreamValidator(_plotly_utils.basevalidators.CompoundValidator):
def __init__(self, plotly_name="stream", parent_name="choropleth", **kwargs):
super(StreamValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@choropleth@_stream.py@.PATH_END.py |
{
"filename": "_marker.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/graph_objs/scatterpolar/unselected/_marker.py",
"type": "Python"
} | from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Marker(_BaseTraceHierarchyType):
# class properties
# --------------------
_parent_path_str = "scatterpolar.unselected"
_path_str = "scatterpolar.unselected.marker"
_valid_props = {"color... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@graph_objs@scatterpolar@unselected@_marker.py@.PATH_END.py |
{
"filename": "util.py",
"repo_name": "google/jax",
"repo_path": "jax_extracted/jax-main/jax/_src/numpy/util.py",
"type": "Python"
} | # Copyright 2020 The JAX Authors.
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in wri... | googleREPO_NAMEjaxPATH_START.@jax_extracted@jax-main@jax@_src@numpy@util.py@.PATH_END.py |
{
"filename": "diffusion_aspherical.py",
"repo_name": "guillochon/MOSFiT",
"repo_path": "MOSFiT_extracted/MOSFiT-master/mosfit/modules/transforms/diffusion_aspherical.py",
"type": "Python"
} | """Definitions for the `DiffusionAspherical` class."""
import numpy as np
from scipy.interpolate import interp1d
from mosfit.constants import C_CGS, DAY_CGS, FOUR_PI, KM_CGS, M_SUN_CGS
from mosfit.modules.transforms.transform import Transform
# Important: Only define one ``Module`` class per file.
class DiffusionA... | guillochonREPO_NAMEMOSFiTPATH_START.@MOSFiT_extracted@MOSFiT-master@mosfit@modules@transforms@diffusion_aspherical.py@.PATH_END.py |
{
"filename": "test_reference_metric.py",
"repo_name": "zachetienne/nrpytutorial",
"repo_path": "nrpytutorial_extracted/nrpytutorial-master/tests/test_reference_metric.py",
"type": "Python"
} | from UnitTesting.create_test import create_test
def test_Spherical():
module = 'reference_metric'
module_name = 'rfm_Spherical'
function_and_global_dict = {'reference_metric(True)': ['xxmin', 'xxmax', 'UnitVectors', 'ReU', 'ReDD', 'ghatDD', 'ghatUU', 'detgammahat',
'detgammahatdD... | zachetienneREPO_NAMEnrpytutorialPATH_START.@nrpytutorial_extracted@nrpytutorial-master@tests@test_reference_metric.py@.PATH_END.py |
{
"filename": "_color.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/table/cells/font/_color.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class ColorValidator(_plotly_utils.basevalidators.ColorValidator):
def __init__(self, plotly_name="color", parent_name="table.cells.font", **kwargs):
super(ColorValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@table@cells@font@_color.py@.PATH_END.py |
{
"filename": "fastframe.py",
"repo_name": "desihub/desisim",
"repo_path": "desisim_extracted/desisim-main/py/desisim/scripts/fastframe.py",
"type": "Python"
} | from __future__ import absolute_import, division, print_function
import sys, os
import numpy as np
from astropy.table import Table
import astropy.units as u
import specsim.simulator
from desispec.frame import Frame
import desispec.io
from desispec.resolution import Resolution
import desisim.io
import desisim.simexp
... | desihubREPO_NAMEdesisimPATH_START.@desisim_extracted@desisim-main@py@desisim@scripts@fastframe.py@.PATH_END.py |
{
"filename": "test_scripts_installed_correctly.py",
"repo_name": "lucabaldini/ixpeobssim",
"repo_path": "ixpeobssim_extracted/ixpeobssim-main/tests/test_scripts_installed_correctly.py",
"type": "Python"
} | import glob
import os
import subprocess as sp
def test_scripts_installed():
cwd = os.path.dirname(__file__)
scripts = glob.glob(os.path.join(cwd, '..', 'bin', '*.py'))
for script in scripts:
if '__init__.py' in script:
continue
name = os.path.basename(script).replace('.py', '... | lucabaldiniREPO_NAMEixpeobssimPATH_START.@ixpeobssim_extracted@ixpeobssim-main@tests@test_scripts_installed_correctly.py@.PATH_END.py |
{
"filename": "_cheatertype.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/carpet/aaxis/_cheatertype.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class CheatertypeValidator(_plotly_utils.basevalidators.EnumeratedValidator):
def __init__(self, plotly_name="cheatertype", parent_name="carpet.aaxis", **kwargs):
super(CheatertypeValidator, self).__init__(
plotly_name=plotly_name,
parent_name=pa... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@carpet@aaxis@_cheatertype.py@.PATH_END.py |
{
"filename": "data_structures.py",
"repo_name": "yt-project/yt",
"repo_path": "yt_extracted/yt-main/yt/frontends/art/data_structures.py",
"type": "Python"
} | import glob
import os
import struct
import weakref
import numpy as np
import yt.utilities.fortran_utils as fpu
from yt.data_objects.index_subobjects.octree_subset import OctreeSubset
from yt.data_objects.static_output import Dataset, ParticleFile
from yt.data_objects.unions import ParticleUnion
from yt.frontends.art.... | yt-projectREPO_NAMEytPATH_START.@yt_extracted@yt-main@yt@frontends@art@data_structures.py@.PATH_END.py |
{
"filename": "_textcasesrc.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/surface/hoverlabel/font/_textcasesrc.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class TextcasesrcValidator(_plotly_utils.basevalidators.SrcValidator):
def __init__(
self, plotly_name="textcasesrc", parent_name="surface.hoverlabel.font", **kwargs
):
super(TextcasesrcValidator, self).__init__(
plotly_name=plotly_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@surface@hoverlabel@font@_textcasesrc.py@.PATH_END.py |
{
"filename": "_legendgroup.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/histogram2dcontour/_legendgroup.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class LegendgroupValidator(_plotly_utils.basevalidators.StringValidator):
def __init__(
