Saravanan666/pypi-org huggingface dataset:
Package: cm2metrics
cm2metricsA lightweight package that analyzes multiple metrics directly from
confusion matrix.FeaturesGet all classes parsing results in nativeDataframeformatPrint all classes or specified class parsing summary in friendly formatOnly requiresnumpyandpandas, without relying on other machine learning packages.Easy to use with a few  APIsSupports16 metricsfor each class:tp: true positivetn:  true negativefp: false positivefn: false negativetpr: true positive ratetnr: true negative ratefpr: false positive ratefnr: false negative rateatc: actual true countafc: actual false countptc: predict true countpfc: predict false countaccruacyprecisionrecallf1GeneralVersion: 0.1Dependency: Python(3.6,3.7.3.8), numpy, pandasInstallpip install cm2metricsUseGeneral useGenerate a confusion matrix#  use scikitlearn
from sklearn.metrics import confusion_matrix

#cm is ndarray, convert to dataframe
cm = confusion_matrix(true_target, pred_target)
df_cm = pd.DataFrame(cm, index=class_names, columns=class_names)

# or, use a randomly generated confusion matrix(for test)
# see details in cm_test.py
class_names = {0:"class0", 1:"class1", 2:"class2"}
df_cm = pd.DataFrame([(1,2,3),(4,5,6),(7,8,9)])
df_cm.rename(index=class_names, columns=class_names, inplace=True)Init a confusion matrix parserfrom cm2metrics.parse_cm import  ConfusionMatrixParser
cm_parser = ConfusionMatrixParser(df_cm)Parse the confusion matrix# parsing result(cm_parsed) is a dataframe
cm_parsed = cm_parser.parse_confusion_matrix()
print(cm_parsed)  

Sample output:

        tp  fp  tn  fn       tpr       fpr       tnr       fnr  atc  afc  ptc  pfc  accuracy  precision    recall        f1
class0   1  28  11   5  0.166667  0.717949  0.282051  0.833333    6   39   12   33  0.644444   0.083333  0.166667  0.111111
class1   5  20  10  10  0.333333  0.666667  0.333333  0.666667   15   30   15   30  0.555556   0.333333  0.333333  0.333333
class2   9  12   9  15  0.375000  0.571429  0.428571  0.625000   24   21   18   27  0.466667   0.500000  0.375000  0.428571


# get class0 true positive
tp = cm_parsed.loc["class0"].at["tp"]Print parsing summary in friendly format# print one class summary by name using class_name parameter
cm_parser.print_summary(class_name="class0")

# print one class summary by index in confusion matrix using class_index parameter
cm_parser.print_summary(class_index=0)

