Saravanan666/pypi-org huggingface dataset:
Package: aedev-tpl-app
tpl_app 0.3.7aedev namespace package portion tpl_app: aedev_tpl_add module main module.installationexecute the following command to install the
aedev.tpl_app package
in the currently active virtual environment:pipinstallaedev-tpl-appif you want to contribute to this portion then first forkthe aedev_tpl_app repository at GitLab.
after that pull it to your machine and finally execute the
following command in the root folder of this repository
(aedev_tpl_app):pipinstall-e.[dev]the last command will install this package portion, along with the tools you need
to develop and run tests or to extend the portion documentation. to contribute only to the unit tests or to the
documentation of this portion, replace the setup extras keydevin the above command withtestsordocsrespectively.more detailed explanations on how to contribute to this projectare available herenamespace portion documentationinformation on the features and usage of this portion are available atReadTheDocs.
Package: aedev-tpl-namespace-root
tpl_namespace_root 0.3.13aedev namespace package portion tpl_namespace_root: templates and outsourced files for namespace root projects..installationexecute the following command to install the
aedev.tpl_namespace_root package
in the currently active virtual environment:pipinstallaedev-tpl-namespace-rootif you want to contribute to this portion then first forkthe aedev_tpl_namespace_root repository at GitLab.
after that pull it to your machine and finally execute the
following command in the root folder of this repository
(aedev_tpl_namespace_root):pipinstall-e.[dev]the last command will install this package portion, along with the tools you need
to develop and run tests or to extend the portion documentation. to contribute only to the unit tests or to the
documentation of this portion, replace the setup extras keydevin the above command withtestsordocsrespectively.more detailed explanations on how to contribute to this projectare available herenamespace portion documentationinformation on the features and usage of this portion are available atReadTheDocs.
Package: aedev-tpl-project
tpl_project 0.3.28aedev namespace package portion tpl_project: outsourced Python project files templates.installationexecute the following command to install the
aedev.tpl_project package
in the currently active virtual environment:pipinstallaedev-tpl-projectif you want to contribute to this portion then first forkthe aedev_tpl_project repository at GitLab.
after that pull it to your machine and finally execute the
following command in the root folder of this repository
(aedev_tpl_project):pipinstall-e.[dev]the last command will install this package portion, along with the tools you need
to develop and run tests or to extend the portion documentation. to contribute only to the unit tests or to the
documentation of this portion, replace the setup extras keydevin the above command withtestsordocsrespectively.more detailed explanations on how to contribute to this projectare available herenamespace portion documentationinformation on the features and usage of this portion are available atReadTheDocs.
Package: aedificator
aedificatorPython project scaffolding tool.Installation$pipinstallaedificatorUsageIn the directory where you want the scaffolding to happen, type$aedificateyour_project_nameThis will create a following structure:current_working_directory
├── .dockerignore
├── .flake8
├── .gitignore
├── Makefile
├── README.md
├── src
│   └── your_project_name
│       └── __init__.py
├── tests
│   └── __init__.py
└── tox.iniYou can now start putting your code in thesrc/your_project_namedirectory.Additional options--target-dirchange the directory where the scaffolding happens (default:.)--line-lengthchange the maximum line length to be enforced byBlackandflake8Consult$ aedificate --helpfor up-to-date info.Aedificator comes with preconfigured formatting, linting, type checking and testing
options, leveraging the power oftox. If you do not havetoxinstalled, type$pipinstalltoxNow, use$tox-elintersfor formatting, linting, and type checking (ortox -e format|flake8|mypyfor just one
of them) and$tox-epy37|py38|py39|p310for your test suites.Use$ toxif you want it all. ;)A small note:toxwill fail as long as you have no tests in yourtestsdirectory.
If you like to see green colour, while you still have no tests, limit yourself totox -e linters(and hurry to add some tests)
Package: ae-django-utils
django_utils 0.3.1ae namespace module portion django_utils: helpers for django projects.installationexecute the following command to install the
ae.django_utils module
in the currently active virtual environment:pipinstallae-django-utilsif you want to contribute to this portion then first forkthe ae_django_utils repository at GitLab.
after that pull it to your machine and finally execute the
following command in the root folder of this repository