self, plotly_name="legendgroup", parent_name="histogram2dcontour", **kwargs
):
super(LegendgroupValidator, self).__init__(
plotly_name=plotly_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@histogram2dcontour@_legendgroup.py@.PATH_END.py |
{
"filename": "_ticktextsrc.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/choroplethmap/colorbar/_ticktextsrc.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator):
def __init__(
self, plotly_name="ticktextsrc", parent_name="choroplethmap.colorbar", **kwargs
):
super(TicktextsrcValidator, self).__init__(
plotly_name=plotly_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@choroplethmap@colorbar@_ticktextsrc.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "scipy/scipy",
"repo_path": "scipy_extracted/scipy-main/scipy/sparse/linalg/_eigen/tests/__init__.py",
"type": "Python"
} | scipyREPO_NAMEscipyPATH_START.@scipy_extracted@scipy-main@scipy@sparse@linalg@_eigen@tests@__init__.py@.PATH_END.py | |
{
"filename": "test_injection_sims.py",
"repo_name": "deepskies/deeplenstronomy",
"repo_path": "deeplenstronomy_extracted/deeplenstronomy-master/exploded_setup_old/test/test_ImSim/test_injection_sims.py",
"type": "Python"
} | from deeplenstronomy.ImSim import inject_simulations
from deeplenstronomy.PopSim.population import Population
import pytest
import numpy as np
import numpy.testing as npt
class TestPopulation(object):
def setup(self):
pass
def test_add_arc(self):
pop = Population()
kwargs_params, kwa... | deepskiesREPO_NAMEdeeplenstronomyPATH_START.@deeplenstronomy_extracted@deeplenstronomy-master@exploded_setup_old@test@test_ImSim@test_injection_sims.py@.PATH_END.py |
{
"filename": "planet_pos.py",
"repo_name": "Hoeijmakers/StarRotator",
"repo_path": "StarRotator_extracted/StarRotator-master/lib/planet_pos.py",
"type": "Python"
} | def calc_orbit_times(time_stamp, transitC, exposure_time, orb_p):
"""
Calculates the start, end and center of the transit from the provided times
input:
time_stamp: type: float, time
transitC: type:float, transit center - 2400000.
exposure_times: type: float, exposure time in seconds... | HoeijmakersREPO_NAMEStarRotatorPATH_START.@StarRotator_extracted@StarRotator-master@lib@planet_pos.py@.PATH_END.py |
{
"filename": "MakeMovie.py",
"repo_name": "saopicc/DDFacet",
"repo_path": "DDFacet_extracted/DDFacet-master/DDFacet/MakeMovie.py",
"type": "Python"
} | #!/usr/bin/env python
'''
DDFacet, a facet-based radio imaging package
Copyright (C) 2013-2016 Cyril Tasse, l'Observatoire de Paris,
SKA South Africa, Rhodes University
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 So... | saopiccREPO_NAMEDDFacetPATH_START.@DDFacet_extracted@DDFacet-master@DDFacet@MakeMovie.py@.PATH_END.py |
{
"filename": "_side.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/histogram2d/colorbar/title/_side.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class SideValidator(_plotly_utils.basevalidators.EnumeratedValidator):
def __init__(
self, plotly_name="side", parent_name="histogram2d.colorbar.title", **kwargs
):
super(SideValidator, self).__init__(
plotly_name=plotly_name,
parent_... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@histogram2d@colorbar@title@_side.py@.PATH_END.py |
{
"filename": "training_utils.py",
"repo_name": "tensorflow/tensorflow",
"repo_path": "tensorflow_extracted/tensorflow-master/tensorflow/python/keras/engine/training_utils.py",
"type": "Python"
} | # Copyright 2018 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... | tensorflowREPO_NAMEtensorflowPATH_START.@tensorflow_extracted@tensorflow-master@tensorflow@python@keras@engine@training_utils.py@.PATH_END.py |
{
"filename": "eis.py",
"repo_name": "spedas/pyspedas",
"repo_path": "pyspedas_extracted/pyspedas-master/pyspedas/projects/mms/eis/eis.py",
"type": "Python"
} | from pyspedas.projects.mms.mms_load_data import mms_load_data
from pyspedas.projects.mms.eis.mms_eis_omni import mms_eis_omni
from pyspedas.projects.mms.eis.mms_eis_spin_avg import mms_eis_spin_avg
from pyspedas.projects.mms.eis.mms_eis_set_metadata import mms_eis_set_metadata
from pyspedas.projects.mms.mms_config impo... | spedasREPO_NAMEpyspedasPATH_START.@pyspedas_extracted@pyspedas-master@pyspedas@projects@mms@eis@eis.py@.PATH_END.py |
{
"filename": "install.md",
"repo_name": "cdslaborg/paramonte",
"repo_path": "paramonte_extracted/paramonte-main/install.md",
"type": "Markdown"
} | ## The ParaMonte library build mechanisms
There are three ways to build the ParaMonte library:
1. Building via the [install.sh](https://github.com/cdslaborg/paramonte/blob/main/install.sh) Bash script located in the root
directory of the [ParaMonte GitHub repository](https://github.com/cdslaborg/paramonte) in t... | cdslaborgREPO_NAMEparamontePATH_START.@paramonte_extracted@paramonte-main@install.md@.PATH_END.py |
{
"filename": "anisotropygammas.py",
"repo_name": "vhaasteren/piccard",
"repo_path": "piccard_extracted/piccard-master/piccard/anisotropygammas.py",
"type": "Python"
} | #!/usr/bin/env python
"""
Copyright (c) 2013 Chiara Mingarelli
Contributed code for anisotropic gravitrational-wave background by Chiara
Mingarelli. Work that uses the anisotropic background functionality should
reference Mingarelli and Vecchio 2013, arXiv:1306.5394
Contributed work on anisotropic gravitational-wave... | vhaasterenREPO_NAMEpiccardPATH_START.@piccard_extracted@piccard-master@piccard@anisotropygammas.py@.PATH_END.py |
{
"filename": "mem.py",
"repo_name": "vortex-exoplanet/VIP",
"repo_path": "VIP_extracted/VIP-master/vip_hci/config/mem.py",
"type": "Python"
} | #! /usr/bin/env python
"""
System memory related functions
"""
__author__ = "Carlos Alberto Gomez Gonzalez"
__all__ = ["check_enough_memory", "get_available_memory"]
from psutil import virtual_memory
def get_available_memory(verbose=True):
"""
Get the available memory in bytes.
