Saravanan666/pypi-org huggingface dataset:
Package: geoscilabs
# GeoSci Labs[![binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/geoscixyz/geosci-labs/main?filepath=notebooks%2Findex.ipynb)
[![pypi](https://img.shields.io/pypi/v/geoscilabs.svg)](https://pypi.python.org/pypi/geoscilabs)
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[![SimPEG](https://img.shields.io/badge/powered%20by-SimPEG-blue.svg)](http://simpeg.xyz)This is a repository of code used to power the notebooks and interactive examples forhttps://em.geosci.xyzandhttps://gpg.geosci.xyz.The examples are based on code available in [SimPEG](http://simpeg.xyz).## WhyInteractive visualizations are a powerful way to interrogate mathematical equations. The goal of this repository is to be the home for code that can be plugged into jupyter notebooks so that we can play with the governing equations of geophysical electromagnetics.## ScopeThe repository contains the python code to run the ipython-widget style apps inhttp://github.com/geoscixyz/geosci-labs. These are mainly plotting code and some simple analytics. More complex numerical simulations depend on [SimPEG](http://simpeg.xyz)## UsageThe notebooks can be run online through [Binder](#Binder), or [downloaded and run locally](#Locally).### Binder[![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/geoscixyz/geosci-labs/main?filepath=notebooks%2Findex.ipynb)Launch the binder by clicking on the badge above or going to:https://mybinder.org/v2/gh/geoscixyz/geosci-labs/main?filepath=notebooks%2Findex.ipynb.
This can sometimes take a couple minutes, so be patient…Select the notebook of interest from the contents[Run the Jupyter notebook](#Running-the-notebooks)![Binder-steps](https://em.geosci.xyz/_images/binder-steps.png)### LocallyTo run them locally, you will need to have python installed, preferably through [anaconda](https://www.anaconda.com/download/).You can then clone this reposiroty. From a command line, run` git clonehttps://github.com/geoscixyz/geosci-labs.git`Thencdintogeosci-labs` cdgeosci-labs`To setup your software environment, we recommend you use the provided conda environment` conda env create-fenvironment.yml conda activategeosci-labs`alternatively, you can install dependencies through pypi` pip install-rrequirements.txt `You can then launch Jupyter` jupyter notebook `Jupyter will then launch in your web-browser.## Running the notebooksEach cell of code can be run withshift + enteror you can run the entire notebook by selectingcell,Run Allin the toolbar.![cell-run-all](https://em.geosci.xyz/_images/run_all_cells.png)For more information on running Jupyter notebooks, see the [Jupyter Documentation](https://jupyter.readthedocs.io/en/latest/)## Using in a course## IssuesIf you run into problems or bugs, please let us know by [creating an issue](https://github.com/geoscixyz/geosci-labs/issues/new) in this repository.## For ContributorsWe are glad you are interested in contributing! Please check out the [contributing guide](CONTRIBUTING.md) for ideas of how to get involved.
