Saravanan666/pypi-org huggingface dataset:
Package: simcem
SimCem thermodynamic and process simulation packageThis package uses thestator Comptational Algebra System
(CAS)to treat
thermodynamics in an equation-oriented way. This is important inappliedthermodynamics as often additional constraints such as
heat transfer, kinetics, or multi-stage processes need to be
included.You may be familiar with Gibb's free energy minimisation, but this on
its own can only consider a single temperature and pressure. Other
constraints need the minimisation of other free energies, for example
including heat loss/gain needs the maximisation of the system entropy.Using an equation-oriented approach reduces the required iterations to
solve these problems and can lead to better optimisation as the whole
problem is exposed to the optimiser; however, it makes the setting up
of such problems significantly more complex. The idea of SimCem is to
hide as much of this complexity as possible.Ultimately the thermodynamic problems are reduced to a constrained
minimisation problem which is solved with theIPOPTlibrary. Using a CAS allows
these problems to be easily exported into other systems, such as
Matlab/Mathematica, for verification.SetupThis library is developed on Linux, but should compile on Windows
(which is still being developed). You will need to install git, Python
3, IPOPT, CMake, and sundials yourself. You can then clone the
repository and its other dependencies (Eigen, sundials, pybind11) like
so:git clone --recurse-submodules http://github.com/toastedcrumpets/SimCemCurrent windows issuesThe real challenge on windows is getting all the
dependencies. Sundials and IPOPT are the two blockers preventing this
at this time. Once the code is released, CI services such as
Travis/Appveyor will be used to build packages for windows to save
everybody this effort.BuildingTo build the package, run./setup.py buildInstallationTo install the package, run./setup.py installUsage/DatabaseYou will need a thermodynamic database to use SimCem. A free one
containing data from NASA is available on request fromm.campbellbannerman@abdn.ac.uk. This will be released for free in a
separate repository shortly.
Package: simcrf
# SimCRFThis project is aim to provide a super easy way to train crf model and extract entities from text.[中文文档](https://github.com/eromoe/SimCRF/blob/master/README.CN.md)## Installationpip install simcrf## Training Data Formatcrf usually use iob tagging (https://en.wikipedia.org/wiki/Inside_Outside_Beginning)input data can be:1. word, pos_tag, iob_tag2. word,  iob_tagiob_tag:- I: inside of entity- O: outside of entity- B: beginning of entityExample:打印机 n O采购 v O品目 n O采购 v O单位 n O曲周县 nr B职业 n I技术 n I教育 vn I中心 n I行政区域 n O曲周县 nr O公告 n O时间 n O技术 n I教育 vn I中心 n I采购 v O单位地址 n O曲周县 nr B职业 n I技术 n I教育 vn I中心 n I采购 v O单位 n O联系方式 l O18932708288 m O中心 n I采购 v O人 n O地址 n O： x O曲周县 nr B职业 n I技术 n I教育 vn I中心 n I采购 v O人 n O联系方式 l O： x O## Usage#### Train model:from simcrf import SimCRFner = SimCRF()# note: also support only tokensX_train = [[('打印机', 'n'), ('采购', 'v'), ('品目', 'n'), ('采购', 