metadata dict | text stringlengths 0 40.6M | id stringlengths 14 255 |
|---|---|---|
{
"filename": "ver.py",
"repo_name": "dstndstn/astrometry.net",
"repo_path": "astrometry.net_extracted/astrometry.net-main/solver/ver.py",
"type": "Python"
} | # This file is part of the Astrometry.net suite.
# Licensed under a 3-clause BSD style license - see LICENSE
import math
try:
import pyfits
except ImportError:
try:
from astropy.io import fits as pyfits
except ImportError:
raise ImportError("Cannot import either pyfits or astropy.io.fits")
f... | dstndstnREPO_NAMEastrometry.netPATH_START.@astrometry.net_extracted@astrometry.net-main@solver@ver.py@.PATH_END.py |
{
"filename": "test_from_records.py",
"repo_name": "pandas-dev/pandas",
"repo_path": "pandas_extracted/pandas-main/pandas/tests/frame/constructors/test_from_records.py",
"type": "Python"
} | from collections.abc import Iterator
from datetime import (
datetime,
timezone,
)
from decimal import Decimal
import numpy as np
import pytest
from pandas._config import using_string_dtype
from pandas.compat import is_platform_little_endian
from pandas import (
CategoricalIndex,
DataFrame,
Index... | pandas-devREPO_NAMEpandasPATH_START.@pandas_extracted@pandas-main@pandas@tests@frame@constructors@test_from_records.py@.PATH_END.py |
{
"filename": "Q_RKF45CuPyTolTestScott.ipynb",
"repo_name": "peijin94/FastQSL",
"repo_path": "FastQSL_extracted/FastQSL-main/demo/Q_RKF45CuPyTolTestScott.ipynb",
"type": "Jupyter Notebook"
} | ```python
import numpy as np
import scipy.io as sciIO
import matplotlib.pyplot as plt
import cupy # CUDA interface for python
%load_ext autoreload
%autoreload 2
%load_ext autotime
import FastQSL
```
time: 344 ms (started: 2021-12-05 09:52:59 +08:00)
```python
cupy.__version__
```
'8.6.0'
t... | peijin94REPO_NAMEFastQSLPATH_START.@FastQSL_extracted@FastQSL-main@demo@Q_RKF45CuPyTolTestScott.ipynb@.PATH_END.py |
{
"filename": "astropt001M.py",
"repo_name": "Smith42/astroPT",
"repo_path": "astroPT_extracted/astroPT-main/config/astropt001M.py",
"type": "Python"
} | # this file will train a ~1M parameter model
#
# launch as the following (e.g. in a tmux session) and wait ~5 days:
# $ OMP_NUM_THREADS=32 torchrun --standalone --nproc_per_node=8 src/train.py config/astropt001M.py
#
# don't forget to $(mkdir logs) !
# params
n_layer=4
n_head=8
n_embd=128
block_size=1024
# here we fo... | Smith42REPO_NAMEastroPTPATH_START.@astroPT_extracted@astroPT-main@config@astropt001M.py@.PATH_END.py |
{
"filename": "_ticktextsrc.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/carpet/aaxis/_ticktextsrc.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class TicktextsrcValidator(_plotly_utils.basevalidators.SrcValidator):
def __init__(self, plotly_name="ticktextsrc", parent_name="carpet.aaxis", **kwargs):
super(TicktextsrcValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_na... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@carpet@aaxis@_ticktextsrc.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/scattermap/selected/marker/_color.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class ColorValidator(_plotly_utils.basevalidators.ColorValidator):
def __init__(
self, plotly_name="color", parent_name="scattermap.selected.marker", **kwargs
):
super(ColorValidator, self).__init__(
plotly_name=plotly_name,
parent_na... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@scattermap@selected@marker@_color.py@.PATH_END.py |
{
"filename": "_dtickrange.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/contourcarpet/colorbar/tickformatstop/_dtickrange.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator):
def __init__(
self,
plotly_name="dtickrange",
parent_name="contourcarpet.colorbar.tickformatstop",
**kwargs,
):
super(DtickrangeValidator, self).__init__(
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@contourcarpet@colorbar@tickformatstop@_dtickrange.py@.PATH_END.py |
{
"filename": "tvtk_segmentation.py",
"repo_name": "enthought/mayavi",
"repo_path": "mayavi_extracted/mayavi-master/docs/source/mayavi/auto/tvtk_segmentation.py",
"type": "Python"
} | """
Using VTK to assemble a pipeline for segmenting MRI images. This example
shows how to insert well-controled custom VTK filters in Mayavi.
This example downloads an MRI scan, turns it into a 3D numpy array,
applies a segmentation procedure made of VTK filters to extract the
gray-matter/white-matter boundary.
The s... | enthoughtREPO_NAMEmayaviPATH_START.@mayavi_extracted@mayavi-master@docs@source@mayavi@auto@tvtk_segmentation.py@.PATH_END.py |
{
"filename": "pgm.py",
"repo_name": "abmantz/lrgs",
"repo_path": "lrgs_extracted/lrgs-master/pgm.py",
"type": "Python"
} | from matplotlib import rc
import daft
rc("font", family="serif", size=12)
rc("text", usetex=True)
pgm = daft.PGM([3.6, 4.1], observed_style="inner")
pgm.add_node(daft.Node("xy", r"$x,y$", 1.95, 0.4, observed=True))
pgm.add_node(daft.Node("M", r"$M$", 2.9, 0.4, fixed=True))
pgm.add_node(daft.Node("eta", r"$\eta$", 2.9... | abmantzREPO_NAMElrgsPATH_START.@lrgs_extracted@lrgs-master@pgm.py@.PATH_END.py |
{
"filename": "model_metrics.py",
"repo_name": "daniel-muthukrishna/astrodash",
"repo_path": "astrodash_extracted/astrodash-master/astrodash/model_metrics.py",
"type": "Python"
} | import os
import pickle
import matplotlib
import matplotlib.pyplot as plt
import itertools
import numpy as np
from astrodash.multilayer_convnet import convnet_variables
try:
import tensorflow.compat.v1 as tf
tf.disable_v2_behavior()
except ModuleNotFoundError:
import tensorflow as tf
def plot_confusion_... | daniel-muthukrishnaREPO_NAMEastrodashPATH_START.@astrodash_extracted@astrodash-master@astrodash@model_metrics.py@.PATH_END.py |
{
"filename": "haloassigned_spectra.py",
"repo_name": "sbird/fake_spectra",
"repo_path": "fake_spectra_extracted/fake_spectra-master/fake_spectra/haloassigned_spectra.py",
"type": "Python"
} | """This module contains a class and functions which do analysis on spectra associated to
galactic halos. This is fundamentally a somewhat wooly idea, because absorbers and halos are not always closely associated!"""
from __future__ import print_function
import numpy as np
try:
import numexpr as ne
except ImportErro... | sbirdREPO_NAMEfake_spectraPATH_START.@fake_spectra_extracted@fake_spectra-master@fake_spectra@haloassigned_spectra.py@.PATH_END.py |
{
"filename": "_uirevision.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/heatmap/_uirevision.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator):
def __init__(self, plotly_name="uirevision", parent_name="heatmap", **kwargs):
super(UirevisionValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@heatmap@_uirevision.py@.PATH_END.py |
{
"filename": "calculator.py",
"repo_name": "NannyML/nannyml",
"repo_path": "nannyml_extracted/nannyml-main/nannyml/stats/median/calculator.py",
"type": "Python"
} | # Author: Nikolaos Perrakis <nikos@nannyml.com>
#
# License: Apache Software License 2.0
"""Simple Statistics Median Calculator."""