# print all classes summary by not specifying parameters
cm_parser.print_summary()

Sample output for class0 summary:
Summary for class0
TP: 1
TN: 28
FP: 11
FN: 5
TPR: 0.167
TNR: 0.718
FPR: 0.282
FNR: 0.833
Actual true count: 6
Actual false count: 39
Predict true count: 12
Predict false count: 33
Accuracy: 0.644
Precision: 0.083
Recall: 0.167
F1: 0.111LicenseMIT license.
Package: cm2py
cm2pycm2py is a Python package for generating and manipulating save strings for the roblox gameCircuit Maker 2.InstallationUse the package managerpipto install cm2py.pipinstallcm2pyUsageBasic program to generate a line of 8 looping OR gates:importcm2pyascm2length=8save=cm2.Save()blocks=[]foriinrange(length):blocks.append(save.addBlock(cm2.OR,(i,0,0)))### Commented out for clarity.### You should store connections in a list if you want to modify them later.# connections = []foriinrange(length):# connections.append(save.addConnection(blocks[i-1], blocks[i]))save.addConnection(blocks[i-1],blocks[i])# Directly add the connections to the save objectsaveString=save.exportSave()print(saveString)(fromthe loop.py example)ContributingPull requests are welcome. For major changes, please open an issue first
to discuss what you would like to change.LicenseMIT
Package: cm2util
cm2utilcm2utilis a collection of utility modules to aid in the creation of Circuit Maker 2 builds. New modules and features are still being added.InstallationUse the package managerpipto install cm2util.pipinstallcm2utilDocumentationImagefromcm2utilimportImageimage=Image("path/to/image",size=50)print(image.raw)#savecodeprint(image.link)#dpaste link containing savecodeMemoryfromcm2utilimportMemoryCircuitfromcm2utilimportCircuitcircuits=Circuit()@circuits.builddefMux(D0,D1,s):not1=circuits.NOT(s)and1=circuits.AND(D0,not1)and2=circuits.AND(D1,s)or1=circuits.OR(and1,and2)output=or1returnoutputsaveCode=circuits.export(Mux)print(saveCode)Compressfromcm2utilimportCompressdpaste_link=Compress(saveCode)print(dpaste_link)ContributingPull requests are welcome. For major changes, please open an issue first
to discuss what you would like to change.Please make sure to update tests as appropriate.LicenseMIT
Package: cmaclp
cmaThis repository defines a command-line tool to predict (clp) datasets according to a cell meta-atlas (cma). At the present time only the meta-atlas for the cornea has been implemented.Install cmaclp into a conda environment and install with PyPI:$ conda create -n cmaclp python=3.9 pip
$ conda activate cmaclp
$ pip install cmaclpTo see what each of the current functions do you can run these commands:$ SVM_performance --help
$ SVM_prediction --help
$ SVM_import --help
$ SVM_pseudobulk --helpThe documentation will be extended and improved upon in later versions.
Package: cmadb
CM AntiDouble - модуль, написанный для СМ, предназначен для предотвращения запуска дублей приложений. Содержит в себе клиент и сервер. При запуске СМ клиент пытается подключиться к серверу, если безуспешно - программа запускается, затем запускается сервер. Суть в том, что если попытаться еще раз запустить приложение, клиент получит ответ от сервера, а значит, программа уже запущена. Таким образом мы предотвратим двойной запуск СМ.
Package: cmadison
cmadisonBecause I couldn't come up with a better name, its called cmadison... cmadison provides a wrapper
around rmadison which includes information regarding the packages in the Ubuntu cloud-archive in
addition to the traditional sources (e.g. debian, ubuntu, etc).UsageQuery the Ubuntu cloud-archive for package versions:wolsen@chaps:~/work/cmadison/cmadison$ ./cmadison.py nova
 nova | 1:2014.2.3-0ubuntu1.2~cloud0 | juno     | source
 nova | 1:2015.1.1-0ubuntu1~cloud2   | kilo     | source
 nova | 2:12.0.0~b2-0ubuntu2~cloud0  | liberty  | source
 nova | 2012.2.4-0ubuntu3.1~cloud0   | folsom   | source
 nova | 1:2013.1.5-0ubuntu1~cloud0   | grizzly  | source
 nova | 1:2013.2.3-0ubuntu1~cloud0   | havana   | source
 nova | 1:2014.1.5-0ubuntu1.2~cloud0 | icehouse | sourceQuery multiple sources:wolsen@chaps:~/work/cmadison/cmadison$ ./cmadison.py -u cloud-archive,ubuntu,debian nova
cloud-archive:
 nova | 1:2014.2.3-0ubuntu1.2~cloud0 | juno     | source
 nova | 1:2015.1.1-0ubuntu1~cloud2   | kilo     | source
 nova | 2:12.0.0~b2-0ubuntu2~cloud0  | liberty  | source
 nova | 2012.2.4-0ubuntu3.1~cloud0   | folsom   | source
 nova | 1:2013.1.5-0ubuntu1~cloud0   | grizzly  | source
 nova | 1:2013.2.3-0ubuntu1~cloud0   | havana   | source
 nova | 1:2014.1.5-0ubuntu1.2~cloud0 | icehouse | source
ubuntu:
 nova | 2012.1-0ubuntu2                              | precise          | source
 nova | 2012.1.3+stable-20130423-e52e6912-0ubuntu1.4 | precise-security | source
 nova | 2012.1.3+stable-20130423-e52e6912-0ubuntu1.4 | precise-updates  | source
 nova | 1:2014.1-0ubuntu1                            | trusty           | source
 nova | 1:2014.1.3-0ubuntu1.1                        | trusty-security  | source
 nova | 1:2014.1.5-0ubuntu1.2                        | trusty-updates   | source
 nova | 1:2015.1~rc1-0ubuntu1                        | vivid            | source
 nova | 1:2015.1.1-0ubuntu1                          | vivid-updates    | source
 nova | 2:12.0.0~b3-0ubuntu2                         | wily             | source
debian:
 nova | 2012.1.1-18       | wheezy           | source
 nova | 2014.1.3-11       | jessie-kfreebsd  | source
 nova | 2014.1.3-11       | jessie           | source
 nova | 2015.1.0-2~bpo8+1 | jessie-backports | source
 nova | 2015.1.0-8        | stretch          | source
 nova | 2015.1.0-8        | sid              | source
 nova | 1:12.0.0~b3-1     | experimental     | source
Package: cma-es
Covariance Matrix Adaptation Evolution Strategy (CMA-ES)A Tensorflow 2 implementation.What is CMA-ES?The CMA-ES (Covariance Matrix Adaptation Evolution Strategy) is an evolutionary algorithm for difficult non-linear non-convex black-box optimisation problems in continuous domain. It is considered as state-of-the-art in evolutionary computation and has been adopted as one of the standard tools for continuous optimisation in many (probably hundreds of) research labs and industrial environments around the world.The CMA Evolution StrategyInstallationThe package isavailable on PyPIand can be installed with pip:pipinstallcma-esExample Usage1. Define the fitness functionCMA attempts tominimizea user-defined fitness function.Function signature:Args:
  x: tf.Tensor of shape (M, N)

