metadata dict | text stringlengths 0 40.6M | id stringlengths 14 255 |
|---|---|---|
{
"filename": "tfsa-2022-161.md",
"repo_name": "tensorflow/tensorflow",
"repo_path": "tensorflow_extracted/tensorflow-master/tensorflow/security/advisory/tfsa-2022-161.md",
"type": "Markdown"
} | ## TFSA-2022-161: `CHECK` fail via inputs in `SdcaOptimizer`
### CVE Number
CVE-2022-41899
### Impact
Inputs `dense_features` or `example_state_data` not of rank 2 will trigger a `CHECK` fail in [`SdcaOptimizer`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/sdca_internal.cc).
```pytho... | tensorflowREPO_NAMEtensorflowPATH_START.@tensorflow_extracted@tensorflow-master@tensorflow@security@advisory@tfsa-2022-161.md@.PATH_END.py |
{
"filename": "gameragm_4D.py",
"repo_name": "nasa/Kamodo",
"repo_path": "Kamodo_extracted/Kamodo-master/kamodo_ccmc/readers/gameragm_4D.py",
"type": "Python"
} | # -*- coding: utf-8 -*-
"""
Created on Wed Jan 4 15:37:59 2023
@author: rringuet,lrastaet
"""
from numpy import vectorize
from datetime import datetime, timezone
model_varnames = {'Bx': ['B_x', 'X-component of magnetic field',
0, 'SM', 'car', ['time', 'X', 'Y', 'Z'], 'nT'],
... | nasaREPO_NAMEKamodoPATH_START.@Kamodo_extracted@Kamodo-master@kamodo_ccmc@readers@gameragm_4D.py@.PATH_END.py |
{
"filename": "osnt090.py",
"repo_name": "juanep97/iop4",
"repo_path": "iop4_extracted/iop4-main/iop4lib/telescopes/osnt090.py",
"type": "Python"
} | # iop4lib config
import iop4lib.config
iop4conf = iop4lib.Config(config_db=False)
# django imports
from abc import ABCMeta, abstractmethod
# other imports
import os
import re
import ftplib
from pathlib import Path
import astropy.io.fits as fits
import astropy.units as u
from astropy.coordinates import Angle, SkyCoord... | juanep97REPO_NAMEiop4PATH_START.@iop4_extracted@iop4-main@iop4lib@telescopes@osnt090.py@.PATH_END.py |
{
"filename": "2022_10_19_155810_af52717cf201_track_retries_restarts.py",
"repo_name": "PrefectHQ/prefect",
"repo_path": "prefect_extracted/prefect-main/src/prefect/server/database/_migrations/versions/sqlite/2022_10_19_155810_af52717cf201_track_retries_restarts.py",
"type": "Python"
} | """Add retry and restart metadata
Revision ID: af52717cf201
Revises: ad4b1b4d1e9d
Create Date: 2022-10-19 15:58:10.016251
"""
import sqlalchemy as sa
from alembic import op
# revision identifiers, used by Alembic.
revision = "af52717cf201"
down_revision = "3ced59d8806b"
branch_labels = None
depends_on = None
def ... | PrefectHQREPO_NAMEprefectPATH_START.@prefect_extracted@prefect-main@src@prefect@server@database@_migrations@versions@sqlite@2022_10_19_155810_af52717cf201_track_retries_restarts.py@.PATH_END.py |
{
"filename": "_prefixsrc.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/table/cells/_prefixsrc.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class PrefixsrcValidator(_plotly_utils.basevalidators.SrcValidator):
def __init__(self, plotly_name="prefixsrc", parent_name="table.cells", **kwargs):
super(PrefixsrcValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@table@cells@_prefixsrc.py@.PATH_END.py |
{
"filename": "paths.py",
"repo_name": "waynebhayes/SpArcFiRe",
"repo_path": "SpArcFiRe_extracted/SpArcFiRe-master/scripts/SpArcFiRe-pyvenv/lib/python2.7/site-packages/astropy/config/paths.py",
"type": "Python"
} | # Licensed under a 3-clause BSD style license - see LICENSE.rst
""" This module contains functions to determine where configuration and
data/cache files used by Astropy should be placed.
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from ..extern impor... | waynebhayesREPO_NAMESpArcFiRePATH_START.@SpArcFiRe_extracted@SpArcFiRe-master@scripts@SpArcFiRe-pyvenv@lib@python2.7@site-packages@astropy@config@paths.py@.PATH_END.py |
{
"filename": "graphics_regression_ceres_residuals.py",
"repo_name": "statsmodels/statsmodels",
"repo_path": "statsmodels_extracted/statsmodels-main/docs/source/plots/graphics_regression_ceres_residuals.py",
"type": "Python"
} | '''
Using a model built from the the state crime dataset, make a CERES plot
with the rate of Poverty as the focus variable.
'''
import matplotlib.pyplot as plt
import statsmodels.api as sm
import statsmodels.formula.api as smf
from statsmodels.graphics.regressionplots import plot_ceres_residuals
crime_data = ... | statsmodelsREPO_NAMEstatsmodelsPATH_START.@statsmodels_extracted@statsmodels-main@docs@source@plots@graphics_regression_ceres_residuals.py@.PATH_END.py |
{
"filename": "FlythroughCommandLine.ipynb",
"repo_name": "nasa/Kamodo",
"repo_path": "Kamodo_extracted/Kamodo-master/docs/notebooks/FlythroughCommandLine.ipynb",
"type": "Jupyter Notebook"
} | # Performing a Flythrough from the Command Line
This notebook tutorial shows how to perform a flythrough from the command line in a variety of methods. The main difference between the notebook and the command line syntaxes is that all of the arguments and default values must be specified in the call from the command li... | nasaREPO_NAMEKamodoPATH_START.@Kamodo_extracted@Kamodo-master@docs@notebooks@FlythroughCommandLine.ipynb@.PATH_END.py |
{
"filename": "meta.py",
"repo_name": "kbwestfall/NIRVANA",
"repo_path": "NIRVANA_extracted/NIRVANA-master/nirvana/data/meta.py",
"type": "Python"
} | """
Provides a class to house and manipulate galaxy global parameters/metadata.
.. include common links, assuming primary doc root is up one directory
.. include:: ../include/links.rst
"""
import warnings
from IPython import embed
import numpy as np
import astropy.units
from astropy.io import fits
from astropy.cosm... | kbwestfallREPO_NAMENIRVANAPATH_START.@NIRVANA_extracted@NIRVANA-master@nirvana@data@meta.py@.PATH_END.py |
{
"filename": "README.md",
"repo_name": "tensorflow/tensorflow",
"repo_path": "tensorflow_extracted/tensorflow-master/tensorflow/lite/experimental/examples/unity/TensorFlowLitePlugin/README.md",
"type": "Markdown"
} | # TF Lite Experimental Unity Plugin
This directory contains an experimental sample Unity (2017) Plugin, based on
the experimental TF Lite C API. The sample demonstrates running inference within
Unity by way of a C# `Interpreter` wrapper.
