Saravanan666/pypi-org huggingface dataset:
Package: icosphere
Geodesic icosahedronCreating geodesic icosahedron given subdivision frequency.InstallationInstall the module usingpip install icosphereor clone the repository.Usefromicosphereimporticospherenu=5# or any other integervertices,faces=icosphere(nu)ExamplesCheck the examples inicosphere github, python script uses matplotlib for visualization, and jupyter notebook uses plotly.Why use subdivision frequency?For a certain subdivision frequencynu, each edge of the icosahedron will be split intonusegments, and each face will be split intonu**2faces.This is different than a more common approach which recursively applies a subdivision withnu = 2, for example as used in pytorch3dico_sphere, pymeshlabsphere, trimeshicosphere, and PyMeshgenerate_icosphere.The advantage of using the subdivision frequency, compared to the recursive subdivision, is in controlling the mesh resolution. Mesh resolution grows quadratically with subdivision frequencies while it grows exponentially with iterations of the recursive subdivision. To be precise, using the recursive subdivision, the number of vertices and faces in the resulting icosphere grows with iterationsiterasnr_vertex = 12 + 10 * (4**iter -1)andnr_face = 10 * 4**iterwhich gives a sequence of mesh vertices12, 42, 162, 642, 2562, 10242, 40962, 163842, 655362, 2621442, 10485762...Notice for example there is no mesh having between 2562 and 10242 vertices. Using subdivision frequency, the number of vertices and faces grows withnuas
Notice for example there is no mesh having between 2562 and 10242 vertices. Using subdivision frequency, the number of vertices and faces grows withnuasnr_vertex = 12 + 10 * (nu**2 -1)andnr_face = 20 * nu**2which gives a sequence of mesh vertices12, 42, 92, 162, 252, 362, 492, 642, 812, 1002, 1212, 1442, 1692, 1962,
 2252, 2562, 2892, 3242, 3612, 4002, 4412, 4842, 5292, 5762, 6252, 6762,
 7292, 7842, 8412, 9002, 9612, 10242...Now there is 15 meshes having between 2562 and 10242 vertices. The advantage is even more pronounced when using higher resolutions.The code was originally developed forthis work.
Package: iCount
iCount: protein-RNA interaction analysisiCount is a Python module and associated command-line interface (CLI),
which provides all the commands needed to process iCLIP data on
protein-RNA interactions and generate:demultiplexed and adapter-trimmed FASTQ files,BAM files with mapped iCLIP reads,identified protein-RNA cross-linked sites, saved to BED files,peaks composed of statistically significant cross-linked sites, saved
to BED files,clusters of significant cross-linked sites, saved to BED files,grouping of individual replicate experiments,RNAmap generation showing the positional distribution of cross-linked
sites relative to genomic landmarks,kmer enrichment analysis,and other.You may start with thetutorialor
dive into thedocumentation.AuthorsiCount is developed and supported byTomaž Curkfrom theBioinformatics Laboratoryat theUniversity of Ljubljana,Faculty of Computer
and Information Scienceand in
collaboration with the laboratory ofJernej
Ule.The development started in late 2008 when Tomaž Curk and Gregor Rot
wrote a first prototype of iCount. In mid-2016,Jure
ZmrzlikarfromGenialishelped refactoring and improving
the code, which is now available here. For details and full
acknowledgments, see thehow to
citesection in
the documentation.ContributingContributions (pull requests) are welcome! Please submit your
contributions by following theguidelines.Reporting problemsUse theissues pageto
report issues and request enhancements. Before submitting, please check
the list of already reported issues. Also, have a look at theFAQto see if the
problem has been addressed already.
Package: iCount-Mini
iCount-MiniThis is a fork of iCount maintained by members ofJernej Ule'sgroup, focussing on the peak calling features of iCount.Run commands using:iCount-Mini <command>Note on small differences of terminology between iCount-Mini and iCountIn iCount-Mini, sigxls = iCount peaks and iCount-Mini peaks = iCount clusters. This is to bring the terminology more in line with the rest of the field.In iCount-Mini RNA-maps have been renamed to 'metagene', to distinguish these plots which include only CLIP data from other RNA-maps which group crosslinks into categories dependent on orthogonal data, such as alternatively spliced exons.iCount: protein-RNA interaction analysisiCount is a Python module and associated command-line interface (CLI), which provides all the commands needed to process iCLIP data on protein-RNA interactions and generate:demultiplexed and adapter-trimmed FASTQ filesBAM files with mapped iCLIP readsidentified protein-RNA cross-linked sites, saved to BED filesstatistically significant cross-linked sites, saved to BED filespeaks of significant cross-linked sites, saved to BED filesgrouping of individual replicate experimentsmetagene generation showing the positional distribution of cross-linked sites relative to genomic landmarkskmer enrichment analysisYou may start with thetutorialor dive into thedocumentation.iCount-Mini AuthorsiCount-Mini is maintained by members ofJernej Ule'sgroup.iCount AuthorsiCount is developed and supported byTomaž Curkfrom theBioinformatics Laboratoryat theUniversity of Ljubljana,Faculty of Computer and Information Scienceand in collaboration with the laboratory ofJernej Ule.The development started in late 2008 when Tomaž Curk and Gregor Rot wrote a first prototype of iCount.