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import pandas as pd
from pandas import MultiIndex
from nannyml.base import AbstractCalculator, _list_... | NannyMLREPO_NAMEnannymlPATH_START.@nannyml_extracted@nannyml-main@nannyml@stats@median@calculator.py@.PATH_END.py |
{
"filename": "_counts.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/parcats/_counts.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class CountsValidator(_plotly_utils.basevalidators.NumberValidator):
def __init__(self, plotly_name="counts", parent_name="parcats", **kwargs):
super(CountsValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
a... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@parcats@_counts.py@.PATH_END.py |
{
"filename": "test_discrete_basic.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/scipy/py3/scipy/stats/tests/test_discrete_basic.py",
"type": "Python"
} | import numpy.testing as npt
from numpy.testing import assert_allclose
import numpy as np
import pytest
from scipy import stats
from .common_tests import (check_normalization, check_moment,
check_mean_expect,
check_var_expect, check_skew_expect,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@scipy@py3@scipy@stats@tests@test_discrete_basic.py@.PATH_END.py |
{
"filename": "_shadow.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/parcoords/legendgrouptitle/font/_shadow.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class ShadowValidator(_plotly_utils.basevalidators.StringValidator):
def __init__(
self,
plotly_name="shadow",
parent_name="parcoords.legendgrouptitle.font",
**kwargs,
):
super(ShadowValidator, self).__init__(
plotly_name=... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@parcoords@legendgrouptitle@font@_shadow.py@.PATH_END.py |
{
"filename": "test_base.py",
"repo_name": "hyperopt/hyperopt",
"repo_path": "hyperopt_extracted/hyperopt-master/hyperopt/tests/test_base.py",
"type": "Python"
} | import copy
import unittest
import numpy as np
import bson
from hyperopt.pyll import scope
from hyperopt.base import JOB_STATE_DONE, JOB_STATE_NEW
from hyperopt.base import TRIAL_KEYS
from hyperopt.base import TRIAL_MISC_KEYS
from hyperopt.base import InvalidTrial
from hyperopt.base import miscs_to_idxs_vals
from hyp... | hyperoptREPO_NAMEhyperoptPATH_START.@hyperopt_extracted@hyperopt-master@hyperopt@tests@test_base.py@.PATH_END.py |
{
"filename": "_tickmode.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/histogram2d/colorbar/_tickmode.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class TickmodeValidator(_plotly_utils.basevalidators.EnumeratedValidator):
def __init__(
self, plotly_name="tickmode", parent_name="histogram2d.colorbar", **kwargs
):
super(TickmodeValidator, self).__init__(
plotly_name=plotly_name,
p... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@histogram2d@colorbar@_tickmode.py@.PATH_END.py |
{
"filename": "setup_package.py",
"repo_name": "D-arioSpace/astroquery",
"repo_path": "astroquery_extracted/astroquery-main/astroquery/vo_conesearch/setup_package.py",
"type": "Python"
} | # Licensed under a 3-clause BSD style license - see LICENSE.rst
def get_package_data():
return {'astroquery.vo_conesearch.tests': ['data/*.xml', 'data/*.json']}
def requires_2to3():
return False
| D-arioSpaceREPO_NAMEastroqueryPATH_START.@astroquery_extracted@astroquery-main@astroquery@vo_conesearch@setup_package.py@.PATH_END.py |
{
"filename": "adapt_data.py",
"repo_name": "micbia/serenet",
"repo_path": "serenet_extracted/serenet-main/utils_data/adapt_data.py",
"type": "Python"
} | import tools21cm as t2c, numpy as np
from sklearn.decomposition import PCA as sciPCA
path_in = '/store/ska/sk02/lightcones/EOS21/test_dataset/'
path_out = '/scratch/snx3000/mibianco/test_skalow/data/'
fout = 'dT4'
print(fout)
#data = np.load(path_in + fout + '_EOS21_EoR.npy')
data = t2c.read_cbin(path_in+fout+'_21cm.... | micbiaREPO_NAMEserenetPATH_START.@serenet_extracted@serenet-main@utils_data@adapt_data.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "PabloVD/HAYASHI",
"repo_path": "HAYASHI_extracted/HAYASHI-master/hayashi/__init__.py",
"type": "Python"
} | __all__ = ['constants', 'cosmo', 'utils', 'subhalos']
from hayashi.constants import *
from hayashi.cosmo import *
from hayashi.utils import *
from hayashi.version import __version__ | PabloVDREPO_NAMEHAYASHIPATH_START.@HAYASHI_extracted@HAYASHI-master@hayashi@__init__.py@.PATH_END.py |
{
"filename": "lensdemo_funcs.py",
"repo_name": "astro-datalab/notebooks-latest",
"repo_path": "notebooks-latest_extracted/notebooks-latest-master/06_EPO/e-TeenAstronomyCafe_Spanish/05_Gravitational_Lensing/lensdemo_funcs.py",
"type": "Python"
} | #
# lensdemo_funcs.py
#
# Function module for strong lensing demos
#
# Intended for use with lensdemo_script.py
#
# Copyright 2009 by Adam S. Bolton
# Creative Commons Attribution-Noncommercial-ShareAlike 3.0 license applies:
# http://creativecommons.org/licenses/by-nc-sa/3.0/
# All redistributions, modified or otherwi... | astro-datalabREPO_NAMEnotebooks-latestPATH_START.@notebooks-latest_extracted@notebooks-latest-master@06_EPO@e-TeenAstronomyCafe_Spanish@05_Gravitational_Lensing@lensdemo_funcs.py@.PATH_END.py |
{
"filename": "test_hera_lk.py",
"repo_name": "21cmfast/21CMMC",
"repo_path": "21CMMC_extracted/21CMMC-master/tests/test_hera_lk.py",
"type": "Python"
} | import numpy as np
from py21cmmc import (
Likelihood1DPowerLightconeUpper,
LikelihoodPlanck,
analyse,
build_computation_chain,
core,
likelihood,
mcmc,
run_mcmc,
)
def test_hera_lk():
lk = Likelihood1DPowerLightconeUpper.from_builtin_data("HERA_H1C_IDR3")
c21cmemu = core.Core2... | 21cmfastREPO_NAME21CMMCPATH_START.@21CMMC_extracted@21CMMC-master@tests@test_hera_lk.py@.PATH_END.py |
{
"filename": "unwrap_woden_phases.py",
"repo_name": "JLBLine/WODEN",
"repo_path": "WODEN_extracted/WODEN-master/scripts/unwrap_woden_phases.py",
"type": "Python"
} | import numpy as np
import os
import warnings
import sys
from astropy.io import fits
from astropy.time import Time, TimeDelta
from astropy.coordinates import EarthLocation
from astropy import units as u
import matplotlib.pyplot as plt
import palpy as pal
D2R = np.pi / 180
MWA_LAT = -26.7033194444
MWA_LAT_RAD = MWA_LAT... | JLBLineREPO_NAMEWODENPATH_START.@WODEN_extracted@WODEN-master@scripts@unwrap_woden_phases.py@.PATH_END.py |
{
"filename": "_hoverlabel.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/graph_objs/scattermapbox/_hoverlabel.py",
"type": "Python"
} | from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Hoverlabel(_BaseTraceHierarchyType):
# class properties
# --------------------
_parent_path_str = "scattermapbox"
_path_str = "scattermapbox.hoverlabel"
_valid_props = {
"align",
... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@graph_objs@scattermapbox@_hoverlabel.py@.PATH_END.py |
{
"filename": "toolbars.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/prompt-toolkit/py2/prompt_toolkit/layout/toolbars.py",
"type": "Python"
} | from __future__ import unicode_literals
from ..enums import IncrementalSearchDirection
from .processors import BeforeInput
from .lexers import SimpleLexer
from .dimension import LayoutDimension
from .controls import BufferControl, TokenListControl, UIControl, UIContent
from .containers import Window, ConditionalCont... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@prompt-toolkit@py2@prompt_toolkit@layout@toolbars.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "jax-ml/jax",
"repo_path": "jax_extracted/jax-main/jax/_src/pallas/triton/__init__.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@jax@_src@pallas@triton@__init__.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/layout/ternary/caxis/tickformatstop/__init__.py",
"type": "Python"
} | import sys
from typing import TYPE_CHECKING
if sys.version_info < (3, 7) or TYPE_CHECKING:
from ._value import ValueValidator
from ._templateitemname import TemplateitemnameValidator
from ._name import NameValidator
from ._enabled import EnabledValidator
from ._dtickrange import DtickrangeValidator... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@layout@ternary@caxis@tickformatstop@__init__.py@.PATH_END.py |
{
"filename": "simulation_example.py",
"repo_name": "nanograv/PINT",
"repo_path": "PINT_extracted/PINT-master/docs/examples/simulation_example.py",
"type": "Python"
} | # %% [markdown]
# # Demonstrate TOA simulation using PINT
# %%
from pint.models import get_model
from pint.simulation import (
make_fake_toas_uniform,
make_fake_toas_fromtim,
)
from pint.residuals import Residuals, WidebandTOAResiduals
from pint.logging import setup as setup_log
from pint import dmu
from pint.... | nanogravREPO_NAMEPINTPATH_START.@PINT_extracted@PINT-master@docs@examples@simulation_example.py@.PATH_END.py |
{
"filename": "visualize_tests.py",
"repo_name": "matplotlib/matplotlib",
"repo_path": "matplotlib_extracted/matplotlib-main/tools/visualize_tests.py",
"type": "Python"