Package: geosea
Project DescriptionGeosea is an open tool box for seafloor geodetic data processing of dircet-path ranging. It supplies a variety of functions to process acoustic baselines and analyze ground movement.DependenciessciPy: miscellaneous statistical functionsmatplotlib: for plottingpandas: data structures and data analysis toolnumPy: 1.7.1 or higherobspy: for date and time typesImport of GeoSEA Moduleimport geoseaFunctionsRead raw csw files into an pandas DataFrame:geosea.read(sal=None ,phi=None, starttime=None, endtime=None, pathname=None, writefile=True, writevariable=True, dateformat=None)Calculates the sound velocity from temperature in °C, pressure in kPa and constant salinity in PSU.Complete Baseline processing of horizontal and vertical changes in time:geosea.bsl(ID=None, st_series=None, bsl_series=None, outlier_flag=False, pathname=None, starttime=None, endtime=None, writefile=True, dateformat=None)Parameters:
SAL                     constant salinity value in PSU
phi                     Latitude for Leroy formular in XX.X°pathname                Pathname of raw CSV Data files
outlier_flag            Cuts outlier mesurements automatically (Default = None)
writefile               Save output data to csv data format (Defulat = True)
dateformat              GMT_DATEFORMAT or MATLAB_DATEFORMAT
Package: geoserver-api
GeoServer ConfigConfiguration for geoserver and additional resources needed to host stuff there.Docker in EC2EC2 SetupLaunch an instance usingthis user data. It is recommended the instance to have >=8Gb RAM and >=30Gb ephemeral storage. A good alternative is thet3.largewhich costs ~60 USD/month as of 02/10/2023.Connect to your instance and add docker to user group by running:sudousermod-aGdocker$USERnewgrpdocker# restarts dockerLaunch GeoserverPull the geoserver image:dockerpulldocker.osgeo.org/geoserver:2.23.xNow run the container, installing COG extension and using a local data directory at/MY/DATADIRECTORY. As detailed in the documentation:this setup allows direct management of the file data shared with the container. This setup is also easy to update to use the latest container.dockerrun--mounttype=bind,src=/MY/DATADIRECTORY,target=/opt/geoserver_data-it-p8080:8080--envINSTALL_EXTENSIONS=true--envCOMMUNITY_EXTENSIONS="cog"--envJAVA_TOOL_OPTIONS="-Xmx4096m"docker.osgeo.org/geoserver:2.23.xTheJAVA_TOOL_OPTIONSis important to increase the maximum hava heap size available for the app. The example command provided earlier sets this limit on ~4Gb For coverage stores, a large heap size is necessary since there is a lot of data to bring. You can adjust it according to your use case. Runjava -XX:+PrintFlagsFinal -version | grep MaxHeapSizefor getting the max heat space in the docker container.Optimization of Geoserver ImageMosaicSee geoserver documentationExample NotebooksCoverage Store using Cog Images: setup a WMS/WMTS-T service using COG rasters located in cloud storageTODOFix creating new datastore with existing database index:geoserver repo issue
Package: geoserver-rest
Python wrapper for GeoServer REST APIFull documentationThe documentation for this project is moved here:https://geoserver-rest.readthedocs.io/.OverviewThegeoserver-restpackage is useful for the management of geospatial data inGeoServer. The package is useful for the creating, updating and deleting geoserver workspaces, stores, layers, and style files.Installationcondainstall-cconda-forgegeoserver-restFor thepipinstallation, check theofficial documentation of geoserver-restSome examplesPlease check thehttps://geoserver-rest.readthedocs.io/for full documentation.