metadata dict | text stringlengths 0 40.6M | id stringlengths 14 255 |
|---|---|---|
{
"filename": "example_linear.py",
"repo_name": "jinshisai/SLAM",
"repo_path": "SLAM_extracted/SLAM-main/example_linear.py",
"type": "Python"
} | import numpy as np
from pvanalysis import PVAnalysis
'-------- INPUTS --------'
fitsfile = './testfits/testlinear.fits'
outname = 'linear' # file name header for outputs
incl = 65. # deg
vsys = 4.0 # km/s
dist = 139. # pc
rms = 2.4e-3 # Jy/beam
thr = 5. # rms
ridgemode = 'mean' # 'mean' or 'gauss'
xlim = [-70, ... | jinshisaiREPO_NAMESLAMPATH_START.@SLAM_extracted@SLAM-main@example_linear.py@.PATH_END.py |
{
"filename": "CustomInterstellar.py",
"repo_name": "xpsi-group/xpsi",
"repo_path": "xpsi_extracted/xpsi-main/examples/examples_modeling_tutorial/modules/CustomInterstellar.py",
"type": "Python"
} | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Jun 6 16:56:44 2024
@author: bas
"""
import xpsi
from xpsi import Parameter
import numpy as np
from scipy.interpolate import Akima1DInterpolator
class CustomInterstellar(xpsi.Interstellar):
""" Apply interstellar attenuation. """
def __init... | xpsi-groupREPO_NAMExpsiPATH_START.@xpsi_extracted@xpsi-main@examples@examples_modeling_tutorial@modules@CustomInterstellar.py@.PATH_END.py |
{
"filename": "intro.ipynb",
"repo_name": "dfm/tinygp",
"repo_path": "tinygp_extracted/tinygp-main/docs/tutorials/intro.ipynb",
"type": "Jupyter Notebook"
} | ```python
try:
import tinygp
except ImportError:
%pip install -q tinygp
```
(intro)=
# An Introduction to tinygp
This tutorial provides a brief introduction to how Gaussian Processes (GPs) are implemented in `tinygp`.
We're not going to provide much of an introduction to GPs themselves, because there are alr... | dfmREPO_NAMEtinygpPATH_START.@tinygp_extracted@tinygp-main@docs@tutorials@intro.ipynb@.PATH_END.py |
{
"filename": "_east.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/layout/mapbox/bounds/_east.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class EastValidator(_plotly_utils.basevalidators.NumberValidator):
def __init__(
self, plotly_name="east", parent_name="layout.mapbox.bounds", **kwargs
):
super(EastValidator, self).__init__(
plotly_name=plotly_name,
parent_name=paren... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@layout@mapbox@bounds@_east.py@.PATH_END.py |
{
"filename": "test_halo_model.py",
"repo_name": "halomod/halomod",
"repo_path": "halomod_extracted/halomod-main/tests/test_halo_model.py",
"type": "Python"
} | """Integration-style tests of the full HaloModel class."""
import warnings
import numpy as np
import pytest
from hmf.density_field.filters import Filter
from hmf.halos.mass_definitions import MassDefinition
from halomod import DMHaloModel, TracerHaloModel
from halomod.bias import Bias
from halomod.concentration impo... | halomodREPO_NAMEhalomodPATH_START.@halomod_extracted@halomod-main@tests@test_halo_model.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "CobayaSampler/cobaya",
"repo_path": "cobaya_extracted/cobaya-master/cobaya/likelihoods/planck_2015_lensing/__init__.py",
"type": "Python"
} | from cobaya.likelihoods.base_classes import PlanckClik
class planck_2015_lensing(PlanckClik):
r"""
Lensing likelihood of Planck's 2015 data release based on temperature+polarization
map-based lensing reconstruction \cite{Ade:2015zua}.
"""
pass
| CobayaSamplerREPO_NAMEcobayaPATH_START.@cobaya_extracted@cobaya-master@cobaya@likelihoods@planck_2015_lensing@__init__.py@.PATH_END.py |
{
"filename": "contact.md",
"repo_name": "lsst-uk/lasair-lsst",
"repo_path": "lasair-lsst_extracted/lasair-lsst-main/docs/source/more_info/contact.md",
"type": "Markdown"
} | ## Contact Us
We really value feedback, especially from our users.
Please ask your question or report your bug with the
[Rubin Community forum](https://community.lsst.org/c/support/support-lasair/55)
under [Support > Lasair](https://community.lsst.org/c/support/support-lasair/55).
You will need to get an account ... | lsst-ukREPO_NAMElasair-lsstPATH_START.@lasair-lsst_extracted@lasair-lsst-main@docs@source@more_info@contact.md@.PATH_END.py |
{
"filename": "mcTestRegisterDeviceWithMultipleSerial.py",
"repo_name": "ACS-Community/ACS",
"repo_path": "ACS_extracted/ACS-master/LGPL/CommonSoftware/monitoring/moncollect/ws/test/mcTestRegisterDeviceWithMultipleSerial.py",
"type": "Python"
} | #!/usr/bin/env python
#*******************************************************************************
# ALMA - Atacama Large Millimiter Array
# (c) Associated Universities Inc., 2002
# (c) European Southern Observatory, 2002
# Copyright by ESO (in the framework of the ALMA collaboration)
# and Cosylab 2002, All right... | ACS-CommunityREPO_NAMEACSPATH_START.@ACS_extracted@ACS-master@LGPL@CommonSoftware@monitoring@moncollect@ws@test@mcTestRegisterDeviceWithMultipleSerial.py@.PATH_END.py |
{
"filename": "_size.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/parcats/tickfont/_size.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class SizeValidator(_plotly_utils.basevalidators.NumberValidator):
def __init__(self, plotly_name="size", parent_name="parcats.tickfont", **kwargs):
super(SizeValidator, 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@parcats@tickfont@_size.py@.PATH_END.py |
{
"filename": "_textfont.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/scattercarpet/_textfont.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class TextfontValidator(_plotly_utils.basevalidators.CompoundValidator):
def __init__(self, plotly_name="textfont", parent_name="scattercarpet", **kwargs):
super(TextfontValidator, 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@scattercarpet@_textfont.py@.PATH_END.py |
{
"filename": "README.md",
"repo_name": "davidpamos/MultiModes",
"repo_path": "MultiModes_extracted/MultiModes-main/README.md",
"type": "Markdown"
} | # MultiModes
- Author: David Pamos Ortega - PhD Student - University of Granada (UGR) -
- Thesis Directors: Dr. Juan Carlos Suárez Yanes - University of Granada (UGR) - and Dr. Antonio García Hernández - University of Granada (UGR) -
- Expert contributor: Dr. Javier Pascual Granado - Institute of Astrophysics of Andal... | davidpamosREPO_NAMEMultiModesPATH_START.@MultiModes_extracted@MultiModes-main@README.md@.PATH_END.py |
{
"filename": "gtest_xml_test_utils.py",
"repo_name": "hpc4cmb/toast",
"repo_path": "toast_extracted/toast-main/src/libtoast/gtest/googletest/test/gtest_xml_test_utils.py",
"type": "Python"
} | #!/usr/bin/env python
#
# Copyright 2006, Google Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list... | hpc4cmbREPO_NAMEtoastPATH_START.@toast_extracted@toast-main@src@libtoast@gtest@googletest@test@gtest_xml_test_utils.py@.PATH_END.py |
{
"filename": "test_ext_lomb_scargle.py",
"repo_name": "quatrope/feets",
"repo_path": "feets_extracted/feets-master/tests/extractors/test_ext_lomb_scargle.py",
"type": "Python"
} | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# The MIT License (MIT)
# Copyright (c) 2017 Juan Cabral
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including withou... | quatropeREPO_NAMEfeetsPATH_START.@feets_extracted@feets-master@tests@extractors@test_ext_lomb_scargle.py@.PATH_END.py |
{
"filename": "base_hmc.py",
"repo_name": "pymc-devs/pymc",
"repo_path": "pymc_extracted/pymc-main/pymc/step_methods/hmc/base_hmc.py",
"type": "Python"
} | # Copyright 2024 The PyMC Developers