In mid-2016,Jure ZmrzlikarfromGenialishelped refactoring and improving the code, which is now available here.DevelopmentTo install a development version of iCount-Mini, use this command.
It's recommended to do this within a Python virtual environment.pipinstall--upgrade-rrequirements-rtd.txt-e.
Package: icoutil
IcoUtilA simple Python library to create.icofiles (Windows icon file format) from.pngfiles.Table of contentsInstallUsageAs a libraryAs a CLI programRemarksCreatorLicenseInstallUse thePyPi.orgpackage index:pip3installicoutilUsageAs a libraryTwo ways to use the library:Creating a.icofile from a single directory that contains multiple.pngfiles:importicoutilico=icoutil.IcoFile()ico.add_png_dir('path/to/dir')ico.write('output.ico')Creating a.icofile from multiple.pngfiles:importicoutilico=icoutil.IcoFile()ico.add_png('path/to/image1.png')ico.add_png('path/to/image2.png')ico.add_png('path/to/image3.png')ico.add_png('...')ico.write('output.ico')As a CLI programTwo ways to use the CLI:Creating a.icofile from a single directory that contains multiple.pngfiles:icoutil--output"icon.io""path/to/dir"Creating a.icofile from multiple.pngfiles:icoutil--output"icon.io""path/to/image1.png""path/to/image2.png""path/to/image3.png"...RemarksThe file specification can be readhere.The following sizes are used by Windows, but not all required:16×1620×2024×2432×3240×4048×4864×6496×96128×128256×256This library won't consider sizes outside the ones specified above.The maximum allowed size is 256×256 pixels.CreatorOlivier Cléro|email|website|github|gitlabLicenseThis project is available under the MIT license. See theLICENSEfile for more info.
Package: icp10125
ICP10125 Barometric Pressure & Temperature SensorPre-requisitesYou must enable:i2c:sudo raspi-config nonint do_i2c 0You can optionally runsudo raspi-configor the graphical Raspberry Pi Configuration UI to enable interfaces.InstallingStable library from PyPi:Just runpip3 install icp10125In some cases you may need to usesudoor install pip with:sudo apt install python3-pipLatest/development library from GitHub:git clone https://github.com/pimoroni/icp10125-pythoncd icp10125-pythonsudo ./install.shChangelog0.0.1Initial Release
Package: ic-parent-api
Infinite Campus Parent APIThis is an async wrapper for theInfinite Campus API.  There are a few types of objects this will retrieve based on the assumption that you are a parent with students enrolled with Canvas.The types of objects that can be returned include:StudentsCoursesAssignmentsTermsThis module is provided for use with the Home Assistant custom integrationInfinite Campushowever it could be useful as a standalone module for your own projects as well.InstallingTo install the module use:python3-mpipinstallic-parent-apiUsageAt the login page inspect the page with developer tools and search for the hidden input with the nameappName. Like in the image below.Example usage to get students, printing first names:importasynciofromic_parent_apiimportInfiniteCampusbase_url="https://school.infinitecampus.com"username="myusername"password="myp4ssw0rd!"district="schooldistrict"#known as appName to infinitecampusasyncdefget_students():client=InfiniteCampus(f"{base_url}",f"{username}",f"{password}",f"{district}")returnawaitclient.students()students=asyncio.run(get_students())forstudentinstudents:print(student.firstname)
Package: icpd
icpdicpd is <>. I created icpd to <>. This is valuable because <_>.icpd is similar to/inspired by <>, <>, <>. The distinguishing feature of icpd its ability to <>.If this project delivers value to you, I ask that youprovide feedback, makecode contributions, and/orpay me.Repositoryhttps://codeberg.org/Fresh2dev/icpdRepo Mirrorhttps://www.Fresh2.dev/code/r/icpdDocumentationhttps://www.Fresh2.dev/code/r/icpd/iLicensehttps://www.Fresh2.dev/code/r/icpd/i/licenseChangeloghttps://www.Fresh2.dev/code/r/icpd/i/changelogContributinghttps://www.Fresh2.dev/code/r/icpd/i/contributingProject Boardhttps://codeberg.org/Fresh2dev/icpd/projectsIssueshttps://codeberg.org/Fresh2dev/icpd/issuesFundinghttps://www.Fresh2.dev/tipTo learn more,read the docsand find examples in the page ofrecipes.View other projects by Fresh2.dev @https://www.Fresh2.dev/projects.