Returns:
  Fitness evaluations: tf.Tensor of shape (M,)WhereMis the number of solutions to evaluate andNis the dimension of a single solution.deffitness_fn(x):"""Six-Hump Camel Functionhttps://www.sfu.ca/~ssurjano/camel6.html"""return((4-2.1*x[:,0]**2+x[:,0]**4/3)*x[:,0]**2+x[:,0]*x[:,1]+(-4+4*x[:,1]**2)*x[:,1]**2)2. Configure CMA-ESfromcmaimportCMAcma=CMA(initial_solution=[1.5,-0.4],initial_step_size=1.0,fitness_function=fitness_fn,)The initial solution and initial step size (i.e. initial standard deviation of the search distribution) are problem specific.The population size is automatically set by default, but it can be overidden by specifying the parameterpopulation_size.For bounded constraint optimization problems, the parameterenforce_boundscan be set, e.g.enforce_bounds=[[-2, 2], [-1, 1]]for a 2D function.3. Run the optimizerThe search method runs until the maximum number of generation is reached or until one of the early termination criteria is met. By default, the maximum number of generations is 500.best_solution,best_fitness=cma.search()The notebookExample 1 - Six Hump Camel Functiongoes into more details, including ways to plot the optimization path such as in the figure below.LoggingA user-defined callback function can be specified to inspect variables during the search.It is mainly intended for logging purpose, e.g:max_epochs=500deflogging_function(cma,logger):ifcma.generation%10==0:fitness=cma.best_fitness()logger.info(f'Generation{cma.generation}- fitness{fitness}')ifcma.termination_criterion_metorcma.generation==max_epochs:sol=cma.best_solution()fitness=cma.best_fitness()logger.info(f'Final solution at gen{cma.generation}:{sol}(fitness:{fitness})')cma=CMA(initial_solution=[1.5,-0.4],initial_step_size=1.0,fitness_function=fitness_fn,callback_function=logging_function,)cma.search(max_epochs)Check out an example logging progress to TensorBoard:tensorboard_example.pyRun on a GPUBy virtue of being written using TensorFlow, it is trivial to run CMA on a GPU:withtf.device('/GPU:0'):cma.search()More examplesJupyter notebooks with examples are available:Example 1 - Six-Hump Camel FunctionExample 2 - Schwefel FunctionExample 3 - Logging to TensorBoardUnit tests provide a few more examples:cma/core_test.pyResourcesCMA-ES at WikipediaThe CMA Evolution StrategyThe CMA Evolution Strategy: A Tutorial
Package: cmagic
Python wrapper for libmagic.Usage# MacOS
$ export MAGIC=/usr/local/Cellar/libmagic/5.39/share/misc/magic.mgc