#
# 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... | pymc-devsREPO_NAMEpymcPATH_START.@pymc_extracted@pymc-main@pymc@step_methods@hmc@base_hmc.py@.PATH_END.py |
{
"filename": "_bordercolor.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/violin/hoverlabel/_bordercolor.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator):
def __init__(
self, plotly_name="bordercolor", parent_name="violin.hoverlabel", **kwargs
):
super(BordercolorValidator, self).__init__(
plotly_name=plotly_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@violin@hoverlabel@_bordercolor.py@.PATH_END.py |
{
"filename": "_labelprefix.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/carpet/baxis/_labelprefix.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class LabelprefixValidator(_plotly_utils.basevalidators.StringValidator):
def __init__(self, plotly_name="labelprefix", parent_name="carpet.baxis", **kwargs):
super(LabelprefixValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@carpet@baxis@_labelprefix.py@.PATH_END.py |
{
"filename": "test_wcs.py",
"repo_name": "astropy/astropy",
"repo_path": "astropy_extracted/astropy-main/astropy/wcs/tests/test_wcs.py",
"type": "Python"
} | # Licensed under a 3-clause BSD style license - see LICENSE.rst
import io
import os
from contextlib import nullcontext
from datetime import datetime
import numpy as np
import pytest
from numpy.testing import (
assert_allclose,
assert_array_almost_equal,
assert_array_almost_equal_nulp,
assert_array_equ... | astropyREPO_NAMEastropyPATH_START.@astropy_extracted@astropy-main@astropy@wcs@tests@test_wcs.py@.PATH_END.py |
{
"filename": "example_9_occurrence_rate_inverse.py",
"repo_name": "GijsMulders/epos",
"repo_path": "epos_extracted/epos-master/EPOS/scriptdir/examples/example_9_occurrence_rate_inverse.py",
"type": "Python"
} | #! /usr/bin/env ipython
'''
Estimate plane occurrence rates using the inverse detection efficiency method
Plots should appear in the directory
png/example_9/occurrence/
Binned occurrence rates are saved in
json/example_9/
This example calculates the occurrence rates for different classes of planets,
defined by a ... | GijsMuldersREPO_NAMEeposPATH_START.@epos_extracted@epos-master@EPOS@scriptdir@examples@example_9_occurrence_rate_inverse.py@.PATH_END.py |
{
"filename": "dust-profiles.md",
"repo_name": "dmentipl/plonk",
"repo_path": "plonk_extracted/plonk-main/docs/source/user-guide/examples/dust-profiles.md",
"type": "Markdown"
} | # Dust profiles
Plot the surface density profile of each dust species.
```{note}
The data is from a Phantom simulation with multiple dust species using the
mixture (or "1-fluid") method with an embedded planet available from
[figshare](https://figshare.com/articles/dataset/Plonk_... | dmentiplREPO_NAMEplonkPATH_START.@plonk_extracted@plonk-main@docs@source@user-guide@examples@dust-profiles.md@.PATH_END.py |
{
"filename": "AIDA_Check_Settings.py",
"repo_name": "erikhom/aida",
"repo_path": "aida_extracted/aida-master/AIDA_Check_Settings.py",
"type": "Python"
} | ################################################################################
#
# File: AIDA_Check_Settings.py
#
# Summary: Function to check input values for AIDA settings loaded from
# 'AIDA_Settings.py', user specified settings file, or the
# command line
#
# Author: ... | erikhomREPO_NAMEaidaPATH_START.@aida_extracted@aida-master@AIDA_Check_Settings.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/barpolar/hoverlabel/font/__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@barpolar@hoverlabel@font@__init__.py@.PATH_END.py |
{
"filename": "loadVAE.ipynb",
"repo_name": "igomezv/simplemc_tests",
"repo_path": "simplemc_tests_extracted/simplemc_tests-main/simplemc/analyzers/neuralike/neural_models/crann_models/loadVAE.ipynb",
"type": "Jupyter Notebook"
} | ```python
import tensorflow as tf
from matplotlib import pyplot as plt
import numpy as np
%matplotlib inline
from tensorflow.keras.models import Model
import pandas as pd
from sklearn.preprocessing import StandardScaler, MinMaxScaler
from tensorflow.keras.optimizers import Adam
from tensorflow.keras.initializers import... | igomezvREPO_NAMEsimplemc_testsPATH_START.@simplemc_tests_extracted@simplemc_tests-main@simplemc@analyzers@neuralike@neural_models@crann_models@loadVAE.ipynb@.PATH_END.py |
{
"filename": "core.py",
"repo_name": "21cmfast/21CMMC",
"repo_path": "21CMMC_extracted/21CMMC-master/src/py21cmmc/core.py",
"type": "Python"
} | """Module providing Core Modules for cosmoHammer.
This is the basis of the plugin system for :mod:`py21cmmc`.
TODO: Add description of the API of cores (and how to define new ones).
"""
import copy
import inspect
import logging
import numpy as np
import py21cmfast as p21
import warnings
from os import path
from scipy... | 21cmfastREPO_NAME21CMMCPATH_START.@21CMMC_extracted@21CMMC-master@src@py21cmmc@core.py@.PATH_END.py |
{
"filename": "output.py",
"repo_name": "CobayaSampler/cobaya",
"repo_path": "cobaya_extracted/cobaya-master/cobaya/output.py",
"type": "Python"
} | """
.. module:: output
:Synopsis: Generic output class and output drivers
:Author: Jesus Torrado
"""
# Global
import os
import sys
import datetime
import re
import shutil
from typing import Optional, Any
from packaging import version
# Local
from cobaya.yaml import yaml_dump, yaml_load, yaml_load_file, \
OutputEr... | CobayaSamplerREPO_NAMEcobayaPATH_START.@cobaya_extracted@cobaya-master@cobaya@output.py@.PATH_END.py |
{
"filename": "__main__.py",
"repo_name": "grand-mother/grand",
"repo_path": "grand_extracted/grand-main/tests/tools/__main__.py",
"type": "Python"
} | """
Run all unit tests for the grand.geo package
"""
from .. import main
if __name__ == "__main__":
main()
| grand-motherREPO_NAMEgrandPATH_START.@grand_extracted@grand-main@tests@tools@__main__.py@.PATH_END.py |
{
"filename": "_metasrc.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/box/_metasrc.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator):
def __init__(self, plotly_name="metasrc", parent_name="box", **kwargs):
super(MetasrcValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
edit_... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@box@_metasrc.py@.PATH_END.py |
{
"filename": "_autocolorscale.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/streamtube/_autocolorscale.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class AutocolorscaleValidator(_plotly_utils.basevalidators.BooleanValidator):
def __init__(
self, plotly_name="autocolorscale", parent_name="streamtube", **kwargs
):
super(AutocolorscaleValidator, self).__init__(
plotly_name=plotly_name,
... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@streamtube@_autocolorscale.py@.PATH_END.py |
{
"filename": "lsstnutssampler.py",
"repo_name": "Harry45/DESEMU",
"repo_path": "DESEMU_extracted/DESEMU-main/lsstnutssampler.py",
"type": "Python"
} | import os
import random
import jax
import jaxlib
import jax_cosmo as jc
import numpyro
from datetime import datetime
import numpyro.distributions as dist
from numpyro.infer import MCMC, NUTS, init_to_median, init_to_value
from lsst.functions import get_params_vec, get_bandpowers_theory, load_data
from utils.helpers imp... | Harry45REPO_NAMEDESEMUPATH_START.@DESEMU_extracted@DESEMU-main@lsstnutssampler.py@.PATH_END.py |
{
"filename": "Hourglass-1d.py",
"repo_name": "LLNL/spheral",
"repo_path": "spheral_extracted/spheral-main/tests/functional/Hydro/Hourglass/Hourglass-1d.py",
"type": "Python"
} | #ATS:test(SELF, "--graphics False", label="Planar Hourglass test problem -- 1-D (serial)")