Parameters
---------... | vortex-exoplanetREPO_NAMEVIPPATH_START.@VIP_extracted@VIP-master@vip_hci@config@mem.py@.PATH_END.py |
{
"filename": "_textsrc.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/scatter/_textsrc.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator):
def __init__(self, plotly_name="textsrc", parent_name="scatter", **kwargs):
super(TextsrcValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
e... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@scatter@_textsrc.py@.PATH_END.py |
{
"filename": "_line.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/graph_objs/violin/_line.py",
"type": "Python"
} | from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Line(_BaseTraceHierarchyType):
# class properties
# --------------------
_parent_path_str = "violin"
_path_str = "violin.line"
_valid_props = {"color", "width"}
# color
# -----
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@graph_objs@violin@_line.py@.PATH_END.py |
{
"filename": "StreamKicks.ipynb",
"repo_name": "jobovy/stream-stream",
"repo_path": "stream-stream_extracted/stream-stream-main/py/StreamKicks.ipynb",
"type": "Jupyter Notebook"
} | ```python
import os, os.path
import numpy
from galpy.df import impulse_deltav_plummer, impulse_deltav_plummerstream
import seaborn as sns
from galpy.util import bovy_plot, bovy_conversion
from stream2_util import R0, V0
from matplotlib import pyplot
from matplotlib.ticker import NullFormatter
nullfmt= NullFormatter()
%... | jobovyREPO_NAMEstream-streamPATH_START.@stream-stream_extracted@stream-stream-main@py@StreamKicks.ipynb@.PATH_END.py |
{
"filename": "anthropic.ipynb",
"repo_name": "langchain-ai/langchain",
"repo_path": "langchain_extracted/langchain-master/docs/docs/integrations/chat/anthropic.ipynb",
"type": "Jupyter Notebook"
} | ---
sidebar_label: Anthropic
---
# ChatAnthropic
This notebook provides a quick overview for getting started with Anthropic [chat models](/docs/concepts/chat_models). For detailed documentation of all ChatAnthropic features and configurations head to the [API reference](https://python.langchain.com/api_reference/anthr... | langchain-aiREPO_NAMElangchainPATH_START.@langchain_extracted@langchain-master@docs@docs@integrations@chat@anthropic.ipynb@.PATH_END.py |
{
"filename": "base.py",
"repo_name": "EranOfek/AstroPack",
"repo_path": "AstroPack_extracted/AstroPack-main/matlab/util/scripts/base.py",
"type": "Python"
} | #----------------------------------------------------------------------------
# Project: ULTRASAT
# Module: Common
# File: base.py
# Title: General utilities
# Author: Chen Tishler, 01/2022
# @Dan - UT & doc
#----------------------------------------------------------------------------
#
# ==================... | EranOfekREPO_NAMEAstroPackPATH_START.@AstroPack_extracted@AstroPack-main@matlab@util@scripts@base.py@.PATH_END.py |
{
"filename": "calibration.py",
"repo_name": "ACCarnall/bagpipes",
"repo_path": "bagpipes_extracted/bagpipes-master/bagpipes/fitting/calibration.py",
"type": "Python"
} | import numpy as np
from numpy.polynomial.chebyshev import chebval, chebfit
class calib_model(object):
""" A class for modelling spectrophotometric calibration.
Parameters
----------
calib_dict : dictionary
Contains the desired parameters for the calibration model.
spectrum : array_like... | ACCarnallREPO_NAMEbagpipesPATH_START.@bagpipes_extracted@bagpipes-master@bagpipes@fitting@calibration.py@.PATH_END.py |
{
"filename": "_showgrid.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/layout/xaxis/_showgrid.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class ShowgridValidator(_plotly_utils.basevalidators.BooleanValidator):
def __init__(self, plotly_name="showgrid", parent_name="layout.xaxis", **kwargs):
super(ShowgridValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@layout@xaxis@_showgrid.py@.PATH_END.py |
{
"filename": "asfgrid.py",
"repo_name": "hposborn/MonoTools",
"repo_path": "MonoTools_extracted/MonoTools-main/MonoTools/stellar/isoclassify/isoclassify/direct/asfgrid.py",
"type": "Python"
