Saravanan666/pypi-org huggingface dataset:
Package: acd-sdk
Merative Annotator for Clinical Data Python SDK Version 2.0.2OverviewThis Python SDK allows developers to programmatically interact with the following service:Service NameImported Class NameAnnotator for Clinical DataAnnotatorForClinicalDataV1PrerequisitesRefer to the Annotation for Clinical Data documentation:PrerequisitesSoftware Development KitsPython 3.7 or aboveInstallationTo install, usepippipinstall--upgradeacd-sdkMigrating from version 1.x.xThe release of version 2 of the Annotator for Clinical Data SDK introduces a Python package name change fromibm_whcs_sdktoacd_sdk.  For the migration from 1.x.x:Runpip uninstall ibm-whcs-sdkRunpip install acd-sdk, and confirm that you have version 2 installed by runningpip show acd-sdk.In your application files that have a dependency onacd-sdk, update any import declarations fromibm_whcs_sdktoacd_sdk.Using the SDKFor general SDK usage information, please seethis linkQuestionsFor questions, refer to:Annotator for Clinical Data documentationAnnotator for Clinical Data Support pageIssuesIf you encounter an issue with the project, you are welcome to submit abug report.ContributingSeeCONTRIBUTING.LicenseThe Annotator for Clinical Data Python SDK is released under the Apache 2.0 license.
The license's full text can be found inLICENSE.
Package: acd-tools
Rockwell ACD Project File ToolsThe Rockwell ACD file is an archive file that contains all the files
that are used by RSLogix/Studio 5000.It consists of a number of text files containing version information, compressed XML
files containing project and tag information as well as a number of database files.Parsing the ACD fileThe exporting of the L5X file isn't complete, we are able to parse the data types, tags and programs into a Controller
python object though.To get the Controller object and get the program/routines/rungs/tags/datatypes, use something like thisfromacd.export_l5ximportExportL5xcontroller=ExportL5x("../resources/CuteLogix.ACD","build/output.l5x").controllerrung=controller.programs[0].routines[0].rungs[0]data_type=controller.data_types[-1]tag_name=controller.tags[75].texttag_data_type=controller.tags[75].data_typeUnzipTo extract the file use the acd.unzip.Unzip class. This extracts the database files to a directory.fromacd.unzipimportUnzipunzip=Unzip('CuteLogix.ACD')unzip.write_files('output_directory')
Package: acdumo
acdumoThis app is a simple implementation of theAccelerated Dual Momentuminvestment strategy. It
queries a Yahoo Finance API for historical ticker price data, calculates ADM
statistics, and suggests a strategy.Installation (command line)For simple command line use of this app, you can install with pip:pip3installacdumoorpip3install--useracdumoInstallation will require an extra step on macOS systems. Run the includedacdumo-install-certificommand.acdumo-install-certifiUsage (command line)To generate a report for the current date, simply run:acdumoOptional arguments can be used to generate reports for different dates or
tickers:acdumo--helpusage: acdumo [-h] [--date <yyyy-mm-dd>] [--tickers <TIC> [<TIC> ...]] [--bonds <TIC>] [--frequency {monthly,weekly}] [<path/to/report/dir/>]

Accelerated dual momentum

positional arguments:
  <path/to/report/dir/>
                        write a HTML report

optional arguments:
  -h, --help            show this help message and exit
  --date <yyyy-mm-dd>   date of interest (default: today)
  --tickers <TIC> [<TIC> ...]
                        tickers to use (default: SPY TLT VSS SCZ)
  --bonds <TIC>         ticker representing bonds (default: TLT)
  --frequency {monthly,weekly}
                        frequency of data to fetch (default: monthly)Installation (full app)To run the app locally, use the following procedure. By default it is
configured to use a gmail account of your choice for account confirmation
emails. The gmail account must be configured to allowless secure apps.gitclonehttps://github.com/anthony-aylward/acdumo.gitcdacdumo
python3-mvenvvenvsourcevenv/bin/activate
pip3install-e.# if on macOS, also run: python3 acdumo/install_certifi.pyexportFLASK_APP=acdumoexportFLASK_ENV=development
mkdir-pinstance/protected
python3config/__init__.py--email<gmailaddress>instance/
flaskdbupgrade
flaskrunYou can then use a web browser to navigate to the app (by default at localhost:5000)
Package: ace-api
Python Bindings for ACE REST APIExamplesConnect to a ServerSetting the default remote host:>>> import ace_api
       