#-------------------------------------------------------------------------------
# A made up 1-D problem to test the anti-hourglassing algorithms.
#-------------------------------------------------------------------------------
f... | LLNLREPO_NAMEspheralPATH_START.@spheral_extracted@spheral-main@tests@functional@Hydro@Hourglass@Hourglass-1d.py@.PATH_END.py |
{
"filename": "adstex.py",
"repo_name": "yymao/adstex",
"repo_path": "adstex_extracted/adstex-main/adstex.py",
"type": "Python"
} | """
adstex: Automated generation of NASA ADS bibtex entries
from citation keys (identifiers, author+year) in your TeX source files.
Project website: https://github.com/yymao/adstex
The MIT License (MIT)
Copyright (c) 2015-2024 Yao-Yuan Mao (yymao)
http://opensource.org/licenses/MIT
"""
from __future__ import absolute... | yymaoREPO_NAMEadstexPATH_START.@adstex_extracted@adstex-main@adstex.py@.PATH_END.py |
{
"filename": "_bordercolor.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/funnel/marker/colorbar/_bordercolor.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class BordercolorValidator(_plotly_utils.basevalidators.ColorValidator):
def __init__(
self, plotly_name="bordercolor", parent_name="funnel.marker.colorbar", **kwargs
):
super(BordercolorValidator, self).__init__(
plotly_name=plotly_name,
... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@funnel@marker@colorbar@_bordercolor.py@.PATH_END.py |
{
"filename": "enumerate-api.py",
"repo_name": "statsmodels/statsmodels",
"repo_path": "statsmodels_extracted/statsmodels-main/tools/releasing/enumerate-api.py",
"type": "Python"
} | """
This tool is used in generating meaningful release notes.
This tool simplifies reading the current statsmodels API to a JSON file. It
can also be used against any installed statsmodels package to read the API.
The typical use would be
source venv/legacy-statsmodels/activate
python enumerate-api.py -of statsmodels... | statsmodelsREPO_NAMEstatsmodelsPATH_START.@statsmodels_extracted@statsmodels-main@tools@releasing@enumerate-api.py@.PATH_END.py |
{
"filename": "contrast.py",
"repo_name": "rodluger/planetplanet",
"repo_path": "planetplanet_extracted/planetplanet-master/scripts/contrast.py",
"type": "Python"
} | #!/usr/bin/env python
# -*- coding: utf-8 -*-
'''
contrast.py |github|
--------------------
Plots an occultation event in two different limits: the airless limit
and the thick atmosphere limit. The asymmetry of the light curve in the
former case betrays a strong day/night temperature contrast on the occulted
planet.
... | rodlugerREPO_NAMEplanetplanetPATH_START.@planetplanet_extracted@planetplanet-master@scripts@contrast.py@.PATH_END.py |
{
"filename": "lextab.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/pycparser/py3/pycparser/lextab.py",
"type": "Python"
} | # lextab.py. This file automatically created by PLY (version 3.10). Don't edit!
_tabversion = '3.10'
_lextokens = set(('AND', 'ANDEQUAL', 'ARROW', 'AUTO', 'BREAK', 'CASE', 'CHAR', 'CHAR_CONST', 'COLON', 'COMMA', 'CONDOP', 'CONST', 'CONTINUE', 'DEFAULT', 'DIVEQUAL', 'DIVIDE', 'DO', 'DOUBLE', 'ELLIPSIS', 'ELSE', 'EN... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@pycparser@py3@pycparser@lextab.py@.PATH_END.py |
{
"filename": "test_fcompiler_intel.py",
"repo_name": "waynebhayes/SpArcFiRe",
"repo_path": "SpArcFiRe_extracted/SpArcFiRe-master/scripts/SpArcFiRe-pyvenv/lib/python2.7/site-packages/numpy/distutils/tests/test_fcompiler_intel.py",
"type": "Python"
} | from __future__ import division, absolute_import, print_function
import numpy.distutils.fcompiler
from numpy.testing import run_module_suite, assert_
intel_32bit_version_strings = [
("Intel(R) Fortran Intel(R) 32-bit Compiler Professional for applications"
"running on Intel(R) 32, Version 11.1", '11.1'),
]
... | waynebhayesREPO_NAMESpArcFiRePATH_START.@SpArcFiRe_extracted@SpArcFiRe-master@scripts@SpArcFiRe-pyvenv@lib@python2.7@site-packages@numpy@distutils@tests@test_fcompiler_intel.py@.PATH_END.py |
{
"filename": "_griddash.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/carpet/baxis/_griddash.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class GriddashValidator(_plotly_utils.basevalidators.DashValidator):
def __init__(self, plotly_name="griddash", parent_name="carpet.baxis", **kwargs):
super(GriddashValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@carpet@baxis@_griddash.py@.PATH_END.py |
{
"filename": "coordinate_handler.py",
"repo_name": "yt-project/yt",
"repo_path": "yt_extracted/yt-main/yt/geometry/coordinates/coordinate_handler.py",
"type": "Python"
} | import abc
import weakref
from functools import cached_property
from numbers import Number
from typing import Any, Literal, overload
import numpy as np
from yt._typing import AxisOrder
from yt.funcs import fix_unitary, is_sequence, parse_center_array, validate_width_tuple
from yt.units.yt_array import YTArray, YTQuan... | yt-projectREPO_NAMEytPATH_START.@yt_extracted@yt-main@yt@geometry@coordinates@coordinate_handler.py@.PATH_END.py |
{
"filename": "iuwt_toolbox.py",
"repo_name": "ratt-ru/PyMORESANE",
"repo_path": "PyMORESANE_extracted/PyMORESANE-master/pymoresane/iuwt_toolbox.py",
"type": "Python"
} | import numpy as np
from scipy import ndimage
import traceback
try:
import pycuda.driver as drv
import pycuda.tools
import pycuda.autoinit
import pycuda.gpuarray as gpuarray
from pycuda.compiler import SourceModule
except:
traceback.print_exc()
print "Pycuda unavailable - GPU mode will fail.... | ratt-ruREPO_NAMEPyMORESANEPATH_START.@PyMORESANE_extracted@PyMORESANE-master@pymoresane@iuwt_toolbox.py@.PATH_END.py |
{
"filename": "CurviBoundaryConditions.py",
"repo_name": "zachetienne/nrpytutorial",
"repo_path": "nrpytutorial_extracted/nrpytutorial-master/Deprecated/CurviBoundaryConditions/CurviBoundaryConditions.py",
"type": "Python"
} | # This module provides functions for setting up Curvilinear boundary conditions,
# as documented in Tutorial-Start_to_Finish-Curvilinear_BCs.ipynb
# Authors: Zachariah B. Etienne
# zachetie **at** gmail **dot* com
# Terrence Pierre Jacques
# First we import needed core NRPy+ modules
from outputC ... | zachetienneREPO_NAMEnrpytutorialPATH_START.@nrpytutorial_extracted@nrpytutorial-master@Deprecated@CurviBoundaryConditions@CurviBoundaryConditions.py@.PATH_END.py |
{
"filename": "multi_client_test.py",
"repo_name": "tensorflow/tensorflow",
"repo_path": "tensorflow_extracted/tensorflow-master/tensorflow/dtensor/python/tests/multi_client_test.py",
"type": "Python"
} | # Copyright 2023 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@dtensor@python@tests@multi_client_test.py@.PATH_END.py |
{
"filename": "sort_lines.py",
"repo_name": "Morisset/PyNeb_devel",
"repo_path": "PyNeb_devel_extracted/PyNeb_devel-master/pyneb/sample_scripts/sort_lines.py",
"type": "Python"
} | # Sort lines of an observational dataset in alphabetical order
import pyneb as pn
