Saravanan666/pypi-org huggingface dataset:
Package: varvar
varvarPython package to model variance in different waysMultiplicative variance trees and the varvar algorithmvarvar is a greedy algorithm for multiplicative variance trees.varvar is to variance as lightgbm/xgboost/... are to expectation.There are currently two implementations of varvar algorithms:using quantile search at every split (invarvar.qtrees)using histograms, with binning before starting (invarvar.htrees)Quantile search is much slower, but can be more accurate.This is similar to the "exact" and "hist" modes in xgboost, except our "exact"
algorithm goes over a small (exact) subset of each feature.Both implementation modules have amultiplicative_variance_treesfunction.Usevarvar.predictfor prediction.The trees are returned as plain python types and can be serialized with pickle
or even as json.Here is an example:from varvar.htrees import multiplicative_variance_trees
from varvar import predict
import numpy as np

random = np.random.RandomState(1729)
n = 200000
x = random.uniform(-1000, 1000, n)
correct_threshold = 300
sigma = 1 * (x <= correct_threshold) + 30 * (x > correct_threshold)
e = sigma * random.randn(n)

trees = multiplicative_variance_trees(
    [x], e**2,
    num_trees=1, max_depth=1, mingain=1, learning_rate=1,
    q=np.linspace(0, 1, 100)[1:-1]
)
preds = predict(trees, [x])

found_threshold = trees[1][0][1]
print(correct_threshold, found_threshold)  # 300, 295
print(np.sqrt(min(preds)), np.sqrt(max(preds)))  # 1, 30conversion to xgboost boosterYou can convert multiplicative variance trees to an xgboost booster.This allows you to use xgboost's predict function (which actually seems to be a bit slower), and more importantly to use the shap package
to interpret varvar predictions.from varvar import mvt_to_xgboost
booster = mvt_to_xgboost(trees)You need xgboost installed to run this code.
Package: varwizard
VarWizardIntroductionVarWizard is a language model-based tool to help generate more meaningful variable names in source code than the original version. It supports 10 programming languages: c, cpp, java, javascript, go, python, php, c_sharp, ruby, rust.InstallationYou can easily install this package by the commandpipinstallvarwizardUsageCommand-lineYou can use VarWizard by running the commandvarwizard[--model-name{bloom-560m,codet5-base}(default:bloom-560m)]--inputINPUT--lang{c,cpp,java,php,go,javascript,ruby,rust,python,c_sharp}[--output-pathOUTPUT_PATH(default:None)][--max-input-lenMAX_INPUT_LEN(default:400)][--deviceDEVICE(default:cpu)][--penalty-alphaPENALTY_ALPHA(default:0.6)][--top-kTOP_K(default:4)][--max-new-tokensMAX_NEW_TOKENS(default:100)]Details for each argument can be found byvarwizard --helpPython APIAnother way is to Python methods.
Here is a simple example of VarWizard.fromvarwizardimportVarWizardmodel=VarWizard(model_name="codet5-base")code="""function chunkData(str, chunk) {var chunk = [];var length = str.length;var i = 0;for (; i < length; i += chunk) {if (i + chunk < length) {chunk.push(str.substring(i, i + chunk));} else {chunk.push(str.substring(i, length));}}return chunk;}"""print(model.make_new_code(code,'javascript',device='cuda:0'))VarWizard produces the outputfunctionchunkData(str,chunk){varchunk=[];varlength=str.length;vari=0;for(;i<length;i+=chunk){if(i+chunk<length){chunk.push(str.substring(i,i+chunk));}else{chunk.push(str.substring(i,length));}}returnchunk;}Playground: You can play at the link:https://varwizard.loca.lt. At the first time to access, you may need to enter: 4.193.50.237ExamplesThere are some examples for varWizard's usage. We can navigate to the folder $examples$ and then go to any subfolder to run the script.