} | #! /usr/bin/env python
# --------------------------------------------------------------
# The asfgrid is a python module to compute asteroseismic
# parameters for a star with given stellar parameters and vice versa.
# Copyright (C) 2015 Sanjib Sharma, Dennis Stello
# This program is free sof... | hposbornREPO_NAMEMonoToolsPATH_START.@MonoTools_extracted@MonoTools-main@MonoTools@stellar@isoclassify@isoclassify@direct@asfgrid.py@.PATH_END.py |
{
"filename": "_weight.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/volume/colorbar/tickfont/_weight.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class WeightValidator(_plotly_utils.basevalidators.IntegerValidator):
def __init__(
self, plotly_name="weight", parent_name="volume.colorbar.tickfont", **kwargs
):
super(WeightValidator, self).__init__(
plotly_name=plotly_name,
parent... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@volume@colorbar@tickfont@_weight.py@.PATH_END.py |
{
"filename": "CONTRIBUTING.md",
"repo_name": "microsoft/vscode",
"repo_path": "vscode_extracted/vscode-main/extensions/json-language-features/CONTRIBUTING.md",
"type": "Markdown"
} | ## Setup
- Clone [microsoft/vscode](https://github.com/microsoft/vscode)
- Run `npm i` at `/`, this will install
- Dependencies for `/extension/json-language-features/`
- Dependencies for `/extension/json-language-features/server/`
- devDependencies such as `gulp`
- Open `/extensions/json-language-features/` as the... | microsoftREPO_NAMEvscodePATH_START.@vscode_extracted@vscode-main@extensions@json-language-features@CONTRIBUTING.md@.PATH_END.py |
{
"filename": "test_svm.py",
"repo_name": "langchain-ai/langchain",
"repo_path": "langchain_extracted/langchain-master/libs/community/tests/unit_tests/retrievers/test_svm.py",
"type": "Python"
} | import pytest
from langchain_core.documents import Document
from langchain_community.embeddings import FakeEmbeddings
from langchain_community.retrievers.svm import SVMRetriever
class TestSVMRetriever:
@pytest.mark.requires("sklearn")
def test_from_texts(self) -> None:
input_texts = ["I have a pen.",... | langchain-aiREPO_NAMElangchainPATH_START.@langchain_extracted@langchain-master@libs@community@tests@unit_tests@retrievers@test_svm.py@.PATH_END.py |
{
"filename": "test_vald.py",
"repo_name": "AWehrhahn/SME",
"repo_path": "SME_extracted/SME-master/test/test_vald.py",
"type": "Python"
} | # -*- coding: utf-8 -*-
from os.path import dirname, join
import numpy as np
import pytest
from pysme.abund import Abund
from pysme.linelist.linelist import LineList
from pysme.linelist.vald import ValdFile
species = "Fe 1"
wlcent = 5502.9931
excit = 0.9582
gflog = -3.047
gamrad = 7.19
gamqst = -6.22
gamvw = 239.249... | AWehrhahnREPO_NAMESMEPATH_START.@SME_extracted@SME-master@test@test_vald.py@.PATH_END.py |
{
"filename": "list_correction.py",
"repo_name": "benrendle/AIMS",
"repo_path": "AIMS_extracted/AIMS-master/Binary_Grid_Generation/list_correction.py",
"type": "Python"
} | # Generates the full file locations for the final output table and saves this
# out to the desired location.
########################################
def get_lines(filename):
lines = []
with open(filename) as f:
for line in f:
lines.append(line)
return lines
##########################################
input... | benrendleREPO_NAMEAIMSPATH_START.@AIMS_extracted@AIMS-master@Binary_Grid_Generation@list_correction.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "BRML/climin",
"repo_path": "climin_extracted/climin-master/climin/__init__.py",
"type": "Python"
} | from __future__ import absolute_import
# Control breaking does not work on Windows after e.g. scipy.stats is
# imported because certain Fortran libraries register their own signal handler
# See:
# http://stackoverflow.com/questions/15457786/ctrl-c-crashes-python-after-importing-scipy-stats
# and https://github.com/num... | BRMLREPO_NAMEcliminPATH_START.@climin_extracted@climin-master@climin@__init__.py@.PATH_END.py |
{
"filename": "test_packaging.py",
"repo_name": "lucabaldini/ixpeobssim",
"repo_path": "ixpeobssim_extracted/ixpeobssim-main/tests/test_packaging.py",
"type": "Python"
} | #!/usr/bin/env python
#
# Copyright (C) 2020, the ixpeobssim team.
#
# 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.
#
#... | lucabaldiniREPO_NAMEixpeobssimPATH_START.@ixpeobssim_extracted@ixpeobssim-main@tests@test_packaging.py@.PATH_END.py |
{
"filename": "statistic.py",
"repo_name": "dazhiUBC/SCUBA2_MF",
"repo_path": "SCUBA2_MF_extracted/SCUBA2_MF-main/statistic.py",
"type": "Python"
} | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
fid_snr = np.load('fide_snr_850.npy')
de = pd.read_csv('850/deboosting_values_snr.dat',delimiter = ' ')
com = pd.read_csv('850/completeness_values_snr.dat',delimiter = ' ')
plt.plot(com['input_snr'],com['fraction'],color='tab:green',label = 'Comple... | dazhiUBCREPO_NAMESCUBA2_MFPATH_START.@SCUBA2_MF_extracted@SCUBA2_MF-main@statistic.py@.PATH_END.py |
{
"filename": "demo12.py",
"repo_name": "GalSim-developers/GalSim",
"repo_path": "GalSim_extracted/GalSim-main/examples/demo12.py",
"type": "Python"
} | # Copyright (c) 2012-2023 by the GalSim developers team on GitHub
# https://github.com/GalSim-developers
#
# This file is part of GalSim: The modular galaxy image simulation toolkit.
# https://github.com/GalSim-developers/GalSim
#
# GalSim is free software: redistribution and use in source and binary forms,
# with or w... | GalSim-developersREPO_NAMEGalSimPATH_START.@GalSim_extracted@GalSim-main@examples@demo12.py@.PATH_END.py |
{
"filename": "_autocolorscale.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/splom/marker/_autocolorscale.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator):
def __init__(
self, plotly_name="autocolorscale", parent_name="splom.marker", **kwargs
):
super(AutocolorscaleValidator, self).__init__(
plotly_name=plotly_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@splom@marker@_autocolorscale.py@.PATH_END.py |
{
"filename": "_tickvalssrc.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/indicator/gauge/axis/_tickvalssrc.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class TickvalssrcValidator(_plotly_utils.basevalidators.SrcValidator):
def __init__(
self, plotly_name="tickvalssrc", parent_name="indicator.gauge.axis", **kwargs
):
super(TickvalssrcValidator, self).__init__(
plotly_name=plotly_name,
... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@indicator@gauge@axis@_tickvalssrc.py@.PATH_END.py |
{
"filename": "flow.py",
"repo_name": "PrefectHQ/prefect",
"repo_path": "prefect_extracted/prefect-main/tests/test-projects/import-project/my_module/flow.py",
"type": "Python"
} | import prefect
from .utils import get_output
@prefect.flow(name="test")
def test_flow():
return get_output()
@prefect.flow(name="test")
def prod_flow():
return get_output()
| PrefectHQREPO_NAMEprefectPATH_START.@prefect_extracted@prefect-main@tests@test-projects@import-project@my_module@flow.py@.PATH_END.py |
{
"filename": "randDemo.py",
"repo_name": "AstroVPK/kali",
"repo_path": "kali_extracted/kali-master/examples/randDemo.py",
"type": "Python"
} | #!/usr/bin/env python
""" Module to draw hardware random numbers.