Note that the native TF Lite plugin(s) *must* be built before using the Unity
Pl... | tensorflowREPO_NAMEtensorflowPATH_START.@tensorflow_extracted@tensorflow-master@tensorflow@lite@experimental@examples@unity@TensorFlowLitePlugin@README.md@.PATH_END.py |
{
"filename": "_kde.py",
"repo_name": "scipy/scipy",
"repo_path": "scipy_extracted/scipy-main/scipy/stats/_kde.py",
"type": "Python"
} | #-------------------------------------------------------------------------------
#
# Define classes for (uni/multi)-variate kernel density estimation.
#
# Currently, only Gaussian kernels are implemented.
#
# Written by: Robert Kern
#
# Date: 2004-08-09
#
# Modified: 2005-02-10 by Robert Kern.
# Contr... | scipyREPO_NAMEscipyPATH_START.@scipy_extracted@scipy-main@scipy@stats@_kde.py@.PATH_END.py |
{
"filename": "DEMO-checkpoint.ipynb",
"repo_name": "lsst-uk/sky-estimation-WP3.7",
"repo_path": "sky-estimation-WP3.7_extracted/sky-estimation-WP3.7-master/makeDwarfs/.ipynb_checkpoints/DEMO-checkpoint.ipynb",
"type": "Jupyter Notebook"
} | # Instructions
Implementation of this code is deliberately simple. As long as you have the lsst.MAG and lsst.MASS tables (available on this page) in the code directory, just create an array representing log(M/Msun), create an instance of a Dwarfs() class object using that array as input, then create a tuple of coordi... | lsst-ukREPO_NAMEsky-estimation-WP3.7PATH_START.@sky-estimation-WP3.7_extracted@sky-estimation-WP3.7-master@makeDwarfs@.ipynb_checkpoints@DEMO-checkpoint.ipynb@.PATH_END.py |
{
"filename": "keywords.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/jedi/py2/jedi/api/keywords.py",
"type": "Python"
} | import pydoc
from jedi.evaluate.utils import ignored
from jedi.evaluate.filters import AbstractNameDefinition
try:
from pydoc_data import topics as pydoc_topics
except ImportError:
# Python 2
try:
import pydoc_topics
except ImportError:
# This is for Python 3 embeddable version, which ... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@jedi@py2@jedi@api@keywords.py@.PATH_END.py |
{
"filename": "_hoverlabel.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/funnelarea/_hoverlabel.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator):
def __init__(self, plotly_name="hoverlabel", parent_name="funnelarea", **kwargs):
super(HoverlabelValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_na... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@funnelarea@_hoverlabel.py@.PATH_END.py |
{
"filename": "setup.py",
"repo_name": "dullemond/radmc3d-2.0",
"repo_path": "radmc3d-2.0_extracted/radmc3d-2.0-master/python/radmc3dPy/setup.py",
"type": "Python"
} | #!/usr/bin/env python
try:
from numpy.distutils.core import setup, Extension
ext = Extension(name = 'radmc3dPy._bhmie',
sources = ['radmc3dPy/bhmie.f90'])
except:
msg = "numpy.distutils.core could not be imported. It is required to build the fast, fortran version of the mie scattering... | dullemondREPO_NAMEradmc3d-2.0PATH_START.@radmc3d-2.0_extracted@radmc3d-2.0-master@python@radmc3dPy@setup.py@.PATH_END.py |
{
"filename": "test_stereo_combination.py",
"repo_name": "cta-observatory/ctapipe",
"repo_path": "ctapipe_extracted/ctapipe-main/src/ctapipe/reco/tests/test_stereo_combination.py",
"type": "Python"
} | import astropy.units as u
import numpy as np
import pytest
from astropy.table import Table
from numpy.testing import assert_allclose, assert_array_equal
from ctapipe.containers import (
ArrayEventContainer,
HillasParametersContainer,
ImageParametersContainer,
ParticleClassificationContainer,
Recons... | cta-observatoryREPO_NAMEctapipePATH_START.@ctapipe_extracted@ctapipe-main@src@ctapipe@reco@tests@test_stereo_combination.py@.PATH_END.py |
{
"filename": "_xpad.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/scattersmith/marker/colorbar/_xpad.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class XpadValidator(_plotly_utils.basevalidators.NumberValidator):
def __init__(
self, plotly_name="xpad", parent_name="scattersmith.marker.colorbar", **kwargs
):
super(XpadValidator, self).__init__(
plotly_name=plotly_name,
parent_na... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@scattersmith@marker@colorbar@_xpad.py@.PATH_END.py |
{
"filename": "serialization_lib_test.py",
"repo_name": "keras-team/keras",
"repo_path": "keras_extracted/keras-master/keras/src/saving/serialization_lib_test.py",
"type": "Python"
} | """Tests for serialization_lib."""
import json
import numpy as np
import pytest
import keras
from keras.src import ops
from keras.src import testing
from keras.src.saving import serialization_lib
def custom_fn(x):
return x**2
class CustomLayer(keras.layers.Layer):
def __init__(self, factor):
supe... | keras-teamREPO_NAMEkerasPATH_START.@keras_extracted@keras-master@keras@src@saving@serialization_lib_test.py@.PATH_END.py |
{
"filename": "optional_input_test.py",
"repo_name": "triton-inference-server/server",
"repo_path": "server_extracted/server-main/qa/L0_optional_input/optional_input_test.py",
"type": "Python"
} | #!/usr/bin/python
# Copyright 2021-2023, NVIDIA CORPORATION & AFFILIATES. 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
# ... | triton-inference-serverREPO_NAMEserverPATH_START.@server_extracted@server-main@qa@L0_optional_input@optional_input_test.py@.PATH_END.py |
{
"filename": "plotkappa.py",
"repo_name": "tomasoshea/chameleon",
"repo_path": "chameleon_extracted/chameleon-main/plotkappa.py",
"type": "Python"
} | # Tom O'Shea 2023
# plot Debye screening scale
from numpy import loadtxt
from matplotlib import pyplot as plt
import numpy as np
plt.style.use("style.txt") # import plot style
# setup plot
fig2 = plt.figure(1) # display is 1920 x 1080 (16:9)
#ax2 = fig2.add_axes((.15,.15,.8,.8))
ax2 = fig2.subplots()
ax2.set(xlim=... | tomasosheaREPO_NAMEchameleonPATH_START.@chameleon_extracted@chameleon-main@plotkappa.py@.PATH_END.py |
{
"filename": "gravsphere_initialise_Sextans.py",
"repo_name": "justinread/gravsphere",
"repo_path": "gravsphere_extracted/gravsphere-master/gravsphere_initialise_Sextans.py",
"type": "Python"
} | import numpy as np
from constants import *
from functions import *
#This file contains all the code options and choices for
#running a given model. Throughout, -1 means auto-calculate.
#Data files and output base filename:
whichgal = 'Sextans'
infile = output_base+whichgal+'/'+whichgal
outdirbase = output_base+whi... | justinreadREPO_NAMEgravspherePATH_START.@gravsphere_extracted@gravsphere-master@gravsphere_initialise_Sextans.py@.PATH_END.py |
{
"filename": "section_2.ipynb",
"repo_name": "NathanSandford/Chem-I-Calc",
"repo_path": "Chem-I-Calc_extracted/Chem-I-Calc-master/notebooks/Sandford_2020/section_2.ipynb",
"type": "Jupyter Notebook"
} | <h1>Table of Contents<span class="tocSkip"></span></h1>
<div class="toc"><ul class="toc-item"><li><span><a href="#Sandford+-2020,-Section-2:--Information-Content-of-Spectra" data-toc-modified-id="Sandford+-2020,-Section-2:--Information-Content-of-Spectra-1"><span class="toc-item-num">1 </span>Sandford+ 2020,... | NathanSandfordREPO_NAMEChem-I-CalcPATH_START.@Chem-I-Calc_extracted@Chem-I-Calc-master@notebooks@Sandford_2020@section_2.ipynb@.PATH_END.py |
{
"filename": "nebulagraph.py",
"repo_name": "langchain-ai/langchain",
"repo_path": "langchain_extracted/langchain-master/libs/langchain/langchain/chains/graph_qa/nebulagraph.py",
"type": "Python"
} | from typing import TYPE_CHECKING, Any
from langchain._api import create_importer
if TYPE_CHECKING:
from langchain_community.chains.graph_qa.nebulagraph import NebulaGraphQAChain
# Create a way to dynamically look up deprecated imports.
# Used to consolidate logic for raising deprecation warnings and
# handling o... | langchain-aiREPO_NAMElangchainPATH_START.@langchain_extracted@langchain-master@libs@langchain@langchain@chains@graph_qa@nebulagraph.py@.PATH_END.py |
{
"filename": "_textfont.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/graph_objs/layout/map/layer/symbol/_textfont.py",
"type": "Python"
} | from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType
import copy as _copy
class Textfont(_BaseLayoutHierarchyType):
# class properties
# --------------------
_parent_path_str = "layout.map.layer.symbol"
_path_str = "layout.map.layer.symbol.textfont"
_valid_props = ... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@graph_objs@layout@map@layer@symbol@_textfont.py@.PATH_END.py |
{
"filename": "test_tools.py",
"repo_name": "pandas-dev/pandas",
"repo_path": "pandas_extracted/pandas-main/pandas/tests/indexes/period/test_tools.py",
"type": "Python"
} | import numpy as np
import pytest
from pandas import (
Period,
PeriodIndex,
period_range,
)
import pandas._testing as tm
class TestPeriodRepresentation:
"""
Wish to match NumPy units
"""
@pytest.mark.parametrize(
"freq, base_date",
[
("W-THU", "1970-01-01"),
... | pandas-devREPO_NAMEpandasPATH_START.@pandas_extracted@pandas-main@pandas@tests@indexes@period@test_tools.py@.PATH_END.py |
{
"filename": "test_imports.py",
"repo_name": "langchain-ai/langchain",
"repo_path": "langchain_extracted/langchain-master/libs/langchain/tests/unit_tests/schema/test_imports.py",
"type": "Python"
} | from langchain.schema import __all__
EXPECTED_ALL = [
"BaseCache",
"BaseMemory",
"BaseStore",
"AgentFinish",
"AgentAction",
"Document",
"BaseChatMessageHistory",
"BaseDocumentTransformer",
"BaseMessage",
"ChatMessage",
"FunctionMessage",
"HumanMessage",
"AIMessage",
... | langchain-aiREPO_NAMElangchainPATH_START.@langchain_extracted@langchain-master@libs@langchain@tests@unit_tests@schema@test_imports.py@.PATH_END.py |
{
"filename": "Finder.ipynb",
"repo_name": "FRBs/FRB",
"repo_path": "FRB_extracted/FRB-main/docs/nb/Finder.ipynb",
"type": "Jupyter Notebook"
} | # Finder Chart Example -- v3
DES
DECaL
log and cutout options
```python
# imports
import numpy as np
from matplotlib import pyplot as plt
from importlib import reload
from astropy.coordinates import SkyCoord
from astropy import units
from astropy.wcs import WCS
from astropy.io import fits
from frb.surve... | FRBsREPO_NAMEFRBPATH_START.@FRB_extracted@FRB-main@docs@nb@Finder.ipynb@.PATH_END.py |
{
"filename": "update_meas_summary.py",
"repo_name": "astro-datalab/nsc",
"repo_path": "nsc_extracted/nsc-master/python/nsc/update_meas_summary.py",
"type": "Python"
} | #!/usr/bin/env python
# Get number of missing OBJECTIDs from nsc_instcal_combine_update_meas.py logs for each exposures
import os
import sys
import numpy as np
import time
from dlnpyutils import utils as dln, db
from astropy.table import Table
from astropy.io import fits
import sqlite3
import socket
from argparse imp... | astro-datalabREPO_NAMEnscPATH_START.@nsc_extracted@nsc-master@python@nsc@update_meas_summary.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/graph_objs/layout/template/data/__init__.py",
"type": "Python"
} | import sys
from typing import TYPE_CHECKING
if sys.version_info < (3, 7) or TYPE_CHECKING:
from ._bar import Bar
from ._barpolar import Barpolar
from ._box import Box
from ._candlestick import Candlestick
from ._carpet import Carpet
from ._choropleth import Choropleth
from ._choroplethmap i... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@graph_objs@layout@template@data@__init__.py@.PATH_END.py |
{
"filename": "_colorsrc.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/table/cells/line/_colorsrc.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator):
def __init__(
self, plotly_name="colorsrc", parent_name="table.cells.line", **kwargs
):
super(ColorsrcValidator, self).__init__(
plotly_name=plotly_name,
parent_name=... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@table@cells@line@_colorsrc.py@.PATH_END.py |
{
"filename": "rad_minimal_new.py",
"repo_name": "amusecode/amuse",
"repo_path": "amuse_extracted/amuse-main/examples/textbook/rad_minimal_new.py",
"type": "Python"
} | import numpy
from amuse.lab import *
from amuse.ic.gasplummer import new_plummer_gas_model
from amuse.ext.spherical_model \
import new_uniform_spherical_particle_distribution
from matplotlib import pyplot
from prepare_figure import single_frame, figure_frame
from distinct_colours import get_distinct
def binned_me... | amusecodeREPO_NAMEamusePATH_START.@amuse_extracted@amuse-main@examples@textbook@rad_minimal_new.py@.PATH_END.py |
{
"filename": "_bgcolorsrc.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/sankey/node/hoverlabel/_bgcolorsrc.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class BgcolorsrcValidator(_plotly_utils.basevalidators.SrcValidator):
def __init__(
self, plotly_name="bgcolorsrc", parent_name="sankey.node.hoverlabel", **kwargs
):
super(BgcolorsrcValidator, self).__init__(
plotly_name=plotly_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@sankey@node@hoverlabel@_bgcolorsrc.py@.PATH_END.py |
{
"filename": "GenerateDEMfromSPHGenerator.py",
"repo_name": "LLNL/spheral",
"repo_path": "spheral_extracted/spheral-main/src/NodeGenerators/GenerateDEMfromSPHGenerator.py",
"type": "Python"
} | from math import *
from NodeGeneratorBase import *
from Spheral import Vector1d, Vector2d, Vector3d, SymTensor1d, SymTensor2d, SymTensor3d
from SpheralTestUtilities import fuzzyEqual
#-------------------------------------------------------------------------------
# Wrapper Generator for DEM based on SPH generators
#... | LLNLREPO_NAMEspheralPATH_START.@spheral_extracted@spheral-main@src@NodeGenerators@GenerateDEMfromSPHGenerator.py@.PATH_END.py |
{
"filename": "libszoom.py",
"repo_name": "ajeldorado/falco-python",
"repo_path": "falco-python_extracted/falco-python-master/falco/proper/libszoom.py",
"type": "Python"
} | def __bootstrap__():
global __bootstrap__, __loader__, __file__
import sys, pkg_resources, imp
__file__ = pkg_resources.resource_filename(__name__, 'libszoom.cpython-36m-x86_64-linux-gnu.so')
__loader__ = None; del __bootstrap__, __loader__
imp.load_dynamic(__name__,__file__)
__bootstrap__()
| ajeldoradoREPO_NAMEfalco-pythonPATH_START.@falco-python_extracted@falco-python-master@falco@proper@libszoom.py@.PATH_END.py |
{
"filename": "_outlinecolor.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/contour/colorbar/_outlinecolor.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class OutlinecolorValidator(_plotly_utils.basevalidators.ColorValidator):
def __init__(
self, plotly_name="outlinecolor", parent_name="contour.colorbar", **kwargs
):
super(OutlinecolorValidator, self).__init__(
plotly_name=plotly_name,
... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@contour@colorbar@_outlinecolor.py@.PATH_END.py |
{
"filename": "interpolative.py",
"repo_name": "scipy/scipy",
"repo_path": "scipy_extracted/scipy-main/scipy/linalg/interpolative.py",
"type": "Python"
} | # ******************************************************************************
# Copyright (C) 2013 Kenneth L. Ho
#
# 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... | scipyREPO_NAMEscipyPATH_START.@scipy_extracted@scipy-main@scipy@linalg@interpolative.py@.PATH_END.py |
{
"filename": "example.py",
"repo_name": "triton-inference-server/server",
"repo_path": "server_extracted/server-main/src/python/examples/example.py",
"type": "Python"
} | # Copyright 2024, NVIDIA CORPORATION & AFFILIATES. 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 of con... | triton-inference-serverREPO_NAMEserverPATH_START.@server_extracted@server-main@src@python@examples@example.py@.PATH_END.py |
{
"filename": "parasail.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/Pygments/py3/pygments/lexers/parasail.py",
"type": "Python"
} | """
pygments.lexers.parasail
~~~~~~~~~~~~~~~~~~~~~~~~
Lexer for ParaSail.