(ae_django_utils):pipinstall-e.[dev]the last command will install this module portion, along with the tools you need
to develop and run tests or to extend the portion documentation. to contribute only to the unit tests or to the
documentation of this portion, replace the setup extras keydevin the above command withtestsordocsrespectively.more detailed explanations on how to contribute to this projectare available herenamespace portion documentationinformation on the features and usage of this portion are available atReadTheDocs.
Package: ae-droid
droid 0.3.10ae namespace module portion droid: android constants and helper functions.installationexecute the following command to install the
ae.droid module
in the currently active virtual environment:pipinstallae-droidif you want to contribute to this portion then first forkthe ae_droid repository at GitLab.
after that pull it to your machine and finally execute the
following command in the root folder of this repository
(ae_droid):pipinstall-e.[dev]the last command will install this module portion, along with the tools you need
to develop and run tests or to extend the portion documentation. to contribute only to the unit tests or to the
documentation of this portion, replace the setup extras keydevin the above command withtestsordocsrespectively.more detailed explanations on how to contribute to this projectare available herenamespace portion documentationinformation on the features and usage of this portion are available atReadTheDocs.
Package: aedttest
DescriptionThis project aims to provide an Automated Framework to test Ansys Electronics Desktop (AEDT).
Users can set up a suite of tests to validate stability/regression of results between
different versions of Ansys Electronics Desktop.Table of ContentsFeaturesInstallationUsageConfiguration fileCLI CommandsOpen CLI commands HelpExamplesLocal machineGenerate only reference resultsRun comparison between versionsSlurmGenerate only reference resultsRun comparison between versionsLimitationsContributorsFeaturesThe current framework provides the following features:Compare results of XY plots, mesh statistics and simulation time.Web page output format for visual comparisonJSON file output format to support automated workflows and use of test results downstream.Parallel distribution of test projectsCross-platform: support for Windows and LinuxCompatibility with local machine and most known cluster schedulers:
LSF, SGE, Slurm, PBS, Windows HPCControl of required resources for each project and optimized distribution of tasksAutomatic generation of reference results (AEDT versions 2019R1+)InstallationTo install the package use:pipinstallaedttestUsageElectronics Desktop testing framework automatically identifies environment where it was launched. In this chapter we
will show basic examples of starting tests on local machine or on clusters with scheduler. In all scenarios we use
Command Line Interface (CLI).Configuration fileFramework requires configuration file as input. Please see example of a configuration fileconfig_with_comments.tomlto understand how to create a file.You can use bothconfig_with_comments.tomlorconfig_without_comments.tomlas template.CLI CommandsTo expose the available commands use the following command lineOpen CLI commands Helpaedt_test_runner-hExamplesLocal machineTo start test on local machine use following command lineGenerate only reference resultsaedt_test_runner--config-folder=examples/configs--aedt-version=193--only-referenceRun comparison between versionsaedt_test_runner--config-folder=examples/configs--aedt-version=231--reference-folder=reference_folderSlurmGenerate only reference resultssbatch\--job-nameaedttest\--partitionottc01\--export"ALL,ANSYSEM_ROOT193=/apps/software/ANSYS_EM_2019R1/AnsysEM19.3/Linux64,ANS_NODEPCHECK=1"\--nodes2-2--ntasks56\--wrap"aedt_test_runner --config-folder=examples/configs --aedt-version=193 --only-reference"Run comparison between versionssbatch\--job-nameaedttest\--partitionottc01\--export"ALL,ANSYSEM_ROOT222=/ott/apps/software/ANSYS_EM_2022R2_211129/v222/Linux64,ANS_NODEPCHECK=1"\--nodes2-2--ntasks56\--wrap"aedt_test_runner --config-folder=examples/configs --aedt-version=222 --reference-folder=~/reference_folder"LimitationsCurrently, project does not support or partially supports following features:Automatic results creation is possible only for versions 2019R1+LS-DSO is not supportedContributorsIf you would like to contribute to this project, please seeCONTRIBUTE.
Package: ae-dynamicod
dynamicod 0.3.14ae namespace module portion dynamicod: dynamic execution of code blocks and expressions.installationexecute the following command to install the
ae.dynamicod module
in the currently active virtual environment:pipinstallae-dynamicodif you want to contribute to this portion then first forkthe ae_dynamicod repository at GitLab.
after that pull it to your machine and finally execute the
following command in the root folder of this repository