    >>> server = 'ace.integraldefense.com'
       
    >>> ace_api.set_default_remote_host(server)
       
    >>> ace_api.ping()
    {'result': 'pong'}Setting the remote host for an Analysis class:>>> analysis = ace_api.Analysis('this is the analysis description')

    >>> analysis.set_remote_host('something.else.com').remote_host
    'something.else.com'If your ACE instance is listening on a port other than 443, specify it like so::>>> ace_api.set_default_remote_host('ace.integraldefense.com:24443')

    >>> ace_api.default_remote_host
    'ace.integraldefense.com:24443'Submit a File to ACE>>> path_to_file = 'Business.doc'
    
    >>> analysis.add_file(path_to_file)
    <ace_api.Analysis object at 0x7f23d57e74e0>
    
    >>> analysis.add_tag('Business.doc').add_tag('suspicious doc')
    <ace_api.Analysis object at 0x7f23d57e74e0>

    >>> analysis.submit()
    <ace_api.Analysis object at 0x7f23d57e74e0>

    >>> analysis.status
    'NEW'

    >>> analysis.status
    'ANALYZING'

    >>> analysis.status
    'COMPLETE (Alerted with 8 detections)'

    >>> result_url = 'https://{}/ace/analysis?direct={}'.format(analysis.remote_host, analysis.uuid)

    >>> print("\nThe results of this submission can be viewed here: {}".format(result_url))The results of this submission can be viewed here:https://ace.integraldefense.com/ace/analysis?direct=137842ac-9d53-4a25-8066-ad2a1f6cfa17Submit a URL to Cloudphish>>> another_url = 'http://medicci.ru/myATT/tu8794_QcbkoEsv_Xw20pYh7ij'

    >>> cp_result = ace_api.cloudphish_submit(another_url)
       
    >>> cp_result['status']
    'NEW'
       
    >>>  # Query again, a moment later:
    ...
    >>> cp_result = ace_api.cloudphish_submit(another_url)

    >>> cp_result['status']
    'ANALYZED'

    >>> cp_result['analysis_result']
    'ALERT'
       
    >>> result_url = 'https://{}/ace/analysis?direct={}'.format(ace_api.default_remote_host, cp_result['uuid'])