:copyright: Copyright 2006-2024 by the Pygments team, see AUTHORS.
:license: BSD, see LICENSE for details.
"""
import re
from pygments.lexer import RegexLexer, include
from pygments.token import Text, Comment, Operator, Ke... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@Pygments@py3@pygments@lexers@parasail.py@.PATH_END.py |
{
"filename": "_title.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/graph_objs/funnel/marker/colorbar/_title.py",
"type": "Python"
} | from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Title(_BaseTraceHierarchyType):
# class properties
# --------------------
_parent_path_str = "funnel.marker.colorbar"
_path_str = "funnel.marker.colorbar.title"
_valid_props = {"font", "s... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@graph_objs@funnel@marker@colorbar@_title.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "NextGenCMB/lensitbiases",
"repo_path": "lensitbiases_extracted/lensitbiases-main/lensitbiases/tests/__init__.py",
"type": "Python"
} | from . import * | NextGenCMBREPO_NAMElensitbiasesPATH_START.@lensitbiases_extracted@lensitbiases-main@lensitbiases@tests@__init__.py@.PATH_END.py |
{
"filename": "test_fitting_kernels_are_frozen.py",
"repo_name": "ArgonneCPAC/diffstar",
"repo_path": "diffstar_extracted/diffstar-main/diffstar/fitting_helpers/tests/test_fitting_kernels_are_frozen.py",
"type": "Python"
} | """Unit tests enforcing that the behavior of Diffstar on the default params is frozen.
"""
import os
import numpy as np
from diffmah.defaults import DEFAULT_MAH_PARAMS, MAH_K
from diffmah.individual_halo_assembly import _calc_halo_history
from jax import numpy as jnp
from ...defaults import DEFAULT_U_MS_PARAMS, DEFAU... | ArgonneCPACREPO_NAMEdiffstarPATH_START.@diffstar_extracted@diffstar-main@diffstar@fitting_helpers@tests@test_fitting_kernels_are_frozen.py@.PATH_END.py |
{
"filename": "checkpoint_view.py",
"repo_name": "tensorflow/tensorflow",
"repo_path": "tensorflow_extracted/tensorflow-master/tensorflow/python/checkpoint/checkpoint_view.py",
"type": "Python"
} | """Manages a Checkpoint View."""
# 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... | tensorflowREPO_NAMEtensorflowPATH_START.@tensorflow_extracted@tensorflow-master@tensorflow@python@checkpoint@checkpoint_view.py@.PATH_END.py |
{
"filename": "utilities.py",
"repo_name": "benrendle/AIMS",
"repo_path": "AIMS_extracted/AIMS-master/AIMS-Py35/utilities.py",
"type": "Python"
} | #!/usr/bin/env python
# coding: utf-8
# $Id: utilities.py
# Author: Daniel R. Reese <daniel.reese@obspm.fr>
# Copyright (C) Daniel R. Reese and contributors
# Copyright license: GNU GPL v3.0
#
# AIMS is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as pu... | benrendleREPO_NAMEAIMSPATH_START.@AIMS_extracted@AIMS-master@AIMS-Py35@utilities.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "ExObsSim/ExoRad2-public",
"repo_path": "ExoRad2-public_extracted/ExoRad2-public-master/exorad/models/optics/__init__.py",
"type": "Python"
} | ExObsSimREPO_NAMEExoRad2-publicPATH_START.@ExoRad2-public_extracted@ExoRad2-public-master@exorad@models@optics@__init__.py@.PATH_END.py | |
{
"filename": "problem_setup.py",
"repo_name": "dullemond/radmc3d-2.0",
"repo_path": "radmc3d-2.0_extracted/radmc3d-2.0-master/examples/run_ppdisk_simple_2/problem_setup.py",
"type": "Python"
} | #
# Import NumPy for array handling
#
import numpy as np
#
# Some natural constants
#
au = 1.49598e13 # Astronomical Unit [cm]
pc = 3.08572e18 # Parsec [cm]
ms = 1.98892e33 # Solar mass [g]
ts = 5.78e3 # Solar temperature [K]
ls = 3.8525e33 # Solar... | dullemondREPO_NAMEradmc3d-2.0PATH_START.@radmc3d-2.0_extracted@radmc3d-2.0-master@examples@run_ppdisk_simple_2@problem_setup.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/parcoords/line/__init__.py",
"type": "Python"
} | import sys
if sys.version_info < (3, 7):
from ._showscale import ShowscaleValidator
from ._reversescale import ReversescaleValidator
from ._colorsrc import ColorsrcValidator
from ._colorscale import ColorscaleValidator
from ._colorbar import ColorbarValidator
from ._coloraxis import ColoraxisVa... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@parcoords@line@__init__.py@.PATH_END.py |
{
"filename": "fitters.py",
"repo_name": "JohannesBuchner/BXA",
"repo_path": "BXA_extracted/BXA-master/bxa/sherpa/background/fitters.py",
"type": "Python"
} | from __future__ import print_function
"""
Lets try something simpler.
Background model has stages
SingleFitter goes through stages and fits each with chi^2, then cstat
MultiFitter fits first one with SingleFitter,
then goes through all the others
by setting the parameter values to those of the previous id
and then fi... | JohannesBuchnerREPO_NAMEBXAPATH_START.@BXA_extracted@BXA-master@bxa@sherpa@background@fitters.py@.PATH_END.py |
{
"filename": "X-rays.py",
"repo_name": "cweniger/swordfish",
"repo_path": "swordfish_extracted/swordfish-master/Examples/X-rays.py",
"type": "Python"
} | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import numpy as np
import swordfish as sf
import scipy.sparse.linalg as la
import pylab as plt
import harpix as hp
import scipy.sparse as sp
import healpy
from operator import mul
def halo():
"""A single-halo & single-Ebin example.
Scenario: 3.5 keV line and Pers... | cwenigerREPO_NAMEswordfishPATH_START.@swordfish_extracted@swordfish-master@Examples@X-rays.py@.PATH_END.py |
{
"filename": "redcal_inspect_2458149.ipynb",
"repo_name": "HERA-Team/H1C_IDR3_Notebooks",
"repo_path": "H1C_IDR3_Notebooks-main/redcal_inspect/redcal_inspect_2458149.ipynb",
"type": "Jupyter Notebook"
} | # Stage 2 Redundant Calibration Nightly Notebook
**Josh Dillon**, Last Revised 7/30/20
```python
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
from hera_cal import io, redcal, apply_cal
from hera_qm.metrics_io import load_metric_file
import glob
import os
from copy import deepcopy
import inspe... | HERA-TeamREPO_NAMEH1C_IDR3_NotebooksPATH_START.@H1C_IDR3_Notebooks-main@redcal_inspect@redcal_inspect_2458149.ipynb@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "NannyML/nannyml",
"repo_path": "nannyml_extracted/nannyml-main/nannyml/io/db/__init__.py",
"type": "Python"
} | # Author: Niels Nuyttens <niels@nannyml.com>
# #
# License: Apache Software License 2.0
"""This package implements writing Results to a database.
The result objects are converted into a more time-series like format using a `Mapper`.