# Import the libraryfromgeo.GeoserverimportGeoserver# Initialize the librarygeo=Geoserver('http://127.0.0.1:8080/geoserver',username='admin',password='geoserver')# For creating workspacegeo.create_workspace(workspace='demo')# For uploading raster data to the geoservergeo.create_coveragestore(layer_name='layer1',path=r'path\to\raster\file.tif',workspace='demo')# For creating postGIS connection and publish postGIS tablegeo.create_featurestore(store_name='geo_data',workspace='demo',db='postgres',host='localhost',pg_user='postgres',pg_password='admin')geo.publish_featurestore(workspace='demo',store_name='geo_data',pg_table='geodata_table_name')# For uploading SLD file and connect it with layergeo.upload_style(path=r'path\to\sld\file.sld',workspace='demo')geo.publish_style(layer_name='geoserver_layer_name',style_name='sld_file_name',workspace='demo')# For creating the style file for raster data dynamically and connect it with layergeo.create_coveragestyle(raster_path=r'path\to\raster\file.tiff',style_name='style_1',workspace='demo',color_ramp='RdYiGn')geo.publish_style(layer_name='geoserver_layer_name',style_name='raster_file_name',workspace='demo')# delete workspacegeo.delete_workspace(workspace='demo')# delete layergeo.delete_layer(layer_name='agri_final_proj',workspace='demo')# delete style filegeo.delete_style(style_name='kamal2',workspace='demo')ContributionGeoserver-rest is the open source library written in python and contributors are needed to keep this library moving forward. Any kind of contributions are welcome. Here are the basic rule for the new contributors:Please use the request library for the http request.One feature per pull request (If the PR is huge, you need to create a issue and discuss).Please add the update about your PR on thechange log documentationas well.CitationFull paper is available here:https://doi.org/10.5194/isprs-archives-XLVI-4-W2-2021-91-2021@Article{isprs-archives-XLVI-4-W2-2021-91-2021,
      AUTHOR = {Tek Bahadur Kshetri, Angsana Chaksana and Shraddha Sharma},
      TITLE = {THE ROLE OF OPEN-SOURCE PYTHON PACKAGE GEOSERVER-REST IN WEB-GIS DEVELOPMENT},
      JOURNAL = {The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences},
      VOLUME = {XLVI-4/W2-2021},
      YEAR = {2021},
      PAGES = {91--96},
      URL = {https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLVI-4-W2-2021/91/2021/},
      DOI = {10.5194/isprs-archives-XLVI-4-W2-2021-91-2021}
  }
Package: geoshape
[![Build Status](https://travis-ci.org/ROGUE-JCTD/rogue_geonode.svg?branch=master)](https://travis-ci.org/ROGUE-JCTD/rogue_geonode)GeoSHAPEGeospatial capabilities for Security, Humanitarian Assistance, Partner Engagement – is designed to
enable collaboration on geospatial information between mission partners in connected and disconnected operations.
GeoSHAPE has been built utilizing open source software and open standards to make it available for partners and
to maximize interoperability. GeoSHAPE is the integration of a geospatial portal (GeoNode), a web mapping
client (MapLoom), and a mobile application (Arbiter), that leverages the infrastructure provided by a geospatial
server and database components (The OpenGeo Suite). GeoSHAPE is the outcome of the Rapid Open Geospatial User-Driven
Enterprise (ROGUE) Joint Capability Technology Demonstration (JCTD).  For more information about GeoSHAPE visit the
project page at [http://geoshape.org](https://geoshape.org/).What is this?A django module that extends [GeoNode](https://github.com/GeoNode/geonode) and adds custom functionality that is required by GeoSHAPE.  Follow
the installation instructions below to try it out.InstallationA GeoSHAPE build consists of several components including GeoNode, Geoserver, GeoGig, and Arbiter that all have to be properly
configured in order to work together correctly. We have a [Google Doc](https://docs.google.com/document/d/1KMpk6dXuqvwfEi0pfRpaGY62j6ikoYtpYUPU0sJQAmk/edit)
that describes the installation process in detail. The easiest way to install and configure these components is by using
[Vagrant](https://www.vagrantup.com) with [Virtualbox](https://www.virtualbox.org/), where you can build an entire GeoSHAPE VM
in only a few commands.:git clone https://github.com/ROGUE-JCTD/rogue-chef-repo.git
cd rogue-chef-repo
vagrant upContributingWe are currently accepting pull requests for this repository. Please provide a human-readable description of the changesin the pull request.
Package: geoshapespc
geoshapespcThe Geometric Shapes Point Cloud aims to provide the tools to perform the creation of point clouds around a geometric shape defined by the user’s input. The code in this package is able to create both an evenly spaced point cloud and a pseudorandomly placed point cloud.