# Read data
obs_data = 'pne.dat'
obs = pn.Observation(obs_data, fileFormat='lines_in_rows', corrected=True)
out_file=open('out.dat', 'w')
# getSortedLines returns lines in sorted order
for line in obs.getSortedLines():
row = li... | MorissetREPO_NAMEPyNeb_develPATH_START.@PyNeb_devel_extracted@PyNeb_devel-master@pyneb@sample_scripts@sort_lines.py@.PATH_END.py |
{
"filename": "plot_release_highlights_1_6_0.py",
"repo_name": "scikit-learn/scikit-learn",
"repo_path": "scikit-learn_extracted/scikit-learn-main/examples/release_highlights/plot_release_highlights_1_6_0.py",
"type": "Python"
} | # ruff: noqa
"""
=======================================
Release Highlights for scikit-learn 1.6
=======================================
.. currentmodule:: sklearn
We are pleased to announce the release of scikit-learn 1.6! Many bug fixes
and improvements were added, as well as some key new features. Below we
detail ... | scikit-learnREPO_NAMEscikit-learnPATH_START.@scikit-learn_extracted@scikit-learn-main@examples@release_highlights@plot_release_highlights_1_6_0.py@.PATH_END.py |
{
"filename": "_range.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/layout/angularaxis/_range.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class RangeValidator(_plotly_utils.basevalidators.InfoArrayValidator):
def __init__(self, plotly_name="range", parent_name="layout.angularaxis", **kwargs):
super(RangeValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@layout@angularaxis@_range.py@.PATH_END.py |
{
"filename": "processors.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/prompt-toolkit/py2/prompt_toolkit/layout/processors.py",
"type": "Python"
} | """
Processors are little transformation blocks that transform the token list from
a buffer before the BufferControl will render it to the screen.
They can insert tokens before or after, or highlight fragments by replacing the
token types.
"""
from __future__ import unicode_literals
from abc import ABCMeta, abstractme... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@prompt-toolkit@py2@prompt_toolkit@layout@processors.py@.PATH_END.py |
{
"filename": "README.md",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/comm/README.md",
"type": "Markdown"
} | # Comm
It provides a way to register a Kernel Comm implementation, as per the Jupyter kernel protocol.
It also provides a base Comm implementation and a default CommManager that can be used.
## Register a comm implementation in the kernel:
### Case 1: Using the default CommManager and the BaseComm implementations
W... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@comm@README.md@.PATH_END.py |
{
"filename": "rrg_to_lenstool-checkpoint.py",
"repo_name": "davidharvey1986/pyRRG",
"repo_path": "pyRRG_extracted/pyRRG-master/src/.ipynb_checkpoints/rrg_to_lenstool-checkpoint.py",
"type": "Python"
} | '''
This script will take the output from rrg and convert
the shears in the format required to be used in lenstool
(using option 7, and the format a, b, theta)
'''
from astropy.io import fits
import os as os
#import mask_catalogue as mask_catalogue
import numpy as np
def rrg_to_lenstool( rrg_catalogue,
... | davidharvey1986REPO_NAMEpyRRGPATH_START.@pyRRG_extracted@pyRRG-master@src@.ipynb_checkpoints@rrg_to_lenstool-checkpoint.py@.PATH_END.py |
{
"filename": "googledrive.py",
"repo_name": "langchain-ai/langchain",
"repo_path": "langchain_extracted/langchain-master/libs/community/langchain_community/document_loaders/googledrive.py",
"type": "Python"
} | # Prerequisites:
# 1. Create a Google Cloud project
# 2. Enable the Google Drive API:
# https://console.cloud.google.com/flows/enableapi?apiid=drive.googleapis.com
# 3. Authorize credentials for desktop app:
# https://developers.google.com/drive/api/quickstart/python#authorize_credentials_for_a_desktop_application ... | langchain-aiREPO_NAMElangchainPATH_START.@langchain_extracted@langchain-master@libs@community@langchain_community@document_loaders@googledrive.py@.PATH_END.py |
{
"filename": "PSDs_README.md",
"repo_name": "CosmoStatGW/gwfast",
"repo_path": "gwfast_extracted/gwfast-master/psds/PSDs_README.md",
"type": "Markdown"
} | # gwfast/psds
We here list the sources of the available Power Spectral Densities, PSDs, or Amplitude Spectral Densities, ASDs available in GWFast, in alphabetical order
### ce\_strain/
Cosmic Explorer ASDs from [*Science-Driven Tunable Design of Cosmic Explorer Detectors*](https://arxiv.org/abs/2201.10668), available... | CosmoStatGWREPO_NAMEgwfastPATH_START.@gwfast_extracted@gwfast-master@psds@PSDs_README.md@.PATH_END.py |
{
"filename": "multiclass.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/scikit-learn/py2/sklearn/multiclass.py",
"type": "Python"
} | """
Multiclass and multilabel classification strategies
===================================================
This module implements multiclass learning algorithms:
- one-vs-the-rest / one-vs-all
- one-vs-one
- error correcting output codes
The estimators provided in this module are meta-estimators: they re... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@scikit-learn@py2@sklearn@multiclass.py@.PATH_END.py |
{
"filename": "test_financial_expired.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/numpy/py3/numpy/lib/tests/test_financial_expired.py",
"type": "Python"
} | import sys
import pytest
import numpy as np
def test_financial_expired():
match = 'NEP 32'
with pytest.warns(DeprecationWarning, match=match):
func = np.fv
with pytest.raises(RuntimeError, match=match):
func(1, 2, 3)
| catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@numpy@py3@numpy@lib@tests@test_financial_expired.py@.PATH_END.py |
{
"filename": "_sizesrc.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/funnel/hoverlabel/font/_sizesrc.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class SizesrcValidator(_plotly_utils.basevalidators.SrcValidator):
def __init__(
self, plotly_name="sizesrc", parent_name="funnel.hoverlabel.font", **kwargs
):
super(SizesrcValidator, self).__init__(
plotly_name=plotly_name,
parent_na... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@funnel@hoverlabel@font@_sizesrc.py@.PATH_END.py |
{
"filename": "_sgs.py",
"repo_name": "sfarrens/sfof",
"repo_path": "sfof_extracted/sfof-master/sfof/python/euclid/dm/_sgs.py",
"type": "Python"
} | # /home/sartor/pymodule/euclid/dm/_sgs.py
# -*- coding: utf-8 -*-
# PyXB bindings for NM:77d3da8c9c0b8eec64b9957d9ec227ca99caec32
# Generated 2014-07-24 16:26:39.933073 by PyXB version 1.2.3
# Namespace http://euclid.esa.org/schema/sys/sgs [xmlns:sgs]
import pyxb
import pyxb.binding
import pyxb.binding.saxer
import io... | sfarrensREPO_NAMEsfofPATH_START.@sfof_extracted@sfof-master@sfof@python@euclid@dm@_sgs.py@.PATH_END.py |
{
"filename": "test_zeus_mock_avg.py",
"repo_name": "Samreay/Barry",
"repo_path": "Barry_extracted/Barry-master/config/examples/test_zeus_mock_avg.py",
"type": "Python"
} | import sys
sys.path.append("..")