Every calculator and estimator has a corresponding table where the results will... | NannyMLREPO_NAMEnannymlPATH_START.@nannyml_extracted@nannyml-main@nannyml@io@db@__init__.py@.PATH_END.py |
{
"filename": "_textcase.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/barpolar/marker/colorbar/title/font/_textcase.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class TextcaseValidator(_plotly_utils.basevalidators.EnumeratedValidator):
def __init__(
self,
plotly_name="textcase",
parent_name="barpolar.marker.colorbar.title.font",
**kwargs,
):
super(TextcaseValidator, self).__init__(
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@barpolar@marker@colorbar@title@font@_textcase.py@.PATH_END.py |
{
"filename": "PolySineAmpModel.py",
"repo_name": "dokester/BayesicFitting",
"repo_path": "BayesicFitting_extracted/BayesicFitting-master/BayesicFitting/source/PolySineAmpModel.py",
"type": "Python"
} | import numpy as numpy
import math
from . import Tools
from .Tools import setAttribute as setatt
from .LinearModel import LinearModel
from .PolynomialModel import PolynomialModel
__author__ = "Do Kester"
__year__ = 2020
__license__ = "GPL3"
__version__ = "2.5.3"
__url__ = "https://www.bayesicfitting.nl"
__status__ = "P... | dokesterREPO_NAMEBayesicFittingPATH_START.@BayesicFitting_extracted@BayesicFitting-master@BayesicFitting@source@PolySineAmpModel.py@.PATH_END.py |
{
"filename": "HOD_library.py",
"repo_name": "franciscovillaescusa/Pylians",
"repo_path": "Pylians_extracted/Pylians-master/library/HOD_library.py",
"type": "Python"
} | import numpy as np
import readsnap
import readsubf
import sys
import time
import random
###############################################################################
#this function returns an array containing the positions of the galaxies (kpc/h)
#in the catalogue according to the fiducial density, M1 and alpha
#CDM... | franciscovillaescusaREPO_NAMEPyliansPATH_START.@Pylians_extracted@Pylians-master@library@HOD_library.py@.PATH_END.py |
{
"filename": "test_beam_model.py",
"repo_name": "rasg-affiliates/healvis",
"repo_path": "healvis_extracted/healvis-master/healvis/tests/test_beam_model.py",
"type": "Python"
} | # -*- mode: python; coding: utf-8 -*
# Copyright (c) 2019 Radio Astronomy Software Group
# Licensed under the 3-clause BSD License
import numpy as np
from astropy_healpix import healpy as hp
import os
import copy
from astropy.cosmology import WMAP9
from pyuvdata import UVBeam
from healvis import beam_model
from healv... | rasg-affiliatesREPO_NAMEhealvisPATH_START.@healvis_extracted@healvis-master@healvis@tests@test_beam_model.py@.PATH_END.py |
{
"filename": "panco.py",
"repo_name": "fkeruzore/panco2",
"repo_path": "panco2_extracted/panco2-main/panco2/old/panco.py",
"type": "Python"
} | #!/usr/bin/env python3
import numpy as np
import matplotlib.pyplot as plt
import astropy.units as u
from astropy.io import fits
from astropy.wcs import WCS
from astropy.nddata import Cutout2D
from astropy.coordinates import SkyCoord
import emcee
from iminuit import Minuit
import sys
import os
import shutil
import json
... | fkeruzoreREPO_NAMEpanco2PATH_START.@panco2_extracted@panco2-main@panco2@old@panco.py@.PATH_END.py |
{
"filename": "demo_IRR_assets.py",
"repo_name": "projectchrono/chrono",
"repo_path": "chrono_extracted/chrono-main/src/demos/python/irrlicht/demo_IRR_assets.py",
"type": "Python"
} | # =============================================================================
# PROJECT CHRONO - http://projectchrono.org
#
# Copyright (c) 2014 projectchrono.org
# All rights reserved.
#
# Use of this source code is governed by a BSD-style license that can be found
# in the LICENSE file at the top level of the distr... | projectchronoREPO_NAMEchronoPATH_START.@chrono_extracted@chrono-main@src@demos@python@irrlicht@demo_IRR_assets.py@.PATH_END.py |
{
"filename": "MWATilemodel2hpm.py",
"repo_name": "dannyjacobs/ECHO",
"repo_path": "ECHO_extracted/ECHO-master/scripts/old/MWATilemodel2hpm.py",
"type": "Python"
} | from mwapy.pb import primary_beam
import optparse,sys
import healpy as hp
import numpy as np
def dB(x):
#for converting power to dB
return 10*np.log10(x)
def dB20(x):
#for converting V/m to dB
return 20*np.log10(x)
o = optparse.OptionParser()
o.set_description('read in the latest mwa beam model and o... | dannyjacobsREPO_NAMEECHOPATH_START.@ECHO_extracted@ECHO-master@scripts@old@MWATilemodel2hpm.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/histogram2dcontour/legendgrouptitle/font/_shadow.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class ShadowValidator(_plotly_utils.basevalidators.StringValidator):
def __init__(
self,
plotly_name="shadow",
parent_name="histogram2dcontour.legendgrouptitle.font",
**kwargs,
):
super(ShadowValidator, self).__init__(
plo... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@histogram2dcontour@legendgrouptitle@font@_shadow.py@.PATH_END.py |
{
"filename": "BaseModel.py",
"repo_name": "dokester/BayesicFitting",
"repo_path": "BayesicFitting_extracted/BayesicFitting-master/BayesicFitting/source/BaseModel.py",
"type": "Python"
} | import numpy as numpy
from astropy import units
import re
import warnings
from . import Tools
from .Tools import setAttribute as setatt
from .Prior import Prior
from .UniformPrior import UniformPrior
__author__ = "Do Kester"
__year__ = 2024
__license__ = "GPL3"
__version__ = "3.2.1"
__url__ = "https://www.bayesicfitt... | dokesterREPO_NAMEBayesicFittingPATH_START.@BayesicFitting_extracted@BayesicFitting-master@BayesicFitting@source@BaseModel.py@.PATH_END.py |
{
"filename": "computeCRKSPHIntegralInst.cc.py",
"repo_name": "LLNL/spheral",
"repo_path": "spheral_extracted/spheral-main/src/CRKSPH/computeCRKSPHIntegralInst.cc.py",
"type": "Python"
} | text = """
//------------------------------------------------------------------------------
// Explicit instantiation.
//------------------------------------------------------------------------------
#include "Geometry/Dimension.hh"
#include "CRKSPH/computeCRKSPHIntegral.cc"
namespace Spheral {
template std::pair<Dim<... | LLNLREPO_NAMEspheralPATH_START.@spheral_extracted@spheral-main@src@CRKSPH@computeCRKSPHIntegralInst.cc.py@.PATH_END.py |
{
"filename": "synthetic_spectrum_example.py",
"repo_name": "pyspeckit/pyspeckit",
"repo_path": "pyspeckit_extracted/pyspeckit-master/examples/synthetic_spectrum_example.py",
"type": "Python"
} | import numpy as np
import itertools
import pyspeckit
import scipy.stats
import pylab as pl
pl.close('all')
pl.figure(1).clf()
xaxis = np.linspace(-50.,150.,100)
sigma = 10.
center = 50.
synth_data = np.exp(-(xaxis-center)**2/(sigma**2 * 2.))