'v'), ('单位', 'n'), ('曲周县', 'nr'), ('职业', 'n'), ('技术', 'n'), ('教育', 'vn'), ('中心', 'n'), ('行政区域', 'n'), ('曲周县', 'nr'), ('公告', 'n'), ('时间', 'n')],[('打印机', 'n'), ('采购', 'v'), ('品目', 'n'), ('采购', 'v'), ('单位', 'n'), ('曲周县', 'nr'), ('职业', 'n'), ('技术', 'n'), ('教育', 'vn'), ('中心', 'n'), ('行政区域', 'n'), ('曲周县', 'nr'), ('公告', 'n'), ('时间', 'n')]]y_train = [['O','O','O','O','O','B','I','I','I','I','O','O','O','O'],['O','O','O','O','O','B','I','I','I','I','O','O','O','O']]X_train = ner.transform(X_train)ner.fit(X_train, y_train)#### Save modelner.save('~/crf_test.pkl')#### Load modelner = SimCRF.load('~/crf_test.pkl')#### Extract entitiesTo support different tokenizer, you need tokenize your text first and feed to crf model.import jieba.posseg as psegner = SimCRF.load('xxxx.pkl')text = '''    　哈尔滨工业大学招标与采购管理中心受总务处的委托，就哈尔滨工业大学部分住宅小区供热入网项目（项目编号：GC2017DX035）组织采购，评标工作已经结束，中标结果如下：一、项目信息项目编号：GC2017DX035项目名称：哈尔滨工业大学部分住宅小区供热入网项目联系人：李占奎 王 吉联系方式：电话： 0451-86417953 13936645563二、采购单位信息采购单位名称：总务处采购单位地址：哈尔滨市南岗区西大直街92号采购单位联系方式：孔繁武 0451-86417975三、项目用途、简要技术要求及合同履行日期：见结果公示四、采购代理机构信息采购代理机构全称：哈尔滨工业大学招标与采购管理中心采购代理机构地址：哈尔滨市南岗区西大直街92号哈尔滨工业大学行政办公楼203房间采购代理机构联系方式：李占奎 王 吉 电话： 0451-86417953 13936645563'''sent = [tuple(pair) for pair in pseg.cut(text)]ret = ner.extract_taggedtokens(sent)print(ret)#### Custom crfsuite modelSimCrf aim to provide a simple and easy way to train and extract entities.It take off the feature trasfroming and trainning apart from you.So to customize crf model, you need train a sklearn-crfsuite model. You would change trainning parameter and generation of features yourself, and pass the model to SimCRF:from simcrf import SimCRFimport sklearn_crfsuitecrf_model = sklearn_crfsuite.CRF(algorithm='lbfgs',c1=0.1,c2=0.1,max_iterations=100,all_possible_transitions=True)crf_model.fit(X_train, y_train)ner = SimCRF(crf_model)ret = ner.extract(sent)sklearn-crfsuite docs: https://sklearn-crfsuite.readthedocs.io/crfsuite docs: http://www.chokkan.org/software/crfsuite/manual.html
Package: simc-support
simc_supportData to support simulations for World of Warcraft with SimulationCraft for each current expansion. First three versioning numbers match World of Warcrafts' build version.Installationpipinstallsimc-supportUsageGet a list of all trinketsfromsimc_support.game_data.TrinketimportTRINKETSfortrinketinTRINKETS:print(f"{trinket.item_id}{trinket.name}")Get a list of all trinkets available to a specific specfromsimc_support.game_data.WowSpecimportget_wow_specfromsimc_support.game_data.Trinketimportget_trinkets_for_specelemental_shaman=get_wow_spec("shaman","elemental")trinkets=get_trinkets_for_spec(elemental_shaman)fortrinketinTRINKETS:print(f"{trinket.item_id}{trinket.name}")Data OriginData in.pyfiles was written by hand.Data in.jsonfiles is automatically generated with the help of SimulationCrafts casc and dbc scripts. See./simc_support/self_update.pyin the repository for more informtion.Exception: Dragonflight Talent data (also.jsonfiles) is being prepared byraidbots.com. Permission was granted to use it here.
Package: sim-csv-script
SIM CSV ScriptPython script to read and write SIM cards.