For a demonstration of the module, please run the module as a command line program eg.
bash-prompt$ python randDemo.py --help
and
bash-prompt$ python randDemo.py -n 100
"""
import numpy as np
import rand
if __name__ == '__main__':
... | AstroVPKREPO_NAMEkaliPATH_START.@kali_extracted@kali-master@examples@randDemo.py@.PATH_END.py |
{
"filename": "ROADMAP.md",
"repo_name": "ledatelescope/bifrost",
"repo_path": "bifrost_extracted/bifrost-master/ROADMAP.md",
"type": "Markdown"
} | # Bifrost Roadmap
This is a high-level outline of Bifrost development plans. Unless otherwise
stated, the items on this page have not yet been developed.
## Algorithms and blocks
* Single-pulse search algorithms
* Baseline removal, peak finding
* Pulsar search algorithms
* Harmonic summing, folding
* Calibr... | ledatelescopeREPO_NAMEbifrostPATH_START.@bifrost_extracted@bifrost-master@ROADMAP.md@.PATH_END.py |
{
"filename": "F2b.py",
"repo_name": "mlares/hearsay",
"repo_path": "hearsay_extracted/hearsay-master/paper/F2b.py",
"type": "Python"
} | from hearsay import hearsay
import numpy as np
import pandas as pd
from itertools import product as pp
from matplotlib import pyplot as plt
# Figura 2a
# (a) Variation of tau_survive for fixed tau_awakening
# -----------------------------------------------------
# 1) Generate points in the paramter space to sample ... | mlaresREPO_NAMEhearsayPATH_START.@hearsay_extracted@hearsay-master@paper@F2b.py@.PATH_END.py |
{
"filename": "combspec_main.py",
"repo_name": "desihub/LSS",
"repo_path": "LSS_extracted/LSS-main/scripts/main/combspec_main.py",
"type": "Python"
} | #standard python
import sys
import os
import shutil
import unittest
from datetime import datetime
import json
import numpy as np
import fitsio
import glob
import argparse
from astropy.table import Table,join,unique,vstack
from matplotlib import pyplot as plt
from desitarget.io import read_targets_in_tiles
from desitarg... | desihubREPO_NAMELSSPATH_START.@LSS_extracted@LSS-main@scripts@main@combspec_main.py@.PATH_END.py |
{
"filename": "test_uncertainties.py",
"repo_name": "hover2pi/sedkit",
"repo_path": "sedkit_extracted/sedkit-main/tests/test_uncertainties.py",
"type": "Python"
} | import unittest
import astropy.units as q
import numpy as np
from sedkit import uncertainties as un
class TestUnum(unittest.TestCase):
"""Tests for the Unum class"""
def setUp(self):
"""Setup the tests"""
# Symmetry
self.sym = un.Unum(10.1, 0.2)
self.asym = un.Unum(9.3, 0.08,... | hover2piREPO_NAMEsedkitPATH_START.@sedkit_extracted@sedkit-main@tests@test_uncertainties.py@.PATH_END.py |
{
"filename": "generalized_linear_model.py",
"repo_name": "statsmodels/statsmodels",
"repo_path": "statsmodels_extracted/statsmodels-main/statsmodels/genmod/generalized_linear_model.py",
"type": "Python"
} | """
Generalized linear models currently supports estimation using the one-parameter
exponential families
References
----------
Gill, Jeff. 2000. Generalized Linear Models: A Unified Approach.
SAGE QASS Series.
Green, PJ. 1984. "Iteratively reweighted least squares for maximum
likelihood estimation, and some ... | statsmodelsREPO_NAMEstatsmodelsPATH_START.@statsmodels_extracted@statsmodels-main@statsmodels@genmod@generalized_linear_model.py@.PATH_END.py |
{
"filename": "tree_sitter_segmenter.py",
"repo_name": "langchain-ai/langchain",
"repo_path": "langchain_extracted/langchain-master/libs/community/langchain_community/document_loaders/parsers/language/tree_sitter_segmenter.py",
"type": "Python"
} | from abc import abstractmethod
from typing import TYPE_CHECKING, List
from langchain_community.document_loaders.parsers.language.code_segmenter import (
CodeSegmenter,
)
if TYPE_CHECKING:
from tree_sitter import Language, Parser
class TreeSitterSegmenter(CodeSegmenter):
"""Abstract class for `CodeSegmen... | langchain-aiREPO_NAMElangchainPATH_START.@langchain_extracted@langchain-master@libs@community@langchain_community@document_loaders@parsers@language@tree_sitter_segmenter.py@.PATH_END.py |
{
"filename": "_constrain.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/layout/xaxis/_constrain.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class ConstrainValidator(_plotly_utils.basevalidators.EnumeratedValidator):
def __init__(self, plotly_name="constrain", parent_name="layout.xaxis", **kwargs):
super(ConstrainValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_n... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@layout@xaxis@_constrain.py@.PATH_END.py |
{
"filename": "GiRaFFEfood_NRPy_Three_Waves.py",
"repo_name": "zachetienne/nrpytutorial",
"repo_path": "nrpytutorial_extracted/nrpytutorial-master/in_progress-GiRaFFE_NRPy/GiRaFFEfood_NRPy/GiRaFFEfood_NRPy_Three_Waves.py",
"type": "Python"
} | # Step 0: Add NRPy's directory to the path
# https://stackoverflow.com/questions/16780014/import-file-from-parent-directory
import os,sys
nrpy_dir_path = os.path.join("..")
if nrpy_dir_path not in sys.path:
sys.path.append(nrpy_dir_path)
nrpy_dir_path = os.path.join("../..")
if nrpy_dir_path not in sys.path:
sy... | zachetienneREPO_NAMEnrpytutorialPATH_START.@nrpytutorial_extracted@nrpytutorial-master@in_progress-GiRaFFE_NRPy@GiRaFFEfood_NRPy@GiRaFFEfood_NRPy_Three_Waves.py@.PATH_END.py |
{
"filename": "cleanup_downloads.py",
"repo_name": "astropy/astroquery",
"repo_path": "astroquery_extracted/astroquery-main/astroquery/utils/cleanup_downloads.py",
"type": "Python"
} | # Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
Utility to cleanup files created during doctesting.
