Saravanan666/pypi-org huggingface dataset:
Package: sblibs
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.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.Download-URL: https://github.com/studyblue/sblibs/archive/0.0.9.tar.gzDescription-Content-Type: UNKNOWNDescription: StudyBlue Python Common Libraries=================================A Collection of commonly used libraries to be used inside our various projects.Platform: UNKNOWNClassifier: Topic :: UtilitiesClassifier: Programming Language :: PythonClassifier: Operating System :: MacOSClassifier: Programming Language :: Python :: 2.4Classifier: Programming Language :: Python :: 2.5Classifier: Programming Language :: Python :: 2.6Classifier: Programming Language :: Python :: 2.7Classifier: Programming Language :: Python :: 3Classifier: License :: OSI Approved :: BSD License
Package: sblog
SBlog========##IntroThis is a simple static blog generator.markdown,ga,disqus are supported.##Usage###1. install`$ python setup.py install`###2. build an environment`$ cd /new/dir/``$ sblog`###3. config`$ vi config.ini`###4. write`$ vi content/sth.mkd`demo:<pre># hello world* date: 0000-00-00* folder: test--------content with markdown supporting~~~pythonsource code here~~~</pre>###5. build site`$ sblog`View [online demo](http://blog.xiaoba.me)##LICENSEThe MIT LicenseCopyright (c) 2012 Yuwei Ba##CHANGE LOGv2.0.0: Rebuildv1.0.2: Mobile Phone Compatiblev1.0.1: Support Sina Weibo "Associating Blog"
Package: sblu
Python library and associated scripts for munging data files from
ClusPro/FTMap/etc.InstallationFrom PyPIEnsure you havepip, then run:[sudo]pipinstallsbluFrom sourceFirst, install psfgen (see below) if you’re planning to usepdbprepfunctionality.Clone the repository to your local machine:gitclonegit@bitbucket.org:bu-structure/sb-lab-utils.gitAfter cloning, you should be able to install using:cdsb-lab-utils[sudo]pipinstall-rrequirements/development.txtpytest[sudo]pythonsetup.pyinstallsudois only needed if you are installing it globally.
We recommend use of Anaconda (https://www.continuum.io).RequirementspsfgenBuilding PSF files requires psfgen utility from NAMD package.Download recent precompiled version of NAMD (2.12 Linux-x86_64-multicore) fromhttp://www.ks.uiuc.edu/Development/Download/download.cgi?UserID=&AccessCode=&ArchiveID=1501(registration is required).Extract the archive and copy the psfgen binary to/usr/local/bin/(or, if you wish, any other location listed in yourPATHenvironment variable):tarzxfNAMD_2.12_Linux-x86_64-multicore.tar.gz&&sudocpNAMD_2.12_Linux-x86_64-multicore/psfgen"/usr/local/bin/"Python modulesIf you’re using Anaconda or already have NumPy installed from any other source,
then you should be fine just runningpip install-rrequirements/development.txt.If you don’t have NumPy, you might get a crypticNo files/directories in/tmp/pip-install-xxxxx/ProDy/pip-egg-info(fromPKG-INFO)error during this step.To resolve it, just install NumPy manually:pip installnumpy>=1.10, and then re-run the command above.UsageSome basic examples are included in the examples directory.
Package: sbmising
SBM IsingThis repository uses Ising model (simulated annealing) to recover labels of stochastic block model.NoteThe code in this repository can only recover symmetric SBM.
Symmetric SBM means that the communities have equal size.The SBM generator is $\textrm{SBM}(n, k, \frac{a \log n}{n}, \frac{b \log n}{n})$.Sample codefromsbmisingimportSIBM,sbm_graphG=sbm_graph(100,2,16,4)X=SIBM(G,k=2)print(X)Reference[1] Zhao, Feng, Min Ye, and Shao-Lun Huang. "Exact Recovery of Stochastic Block Model by Ising Model." Entropy 23.1 (2021): 65.
Package: sbml2dae
SBML2dae: a customizable SBML to Matlab parserDescriptionAt the same time as we developedOneModel, we created SBML2dae: a SBML-compatible python package which provides programming tools to generate SBML exporters to other programming languages for simulation or analysis.
SBML2dae is open-source and complies with OneModel's design philosophy.By default, SBML2dae only allows exporting SBML to Matlab.
However, it is straightforward for an expert user to create a new parser for another programming language such as Modelica, Julia, or Python.
We expect more syntactic parsers to be incorporated using SBML2dae (by our group or by the community).The differences with other Matlab parsers are (i) SBML2dae allows the simulation of algebraic loops (an indispensable element for the simulation of reduced-order models, using the quasi-steady-state approximation), (ii) it generates Matlab code using classes that significantly facilitates the integration of the models with the rest of Matlab tools and (iii) SBML2dae is easily modifiable to change the way of exporting the models.MotivationThere are excellent tools for simulation and analysis of SBML models, but one of the most significant drawbacks is when the tool does not fit the needs of pre-existing workflows.
SBML2dae solves this problem by allowing the user to implement customized SBML parsers that fit their particular workflow quickly.How to setupSBML2dae can be installed from PyPI and is compatible with Python 3.7+ for Window, Mac and Linux.The latest package can be installed with:pipinstallsbml2daeQuick exampleSBML2dae provides a simple command-line interface to export SBML models into Matlab code.Go to the examples folder in this repository and use the following command:sbml2dae export ex01_simple_gene_expression.xmlIt will generate abuildfolder with the SBML model exported into Matlab.CitingIf you use SBML2dae in your research, please use the following citations in your published works:Santos-Navarro, F. N., Navarro, J. L., Boada, Y., Vignoni, A., & Picó, J. (2022). "OneModel: an open-source SBML modeling tool focused on accessibility, simplicity, and modularity."DYCOPS.Santos-Navarro, F. N., Vignoni, A., & Picó, J. (2022). "Multi-scale host-aware modeling for analysis and tuning of synthetic gene circuits for bioproduction."PhD thesis.LicenseCopyright 2022 Fernando N. Santos-Navarro, Jose Luis Herrero, Yadira Boada, Alejandro Vignoni, and Jesús PicóLicensed under the Apache License, Version 2.0 (the "License"); you may not use this software except in compliance with the License. You may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