Fields and values are specified in a CSV file, and optionally a filter script can be supplied as a command line argument for dynamically changing the CSV contents for each card.System RequirementsPython 3.6 or later (Python Installation Steps)InstallationMethod #1: Source Distribution (.tar.gzfile)Windowspython -m pip install --upgrade {sim_csv_script-VERSION.tar.gz}Linuxpython3 -m pip install --upgrade {sim_csv_script-VERSION.tar.gz}Method #2: Source CodeFirst, change into the directory that containssetup.pyorsetup.cfgfileWindowspython -m pip install --upgrade -e .Windows: if you get a "swig.exe" error while running the installation command, you will need to download the swig prebuilt executable (http://www.swig.org/download.html), extract the zip, and add the folder to your PATH.  Try running the installation steps again, and if it fails with a "Visual Studio Build Tools" error, then you will need to downloadhttps://visualstudio.microsoft.com/visual-cpp-build-tools/, install it, and select the "Desktop development with C++"Linuxpython3 -m pip install --upgrade -e .Linux: if you get a "swig: not found" error while running the installation command, first ensure that Python 3.6 or later is installed (python3 --version).  If so, install swig withsudo apt install swigand retry the installation commandCOMMAND LINE SCRIPTHelp and Documentationsim_csv_script -hList valid field names that can used in CSV filesim_csv_script --list-field-namesExample Read Singlesim_csv_script {example.csv}Example Write Single (reading ADM pin from CLI arg)Specify ASCII ADM pin without the leading "0x"sim_csv_script {example.csv} --write --pin-adm 0x8888888888888888Example Write Single (reading hexadecimal ADM pin from JSON file with {"IMSI key" : "ADM pin value"})Specify ASCII ADM pins without the leading "0x"sim_csv_script {example.csv} --write --pin-adm-json {IMSI_TO_ADM.json}Example Read Multiplesim_csv_script {example.csv} --multipleFilter ScriptWindows: substitutepython3withpythonProvide a filter script (doesn't have to be Python) that reads in a CSV file from STDIN, modifies it, and outputs a new CSV file to STDOUTThe filter script should function as a standalone program "python3 filter_script.py {arg1} < {example.csv}", and print out the filtered csv fileOn Windows, run this in Command Prompt because Powershell does not have the "<" operatorIn theory if standalone program works, copy and paste everything before the "<" as the--filter. (e.g. "--filter python3 filter_script.py {arg1}")Filter script must exit with a 0 return code to indicate Success.Any other return code will be treated as failureIf each card needs different filter script arguments, specify--ask-filter-args.User will be prompted for input, which will be appended to end of--filterExample Read Multiple with --filtersim_csv_script {example.csv} --multiple --filter python3 filter_script.py {arg1}Example Read Multiple with --filter and --ask-filter-argssim_csv_script {example.csv} --multiple --filter python3 filter_script.py --ask-filter-argsForDevelopment Documentation
Package: simcubeltd-pulumi-nexus
Sonatype Nexus ProviderSonatype Nexus WebsiteBased on thenexus terraform providerby datadrivers.The Nexus resource provider for Pulumi lets you use and manage Sonatype Nexus resources in your Infrastructure as Code deployments.InstallingThis package is available in C#, TypeScript, Python and Go.NETTo use from .NET, install usingdotnet add package:dotnetaddpackagePulumi.NexusNode.js (Java/TypeScript)npminstall@simcubeltd/pulumi-nexusoryarn:yarnadd@simcubeltd/pulumi-nexusPythonTo use from Python, install usingpip:pipinstallsimcubeltd_pulumi_nexusGoTo use from Go, usego getto grab the latest version of the library:gogetgithub.com/SimCubeLtd/pulumi-nexus/sdk/go/nexusConfigurationThe following configuration entries are available:KeyValuenexus:insecureBoolean, true if http, false if https.nexus:urlUrl to the nexus instance, including relevant port.nexus:usernameAccount Username for Nexus (account must have admin role).nexus:passwordAccount password for Nexus (account must have admin role).