"""
import glob
import os
import shutil
__all__ = ['cleanup_saved_downloads']
def cleanup_saved_downloads(names):
""" Function to clean up save files.
Parameters
----------
names :... | astropyREPO_NAMEastroqueryPATH_START.@astroquery_extracted@astroquery-main@astroquery@utils@cleanup_downloads.py@.PATH_END.py |
{
"filename": "_valueformat.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/indicator/number/_valueformat.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class ValueformatValidator(_plotly_utils.basevalidators.StringValidator):
def __init__(
self, plotly_name="valueformat", parent_name="indicator.number", **kwargs
):
super(ValueformatValidator, self).__init__(
plotly_name=plotly_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@indicator@number@_valueformat.py@.PATH_END.py |
{
"filename": "_minzoom.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/layout/mapbox/layer/_minzoom.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class MinzoomValidator(_plotly_utils.basevalidators.NumberValidator):
def __init__(
self, plotly_name="minzoom", parent_name="layout.mapbox.layer", **kwargs
):
super(MinzoomValidator, self).__init__(
plotly_name=plotly_name,
parent_na... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@layout@mapbox@layer@_minzoom.py@.PATH_END.py |
{
"filename": "_familysrc.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/sunburst/textfont/_familysrc.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator):
def __init__(
self, plotly_name="familysrc", parent_name="sunburst.textfont", **kwargs
):
super(FamilysrcValidator, self).__init__(
plotly_name=plotly_name,
parent_n... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@sunburst@textfont@_familysrc.py@.PATH_END.py |
{
"filename": "ClassSpectralFunctions.py",
"repo_name": "saopicc/DDFacet",
"repo_path": "DDFacet_extracted/DDFacet-master/DDFacet/ToolsDir/ClassSpectralFunctions.py",
"type": "Python"
} | '''
DDFacet, a facet-based radio imaging package
Copyright (C) 2013-2016 Cyril Tasse, l'Observatoire de Paris,
SKA South Africa, Rhodes University
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; eit... | saopiccREPO_NAMEDDFacetPATH_START.@DDFacet_extracted@DDFacet-master@DDFacet@ToolsDir@ClassSpectralFunctions.py@.PATH_END.py |
{
"filename": "_selected.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/choropleth/_selected.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class SelectedValidator(_plotly_utils.basevalidators.CompoundValidator):
def __init__(self, plotly_name="selected", parent_name="choropleth", **kwargs):
super(SelectedValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@choropleth@_selected.py@.PATH_END.py |
{
"filename": "ceres_optimizer.py",
"repo_name": "dstndstn/tractor",
"repo_path": "tractor_extracted/tractor-main/tractor/ceres_optimizer.py",
"type": "Python"
} | from __future__ import print_function
import numpy as np
from astrometry.util.ttime import Time
from tractor.engine import logverb
from tractor.optimize import Optimizer
class CeresOptimizer(Optimizer):
def __init__(self, BW=10, BH=10, threads=None):
super(CeresOptimizer, self).__init__()
self.... | dstndstnREPO_NAMEtractorPATH_START.@tractor_extracted@tractor-main@tractor@ceres_optimizer.py@.PATH_END.py |
{
"filename": "tutorial_mast.md",
"repo_name": "rbuehler/vasca",
"repo_path": "vasca_extracted/vasca-main/docs/tutorials/tutorial_mast.md",
"type": "Markdown"
} | ---
jupytext:
hide_notebook_metadata: true
text_representation:
extension: .md
format_name: myst
format_version: 0.13
jupytext_version: 1.16.4
kernelspec:
display_name: vasca-github
language: python
name: vasca-github
---
```{code-cell}
:tags: [remove-input]
import pandas as pd
from IPython.... | rbuehlerREPO_NAMEvascaPATH_START.@vasca_extracted@vasca-main@docs@tutorials@tutorial_mast.md@.PATH_END.py |
{
"filename": "predict.py",
"repo_name": "jtdinsmore/leakagelib",
"repo_path": "leakagelib_extracted/leakagelib-main/examples/predict.py",
"type": "Python"
} | import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
import sys, os
sys.path.append("../..")
import leakagelib
import time
SOURCE_SIZE = 53 # pixels
PIXEL_SIZE = 2.8 # arcsec
VMAX = 0.5
SPECTRUM = leakagelib.Spectrum.from_power_law_index(2)
leakagelib.funcs.override_matplotlib_defaults() # Set ... | jtdinsmoreREPO_NAMEleakagelibPATH_START.@leakagelib_extracted@leakagelib-main@examples@predict.py@.PATH_END.py |
{
"filename": "generative_agents_interactive_simulacra_of_human_behavior.ipynb",
"repo_name": "langchain-ai/langchain",
"repo_path": "langchain_extracted/langchain-master/cookbook/generative_agents_interactive_simulacra_of_human_behavior.ipynb",
"type": "Jupyter Notebook"
} | # Generative Agents in LangChain
This notebook implements a generative agent based on the paper [Generative Agents: Interactive Simulacra of Human Behavior](https://arxiv.org/abs/2304.03442) by Park, et. al.
In it, we leverage a time-weighted Memory object backed by a LangChain Retriever.