Package: varwwwhtml
servestaticservestatic is a lightweight Python module that provides a simple HTTP server for serving static files. It offers an easy-to-use solution for quickly hosting static web content locally. Whether you're developing a small web application or need a temporary server for testing purposes, servestatic has got you covered.Key FeaturesSimple and intuitive HTTP server for static filesLightweight and easy to installMinimal dependenciesCompatible with Python 3.xInstallationYou can install servestatic via pip, which is the recommended method:pipinstallservestaticUsageTo start serving your static files, follow these steps:Open a terminal and navigate to the folder where your static project is located.Run the following command:python-mservestaticThe server will start running, and you can access your static content by opening a web browser and entering the server's URL.
Package: vaslapp5generator
# VaslApp v5 generator
This repository provided for vasl baas team to generate initial stuff for a new entity,
including entity class, repository, service, adapter and so on.## Installationpip install vaslapp5generator## Configuration
Provide a config file where you want to use the command.
Useconfig.example.pyto provideconfig.pyconfiguration file.## Usage### Config file
Run the command to generate a sample config file namedva-config.json.`vaslapp5generator config`Then you need to edit this file according to your needs.### Generate files for an entityAfter generating and editing config file, run this command to generate entity.`vaslapp5generator entity`
Package: vaspplotsuite
VASP Plot Suite(C) AG 2022Vasp Plot Suite is a program for processing and plotting electronic structure data
from VASP calculations output. It has two modules:a) DosApp: for plotting electronic density of states (eDOS),b) BandsApp: for plotting electronic band structure.Instructions for each of module can be found in their respective README files.This library is available via pip:pip install vaspplotsuiteAfter that, you can run it from your command line by typingvaspplot.ExecutablesThis program can be compliled into an executable.
I can provide ones for Windows or MacOS upon request.This program is still being testedIf you notice any errors or discrepancies, or if you have any practical suggestions,
I would be grateful if you report them.
I have also included sample data for AgF2 system if you want to give it a try.Contactcontact@adamgrzelak.comUpdate history15.05.2022 - updated fonts13.05.2022 - added command line script12.05.2022 - publication of version 1.0 Vasp Plot Suite as a whole on PyPI11.05.2022 - publication of functional BandsApp10.05.2022 - incorporatedmatplotlibwidget into the main window05.05.2022 - refactored the application to readvasprun.xml21.03.2022 - incorporated exception handling into vasp-dos-tools and refactored frontend to
display them
Package: vasprocar
VASProcar Copyright (C) 2023   -   GNU GPL-3.0 licenseVASProcar is an open-source package written in the Python 3 programming language, which aims to provide an intuitive tool for the post-processing of the output files produced by the DFT VASP or QE code, through an interactive user interface.VASProcar extracts information and results from the following VASP output files (CONTCAR, KPOINTS, OUTCAR, PROCAR, DOSCAR, LOCPOT, PARCHG and vasprun.xml) or QE output files (scf.in, scf.out, nscf.in, nscf.out, bands.in, bands.out, projwfc.in, projwfc.out, "filband", "filproj".projwfc_up and "filpdos".pdos_atm#_wfc).Please use the following DOI (10.5281/zenodo.6343960) to cite the use of the code in publications.Repositories:ZENODO,GitHub, andPyPiFor more informations/questions send an e-mail to:augusto-lelis@outlook.comInstallationRequirementsNumpyScipyMatplotlibPlotlyMoviepyKaleidoUsing Pip:pipinstallvasprocarManual Installation:pythonmanual_installation.pyRun Code:python-mvasprocar
Package: vasprun-xml
vasprun-xml is used for quick analysis of vasp calculation solely from vasprun.xml. It has the following features:band gap calculationdos plot (total dos / orbital partial dos / atomic partial dos)band structure plot (with color map enhancement)incar/potcar/poscar generationforce analysysKS orbital eigenvalue analysysdynamical matrixelastic constants (to add)dielectric constantspolarizationA full documentation has been moved tohttps://vasprun-xml.readthedocs.io/en/latest/index.html
Package: vasp-suite