    >>> print("\nThe results of this submission can be viewed here: {}".format(result_url))The results of this submission can be viewed here:https://ace.integraldefense.com/ace/analysis?direct=732ec396-ce20-463f-82b0-6b043b07f941DocumentationACE's API documentation:View ACE's full documentation here:https://ace-analysis.readthedocs.io/en/latest/
Package: ace-cream
Build StatusPyPIWindowsThis project provides a wrapper program of Python for ACE algorithm
implementation of Fortran.Install Binary DistributionCurrently, only 64-bit binary distribution is provided. Runpip install ace_creamto install the binary distribution.Platformpy3.6py3.7py2.7WindowsTTTMacOSTTLinuxTTTHow to buildYou neednumpyand fortran compiler to build from source.WindowsInstallVisual
C++toolchain.Download MinGW-w64 fromsourceforge,
which provides the necessary fortran compilerInstall MinGW-w64 and add{install_dir}\mingw64\binpath to
environment variable (makegfortranaccessible from command
line).(for conda environment) Add{install_dir}\Anaconda3\Scriptsto
environment variable (makef2pyaccessible from command line).MacYou can use package manager to installgfortran(included within gnu
compiler collection). For example, withHomebrewyou can usebrewinstallgccUbuntuTo installgfortran, use the default package manager:sudoapt-getinstallgfortranRunpython setup.py installfrom command line at the project root
directory.How to useimportnumpyasnpfromace_creamimportace_cream# discrete case, binary symmetric channel with crossover probability 0.1x=np.random.choice([0,1],size=N_SIZE)n=np.random.choice([0,1],size=N_SIZE,p=[0.9,0.1])y=np.mod(x+n,2)# set both x(cat=0) and y(cat=-1) as categorical typetx,ty=ace_cream(x,y,cat=[-1,0])# continuous casex=np.random.uniform(0,np.pi,200)y=np.exp(np.sin(x)+np.random.normal(size=200)/2)tx,ty=ace_cream(x,y)Resultimagechange logv0.1 initial commitv0.2 modify to relative import in__init__.pyv0.3 add support for multiple columns of x and other directions of
transformationv0.4 addf_mappingfunction and unittests for this functionLicenseApache License Version 2.0Referencehttps://en.wikipedia.org/wiki/Alternating_conditional_expectations
Package: acedatacloud-scaffold
Ace Data Cloud ScaffoldInstall:pip install acedatacloud-scaffoldSample:fromacedatacloud_scaffoldimportBaseControllerasControllerfromacedatacloud_scaffoldimportBaseHandlerimportjsonclassHandler(BaseHandler):asyncdefget(self,id=None):result={'value':id}self.write(json.dumps(result))controller=Controller()controller.add_handler(r'/test/(.*)',Handler)controller.start()
Package: aceditor
Ace EditorACE full stack editor with JavaScript and Python CGI.FeaturesCommon Keyboard ShortcutsQuick Access ToolbarEvent Status BarFile Bookmarks with Import/ExportFile History for BackupLine Separator ChangerPrint Function, Log FilePreviewDemo:https://foxe6.github.io/aceditor/ExampleSee/aceditor/aceditor/example/.
Package: aced-submission
submissionUtilities to upload metadata and files to ACED's Gen3 instanceSetuppython3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
pip install -e .Usesee etl podDistributionPyPi# update pypi

# pypi credentials - see https://twine.readthedocs.io/en/stable/#environment-variables

export TWINE_USERNAME=  #  the username to use for authentication to the repository.
export TWINE_PASSWORD=  # the password to use for authentication to the repository.

# this could be maintained as so: export $(cat .env | xargs)

rm -r dist/
python3  setup.py sdist bdist_wheel
twine upload dist/*
Package: ace-elispot
ACE Configurator for ELISpotACE facilitates (1) generation of ELISpot configurations (peptide-pool assignments)
using a deep learning approach to cluster similar peptides and (2) deconvolution
of pool spot counts for identification of immunogenic peptides.01. Installation01-1. Standalone Graphical User Interface (Recommended)Please note that the ACE GUI software will take a long time to load (~30 seconds :coffee:).
We also recommend that you haveGoogle Chromeinstalled on your machine.Operating SystemLinkVersionMacDownloadv0.1.1.0 (latest)Windows 10Downloadv0.1.1.0 (latest)For Windows versions, first unzip the file and look for an application file calledACEinside the unzipped foler.
Previous versions of ACE are availablehere.01-2. Python PackageACE is available onPyPIpip install ace-elispotYou can also download a specific version of ACE fromhere.Subsequently install the ACE package using pip:pip install ace-elispot-<version>.tar.gzDependenciespython3 (>= 3.10)pandas (>=1.5.2)numpy (>=1.23.1)ortools (9.3.10497)torchtransformers (==4.30.2)scikit-learnopenpyxlgolfy (>=2.5.0)levenshtein02. UsageACE is available as a command-line interface after you install the python package:usage: ace [-h] [--version] {generate,deconvolve,verify} ...