This package was created in order to generate rough simulations of LiDAR returns point cloud over a defined and known 3D geometric shape.This package was developed while in my PhD research in the Department of Geography at University College London, supervised by Dr Mat Disney (Earth Observation/Remote Sensing).If you have any problem, question or suggestion, please, don’t hesitate to contact the author.DependenciesnumpymathAuthorMatheus Boni Vicari (@matt_bv)Who do I talk to?Matheus Boni Vicari (matheus.boni.vicari@gmail.comormatheus.vicari.15@ucl.ac.uk)
Package: geoshoplib
Small library which provides api to contact to geoshop.For reading all products:create a base_servicecreate a user_service with user/password and base_service as service parameterread the products => get_products()For reading a specific product definition:create a base_servicecreate a product with a known product_id, user/password and base_service as parameterread the definition => get_definition()Have fun!0.4.0
—Set correct version configuration.0.3.0
—Use geoshop id for error handling now.0.2.0
—Fix bug when fields are not set in geoshop, now it is printed out to the console but the lib keeps running0.1.0
—Initial version.implements first views for connection data sets
Package: geosky
Geo skyA Python package to get all city, stae and country namesUsageFollowing methods can be utilized to get info..from geosky import geo_plug

geo_plug.all_CountryNames()

geo_plug.all_Country_StateNames()

geo_plug.all_State_CityNames(name)# name == 'all' or stae name
geo_plug.all_State_CityNames('Odisha')To uninstall execute following..pip uninstall geosky
Package: geoslurp
Download and manage datasets in a PostGreSQL database with the PostGISThe idea is that this tool contains script to download (i.e.slurp) commonly used datasets and to register them in a postgresql+postgis database. This database can then be queried allowing the retrieval of the relevant data or datafiles.The main documentation lives atwobbly.earth/geoslurpWorkingsThe geoslurp module itself is a pure python module, which acts as a client. For this to work one needs toset up a running PostGreSQL database.
Package: geoso
geosoA Python package for collecting and spatio-temporal analysis of social media contentsGitHub repo:https://github.com/MahdiFarnaghi/geosoPyPI:https://pypi.org/project/geoso/Documentation:https://MahdiFarnaghi.github.io/geosoFree software: MIT licenseIntroductiongeosois a Python library, being developed to facilitate collection, cleansing, and spatial and spatio-temporal analysis of social media data.The vision is that the library provided the possibility to download geo-tagged social media content into a database, e.g., PostgreSQL, preprocess the stored data, retrieve, and analyse the data.FeaturesTwitterDownload tweets from Twitter Streaming API and save them into either a database orJSON Linestext files.Import tweets that were fromJSON Linestext files into the database.Export tweets to CSV file.Clean tweets text in the database.Retrieve tweets from the database aspandas DataFrame.Under development featuresTwitterClean tweets text in the database.Detect tweets that were published by bots.Scientific publicationsIf you are using this library, the following scientific publications could be of your interest.Farnaghi, M., Ghaemi, Z., & Mansourian, A. (2020).Dynamic Spatio-Temporal Tweet Mining for Event Detection: A Case Study of Hurricane Florence. International Journal of Disaster Risk Science, 11, 378-393.Ostermann, F. O. (2021).Linking geosocial sensing with the socio-demographic fabric of smart cities. ISPRS international journal of geo-information, 10(2), 1-22. [52].Zahra, K., Imran, M., Ostermann, F. O. (2020).Automatic identification of eyewitness messages on twitter during disasters. Information processing & management 57 (1), 102107Ghaemi, Z. & Farnaghi, M. 2019.A Varied Density-based Clustering Approach for Event Detection from Heterogeneous Twitter Data.ISPRS International Journal of Geo-Information, 8 (2).CreditsspaCyis used for cleaning texts.Tweepyis used to develop Twitter data retrieval functionalities.This package was created withCookiecutterand thegiswqs/pypackageproject template and instructions fromPython Packagesbook.