Package: sbml2julia
SBML2JuliaSBML2Juliais a tool to for optimizing parameters of ordinary differential equation (ODE) models.SBML2Juliatranslates a model from SBML/PEtabformat into Julia for Mathematical Programming (JuMP), performes the optimization task and returns the results.Optimization methodSBML2Juliauses the optimization method presented inScalable nonlinear programming framework for parameter estimation in dynamic biological system models. In brief, contrary to typical parameter optimization methods for ODE systems,SBML2Juliadoes not rely on simulation of the ODE system. InsteadSBML2Juliauses an implicit Euler scheme to time-discretize an ODE system of n equations into m time steps. This transforms the ODE system into a system of n * (m - 1) algebraic equations with n * m variables. These n * m variables (or a subset thereof) can then be cast into an objective function.SBML2Juliathen uses interior-point optimization implemented in the Julia language to minimize the objective function constraint to the n * (m - 1) algebraic equations.InstallationSBML2Juliadepends on several Python and Julia packages. If you have Docker installed on your machine, the easiest way of installing these dependencies is to pull the latestSBML2Julia docker imagefrom Docker Hub and build a container.user@bash:/$ docker pull paulflang/sbml2julia:latest
user@bash:/$ docker run -it paulflang/sbml2julia:latestTo install the latestSBML2Juliaversion in the Docker container, run:user@bash:/$ git clone https://github.com/paulflang/sbml2julia.git
user@bash:/$ python3 -m pip install -e sbml2juliaTo check if the installation was succesful, run:user@bash:/$ sbml2julia -hAlternatively, theSBML2Juliadependencies can be installed as indicated in theDockerfilein theSBML2JuliaGitHub repository. Once these dependencie are installed,SBML2Juliacan be installed as above:user@bash:/$ git clone https://github.com/paulflang/sbml2julia.git
user@bash:/$ python3 -m pip install -e sbml2julia
user@bash:/$ sbml2julia -hInterfacesOptimization tasks can be performed from a Python API or a command line interface.Tutorial, and documentationPlease see thedocumentationfor a description of how to useSBML2Julia.LicenseThe package is released under theMIT license.Development teamThis package was developed byPaul F. Langat the University of Oxford, UK andSungho Shinat the University of Wisconsin-Madison, USA..Questions and commentsPlease contactPaul F. Langwith any questions or comments.
Package: sbmlcore
sbmlcoreCollection of core classes to help with building structure- and chemistry-based feature datasets to train machine learning models to predict antimicrobial resistance.This is under active development and so is subject to change with no notice.We will be making a series of jupyter-notebooks demonstrating how to use the classes availablehere.Included featuresChanges in Amino Acid PropertiesVolumeHydropathy scales: Kyte-Doolittle (paper) and WimleyWhite (paper)Molecular weightIsoelectric pointSecondary structureSTRIDE (websiteandpaper)Solvent accessible surface areasFreeSASA (paper)STRIDE (websiteandpaper)Likelihood of changes in protein functionSNAP2 (serverandpaper)Effect of mutation on protein stabilityDeepDDG: a more recent neural network that claims to outperform DUET, PopMusic etc. (paperandserver). Can do all possible mutations in one job.Structural distancesDistances between mutated residues and any atom/group of atoms of interest. Uses MDAnalysis (paper1andpaper2).To potentially include at a later stageSecondary structure: DSSP (do not anticipate much difference to STRIDE)Protein stability:StabilityPredict. Online metapredictor, single amino acid at a time. Josh used in the pncA paper but had to contact them directly to run the entirity of PncA. (paper)DynaMUT. Also claims to outperform DUET etc. (paper). Can process a list of specified mutations in one job. (server)PWF, 9 May 2023
Package: sbmlmath
sbmlmath - a Python library for handling SBML MathMLThis is Python library for interconvertingSymPyexpressions andSBMLMathML.
SBML uses a subset ofMathMLthat this library
tries to support. This is not (intended to be) a general MathML parser.Main functionality:sympy -> SBML MathMLSBML MathML -> sympyin particular for cases wheresympy.sympify(libsbml.formulaToL3String(...))won't do the jobretaining unit annotations and other<ci>attributesNOTE: This is under development and the API is to be considered unstablePython support policy: sbmlmath followsNEP 29.UsagefromsbmlmathimportSBMLMathMLPrinter,SBMLMathMLParserimportsympyasspsympy_expr=sp.sympify("A ** B + exp(C) * D")mathml=SBMLMathMLPrinter().doprint(sympy_expr)print(mathml)cycled_sympy=SBMLMathMLParser().parse_str(mathml)print(cycled_sympy)assertsympy_expr==cycled_sympy
Package: sbmlplot
Sbmlplot is a python tool built on libSBNE, an API which can read or automatically generate, manipulate, and write SBML Layout and Redner information. Using either the already-included or auto-generated information about Layout and Render extensions of an SBML model, sbmlplot helps you render a static illustration of the biological network of the SBML model through matplotlib and generate a .json file containing the elements and styles information required to render a dynamic illustration of the biological network of the model through cytoscape.js.
Package: sbmlsh
sbmlsh - SBML-shorthandThis page describes a "shorthand" version ofSBMLthat is much easier to read and write by hand than real SBML, together
with a software tool that translates the shorthand model description to
real SBML.It isn't really meant as a complete alternative to GUI model-building
tools. It is just a useful tool for rapid building of essential model
structure. Once the basics are defined, you can translate to SBML and
load up in the GUI tool of your choice.ExampleThe following is a complete description of a simple enzyme-kinetics
model using the shorthand notation.@model:2.3.1=MichaelisMentenKinetics "Michaelis-Menten Kinetics"
@compartments
 cell=1
@species
 cell:Substrate=1000
 cell:Enzyme=100
 cell:Complex=0
 cell:Product=0
@parameters
 k1=1
 k1r=2
@reactions
@rr=SubstrateEnzymeBinding "Substrate-enzyme binding"
 Substrate+Enzyme -> Complex
 k1*Substrate*Enzyme-k1r*Complex
@r=Conversion