} | #!/usr/bin/env python
#
# This builds a html page of all images from the image comparison tests
# and opens that page in the browser.
#
# $ python tools/visualize_tests.py
#
import argparse
import os
from collections import defaultdict
# Non-png image extensions
NON_PNG_EXTENSIONS = ['pdf', 'svg', 'eps']
html_temp... | matplotlibREPO_NAMEmatplotlibPATH_START.@matplotlib_extracted@matplotlib-main@tools@visualize_tests.py@.PATH_END.py |
{
"filename": "_edists.py",
"repo_name": "LoganAMorrison/blackthorn",
"repo_path": "blackthorn_extracted/blackthorn-master/blackthorn/phase_space/_edists.py",
"type": "Python"
} | from typing import Sequence, Optional
from ..fields import QuantumField
from ._proto import SquaredMatrixElement
from ._three_body import energy_distributions_three_body_decay
from ._nbody import energy_distributions_nbody_decay
def energy_distributions_decay(
cme,
final_states: Sequence[QuantumField],
... | LoganAMorrisonREPO_NAMEblackthornPATH_START.@blackthorn_extracted@blackthorn-master@blackthorn@phase_space@_edists.py@.PATH_END.py |
{
"filename": "pixreplace.py",
"repo_name": "spacetelescope/drizzlepac",
"repo_path": "drizzlepac_extracted/drizzlepac-main/drizzlepac/pixreplace.py",
"type": "Python"
} | """ Pixreplace -- Replace pixels which have one value with another value
:License: :doc:`/LICENSE`
"""
import os
import numpy as np
from astropy.io import fits
from stsci.tools import parseinput
from . import util
__all__ = ['replace', 'help']
__taskname__ = 'pixreplace'
def replace(input, **pars):
""... | spacetelescopeREPO_NAMEdrizzlepacPATH_START.@drizzlepac_extracted@drizzlepac-main@drizzlepac@pixreplace.py@.PATH_END.py |
{
"filename": "core.py",
"repo_name": "D-arioSpace/astroquery",
"repo_path": "astroquery_extracted/astroquery-main/astroquery/dace/core.py",
"type": "Python"
} | # Licensed under a 3-clause BSD style license - see LICENSE.rst
from collections import defaultdict
from json import JSONDecodeError
from astropy.table import Table
from ..query import BaseQuery
from ..utils import async_to_sync
from . import conf
__all__ = ['Dace', 'DaceClass']
class ParseException(Exception):
... | D-arioSpaceREPO_NAMEastroqueryPATH_START.@astroquery_extracted@astroquery-main@astroquery@dace@core.py@.PATH_END.py |
{
"filename": "RTS_ScaledownZ.ipynb",
"repo_name": "NuGrid/NuPyCEE",
"repo_path": "NuPyCEE_extracted/NuPyCEE-master/regression_tests/temp/RTS_ScaledownZ.ipynb",
"type": "Jupyter Notebook"
} | # Regression test suite: Test of scaling of yields below Z=1e-4
Yields of 1e-5 and 1e-6 as a input for SYGMA can be calculated by scaling down the yields fromm Z=1e-4.
SYGMA is doing it in the read_yields.py.
You can find the documentation <a href="doc/sygma.html">here</a>.
Run this to set up the environment:
... | NuGridREPO_NAMENuPyCEEPATH_START.@NuPyCEE_extracted@NuPyCEE-master@regression_tests@temp@RTS_ScaledownZ.ipynb@.PATH_END.py |
{
"filename": "line_endings.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/numpy/py2/numpy/distutils/line_endings.py",
"type": "Python"
} | """ Functions for converting from DOS to UNIX line endings
"""
from __future__ import division, absolute_import, print_function
import sys, re, os
def dos2unix(file):
"Replace CRLF with LF in argument files. Print names of changed files."
if os.path.isdir(file):
print(file, "Directory!")
ret... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@numpy@py2@numpy@distutils@line_endings.py@.PATH_END.py |
{
"filename": "testing.py",
"repo_name": "sherpa/sherpa",
"repo_path": "sherpa_extracted/sherpa-main/sherpa/plot/testing.py",
"type": "Python"
} | #
# Copyright (C) 2023, 2024
# MIT
#
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
#
# This program is distri... | sherpaREPO_NAMEsherpaPATH_START.@sherpa_extracted@sherpa-main@sherpa@plot@testing.py@.PATH_END.py |
{
"filename": "_fftlog_backend.py",
"repo_name": "scipy/scipy",
"repo_path": "scipy_extracted/scipy-main/scipy/fft/_fftlog_backend.py",
"type": "Python"
} | import numpy as np
from warnings import warn
from ._basic import rfft, irfft
from ..special import loggamma, poch
from scipy._lib._array_api import array_namespace
__all__ = ['fht', 'ifht', 'fhtoffset']
# constants
LN_2 = np.log(2)
def fht(a, dln, mu, offset=0.0, bias=0.0):
xp = array_namespace(a)
a = xp.a... | scipyREPO_NAMEscipyPATH_START.@scipy_extracted@scipy-main@scipy@fft@_fftlog_backend.py@.PATH_END.py |
{
"filename": "main.py",
"repo_name": "pyro-ppl/pyro",
"repo_path": "pyro_extracted/pyro-master/examples/air/main.py",
"type": "Python"
} | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
"""
AIR applied to the multi-mnist data set [1].
[1] Eslami, SM Ali, et al. "Attend, infer, repeat: Fast scene
understanding with generative models." Advances in Neural Information
Processing Systems. 2016.