# Add noise
stddev = 0.1
noise = np.random.randn(xaxis.size)*stddev
error =... | pyspeckitREPO_NAMEpyspeckitPATH_START.@pyspeckit_extracted@pyspeckit-master@examples@synthetic_spectrum_example.py@.PATH_END.py |
{
"filename": "mytests.py",
"repo_name": "GRTLCollaboration/engrenage",
"repo_path": "engrenage_extracted/engrenage-main/source/mytests.py",
"type": "Python"
} | # mytests.py
# File providing test data for the tests - these are solutions where the curvature quantities are known
# so provide a test that everything is working ok
import numpy as np
from source.grid import Grid
from source.uservariables import *
from source.tensoralgebra import *
# This routine gives us somet... | GRTLCollaborationREPO_NAMEengrenagePATH_START.@engrenage_extracted@engrenage-main@source@mytests.py@.PATH_END.py |
{
"filename": "conf.py",
"repo_name": "rychallener/ThERESA",
"repo_path": "ThERESA_extracted/ThERESA-master/doc/conf.py",
"type": "Python"
} | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... | rychallenerREPO_NAMEThERESAPATH_START.@ThERESA_extracted@ThERESA-master@doc@conf.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/layout/smith/realaxis/__init__.py",
"type": "Python"
} | import sys
from typing import TYPE_CHECKING
if sys.version_info < (3, 7) or TYPE_CHECKING:
from ._visible import VisibleValidator
from ._tickwidth import TickwidthValidator
from ._tickvalssrc import TickvalssrcValidator
from ._tickvals import TickvalsValidator
from ._ticksuffix import TicksuffixVal... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@layout@smith@realaxis@__init__.py@.PATH_END.py |
{
"filename": "_idssrc.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/contourcarpet/_idssrc.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator):
def __init__(self, plotly_name="idssrc", parent_name="contourcarpet", **kwargs):
super(IdssrcValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@contourcarpet@_idssrc.py@.PATH_END.py |
{
"filename": "analysis.py",
"repo_name": "PynPoint/PynPoint",
"repo_path": "PynPoint_extracted/PynPoint-main/pynpoint/util/analysis.py",
"type": "Python"
} | """
Functions for point source analysis.
"""
import math
from typing import Optional, Tuple
import numpy as np
from typeguard import typechecked
from scipy.stats import t
from scipy.ndimage import gaussian_filter
from skimage.feature import hessian_matrix
from photutils.aperture import aperture_photometry, Circular... | PynPointREPO_NAMEPynPointPATH_START.@PynPoint_extracted@PynPoint-main@pynpoint@util@analysis.py@.PATH_END.py |
{
"filename": "_colorscale.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/histogram/marker/_colorscale.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator):
def __init__(
self, plotly_name="colorscale", parent_name="histogram.marker", **kwargs
):
super(ColorscaleValidator, self).__init__(
plotly_name=plotly_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@histogram@marker@_colorscale.py@.PATH_END.py |
{
"filename": "canyon_decimation.py",
"repo_name": "enthought/mayavi",
"repo_path": "mayavi_extracted/mayavi-master/docs/source/mayavi/auto/canyon_decimation.py",
"type": "Python"
} | """
Use the greedy-terrain-decimator to display a decimated terrain view.
This example illustrates decimating a terrain. We use the
greedy-terrain-decimator to create a reduced mesh with an optimized grid that
approximates the initial regular grid.
The initial grid is displayed in white, and the optimized grid is dis... | enthoughtREPO_NAMEmayaviPATH_START.@mayavi_extracted@mayavi-master@docs@source@mayavi@auto@canyon_decimation.py@.PATH_END.py |
{
"filename": "_showlegend.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/scatterpolar/_showlegend.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class ShowlegendValidator(_plotly_utils.basevalidators.BooleanValidator):
def __init__(self, plotly_name="showlegend", parent_name="scatterpolar", **kwargs):
super(ShowlegendValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_n... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@scatterpolar@_showlegend.py@.PATH_END.py |
{
"filename": "cm_region.py",
"repo_name": "HERA-Team/hera_mc",
"repo_path": "hera_mc_extracted/hera_mc-main/scripts/cm_region.py",
"type": "Python"
} | #! /usr/bin/env python
# -*- mode: python; coding: utf-8 -*-
# Copyright 2016 the HERA Collaboration
# Licensed under the 2-clause BSD license.
"""
Script to check region(s) of a list of antenna(s).
"""
import argparse
from hera_mc import geo_sysdef
parser = argparse.ArgumentParser()
parser.add_argument("ants", hel... | HERA-TeamREPO_NAMEhera_mcPATH_START.@hera_mc_extracted@hera_mc-main@scripts@cm_region.py@.PATH_END.py |
{
"filename": "_label.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/parcats/dimension/_label.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class LabelValidator(_plotly_utils.basevalidators.StringValidator):
def __init__(self, plotly_name="label", parent_name="parcats.dimension", **kwargs):
super(LabelValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@parcats@dimension@_label.py@.PATH_END.py |
{
"filename": "Neural_Network_and_Data_Loading.ipynb",
"repo_name": "jax-ml/jax",
"repo_path": "jax_extracted/jax-main/docs/notebooks/Neural_Network_and_Data_Loading.ipynb",
"type": "Jupyter Notebook"
} | # Training a simple neural network, with PyTorch data loading
<!--* freshness: { reviewed: '2024-05-03' } *-->
[](https://colab.research.google.com/github/jax-ml/jax/blob/main/docs/notebooks/Neural_Network_and_Data_Loading.ipynb) [![Open in Kag... | jax-mlREPO_NAMEjaxPATH_START.@jax_extracted@jax-main@docs@notebooks@Neural_Network_and_Data_Loading.ipynb@.PATH_END.py |
{
"filename": "hist_plot.py",
"repo_name": "matplotlib/matplotlib",
"repo_path": "matplotlib_extracted/matplotlib-main/galleries/plot_types/stats/hist_plot.py",
"type": "Python"
} | """
=======
hist(x)
=======
Compute and plot a histogram.
See `~matplotlib.axes.Axes.hist`.
"""
import matplotlib.pyplot as plt
import numpy as np
plt.style.use('_mpl-gallery')
# make data
np.random.seed(1)
x = 4 + np.random.normal(0, 1.5, 200)
# plot:
fig, ax = plt.subplots()
ax.hist(x, bins=8, linewidth=0.5, edg... | matplotlibREPO_NAMEmatplotlibPATH_START.@matplotlib_extracted@matplotlib-main@galleries@plot_types@stats@hist_plot.py@.PATH_END.py |
{
"filename": "mpi_test.py",
"repo_name": "rmjarvis/TreeCorr",
"repo_path": "TreeCorr_extracted/TreeCorr-main/tests/mpi_test.py",
"type": "Python"
} | # Copyright (c) 2003-2024 by Mike Jarvis
#
# TreeCorr is free software: redistribution and use in source and binary forms,
# with or without modification, are permitted provided that the following
# conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, this
# list of condi... | rmjarvisREPO_NAMETreeCorrPATH_START.@TreeCorr_extracted@TreeCorr-main@tests@mpi_test.py@.PATH_END.py |
{
"filename": "stratsi_maxvshear.py",
"repo_name": "minkailin/stratsi",
"repo_path": "stratsi_extracted/stratsi-master/stratsi_maxvshear.py",
"type": "Python"
} | import numpy as np
import scipy.optimize
delta = 1e-6
stokes= 0.01
hd = np.sqrt(delta/(stokes+delta))
metal = 0.03
dgmid = metal/hd
eta_hat=0.05
def func(x):
return (x - 1)/(x + 1) - dgmid*np.exp(-x/2.0)
def epsilon(z):
return dgmid*np.exp(-stokes*z*z/(2.0*delta))
def depsilon(z):
return -stokes... | minkailinREPO_NAMEstratsiPATH_START.@stratsi_extracted@stratsi-master@stratsi_maxvshear.py@.PATH_END.py |
{
"filename": "mapping.py",
"repo_name": "ratt-ru/QuartiCal",
"repo_path": "QuartiCal_extracted/QuartiCal-main/quartical/calibration/mapping.py",
"type": "Python"
} | import dask.array as da
import numpy as np
import xarray
from uuid import uuid4
def make_mapping_datasets(data_xds_list, chain):
mapping_xds_list = []
for data_xds in data_xds_list:
mappings = {}
for gain_obj in chain:
# Check whether we are dealing with BDA data.
... | ratt-ruREPO_NAMEQuartiCalPATH_START.@QuartiCal_extracted@QuartiCal-main@quartical@calibration@mapping.py@.PATH_END.py |
{
"filename": "acscourseMountConsumer.py",
"repo_name": "ACS-Community/ACS",
"repo_path": "ACS_extracted/ACS-master/LGPL/CommonSoftware/acscourse/ws/src/acscourseMountConsumer.py",
"type": "Python"
} | #!/usr/bin/env python
# @(#) $Id: acscourseMountConsumer.py,v 1.4 2005/07/04 16:51:58 dfugate Exp $
#*******************************************************************************
# ALMA - Atacama Large Millimiter Array
# (c) Associated Universities Inc., 2002
# (c) European Southern Observatory, 2002
# Copyright by ... | ACS-CommunityREPO_NAMEACSPATH_START.@ACS_extracted@ACS-master@LGPL@CommonSoftware@acscourse@ws@src@acscourseMountConsumer.py@.PATH_END.py |
{
"filename": "_yanchor.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/scatterpolargl/marker/colorbar/_yanchor.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class YanchorValidator(_plotly_utils.basevalidators.EnumeratedValidator):
def __init__(
self,
plotly_name="yanchor",
parent_name="scatterpolargl.marker.colorbar",
**kwargs,
):
super(YanchorValidator, self).__init__(
plotly... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@scatterpolargl@marker@colorbar@_yanchor.py@.PATH_END.py |
{
"filename": "plot.py",
"repo_name": "AstroUGent/shadowfax",
"repo_path": "shadowfax_extracted/shadowfax-master/rundir/testsuite/vacuum/plot.py",
"type": "Python"
} | ################################################################################
# This file is part of Shadowfax
# Copyright (C) 2015 Bert Vandenbroucke (bert.vandenbroucke@gmail.com)
#
# Shadowfax is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as ... | AstroUGentREPO_NAMEshadowfaxPATH_START.@shadowfax_extracted@shadowfax-master@rundir@testsuite@vacuum@plot.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "AOtools/aotools",
"repo_path": "aotools_extracted/aotools-main/aotools/__init__.py",
"type": "Python"
} | from . import astronomy, functions, image_processing, wfs, turbulence, opticalpropagation
from .astronomy import *
from .functions import *
from .fouriertransform import *
from .interpolation import *
from .turbulence import *
from .image_processing import *
from ._version import get_versions
__version__ = get_versio... | AOtoolsREPO_NAMEaotoolsPATH_START.@aotools_extracted@aotools-main@aotools@__init__.py@.PATH_END.py |
{
"filename": "chunkstore_s3.py",
"repo_name": "ska-sa/katdal",
"repo_path": "katdal_extracted/katdal-master/katdal/chunkstore_s3.py",
"type": "Python"
} | ################################################################################
# Copyright (c) 2017-2023, National Research Foundation (SARAO)
#
# Licensed under the BSD 3-Clause License (the "License"); you may not use
# this file except in compliance with the License. You may obtain a copy
# of the License at
#
# ... | ska-saREPO_NAMEkatdalPATH_START.@katdal_extracted@katdal-master@katdal@chunkstore_s3.py@.PATH_END.py |
{
"filename": "Units.ipynb",
"repo_name": "hannorein/REBOUND",
"repo_path": "REBOUND_extracted/REBOUND-main/ipython_examples/Units.ipynb",
"type": "Jupyter Notebook"
} | # Unit convenience functions
For convenience, REBOUND offers simple functionality for converting units. One implicitly sets the units for the simulation through the values used for the initial conditions, but one has to set the appropriate value for the gravitational constant `G`, and sometimes it is convenient to ge... | hannoreinREPO_NAMEREBOUNDPATH_START.@REBOUND_extracted@REBOUND-main@ipython_examples@Units.ipynb@.PATH_END.py |
{
"filename": "invert.py",
"repo_name": "j0r1/GRALE2",
"repo_path": "GRALE2_extracted/GRALE2-master/inversion_examples/example6/invert.py",
"type": "Python"
} | from grale.constants import *
import grale.inversion as inversion
import grale.renderers as renderers
import grale.plotutil as plotutil
from grale.cosmology import Cosmology
import grale.images as images
import numpy as np
# Write the RNG state, in case we want to reproduce the run exactly
# (note that the GRALE_DEBUG... | j0r1REPO_NAMEGRALE2PATH_START.@GRALE2_extracted@GRALE2-master@inversion_examples@example6@invert.py@.PATH_END.py |
{
"filename": "_font.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/graph_objs/sunburst/marker/colorbar/title/_font.py",
"type": "Python"
} | from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Font(_BaseTraceHierarchyType):
# class properties
# --------------------
_parent_path_str = "sunburst.marker.colorbar.title"
_path_str = "sunburst.marker.colorbar.title.font"
_valid_props... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@graph_objs@sunburst@marker@colorbar@title@_font.py@.PATH_END.py |
{
"filename": "faceted_histogram.py",
"repo_name": "mwaskom/seaborn",
"repo_path": "seaborn_extracted/seaborn-master/examples/faceted_histogram.py",
"type": "Python"
} | """
Facetting histograms by subsets of data
=======================================
_thumb: .33, .57
"""
import seaborn as sns
sns.set_theme(style="darkgrid")
df = sns.load_dataset("penguins")
sns.displot(
df, x="flipper_length_mm", col="species", row="sex",
binwidth=3, height=3, facet_kws=dict(margin_titles=... | mwaskomREPO_NAMEseabornPATH_START.@seaborn_extracted@seaborn-master@examples@faceted_histogram.py@.PATH_END.py |
{
"filename": "config.py",
"repo_name": "ivkram/specvizitor",
"repo_path": "specvizitor_extracted/specvizitor-main/specvizitor/config/config.py",
"type": "Python"
} | from dataclasses import dataclass, field
from typing import Any
from ..utils.params import Params
@dataclass
class Catalogue:
filename: str | None = None
translate: dict[str, list[str]] = field(default_factory=dict)
@dataclass
class Image:
filename: str
wcs_source: str | None = None
loader: str... | ivkramREPO_NAMEspecvizitorPATH_START.@specvizitor_extracted@specvizitor-main@specvizitor@config@config.py@.PATH_END.py |
{
"filename": "test_mpl_imshow.py",
"repo_name": "scikit-image/scikit-image",
"repo_path": "scikit-image_extracted/scikit-image-main/skimage/io/tests/test_mpl_imshow.py",
"type": "Python"
} | import numpy as np
import pytest
from skimage import io
from skimage._shared._warnings import expected_warnings
from skimage._shared._dependency_checks import is_wasm
plt = pytest.importorskip("matplotlib.pyplot")
if plt:
plt.switch_backend("Agg")
@pytest.fixture(autouse=True)
def _reset_plugins():
io.rese... | scikit-imageREPO_NAMEscikit-imagePATH_START.@scikit-image_extracted@scikit-image-main@skimage@io@tests@test_mpl_imshow.py@.PATH_END.py |
{
"filename": "_ellip_harm.py",
"repo_name": "waynebhayes/SpArcFiRe",
"repo_path": "SpArcFiRe_extracted/SpArcFiRe-master/scripts/SpArcFiRe-pyvenv/lib/python2.7/site-packages/scipy/special/_ellip_harm.py",
"type": "Python"
} | from __future__ import division, print_function, absolute_import
import threading
import numpy as np
from ._ufuncs import _ellip_harm
from ._ellip_harm_2 import _ellipsoid, _ellipsoid_norm
def ellip_harm(h2, k2, n, p, s, signm=1, signn=1):
r"""
Ellipsoidal harmonic functions E^p_n(l)
These are also kno... | waynebhayesREPO_NAMESpArcFiRePATH_START.@SpArcFiRe_extracted@SpArcFiRe-master@scripts@SpArcFiRe-pyvenv@lib@python2.7@site-packages@scipy@special@_ellip_harm.py@.PATH_END.py |
{
"filename": "logprobs.ipynb",
"repo_name": "langchain-ai/langchain",
"repo_path": "langchain_extracted/langchain-master/docs/docs/how_to/logprobs.ipynb",
"type": "Jupyter Notebook"
} | # How to get log probabilities
:::info Prerequisites
This guide assumes familiarity with the following concepts:
- [Chat models](/docs/concepts/chat_models)
- [Tokens](/docs/concepts/tokens)
:::
Certain [chat models](/docs/concepts/chat_models/) can be configured to return token-level log probabilities representing... | langchain-aiREPO_NAMElangchainPATH_START.@langchain_extracted@langchain-master@docs@docs@how_to@logprobs.ipynb@.PATH_END.py |
{
"filename": "conf.py",
"repo_name": "sibirrer/AstroObjectAnalyser",
"repo_path": "AstroObjectAnalyser_extracted/AstroObjectAnalyser-master/docs/conf.py",
"type": "Python"