Package: icpmsflow
icpmsflowPackage to work with icpms dataFree software: NIST licenseDocumentation:https://icpmsflow.readthedocs.io.InstallationThis project is available on pypi and conda in two flavors.  The core package includes only the
packages needed to perform the data analysis.  This can be installed from pip with$pipinstallicpmsflowor from conda with$condainstall-cconda-forge-cwpk-nisticpmsflowOptionally, include a-n {env-name}to specify the install environment.To install the optional plotting/jupyter dependencies, use either$pipinstallicpmsflow[all]or$condainstall-cconda-forge-cwpk-nisticpmsflow-allIf you prefer to install from github, use either$pipinstallgit+https://github.com/wpk-nist-gov/icpmsflow.git@developfor basic install, or$pipinstall'git+https://github.com/wpk-nist-gov/icpmsflow.git@develop#egg=icpmsflow[all]'Example usageSee demo notebook :demoExample dataset :example <https://github.com/wpk-nist-gov/icpmsflow/blob/develop/notebooks/example.tgz?raw=true>_FeaturesTODOCreditsThis package was created withCookiecutterand thewpk-nist-gov/cookiecutter-pypackageProject template forked fromaudreyr/cookiecutter-pypackage.History0.0.1 (2021-04-03)First release on PyPI.This software was developed by employees of the National Institute of Standards
and Technology (NIST), an agency of the Federal Government. Pursuant to title 17
United States Code Section 105, works of NIST employees are not subject to
copyright protection in the United States and are considered to be in the public
domain. Permission to freely use, copy, modify, and distribute this software and
its documentation without fee is hereby granted, provided that this notice and
disclaimer of warranty appears in all copies.THE SOFTWARE IS PROVIDED ‘AS IS’ WITHOUT ANY WARRANTY OF ANY KIND, EITHER
EXPRESSED, IMPLIED, OR STATUTORY, INCLUDING, BUT NOT LIMITED TO, ANY WARRANTY
THAT THE SOFTWARE WILL CONFORM TO SPECIFICATIONS, ANY IMPLIED WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, AND FREEDOM FROM
INFRINGEMENT, AND ANY WARRANTY THAT THE DOCUMENTATION WILL CONFORM TO THE
SOFTWARE, OR ANY WARRANTY THAT THE SOFTWARE WILL BE ERROR FREE. IN NO EVENT
SHALL NIST BE LIABLE FOR ANY DAMAGES, INCLUDING, BUT NOT LIMITED TO, DIRECT,
INDIRECT, SPECIAL OR CONSEQUENTIAL DAMAGES, ARISING OUT OF, RESULTING FROM, OR
IN ANY WAY CONNECTED WITH THIS SOFTWARE, WHETHER OR NOT BASED UPON WARRANTY,
CONTRACT, TORT, OR OTHERWISE, WHETHER OR NOT INJURY WAS SUSTAINED BY PERSONS OR
PROPERTY OR OTHERWISE, AND WHETHER OR NOT LOSS WAS SUSTAINED FROM, OR AROSE OUT
OF THE RESULTS OF, OR USE OF, THE SOFTWARE OR SERVICES PROVIDED HEREUNDER.Distributions of NIST software should also include copyright and licensing
statements of any third-party software that are legally bundled with the code in
compliance with the conditions of those licenses.
Package: icpp-candid
C++ Candid LibraryThe C++ Candid Library oficpp-proAPI ReferenceThe C++ Candid Library is extensively tested in ourQA Canister.If you want to contribute, please reach out.How to useC++ Smart ContractsTo write a C++ smart contract that runs in a Canister, you do not useicpp-candiddirectly, but you install icpp-pro, which is a full-blown C++ Canister Development Kit.Simplyinstall&Get Started!C++ Rich ClientsIf you want to use the C++ Candid Library in your Rich Client, you need to include it in your application and then compile it to a native executable.We already do this ourselves as part oficpp-proto enable interactive debugging with VS Code, as describedhere.The command we use is:icppbuild-nativeWhich uses the Clang++ compiler to create a native debug executable namedmockic.exeSupportFor support, kindly create a GitHub Issue as outlined in theSupportdocumentation page.
