Saravanan666/pypi-org huggingface dataset:
Package: evt
Estimators and analysis for extreme value theory (EVT).
The package is structured as follows.
Example notebooks are provided as links.TheDatasetobjectperforms sanity-checks and contains plotting routines.Generic plots of the dataset.Maximum-to-sum plot.Mean excess function.Thepeaks over thresholdmethod.Plot the tail.QQ-plot against exponential.Zipf-plot.Theblock maximamethod.Plot block maxima against the dataset.Estimators: calculate estimates andconfidence intervals. Plotting routines for analysis.Hill estimator.
Plot against order statistics.Moment estimator(Dekkers-Einmahl-De Haan).
Plot against order statistics.Maximum likelihood for the generalized Pareto distribution.
Plot fit quality.Maximum likelihood for the generalized extreme value distribution.
Plot fit quality.DocumentationDocumentation is providedhere.
Example notebooks are providedhere.InstallationReleases are made available on PyPi.
The recommended installation method is viapip:pipinstallevtFor a development setup, the requirements are indev-requirements.txt.
Subsequently, the repo can be locallypip-installed.
Package: evt73-distributions
contains two classes for performing calculations and their graphics.Available distributions: -Gaussian -BinomialThese distributions have some methods such as mean calculation, standarddeviation calculation, histograms, sum of distributions, …Each object has its data attribute, so you can put a list on the objectand perform all calculationsExample:from distributions import Gaussian, Binomialdist_gaussian=Gaussian(3, 5)  mean=3, std=5dist_gaussian.data=[1, 3, 5, 6 ,2,  1, 2, 3, 4, 3, 2, 5, 2, 4, 6, 2, 3, 5, 8]dist_gaussian.replace_stats_with_data()dist_gaussian.plot_histogram_pdf()Platform: UNKNOWN
Package: evtech
EVTechSimple tools for working with data provided by Eagleview for the RIT Hack.tiff 2020 HackathonFree software: MIT licenseDocumentation:https://evtech.readthedocs.io.History1.1.0 (2020-01-24)Documentation fixesAdded access to camera elevation1.0.1 (2020-01-22)Documentation build fixes1.0.0 (2020-01-22)Added ability to get shapely geometry of image bounds on groundIncluded example application for measuring height from an image0.7.0 (2020-01-20)Added triangulation functionUpdated usage docsFixed bug in project from camera0.6.0 (2020-01-20)Added height from two points to camera classAdded ray interesection with elevation0.5.0 (2020-01-19)Added ray classAdded project from camera to camera class0.4.0 (2020-01-13)Added coverage checking.Added functions for reading a full dataset with nadirs and obliques0.3.0 (2020-01-08)First release on PyPI.
Package: evtool
evToolAnalyse and display output from the binary stellar-evolution code ev (a.k.a. STARS and TWIN).The code is being developed byMarc van der Sluysof the Department of Physics
at Utrecht University in The Netherlands, and the Netherlands Institute of Nuclear and High-Energy Physics
(Nikhef) in Amsterdam.  The evTool package can be used under the conditions of theEUPL
1.2licence.InstallationThis package can be installed usingpip install evtool.  This should automatically install the
dependency packagespandas, if they haven't been installed already.  If you are
installing by hand, ensure that these packages are installed as well.Example use"""Example Python script using the evTool package."""importevtoolevTool pagesPypi: evTool Python packageGitHub: evTool source codeReadTheDocs: evTool documentationAuthor and licenceAuthor: Marc van der SluysContact:http://marc.vandersluys.nlLicence:EUPL 1.2ReferencesCopyright (c) 2023 Marc van der Sluys
Package: evtt
EvttDjango app that use vosk library to convert voice to text.Quick start1.Add "evtt" to your INSTALLED_APPS in your project setting.py file:INSTALLED_APPS = [
...,
'evtt',
]2.Include the evtt URLconf in your project urls.py like this:path('evtt/', include('evtt.urls')),3.Visithttp://127.0.0.1:8000/evtt/to voice to text.