Package: simcubeltd-pulumi-onepassword
1Password Provider1Password WebsiteBased on the1Password terraform providerThe 1Password resource provider for Pulumi lets you use 1Password resources in your Infrastructure as Code deployments.InstallingThis package is available in C#, TypeScript, Python and Go.NETTo use from .NET, install usingdotnet add package:dotnetaddpackagePulumi.OnepasswordNode.js (Java/TypeScript)npminstall@SimCubeLtd/pulumi-onepasswordoryarn:yarnadd@SimCubeLtd/pulumi-onepasswordPythonTo use from Python, install usingpip:pipinstallsimcubeltd_pulumi_onepasswordGoTo use from Go, usego getto grab the latest version of the library:gogetgithub.com/SimCubeLtd/pulumi-onepassword/sdk/go/onepasswordConfigurationThe following configuration entries are available:KeyValueonepassword:tokenThe access token for your 1Password Connect serveronepassword:urlURL where your 1Password Connect API is being served
Package: simcx
Simulator for Complex Systems. Developed for the course in Complex Systems from
the Department of Informatics Engineering of the University of Coimbra. This
software is still in beta stage. Tutorials and documentation are available, but
are still in development (check link above).Note that due to its main purpose (education), most of the code is written with
a focus on readability, rather than performance.Copyright (c) 2015-2023 Tiago Baptista -baptista@dei.uc.ptLicensed under the Apache License, Version 2.0 (see LICENSE.txt)DependenciesPython 3 (http://www.python.org) (should also work on Python 2.7)pyglet (http://www.pyglet.org)matplotlib (http://www.matplotlib.org)numpy (http://www.numpy.org)pyafai (https://github.com/tbaptista/pyafai)numexpr (https://github.com/pydata/numexpr) (optional)Main AuthorsTiago BaptistaErnesto Costa
Package: simd5
si_md5_filePython module to create MD5 files for digital deliveries.A project of the Digitization Program Office, OCIO, Smithsonian.https://dpo.si.edu/InstallationTo install:python3-mpipinstallsimd5To upgrade add-U:python3-mpipinstall-Usimd5UsageTo create a MD5 file with the filenames and hashes:fromsimd5importsimd5simd5.md5_file(folder="files",fileformat="m f",workers=4)The command can take these arguments:folder: Which folder to run in. Will ignore subfolders.fileformat: What format to use when creating the MD5 file:
**m f:[MD5 hash] [filename](space-separated)
**f m:[filename] [MD5 hash](space-separated)
**m,f:[MD5 hash],[filename](comma-separated)
**f,m:[filename],[MD5 hash](comma-separated)workers: How many parallel processes to use. By default, it will use the number of cores found in the system.LicenseAvailable under the Apache License 2.0. Consult theLICENSEfile for details.
Package: simdak
SimdakPython client module Simdak KemdikbudFiturFitur export dan import dataSimdak Paud-Dikmas.Legal / HukumKode ini sama sekali tidak berafiliasi dengan, diizinkan, dipelihara, disponsori atau didukung olehKemdikbudatau afiliasi atau anak organisasinya. Ini adalah perangkat lunak yang independen dan tidak resmi.Gunakan dengan risiko Anda sendiri.
Package: simdec
WarningThis library is under active development and things can change at anytime! Suggestions and help are greatly appreciated.Simulation decompositionorSimDecis an uncertainty and sensitivity
analysis method, which is based on Monte Carlo simulation. SimDec consists of
three major parts:computing sensitivity indices,creating multi-variable scenarios and mapping the output values to them, andvisualizing the scenarios on the output distribution by color-coding its segments.SimDec reveals the nature of causalities and interaction effects in the model.
See ourpublicationsand join ourdiscord community.Python APIThe library is distributed on PyPi and can be installed with:pip install simdecTo install the development version, download the source and from the root of
the repository:pip install -e .[dev]DashboardA live dashboard is available at:https://simdec.ioLocal useThe dashboard can be run locally using:make serveDeploymentThe live version of the dashboard is hosted on GCP. To deploy a new version:PANEL_TOKEN=... make productionCitationsThe algorithms and visualizations used in this package came primarily out of
research at LUT University, Lappeenranta, Finland, and Stanford University,
California, U.S., supported with grants from Business Finland, Wihuri
Foundation, and Finnish Foundation for Economic Education.If you use SimDec in your research we would appreciate a citation to the
following publications:Kozlova, M., & Yeomans, J. S. (2022). Monte Carlo Enhancement via Simulation
Decomposition: A “Must-Have” Inclusion for Many Disciplines.INFORMS
Transactions on Education, 22(3), 147-159. DOI:10.1287/ited.2019.0240.Kozlova, M., Moss, R. J., Yeomans, J. S., & Caers, J. (forthcoming).
Uncovering Heterogeneous Effects in Computational Models for Sustainable
Decision-making.Environmental Modelling & Software.Kozlova, M., Moss, R. J., Roy, P., Alam, A., & Yeomans, J. S. (forthcoming).