vasp_suitevasp_suiteis a package for generating input and submission files for vasp calculationsInstallation viapipInstallvasp_suiteusingpip(if using a shared machine, add the--userargument afterinstall)pip install vasp_suiteUpdatingUpdate the code usingpip(if using a shared machine, add the--userargument afterinstall)pip install vasp_suite --upgradeInstallation withpipeditable installOnly do this if you are developing (i.e. changing) the code.Clone a copy of this repository, preferably while within a directory called gitmkdir -p git; cd git
git clone https://gitlab.com/chilton-group/vasp_suiteNavigate to the package directorycd vasp_suite/packagesand install the package in editable mode (if using a shared machine, add the--userargument afterinstall)pip install -e .When you're done developing (i.e. your changes have been merged to the master),
or if you just want to use the current release version of the package, uninstall usingpippip uninstall vasp_suiteand follow the Installation viapipinstructions above.UsageThevasp_suitecommand line interface can be invoked withvasp_suite -hwhich prints a list of available subprograms.Alternatively, the individual submodules can be imported into a python program or script as per usual.Building a.whlfile (Advanced)Only do this if you are told to.To build a copy of thevasp_suite.whlfile, move to thepackagedirectory.Now run./build_binaries.shThen install the.whlfile withpip(if using a shared machine, add the--userargument afterinstall)pip install dist/*.whlDocumentationThedocumentationfor this package is hosted by gitlab, and is automatically generated whenever new code is committed to themainbranch. The automatic generation of this documentation relies on a common layout for comments and docstrings within the code, seecontributingfor more information.DevelopmentBefore making changes to this repository, please follow the steps outlined in theChilton group wiki.BugsIf you believe you have a bug,please check that you are using the most up to date version of the code.If that does not fix the problem, please create an issue on GitLab detailing the following:The commands you enteredThe error messageRemember to simplify the problem as much as possible in order to provide a minimum working example, e.g. an example for a small molecule rather than one with 100000 atoms.Then, look at the code, try and figure out what you think is wrong if possible, and include this in your issue.
Package: vasptools
vasptoolstools for vaspInstallationpipinstallvasptoolsCLI mode$vasptools-h
usage:vasptools[-h][-p][-ppathPATH][-t][-tdPATH][-s][-D][-V]subcommand...

VASPTOOLS

positionalarguments:subcommandpotcarPOTCARincarINCARLISTSUBCOMMANDlistallsubcommands,justfortestoptionalarguments:-h,--helpshowthishelpmessageandexit-p,--previewpreview-ppathPATH,--potpathPATHsetvasppot_path,youcouldalsosetenvVASPPOT-t,--testruntest-tdPATH,--test_dirPATHtest_dir-s,--shellshellmode,execshellscript-D,--DEBUGdebug-Vshowprogram's version number and exit$ vasptools potcar -husage: vasptools potcar [-h] [-i PATH] [-d PATH] [-p PTYPE] [-l][pp_names [pp_names ...]]positional arguments:pp_namesoptional arguments:-h, --help            show this help message and exit-i PATH, --input PATHGenerate POTCAR with POSCAR-d PATH, --dirname PATHdirectory to generate file-p PTYPE, --ptype PTYPEpotcar type, avail: ['potcar', 'potcarGGA', 'potpaw','potpaw_GGA', 'potpaw_PBE']-l,--listlistavailablepotcarPOSCAR>>>fromvasptoolsimportpotcar>>>potcar.get_potcar_content(pp_names=['H','He','Li',pp_type='potpaw_PBE')' PAW_PBE H 15Jun2001\n1.00000000000000000\nparameters from PSCTR are:\nVRHFIN =H: ultrasoft test\n'>>>potcar.gen_potcar(pp_names=['H'],pp_type='potpaw_PBE')INCAR>>>fromvasptoolsimportincar>>>incar_dict=incar.parse_incar(incarfile)>>>print(incar_dict)OrderedDict([('system','si series'),('prec','accurate'),('encut','245.345'),('ibrion','-1'),('nsw','0'),('nelmin','2'),('ediff','1.0e-05'),('ediffg','-0.02'),('voskown','1'),('nblock','1'),('lvtot','.true.'),('nelm','60'),('algo','fast   (blocked davidson)'),('gga','pe'),('ispin','1'),('iniwav','1'),('istart','0'),('icharg','2'),('lwave','.false.'),('lcharg','.true.'),('addgrid','.false.'),('lhyperfine','.false.'),('ismear','0'),('sigma','0.2'),('rwigs','1.11')])>>>print(output_incar(incar_dict))system=siseriesprec=accurateencut=245.345ibrion=-1nsw=0nelmin=2TODOINCARPOSCARKPOINTSOUTCARDOSCARCHGCARCHGWAVECAR...