```python
# Use termcolor ... | langchain-aiREPO_NAMElangchainPATH_START.@langchain_extracted@langchain-master@cookbook@generative_agents_interactive_simulacra_of_human_behavior.ipynb@.PATH_END.py |
{
"filename": "_visible.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/scatter3d/error_y/_visible.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class VisibleValidator(_plotly_utils.basevalidators.BooleanValidator):
def __init__(
self, plotly_name="visible", parent_name="scatter3d.error_y", **kwargs
):
super(VisibleValidator, self).__init__(
plotly_name=plotly_name,
parent_nam... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@scatter3d@error_y@_visible.py@.PATH_END.py |
{
"filename": "_textcase.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/sankey/hoverlabel/font/_textcase.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class TextcaseValidator(_plotly_utils.basevalidators.EnumeratedValidator):
def __init__(
self, plotly_name="textcase", parent_name="sankey.hoverlabel.font", **kwargs
):
super(TextcaseValidator, self).__init__(
plotly_name=plotly_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@sankey@hoverlabel@font@_textcase.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "rapidsai/cuml",
"repo_path": "cuml_extracted/cuml-main/python/cuml/cuml/neighbors/__init__.py",
"type": "Python"
} | #
# Copyright (c) 2019-2023, NVIDIA 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 required by applicable law or ag... | rapidsaiREPO_NAMEcumlPATH_START.@cuml_extracted@cuml-main@python@cuml@cuml@neighbors@__init__.py@.PATH_END.py |
{
"filename": "test_psfs.py",
"repo_name": "LouisDesdoigts/dLux",
"repo_path": "dLux_extracted/dLux-main/tests/test_psfs.py",
"type": "Python"
} | from jax import numpy as np, config
config.update("jax_debug_nans", True)
import pytest
from dLux import PSF
@pytest.fixture
def psf():
return PSF(np.ones((16, 16)), 1 / 16)
class TestPSF:
def test_constructor(self, psf):
assert psf.npixels == 16
assert psf.pixel_scale == 1 / 16
def te... | LouisDesdoigtsREPO_NAMEdLuxPATH_START.@dLux_extracted@dLux-main@tests@test_psfs.py@.PATH_END.py |
{
"filename": "_labelalias.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/densitymap/colorbar/_labelalias.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class LabelaliasValidator(_plotly_utils.basevalidators.AnyValidator):
def __init__(
self, plotly_name="labelalias", parent_name="densitymap.colorbar", **kwargs
):
super(LabelaliasValidator, self).__init__(
plotly_name=plotly_name,
par... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@densitymap@colorbar@_labelalias.py@.PATH_END.py |
{
"filename": "adamax_test.py",
"repo_name": "keras-team/keras",
"repo_path": "keras_extracted/keras-master/keras/src/optimizers/adamax_test.py",
"type": "Python"
} | # flake8: noqa
import numpy as np
from keras.src import backend
from keras.src import ops
from keras.src import testing
from keras.src.optimizers.adamax import Adamax
class AdamaxTest(testing.TestCase):
def test_config(self):
optimizer = Adamax(
learning_rate=0.5,
beta_1=0.8,
... | keras-teamREPO_NAMEkerasPATH_START.@keras_extracted@keras-master@keras@src@optimizers@adamax_test.py@.PATH_END.py |
{
"filename": "dump.py",
"repo_name": "langchain-ai/langchain",
"repo_path": "langchain_extracted/langchain-master/libs/core/langchain_core/load/dump.py",
"type": "Python"
} | import json
from typing import Any
from langchain_core.load.serializable import Serializable, to_json_not_implemented
def default(obj: Any) -> Any:
"""Return a default value for a Serializable object or
a SerializedNotImplemented object.
Args:
obj: The object to serialize to json if it is a Seri... | langchain-aiREPO_NAMElangchainPATH_START.@langchain_extracted@langchain-master@libs@core@langchain_core@load@dump.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "Starfish-develop/Starfish",
"repo_path": "Starfish_extracted/Starfish-master/Starfish/__init__.py",
"type": "Python"
} | __version__ = "0.4.2"
from .spectrum import Spectrum
__all__ = [
"constants",
"emulator",
"grid_tools",
"models",
"samplers",
"spectrum",
"Spectrum",
"transforms",
"utils",
]
| Starfish-developREPO_NAMEStarfishPATH_START.@Starfish_extracted@Starfish-master@Starfish@__init__.py@.PATH_END.py |
{
"filename": "centroid.py",
"repo_name": "SAMI-Galaxy-Survey/sami",
"repo_path": "sami_extracted/sami-master/observing/centroid.py",
"type": "Python"
} | """
This file contains some functions used during SAMI observing. These revolve around fitting stars in the RSS data.
1) centroid(infile, ifus='all', outfile=None, plot=True)
-infile should be a reduced RSS file, already passed through 2dfdr.