ACE Configurator for ELISpot.

positional arguments:
  {generate,deconvolve,verify}
                        ACE sub-commands.
    generate            Generates an ELISpot experiment configuration.
    deconvolve          Deconvolve hit peptide IDs given read-outs from an ELISpot experiment.
    verify              Verifies whether an ELISpot assignment satisfies all ACE constraints.

options:
  -h, --help            show this help message and exit
  -v, --version         show program version number and exitRead the full documentation on the python package athttps://pirl-unc.github.io/ace/03. CitationIf you use ACE in a publication, please cite ourpreprintdescribing ACE.
Package: acefile
This single-file, pure python 3, no-dependencies implementation is intended
to be used as a library, but also provides a stand-alone unace utility.
As mostly pure-python implementation, it is significantly slower than
native implementations, but more robust against vulnerabilities.This implementation supports up to version 2.0 of the ACE archive format,
including the EXE, DELTA, PIC and SOUND modes of ACE 2.0, password protected
archives and multi-volume archives.  It does not support writing to archives.
It is an implementation from scratch, based on the 1998 document titled
“Technical information of the archiver ACE v1.2” by Marcel Lemke, using
unace 2.5 and WinAce 2.69 by Marcel Lemke as reference implementations.For more information, API documentation, source code, packages and release
notifications, refer to:https://www.roe.ch/acefilehttps://apidoc.roe.ch/acefilehttps://github.com/droe/acefilehttps://pypi.python.org/pypi/acefilehttps://twitter.com/droethlisberger
Package: acellera-htmd
[![Build Status](https://travis-ci.org/Acellera/htmd.svg?branch=master)](https://travis-ci.org/Acellera/htmd)
[![Language Grade: Python](https://img.shields.io/lgtm/grade/python/g/Acellera/htmd.svg?logo=lgtm&logoWidth=18)](https://lgtm.com/projects/g/Acellera/htmd/context:python)
[![Conda](https://anaconda.org/acellera/htmd/badges/version.svg)](https://anaconda.org/acellera/HTMD)
<!—[![Build status](https://ci.appveyor.com/api/projects/status/m1bxrop34b2qw68x/branch/master?svg=true)](https://ci.appveyor.com/project/acelleraci/htmd/branch/master)—># HTMD: Programming Environment for Molecular Discovery
[HTMD](https://www.htmd.org) (acronym for High-Throughput Molecular Dynamics) is a programmable, extensible platform
written in Python. It provides a complete workspace for simulation-based discovery through molecular simulations while
aiming to solve the data generation and analysis problem as well as increase reproducibility.## Licensing
HTMD Community Edition is free to use for non-profit work. Contact Acellera
[www.acellera.com/contact](https://www.acellera.com/contact/) for information on the full version HTMD Pro or if you need a different license.## Download HTMD### Using released versions
HTMD is distributed through conda package manager. The instructions for downloading HTMD can be found in
[https://software.acellera.com/download.html](https://software.acellera.com/download.html).### Using this repository
If you want to use this repository, we recommend to still download a released version of HTMD to have all dependencies
and then set PYTHONPATH to the git directory.## HTMD Documentation and User Guide
For HTMD Documentation, please visit:
[https://software.acellera.com/docs/latest/htmd/api.html](https://software.acellera.com/docs/latest/htmd/api.html).For a User Guide (easy to start examples), please visit:
[https://software.acellera.com/docs/latest/htmd/tutorials.html](https://software.acellera.com/docs/latest/htmd/tutorials.html)## Support and DevelopmentPlease report bugs via [GitHub Issues](https://github.org/acellera/htmd/issues).HTMD is an open-source software and we welcome contributions from the community. For more information on how to
contribute to HTMD, please visit:
[https://software.acellera.com/docs/latest/htmd/developers/howto.html](https://software.acellera.com/docs/latest/htmd/developers/howto.html)## Citing HTMDIf you use HTMD in your publication please cite:Stefan Doerr, Matthew J. Harvey, Frank Noé, and Gianni De Fabritiis.HTMD: High-throughput molecular dynamics for molecular discovery.Journal of Chemical Theory and Computation,2016,12(4), pp 1845–1852.
[doi:10.1021/acs.jctc.6b00049](http://pubs.acs.org/doi/abs/10.1021/acs.jctc.6b00049)
Package: ace-magnetometer
ACE magnetometer: Load and plotLoad and Plot ACE satelite magnetometer data for Python.PythonGet data from FTP siteftp://mussel.srl.caltech.edu/pub/ace/browse/MAG16secautomatically: ACE magnetometer 16 second cadence by date:DownloadACE.py2012-02-03~/dataLoad and Plot ACE magnetometer dataPlotACE.py2012-02-03~/dataMatlabMatlab is not regularly used.PlotACE()
Package: ace-nn
ace_nnIntroductionThis repo contains experimental implementation of ace algorithm via neural network. It is shown byxiangxiang-xuthat calculating optimal features byAlternating Conditional Expectationis equivalent to maximizeH-score.How to runThree examples are provided ( one for continuous variable and the other twos are for discrete variable) and their results are the same asace. The main function isace_nnand its parameters are very similar toace_cream.importnumpyasnpfromace_nnimportace_nn# discrete case, binary symmetric channel with crossover probability 0.1N_SIZE=1000x=np.random.choice([0,1],size=N_SIZE)n=np.random.choice([0,1],size=N_SIZE,p=[0.9,0.1])y=np.mod(x+n,2)# set both x(cat=0) and y(cat=-1) as categorical typetx,ty=ace_nn(x,y,cat=[-1,0],epochs=100)# continuous casex=np.random.uniform(0,np.pi,200)y=np.exp(np.sin(x)+np.random.normal(size=200)/2)tx,ty=ace_nn(x,y)For more detail, runhelp(ace_nn)to see the parameters and returns of this function.Further discussionCurrently, the neural networks used to approximate optimal $f(x)$ and $g(y)$ are two-layer MLP withtanhas activation function. More turns of epochs are needed for large alphabet  $|\mathcal{X}|$ and  $|\mathcal{Y}|$ and the running time is not short.Also,batch_sizeandhidden_units_numcan be hypertuned, and there is no guarantee that current configuration of neural network is optimal for solving ace.Applicationwe can useace_nn(x, y, return_hscore = True)to calculate a lower bound of $\frac{\norm{B}_F^2}{2}$
Package: acentoweb.addusergroup
acentoweb.addusergroupAdds new users automatically to groupsFeaturesAdds settings to the medialog control panelthe Group settings will add all users to these groups on loginInstallationInstall acentoweb.addusergroup by adding it to your buildout:[buildout]