Package: evtx
pyevtx-rsPython bindings forhttps://github.com/omerbenamram/evtx/.InstallationAvailable on PyPi -https://pypi.org/project/evtx/.To install from PyPi -pip install evtxWheelsWheels are currently automatically built for Python 3.7+ using abi3 tag (which means they are compatible with all version from 3.7 onwards).Supported platforms are:Linux x86_64macOS x86_64macOS arm64 (m1)Windows x86_64Installation from sourcesInstallation is possible for other platforms by installing from sources.This requires a Rust compiler and a recent enough Setuptools and Pip.Runpip install -e .UsageThe API surface is currently fairly limited (only yields events as XML/JSON documents), but is planned to be expanded in the future.This will print each record as an XML string.fromevtximportPyEvtxParserdefmain():parser=PyEvtxParser("./samples/Security_short_selected.evtx")forrecordinparser.records():print(f'Event Record ID:{record["event_record_id"]}')print(f'Event Timestamp:{record["timestamp"]}')print(record['data'])print(f'------------------------------------------')And this will print each record as a JSON string.fromevtx.parserimportPyEvtxParserdefmain():parser=PyEvtxParser("./samples/Security_short_selected.evtx")forrecordinparser.records_json():print(f'Event Record ID:{record["event_record_id"]}')print(f'Event Timestamp:{record["timestamp"]}')print(record['data'])print(f'------------------------------------------')File-like objects are also supported.fromevtx.parserimportPyEvtxParserdefmain():a=open("./samples/Security_short_selected.evtx",'rb')# io.BytesIO is also supported.parser=PyEvtxParser(a)forrecordinparser.records_json():print(f'Event Record ID:{record["event_record_id"]}')print(f'Event Timestamp:{record["timestamp"]}')print(record['data'])print(f'------------------------------------------')
Package: evtx2df
converts Windows Event Logs (EVTX) into pandas DataFrames / CSV filespip install evtx2dfTested against Windows 10 / Python 3.10 / AnacondaThis script provides a convenient way to convert EVTX data into a structured DataFrame format using Pandas, which can facilitate further data analysis, exploration, and visualization.To extract strings from individual files:# Converts evtx into csv from the command line:pythonpath_to_the_package\__init__.py"C:\Windows\System32\winevt\Logs\Microsoft-Windows-AppReadiness%4Admin.evtx""C:\Microsoft-Windows-AppReadinessAdmin.csv"# as well as in a python script, and ...fromevtx2dfimportdataframe_from_evtxdf=dataframe_from_evtx(evtx_file_path=r"C:\Windows\System32\winevt\Logs\Microsoft-Windows-AppReadiness%4Admin.evtx")print(df[19:25].to_string())aa_valueaa_key_0aa_key_1aa_key_2aa_key_3aa_key_4aa_event_record_idaa_timestampaa_kind_of_event191EventSystemTask<NA><NA>12982023-03-2503:07:30.497541+00:00<NA>202023-03-25T03:07:30.497541ZEventSystemTimeCreated#attributes  SystemTime                1298 2023-03-25 03:07:30.497541+00:00             <NA>210EventSystemVersion<NA><NA>12982023-03-2503:07:30.497541+00:00<NA>22http://schemas.microsoft.com/win/2004/08/events/eventEvent#attributes        xmlns         <NA>        <NA>                1297 2023-03-25 03:07:30.497538+00:00             <NA>2372EventEventDataTaskCount<NA><NA>12972023-03-2503:07:30.497538+00:00<NA>24install::Microsoft.MicrosoftEdge_8wekyb3d8bbweEventEventDataTaskId<NA><NA>12972023-03-2503:07:30.497538+00:00<NA># ... finds all evtx files on your HDDevtxdf=list_all_evtx_files_in_path(hdd='c:\\')print(evtxdf[11:15].to_string())aa_pathaa_nameaa_path_onlyaa_sizeaa_size_on_diskaa_createdaa_last_writtenaa_last_accessedaa_descendentsaa_read_onlyaa_archiveaa_systemaa_hiddenaa_offlineaa_not_content_indexed_fileaa_no_scrub_fileaa_integrityaa_pinnedaa_unpinnedaa_directory_flagaa_compressedaa_encryptedaa_sparseaa_reparseaa_attributes11C:\Windows\System32\winevt\Logs\VisualStudio.evtxVisualStudio.evtxC:\Windows\System32\winevt\Logs6963269632b'2023-03-30 19:39:28'b'2023-03-31 19:54:38'b'2023-03-31 19:54:38'00100000000000003212C:\Windows\System32\winevt\Logs\SquidServiceLog.evtxSquidServiceLog.evtxC:\Windows\System32\winevt\Logs6963269632b'2023-03-25 05:52:15'b'2023-03-25 12:53:59'b'2023-03-25 12:53:59'00100000000000003213C:\Windows\System32\winevt\Logs\Microsoft-Windows-Sysmon%4Operational.evtxMicrosoft-Windows-Sysmon%4Operational.evtxC:\Windows\System32\winevt\Logs1894400018944000b'2023-05-17 23:15:01'b'2023-05-18 00:59:07'b'2023-05-18 00:59:07'00100000000000003214C:\Windows\System32\winevt\Logs\State.evtxState.evtxC:\Windows\System32\winevt\Logs6963269632b'2023-03-24 23:46:26'b'2023-03-25 00:06:45'b'2023-03-25 00:06:45'001000000000000032