"""
import argparse
i... | pyro-pplREPO_NAMEpyroPATH_START.@pyro_extracted@pyro-master@examples@air@main.py@.PATH_END.py |
{
"filename": "_base.py",
"repo_name": "snad-space/ztf-viewer",
"repo_path": "ztf-viewer_extracted/ztf-viewer-master/ztf_viewer/catalogs/conesearch/_base.py",
"type": "Python"
} | import dataclasses
import logging
import urllib.parse
from functools import partial
from typing import Dict, List, Optional
import pandas as pd
import requests
from astropy.coordinates import SkyCoord
from astropy.cosmology import FlatLambdaCDM
from astropy.table import Table
from astroquery.utils.commons import Table... | snad-spaceREPO_NAMEztf-viewerPATH_START.@ztf-viewer_extracted@ztf-viewer-master@ztf_viewer@catalogs@conesearch@_base.py@.PATH_END.py |
{
"filename": "kepimages.py",
"repo_name": "KeplerGO/PyKE",
"repo_path": "PyKE_extracted/PyKE-master/pyke/kepimages.py",
"type": "Python"
} | from .utils import PyKEArgumentHelpFormatter
import sys
import numpy as np
from astropy.io import fits as pyfits
from tqdm import tqdm
from . import kepio, kepmsg, kepkey, kepstat
__all__ = ['kepimages']
def kepimages(infile, prefix, imtype='FLUX', ranges='0,0', overwrite=True,
verbose=True, logfile='... | KeplerGOREPO_NAMEPyKEPATH_START.@PyKE_extracted@PyKE-master@pyke@kepimages.py@.PATH_END.py |
{
"filename": "_hoverinfo.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/ohlc/_hoverinfo.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator):
def __init__(self, plotly_name="hoverinfo", parent_name="ohlc", **kwargs):
super(HoverinfoValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@ohlc@_hoverinfo.py@.PATH_END.py |
{
"filename": "test_sed_apl.py",
"repo_name": "mirochaj/ares",
"repo_path": "ares_extracted/ares-main/examples/sources/test_sed_apl.py",
"type": "Python"
} | """
test_sed_apl.py
Author: Jordan Mirocha
Affiliation: University of Colorado at Boulder
Created on: Thu May 2 10:46:44 2013
Description: Plot an absorbed power-law spectrum.
"""
import ares
import numpy as np
import matplotlib.pyplot as pl
pars = \
{
'source_type': 'bh',
'source_sed': 'pl',
'source_Emin': ... | mirochajREPO_NAMEaresPATH_START.@ares_extracted@ares-main@examples@sources@test_sed_apl.py@.PATH_END.py |
{
"filename": "shorten.py",
"repo_name": "LSSTDESC/chroma",
"repo_path": "chroma_extracted/chroma-master/doc/shorten.py",
"type": "Python"
} | #!/usr/bin/env python
#
# shorten.py exerpted and modified from prep_jour.py by M. Fitzgerald.
# Copyright information for prep_jour.py follows.
# Kyle Barbary, November 2010
#
# Copyright (c) 2007, Michael P. Fitzgerald (mpfitz@berkeley.edu)
# All rights reserved.
#
# Redistribution and use in source and binary forms... | LSSTDESCREPO_NAMEchromaPATH_START.@chroma_extracted@chroma-master@doc@shorten.py@.PATH_END.py |
{
"filename": "image_classification_Dense.py",
"repo_name": "ahmedfgad/GeneticAlgorithmPython",
"repo_path": "GeneticAlgorithmPython_extracted/GeneticAlgorithmPython-master/examples/TorchGA/image_classification_Dense.py",
"type": "Python"
} | import torch
import pygad.torchga
import pygad
import numpy
def fitness_func(ga_instanse, solution, sol_idx):
global data_inputs, data_outputs, torch_ga, model, loss_function
predictions = pygad.torchga.predict(model=model,
solution=solution,
... | ahmedfgadREPO_NAMEGeneticAlgorithmPythonPATH_START.@GeneticAlgorithmPython_extracted@GeneticAlgorithmPython-master@examples@TorchGA@image_classification_Dense.py@.PATH_END.py |
{
"filename": "_showticklabels.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/funnel/marker/colorbar/_showticklabels.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class ShowticklabelsValidator(_plotly_utils.basevalidators.BooleanValidator):
def __init__(
self,
plotly_name="showticklabels",
parent_name="funnel.marker.colorbar",
**kwargs
):
super(ShowticklabelsValidator, self).__init__(
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@funnel@marker@colorbar@_showticklabels.py@.PATH_END.py |
{
"filename": "_colorscale.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/isosurface/_colorscale.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator):
def __init__(self, plotly_name="colorscale", parent_name="isosurface", **kwargs):
super(ColorscaleValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@isosurface@_colorscale.py@.PATH_END.py |
{
"filename": "TestEvidence2.py",
"repo_name": "dokester/BayesicFitting",
"repo_path": "BayesicFitting_extracted/BayesicFitting-master/BayesicFitting/test/TestEvidence2.py",
"type": "Python"
} | # run with : python3 -m unittest TestEvidence2
import unittest
import os
import numpy
import math
from numpy.testing import assert_array_almost_equal as assertAAE
import matplotlib.pyplot as plt
from BayesicFitting import *
from BayesicFitting import formatter as fmt
from FitPlot import plotFit
from FitPlot import ... | dokesterREPO_NAMEBayesicFittingPATH_START.@BayesicFitting_extracted@BayesicFitting-master@BayesicFitting@test@TestEvidence2.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "SKA-INAF/caesar-rest",
"repo_path": "caesar-rest_extracted/caesar-rest-master/caesar_rest/__init__.py",
"type": "Python"
} | #! /usr/bin/env python
__title__ = 'caesar_rest'
__version__ = '1.0.0'
__author__ = 'Simone Riggi'
__license__ = 'GPL3'
__date__ = '2020-04-17'
__copyright__ = 'Copyright 2020 by Simone Riggi - INAF'
# - Create the standard Logger
import logging
import logging.handlers
#import logging.config
#logging.basicConfig(f... | SKA-INAFREPO_NAMEcaesar-restPATH_START.@caesar-rest_extracted@caesar-rest-master@caesar_rest@__init__.py@.PATH_END.py |
{
"filename": "test_geom.py",
"repo_name": "gammapy/gammapy",
"repo_path": "gammapy_extracted/gammapy-main/gammapy/maps/hpx/tests/test_geom.py",
"type": "Python"
} | # Licensed under a 3-clause BSD style license - see LICENSE.rst
import pytest
import numpy as np
from numpy.testing import assert_allclose
from astropy import units as u
from astropy.coordinates import SkyCoord
from astropy.io import fits
from regions import CircleSkyRegion
from gammapy.maps import HpxGeom, MapAxis, Ma... | gammapyREPO_NAMEgammapyPATH_START.@gammapy_extracted@gammapy-main@gammapy@maps@hpx@tests@test_geom.py@.PATH_END.py |
{
"filename": "_line.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/graph_objs/pie/marker/_line.py",
"type": "Python"
} | from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Line(_BaseTraceHierarchyType):
# class properties
# --------------------
_parent_path_str = "pie.marker"
_path_str = "pie.marker.line"
_valid_props = {"color", "colorsrc", "width", "width... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@graph_objs@pie@marker@_line.py@.PATH_END.py |
{
"filename": "_box.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/graph_objs/_box.py",
"type": "Python"
} | from plotly.basedatatypes import BaseTraceType as _BaseTraceType
import copy as _copy
class Box(_BaseTraceType):
# class properties
# --------------------
_parent_path_str = ""
_path_str = "box"
_valid_props = {
"alignmentgroup",
"boxmean",
"boxpoints",
"customdata... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@graph_objs@_box.py@.PATH_END.py |
{
"filename": "gen.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/tools/enum_parser/parse_enum/benchmark_build/lib/gen.py",
"type": "Python"
} | #!/usr/bin/env python3
# - * - encoding: UTF-8 - * -
from argparse import ArgumentParser
import random
import sys
import math
def parse_args():
parser = ArgumentParser(description="")
parser.add_argument('--range', type=int)
parser.add_argument('--enum', nargs=2, action="append", metavar=("NAME", "SIZE")... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@tools@enum_parser@parse_enum@benchmark_build@lib@gen.py@.PATH_END.py |
{
"filename": "ensemble_predict.py",
"repo_name": "ExoplanetML/Nigraha",
"repo_path": "Nigraha_extracted/Nigraha-main/models/ensemble_predict.py",
"type": "Python"
} | '''Script that generates PC predictions using an ensemble predictor and writes their output to a file.'''