sys.path.append("../..")
from barry.config import setup
from barry.fitter import Fitter
from barry.models.bao_power_Beutler2017 import PowerBeutler2017
from barry.datasets.dataset_power_spectrum import PowerSpectrum_SDSS_DR12
from barry.utils import plot_bestfit
from barry.samplers imp... | SamreayREPO_NAMEBarryPATH_START.@Barry_extracted@Barry-master@config@examples@test_zeus_mock_avg.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "supernnova/SuperNNova",
"repo_path": "SuperNNova_extracted/SuperNNova-main/python/supernnova/visualization/__init__.py",
"type": "Python"
} | supernnovaREPO_NAMESuperNNovaPATH_START.@SuperNNova_extracted@SuperNNova-main@python@supernnova@visualization@__init__.py@.PATH_END.py | |
{
"filename": "format_read.py",
"repo_name": "ellawang44/Breidablik",
"repo_path": "Breidablik_extracted/Breidablik-master/breidablik/analysis/format_read.py",
"type": "Python"
} | from breidablik.analysis import tools
import numpy as np
def pixel_format(data, wavelength, center = 670.9659, lower = 0.4, upper = 0.4, ftype = 'flux'):
"""Changes the data from read into a machine learning format. This function is for machine learning over pixels.
Parameters
----------
data : dict
... | ellawang44REPO_NAMEBreidablikPATH_START.@Breidablik_extracted@Breidablik-master@breidablik@analysis@format_read.py@.PATH_END.py |
{
"filename": "test_quickspectra.py",
"repo_name": "desihub/desisim",
"repo_path": "desisim_extracted/desisim-main/py/desisim/test/test_quickspectra.py",
"type": "Python"
} | import unittest, os, shutil, tempfile, subprocess
import numpy as np
from desisim.scripts import quickspectra
import desispec.io
from astropy.io import fits
class TestQuickSpectra(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.origdir = os.getcwd()
cls.testdir = tempfile.mkdtemp()
... | desihubREPO_NAMEdesisimPATH_START.@desisim_extracted@desisim-main@py@desisim@test@test_quickspectra.py@.PATH_END.py |
{
"filename": "test_plot_clumping_factor_Chary.py",
"repo_name": "roban/CosmoloPy",
"repo_path": "CosmoloPy_extracted/CosmoloPy-master/tests/test_plot_clumping_factor_Chary.py",
"type": "Python"
} |
from __future__ import absolute_import, division, print_function
import sys
import numpy
import pylab
import cosmolopy.reionization as cr
def plot_clumping_factor_Chary():
"""Plot clumping factor from Chary paper.
"""
z = numpy.linspace(5,15,500)
cf = cr.clumping_factor_Chary(z)
pylab.plot(z,c... | robanREPO_NAMECosmoloPyPATH_START.@CosmoloPy_extracted@CosmoloPy-master@tests@test_plot_clumping_factor_Chary.py@.PATH_END.py |
{
"filename": "mutable_array_test.py",
"repo_name": "jax-ml/jax",
"repo_path": "jax_extracted/jax-main/tests/mutable_array_test.py",
"type": "Python"
} | # Copyright 2024 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@mutable_array_test.py@.PATH_END.py |
{
"filename": "_tick0.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/histogram/marker/colorbar/_tick0.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class Tick0Validator(_plotly_utils.basevalidators.AnyValidator):
def __init__(
self, plotly_name="tick0", parent_name="histogram.marker.colorbar", **kwargs
):
super(Tick0Validator, self).__init__(
plotly_name=plotly_name,
parent_name=... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@histogram@marker@colorbar@_tick0.py@.PATH_END.py |
{
"filename": "split_by_token.ipynb",
"repo_name": "langchain-ai/langchain",
"repo_path": "langchain_extracted/langchain-master/docs/docs/how_to/split_by_token.ipynb",
"type": "Jupyter Notebook"
} | # How to split text by tokens
Language models have a [token](/docs/concepts/tokens/) limit. You should not exceed the token limit. When you [split your text](/docs/concepts/text_splitters/) into chunks it is therefore a good idea to count the number of tokens. There are many tokenizers. When you count tokens in your ... | langchain-aiREPO_NAMElangchainPATH_START.@langchain_extracted@langchain-master@docs@docs@how_to@split_by_token.ipynb@.PATH_END.py |
{
"filename": "radiative_functions.py",
"repo_name": "joshuakt/Oxygen-False-Positives",
"repo_path": "Oxygen-False-Positives_extracted/Oxygen-False-Positives-main/radiative_functions.py",
"type": "Python"
} | ##################################
import numpy as np
import pylab
from scipy.integrate import *
from scipy.interpolate import interp1d
from scipy import optimize
import scipy.interpolate
from numba import jit
#################################
### H2O and CO2 ranges for OLR grid
P_H2O_grid_new = np.logspace(1,9,34)
P... | joshuaktREPO_NAMEOxygen-False-PositivesPATH_START.@Oxygen-False-Positives_extracted@Oxygen-False-Positives-main@radiative_functions.py@.PATH_END.py |
{
"filename": "test_mag_likelihood.py",
"repo_name": "sibirrer/hierArc",
"repo_path": "hierArc_extracted/hierArc-main/test/test_Likelihood/test_LensLikelihood/test_mag_likelihood.py",
"type": "Python"
} | import pytest
import numpy as np
import numpy.testing as npt
from hierarc.Likelihood.LensLikelihood.mag_likelihood import MagnificationLikelihood
from lenstronomy.Util.data_util import magnitude2cps
class TestMagnificationLikelihood(object):
def setup_method(self):
pass
def test_log_likelihood(self):... | sibirrerREPO_NAMEhierArcPATH_START.@hierArc_extracted@hierArc-main@test@test_Likelihood@test_LensLikelihood@test_mag_likelihood.py@.PATH_END.py |
{
"filename": "_b.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/scattercarpet/_b.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class BValidator(_plotly_utils.basevalidators.DataArrayValidator):
def __init__(self, plotly_name="b", parent_name="scattercarpet", **kwargs):
super(BValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
edit_ty... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@scattercarpet@_b.py@.PATH_END.py |
{
"filename": "test_gammainc.py",
"repo_name": "waynebhayes/SpArcFiRe",
"repo_path": "SpArcFiRe_extracted/SpArcFiRe-master/scripts/SpArcFiRe-pyvenv/lib/python2.7/site-packages/scipy/special/tests/test_gammainc.py",
"type": "Python"
} | from __future__ import division, print_function, absolute_import
import numpy as np
from scipy.special import gammainc
from scipy.special._testutils import FuncData
def test_line():
