Saravanan666/pypi-org huggingface dataset:
Package: epicycler
epicyclerEpicylceshave been used for
millenia to describe the motion of planets; evenCopernicusstill used them. They
got out of fashion whenKeplerthought about ellipses, but one can still fool around with epicycles a bit. Seemathologer's awesome video about it(which in fact
motivated this little package).Create animations from polygonsGiven a number of 2D polygonal points, epicycler creates nice animations. For example,
the above is created withepicycler-poly\0.00.0\1.00.0\1.02.0\-0.51.1\-0.52.1\--xylim-1.5+2.0-1.33.0Seeepicycler-poly-hfor more options.Installationepicycler isavailable from the Python Package
Index, so simply typepip install -U epicyclerto install or upgrade.Create animations from image filesGiven a (small) linedrawing image file like the above seagull,
epicycler can create an animation from itepicycler-imagein.png-c0.5Use the-coption for reducing the number of circles by cutting off those smaller than
the given threshold radius; notice then how the polygon points are not followed exactly:Creating a GIFffmpeg-iout.mp4-r10'frame-%03d.png'convert-delay5-loop0frame-*.pngout.gifTestingTo run the epicycler unit tests, check out this repository and typepytestDistributionTo create a new releasebump the__version__number,publish to PyPi and GitHub:make publishLicenseepicycler is published under theMIT license.
Package: epidtool
EpidtoolsA Python toolkit for analysis, modelling and forecasting EpidemicRequirments :Scipy : 1.4.1 +Numpy : 1.4.1 +scikit-learnpandasstatsmodelsKey features:Epidemic outbreak modeling and short-term forecasting using predefined fitted growth functions.Estimation of  time-dependent transmission coefficients and efective reproduction number.Epidemic dynamics modeling and estimation of transmission epidemiological parameters using the Runge-Kutta initial value problem solver and iterative (limited memory) BFGS optimizer.Epidemic decay dynamics modeling with time dependent contact rate using different decay functions (exp, power, tanh).Estimation of effective reproduction number using Kalman filtering techniques directly from the real-time infection data.How to install epitools[!IMPORTANT]
All the dependencies should be installed first.Epitools can be installed using the following command on terminal:pip install epitoolTutorials and documentation:The tutorials can be accessed fromhere.
Package: epifx
DescriptionGenerate forecasts of infectious disease epidemics by combining simulation models with real-time data.
See theonline documentationfor tutorials, how-to guides, and API documentation.LicenseThe code is distributed under the terms of theBSD 3-Clause license(seeLICENSE), and the documentation is distributed under the terms of theCreative Commons BY-SA 4.0 license.InstallationTo install the latest release:pip install epifxTo install the latest development version, clone this repository and run:pip install .
Package: epigeec
TheepiGenomic Efficient Correlatortool is designed to efficiently perform pairwise correlations of thousands of epigenomic datasets. It supports a growing number of file formats and offers the possibility to compute correlations at any resolution on costum or predefined filtered regions.A galaxy implementation including thousands of pre-computed public datasets is availalble athttp://epigeec.genap.ca/galaxy/and also includes support for the WIG format and Spearman correlation(coming soon to command line version). It also offers tools for further annotation and analysis of the matrix files created by epiGeEC.For more information see the official repository for the epiGeEC tool athttps://bitbucket.org/labjacquespe/epigeec
Package: epigeec-analysis
epiGeEC AnalysisTheepiGenomic Efficient Correlator (epiGeEC) Analysisis a suite of tools to process, annotate and analyse correlation matrices generated byepiGeEC. A galaxy implementation featuring these tools and including thousands of pre-computed public epigenomic datasets is availalble athttp://epigeec.genap.ca/galaxy/.InstallationLinux/x64 is the only OS currently supported, but it can work on any platform with python and pip installed.DependenciesYou will need pip to install the python package, use the following command if not already installedsudo apt-get install python-pipPip will attempt to install all dependencies but most likely will failSee documentation on how to installpandas.You might have more success withsudo apt-get install python-pandasInstall epiGeEC Analysissudo pip install epigeec-analysisHow To UseThis tool suite provide multiple analysis program.For more info on each parameter use the help flagepigeec-analysis [tool] --helpAnnotate matrixEssentialy, this tool apply a hierachical cluster method on a correlation matrix to