# Ubuntu
$ export MAGIC=/usr/lib/file/magic.mgcimportcmagic# Database path from MAGIC environment variablem=cmagic.Magic()ifm.check():print("Database is ok")m.load()m.guess_file("/etc/hosts")# 'ASCII text'm.guess_bytes("hello world")# 'ASCII text'# Setting flagsm.set_flags(mime_type=True)m=cmagic.Magic(# Setting flags heremime_type=True)# Trying to find database on the standard pathsm.load(cmagic.find_db())m.guess_file("/etc/hosts")# 'text/plain'm.guess_bytes("hello world")# 'text/plain'asyncio exampleimportasyncioimportcmagicfromthreadingimportlocalmagic_tls=local()defget_instance():globalmagic_tlsifnothasattr(magic_tls,"instance"):m=cmagic.Magic(mime_type=True)m.load(cmagic.find_db())magic_tls.instance=mreturnmagic_tls.instanceasyncdefguess_file(fname):loop=asyncio.get_event_loop()defrun():m=get_instance()returnm.guess_file(fname)returnawaitloop.run_in_executor(None,run)asyncdefguess_bytes(payload):loop=asyncio.get_event_loop()defrun():m=get_instance()returnm.guess_bytes(payload)returnawaitloop.run_in_executor(None,run)if__name__=="__main__":print(asyncio.run(guess_file("/etc/hosts")))# text/plainprint(asyncio.run(guess_bytes(b"\0\0\0\0\0\0\0")))# application/octet-streamInstallationUbuntu/Debianapt-getinstall-ylibmagic1libmagic-mgc# when using manilinux wheelapt-getinstall-ylibmagic-dev# for building from sourcespython3-mpipinstallcmagicCentosyuminstall-yfile-libs# when using manilinux wheelyuminstall-yfile-devel# for building from sourcespython3-mpipinstallcmagicMacOSbrewinstalllibmagicexportCFLAGS="-I$(brew--prefixlibmagic)/include"LDFLAGS="-L$(brew--prefixlibmagic)/lib"python3-mpipinstallcmagic
Package: cmagick
cmagickCmagick is asubprocess-basedsimpleImageMagickinteraction for Python, supporting Python 3.6+ and Linux distributions.The functionalities of ImageMagick implemented in cmagick are:-Converting images to the following formats (bmp,eps,gif,tiff,webp,wbmp,tga,png,jpg,jpeg,hdr,exr)-Resizing pictures with a declarative size-Support path argumentsUsageExamples:To convert imagesfrom cmagick import cmagick

cmagick.convert('website.jpg', 'website.webp')To resize imagesfrom cmagick import cmagick

cmagick.resize('website.jpg','100x100','website.jpg')To convert and save in a defined directoryfrom cmagick import cmagick

cmagick.convert('website.jpg', '/Desktop/newname.webp')To check the current formats availablefrom cmagick import cmagick

print(cmagick.list_formats())PrerequisitesPython 3.6+imagemagick for apt Debian/Ubuntu
ImageMagick for yum RPMInstallationYou can install the package from PyPI:pip install cmagickYou can install the package the GitHub repository:$ git clone git://github.com/aissa-laribi/cmagick.git
$ cd cmagick/
$ python3 setup.py install --userTo Uninstall$ pip uninstall cmagick
Package: cmail
cmailA simple command-line email client!send emailwith attachmentssave contactsInstallationTo install cmail, simply,$ pip install bshareUsageHelp command:$ cmail -h

usage: cmail.py [-h] [-m] [-c] [-r] [-a name email]

A simple command-line email client!

optional arguments:
  -h, --help            show this help message and exit
  -m, --mail            Send mail.
  -c, --contacts        Shows the saved email contacts.
  -r, --reset           Reset contacts list to default.
  -a name email, --add name email
                        Add new contact.To send mail:$ cmail -m