Package: vasp-tools
VASP Tools is a set of modules and scripts that automate routine tasks
involving VASP files using a very intuitive CLI. The/scriptsdirectory contains the scripts that implement the/vaspmodule to
perform routine tasks on VASP files. This project is still a WIP and new
scripts/modules will be added regularly over the next few weeks.RequirementsAs of now, this package is only supported onPython>=3.5. Since
support forPython 2.7is set to be pulled by 2020, updates in the
near future extending support toPython<=3.0seems unlikely.The following libraries are required to run all the scripts and modules.
-numpy-argparse-sympy-ujson-jsonschema-tabulateFor a full list of requirements, read requirements.txt. If not already
present within the environment, they’ll be installed as dependencies
during setup.InstallationThe installation process is quite simple, ensure you have a working
version ofPython>=3.5installed and type the following into the
console,pip install vasp-toolsAny required libraries that aren’t installed in the current environment
will be automatically installed. This will also automatically install
the scripts and add them to $PATH for easy access.CompatibilityThe package, so far, was only tested within a Linux environment and
isn’t officially compatible with Windows yet. The scripts can be
compiled into executables usingPyInstallerto work
independently of python on any system, though it should be run in an
environment with an identical OS. Use of VMs/Containers is suggested,
though not tested as of yet.UsageThe code present in/vaspcan be imported in the form of standard
modules. However, the primary purpose of this project was the creation
of scripts (present in/scripts) to automate daily tasks faced by
the Computational Chemist/Material Scientist. With this in mind, the
scripts were designed to be extremely modular and user-friendly by
implementing a`dplyr<https://style.tidyverse.org/pipes.html>`__-esque piping
paradigm. For example, the process of:Importing a molecule from aPOSCARfile.Rotating it into a certain configuration (90 degrees wrt the x-axis)Positioning it at a specified point above a crystal taken from
anotherPOSCARfileFixing atomic positions within the crystal below a certain cutoff
heightConverting the coordinates toDirectfromCartesianor vice
versaSave to a newPOSCARfile.can be implemented in a single line like so.cat POSCAR1 | ./rotate.py -x 90 -y 10 | ./place-at.py "POSCAR2" 0.5 0.5 2.0 | ./fix-upto.py 10.0 | ./cart-direct > POSCARnewAlternatively, you can also call each script individually or pass
“POSCAR1” as one of the positional arguments. For example,./place-at.py"POSCAR2" "POSCAR1" 0.5 0.5 2.0is perfectly equivalent tocat POSCAR1 |./place-at.py"POSCAR2" 0.5 0.5 2.0Detailed instructions on how to use the scripts are available indocs.Written with `StackEdit <https://stackedit.io/>`__History0.1.0 (2019-07-19)First release on PyPI.