Package: evtx2pandas
ContentsIntroductionInstallationUsageLicenseIntroductionConvert EVTX (Log file created by the Windows 7 Event Viewer) to pandas, but also CSV, JSON or Dask DataFrame.JSON creation is based on:https://github.com/thibaultbl/evtxInstallationpip install evtx2pandasUsagefrom evtx2pandas.json_to_csv import EvtxParser

# To convert evtx to pandas DataFrame
df = reader.evtx_to_df(evtx_path)

# To convert evtx to Dask DataFrame
dask_dd = reader.evtx_to_dask(json_path)

# To write evtx as json
reader.evtx_to_json(json_path, output_path=temp_file)

mydict = json.load(open(temp_file)) # To read the JSON output as python dict

# To write evtx as CSV
reader.evtx_to_csv(json_path, output_path=temp_file)

df = pd.read_csv(temp_file, sep=";") # To read the CSV output as padnas DataFrameLicenseevtx2pandas is free software; you can redistribute it and/or modify it
under the terms of the GNU General Public License as published by the Free
Software Foundation; either version 2 of the License, or (at your option)
any later version.See the file COPYING for the full text of GNU General Public License version 2.
Package: evue
evueEvue is a high-performance gui framework base an html/css which can run on windows/linux/macos/web/ios/andriod/rtos! Write once, run everywhere!Githubhttps://github.com/scriptiot/evueInstallationUse the package managerpipto install evue.pipinstallevueorgitclonehttps://github.com/scriptiot/evue.gitcdevue
pythonsetup.pyinstall# also `pip install ."Getting startedevue_websitecdexamplespythonevuebroswer.py./evue_website/project.jsonorpythonevuebroswer.py./evue_website/app.pyevue_logincdexamplespythonevuebroswer.py./evue_login/project.jsonorpythonevuebroswer.py./evue_login/app.py
Package: ev-ui
Machine Learning on EISProject Objectives:Current Functionality:Our results are presented in the user interface called echem_pred. This UI has the following functionalities:Data visualization:EIS plottingdqdvBattery cycling plottingMachine Learning:
Our machine learning has two different modes: online training and offline training. Online training includes.... while offline training uses developed....Offline data trainingOnline data trainingDecision TreeModules Overview:echem_pred.py: Main file for the user interface. Including three main parts: main window, data visualization (window 2), and machine learning (window 3).Software Tutorial:After cloning this repo annd installing the requirements, the Echem Visualizer App can be used to interact the xx functions to visualize cycling data.To start the app please run....:After running, the main page should look like this:Installation:Environment:(What's the required environment)Instruction:(How to install)Acknowledgement:
Package: evv4esm
Extended Verification and Validation for Earth System ModelsEVV is a python-based toolkit for extended verification and validation of Earth
system models (ESMs). Currently, it provides a number tests to determine if
modifications to an ESM isclimate changing.ContactIf you would like to suggest features, request tests, discuss contributions,
report bugs, ask questions, or contact us for any reason, use theIssue Tracker.Want to send us a private message?Michael Kellehergithub: @mkstratosemail:kelleherme [at] ornl.govJoseph H. Kennedygithub: @jhkennedyemail:kennedyjh [at] ornl.gov
Package: evxpredictor
Evx predictor mlbotThis is a simple package used to generate buy and sell signals for crypto and conventional stock markets based on the excess volume indicator(EVX)You can read more about Evx in the whitepaperhereUsageIn your python script simply import the module and use as followsfrom evxpredictor import mlbotprint(mlbot.signal(20,65,120, 0.98,'buy'))The above methods take an assets opening, closing, and volume of the asset based on the time interval you have chosen, while the last variable is alpha, a probabilistic value. A zero classification output would instruct the user to sell, while one output means don't sell or buy if the asset is not already present in the orders.You can use empty space instead of alpha to make use of the default value.