...

eggs =
    acentoweb.addusergroupand then runningbin/buildoutAuthorsEspen Moe-NilssenContributeIssue Tracker:https://github.com/collective/acentoweb.addusergroup/issuesSource Code:https://github.com/collective/acentoweb.addusergroupDocumentation:https://docs.plone.org/foo/barSupportIf you are having issues, please let us know.
We have a mailing list located at:project@example.comLicenseThe project is licensed under the GPLv2.ContributorsEspen Moe-Nilssen,espen@medialog.noChangelog1.0a1 (unreleased)Initial release.
[espenmn]
Package: acentoweb.collectionactions
Tell me what your product doesFeaturesAdds behaviors to Collection so you can move or copy all items to a folder.InstallationInstall acentoweb.collectionactions by adding it to your buildout:[buildout]

...

eggs =
    acentoweb.collectionactionsand then runningbin/buildoutContributeIssue Tracker:https://github.com/espenmn/acentoweb.collectionactions/issuesSource Code:https://github.com/espenmn/acentoweb.collectionactionsSupportIf you are having issues, please let us know (espen@medialog.no)LicenseThe project is licensed under the GPLv2.ContributorsEspen Moe-Nilssen,espen@medialog.noChangelog1.0a1 (unreleased)Initial release.
[espenmn]
Package: acentoweb.ecv
Exports ECV files from Plone CMSFeaturesView to export ECV filesDocumentationFull documentation for end users can be found in the “docs” folder, and is also available online athttp://docs.plone.org/foo/barTranslationsThis product has been translated intoenglish (default=)InstallationInstall acentoweb.ecv by adding it to your buildout:[buildout]

...