Package: icpyedu
ICPyEduICPyEduis a tool for Digital Signatures using ICPEdu Certificate. Thispackagewas developed as a complementary artifact to the completion of the course work of the studentKemuel dos Santos Rochato obtain the Bachelor's degree in Computer Engineering.ICPyEduis a library for educational purposes and allows signing documents in.pdfformat, as well as verifying the digital signature.How to install the libraryTo install the library, just run the command below:pipinstallicpyeduHow to import library classes and methodsTo use the features of thepackage, import with the following code:fromicpyeduimportsignerTo instantiate the class responsible for the digital signature methods, just declare a variable receivingSignas follows:var=signer.Sign()To instantiate the class responsible for the digital signature verification methods, just declare a variable receivingVerifieras follows:var=signer.Verify()Finally, to use it to sign a pdf, just call thesignFilefunction passing the requested parameters, for example:var.signFile("email","password","filePath","certificatePath")Similarly, to verify a pdf, just call theverifySignaturefunction passing the requested parameters, for example:var.verifySignature("pdf","certifying authority_1","certifying authority_2")Certificate authority certificates are files that come with the personal certificate exported by ICPEdu
Package: icrop
introsuppose you want to make a comand line tool called icrop.
it accept integer as numbers
ouput carrots we need to feedex:
	cmd> icrop 2 
	ouput: 4we can get the output by two ways:command lineicrop2call python moudlepython-microp2best practice schemaenvGenerated bymake envThis is first step you need to do in any python projectit will create a virtual envauto source itinstall requirements for the start uptestrunmake testrunmake runwill run in module modemake mainwill run in normal modeYou can see thatmain.pyandicrop/__main__.pyare the same  content file.why do we needmain.py?
It is eay to make an  entry in IDE , like intellij.Could I just use__main__.pyto run  like this?pythonicrop/__main__.pyYou cound not.That is because the top-level package problem.Ex:python main.py 
top-level package is the same as main.py

python src/func/main.py  
top-level package is the same as main.py, aka func 
top-level package is the folder where you run this command fromSo , whyicrop/__main__.pydoes not work?because top-level package is icrop now.loggingAlways use logging for log print,dont useprintlogging config is controlled bylogging.yml, which can control every module level callsetup_logging` in main file (ra)make moduleupdate readmeput moudle in the folder parallel with logx folder.logxyour_modulepacking module or cmdlocalfor quick test purposeinstall:pip install .uninstall:pip uninstall <module_name>make install
make uninstallupload to test or prod PYPI serverupload to test server:make upload-to-testupload to prod server:make upload-to-prodtest and coveragepure testmake testtest with coveragemake coverage
Package: ics
Original repository(GitHub) -Bugtracker and issues(GitHub) -PyPi package(ics) -Documentation(Read The Docs).Ics.py is a pythonic and easy iCalendar library.
Its goals are to read and write ics data in a developer friendly way.iCalendar is a widely-used and useful format but not user friendly.
Ics.py is there to give you the ability of creating and reading this
format without any knowledge of it.It should be able to parse every calendar that respects therfc5545and maybe some more…
It also outputs rfc compliant calendars.iCalendar (file extension.ics) is used by Google Calendar,
Apple Calendar, Android and many more.Ics.py is available for Python>=3.6 and is Apache2 Licensed.Quickstart$pipinstallicsfromicsimportCalendar,Eventc=Calendar()e=Event()e.name="My cool event"e.begin='2014-01-01 00:00:00'c.events.add(e)c.events# [<Event 'My cool event' begin:2014-01-01 00:00:00 end:2014-01-01 00:00:01>]withopen('my.ics','w')asmy_file:my_file.writelines(c.serialize_iter())# and it's done !More examples are available in thedocumentation.DocumentationAll thedocumentationis hosted onreadthedocs.organd is updated automatically
at every commit.QuickstartAPIAboutContributeContribution are welcome of course! For more information, seecontributing.Testing & Docs# setup virtual environment$sudopipinstallvirtualenv$virtualenvve$sourceve/bin/activate# tests$pipinstall-rrequirements.txt$pipinstall-rdev/requirements-test.txt$pythonsetup.pytest# tests coverage$pipinstall-rrequirements.txt$pipinstall-rdev/requirements-test.txt$pythonsetup.pytest$coveragehtml$firefoxhtmlcov/index.html# docs$pipinstall-rrequirements.txt$pipinstall-rdev/requirements-doc.txt$cddoc$makehtmlLinksrfc5545Vulgarised RFC
Package: ics2caldav
Module to help importing .ics files to CalDAV server.InstallationYou can install the most recentics 2 CalDAV Importerversion using pip:pip install ics2caldavUsageseeexamples/redmine_to_owncloud_example.pyTODO: write simple and extended usageContributingDevelopment ofics2caldavhappens at github and any idea and contribution is welcome.https://github.com/wtayyeb/ics2caldavCreditsw.Tayyeb:https://github.com/wtayyebLicenseics2cadav is licensed under MIT license.