Package: evydcloud
Tools for Evydence CloudGetting StartedThese instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.PrerequisitesWhat things you need to install the software and how to install themGive examplesInstallingA step by step series of examples that tell you have to get a development env runningSay what the step will beGive the exampleAnd repeatuntil finishedEnd with an example of getting some data out of the system or using it for a little demoRunning the testsExplain how to run the automated tests for this systemBreak down into end to end testsExplain what these tests test and whyGive an exampleAnd coding style testsExplain what these tests test and whyGive an exampleDeploymentAdd additional notes about how to deploy this on a live systemBuilt WithDropwizard- The web framework usedMaven- Dependency ManagementROME- Used to generate RSS FeedsContributingPlease readCONTRIBUTING.mdfor details on our code of conduct, and the process for submitting pull requests to us.VersioningWe useSemVerfor versioning. For the versions available, see thetags on this repository.AuthorsBillie Thompson-Initial work-PurpleBoothSee also the list ofcontributorswho participated in this project.LicenseThis project is licensed under the MIT License - see theLICENSE.mdfile for detailsAcknowledgmentsHat tip to anyone who's code was usedInspirationetc
Package: ewatercycle
ewatercycleA Python package for running hydrological models.The eWaterCycle package makes it easier to use hydrological models
without having intimate knowledge about how to install and run the
models.Uses container for running models in an isolated and portable way
withgrpc4bmiGenerates rain and sunshine required for the model usingESMValToolSupports observation data fromGRDC or
USGSExposessimple
interfaceto quickly get up and runningInstallThe ewatercycle package needs some geospatial non-python packages to
generate forcing data. It is preferred to create a Conda environment to
install those dependencies:wgethttps://raw.githubusercontent.com/eWaterCycle/ewatercycle/main/environment.yml
condainstallmamba-nbase-cconda-forge-y
mambaenvcreate--fileenvironment.yml
condaactivateewatercycleThe ewatercycle package is installed withpipinstallewatercycleThe ewatercycle package ships without any models. Models are packaged inplugins. To install all endorsed plugins usepipinstallewatercycle-hypeewatercycle-lisfloodewatercycle-marrmotewatercycle-pcrglobwbewatercycle-wflowewatercycle-leakybucketBesides installing software you will need to create a configuration
file, download several data sets and get container images. See thesystem setup
chapterfor instructions.UsageExample using theMarrmot M14
(TOPMODEL)hydrological model on Merrimack catchment to generate forcing, run it
and produce a hydrograph.importpandasaspdimportewatercycle.analysisimportewatercycle.forcingimportewatercycle.modelsimportewatercycle.observation.grdcforcing=ewatercycle.forcing.generate(target_model='marrmot',dataset='ERA5',start_time='2010-01-01T00:00:00Z',end_time='2010-12-31T00:00:00Z',shape='Merrimack/Merrimack.shp')model=ewatercycle.models.MarrmotM14(version="2020.11",forcing=forcing)cfg_file,cfg_dir=model.setup(threshold_flow_generation_evap_change=0.1,leakage_saturated_zone_flow_coefficient=0.99,zero_deficit_base_flow_speed=150.0,baseflow_coefficient=0.3,gamma_distribution_phi_parameter=1.8)model.initialize(cfg_file)observations_df,station_info=ewatercycle.observation.grdc.get_grdc_data(station_id=4147380,start_time=model.start_time_as_isostr,end_time=model.end_time_as_isostr,column='observation',)simulated_discharge=[]timestamps=[]while(model.time<model.end_time):model.update()value=model.get_value('flux_out_Q')[0]# flux_out_Q unit conversion factor from mm/day to m3/sarea=13016500000.0# from shapefile in m2conversion_mmday2m3s=1/(1000*24*60*60)simulated_discharge.append(value*area*conversion_mmday2m3s)timestamps.append(model.time_as_datetime.date())simulated_discharge_df=pd.DataFrame({'simulated':simulated_discharge},index=pd.to_datetime(timestamps))ewatercycle.analysis.hydrograph(simulated_discharge_df.join(observations_df),reference='observation')model.finalize()More examples can be found in the plugins listed in thedocumentation.ContributingIf you want to contribute to the development of ewatercycle package,
