Saravanan666/pypi-org huggingface dataset:
Package: gemcat
GEMCAT: Gene Expression based Metabolite Centrality Analyses ToolCompatibilityThe package is tested for compatibility with Python >= 3.10 on Ubuntu and Windows.InstallationInstall from pip:pip install gemcatOr clone the repository and install GEMCAT from there using:pip install .UsageStandard workflow from the Command-Line Interface (CLI)gemcat ./expression_file.csv ./model_file.xml -e column_name -a pure -g 1.0 -o result_file.csvStandard workflow in Python using a CobraPy modelimport gemcat as gc
results = gc.workflows.workflow_standard(cobra_model: cobra.Model,
                                        mapped_genes_baseline: pd.Series,
                                        mapped_genes_comparison: pd.Series,
                                        adjacency = gc.adjacency_transformation.ATPureAdjacency,
                                        ranking = gc.ranking.PagerankNX,
                                        gene_fill = 1.0
                                        )This will return the changes in centrality relative to the baseline in a Pandas Series.
When using fold-changes as the mapped expression, use a vector of all ones as a comparison.Modularity and ConfigurationGEMCAT is designed to be modular, and its central components can easily be swapped out or appended by other components
adhering to the specifications laid out in the module base classes (primarily adjacency transformation, expression integration, and ranking components).
All classes inheriting from the abstract base classes laid out in the modules are swappable.Core modulesModelThe core of the package is the GEMCAT model structure that contains the model data, integrates the workflow, and calculates the results.AdjacencyDifferent approaches can be used to calculate adjacency in the networks.
We offer alternatives and a platform to create custom algorithms for the model.ExpressionModule covering the mapping of gene values onto reactions in the model via gene product rules.
Providing different algorithms along with a platform to create alternatives.PagerankModule providing ranking algorithms for the models along with a platform to include custom algorithms.workflowsThe workflow module contains example workflows.
To customize the workflow to your needs simply copy the provided functions and switch out the desired steps.ioInput and output functions that create GEMCAT models from different sources.utilsContains common utility functions used throughout the package.verificationFunctions to verify data integrity.
Package: gemclus
[![CircleCI](https://dl.circleci.com/status-badge/img/gh/gemini-clustering/GemClus/tree/main.svg?style=svg)](https://dl.circleci.com/status-badge/redirect/gh/gemini-clustering/GemClus/tree/main)# GEMCLUS - A package for discriminative clustering using GEMINIThegemcluspackage provides simple tools to perform discriminative clustering using the generalised mutual
information (GEMINI).
The package was written to be a scikit-learn compatible extension.You can find the complete documentation of the package here: [https://gemini-clustering.github.io/](https://gemini-clustering.github.io/)The documentation for the latest updates is at: [https://gemini-clustering.github.io/main](https://gemini-clustering.github.io/main/)The official source code can be found here: [https://github.com/gemini-clustering/GemClus](https://github.com/gemini-clustering/GemClus)## Installation### Official packageUse the following instruction for installing the package:`commandline pip install gemclus `The library requires a couple scientific package to run:NumPyScipyPOTScikit-learn### Latest versionYou may download the latest version of the package by installing the content of the repo.`commandline git clonehttps://github.com/gemini-clustering/GemCluscd GemClus pip install . `## ReferenceIf this work helped you, please cite our original NeurIPS work:` Ohl, L., Mattei, P. A., Bouveyron, C., Harchaoui, W., Leclercq, M., Droit, A., & Precioso, F. (2022, October). Generalised Mutual Information for Discriminative Clustering. In Advances in Neural Information Processing Systems. `or`bibtex @inproceedings{ohl2022generalised,title={GeneralisedMutual Information for Discriminative Clustering},author={LouisOhl andPierre-AlexandreMattei and Charles Bouveyron and Warith Harchaoui andMicka{\"e}lLeclercq and Arnaud Droit and Frederic Precioso},booktitle={Advancesin Neural Information Processing Systems},editor={AliceH. Oh and Alekh Agarwal and Danielle Belgrave and Kyunghyun Cho},year={2022},url={https://openreview.net/forum?id=0Oy3PiA-aDp}} `## AcknowledgementsThis work has been supported by the French government, through the 3IA Côte d’Azur, Investment in the Future, project
managed by the National Research Agency (ANR) with the reference number ANR-19-P3IA-0002. We would also like to thank
the France Canada Research Fund (FFCR) for their contribution to the project. This work was partly supported by
EU Horizon 2020 project AI4Media, under contract no. 951911.Also many many thanks to Pierre-Alexandre Mattei, Frederic Precioso and Charles Bouveyron for their contribution
in the GEMINI project, as well as Mickaël Leclercq and Arnaud Droit. Special thanks go to Jhonatan Torres for his
insights on the development.