from data import records_io
import tensorflow as tf
from tensorflow import keras
import numpy as np
import pandas as pd
import os, sys
import pprint
import json
from train import get_absolute_path_listings
#import... | ExoplanetMLREPO_NAMENigrahaPATH_START.@Nigraha_extracted@Nigraha-main@models@ensemble_predict.py@.PATH_END.py |
{
"filename": "_cauto.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/histogram/marker/_cauto.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class CautoValidator(_plotly_utils.basevalidators.BooleanValidator):
def __init__(self, plotly_name="cauto", parent_name="histogram.marker", **kwargs):
super(CautoValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@histogram@marker@_cauto.py@.PATH_END.py |
{
"filename": "twavpol.py",
"repo_name": "spedas/pyspedas",
"repo_path": "pyspedas_extracted/pyspedas-master/pyspedas/analysis/twavpol.py",
"type": "Python"
} | """
Perform polarisation analysis of three orthogonal component time series data.
Assumes data are in righthanded fieldaligned coordinate system
with Z pointing the direction of the ambient magnetic field.
The program outputs five spectral results derived from the
fourier transform of the covariance matrix (spectral ... | spedasREPO_NAMEpyspedasPATH_START.@pyspedas_extracted@pyspedas-master@pyspedas@analysis@twavpol.py@.PATH_END.py |
{
"filename": "kmpfit_chauvenet.py",
"repo_name": "kapteyn-astro/kapteyn",
"repo_path": "kapteyn_extracted/kapteyn-master/doc/source/EXAMPLES/kmpfit_chauvenet.py",
"type": "Python"
} | #!/usr/bin/env python
# Demonstrate criterion of Chauvenet to exclude poor data
from numpy.random import normal
from scipy.special import erf, erfc
import numpy
from kapteyn import kmpfit
from matplotlib.pyplot import figure, show, rc
def chauvenet(x, y, mean=None, stdv=None):
#------------------------------------... | kapteyn-astroREPO_NAMEkapteynPATH_START.@kapteyn_extracted@kapteyn-master@doc@source@EXAMPLES@kmpfit_chauvenet.py@.PATH_END.py |
{
"filename": "tool.py",
"repo_name": "langchain-ai/langchain",
"repo_path": "langchain_extracted/langchain-master/libs/community/langchain_community/tools/e2b_data_analysis/tool.py",
"type": "Python"
} | from __future__ import annotations
import ast
import json
import os
from io import StringIO
from sys import version_info
from typing import IO, TYPE_CHECKING, Any, Callable, List, Optional, Type, Union
from langchain_core.callbacks import (
AsyncCallbackManagerForToolRun,
CallbackManager,
CallbackManagerF... | langchain-aiREPO_NAMElangchainPATH_START.@langchain_extracted@langchain-master@libs@community@langchain_community@tools@e2b_data_analysis@tool.py@.PATH_END.py |
{
"filename": "simple_functions.py",
"repo_name": "icrar/daliuge",
"repo_path": "daliuge_extracted/daliuge-master/daliuge-engine/dlg/apps/simple_functions.py",
"type": "Python"
} | #
# ICRAR - International Centre for Radio Astronomy Research
# (c) UWA - The University of Western Australia, 2017
# Copyright by UWA (in the framework of the ICRAR)
# All rights reserved
#
# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser G... | icrarREPO_NAMEdaliugePATH_START.@daliuge_extracted@daliuge-master@daliuge-engine@dlg@apps@simple_functions.py@.PATH_END.py |
{
"filename": "_shadow.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/layout/slider/currentvalue/font/_shadow.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class ShadowValidator(_plotly_utils.basevalidators.StringValidator):
def __init__(
self,
plotly_name="shadow",
parent_name="layout.slider.currentvalue.font",
**kwargs,
):
super(ShadowValidator, self).__init__(
plotly_name=... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@layout@slider@currentvalue@font@_shadow.py@.PATH_END.py |
{
"filename": "_stream.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/splom/_stream.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class StreamValidator(_plotly_utils.basevalidators.CompoundValidator):
def __init__(self, plotly_name="stream", parent_name="splom", **kwargs):
super(StreamValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
d... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@splom@_stream.py@.PATH_END.py |
{
"filename": "_outlinewidth.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/densitymapbox/colorbar/_outlinewidth.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class OutlinewidthValidator(_plotly_utils.basevalidators.NumberValidator):
def __init__(
self, plotly_name="outlinewidth", parent_name="densitymapbox.colorbar", **kwargs
):
super(OutlinewidthValidator, self).__init__(
plotly_name=plotly_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@densitymapbox@colorbar@_outlinewidth.py@.PATH_END.py |
{
"filename": "test_performance.py",
"repo_name": "radio-astro-tools/spectral-cube",
"repo_path": "spectral-cube_extracted/spectral-cube-master/spectral_cube/tests/test_performance.py",
"type": "Python"
} | """
Performance-related tests to make sure we don't use more memory than we should.
For now this is just for SpectralCube, not DaskSpectralCube.
"""
import numpy as np
import pytest
import tempfile
import sys
try:
import tracemalloc
tracemallocOK = True
except ImportError:
tracemallocOK = False
# The c... | radio-astro-toolsREPO_NAMEspectral-cubePATH_START.@spectral-cube_extracted@spectral-cube-master@spectral_cube@tests@test_performance.py@.PATH_END.py |
{
"filename": "pyNTHCOMP.py",
"repo_name": "scotthgn/AGNvar",
"repo_path": "AGNvar_extracted/AGNvar-main/src/pyNTHCOMP.py",
"type": "Python"
} |
"""
This was taken from https://github.com/arnauqb/qsosed/tree/master/qsosed,
which in turn was taken from https://github.com/ADThomas-astro/oxaf/blob/master/oxaf.py .
Credit to A.D. Thomas.
Code was adapted from Xspec for https://arxiv.org/pdf/1611.05165.pdf .
"""
import numpy as np
def donthcomp(ear, param):
... | scotthgnREPO_NAMEAGNvarPATH_START.@AGNvar_extracted@AGNvar-main@src@pyNTHCOMP.py@.PATH_END.py |
{
"filename": "_font.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/graph_objs/volume/hoverlabel/_font.py",
"type": "Python"
} | from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Font(_BaseTraceHierarchyType):
# class properties
# --------------------
_parent_path_str = "volume.hoverlabel"
_path_str = "volume.hoverlabel.font"
_valid_props = {"color", "colorsrc", "... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@graph_objs@volume@hoverlabel@_font.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "pynbody/pynbody",
"repo_path": "pynbody_extracted/pynbody-master/pynbody/analysis/__init__.py",
"type": "Python"
} | """Tools for scientific analysis with pynbody
This sub-package contains a number of modules that enable scientific analysis beyond the basic capabilities of pynbody.