To: example@gmail.com
Subject: test
Text: hi there!
Want to attach any files? (y/n): n
Enter username (press Enter to use default 'me'): indianpythonista@gmail.com
Enter password:
Your mail was sent successfully!To save a contact:$ cmail -a me nikhilksingh97@gmail.com
New contact saved!To show contacts:$ cmail -c

+---------+--------------------------+
| name    | email                    |
+=========+==========================+
| me      | nikhilksingh97@gmail.com |
+---------+--------------------------+
| example | example@example.com      |
+---------+--------------------------+Clear contacts list:$ cmail -r

Contacts list reset to default.
Package: cmake
CMakeis used to control the software compilation
process using simple platform and compiler independent configuration files,
and generate native makefiles and workspaces that can be used in the
compiler environment of your choice.The suite of CMake tools were created by Kitware in response to the need
for a powerful, cross-platform build environment for open-source projects
such as ITK and VTK.The CMake python wheels provideCMake 3.28.3.Latest ReleaseVersionsDownloadsBuild StatusGitHub Actions (Windows, macOS, Linux)PyPIPlatformsThe following platforms are supported with binary wheels:OSArchWindows64-bit32-bitLinux Intelmanylinux2010+ 64-bitmusllinux 64-bitmanylinux2010+ 32-bitmusllinux 32-bitLinux ARMmanylinux2014+ AArch64musllinux AArch64Linux PowerPCmanylinux2014+ ppc64lemusllinux ppc64leLinux IBM Zmanylinux2014+ s390xmusllinux s390xmacOS 10.10+IntelmacOS 11+Apple SiliconThe last version to providemanylinux1wheels was3.22.x.MaintainersHow to update CMake version?How to make a release?MiscellaneousDocumentation:http://cmake-python-distributions.readthedocs.io/en/latest/Source code:https://github.com/scikit-build/cmake-python-distributionsMailing list:https://groups.google.com/forum/#!forum/scikit-buildLicenseThis project is maintained by Jean-Christophe Fillion-Robin from Kitware Inc.
It is covered by theApache License, Version 2.0.CMake is distributed under the OSI-approved BSD 3-clause License.
For more information about CMake, visithttp://cmake.orgHistorycmake-python-distributions was initially developed in September 2016 by
Jean-Christophe Fillion-Robin to facilitate the distribution of project usingscikit-buildand depending on CMake.
Package: cmake-analyzer
CMake AnalyzerCMake Analyzer (cmana) is a tool that helps developers to find common issues
in CMake code. It searches for deprecated commands/keywords, bad codestyle,
potential problems.Installation$ pip install cmake-analyzerUsageThis tool works by bothpython -m cmake_analyzerandcmanaconsole commands.Simple usage pattern:$ cmana -p /some/directory/to/your/projectFull help is available by-hkey as the following:$ cmana -h
usage: cmana [-h] [-c CHECKS [CHECKS ...]] [-v] [--custom-checks PATH]
            (-p PATH | --list-checks) [--exclude EXCLUDE [EXCLUDE ...] |
            --include INCLUDE [INCLUDE ...]]

optional arguments:
    -h, --help            show this help message and exit
    -c CHECKS [CHECKS ...], --checks CHECKS [CHECKS ...]
                            enable checks in the following format: style* legacy*
    -v, --verbose         enable verbose logging for large projects
    --custom-checks PATH  directory with user-defined checks
    -p PATH, --path PATH  path to start check from
    --list-checks         list all available checks
    --exclude EXCLUDE [EXCLUDE ...]
                            filter out files by mask
    --include INCLUDE [INCLUDE ...]
                            include only files by maskLicenseYou may use CMake Analyzer under the terms of the MIT license
described in the enclosedLICENSE.mdfile.
Package: cmake-checker
cmake-checkercmake-checker is a tool to search for violations to 'modern' cmake rules.Usageusage: __main__.py [-h] [--warn-only] [--reporter {console,junit}]
                        [-o OUTPUT_FILE] [--whitelist WHITELIST]
                        PATH [PATH ...]