Package: vaspwiki
IntroductionThe VASP team hosts a very usefulonline VASP manual,
here,
I provide a python interface so that other colleagues in the community of computational
materials and physics
can get access to vaspwiki much easier via executing
commands in their terminals (Linux, Windows, and Mac OS).
The corresponding wiki page of the requested keyword will show up in your defaultweb browser.
(We may need install x11 windows in some terminals)
Searching for several keywords in a batch way
is supported, see details in the section of Usage.InstallationStep 1: install vaspwiki to your virtual environmentTo install vaspwiki, use$ pip install vaspwikior$ git clonehttps://github.com/yw-fang/vaspwiki.git$ cd vaspwiki$ python setup.py installUsageNote that vaspwiki is case-sensitive.Search for one keyword:$ vaspwiki INCARSearch for multiple keywords in one shot:$ vaspwiki INCAR LOCPOTWe can also use vaspwiki in the interactive ipython:In [1]: from vaspwiki import vaspwikiIn [2]: vaspwiki.help_function(‘INCAR’)LicenseMIT LICENSE. See LICENSE file for more details.
Package: vaspy
IntroductionVASPy is a pure Python library designed to make it easy and quick to manipulate VASP files.You can use VASPy to manipulate VASP files in command lins or write your own python scripts to process VASP files and visualize VASP data.In/scripts, there are some scripts written by me for daily use.InstallationVia pip(recommend):pip install vaspyVia easy_install:easy_install vaspyFrom source:python setup.py installIf you want to usemayavito visualize VASP data, it is recommened to installCanopy environmenton your device instead of installing it manually.After installing canopy, you can set corresponding aliases, for example:aliascanopy='/Users/<yourname>/Library/Enthought/Canopy/edm/envs/User/bin/python'aliascanopy-pip='/Users/zjshao/Library/Enthought/Canopy/edm/envs/User/bin/pip'aliascanopy-ipython='/Users/<yourname>/Library/Enthought/Canopy/edm/envs/User/bin/ipython'aliascanopy-jupyter='/Users/<yourname>/Library/Enthought/Canopy/edm/envs/User/bin/jupyter'Then you can install VASPy to canopy:canopy-pip install vaspy
Package: vassal
# Vassal - automated terminal<img title=”vassal_logo” src=”https://s3.amazonaws.com/aws-website-shawnshancom-tm5f7/styles/logo.png” data-canonical-src=”https://s3.amazonaws.com/aws-website-shawnshancom-tm5f7/styles/logo.png” width=”250” height=”250”/>[![license](https://img.shields.io/github/license/mashape/apistatus.svg?maxAge=2592000)](https://github.com/Shawn-Shan/vassal/blob/master/LICENSE)Vassal is a python package provide terminal automation. Save developers unnecessary labor to type in tons of duplicated and similar commands.## Getting StartedRun a list of commands on a ssh server` from vassal.terminal import Terminal shell =Terminal(["sshusername@host", "cd scripts", "python foo1.py", "pythonfoo2.py"])shell.run() `upload/download files through scp` shell =Terminal(["scpusername@host:/home/foo.txtfoo_local.txt"])shell.run() `### Installing` pip install vassal `## Built With[paramiko](http://www.paramiko.org/) - SSHv2 protocol## ContributingPlease read [CONTRIBUTING.md](https://gist.github.com/PurpleBooth/b24679402957c63ec426) for details on our code of conduct, and the process for submitting pull requests to us.## AuthorsShawn Shan-Initial work- [https://www.shawnshan.com/](https://www.shawnshan.com/)## LicenseThis project is licensed under the MIT License - see the [LICENSE](https://github.com/Shawn-Shan/vassal/blob/master/LICENSE) file for details
Package: vastaanottaa
VastaanottaaReceive (Finnish: vastaanottaa) text traversing unknown territories.License: MITThird party dependencies are documented in the folderthird-party.DocumentationUser and developerdocumentation of vastaanottaa.Bug TrackerAny feature requests or bug reports shall go to thetodos of vastaanottaa.Primary Source repositoryThe main source ofvastaanottaais on a mountain in central Switzerland.