Package: gemeinsprache
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.Description: gemeinsprache: utility functions and class objects========================>Don't repeat yourself (or do not repeat yourself; aka DRY) is a principle of software development aimed at reducing repetition of software patterns,[1] replacing it with abstractions or using data normalization to avoid redundancy.`Learn more <https://en.wikipedia.org/wiki/Don%27t_repeat_yourself>`_.---------------✨🍰✨Platform: UNKNOWN
Package: gemf
General Ecosystem Modeling FrameworkGEMF is a ecosystem modelling framework written in python.
It is designed to offer an easy to use method for modelling ecosystems with low- to intermediate complexity.The framework offers the functionality to handle non-equilibrium, non-linear interactions.
For the typical use-cases, user do need to write any code but only provide a model configuration.
The use-cases can easily be extended with simple user written functions without needing to change any of the framework code.The framework offers an easy to use method that fits any parameter of the model to mimic the studied system.
For simplicity, the current version of the framework is limited to non-spatially resolved models (box-models).InstallationOn LinuxPython and its package manger (pip) should be preinstalled.
Hence, it can simply be installed through:pipinstallgemfOn Windows:Get the latest python version from here.
For example the 3.8.3 version installer
This also installs pythons integrated package manager (pip).Then, the following install command can be used in windows "powershell":python-mpipinstallgemfQuick StartSee examples.py. For a set of exemplary framework configurations seeconfiguration_filesUsageimportgemfas# A model configuration is defined in a yaml file. To read this file:model=gemf.load_model_configuration('path/to/model_configuration.yml')# To draw a graph visualizing the model configuration:gemf.interaction_graph(model)# To solve the time integration of this model call:forward_results=gemf.forward_model(model)# To also solve the inverse problem as defined in the configuration, call:inverse_results=gemf.inverse_model(model)# To plot the results callgemf.plot.output_summary(inverse_results)For details on the yaml configuration file, seeREADME_YAML.mdThe presented functions offer many (crucial) options, which are discussed in thedocumentation.How does it work?For a conceptual description of the internals of this library, seeREADME_concept.mdExampleA simple example might be a simple NPZD model as presented below:The user needs to define the compartments and interactions between them.
If the model should be fitted, they also need to provide some constraints and some data to fit it to.After that the model automatically generates a graph to visualize the system and to find potential errors in the configuration.Once the model is configured the framework handles the time integration as well as the fitting without any further required user-interaction.The results of such a run might then look like the following:Top left shows the cost of the current model configuration. The cost is a quadratic measure of distance of the current model to the desired model.
Top right shows a output of the model after it reached its steady state for every parameter set tested.
Bottom left shows the all tested parameters sets.
Bottom right shows the full model output of the best fitted model found.
Package: gemfileparser
gemfileparser parses Ruby Gemfile using Python with supports Ruby Gemfiles
and .gemspec files as well as Cocoapod .podspec files.InstallationIn a virtualenv, use the command:pip install gemfileparserOtherwise from a git clone, use the following commands in a virtualenv:git clone https://github.com/gemfileparser/gemfileparser.git
cd gemfileparser
    python setup.py installUsagefrom gemfileparser import GemfileParser
parser = GemfileParser(<path to Gemfile>, <name of the application (optional)>)
dependency_dictionary = parser.parse()The parse() method returns a dict object of the following format:{
    'development': [list of dependency objects inside group 'development'],
    'runtime': [list of runtime dependency objects],
    .
    .