} | # -*- coding: utf-8 -*-
#
# complexity documentation build configuration file, created by
# sphinx-quickstart on Tue Jul 9 22:26:36 2013.
#
# This file is execfile()d with the current directory set to its containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# ... | sibirrerREPO_NAMEAstroObjectAnalyserPATH_START.@AstroObjectAnalyser_extracted@AstroObjectAnalyser-master@docs@conf.py@.PATH_END.py |
{
"filename": "line_identify_simple.py",
"repo_name": "igrins/plp",
"repo_path": "plp_extracted/plp-master/igrins/procedures/line_identify_simple.py",
"type": "Python"
} | import numpy as np
import itertools
from scipy.interpolate import interp1d
import scipy.spatial as spatial
import operator
import json
import os
def match_lines1_pixel(cent_list, ref_pix_list):
"""
"""
if len(cent_list):
# find nearest matches
kdtree = spatial.KDTree(cent_list.reshape([... | igrinsREPO_NAMEplpPATH_START.@plp_extracted@plp-master@igrins@procedures@line_identify_simple.py@.PATH_END.py |
{
"filename": "detector.py",
"repo_name": "gwastro/pycbc",
"repo_path": "pycbc_extracted/pycbc-master/pycbc/detector.py",
"type": "Python"
} | # -*- coding: UTF-8 -*-
# Copyright (C) 2012 Alex Nitz
#
#
# 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 pr... | gwastroREPO_NAMEpycbcPATH_START.@pycbc_extracted@pycbc-master@pycbc@detector.py@.PATH_END.py |
{
"filename": "pysimple.py",
"repo_name": "Trovemaster/TROVE",
"repo_path": "TROVE_extracted/TROVE-master/wigxjpf-1.5/example/pysimple.py",
"type": "Python"
} | #!/usr/bin/python
#
# Copyright 2015 Christian Forssen
#
# This file is part of WIGXJPF.
#
# WIGXJPF is free software: you can redistribute it and/or modify it
# under the terms of the GNU Lesser General Public License as
# published by the Free Software Foundation, either version 3 of the
# License, or (at your o... | TrovemasterREPO_NAMETROVEPATH_START.@TROVE_extracted@TROVE-master@wigxjpf-1.5@example@pysimple.py@.PATH_END.py |
{
"filename": "converter.py",
"repo_name": "pandas-dev/pandas",
"repo_path": "pandas_extracted/pandas-main/pandas/plotting/_matplotlib/converter.py",
"type": "Python"
} | from __future__ import annotations
import contextlib
import datetime as pydt
from datetime import (
datetime,
tzinfo,
)
import functools
from typing import (
TYPE_CHECKING,
Any,
cast,
)
import warnings
import matplotlib as mpl
import matplotlib.dates as mdates
import matplotlib.units as munits
imp... | pandas-devREPO_NAMEpandasPATH_START.@pandas_extracted@pandas-main@pandas@plotting@_matplotlib@converter.py@.PATH_END.py |
{
"filename": "test_spectral.py",
"repo_name": "scikit-learn/scikit-learn",
"repo_path": "scikit-learn_extracted/scikit-learn-main/sklearn/cluster/tests/test_spectral.py",
"type": "Python"
} | """Testing for Spectral Clustering methods"""
import pickle
import re
import numpy as np
import pytest
from scipy.linalg import LinAlgError
from sklearn.cluster import SpectralClustering, spectral_clustering
from sklearn.cluster._spectral import cluster_qr, discretize
from sklearn.datasets import make_blobs
from skl... | scikit-learnREPO_NAMEscikit-learnPATH_START.@scikit-learn_extracted@scikit-learn-main@sklearn@cluster@tests@test_spectral.py@.PATH_END.py |
{
"filename": "masksmodels.py",
"repo_name": "jtschindler/sculptor",
"repo_path": "sculptor_extracted/sculptor-main/sculptor/masksmodels.py",
"type": "Python"
} | #!/usr/bin/env python
import os
import glob
import importlib
import numpy as np
import pkg_resources
from astropy import constants as const
from lmfit import Model, Parameters
c_km_s = const.c.to('km/s').value
# ------------------------------------------------------------------------------
# Model functions
# -----... | jtschindlerREPO_NAMEsculptorPATH_START.@sculptor_extracted@sculptor-main@sculptor@masksmodels.py@.PATH_END.py |
{
"filename": "transform.py",
"repo_name": "GeminiDRSoftware/DRAGONS",
"repo_path": "DRAGONS_extracted/DRAGONS-master/gempy/library/transform.py",
"type": "Python"
} | # Copyright(c) 2018-2020 Association of Universities for Research in Astronomy, Inc.
#
"""
transform.py
This module contains classes related to the geometric transformation of
arrays and AstroData objects.
Classes:
Block: a container for array-like objects that are adjacent to each other
and so much be... | GeminiDRSoftwareREPO_NAMEDRAGONSPATH_START.@DRAGONS_extracted@DRAGONS-master@gempy@library@transform.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/funnel/marker/__init__.py",
"type": "Python"
} | import sys
from typing import TYPE_CHECKING
if sys.version_info < (3, 7) or TYPE_CHECKING:
from ._showscale import ShowscaleValidator
from ._reversescale import ReversescaleValidator
from ._opacitysrc import OpacitysrcValidator
from ._opacity import OpacityValidator
from ._line import LineValidator... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@funnel@marker@__init__.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "s-ilic/ECLAIR",
"repo_path": "ECLAIR_extracted/ECLAIR-master/likelihoods/CMB/Planck/PR4/hillipop_TT/__init__.py",
"type": "Python"
} | import glob
import logging
import os
import re
from itertools import combinations
from typing import Optional
import astropy.io.fits as fits
import numpy as np
from . import foregrounds as fg
from . import tools
#############################
### First initialisations ###
#############################
planck_pr4_ro... | s-ilicREPO_NAMEECLAIRPATH_START.@ECLAIR_extracted@ECLAIR-master@likelihoods@CMB@Planck@PR4@hillipop_TT@__init__.py@.PATH_END.py |
{
"filename": "RedClump_GSP-Spec_SF.ipynb",
"repo_name": "gaia-unlimited/gaiaunlimited",
"repo_path": "gaiaunlimited_extracted/gaiaunlimited-main/docs/notebooks/RedClump_GSP-Spec_SF.ipynb",
"type": "Jupyter Notebook"
} | # 🔴 Selecting red clump stars from Gaia DR3 with good GSP-Spec abundances
We start with this query, which selects stars whose location in a colour-absolute magnitude diagram (not corrected for extinction) is within 0.4 mag of the fiducial line corresponding to the red clump:
```sql
select * from
( select ra,... | gaia-unlimitedREPO_NAMEgaiaunlimitedPATH_START.@gaiaunlimited_extracted@gaiaunlimited-main@docs@notebooks@RedClump_GSP-Spec_SF.ipynb@.PATH_END.py |
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