regroup datasets in clusters associated with their metadatas.epigeec-analysis annotate --pdf output.pdf --tsv output.tsv epiGeEC_Correlate.mat epiGeEC_Datasets.json assay cell_type timepointEvaluate clustersepigeec-analysis evaluate epiGeEC_Correlate.mat epiGeEC_Datasets.json -b assay cell_type timepoint -r assay cell_type timepoint > output.ariLicenseGNU General Public License v3
Package: epigos
Epigos PythonEpigos provides an end-to-end platform to annotate data, train computer vision AI models,
deploy them seamlessly and host the models via API's.For more details, visitepigos.ai.The Epigos Python Package is a python wrapper around the core Epigos AI web application and REST API.InstallationTo install this package, please usePython 3.9or higher.To addepigosto your project simply install with pip:pipinstallepigosOr with poetrypoetryaddepigosGetting StartedTo make your first API call, you will need to signup atepigos.aiand create an
API key for your workspace. Please contact our sales team for a demo.Initialization:importepigosclient=epigos.Epigos("api_key")Project:Manage project and upload dataset into your project using theProject ID.Upload an image with annotationimportepigosclient=epigos.Epigos("api_key")# load projectproject=client.project("project_id")# upload image with Pascal VOC annotationrecord=project.upload("path/to/image.jpg",annotation_path="path/to/image.xml",box_format="pascal_voc")print(record)# upload image with YOLO annotationrecord=project.upload("path/to/image.jpg",annotation_path="path/to/image.txt",box_format="yolo")print(record)Upload an entire dataset folderimportepigosclient=epigos.Epigos("api_key")# load projectproject=client.project("project_id")# upload Pascal VOC annotation datasetrecords=project.upload_dataset("path/to/folder",box_format="pascal_voc")print(tuple(records))# upload YOLO annotation datasetrecords=project.upload_dataset("path/to/folder",box_format="yolo")print(tuple(records))Prediction:Make predictions with any of the models deployed in your workspace using theModel ID.Classificationimportepigosclient=epigos.Epigos("api_key")# load classification modelmodel=client.classification("model_id")# make predictionsresults=model.predict("path/to/your/image.jpg")print(results.dict())Object detectionimportepigosclient=epigos.Epigos("api_key")# load object detection modelmodel=client.object_detection("model_id")# make predictionsresults=model.detect("path/to/your/image.jpg")print(results.dict())# visualize detectionsresults.show()ContributingIf you want to extend our Python library or if you find a bug, please open a PR!Also be sure to test your code with themakecommand at the root level directory.Run tests:maketestCommit message guidelinesIt’s important to write sensible commit messages to help the team move faster.Please follow thecommit guidelinesVersioningThis project usesSemantic Versioning.PublishingThis project is published on PyPiLicenseThis library is released under theMIT License.
Package: epigraph
CHIME/FRB APIReleaseStyleDocumentationepigraphAutomated GraphQL APIInstallationpip install epigraphRunning the APIIn[1]:fromepigraphimportgraphql_apiIn[2]:API=graphql_api.GraphQLAPI(url="https://swapi.graph.cool/")In[3]:API.query('Planet').args({'name':"Alderaan"}).fetch(['climate'])Out[3]:{"data":{"Planet":{"climate":["temperate"]}}}
Package: epigraphdbpy
Perform fast queries in Python against EpiGraphDBThe increasing availability of complex, high-dimensional epidemiological data necessitates innovative and scalable approaches to harness its potential to address research questions of biomedical importance. EpiGraphDB is an analytical platform and database that aims to address this challenge, supporting data mining in epidemiology.Our core objectives are to:Develop approaches for the appropriate application and interpretation of causal inference in systematic automated analyses of many phenotypes using data from a rich array of bioinformatic resources.Apply data mining approaches to the same integrated dataset to make novel discoveries about disease mechanisms and potential interventions relevant to population health.Installation:To be added
Package: epigraphhub