 Complex -> Product + Enzyme
 k2*Complex : k2=3You can download this example:mm.mod. Using the translation
tool below, this model translates tothis SBML.Latest SBML-shorthand specificationSBML-shorthand specification, version 3.1.1
(PDF) - targeted at SBML Level 3, Version 1.Python package containing conversion toolspipinstallsbmlshmod2sbml model translation scriptmod2sbml documentation
(PDF) (version 3.1.1.1), which is targeted
at SBML-shorthand version 3.1.1,and all previous versions.sbml2mod reverse translation scriptsbml2mod (version 3.1.1.1) is the reverse
translation tool for Level 3, version 1 and all previous versions.Obviously, as the shorthand specification does not contain all SBML
features, there is likely to be loss involved. However, there should be
no semantic loss in the round-trip SBML-sh -> SBML -> SBML-sh. ie.
doing amod2sbmlconversion followed by asbml2modconversion
should get back to a shorthand file that is semantically equivalent to
the original.
Package: sbmlsim
sbmlsim: SBML simulation made easysbmlsim is a collection of python utilities to simplify simulations withSBMLmodels implemented on top ofroadrunner. Source code is available fromhttps://github.com/matthiaskoenig/sbmlsim.Features include among otherssimulation experimentssimulation reportsparameter fittingThe documentation is available onhttps://sbmlsim.readthedocs.io.
If you have any questions or issues pleaseopen an issue.How to citeContributingContributions are always welcome! Please read thecontributing guidelinesto
get started.LicenseSource Code:LGPLv3Documentation:CC BY-SA 4.0The sbmlsim source is released under both the GPL and LGPL licenses version 2 or
later. You may choose which license you choose to use the software under.This program is free software: you can redistribute it and/or modify it under
the terms of the GNU General Public License or the GNU Lesser General Public
License as published by the Free Software Foundation, either version 2 of the
License, or (at your option) any later version.This program is distributed in the hope that it will be useful, but WITHOUT ANY
WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
PARTICULAR PURPOSE. See the GNU General Public License for more details.FundingMatthias König is supported by the Federal Ministry of Education and Research (BMBF, Germany)
within the research network Systems Medicine of the Liver (LiSyM, grant number 031L0054)
and by the German Research Foundation (DFG) within the Research Unit Programme FOR 5151
“QuaLiPerF(Quantifying Liver Perfusion-Function Relationship in Complex Resection -
A Systems Medicine Approach)” by grant number 436883643. Matthias König has received funding from the EOSCsecretariat.eu which has received funding
from the European Union’s Horizon Programme call H2020-INFRAEOSC-05-2018-2019, grant Agreement number 831644.Installationsbmlsimis available frompypiand
can be installed via:pip install sbmlsimRequirementsHDF5 support is required which can be installed on linux via:sudo apt-get install -y libhdf5-serial-devDevelop versionThe latest develop version can be installed via:pip install git+https://github.com/matthiaskoenig/sbmlsim.git@developOr via cloning the repository and installing via:git clone https://github.com/matthiaskoenig/sbmlsim.git
cd sbmlsim
pip install -e .To install for development use:pip install -e .[development]© 2019-2020 Matthias König
Package: sbmlutils
sbmlutils: python utilities for SBMLsbmlutils is a collection of python utilities for working withSBMLmodels implemented on top oflibsbmland other libraries
with source code available fromhttps://github.com/matthiaskoenig/sbmlutils.Features include among othershelper functions for model creation, manipulation, and annotationHTML reports of SBML modelshttps://sbml4humans.de.file converters (XPP)The documentation is available onhttps://sbmlutils.readthedocs.io.
If you have any questions or issues pleaseopen an issue.How to citeContributingContributions are always welcome! Please read thecontributing guidelinesto
get started.LicenseSource Code:LGPLv3Documentation:CC BY-SA 4.0The sbmlutils source is released under both the GPL and LGPL licenses version 2 or
later. You may choose which license you choose to use the software under.This program is free software: you can redistribute it and/or modify it under
the terms of the GNU General Public License or the GNU Lesser General Public
License as published by the Free Software Foundation, either version 2 of the
License, or (at your option) any later version.This program is distributed in the hope that it will be useful, but WITHOUT ANY
WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
PARTICULAR PURPOSE. See the GNU General Public License for more details.FundingMatthias König is supported by the Federal Ministry of Education and Research (BMBF, Germany)
within the research network Systems Medicine of the Liver (LiSyM, grant number 031L0054)
and by the German Research Foundation (DFG) within the Research Unit Programme FOR 5151
“QuaLiPerF(Quantifying Liver Perfusion-Function Relationship in Complex Resection -
A Systems Medicine Approach)” by grant number 436883643 and by grant number
465194077 (Priority Programme SPP 2311, Subproject SimLivA).
SBML4Humans was funded as part ofGoogle Summer of Code 2021.
Matthias König has received funding from the EOSCsecretariat.eu which has received funding
from the European Union’s Horizon Programme call H2020-INFRAEOSC-05-2018-2019, grant Agreement number 831644.Installationsbmlutilsis available frompypiand
can be installed via:pip install sbmlutilsRequirementstkinteris required which can be installed on linux via:apt-get install python-tk
apt-get install python3-tkPlease see the respective installation instructions for your operating system.Develop versionThe latest develop version can be installed via:pip install git+https://github.com/matthiaskoenig/sbmlutils.git@developOr via cloning the repository and installing via:git clone https://github.com/matthiaskoenig/sbmlutils.git
cd sbmlutils
pip install -e .To install for development use:pip install -e .[development]© 2017-2023 Matthias König
Package: sbmodder
How To Usepoetryinstall
poetryrunsbmodderaddhttps://github.com/cloudflare/hellogopher.githoge
poetryrunsbmodderdeletehoge