(ae_dynamicod):pipinstall-e.[dev]the last command will install this module portion, along with the tools you need
to develop and run tests or to extend the portion documentation. to contribute only to the unit tests or to the
documentation of this portion, replace the setup extras keydevin the above command withtestsordocsrespectively.more detailed explanations on how to contribute to this projectare available herenamespace portion documentationinformation on the features and usage of this portion are available atReadTheDocs.
Package: aeecde
Adaptive Differential Evolution based on Exploration and Exploitation Control (AEEC-DE)Click here to read the full paper online.AbstractSearch operator design and parameter tuning are essential parts of algorithm design. However, they often involve trial-and-error and are very time-consuming. A new differential evolution (DE) algorithm with adaptive exploration and exploitation control (AEEC-DE) is proposed in this work to tackle this challenge. The proposed method improves the performance of DE by automatically selecting trial vector generation strategies (both mutation and crossover operators) and dynamically generating the associated control parameter values. A probability-based exploration and exploitation measurement is introduced to estimate whether the state of each newly generated individual is in exploration or exploitation. The state of historical individuals is used to assess the exploration and exploitation capabilities of different generation strategies and parameter values. Then, the strategies and parameters of DE are adapted following the common belief that evolutionary algorithms (EAs) should start with exploration and then gradually change into exploitation. The performance of AEEC-DE is evaluated through experimental studies on a set of test problems and compared with several state-of-the-art adaptive DE variants.KeywordsAlgorithm Configuration, Differential Evolution, Parameter Control, Exploration and ExploitationAbout this repositoryHow to installpip install aeecdeHow to useimport aeecdeTutorialClick here to read the full tutorial.CitationYou may cite this work in a scientific context as:H. Bai, C. Huang and X. Yao, "Adaptive Differential Evolution based on Exploration and Exploitation Control", 2021 IEEE Congress on Evolutionary Computation (CEC), 2021, pp. 41-48, doi:10.1109/CEC45853.2021.9504876Or copy the folloing BibTex file:@INPROCEEDINGS{AEECDE,
author    ={Hao Bai and Changwu Huang and Xin Yao},
title     ={Adaptive Differential Evolution based on Exploration and Exploitation Control},
booktitle ={2021 IEEE Congress on Evolutionary Computation (CEC)},
volume    ={},
number    ={},
pages     ={41-48},
year      ={2021},
url       ={https://ieeexplore.ieee.org/abstract/document/9504876},
doi       ={10.1109/CEC45853.2021.9504876},}Ordownload the citation in RIS file (through IEEE Xplore).Related workOnline algorithm configuration for differential evolution algorithm (OAC-DE)ContactAsst. Prof. Changwu HUANG
Package: ae-enaml-app
enaml_app 0.3.27ae namespace package portion enaml_app: enaml application widgets, helper functions and classes.installationexecute the following command to install the
ae.enaml_app package
in the currently active virtual environment:pipinstallae-enaml-appif you want to contribute to this portion then first forkthe ae_enaml_app repository at GitLab.
after that pull it to your machine and finally execute the
following command in the root folder of this repository
(ae_enaml_app):pipinstall-e.[dev]the last command will install this package portion, along with the tools you need
to develop and run tests or to extend the portion documentation. to contribute only to the unit tests or to the
documentation of this portion, replace the setup extras keydevin the above command withtestsordocsrespectively.more detailed explanations on how to contribute to this projectare available herenamespace portion documentationinformation on the features and usage of this portion are available atReadTheDocs.
Package: aef
Audio effects frameworkThe audio effects framework is a python module that allows for easy use of audio effects created in puredata (https://puredata.info).DependenciesThese installs are needed for core functionality:pip install watchdog
pip install aitpi
sudo apt install puredata
sudo apt install jackdDepending on your use case, these packages may be needed:For aitpi keyboard input -pip install pynputFor the GUI app -pip install PyQt6For bluetooth -sudo apt install bluez python-bluezUseThe audio effect framework was built upon the AITPI system (https://github.com/c3n3/AITPI). This system is used in order to control the application and modification of the audio effects framework. It allows inputs (currently supported keyboard input, raspberry pi GPIO buttons, and raspberry pi GPIO encoders) to be written in JSON to control what audio effects are applied in real time. These inputs are to be expanded over time.RunningIn order to run the aef:import aef
import aitpi