}Each dependency object contains the following attributes:name - Name of the gemrequirement - Version requirementautorequire - Autorequire valuesource - Source URL of the gemparent - Dependency of which gemgroup - Group that a gem is a member of (default : runtime)Examplefrom gemfileparser import GemfileParser
n = GemfileParser('Gemfile', 'diaspora')
deps = n.parse()
for key in deps:
   if deps[key]:
       print key
       for dependency in deps[key]:
           print("\t", dependency)TestsDo this to run tests:pip install -e .
pip install pytest
pytest -vvs testsCopyrightCopyright (c) 2020 Gemfileparser authors (listed in AUTHORS file)Copyright (c) 2015-2018 Balasankar C <balasankarc@autistici.org>Licensegemfileparser is dual-licensed under your choice of theGNU GPL version 3 (or later) Licenseor theMIT License.It is preferred anyone using this project to respect the GPL-3+ license and use
that itself for derivative works - thus making them also Free Software. But,
your call.When making contributions to gemfileparser you agree to license these contributions
under the same choice of licenses.
Package: gemfileparser2
gemfileparser2 parses Ruby Gemfile using Python with supports Ruby Gemfiles
and .gemspec files as well as Cocoapod .podspec files.This is a maintained fork ofhttps://github.com/gemfileparser/gemfileparserthat is no longer active (even though it was maintained by the same folks)InstallationIn a virtualenv, use the command:pip install gemfileparser2Usagefrom gemfileparser2 import GemfileParser
parser = GemfileParser(<path to Gemfile>, <name of the application (optional)>)
dependency_dictionary = parser.parse()The parse() method returns a dict object of the following format:{
    'development': [list of dependency objects inside group 'development'],
    'runtime': [list of runtime dependency objects],
    .
    .
}Each dependency object contains the following attributes:name - Name of the gemrequirement - Version requirementautorequire - Autorequire valuesource - Source URL of the gemparent - Dependency of which gemgroup - Group that a gem is a member of (default : runtime)Examplefrom gemfileparser2 import GemfileParser
n = GemfileParser('Gemfile', 'diaspora')
deps = n.parse()
for key in deps:
   if deps[key]:
       print key
       for dependency in deps[key]:
           print("\t", dependency)TestsDo this to run tests:pip install -e .
pip install pytest
pytest -vvs testsCopyrightCopyright (c) 2020 Gemfileparser authors (listed in AUTHORS file)Copyright (c) 2015-2018 Balasankar C <balasankarc@autistici.org>Licensegemfileparser2 is dual-licensed under your choice of theGNU GPL version 3 (or later) Licenseor theMIT License.It is preferred anyone using this project to respect the GPL-3+ license and use
that itself for derivative works - thus making them also Free Software. But,
your call.When making contributions to gemfileparser2 you agree to license these contributions
under the same choice of licenses.
Package: gemgis-data
Spatial data and information processing for geomodelingOverviewThis repository provides the notebooks and data to theexample modelsof GemGIS and GemPy.For more information about GemGIS and GemPy see the dedicated Github Repositories and Documentation pages:GemGIS RepositoryGemGIS Installation & DocsGemPy RepositoryGemPy Installation & DocsReferencesJüstel, A., Endlein Correira, A., Wellmann, F. and Pischke, M.: GemGIS – GemPy Geographic: Open-Source Spatial Data Processing for Geological Modeling. EGU General Assembly 2021,https://doi.org/10.5194/egusphere-egu21-4613, 2021Jüstel, A.: 3D Probabilistic Modeling and Data Analysis of the Aachen-Weisweiler Area: Implications for Deep Geothermal Energy Exploration, unpublished Master Thesis at RWTH Aachen University, 2020de la Varga, M., Schaaf, A., and Wellmann, F.: GemPy 1.0: open-source stochastic geological modeling and inversion, Geosci. Model Dev., 12, 1-32,https://doi.org/10.5194/gmd-12-1-2019, 2019Powell, D.: Interpretation of Geological Structures Through Maps: An Introductory Practical Manual, Longman, pp. 192, 1992Bennison, G.M.: An Introduction to Geological Structures and Maps, Hodder Education Publication, pp. 78, 1990
Package: gemican
GemicanGemican is a static gemini capsule generator, written inPython, and based on the static site generatorPelican.Write content inMarkdownor directly in Gemtext using your editor of choiceIncludes a simple command line tool to (re)generate capsule filesEasy to interface with version control systems and web hooksCompletely static output is simple to host anywhereFeaturesGemican’s feature highlights include:Chronological content (e.g., articles, blog posts) as well as static pagesSite themes (created using Jinja2_ templates)Publication of articles in multiple languagesGeneration of Atom and RSS feedsImport existing content from WordPress, Dotclear, or RSS feedsFast rebuild times due to content caching and selective output writingCheck outGemican's documentationfor further information.Source codeGemican's source code ishosted on GitHub. If you feel like hacking, take a look atPelican's internals.Why the name "Gemican"?"Gemican" is an anagram ofcamegin, which means nothing.Only joking - Gemican is based on the Pelican static site generator, and took its name from that.