We use distributed version control (git).
There is no central hub.
Every clone can become a new source for the benefit of all.
The preferred public clones ofvastaanottaaare:on codeberg- a democratic community-driven, non-profit software development platform operated by Codeberg e.V.at sourcehut- a collection of tools useful for software development.ContributionsPlease do not submit "pull requests" (I found no way to disable that "feature" on GitHub).
If you like to share small changes under the repositories license please kindly do so by sending a patchset.
You can either send such a patchset per email usinggit send-emailor
if you are a sourcehut user by selecting "Prepare a patchset" on the summary page of your fork atsourcehut.StatusExperimental.NoteThe default branch isdefault.
Package: vastai-client
vastai-clientPython client for the Vast.ai cloud rent service. This package provides a Python client, that allows to list, create, destroy GPU instances programmaticaly, using Python.There is an official Vast.aiCLI, however it can only be used through the command line.Installationpipinstallvastai-clientExampleWith the package you can list offers and run selected machines:fromvastai_clientimportVastClientclient=VastClient(api_key=<your_api_key>)available_machines=client.search_offers(search_query='reliability > 0.98 num_gpus=1 gpu_name=RTX_3090',sort_order='dph-')print(available_machines)selected_machine=available_machines[0]client.create_instance(id=selected_machine.id,image='pytorch/pytorch',ssh=True)For more details, watch documentation.LicenseMITCreditsThis project was generated withwemake-python-package. Current template version is:9899cb192f754a566da703614227e6d63227b933. See what isupdatedsince then.
Package: vastdb
VastdbApiis a Python based API designed for interacting withVastDB&Vast Catalog, enabling operations such as schema and table management, data querying, and transaction handling.
Key libraries used in this API include requests for HTTP requests, pyarrow for handling Apache Arrow data formats, and flatbuffers for efficient serialization of data structures.pip install vastdbCreating the initial session with VastdbApi:fromvastdbimportapiimportpyarrowaspaimportvast_flatbuffromvastdb.apiimportVastdbApidefcreate_vastdb_session(access_key,secret_key):returnVastdbApi(host='VAST_VIP_POOL_DNS_NAME',access_key=access_key,secret_key=secret_key)access_key='D8UDFDF...'secret_key='B7bqMegmj+TDN..'vastdb_session=create_vastdb_session(access_key,secret_key)For the complete Guide for the SDK please go to VastData github:https://github.com/vast-data/vastdb_sdk
Package: vastpy
VASTPYThis package is a Python SDK to the VMS (VAST Management System) REST API.While developing against the VMS API use the documentation locally available athttps://vms-host-name/docs.InstallpipinstallvastpyThe package is hosted in PyPI:https://pypi.org/project/vastpy/UsageInitialization:fromvastpyimportVASTClientclient=VASTClient(user='user',password='********',address='vast-vms')The API is straightforward:client.<collection>.get()client.<collection>.post()client.<collection>[<object>].get()client.<collection>[<object>].patch()client.<collection>[<object>].delete()Accessing collections:forviewinclient.views.get():print(view)Creating objects:policy,=client.viewpolicies.get(name='default')view=client.views.post(path='/prod/pgsql',policy_id=default['id'],create_dir=True)Modifying/deleting objects:view,=client.views.get(path='/prod/pgsql')view=client.views[view['id']].patch(protocols=['NFS','SMB'])client.views[view['id']].delete()Reading metrics:client.monitors.ad_hoc_query.get(object_type='cluster',time_frame='5m',prop_list=['ProtoMetrics,proto_name=ProtoCommon,iops','ProtoMetrics,proto_name=ProtoCommon,iops'])Version CompatibilityThis package is compatible with any VAST version as it's schema-less.Python objects are simply translated to URLs:client.collection[object].get()is translated toGET /api/collection/object.