SimDec algorithm. In M. Kozlova & J. S. Yeomans (Eds.),Sensitivity Analysis
for Business, Technology, and Policymaking Made Easy with Simulation
Decomposition. Routledge.
Package: simdeplower
simdeplower is a python tool that you can use to deploy vCenter Server Appliances and have them
magically configured in simulator mode (or how ever you see fit using a shell script).Getting Startedsimdeplower has been tested extensively on OSX, but should work anywhere that subprocess32 and paramiko will run.
simdeplower requires either VMWare Workstation or Fusion to be successful. From those products simdeplower will use
vmrun and ovftool. simdeplower uses ovftool to deploy (extract) an ova onto the filesystem then uses vmrun to launch
the extracted VMX. Once the VM is up and running simdeplower uses paramiko to ssh in using the default username and
password of “root” and “vmware” and executes a shell script you provide, or a bundled script that will configure the
appliance as a simulator. This only works on VCSA 5.x products because simulator no longer works on 6.xInstallingTo install it is best to create a new virtualenv and install using pip
For detailed instructions see thewikion GitHubContributingTo contribute to simdeplower please follow the fork, branch, pull request work flow. Tests are required where applicable.
All code should follow pep8 standards, and must support python 2.7 When opening a pull request please
do so against the development branch.Python Supportsimdeplower 0.1 and later support Python 2.7Reporting IssuesTo report a problem with simdeplower or to make a feature request open anissueon GitHub.Usage ExamplesSee thewikion GitHubReleasessimdeplower 0.1
Package: simd-structts
simd-structtsMultivariate forecasting using StructTS/Unobserved Components model without MLE param estimation.🤦🏾‍ MotivationI love structts model and Kalman filters for forecasting. Sometimes you just want a model that works out of the box
withoutdesigninga model with a Kalman filter, especially if you need to use long seasonalites and exog variables.
Defining all these state space matrices gets tedious pretty quickly...The code in this repo is an attempt to bring a familiar API to multivariate StructTS model, currently with the simdkalman library as a backend.👩🏾‍🚀 Installationpip install simd-structts📋 WIP:Statsmodels and simdkalman backend implementation.Equal filtered/smoothed/predicted states for level/trend models.Proper testing for multiple python versions.Equal filtered/smoothed/predicted states for exog components.Equal filtered/smoothed/predicted states for long seasonal fourier components.Passing tests for statsmodels-like initialization of model.Pretty API with ABC and stuff.Example notebookGradient methods for finding optimal params
Package: sime-library
Sime librarySime library - это библиотека для Python, которая предоставляет набор функций для улучшения удобности кодаУстановкаВы можете установить библиотеку с помощью pip:pip install sime-libraryИспользованиеЗдесь я не могу расписать всё очень подробно но, у меня есть с сайт с полной документацией библиотеки. Ссылка:https://dmitros-organization.gitbook.io/sime_library/2.LICENSE:MIT LicenseАвторское право (c) [2023] [Dmitro]Данная лицензия разрешает лицам, получившим копию данного программного обеспечения и сопутствующей документации (в дальнейшем именуемыми "Программное обеспечение"), безвозмездно использовать Программное обеспечение без ограничений, включая без ограничений право на использование, копирование, изменение, объединение, публикацию, распространение, sublicense и/или продажу копий Программного обеспечения, а также лицам, которым предоставляется данное Программное обеспечение, при соблюдении следующих условий:Уведомление об авторском праве и данной лицензии должно быть включено во все копии или значительные части Программного обеспечения.ПРОГРАММНОЕ ОБЕСПЕЧЕНИЕ ПОСТАВЛЯЕТСЯ "КАК ЕСТЬ", БЕЗ КАКИХ-ЛИБО ГАРАНТИЙ, ЯВНЫХ ИЛИ ПОДРАЗУМЕВАЕМЫХ, ВКЛЮЧАЯ, НО НЕ ОГРАНИЧИВАЯСЬ, ГАРАНТИЯМИ КОММЕРЧЕСКОЙ ЦЕННОСТИ, ПРИГОДНОСТИ ДЛЯ ОПРЕДЕЛЕННЫХ ЦЕЛЕЙ И НЕНАРУШЕНИЯ ПРАВ. В НИКАКОМ СЛУЧАЕ АВТОРЫ ИЛИ ПРАВООБЛАДАТЕЛИ НЕ НЕСУТ ОТВЕТСТВЕНОСТИ ПО КАКИМ-ЛИБО ИСКАМ, УБЫТКАМ ИЛИ ДРУГИМ ОТВЕТСТВЕННОСТЯМ, БУДЬ ТО В ДОГОВОРЕ, ВИНЕ ИЛИ ИНЫМ ОБРАЗОМ, ВЫТЕКАЮЩИМ ИЗ ИЛИ СВЯЗАННЫМ С ПРОГРАММНЫМ ОБЕСПЕЧЕНИЕМ ИЛИ ИСПОЛЬЗОВАНИЕМ ПРОГРАММНОГО ОБЕСПЕЧЕНИЯ.