# Test on the line a = x where a simpler asymptotic expansion
# (analog of DLMF 8.12.15) is available.
def gammainc_line(x)... | waynebhayesREPO_NAMESpArcFiRePATH_START.@SpArcFiRe_extracted@SpArcFiRe-master@scripts@SpArcFiRe-pyvenv@lib@python2.7@site-packages@scipy@special@tests@test_gammainc.py@.PATH_END.py |
{
"filename": "QuadraticInterpolator.py",
"repo_name": "LLNL/spheral",
"repo_path": "spheral_extracted/spheral-main/src/PYB11/Utilities/QuadraticInterpolator.py",
"type": "Python"
} | #-------------------------------------------------------------------------------
# QuadraticInterpolator
#-------------------------------------------------------------------------------
from PYB11Generator import *
class QuadraticInterpolator:
"""Encapsulates the algorithm and data for parabolic interpolation in ... | LLNLREPO_NAMEspheralPATH_START.@spheral_extracted@spheral-main@src@PYB11@Utilities@QuadraticInterpolator.py@.PATH_END.py |
{
"filename": "_variant.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/histogram2dcontour/contours/labelfont/_variant.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class VariantValidator(_plotly_utils.basevalidators.EnumeratedValidator):
def __init__(
self,
plotly_name="variant",
parent_name="histogram2dcontour.contours.labelfont",
**kwargs,
):
super(VariantValidator, self).__init__(
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@histogram2dcontour@contours@labelfont@_variant.py@.PATH_END.py |
{
"filename": "_style.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/sunburst/textfont/_style.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class StyleValidator(_plotly_utils.basevalidators.EnumeratedValidator):
def __init__(self, plotly_name="style", parent_name="sunburst.textfont", **kwargs):
super(StyleValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@sunburst@textfont@_style.py@.PATH_END.py |
{
"filename": "aggregate_results.py",
"repo_name": "victoria-tiki/transformer_complex",
"repo_path": "transformer_complex_extracted/transformer_complex-main/inference/aggregate_results.py",
"type": "Python"
} | import os
import numpy as np
import h5py
def aggregate_results(output_dir, world_size):
aggregated_hdf5_path = os.path.join(output_dir, 'aggregated_results_model_separate_ff_separate_conv_resume2_160_80_10_epoch=10.h5')
# creat h5 file to store results
with h5py.File(aggregated_hdf5_path, 'w') as agg_h5f... | victoria-tikiREPO_NAMEtransformer_complexPATH_START.@transformer_complex_extracted@transformer_complex-main@inference@aggregate_results.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "amusecode/amuse",
"repo_path": "amuse_extracted/amuse-main/src/amuse/community/fractalcluster/__init__.py",
"type": "Python"
} | from .interface import Fractalcluster
| amusecodeREPO_NAMEamusePATH_START.@amuse_extracted@amuse-main@src@amuse@community@fractalcluster@__init__.py@.PATH_END.py |
{
"filename": "non_maxwellianity.py",
"repo_name": "fmihpc/analysator",
"repo_path": "analysator_extracted/analysator-master/pyCalculations/non_maxwellianity.py",
"type": "Python"
} | import numpy as np
from scipy.constants import k, m_e, m_p
import pytools as pt
import warnings
import logging
import random
def epsilon_M(f,cell,pop="proton",m=m_p, bulk=None, B=None,
model="bimaxwellian",
normorder=1, norm=2, threshold=0,
dummy=None):
''' Calcula... | fmihpcREPO_NAMEanalysatorPATH_START.@analysator_extracted@analysator-master@pyCalculations@non_maxwellianity.py@.PATH_END.py |
{
"filename": "double_source_plane.ipynb",
"repo_name": "sibirrer/hierArc",
"repo_path": "hierArc_extracted/hierArc-main/notebooks/double_source_plane.ipynb",
"type": "Jupyter Notebook"
} | # Double source plane cosmology forecast
```python
# import standard python modules
import numpy as np
import corner
import copy
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
%matplotlib inline
# import lenstronomy and hierArc modules
from lenstronomy.Cosmo.lens_cosmo import LensCosmo
from h... | sibirrerREPO_NAMEhierArcPATH_START.@hierArc_extracted@hierArc-main@notebooks@double_source_plane.ipynb@.PATH_END.py |
{
"filename": "camvid_segmentation_multiclass.ipynb",
"repo_name": "qubvel/segmentation_models.pytorch",
"repo_path": "segmentation_models.pytorch_extracted/segmentation_models.pytorch-main/examples/camvid_segmentation_multiclass.ipynb",
"type": "Jupyter Notebook"
} | [](https://colab.research.google.com/github/qubvel/segmentation_models.pytorch/blob/main/examples/camvid_segmentation_multiclass.ipynb)
# Install package
```python
%%capture
%pip install --upgrade segmentation-models-pytorch lightning albument... | qubvelREPO_NAMEsegmentation_models.pytorchPATH_START.@segmentation_models.pytorch_extracted@segmentation_models.pytorch-main@examples@camvid_segmentation_multiclass.ipynb@.PATH_END.py |
{
"filename": "_idssrc.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/heatmapgl/_idssrc.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator):
def __init__(self, plotly_name="idssrc", parent_name="heatmapgl", **kwargs):
super(IdssrcValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
ed... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@heatmapgl@_idssrc.py@.PATH_END.py |
{
"filename": "generatePlots.py",
"repo_name": "claudiok/clsim",
"repo_path": "clsim_extracted/clsim-master/resources/scripts/compareToPPCredux/generatePlots.py",
"type": "Python"
} | #!/usr/bin/env python
from __future__ import print_function
import matplotlib
matplotlib.use("PDF")
from optparse import OptionParser
usage = "usage: %prog [options] inputfile"
parser = OptionParser(usage)
import os
options,args = parser.parse_args()
if len(args) != 0:
parser.error("wrong number of options")
... | claudiokREPO_NAMEclsimPATH_START.@clsim_extracted@clsim-master@resources@scripts@compareToPPCredux@generatePlots.py@.PATH_END.py |
{
"filename": "_tickvals.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/parcats/line/colorbar/_tickvals.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class TickvalsValidator(_plotly_utils.basevalidators.DataArrayValidator):
def __init__(
self, plotly_name="tickvals", parent_name="parcats.line.colorbar", **kwargs
):
super(TickvalsValidator, self).__init__(
plotly_name=plotly_name,
p... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@parcats@line@colorbar@_tickvals.py@.PATH_END.py |
{
"filename": "README.md",
"repo_name": "nuclear-multimessenger-astronomy/nmma",
"repo_path": "nmma_extracted/nmma-main/tutorials/README.md",
"type": "Markdown"
} | nuclear-multimessenger-astronomyREPO_NAMEnmmaPATH_START.@nmma_extracted@nmma-main@tutorials@README.md@.PATH_END.py | |
{
"filename": "base.py",
"repo_name": "langchain-ai/langchain",
"repo_path": "langchain_extracted/langchain-master/libs/langchain/langchain/vectorstores/redis/base.py",
"type": "Python"
} | from typing import TYPE_CHECKING, Any
from langchain._api import create_importer
if TYPE_CHECKING:
from langchain_community.vectorstores import Redis
from langchain_community.vectorstores.redis.base import (
RedisVectorStoreRetriever,
check_index_exists,
)
# Create a way to dynamically lo... | langchain-aiREPO_NAMElangchainPATH_START.@langchain_extracted@langchain-master@libs@langchain@langchain@vectorstores@redis@base.py@.PATH_END.py |
{
"filename": "noise.py",
"repo_name": "ACCarnall/bagpipes",
"repo_path": "bagpipes_extracted/bagpipes-master/bagpipes/fitting/noise.py",
"type": "Python"
} | import numpy as np
try:
import george
from george import kernels
except ImportError:
pass
class noise_model(object):
""" A class for modelling the noise properties of spectroscopic
data, including correlated noise.