The most essential tools are imported into the sub-package itself, so that they can be accessed directly from
pynbody.analysis. For example, :meth:`pynbo... | pynbodyREPO_NAMEpynbodyPATH_START.@pynbody_extracted@pynbody-master@pynbody@analysis@__init__.py@.PATH_END.py |
{
"filename": "01_🔵_Home.py",
"repo_name": "ander-son-almeida/DashboardOCmass",
"repo_path": "DashboardOCmass_extracted/DashboardOCmass-main/01_🔵_Home.py",
"type": "Python"
} | # -*- coding: utf-8 -*-
"""
Created on Tue Aug 16 23:50:07 2022
@author: Anderson Almeida
"""
import streamlit as st
st.set_page_config(page_title="Home",layout='centered', page_icon='🔵')
st.sidebar.image("images/logo.png", use_column_width=True)
st.title('Revisiting the mass of open clusters with Gaia data')
... | ander-son-almeidaREPO_NAMEDashboardOCmassPATH_START.@DashboardOCmass_extracted@DashboardOCmass-main@01_🔵_Home.py@.PATH_END.py |
{
"filename": "broadening.py",
"repo_name": "radis/radis",
"repo_path": "radis_extracted/radis-master/radis/lbl/broadening.py",
"type": "Python"
} | # -*- coding: utf-8 -*-
"""
Summary
-------
A class to handle all broadening related functions (and unload factory.py)
BroadenFactory is inherited by SpectrumFactory eventually
Routine Listing
---------------
Most methods are written in inherited class with the following inheritance scheme:
:py:class:`~radis.lbl.... | radisREPO_NAMEradisPATH_START.@radis_extracted@radis-master@radis@lbl@broadening.py@.PATH_END.py |
{
"filename": "p10advtables.py",
"repo_name": "kevin218/POET",
"repo_path": "POET_extracted/POET-master/code/lib/p10advtables.py",
"type": "Python"
} | #! /usr/bin/env python
# $Author: kevin $
# $Revision: 549 $
# $Date: 2011-08-24 12:40:35 -0400 (Wed, 24 Aug 2011) $
# $HeadURL: file:///home/esp01/svn/code/python/pipeline/trunk/p10advtables.py $
# $Id: p10advtables.py 549 2011-08-24 16:40:35Z kevin $
'''
To run this program, please fill in all the fields commented
... | kevin218REPO_NAMEPOETPATH_START.@POET_extracted@POET-master@code@lib@p10advtables.py@.PATH_END.py |
{
"filename": "test_pair_all.py",
"repo_name": "Jammy2211/PyAutoLens",
"repo_path": "PyAutoLens_extracted/PyAutoLens-main/test_autolens/point/fit/positions/image/test_pair_all.py",
"type": "Python"
} | import numpy as np
import pytest
import autolens as al
def test__three_sets_of_positions__model_is_repeated__does_not_double_count():
point = al.ps.Point(centre=(0.1, 0.1))
galaxy = al.Galaxy(redshift=1.0, point_0=point)
tracer = al.Tracer(galaxies=[al.Galaxy(redshift=0.5), galaxy])
data = al.Grid2D... | Jammy2211REPO_NAMEPyAutoLensPATH_START.@PyAutoLens_extracted@PyAutoLens-main@test_autolens@point@fit@positions@image@test_pair_all.py@.PATH_END.py |
{
"filename": "test_photometry_lc_interp_singlemet.py",
"repo_name": "LSSTDESC/lsstdesc-diffsky",
"repo_path": "lsstdesc-diffsky_extracted/lsstdesc-diffsky-main/lsstdesc_diffsky/photometry/tests/test_photometry_lc_interp_singlemet.py",
"type": "Python"
} | """
"""
import numpy as np
from dsps.data_loaders.retrieve_fake_fsps_data import load_fake_ssp_data
from dsps.metallicity.mzr import DEFAULT_MET_PDICT
from jax import random as jran
from ... import read_diffskypop_params
from ...defaults import DEFAULT_DIFFGAL_PARAMS
from ...disk_bulge_modeling.disk_knots import FKNOT... | LSSTDESCREPO_NAMElsstdesc-diffskyPATH_START.@lsstdesc-diffsky_extracted@lsstdesc-diffsky-main@lsstdesc_diffsky@photometry@tests@test_photometry_lc_interp_singlemet.py@.PATH_END.py |
{
"filename": "test_krome.py",
"repo_name": "amusecode/amuse",
"repo_path": "amuse_extracted/amuse-main/src/amuse/test/suite/codes_tests/test_krome.py",
"type": "Python"
} | import os.path
import numpy
from amuse.test.amusetest import TestWithMPI
from amuse.community.krome.interface import KromeInterface, Krome, solar_abundances
from amuse.units import units
from amuse.datamodel import Particles
from amuse.io import read_set_from_file
# default_options={}
default_options = dict(redirect... | amusecodeREPO_NAMEamusePATH_START.@amuse_extracted@amuse-main@src@amuse@test@suite@codes_tests@test_krome.py@.PATH_END.py |
{
"filename": "ScalEqs.ipynb",
"repo_name": "SBU-COSMOLIKE/CAMBLateDE",
"repo_path": "CAMBLateDE_extracted/CAMBLateDE-main/docs/ScalEqs.ipynb",
"type": "Jupyter Notebook"
} | ```python
# Notebook demonstrating the use of quantities defined incamb.symbolic, and examples of usage
# for defining custom sources and plotting different quantities.
# Set of scalar equations implemented in CAMB, and calculation of the line-of-sight sources
# indices are:
# g - photons, r- massless neutrinos, c - ... | SBU-COSMOLIKEREPO_NAMECAMBLateDEPATH_START.@CAMBLateDE_extracted@CAMBLateDE-main@docs@ScalEqs.ipynb@.PATH_END.py |
{
"filename": "README.md",
"repo_name": "SNOwGLoBES/snowglobes",
"repo_path": "snowglobes_extracted/snowglobes-master/README.md",
"type": "Markdown"
} | # SNOwGLoBES
SuperNova Observatories with GLoBES
## Dependencies
Make sure you have **gcc** and **GNU gls** installed (GLoBES install prerequisite) <br>
* **ROOT** must be installed !