epigraphhub_pyEpigraphhub Python packageTheEpiGraphHub libraryis designed to provide external users with all of the analytical functionality used to power theEpiGraphHub platformand its applications. In fact, all applications designed to run on the EpiGraphHub platform rely heavily on it.This library should be used by users that want to contribute to the platform as well as by users that want to borrow some of the tools developed by our team in other opensource projects.EpiGraphHub library allows users make and apply:Bayesian StatisticsEpidemiological analysisMathematical modellingCost-effectiveness analysisForecastingMachine LearningText MiningGeo-Spatial analysisThe EpiGraphHub library is also available for theRlanguage.InstallationThe EpigraphHub library can be installed using pip:$ pip install epigraphhubUsageView Example EpiGraphHub Applications in Our Documentation:Downloading Google Trends Data (Python version)Fetching Raster data from WorldPopDownloading data from World Bank DataEpidemiological Data AnalysisDocumentationThe official documentation is hosted onReadtheDocs.Check ourwebsitefor most details about the EpiGraphHub project.How to contributeIf you want to contribute to EpiGraphHub, check ourContributing Guide.Code of conductCheck ourCode of conduct.📈 ReleasesYou can see the list of available releases on theGitHub Releasespage.🛡 LicenseThis project is licensed under the terms of theGNU GPL v3.0license. SeeLICENSEfor more details.📃 Citation@misc{epigraphhub_py,author={thegraphnetwork},title={Epigraphhub Python package},year={2021},publisher={GitHub},journal={GitHub repository},howpublished={\url{https://github.com/thegraphnetwork/epigraphhub_py}}}
Package: epijats
epijatsepijatsconvertsbaseprintJATS XML to PDF in three independent stages:JATS
Stage 1:   ▼
          "webstract" interchange format (json, yaml, or jsoml)
Stage 2:   ▼
          HTML
Stage 3:   ▼
          PDFUsing theepijatscommand line tool, you can start and stop at any stage with the--fromand--tocommand line options. The output ofepijats --helpis:usage: __main__.py [-h] [--from {jats,json,yaml,jsoml,html}]
                   [--to {json,yaml,jsoml,html,html+pdf,pdf}] [--no-web-fonts]
                   inpath outpath

Eprint JATS

positional arguments:
  inpath                input directory/path
  outpath               output directory/path

options:
  -h, --help            show this help message and exit
  --from {jats,json,yaml,jsoml,html}
                        format of source
  --to {json,yaml,jsoml,html,html+pdf,pdf}
                        format of target
  --no-web-fonts        Do not use online web fontsInstallationpython3 -m pip install epijats[format1,format2,...]where eachformatNetc.. is one ofjats,html,pdf,yaml, orjsoml.
Json support is automatic.Non-Python requirementsIf you are converting from JATS, the following dependencies must be installed:pandocpandoc-katex-filter Node.js NPM packagegitAll other dependencies will be automatically installed bypip.
Package: epijinn
EpiJinn is a Python package that checks whether recognition sites of prokaryotic DNAmethylase enzymesoverlap with a recognition site of arestriction enzyme, in a DNA sequence. Methylation of restriction site nucleotides blocks recognition/restriction and thus DNA assembly.Install:pipinstallepijinnLicense:MIT, Copyright 2021 Edinburgh Genome FoundryMore biology softwareEpiJinn is part of theEGF Codonssynthetic biology software suite for DNA design, manufacturing and validation.
Package: epilogos
Information-theoretic navigation of multi-tissue functional genomic annotationsEpilogos is an approach for analyzing, visualizing, and navigating multi-biosample functional genomic annotations, with an emphasis on chromatin state maps generated with e.g. ChromHMM or Segway.The software provided in this repository implements the methods underlying Epilogos using Python 3.9. We provide a proof-of-principle dataset based on chromatin state calls from the EpiMap dataset (Boix et al., Nature 2021).Created by: Wouter Meuleman, Jacob Quon, Alex Reynolds, and Eric RynesInstallationAlthough not required, it is good practice to create a virtual environment in which
specific versions of Python and its libraries are installed.
This can be done usingconda, for instance as such:$condainitbash## only needed upon first use of conda. Restart shell after this.$condacreate-nepilogospython=3.9$condaactivateepilogosTo install Epilogos simply run the following two commands$pipinstallepilogosAlternatively, install Epilogos directly from the Git repositority using$pipinstallgit+https://github.com/meuleman/epilogosPrerequisitesTo compute epilogos, you will need to have the following python libraries installed:statsmodels,click,numpy,scipy,matplotlib,pandas,pysam,scikit-learn,natsort,pyranges, andrich.