# Any application setup...

aef.run(effectsFolder, recordingsFolder, presetsFolder, sys.argv)
inputJson = os.path.join(dirname, 'your_input.json')
aitpi.initInput(inputJson)And when done:aef.shutdown()Aef will automatically link into the jack audio system and will automatically start receiving input.NOTE: Currently the setup is to use Qjackctl with a preset named 'guitar-module'. This setup must be done before hand. This will be ammended in the future.Setting up AITPISeehttps://github.com/c3n3/AITPI. The possible commands to link to are all listed out in the temp folder.NOTE: wherever you run the aef, it will create a ./temp/ folder in the local directory. This will contain all temporary files such as recordings, puredata temp files, and the command registry. This allows for persistent saves, if everything is run from the same directories.Currently you can retrieve these commands by calling:aef.getCommands()You can also change the input links on the fly by calling:aef.changeLink(inputName, newCommandToLink)PresetsYou can create presets that specify multiple audio effects to apply at once. These are simply text files that list out the names of all effects. You can see examples of these in the default_presets folder. These will show up automatically in the command registry if they are put into the 'presetsFolder' (specified inaef.run).EffectsYou can create new puredata patches in input them into the 'effectsFolder' (specified inaef.run). These must follow a specific format in puredata in order to be linked properly. TODO: Specify puredata format rules.RecordingsRecordings are created with the 'save' command. It will save whatever was the last 'record' audio into the recordings folder (as specified inaef.run). This will then be added to the command list in so that you can replay the recording with a keystroke (based on AITPI).
Package: aefaalgo
AEFAAEFA is a Python library for AEFA: Artificial electric field algorithm, a novel algorithm for solving non-linear optimization problems.
The details of the algorithm can be found here at:https://medium.com/artifical-mind/artificial-electric-field-algorithm-for-optimization-fb6f57f413b4You may access the paper for the same athttp://www.sciencedirect.com/science/article/pii/S2210650218305030InstallationUse the package managerpipto install aefaalgo.pipinstallaefaalgoUsagefromaefaalgo.aefa_optimizeimportaefa# returns optimum fitness value and space coordinatesaefa().optimize(N,max_iter,func_num)Keywordarguments:N:numberofparticlesinsearchspacemax_iter:numberofiterationsfunc_num:SpecifiesthefunctiontobeoptimizedOptionalKeywordArguments:tag:specifieswhetherwewantmaximaorminima.0bydefaultformaximization.Specifytag=1forminimization.Rpower:exponentforthenormalizeddistancebetweentheparticles.Defaultvalue1FCheck:Thisfactorensuresthatonly2-6%chargesapplyforcetoothersinthelastiterations.SettoTruebydefault.show_plot:Trueifyouwanttovisualizeconvergencetotheoptimum,Falseotherwiseanddefault.ContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.LicenseMIT
Package: ae-ffmpeg
AE-FFmpegStatic FFmpeg and FFprobe binaries for use with Auto-Editor.Installpip install ae-ffmpegCopyrightThe FFmpeg/FFprobe binaires used are under the LGPLv3. Only libraries that are compatible with the LGPLv3 are included.How to Compile on MacOSUsehttps://github.com/WyattBlue/ffmpeg-build-script/How to Compile on WindowsI usehttps://github.com/m-ab-s/media-autobuild_suiteto compile on Windows.Is There a Linux Build?Linux distros generally already ship ffmpeg, so having another ffmpeg would be redundant.MacOS flags--enable-videotoolbox --enable-libdav1d --enable-libvpx --enable-libzimg --enable-libmp3lame --enable-libopus --enable-libvorbis --disable-debug --disable-doc --disable-shared --disable-network --disable-indevs --disable-outdevs --disable-sdl2 --disable-xlib --disable-ffplay --enable-pthreads --enable-static --enable-version3 --extra-cflags=-I/Users/wyattblue/projects/ffmpeg-build-script/workspace/include --extra-ldexeflags= --extra-ldflags=-L/Users/wyattblue/projects/ffmpeg-build-script/workspace/lib --extra-libs='-ldl -lpthread -lm -lz' --pkgconfigdir=/Users/wyattblue/projects/ffmpeg-build-script/workspace/lib/pkgconfig --pkg-config-flags=--static --prefix=/Users/wyattblue/projects/ffmpeg-build-script/workspace --extra-version=5.0.1
Package: ae-files
files 0.3.22ae namespace module portion files: generic file object helpers.installationexecute the following command to install the
ae.files module
in the currently active virtual environment:pipinstallae-filesif you want to contribute to this portion then first forkthe ae_files repository at GitLab.
after that pull it to your machine and finally execute the
following command in the root folder of this repository
(ae_files):pipinstall-e.[dev]the last command will install this module portion, along with the tools you need
to develop and run tests or to extend the portion documentation. to contribute only to the unit tests or to the
documentation of this portion, replace the setup extras keydevin the above command withtestsordocsrespectively.more detailed explanations on how to contribute to this projectare available herenamespace portion documentationinformation on the features and usage of this portion are available atReadTheDocs.
Package: aef-nattanon-py
aef-nattanon-py-libInstall$pipinstallaef-nattanon-pySimple Demo# Import aef_nattanon_py from your libraryimportaef_nattanon_pyasaefimportcv2# Multiplicationmultiplication=aef.Multiplication(2)print(multiplication.multiply(5))# 10# direct_by_img_pathmyDetector=aef.Detector('coco.names','yolov3-tiny.cfg','yolov3-tiny.weights')myDetector.detact_by_img_path('my-photo.jpeg')cv2.imshow("Image",myDetector.detect_img)cv2.waitKey(100)# direct_by_framecap=cv2.VideoCapture(0)whileTrue:_,frame=cap.read()myDetector.detact_by_frame(frame)cv2.imshow("Image",myDetector.detect_img)cv2.waitKey(1)cv2.destroyAllWindows()# YoloV3DirectormyDetector=aef.YoloV3Detector()cap=cv2.VideoCapture(0)whileTrue:_,frame=cap.read()myDetector.detect_by_frame(frame)cv2.imshow("Image",myDetector.detect_img)cv2.waitKey(1)cv2.destroyAllWindows()
Package: aefReader
инструкция по библиотеке "aefReader"классы:Readметоды:about()метод "about":выводит текст, рассказывающий о расширении файла .aefкласс "Read":аргументы: file_name, notOut=False, ignoringMeta=Falsefile_name - обязательный аргумент. Путь до файла, который нужно открыть.