poetryshell
sbmodderaddhttps://github.com/cloudflare/hellogopher.githoge
sbmodderdeletehoge確認サブモジュールに変更があった場合: 強制的に削除される
Package: sbmsdp
SBMSDP2This repository uses semi-definite programming to recover labels of stochastic block model.NoteThe code in this repository can only recover symmetric SBM with two underlining communities.
Symmetric SBM means that the two communities have equal size.The SBM generator is $\textrm{SBM}(n, \frac{a \log n}{n}, \frac{b \log n}{n})$.Sample codefromsbmsdpimportsbm2,sdp2G=sbm2(100,16,4)X=sdp2(G)print(X)Reference
Package: sbn
NAMESBN - Skull, Bones and Number (OTP-CR-117/19)SYNOPSISsbn <cmd> [key=val] [key==val]
sbn [-a] [-c] [-d] [-h] [-v]DESCRIPTIONSBN holds evidence that king netherlands is doing a genocide, a
written response where king netherlands confirmed taking note of
“what i have written”, namely proof that medicine he uses in
treatement laws like zyprexa, haldol, abilify and clozapine are
poison that make impotent, is both physical (contracted muscles)
and mental (make people hallucinate) torture and kills members
of the victim groups.

SBN contains correspondence with the International Criminal Court,
asking for arrest of the king of the netherlands, for the genocide
he is committing with his new treatement laws. Current status is
"no basis to proceed" judgement of the prosecutor which requires a
"basis to prosecute" to have the king actually arrested.INSTALL$ pipx install sbnUSAGEwithout any argument the bot does nothing