These can be installed with one of the following commands$pipinstall'click==8.1.3''numpy==1.23.4''pandas==1.5.1''scipy==1.9.3''matplotlib==3.6.1''statsmodels==0.13.2''scikit-learn==1.1.3''pysam==0.19.1''natsort==8.2.0''pyranges==0.0.117''rich==12.6.0'or while in the epilogos directory$pipinstall-rrequirements.txtAdditionally, it is recommended that python is updated to version 3.9 or later. We cannot guarantee the validity of results generated by earlier verions of python.Running EpilogosTo be presented with basic documentation of arguments needed to run epilogos, simply run the commandepilogos--helporpython-mepilogos--help(More in-depth explanation is given on thegithub README).By default, Epilogos assumes access to a computational cluster managed bySLURM.
A version of epilogos has been created for those without access to a SLURM cluster and can be run by using the-lflag to your command (e.g.epilogos-l).For a more extensive set of documentation, please refer toour github.
Package: epipackpy
EpiPackEpiPack v 0.1.0dev6DescriptionEpiPack is single-cell ATAC-seq atlas construction (integration) and cell type annotation tool. Leveraging its heterogeneous domain adaptation framework, EpiPack is able toIntegrate multi-source scATAC-seq datasets without aligned peak setreference mapping of query datasetscell type annotation including OOR detectionDependencypython >= 3.8
    pytorch >= 1.11.0
    sklearn >= 0.22.1
    numpy >= 1.21.6
    pandas >= 1.3.5Note: For pytorch installation, we recommend users go to the pytorch portal to download based on their CUDA version.InstallationThe package has been uploaded to PyPI. Users can download the package and dependent packages by:pip install epipackpyTutorialPlease checkout the documentations and tutorials atepipack.readthedocs.io.
Package: epiphancloud
Epiphan Cloud APIThis repo contains:/epiphancloud: Python wrapper for Epiphan Cloud API/docs: API reference/examples/full_lifecycle.py: Usage exampleInstallation$ git clone https://github.com/epiphan-video/epiphancloud_api.git
$ cd epiphancloud_api
$ pip install -r requirements.txtDocumentationAPI documentation is available via Github Pages:https://epiphan-video.github.io/epiphancloud_apiHow to update docsDocumentation source is stored indocs-source-slatefolder.Build a slate builder container (once):$cdslate
$dockerbuild-tslate-builder.(optional) Start doc server:dockerrun-it--rm\-v$(pwd)/docs-source-slate/:/slate/source\-v$(pwd)/docs:/slate/build\-p4567:4567\slate-builderbundleexecmiddlemanserver...and openhttp://localhost:4567/in your browser.When editing is done, use the container to build static docs:dockerrun-it--rm-v$(pwd)/docs-source-slate/:/slate/source-v$(pwd)/docs:/slate/buildslate-builderThis command will update files indocsfolder, if necessary.git commit and pushExporting notebook tutorial:jupyter nbconvert --to html --execute device_api.ipynb --ExecutePreprocessor.timeout=-1
Package: epiphani-ecube
ecubeepiphani execution engine (e3) allows running local scripts and commands in conjunction with other cloud based connectors to create low-code playbooks. These can be shared with other team members using collaboration tools such as Slack. For more information visit:https://www.epiphani.aiInstallation$ pip install epiphani-ecubeecube config & argumentsIn order to use ecube, you need to first create an epiphani account. Once you have the account, you need to setup ecube by adding your credentials in~/.e3.ini(ecube) pmadhav@ip-172-31-46-212:~$ e3 --help
usage: e3 <command> [<args>]
The following commands are supported:
    run      Run a local connector
    runcli   Run a cli as a connector 
    playbook Interact with the playbook engine 

Please create a config file ~/.e3.ini with following content:
[DEFAULT]
username = <epiphani username> <REQUIRED>
password = <epiphani password> <REQUIRED>
login = URL to epiphani <OPTIONAL>
log_file = foo.log <OPTIONAL>
local_install = true <OPTIONAL | Use local installation | Default: false>
local_install_host = localhost <OPTIONAL | IP/FQDN of local installation | Default: localhost>
local_install_port = 31050 <OPTIONAL | GraphQL server port number | Default: 31050>

If you set local_install_host or local_install_port, local_install is automatically set to true

e3 (ecube) -> epiphani execution engine

positional arguments:
  command     Subcommand to run

optional arguments:
  -h, --help  show this help message and exit
(ecube) pmadhav@ip-172-31-46-212:~$Using ecube examplesrunclie3 runcli --name pmCliThis will create a connector that will be executed on the machine that is running e3. It can be made a part of any playbooks on the playbook engine. Please see this:https://github.com/epiphani-inc/ecube/wiki/InstallUse ecube to create & run playbooksCreate a playbookThere are some simple sample playbooks in the gitrepo @ ./samples/playbooks
You will have to edit them to add you AWS secret and key information where it says <>.Once you have the samples edited and e3 installed, you can just create the playbook like this:e3 playbook create --directory ./samples/playbooks/threeNode --name EC2CL109Execute a playbookTo execute a playbook you just need to give the name of the playbook to rune3 playbook run --vars '{"region": "us-west-2"}' --name EC2CL108In this case the playbook needs variables - region where it is going to fetch the state from.