* **gcc** can be installed through the ROOT prereqs
* **GNU gls** can be intalled through the ROOT Optional prereqs
* Se... | SNOwGLoBESREPO_NAMEsnowglobesPATH_START.@snowglobes_extracted@snowglobes-master@README.md@.PATH_END.py |
{
"filename": "_separatethousands.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/layout/polar/angularaxis/_separatethousands.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class SeparatethousandsValidator(_plotly_utils.basevalidators.BooleanValidator):
def __init__(
self,
plotly_name="separatethousands",
parent_name="layout.polar.angularaxis",
**kwargs,
):
super(SeparatethousandsValidator, self).__init_... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@layout@polar@angularaxis@_separatethousands.py@.PATH_END.py |
{
"filename": "chain_plot.py",
"repo_name": "jmeyers314/linmix",
"repo_path": "linmix_extracted/linmix-master/tests/chain_plot.py",
"type": "Python"
} | import numpy as np
import astropy.io.ascii as ascii
import matplotlib.pyplot as plt
pyout = ascii.read('test.pyout')
idlout = ascii.read('test.idlout')
fig, axarr = plt.subplots(4, 2, figsize=(10, 10))
fig.suptitle("python")
axarr[0,0].plot(pyout['alpha'])
axarr[0,0].set_ylabel('alpha')
axarr[0,1].plot(pyout['beta']... | jmeyers314REPO_NAMElinmixPATH_START.@linmix_extracted@linmix-master@tests@chain_plot.py@.PATH_END.py |
{
"filename": "_maxallowed.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/layout/scene/xaxis/autorangeoptions/_maxallowed.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class MaxallowedValidator(_plotly_utils.basevalidators.AnyValidator):
def __init__(
self,
plotly_name="maxallowed",
parent_name="layout.scene.xaxis.autorangeoptions",
**kwargs,
):
super(MaxallowedValidator, self).__init__(
... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@layout@scene@xaxis@autorangeoptions@_maxallowed.py@.PATH_END.py |
{
"filename": "IsothermalAtmo.py",
"repo_name": "DavidDahlbudding/AtmosphericScatteringPinn",
"repo_path": "AtmosphericScatteringPinn_extracted/AtmosphericScatteringPinn-main/EquationModels/IsothermalAtmo.py",
"type": "Python"
} | from ImportFile import *
import time
#from petitRADTRANS import Radtrans
pi = math.pi
extrema_values = None
space_dimensions = 1
time_dimensions = 0
domain_values = torch.tensor([[-1.0, 1.0]]) # x, only boundary condition at x = -1
parameters_values = torch.tensor([[-1.0, 1.0]]) # y, other parameters added with appen... | DavidDahlbuddingREPO_NAMEAtmosphericScatteringPinnPATH_START.@AtmosphericScatteringPinn_extracted@AtmosphericScatteringPinn-main@EquationModels@IsothermalAtmo.py@.PATH_END.py |
{
"filename": "tfsa-2021-066.md",
"repo_name": "tensorflow/tensorflow",
"repo_path": "tensorflow_extracted/tensorflow-master/tensorflow/security/advisory/tfsa-2021-066.md",
"type": "Markdown"
} | ## TFSA-2021-066: Undefined behavior and `CHECK`-fail in `FractionalMaxPoolGrad`
### CVE Number
CVE-2021-29580
### Impact
The implementation of `tf.raw_ops.FractionalMaxPoolGrad` triggers an undefined
behavior if one of the input tensors is empty:
```python
import tensorflow as tf
orig_input = tf.constant([2, 3], s... | tensorflowREPO_NAMEtensorflowPATH_START.@tensorflow_extracted@tensorflow-master@tensorflow@security@advisory@tfsa-2021-066.md@.PATH_END.py |
{
"filename": "_cmin.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/splom/marker/_cmin.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class CminValidator(_plotly_utils.basevalidators.NumberValidator):
def __init__(self, plotly_name="cmin", parent_name="splom.marker", **kwargs):
super(CminValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
ed... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@splom@marker@_cmin.py@.PATH_END.py |
{
"filename": "_family.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/scattermapbox/marker/colorbar/tickfont/_family.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class FamilyValidator(_plotly_utils.basevalidators.StringValidator):
def __init__(
self,
plotly_name="family",
parent_name="scattermapbox.marker.colorbar.tickfont",
**kwargs
):
super(FamilyValidator, self).__init__(
plotly... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@scattermapbox@marker@colorbar@tickfont@_family.py@.PATH_END.py |
{
"filename": "Interactive_data.ipynb",
"repo_name": "ialopezt/GalLenspy",
"repo_path": "GalLenspy_extracted/GalLenspy-master/Puntual_source/Mass_reconstruction/Interactive_data.ipynb",
"type": "Jupyter Notebook"
} | ```python
from scipy.misc import *
import numpy as np
import pylab as plb
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from scipy.integrate import quad
from scipy.integrate import nquad
from scipy.misc import derivative
from ipywidgets import interact, interactive, fixed, interact_manual
from ipywidgets i... | ialopeztREPO_NAMEGalLenspyPATH_START.@GalLenspy_extracted@GalLenspy-master@Puntual_source@Mass_reconstruction@Interactive_data.ipynb@.PATH_END.py |
{
"filename": "SAGE_MM.ipynb",
"repo_name": "darrencroton/sage",
"repo_path": "sage_extracted/sage-master/output/SAGE_MM.ipynb",
"type": "Jupyter Notebook"
} | ```
%pylab inline
```
Populating the interactive namespace from numpy and matplotlib
```
import urllib
import os
import time
```
```
datadir = 'sage_output/' # Change me to whatever you like
# Retrieve output of SAGE from Mini Millennium with fiducial parameters if directory is empty
# Run this for an empty d... | darrencrotonREPO_NAMEsagePATH_START.@sage_extracted@sage-master@output@SAGE_MM.ipynb@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "JulianBMunoz/21cmvFAST",
"repo_path": "21cmvFAST_extracted/21cmvFAST-master/public_21CMvFAST_MC/Programs/CosmoHammer_21CMMC/likelihood/module/wmap/__init__.py",
"type": "Python"
} | JulianBMunozREPO_NAME21cmvFASTPATH_START.@21cmvFAST_extracted@21cmvFAST-master@public_21CMvFAST_MC@Programs@CosmoHammer_21CMMC@likelihood@module@wmap@__init__.py@.PATH_END.py | |
{
"filename": "lax_test.py",
"repo_name": "jax-ml/jax",
"repo_path": "jax_extracted/jax-main/tests/lax_test.py",
"type": "Python"
} | # Copyright 2018 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@lax_test.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "VChristiaens/MINDS",
"repo_path": "MINDS_extracted/MINDS-main/src/minds/__init__.py",
"type": "Python"
} | from . import _version
try:
__version__ = _version.version
except Exception:
__version__ = "dev" | VChristiaensREPO_NAMEMINDSPATH_START.@MINDS_extracted@MINDS-main@src@minds@__init__.py@.PATH_END.py |
{
"filename": "CONTRIBUTING.md",
"repo_name": "scikit-optimize/scikit-optimize",
"repo_path": "scikit-optimize_extracted/scikit-optimize-master/CONTRIBUTING.md",
"type": "Markdown"
} | # Contributing
Scikit-Optimize is an open-source project and contributions of all kinds
are welcome. We believe in this [code of conduct](CONDUCT.md).
You can contribute with documentation, examples, reviewing pull requests, code,
helping answer questions in issues, creating visualizations, maintaining project
infras... | scikit-optimizeREPO_NAMEscikit-optimizePATH_START.@scikit-optimize_extracted@scikit-optimize-master@CONTRIBUTING.md@.PATH_END.py |
{
"filename": "_colorbar.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/graph_objs/mesh3d/_colorbar.py",
"type": "Python"
} | from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class ColorBar(_BaseTraceHierarchyType):
# class properties
# --------------------
_parent_path_str = "mesh3d"
_path_str = "mesh3d.colorbar"
_valid_props = {
"bgcolor",
"borderc... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@graph_objs@mesh3d@_colorbar.py@.PATH_END.py |
{
"filename": "limongi_chieffi_yields.py",
"repo_name": "bretthandrews/flexCE",
"repo_path": "flexCE_extracted/flexCE-master/flexCE/calc_yields/limongi_chieffi_yields.py",
"type": "Python"
} | """Generate finely spaced grid of SN II isotopic yields.
Use a combination of the Chieffi & Limongi (2004) & Limongi & Chieffi (2006).