Package: ics2todoist
A tool (and library) to convert tasks in iCalendar format (RFC 5545) to CSV
format (RFC 4180) forimport into Todoist.InstallationThis packagecan be installed usingpip, by running:pipinstallics2todoistCommand-Line ExamplesTo convert iCalendar files with extension.icsto a CSV file namedtodo.csv:ics2todoist-otodo.csv*.icsTo convert iCalendar files with extension.icsto a CSV file namedtodo.csvusing redirection:cat*.ics|ics2todoist>todo.csvAPI ExamplesTo convert iCalendar intodo.icsto CSV onstdout:fromics2todoistimportics_to_todoistics_to_todoist(['todo.ics'],sys.stdout)To convert iCalendar files with extension.icsto a CSV file namedtodo.csv:fromglobimportglobfromics2todoistimportics_to_todoistwithopen('todo.csv','w',encoding='utf-8')ascsvfile:ics_to_todoist(glob('*.ics'),csvfile)To convert a string of iCalendar data into aTodoistCsvRow:fromics2todoistimportIcs2TodoistConverterconverter=Ics2TodoistConverter()row=converter.ical_to_todoist(get_ical_string())DocumentationTheproject documentationis hosted onRead the Docs.  See theCLI
documentationfor command-line options and usage, and theAPI documentationfor the Python API.ContributingContributions are welcome and very much appreciated!  See thecontributing
guidelinesfor recommendations.LicenseThis project is available under the terms of theMIT License.
See thesummary at TLDRLegal
Package: icsd
BSD 3-Clause LicenseCopyright (c) 2022, Peruz
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 conditions and the following disclaimer.Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.Neither the name of the copyright holder nor the names of its
contributors may be used to endorse or promote products derived from
this software without specific prior written permission.THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS”
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Package: icsdll
ICSdll is a Python ctypes interface to the Image Correlation Spectroscopy
Dynamic Link Library (ICSx64.dll) developed at the Laboratory for Fluorescence
Dynamics (LFD) for the Globals for Images SimFCS software.ICSx64.dll is implemented in C++ using the Intel(r) oneAPI Math Kernel Library
and OpenMP. It provides functions and classes for the analysis of fluorescence
time series data:1D, 2D, and 3D auto- and cross-correlationImage pair correlation function (ipCF)Airy detector pair correlation function (apCF)Image mean square displacement (iMSD)Line spatio-temporal image correlation spectroscopy (lSTICS)Fit 1D pair correlation functions to the results of ipCF analysisSubtract immobile fractionsCorrect photo-bleaching1D DFTs of image stackAuthor:Christoph GohlkeLicense:BSD 3-ClauseVersion:2024.1.6RequirementsThis revision was tested with the following requirements and dependencies
(other versions may work):CPython3.9.13, 3.10.9, 3.11.7, 3.12.1, 64-bitNumpy1.26.3Intel(r) oneAPI Math Kernel Library2024.0.0 (build)Visual Studio 2022 C++ compiler(build)Revisions2024.1.6Rebuild package with oneAPI MKL 2024.0.0.2023.1.6Rebuild package with oneAPI MKL 2022.2.1 and Visual Studio 2022.Update metadata.2022.2.6Rebuild package with oneAPI 2022.2021.3.2Rebuild package.2019.11.22Wrap yxt_dft functions.Upgrade to ICSx64.DLL version 2019.11.22.2019.7.10Pass 22 tests.Wrap apcf, imsd, and lstics functions.Raise IcsError in case of DLL function errors.Use ICSx64.DLL version 2019.7.10.2019.5.22Initial release based on ICSx64.DLL version 2018.7.18.NotesICSdll was developed, built, and tested on 64-bit Windows only.The API is not stable and might change between revisions.Refer to the C++ header file and source code for function signatures.Referencesipcf.ipynbPair correlation function analysis of fluorescence fluctuations in
big image time series using Python.Globals for Images SimFCS,
Software for fluorescence image acquisition, analysis, and simulation.Globals for Airyscan,
Image correlation analysis for the ZEISS(tm) LSM 880 Airyscan detector.