Package: simelixir
ElixirModeling blood flow and especially the propagation of the pulse wave in systemic
arteries is a topic that is interesting to the medical society since the shape of the
pressure profiles has diagnostic significance. We build a package that can
simulate blood flow and pressure in large arteries by solving a nonlinear onedimensional
model based on the incompressible Navier-Stokes equations for a
Newtonian fluid in an elastic tube. Our method, however, does not require the
usage of discretized methods for solving differential equations such as the
popular Lax-Wendroff method (LW) but instead uses automatic differentiation to
achieve a similar result.Modeling blood flow and pressure in the systemic arteries has been a topic of
interest both to theoretical and clinical investigators. Thus, research in this area
has a vital interdisciplinary aspect. This project aims to develop a package capable
of performing such simulations using the models we develop to treat
cardiovascular diseases better. This is important since most deaths in developed
countries result from cardiovascular diseases, mostly associated with abnormal
flow in the arteries.The original project's inspiration arose from previous and present efforts to
develop an anaesthesia simulator based on mathematical models. An important
part of which is having a good model for the cardiovascular system.
However, as stated previously, the traditional focus of such projects generally is
developing a good model.The choice of the method to be used to solve the associated equations generally
comes from a standard list of such methods.We present a new method that, unlike its predecessors, offers a continuous
solution, along with other benefits such as GPU support, a massive community,
and such like.Watch our video that highlights the fundamental idea of the project.
Package: simemobilecity
SimeMobileCity: Charging Infrastructure Simulation SuiteDocumentationOnline documentation is available atajax23.github.io/SimeMobileCity.The docs include anAPI reference.DependenciesSimeMobileCity supports Python 3.5+.Installation requiresosmnx,scikit-learn,pandasandseaborn.InstallationThe latest stable release (and older versions) can be installed from PyPI:pip install simemobilecityYou may instead want to use the development version from Github:pip install git+https://github.com/ajax23/simemobilecity.git#egg=simemobilecity

pip install git+https://github.com/ajax23/simemobilecity.git@develop#egg=simemobilecityOr download the repository and install in the top directory via:pip install .TestingTo test SimeMobileCity, run the test in the test directory.DevelopmentSimeMobileCity development takes place on Github:www.github.com/Ajax23/SimeMobileCityPlease submit any reproducible bugs you encounter to theissue tracker.How to Cite SimeMobileCityWhen citing SimeMobileCity please use the currentZenodo DOIcorresponding to the used SimeMobileCity version. (Current DOI is listed in the badges.)
Package: simerse
Simerse Python ToolsIf you can't be bothered digging through the output files of your Simerse dataset,
then the official Simerse Python Tools are for you.Currently the tools includeThe Simerse Data Loader, which loads datasets into friendly Python objectsThe Simerse Data Visualizer, which makes it easy to visualize Simerse dataset observationsFor more on how to use the tools, visithttps://www.simerse.com/learnfor tutorials and documentation!Or, check out the source (with examples) athttps://github.com/Simerse/Python-Tools