-ifus should be a list of the probe numbers you want to run on, e.g. [11,12... | SAMI-Galaxy-SurveyREPO_NAMEsamiPATH_START.@sami_extracted@sami-master@observing@centroid.py@.PATH_END.py |
{
"filename": "python-features-data__desc.md",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/catboost/docs/en/concepts/python-features-data__desc.md",
"type": "Markdown"
} | # FeaturesData
```python
class FeaturesData(num_feature_data=None,
cat_feature_data=None,
num_feature_names=None,
cat_feature_names=None)
```
## {{ dl--purpose }} {#purpose}
Allows to optimally store the feature data for further passing to the [Pool](python-re... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@catboost@docs@en@concepts@python-features-data__desc.md@.PATH_END.py |
{
"filename": "main.py",
"repo_name": "cdslaborg/paramonte",
"repo_path": "paramonte_extracted/paramonte-main/benchmark/fortran/pm_sampleCov/setCov_dim1_vs_dim2/main.py",
"type": "Python"
} | #!/usr/bin/env python
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import os
dirname = os.path.basename(os.getcwd())
fontsize = 14
df = pd.read_csv("main.out", delimiter = ",")
colnames = list(df.columns.values)
############################################################################... | cdslaborgREPO_NAMEparamontePATH_START.@paramonte_extracted@paramonte-main@benchmark@fortran@pm_sampleCov@setCov_dim1_vs_dim2@main.py@.PATH_END.py |
{
"filename": "test_hidden_layer.py",
"repo_name": "pyro-ppl/pyro",
"repo_path": "pyro_extracted/pyro-master/tests/contrib/bnn/test_hidden_layer.py",
"type": "Python"
} | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
import torch.nn.functional as F
from torch.distributions import Normal
from pyro.contrib.bnn import HiddenLayer
from tests.common import assert_equal
@pytest.mark.parametrize("non_linearity", [F.relu])... | pyro-pplREPO_NAMEpyroPATH_START.@pyro_extracted@pyro-master@tests@contrib@bnn@test_hidden_layer.py@.PATH_END.py |
{
"filename": "aft_survival_demo.py",
"repo_name": "dmlc/xgboost",
"repo_path": "xgboost_extracted/xgboost-master/demo/aft_survival/aft_survival_demo.py",
"type": "Python"
} | """
Demo for survival analysis (regression).
========================================
Demo for survival analysis (regression). using Accelerated Failure Time (AFT) model.
"""
import os
import numpy as np
import pandas as pd
from sklearn.model_selection import ShuffleSplit
import xgboost as xgb
# The Veterans' Admi... | dmlcREPO_NAMExgboostPATH_START.@xgboost_extracted@xgboost-master@demo@aft_survival@aft_survival_demo.py@.PATH_END.py |
{
"filename": "physical_constants.py",
"repo_name": "xraypy/xraylarch",
"repo_path": "xraylarch_extracted/xraylarch-master/larch/utils/physical_constants.py",
"type": "Python"
} | # Useful physical constants
# most of these are put into common X-ray units (Angstroms, ev)
import scipy.constants as consts
from numpy import pi
I = 0.0 + 1.0j
RAD2DEG = 180.0/pi
DEG2RAD = pi/180.0
PI = pi
TAU = 2*pi
# cross-section unit
BARN = 1.e-24 # cm^2
# atoms/mol = 6.0221413e23 atoms/mol
AVOGADRO =... | xraypyREPO_NAMExraylarchPATH_START.@xraylarch_extracted@xraylarch-master@larch@utils@physical_constants.py@.PATH_END.py |
{
"filename": "activations_test.py",
"repo_name": "keras-team/keras",
"repo_path": "keras_extracted/keras-master/keras/src/activations/activations_test.py",
"type": "Python"
} | import numpy as np
from keras.src import activations
from keras.src import backend
from keras.src import testing
def _ref_softmax(values):
m = np.max(values)
e = np.exp(values - m)
return e / np.sum(e)
def _ref_softplus(x):
return np.log(np.ones_like(x) + np.exp(x))
def _ref_log_softmax(values):
... | keras-teamREPO_NAMEkerasPATH_START.@keras_extracted@keras-master@keras@src@activations@activations_test.py@.PATH_END.py |
{
"filename": "PsBsB.py",
"repo_name": "nickhand/pyRSD",
"repo_path": "pyRSD_extracted/pyRSD-master/pyRSD/rsd/power/gal/Pss/PsBsB.py",
"type": "Python"
} | from .. import TwoHaloTerm, OneHaloTerm, DampedGalaxyPowerTerm
class PsBsB_2h(TwoHaloTerm):
"""
The 2-halo term for `PsBsB`
"""
name = 'PsBsB_2h'
def __init__(self, model):
super(PsBsB_2h, self).__init__(model, 'b1_sB')
class PsBsB_1h(OneHaloTerm):
"""
The 1-halo term for `PsBsB`
... | nickhandREPO_NAMEpyRSDPATH_START.@pyRSD_extracted@pyRSD-master@pyRSD@rsd@power@gal@Pss@PsBsB.py@.PATH_END.py |
{
"filename": "bimod_censat_params.py",
"repo_name": "ArgonneCPAC/diffmah",
"repo_path": "diffmah_extracted/diffmah-main/diffmah/diffmahpop_kernels/bimod_censat_params.py",
"type": "Python"
} | """
"""
from collections import OrderedDict, namedtuple
from jax import jit as jjit
from . import (
covariance_kernels,
early_index_bimod,
frac_early_cens,
late_index_bimod,
logtc_bimod,
)
from .bimod_logm0_kernels import logm0_pop_bimod
from .bimod_logm0_sats import logm0_pop_bimod_sats
from .t_... | ArgonneCPACREPO_NAMEdiffmahPATH_START.@diffmah_extracted@diffmah-main@diffmah@diffmahpop_kernels@bimod_censat_params.py@.PATH_END.py |
{
"filename": "test_na_scalar.py",
"repo_name": "pandas-dev/pandas",
"repo_path": "pandas_extracted/pandas-main/pandas/tests/scalar/test_na_scalar.py",
"type": "Python"
} | from datetime import (
date,
time,
timedelta,
)
import pickle
import numpy as np
import pytest
from pandas._libs.missing import NA
from pandas.core.dtypes.common import is_scalar
import pandas as pd
import pandas._testing as tm
def test_singleton():
assert NA is NA
new_NA = type(NA)()
asse... | pandas-devREPO_NAMEpandasPATH_START.@pandas_extracted@pandas-main@pandas@tests@scalar@test_na_scalar.py@.PATH_END.py |
{
"filename": "_itertools.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/tools/python3/Lib/importlib/resources/_itertools.py",
"type": "Python"
} | # from more_itertools 9.0
def only(iterable, default=None, too_long=None):
"""If *iterable* has only one item, return it.
If it has zero items, return *default*.
If it has more than one item, raise the exception given by *too_long*,
which is ``ValueError`` by default.
>>> only([], default='missing')... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@tools@python3@Lib@importlib@resources@_itertools.py@.PATH_END.py |
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