positional arguments:
  PATH                  Path to the file or directory where the checks should
                        be done

optional arguments:
  -h, --help            show this help message and exit
  --warn-only           Program will return 0 even if violations are found
  --reporter {console,junit}
                        Specify type of reporter to output
  -o OUTPUT_FILE, --output-file OUTPUT_FILE
                        Output results to file with given name
  --whitelist WHITELIST
                        Whitelist file with rules to ignore certain files or
                        dirs (.gitignore style)What&Why tool warns aboutfile(GLOB ...)CMake will not track the dependencies of a new file on disk correctly. If no CMakeLists.txt file changes when a source
is added or removed then the generated build system cannot know when to ask CMake to regenerate.You can't ensure that only files you want are added. Globbing may pick up stray files that you do not want.Functionsadd_compile_optionsadd_compile_definitionslink_librariesadd_definitionsinclude_directoriesFunctions work on directory scope instead of target scope. Every single one of listed functions has
equivalent for target scope which should be used.PropertiesCOMPILE_<LANG>_FLAGSThese properties should be set for a target - not modified globallyClosing commands with clausesendifendfunctionendmacroendforeachExample:macro(foo ...)
...
endmacro(foo)Set/unset includingENVCACHE../..intarget_sourcesfunctionSet/unsetPARENT_SCOPEoutside of function declarationPossibility to disable checkIf you need to disable for any specific reasons checks you can do it using:# cmake-check disable
...
# cmake-check enable
Package: cmake-common
cmake-commonUtilities to help develop C++/CMake projects.DescriptionThis main goal of this project is to make it easier to build (potentially,
cross-compile) Boost and CMake projects using different toolsets.
It does so providing a set of command-line utilities that allow users to
download/build Boost & use it in a CMake project in a consistent way — no
matter the compiler or the target platform.InstallationVia PyPI:pip install cmake-commonAs a submodule:git submodule add https://github.com/egor-tensin/cmake-common.gitAll the scripts provided by the PyPI package are thin wrappers around theprojectpackage modules:ScriptModuleboost-downloadpython3 -m project.boost.downloadboost-buildpython3 -m project.boost.buildproject-buildpython3 -m project.buildToolsetsSupported platform/build system/compiler combinations include, but are not
limited to:PlatformBuild systemCompilerLinuxmakeClangGCCMinGW-w64Windowsmake [1]Clang [2]MinGW-w64msbuildMSVCCygwinmakeClangGCCMinGW-w64Both GNU make and MinGW mingw32-make.clang-cl is supported by Boost 1.69.0 or higher only.All of those are verified continuously by theBoost (toolsets)andExamples
(toolsets)workflows.For a complete list of possible--toolsetparameter values, pass the--help-toolsetsflag to eitherboost-buildorproject-build.UsageBoostDownload & build the Boost libraries in a cross-platform way.$ boost-download 1.72.0
...

$ boost-build -- boost_1_72_0/ --with-filesystem --with-program_options
...Pass the--helpflag to view detailed usage information.CMake projectBuild (and optionally, install) a CMake project.$ project-build --configuration Release --install path/to/somewhere --boost path/to/boost -- examples/simple build/
...

$ ./path/to/somewhere/bin/foo
fooPass the--helpflag to view detailed usage information.common.cmakeUse in a project by puttinginclude(path/to/common.cmake)in CMakeLists.txt.This file aids in quick-and-dirty development bylinking everything (including the runtime) statically by default,setting some useful compilation options (enables warnings, defines common
Windows-specific macros, strips debug symbols in release builds, etc.).Everything is enabled by default (use theCC_*CMake options to opt out).Toolsproject-clang-format.py—clang-formatall C/C++ files in the
project.ctest-driver.py— wrap an executable for testing with CTest;
cross-platformgrep.ExamplesI use this in all of my C++/CMake projects, e.g.aes-toolsandmath-server.DevelopmentMake a git tag:git tag "v$( python -m setuptools_scm --strip-dev )"You can then review that the tag is fine and push w/git push --tags.LicenseDistributed under the MIT License.
SeeLICENSE.txtfor details.