notOut - необязательный аргумент. Если True, то при попытке вывода информации из открытого файла вызывает исключение

ignoringMeta - необязательный аргумент. Если True, то, при открытии файла, его метаданные будут игнорироваться и попытка их вывода приведёт к вызову исключенияметоды класса:Out() - возвращает строку с декодированным текстом

ByteOut(array=True) - если array=True, то возвращает массив байтов открытого файла в шеснадцатиричной кодировке. Если array=False, то возвращает строку байтов в шеснадцатиричной кодировке

MetaOut(datatime_mode=True) - возвращает дату создания файла, если она есть, в противном случае вызывает исключение. Если datatime_mode=True, то возвращает дату в виде экземпляра класса datatime, иначе возвращает дату в виде строки в формате "год-месяц-день часы-минуты"пример кода с использованием библиотеки:import aefReader  # импортирование библиотеки

	aef_file = aefReader.Read("C:/my_folder/file.aef")  # открытие файла file.aef
	print(aef_file.Out())  # вывод текста из этого файла
	#
	for byte_in_array in aef_file.ByteOut():  # поочерёдный вывод байтов файла
			print(byte_in_array)исключения:Location - вызывается если указанный файл не найден

Access - вызывается, если скрипт не имеет доступ к файлу

FileType - вызывается, если открываемый файл определяется как не формата aef

NoneMeta - вызывается при попытке вывода отсутствующих или игнорируемых метаданных

OutBlock - вызывается при попытке вывода содержимого файла