Parameters
----------
noise_dict : dictionary
Contains the ... | ACCarnallREPO_NAMEbagpipesPATH_START.@bagpipes_extracted@bagpipes-master@bagpipes@fitting@noise.py@.PATH_END.py |
{
"filename": "reference_metric.py",
"repo_name": "zachetienne/nrpytutorial",
"repo_path": "nrpytutorial_extracted/nrpytutorial-master/reference_metric.py",
"type": "Python"
} | # reference_metric.py: Define all needed quantities
# for a reference metric.
# Given uniform (reference metric) coordinate
# (xx[0],xx[1],xx[2]), you must define:
# 1) xxmin[3],xxmax[3]: Valid ranges for each
# uniform coordinate xx0,xx1,xx2
# 2) xxSph[3]: Spherical coordinate (r,theta,phi),
# ... | zachetienneREPO_NAMEnrpytutorialPATH_START.@nrpytutorial_extracted@nrpytutorial-master@reference_metric.py@.PATH_END.py |
{
"filename": "_size.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/icicle/insidetextfont/_size.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class SizeValidator(_plotly_utils.basevalidators.NumberValidator):
def __init__(
self, plotly_name="size", parent_name="icicle.insidetextfont", **kwargs
):
super(SizeValidator, self).__init__(
plotly_name=plotly_name,
parent_name=pare... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@icicle@insidetextfont@_size.py@.PATH_END.py |
{
"filename": "test_model_intensity.py",
"repo_name": "lucabaldini/ixpeobssim",
"repo_path": "ixpeobssim_extracted/ixpeobssim-main/tests/test_model_intensity.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_model_intensity.py@.PATH_END.py |
{
"filename": "plot_mock_data.py",
"repo_name": "LSSTDESC/NaMaster",
"repo_path": "NaMaster_extracted/NaMaster-master/sandbox_validation/data/plot_mock_data.py",
"type": "Python"
} | from __future__ import print_function
from optparse import OptionParser
import numpy as np
import healpy as hp
import matplotlib.pyplot as plt
import flatmaps as fm
import os
from matplotlib import rc
import matplotlib
rc('font',**{'family':'sans-serif','sans-serif':['Helvetica']})
rc('text', usetex=True)
def opt_call... | LSSTDESCREPO_NAMENaMasterPATH_START.@NaMaster_extracted@NaMaster-master@sandbox_validation@data@plot_mock_data.py@.PATH_END.py |
{
"filename": "plot_ci_vs_fwhm.py",
"repo_name": "spacetelescope/drizzlepac",
"repo_path": "drizzlepac_extracted/drizzlepac-main/drizzlepac/devutils/plot_ci_vs_fwhm.py",
"type": "Python"
} | #!/usr/bin/env python
import argparse
import pdb
from astropy.stats import sigma_clipped_stats
from astropy.table import Table, vstack
import matplotlib.pyplot as plt
import numpy as np
from drizzlepac.devutils.comparison_tools import compare_sourcelists
from drizzlepac.haputils.diagnostic_utils import read_json_file... | spacetelescopeREPO_NAMEdrizzlepacPATH_START.@drizzlepac_extracted@drizzlepac-main@drizzlepac@devutils@plot_ci_vs_fwhm.py@.PATH_END.py |
{
"filename": "sim_image.py",
"repo_name": "astrostat/LIRA",
"repo_path": "LIRA_extracted/LIRA-master/lira/python/test/sim_image.py",
"type": "Python"
} | # sim_image - function to make simulated null 2D images, based on the
# assumed model - gauss + constant
#
# It requires CIAO4.5/ciao_contrib script package and Sherpa
#
# INPUT: indirs directories with the data files (could be more than one)
# infile - image file
# psffile - corresponding psf file
# ... | astrostatREPO_NAMELIRAPATH_START.@LIRA_extracted@LIRA-master@lira@python@test@sim_image.py@.PATH_END.py |
{
"filename": "sort_ops_test.py",
"repo_name": "tensorflow/tensorflow",
"repo_path": "tensorflow_extracted/tensorflow-master/tensorflow/python/ops/sort_ops_test.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@ops@sort_ops_test.py@.PATH_END.py |
{
"filename": "plot_video_api.py",
"repo_name": "pytorch/vision",
"repo_path": "vision_extracted/vision-main/gallery/others/plot_video_api.py",
"type": "Python"
} | """
=========
Video API
=========
.. note::
Try on `Colab <https://colab.research.google.com/github/pytorch/vision/blob/gh-pages/main/_generated_ipynb_notebooks/plot_video_api.ipynb>`_
or :ref:`go to the end <sphx_glr_download_auto_examples_others_plot_video_api.py>` to download the full example code.