$ sbn
$

see list of commands

$ sbn cmd
cfg,cmd,mre,now,pwd

the cfg command configures irc

$ sbn cfg
channel=#sbn commands=True nick=sbn port=6667 server=localhost

start a console

$ sbn -c
>

use -v for verbose

$ sbn -cv
SBN started CV started Sat Dec 2 17:53:24 2023
>

start daemon

$ sbnd
$

show request to the prosecutor

$ sbn req
Information and Evidence Unit
Office of the Prosecutor
Post Office Box 19519
2500 CM The Hague
The Netherlands

show how many died in the WvGGZ

$ sbn now
4y18d patient #47324 died from mental illness (14/32/11682) every 44m59sCONFIGURATIONirc

$ sbn cfg server=<server>
$ sbn cfg channel=<channel>
$ sbn cfg nick=<nick>

sasl

$ sbn pwd <nsvnick> <nspass>
$ sbn cfg password=<frompwd>

 rss

$ sbn rss <url>
$ sbn dpl <url> <item1,item2>
$ sbn rem <url>
$ sbn nme <url< <name>COMMANDScfg - irc configuration
cmd - commands
mre - displays cached output
now - show genocide stats
pwd - sasl nickserv name/pass
req - reconsider
wsd - show wisdomSYSTEMDsave the following it in /etc/systems/system/sbn.service and
replace "<user>" with the user running pipx


[Unit]
Description=Skull, Bones and Number (OTP-CR-117/19)
Requires=network-online.target
After=network-online.target

[Service]
Type=simple
User=<user>
Group=<user>
WorkingDirectory=/home/<user>/.sbn
ExecStart=/home/<user>/.local/pipx/venvs/sbn/bin/sbnd
RemainAfterExit=yes

[Install]
WantedBy=multi-user.target


then run this

$ mkdir ~/.sbn
$ sudo systemctl enable sbn --now

default channel/server is #sbn on localhostFILES~/.sbn
~/.local/bin/sbn
~/.local/bin/sbnd
~/.local/pipx/venvs/sbn/AUTHOROTP-CR-117/19 <skullbonesandnumber@gmail.com>COPYRIGHTSBN is Public Domain.