have a look at thecontribution guidelines.LicenseCopyright (c) 2018, Netherlands eScience Center & Delft University of
TechnologyApache Software License 2.0
Package: ewatercycle-experiment-launcher
# experiment-launcher[![Build Status](https://travis-ci.org/eWaterCycle/experiment-launcher.svg?branch=master)](https://travis-ci.org/eWaterCycle/experiment-launcher)
[![SonarCloud quality gate](https://sonarcloud.io/api/project_badges/measure?project=experiment-launcher&metric=alert_status)](https://sonarcloud.io/dashboard?id=experiment-launcher)
[![SonarCloud coverage](https://sonarcloud.io/api/project_badges/measure?project=experiment-launcher&metric=coverage)](https://sonarcloud.io/component_measures?id=experiment-launcher&metric=coverage)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1453264.svg)](https://doi.org/10.5281/zenodo.1453264)eWaterCycle Experiment Launcher a webservice to generate and launch a Jupyter notebook.The API of the webservice is described in OpenAPI specification at [openapi.yaml](https://github.com/eWaterCycle/experiment-launcher/blob/master/ewatercycle_experiment_launcher/swagger.yaml) and can be seen in [Swagger UI](http://petstore.swagger.io/?url=https://raw.githubusercontent.com/eWaterCycle/experiment-launcher/master/ewatercycle_experiment_launcher/openapi.yaml)# Install## JupyterHub serverThe experiment launcher needs to communicate with a Jupyter Hub server.
The JupyterHub server must running with a service which has a known token and has admin rights.`bash pip install jupyterhub dockerspawner sudo npm install-gconfigurable-http-proxycp jupyterhub_config.py.example jupyterhub_config.py # Generate token exportJUPYTERHUB_TOKEN=$(opensslrand-hex32) echo $JUPYTERHUB_TOKEN # Set token nano jupyterhub_config.py docker pullewatercycle/jupyterlab-experiment-builderjupyterhub `Test JupyterHub by going tohttp://172.17.0.1:8000and login with OS credentials.## Installation for production`bash pip install ewatercycle_experiment_launcher `## Installation for developmentTo install the launcher in development mode clone the repo and run`bash python setup.py develop `# Run`bash # JUPYTERHUB_TOKEN env var should be set to same value as token in jupyterhub_config.py exportJUPYTERHUB_URL=http://172.17.0.1:8000gunicorn-w4-b0.0.0.0:8888 ewatercycle_experiment_launcher.serve:app `Gotohttp://localhost:8888/ui/for Swagger UI.The JupyterHub and Experiment Launcher use local OS accounts for authentication and authorization.In the Swagger UI you must authorize before trying an operation.When running on Internet make sure https is enforced so the authentication is secure.# Changelog
All notable changes to this project will be documented in this file.The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/)
and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.html).## [Unreleased]## [0.2.0] - 2018-12-06### Fixedworkspace is already in use in another JupyterLab window (#11)### ChangedUpgraded to Connexion v2Upgraded to OpenAPI v3## [0.1.0] - 2018-10-09Initial release
Package: ewatercycle-HBV