eggs =
    acentoweb.ecvand then runningbin/buildoutContributeIssue Tracker:https://github.com/espenmn/acentoweb.ecv/issuesSource Code:https://github.com/espenmn/acentoweb.ecvSupportIf you are having issues, please let us know.espen@medialog.noLicenseThe project is licensed under the GPLv2.ContributorsEspen Moe-Nilssen,espen@medialog.noChangelog1.0 (02.11.2022)Initial release.
[espenmn]1.1 (03.11.2022)Add view permission and portal action.
[espenmn]1.2 (03.11.2022)Remove (uncomment) permissions [espenmn]1.3 (05.12.2022)Added view ecv-display1.4 (09.12.2022)Change id field nameChange ‘ to “1.4.2 (13.12.2022)Add replace in export ( “ => ‘ )
Package: acenv
PROJECTAcenv (Algebraic Calculation Environment)A python 3 package that provides some tools to perform operations over complex
polynomials objects, useful if you are working on a project that requires your program solving
equations and polynomials expression parsing in general.FEATURESFully implemented in Python 3;No external dependencies;Class for representing real numbers in single objects, enabling operations with more complex
numbers in an algebraic sense (the sum âˆš2 + âˆš2 returns 2âˆš2,
not the approximated float value 2.828...);Class for representing polynomials as single objects, enabling operations with algebraic entities
containing one or more literal variables and real numbers;Polynomial factorization engine;Polynomial string parsers, which permits the user to simply type the readable string
representation of the object, avoiding tedious object instantiation procedures;Algebraic expression parser, which takes a string representing an expression, simplifies it and
can return both the resulting polynomial and the factorized form.PREREQUISITES AND INSTALLATION GUIDEWith the library running without any external dependency, there is no need
for you to install any other code than the one provided here. So, to install the library,
it is sufficient to use the 'pip' command in terminal:pip install acenvDOCUMENTATIONThe complete documentation should have been downloaded together with the
rest of the packageHOW TO USEJust import the components you need:from acenv import Exand start creating the objects you intend to useexpression = Ex('x^2+4(1-x)')

print(expression.value.numerator)
print(expression.reduced)and the output is'+4-4x^(1)+1x^(2)'
[['+2-1x^(1)', '+2-1x^(1)'], ['+1']]For more checking the documentation is highly encouragedNOTESThe project is still in its early stages of development, and it is born
as a school project of mine for my ICT class. A lot of work and changes have
been done since then, but there are still a lot of thing than can be hugely
improved, so every feedback and bug report is widely appreciated.LICENSEMIT license, see LICENSE.txt that should have been downloaded with the package
or simply go tohttps://opensource.org/licenses/MIT.CONTACT MEFor any feedback, bug report or problems, you can contact me at:vigano02aceproject@gmail.com
Package: acequia
ACEQUIAAcequia is a python package to facilitate data management for
ground water time series. It provides tools for Dutch
groundwater practitioners who deal with files from Dinoloket,
Menyanthes, and KNMI precipitation files.Current functionalityRead groundwater head data from Dinoloket csv files and Menyanthes Hydromonitor csv files.Read knmi precipitation and evaporation data from KNMI csv files or download data directly from the KNMI website.Calculate descriptive statistics for groundwater head series, taking into account hydrological years and measurments taken on the 14th and 28th of eacht month.Getting startedAcequia depends on Fiona for reading spatial data. Unfortunately,
Fiona depends on GDAL which can not be installed using pip. Therefore
Fiona must be installed on your machine before you can install Acequia.For example, if you are using a clean conda environment with python
installed you can do:>>> conda install fiona  
>>> pip install acequiaAcequia depends on the following packages:numpy, maplotlib, pandas, scipy, statsmodels, seaborn, geopandas, simplekml.Basic exampleAs a very basic example, read a Dinoloket csv file named B28A0475002_1.csv and resample to measurements on the 14th and 28th:>>> import acequia as aq
>>> gw = aq.GwSeries.from_dinogws('B28A0475002_1.csv')
>>> sr = gw.heads(ref='datum')
>>> sr1428 = gw.heads1428(maxlag=3)```