Package: gemini3d
PyGeminiA Python interface toGemini3D, funded in part by NASA HDEE.Setup PyGemini by:gitclonehttps://github.com/gemini3d/pygemini

pipinstall-epygeminiDevelopersFor those working with GEMINI Fortran code itself or to work with non-release versions of GEMINI Fortran code:install PyGemini in development mode as aboveset environment variable GEMINI_ROOT to the Gemini3D Fortran code directory, otherwise PyGemini will Git clone a new copy.Run simulationmake aconfig.nmlwith desired parameters for an equilibrium sim.setup and/or run the equilibrium sim:python-mgemini3d.model/sim_equil/config.nml/path_to/sim_eq/# orpython-mgemini3d.run/sim_equil/config.nml/path_to/sim_eq/create a new config.nml for the actual simulation and runpython-mgemini3d.model/sim/config.nml/path_to/sim_out/# orpython-mgemini3d.run/sim/config.nml/path_to/sim_out/PlotsAn important part of any simulation is viewing the output.
Because of the large data involved, most plotting functions automatically save PNG stacks to disk for quick flipping through with your preferred image viewing program.GridHelp ensure the simulation grid is what you intended by the following, which can be used before or after running the simulation.importgemini3d.plotgemini3d.plot.grid("path/to/sim")simulation outputsThese commands create plots and save to disk under the "plots/" directory under the specified data directory.command line:python-mgemini3d.plotpath/to/data-savepngor from within Python:importgemini3d.plotasplotplot.frame("path/to/data",datetime(2020,1,2,1,2,3),saveplot_fmt="png")# orplot.plot_all("path/to/data",saveplot_fmt="png")Convert data files to HDF5There is a a script to convert data to HDF5, and another to convert grids to HDF5.
The scripts convert from {raw, Matlab, NetCDF4} to HDF5.
The benefits of doing this are especially significant for raw data, and HDF5 may compress by 50% or more, and make the data self-describing.pythonscripts/convert_data.pyh5~/mysimpythonscripts/convert_grid.pyh5~/mysim/inputs/simgrid.dat
Package: gemini-builder
gemini_builderThis Python package makes creation of Gemini text documents forProject Geminia little
easier.To create a document, instantiate the Page class and add lines
using the appropriate methods. Finally, you can convert the
page to a string, print it, etc.MethodsThe following methods are used to add content to the page:add_raw_line(raw_line)Add any text as a line. Be cautious or you will screw everything up.add_text(line=None)Add normal text as a line. Can also be used to add an empty line.add_heading(text, level=1)Add a heading line. You can provide a level of 1, 2 or 3.add_link(url, label=None)Add a link line. The URL must already be properly quoted.add_quote(quote)Add a quote line.add_list(items)Add a list. The items argument should be an iterable that returns strings.add_preformatted_lines(preformatted_lines, alt_text=None):Add a block of preformatted lines. The preformatted_lines argument should be an iterable that returns strings. The optional alt_text argument will be added to the opening toggle line if present.ExceptionsThe following exceptions can be thrown:GeminiBuilderExceptionBase class for all exceptions. Not instantiated.InvalidHeadingLevelExceptionYou tried to add a heading with a level that is not 1, 2 or 3.NotIterableExceptionYou tried to add a list but provided a non-iterable argument.InvalidTextLineExceptionYou provided a text line that starts with one of the reserved characters. Use add_raw_line to add any raw content.PreformattedLineCannotStartLikeThisExceptionOne of your pre-formatted lines begins with the reserved sequence for preformatted lines.