Chieffi & Limongi (2004): M = 13--35 Msun; Z = 0--solar
Limongi & Chieffi (2006): M = 11--120; Z = solar
Mass cut = 0.1 Msun Ni56
"""
from __future__ import print_function, division... | bretthandrewsREPO_NAMEflexCEPATH_START.@flexCE_extracted@flexCE-master@flexCE@calc_yields@limongi_chieffi_yields.py@.PATH_END.py |
{
"filename": "_style.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/carpet/aaxis/title/font/_style.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class StyleValidator(_plotly_utils.basevalidators.EnumeratedValidator):
def __init__(
self, plotly_name="style", parent_name="carpet.aaxis.title.font", **kwargs
):
super(StyleValidator, self).__init__(
plotly_name=plotly_name,
parent_... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@carpet@aaxis@title@font@_style.py@.PATH_END.py |
{
"filename": "loginterp.py",
"repo_name": "sfschen/velocileptors",
"repo_path": "velocileptors_extracted/velocileptors-master/velocileptors/Utils/loginterp.py",
"type": "Python"
} | import numpy as np
from scipy.interpolate import InterpolatedUnivariateSpline as interpolate
from scipy.misc import derivative
import inspect
def loginterp(x, y, yint = None, side = "both", lorder = 9, rorder = 9, lp = 1, rp = -2,
ldx = 1e-6, rdx = 1e-6,\
interp_min = -12, interp_max = 12, ... | sfschenREPO_NAMEvelocileptorsPATH_START.@velocileptors_extracted@velocileptors-master@velocileptors@Utils@loginterp.py@.PATH_END.py |
{
"filename": "fista.py",
"repo_name": "hmuellergoe/mrbeam",
"repo_path": "mrbeam_extracted/mrbeam-main/mr_beam/itreg/regpy/solvers/fista.py",
"type": "Python"
} | import logging
import numpy as np
from regpy.solvers import Solver
from regpy import util
from regpy.functionals import Functional
"""
The generalized FISTA algorithm for minimization of regpar * G+H (where G, H: Hdomain -> R are the penalty term and the data fidelity term respectively).
We assume:
-> G, H are co... | hmuellergoeREPO_NAMEmrbeamPATH_START.@mrbeam_extracted@mrbeam-main@mr_beam@itreg@regpy@solvers@fista.py@.PATH_END.py |
{
"filename": "pyqt_nonblock.py",
"repo_name": "spacetelescope/specview",
"repo_path": "specview_extracted/specview-master/proto/specviewer/samp-based/pyqt_nonblock.py",
"type": "Python"
} | '''Setup for non-blocking PyQt apps
Routine Listings
----------------
There are two interfaces:
pyqtapplication: Functional interface that returns the QApplication instance
PyQtNonblock: Class that ensures the QApplication instance never goes out-of-scope
Usage
-----
The main class inherits PyQtNonblock, ensu... | spacetelescopeREPO_NAMEspecviewPATH_START.@specview_extracted@specview-master@proto@specviewer@samp-based@pyqt_nonblock.py@.PATH_END.py |
{
"filename": "_symbol.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/scatterternary/marker/_symbol.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class SymbolValidator(_plotly_utils.basevalidators.EnumeratedValidator):
def __init__(
self, plotly_name="symbol", parent_name="scatterternary.marker", **kwargs
):
super(SymbolValidator, self).__init__(
plotly_name=plotly_name,
parent... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@scatterternary@marker@_symbol.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "simonsobs/nextline-rdb",
"repo_path": "nextline-rdb_extracted/nextline-rdb-main/src/nextline_rdb/models/strategies/__init__.py",
"type": "Python"
} | __all__ = [
'st_model_instance_list',
'st_model_prompt',
'st_model_prompt_list',
'st_model_run',
'st_model_run_list',
'st_model_script',
'st_model_script_list',
'st_model_stdout',
'st_model_stdout_list',
'st_model_trace',
'st_model_trace_list',
'st_model_trace_call',
... | simonsobsREPO_NAMEnextline-rdbPATH_START.@nextline-rdb_extracted@nextline-rdb-main@src@nextline_rdb@models@strategies@__init__.py@.PATH_END.py |
{
"filename": "adi_tools.py",
"repo_name": "markusbonse/fours",
"repo_path": "fours_extracted/fours-main/fours/utils/adi_tools.py",
"type": "Python"
} | import numpy as np
import multiprocessing
from scipy.ndimage import rotate
from tqdm import tqdm
import torch
from fours.models.rotation import FieldRotationModel
def cadi_psf_subtraction(
images: np.ndarray,
angles: np.ndarray):
median_frame = np.median(images, axis=0)
residual_sequence = ... | markusbonseREPO_NAMEfoursPATH_START.@fours_extracted@fours-main@fours@utils@adi_tools.py@.PATH_END.py |
{
"filename": "train_model_on_catalog.py",
"repo_name": "mwalmsley/zoobot",
"repo_path": "zoobot_extracted/zoobot-main/zoobot/tensorflow/examples/train_from_scratch/train_model_on_catalog.py",
"type": "Python"
} | import logging
import argparse
import os
import pandas as pd
import tensorflow as tf
import wandb
from galaxy_datasets.shared import label_metadata
from zoobot.shared import schemas
from zoobot.tensorflow.training import train_with_keras
if __name__ == '__main__':
"""
Convenient command-line API/example fo... | mwalmsleyREPO_NAMEzoobotPATH_START.@zoobot_extracted@zoobot-main@zoobot@tensorflow@examples@train_from_scratch@train_model_on_catalog.py@.PATH_END.py |
{
"filename": "_familysrc.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/sankey/node/hoverlabel/font/_familysrc.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class FamilysrcValidator(_plotly_utils.basevalidators.SrcValidator):
def __init__(
self,
plotly_name="familysrc",
parent_name="sankey.node.hoverlabel.font",
**kwargs
):
super(FamilysrcValidator, self).__init__(
plotly_name... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@sankey@node@hoverlabel@font@_familysrc.py@.PATH_END.py |
{
"filename": "__main__.py",
"repo_name": "maxmahlke/ssos",
"repo_path": "ssos_extracted/ssos-master/ssos/__main__.py",
"type": "Python"
} | #!/usr/bin/env python
"""
Pipeline to search for Solar System objects in wide-field imaging surveys
Information on the project can be found in arXiv:1711.02780
and arXiv:1906.03673
For questions, contact max.mahlke (at) oca.eu
Call as: ssos
"""
import os
import shutil
import sys
import time
... | maxmahlkeREPO_NAMEssosPATH_START.@ssos_extracted@ssos-master@ssos@__main__.py@.PATH_END.py |
{
"filename": "_ticksuffix.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/layout/ternary/caxis/_ticksuffix.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator):
def __init__(
self, plotly_name="ticksuffix", parent_name="layout.ternary.caxis", **kwargs
):
super(TicksuffixValidator, self).__init__(
plotly_name=plotly_name,
... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@layout@ternary@caxis@_ticksuffix.py@.PATH_END.py |
{
"filename": "test_units.py",
"repo_name": "gammapy/gammapy",
"repo_path": "gammapy_extracted/gammapy-main/gammapy/utils/tests/test_units.py",
"type": "Python"
} | # Licensed under a 3-clause BSD style license - see LICENSE.rst
import pytest
import numpy as np
import astropy.units as u
from gammapy.maps import MapAxis
from gammapy.utils.units import energy_unit_format, standardise_unit
def test_standardise_unit():
assert standardise_unit("ph cm-2 s-1") == "cm-2 s-1"
ass... | gammapyREPO_NAMEgammapyPATH_START.@gammapy_extracted@gammapy-main@gammapy@utils@tests@test_units.py@.PATH_END.py |
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