This ex... | pytorchREPO_NAMEvisionPATH_START.@vision_extracted@vision-main@gallery@others@plot_video_api.py@.PATH_END.py |
{
"filename": "_showticksuffix.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/sunburst/marker/colorbar/_showticksuffix.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class ShowticksuffixValidator(_plotly_utils.basevalidators.EnumeratedValidator):
def __init__(
self,
plotly_name="showticksuffix",
parent_name="sunburst.marker.colorbar",
**kwargs,
):
super(ShowticksuffixValidator, self).__init__(
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@sunburst@marker@colorbar@_showticksuffix.py@.PATH_END.py |
{
"filename": "results_teffects.py",
"repo_name": "statsmodels/statsmodels",
"repo_path": "statsmodels_extracted/statsmodels-main/statsmodels/treatment/tests/results/results_teffects.py",
"type": "Python"
} | # flake8: noqa
# file is mostly autogenerated
import numpy as np
class Bunch(dict):
def __init__(self, **kw):
dict.__init__(self, kw)
self.__dict__ = self
table = np.array([
-239.63921146434, 23.82402100183, -10.058722305774, 8.408247034e-24,
-286.33343459485, -192.94498833383, np.na... | statsmodelsREPO_NAMEstatsmodelsPATH_START.@statsmodels_extracted@statsmodels-main@statsmodels@treatment@tests@results@results_teffects.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/cone/hoverlabel/font/__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... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@cone@hoverlabel@font@__init__.py@.PATH_END.py |
{
"filename": "README.md",
"repo_name": "mkplummer/Imber",
"repo_path": "Imber_extracted/Imber-main/README.md",
"type": "Markdown"
} | # Imber
Doppler imaging and light curve inverstion tool created by [Michael K. Plummer](https://www.michaelplummer.dev) for modeling stellar/substellar surfaces. The Python module simulates spectroscopic and photometric observations with both a gridded, numerical simulation and analytical model. Imber has been specific... | mkplummerREPO_NAMEImberPATH_START.@Imber_extracted@Imber-main@README.md@.PATH_END.py |
{
"filename": "test_convolve_kernels.py",
"repo_name": "astropy/astropy",
"repo_path": "astropy_extracted/astropy-main/astropy/convolution/tests/test_convolve_kernels.py",
"type": "Python"
} | # Licensed under a 3-clause BSD style license - see LICENSE.rst
import itertools
import numpy as np
import pytest
from numpy.testing import assert_allclose, assert_almost_equal
from astropy import units as u
from astropy.convolution.convolve import convolve, convolve_fft
from astropy.convolution.kernels import (
... | astropyREPO_NAMEastropyPATH_START.@astropy_extracted@astropy-main@astropy@convolution@tests@test_convolve_kernels.py@.PATH_END.py |
{
"filename": "gather_test.py",
"repo_name": "tensorflow/tensorflow",
"repo_path": "tensorflow_extracted/tensorflow-master/tensorflow/compiler/tests/gather_test.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@compiler@tests@gather_test.py@.PATH_END.py |
{
"filename": "_lineposition.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/layout/legend/title/font/_lineposition.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class LinepositionValidator(_plotly_utils.basevalidators.FlaglistValidator):
def __init__(
self,
plotly_name="lineposition",
parent_name="layout.legend.title.font",
**kwargs,
):
super(LinepositionValidator, self).__init__(
... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@layout@legend@title@font@_lineposition.py@.PATH_END.py |
{
"filename": "test_imgproc.py",
"repo_name": "itseez/opencv",
"repo_path": "opencv_extracted/opencv-master/modules/imgproc/misc/python/test/test_imgproc.py",
"type": "Python"
} | #!/usr/bin/env python
from __future__ import print_function
import numpy as np
import cv2 as cv
from tests_common import NewOpenCVTests
class Imgproc_Tests(NewOpenCVTests):
def test_python_986(self):
cntls = []
img = np.zeros((100,100,3), dtype=np.uint8)
color = (0,0,0)
cnts = n... | itseezREPO_NAMEopencvPATH_START.@opencv_extracted@opencv-master@modules@imgproc@misc@python@test@test_imgproc.py@.PATH_END.py |
{
"filename": "test_paper_models.py",
"repo_name": "henrysky/astroNN",
"repo_path": "astroNN_extracted/astroNN-master/tests/test_paper_models.py",
"type": "Python"
} | ##########################################################################
# To make sure published models in papers actually are still working fine
##########################################################################
import os
import shutil
import subprocess
import warnings
import numpy as np
from astroNN.apo... | henryskyREPO_NAMEastroNNPATH_START.@astroNN_extracted@astroNN-master@tests@test_paper_models.py@.PATH_END.py |
{
"filename": "fastchem_c_o.py",
"repo_name": "NewStrangeWorlds/FastChem",
"repo_path": "FastChem_extracted/FastChem-master/python/fastchem_c_o.py",
"type": "Python"
} | import pyfastchem
import numpy as np
import os
from save_output import saveChemistryOutput, saveMonitorOutput, saveChemistryOutputPandas, saveMonitorOutputPandas
import matplotlib.pyplot as plt
from astropy import constants as const
#input values for temperature (in K) and pressure (in bar)
#we only use a single value... | NewStrangeWorldsREPO_NAMEFastChemPATH_START.@FastChem_extracted@FastChem-master@python@fastchem_c_o.py@.PATH_END.py |
{
"filename": "600_Interpolation.ipynb",
"repo_name": "rometsch/fargocpt",
"repo_path": "fargocpt_extracted/fargocpt-master/examples/600_Interpolation.ipynb",
"type": "Jupyter Notebook"
} | # Interpolation of grids
This notebook shows how fields defined on the interfaces can be interpolated to cell centers.
This is used in the Loader class provided by the `fargocpt` module.
We make use of the underlying symmetry of the grids.
This brings the interpolation time down from 1.5 seconds using `scipy.interpol... | rometschREPO_NAMEfargocptPATH_START.@fargocpt_extracted@fargocpt-master@examples@600_Interpolation.ipynb@.PATH_END.py |
{
"filename": "5_analyze_air_shower_reco.py",
"repo_name": "nu-radio/NuRadioMC",
"repo_path": "NuRadioMC_extracted/NuRadioMC-master/NuRadioReco/examples/cr_efficiency_analysis/5_analyze_air_shower_reco.py",
"type": "Python"
} | import numpy as np
import os
import glob
import helper_cr_eff as hcr
import json
import NuRadioReco.modules.io.eventReader as eventReader
from NuRadioReco.framework.parameters import stationParameters as stnp
from NuRadioReco.framework.parameters import showerParameters as shp
from NuRadioReco.utilities import units
im... | nu-radioREPO_NAMENuRadioMCPATH_START.@NuRadioMC_extracted@NuRadioMC-master@NuRadioReco@examples@cr_efficiency_analysis@5_analyze_air_shower_reco.py@.PATH_END.py |
{
"filename": "orbit.py",
"repo_name": "rpoleski/MulensModel",
"repo_path": "MulensModel_extracted/MulensModel-master/source/MulensModel/orbits/orbit.py",
"type": "Python"
} | import numpy as np
import math
"""
Classes that can be accessed directly:
- Orbit
- OrbitCircular
- OrbitEccentric
"""
class Orbit(object):
"""
Class that combines :py:class:`OrbitCircular` and
:py:class:`OrbitEccentric`.
"""
def __new__(self, **kwargs):
for Class_ in [OrbitCircular, Orbi... | rpoleskiREPO_NAMEMulensModelPATH_START.@MulensModel_extracted@MulensModel-master@source@MulensModel@orbits@orbit.py@.PATH_END.py |
{
"filename": "event.py",
"repo_name": "gautiernguyen/Automatic-detection-of-ICMEs-at-1-AU-a-deep-learning-approach",
"repo_path": "Automatic-detection-of-ICMEs-at-1-AU-a-deep-learning-approach_extracted/Automatic-detection-of-ICMEs-at-1-AU-a-deep-learning-approach-master/event.py",
"type": "Python"
} | import pandas as pds
import datetime
import numpy as np
import time
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
class Event:
def __init__(self, begin, end, param=None):
self.begin = begin
self.end = end
self.proba = None
self.duration = self.end-self.begin
... | LONG_NAME_3.py |
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