Package: gemini-engine
Gemini EngineGemini Engine is a monospace 2D ASCII rendering engine. It includes collisions, layers, inputs and the ability to handle solid objects as well as ascii art. Examples can be found on theGeminiExamples githubWARNING: It’s important to use a monospace font in the terminal for the engine to render images properlyQuick startGemini Engine can be installed using pip:python3 -m pip install -U gemini-engineIf you want to run the latest version of the code, you can install from github:python3 -m pip install -U git+https://github.com/redpenguinyt/GeminiEngine.git@latestNow that you have installed the library, instance a Scene and an Entity, then render the scenefromgeminiimportScene,Entityscene=Scene(size=(20,10))entity=Entity(pos=(5,5),size=(2,1),parent=scene)scene.render()You should get something like this in your console:Look at that! You just made your first Gemini project! Now try adding a while loop to the end of your codefromgeminiimportScene,Entity,sleepscene=Scene(size=(20,10))entity=Entity(pos=(5,5),size=(2,1),parent=scene)whileTrue:entity.move((1,0))scene.render()sleep(.1)Now the entity should be moving across the screen! When the entity goes out of the screen's bounds it will loop back round to the other side.SpritesThe code below will animate a car moving across the screen:fromgeminiimportScene,Sprite,sleepcar_image="""______/|_||_\`.__(¶¶¶_¶¶¶¶_¶_\\=`-(_)--(_)-'"""scene=Scene((30,10),is_main_scene=True)car=Sprite((5,5),car_image)whileTrue:scene.render()car.move(1,0)sleep(.1)
Package: gemini-pro-class-generator
gemini-pro-class-generatorEven wondered about generating classes with their attributes and methods without manually writing hundreds of
lines of code?Gemini Pro Class Generatoris the tool to do so. This tool generates code for a class in a
programming language of your choice based on the given specifications.Source CodeThe source code of the applicationGemini Pro Class Generatoris available inSource Code.Installationpip install gemini-pro-class-generatorHow to Use the Application?Pre-requisites:Pythoninstalled in your device..env file in the same directory as <GEMINI_PRO_CLASS_GENERATOR_DIRECTORY> and has the value of GEMINI_API_KEY.First, open a Terminal or Command Prompt window and run the following command.cd <GEMINI_PRO_CLASS_GENERATOR_DIRECTORY>
python3 main.pyNote:Replace <GEMINI_PRO_CLASS_GENERATOR_DIRECTORY> with the path to the directory of the applicationGemini Pro Class Generator.Then, the application will start with something looking like in the screenshot below.You will then be asked to input the following values.Temperature - between 0 and 1 inclusiveTop P - between 0 and 1 inclusiveTop K - at least 1Max output tokens - at least 1The following screenshot shows what is displayed after inputting the mentioned values.You will be required to input the following pieces of information.The name of the programming language you want to create a class in.The name of the class you want to create.The number of attributes you want to include in the class.Name and description of each class attribute.The number of methods you want to include in the class.Name and description of each class method.Once you enter the values mentioned above, the file containing the code will be created inside "classes" directory.
Then, you will be asked whether you still want to continue unit testing or not. If you enter 'Y',
you will be redirected to an application window like in screenshot above. Else, you will exit the application.Below demonstrates how a class generated by the application looks like.
Package: gemini-pro-cli
gemini-pro-cliThis application allows users to use Gemini Pro on command-line interface (CLI).Source CodeThe source code for the Gemini Pro CLI application is available inhttps://github.com/GlobalCreativeApkDev/gemini-pro-cli/blob/master/main.py.Installationpip install gemini-pro-cliHow to Use the Application?Pre-requisites:Pythoninstalled in your device..env file in the same directory as <GEMINI_PRO_CLI_DIRECTORY> and has the value of GENAI_API_KEY.First, open a Terminal or Command Prompt window and run the following command.python3 <GEMINI_PRO_CLI_DIRECTORY>/main.pyNote:Replace <GEMINI_PRO_CLI_DIRECTORY> with the path to the directory of the application gemini-pro-cli.Then, the application will start with something looking like in the screenshot below.You will then be asked to input the following values.Temperature - between 0 and 1 inclusiveTop P - between 0 and 1 inclusiveTop K - at least 1Max output tokens - at least 1The following screenshot shows what is displayed after inputting the mentioned values.Next, you will have two choices:Enter a non-empty prompt to receive a response from the AI.Enter an empty prompt to exit the application.Below is an example of what happens when you entered a non-empty prompt.