eWaterCycle plugin - HBVThis package is based on theLeaky bucket& is a wrapper for theHBV-bmimodel.HBV (Hydrologiska Byråns Vattenbalansavdelning) is a conceptual hydrological model. For more information on it's history, see thispaper.This current implementation iswithouta snow reservoir.InstallationInstall this package alongside your eWaterCycle installationpip install ewatercycle-hbvThen HBV becomes available as one of the eWaterCycle modelsfromewatercycle.modelsimportHBVImplementing your own modelFor more information on how this plugin works, and on how to implement your own model see theplugin guideLicenseThis is aewatercycle-plugin& thus this is distributed under the same terms as the template: theApache-2.0license.Changelogv1.0.0working basic version after various testingversionsv1.1.0upgrade to new version: added support for updating memory vector on the fly for Data assimilationv1.1.1Fixed bug with Tlag and setting memory vector correctlyv1.1.2Adding.finalize()method - clears up the directory. Especially useful for DA.V1.2.0pretty big issue with setting values fixed - won't affect most use but will cause issues for Data Assimilationuse opportunity to name all HBV packages/naming/images to 1.2.0V1.3.1now supports camels.txt files natively. Just download the ones you want from there and add it.make sure you also include the alpha value which is a model output from the run, defaults to 1.26 but varies per catchment. Eq1 of camels paper.v1.3.2. - 1.3.3now correctly slices the ds to given start and end time whoopsv1.3.4 - 1.3.9formalises forcing: either.txtor (two).ncforcing supplied & run corresponding code
Package: ewatercycle-hype
eWaterCycle plugin for HYPE hydrological modelHYPE plugin foreWatercycle.HYPE documentation athttp://www.smhi.net/hype/wiki/doku.php.InstallationeWaterCycle must be installed in amambaenvironment. The environment can be created withwget https://raw.githubusercontent.com/eWaterCycle/ewatercycle/main/environment.ymlmamba env create --name ewatercycle-hype --file environment.ymlconda activate ewatercycle-hypeInstall this package alongside your eWaterCycle installationpip install ewatercycle-hypeThen Hype becomes available as one of the eWaterCycle modelsfromewatercycle.modelsimportHypeUsageUsage of HYPE forcing generation and model execution is shown indocs/generate_forcing.ipynbanddocs/model.ipynbrespectively.Licenseewatercycle-hypeis distributed under the terms of theApache-2.0license.
Package: ewatercycle-lisflood
eWaterCycle plugin for LISFLOOD hydrological modelLISFLOOD plugin foreWatercycle.LISFLOOD documentation athttp://www.smhi.net/lisflood/wiki/doku.php.InstallationeWaterCycle must be installed in amambaenvironment. The environment can be created withwget https://raw.githubusercontent.com/eWaterCycle/ewatercycle/main/environment.ymlmamba env create --name ewatercycle-lisflood --file environment.ymlconda activate ewatercycle-lisfloodInstall this package alongside your eWaterCycle installationpip install ewatercycle-lisfloodThen Lisflood becomes available as one of the eWaterCycle modelsfromewatercycle.modelsimportLisfloodUsageUsage of LISFLOOD forcing generation and model execution is shown indocs/generate_forcing.ipynbanddocs/model.ipynbrespectively.Licenseewatercycle-lisfloodis distributed under the terms of theApache-2.0license.
Package: ewatercycle-marrmot
eWaterCycle plugin for MARRMoT hydrological modelMARRMoT plugin foreWatercycle.MARRMoT documentation athttps://github.com/wknoben/MARRMoT.InstallationeWaterCycle must be installed in amambaenvironment. The environment can be created withwget https://raw.githubusercontent.com/eWaterCycle/ewatercycle/main/environment.ymlmamba env create --name ewatercycle-marrmot --file environment.ymlconda activate ewatercycle-marrmotInstall this package alongside your eWaterCycle installationpip install ewatercycle-marrmotThen MARRMoT models become available as eWaterCycle modelsfromewatercycle.modelsimportMarrmotM01,MarrmotM14UsageExample notebooks:Forcing generation atdocs/generate_forcing.ipynbMarrmot Collie River 1 (traditional bucket) modeldocs/MarrmotM01.ipynbMarrmot Top Model hydrological modeldocs/MarrmotM14.ipynbLicenseewatercycle-marrmotis distributed under the terms of theApache-2.0license.