Package: epippy
EPIPPyExpansion Planning Input Preprocessing in PythonEPIPPy provides a set of functions and scripts to preprocess data that can be then used in an expansion planning model.Current capabilities(Retrieval), preprocessing and management of:generationdata (hydro capacities and flows, RES existing capacities, capacity factors, potentials, ...)geographicaldata (computation of countries and sub-regions shapes, manipulation of points, codes, ...)populationdataemissions(annual emission computation)load(yearly and hourly load computation)technologies(costs and parameters)topologiesDataFor EPIPPy to work properly, it has to have access to a database following a certain structure. This database can be downloadedhere.After downloading the database, the path to the folder containing it must be specified in epippy/__init__.py (to be updated).DependenciesTo be complentedInstallationClone gitAdd epippy to your PYTHONPATH
Package: epipylib
EpiPylib is a collection of different epidemic models and fitting functions.FeaturesDocumentationInstallationExampleChangelogLicenseFeaturesFitting functions:Manual and optimized manipulation epidemic model parametersEpidemic models:SusceptibleInfectedRecovered (Simple, With births and deaths, With Vaccine)SusceptibleInfectedRecoveredSusceptible (Simple, With births and deaths)SusceptibleExposedInfectedRecovered (Simple)LicenseMITlicense
Package: episcanpy
EpiScanpy – Epigenomics single cell analysis in pythonEpiScanpyis a toolkit to analyse single-cell open chromatin (scATAC-seq) and single-cell DNA methylation (for example scBS-seq) data.EpiScanpyis the epigenomic extension of the very popular scRNA-seq analysis toolScanpy(Genome Biology, 2018) [Wolf18]. For more information on scanpy, read the followingdocumentation.EpiScanpy paper is now accessible onNature Communications. For more information on how to use the package, more information are available on thewebsite.ReleasesBuild status via CondaPython versionsOperating SystemDocument statusGithub statusDocumentationThe documentation for epiScanpy is availablehere. If epiScanpy is useful to your research, consider citingepiScanpy.
Package: episcen
DescriptionA collection of epidemic models designed for scenario modelling analyses, in order to inform pandemic preparedness and response activities.LicenseThe code is distributed under the terms of theBSD 3-Clause license(seeLICENSE), and the documentation is distributed under the terms of theCreative Commons BY-SA 4.0 license.InstallationTo install the latest release:pip install episcenTo install the latest development version, clone this repository and run:pip install .
Package: episoder
episoderEpisoder is a tool to tell you about new episodes of your favourite TV shows. It
does so by parsing online TV episode guides.Currently episoder can get data fromepguidesandTheTVDBand tells you whenever a new episode of a
show listed on one of those sites is aired.There is also a web-based version of episoder, calledwebisoderwhich can be used for free
atwebisoder.net.DependenciesIn order to use episoder, you will need python installed on your system. In
addition to the default distribution, therequests,argparse,sqlalchemyandbeautifulsoup4modules are required.DownloadingThe official website, bug tracker etc. for episoder can be found atcode.ott.net/episoder.InstallationYou can install episoder throughpypi(usingeasy_installorpip) or by runningsetup.pyfrom the downloaded and
extracted tarball.ConfigurationThe configuration file at~/.episodercontains your default settings for
episoder. After installing episoder, the man page will help you with the
configuration.Using episoderTo use episoder you will typically:Create a cron job to update your database once a day usingepisoder updateAddepisoderto your~/.bashrc,~/.bash_profile,/etc/bash.bashrcor/etc/profileif you want to see your upcoming shows every time you start a
shell. Consult your shell's documentation to find out which file to use.Or runepisoder notifyat regular intervals to get notifications by e-mail.