Package: geosol
Geometry Problem Solver (geosol) automatically solves a geometry problem
consisting of question text and a diagram.Geosol is consisted of largely 3 processes:
1. Textual understanding
2. Diagram understanding
3. Geometric inferencePlease see below for detailed explanations.
Typical usage often looks like this:import geosol.txt as gtxt       # modules for (1)
import geosol.dgm as gdgm       # modules for (2)
import geosol.inf as ginf       # modules for (3)img = gdgm.open(“diagram.png”)
qt = gtxt.open(“question.txt”)
txt_rep = gtxt.rep(qt) # abstract representation of question text
dgm_rep = gdgm.rep(img, txt_rep) # rep of diagram
inf_mod = ginf.inf(dgm_rep, txt_rep) # inference module
print(inf_mod.get_answer())DependenciesStandard Python packages to be installed (via pip) are:
numpy, scipy, pillow, scikit-learn, tinyocrPlease note that tinyocr is an OCR package built
by the same author. OCR being a distinct function itself,
it has been separately packaged.In addition, OpenCV and Python wrapper needs to be
installed. Please visit the opencv web page.
The author has version 2.4.Textual UnderstandingDiagram UnderstandingGeometric Inference
Package: geosoup
Geosoup v0.1.82Geosoup is a python package for geospatial data manipulation usingGDALandGDAL bindingsin python.This package is a minimalistic software distribution for limited manipulation of common geospatial data types such as rasters, vectors and tables. All the heavy lifting is done byGDAL,numpyand,scipy.Install using:pip install geosoupNote: Must haveGDAL >= 2.1.3up and running before installing this package.
Package: geosoupML
## Geosoup Machine Learning library v0.1.56[![DOI](https://zenodo.org/badge/259178307.svg)](https://zenodo.org/badge/latestdoi/259178307)Geosoup is a python package for geospatial data manipulation usingGDALandGDAL bindingsin python.
This library is for machine learning support for the geosoup library.Currently implemented:Random Forest RegressorMultiple Linear RegressorInstall using:pip install geosoupMLNote: Must haveGDAL >= 2.1.3up and running before installing geosoup and geosoupML.
Package: geospace
A python library for geospatial processing based GDAL and Google Earth Engine=======================Installationpipinstallgeospace-UTo DoTime series extration using Google Earth Engine.Pull requests are encouraged!LicenseThis is free and unencumbered software released into the public domain.Anyone is free to copy, modify, publish, use, compile, sell, or
distribute this software, either in source code form or as a compiled
binary, for any purpose, commercial or non-commercial, and by any means.
Package: geospark
geosparkThis library is Python wrapper on GeoSpark library.GeoSpark is a cluster computing system for processing large-scale spatial data. GeoSpark extends Apache Spark / SparkSQL with a set of out-of-the-box Spatial Resilient Distributed Datasets (SRDDs)/ SpatialSQL that efficiently load, process, and analyze large-scale spatial data across machines.Python version supports:GeoSpark coreGeoSpark SQLPlease follow tutorial on official GeoSpark website:https://datasystemslab.github.io/GeoSpark/
Package: geosphere
This small pure python package provides two functions which do
computations in spherical trigonometry that are needed for
navigating on the surface of the earth.The functiondestination(lat_deg, long_deg, distance_nm, bearing_deg)returns the latitude and longitude of the location
reached by traveling distance_nm nautical miles along the great circle
route starting at the location with latitude lat_deg and longitude
long_deg and having the specified initial bearing.The functiondistance_bearing(lat1_deg, long1_deg, lat2_deg, long2_deg)returns the distance in nautical miles and the bearing in degrees from
the location given by the first latitude-longitude pair to the
location given by the second latitude-longitude pair.  If the points
are too close together the bearing is 0.  If the first point is at a
pole, the bearing is 0 or 180, as appropriate.  If the points are
antipodes, so the bearing is undefined, then the bearing returned
is 0.
Package: geo-spider
geo-spidercrawl all GEO metadata, features:crawl platformscrawl samplescrawl seriesincremental crawlingmissed crawlingTable of Contentsinstallationoutput file formatlogsplatformsdenovo crawlingincremental crawlingmissed crawlingsamplesdenovo crawlingincremental crawlingmissed crawlingseriesdenovo crawlingincremental crawlingmissed crawlinginstallationpip install geo-spideroutput file formatgeo-spider saves files in jsonlines form,
Refer tothis sitefor details.logsgeo-spider default generate logs to geo-spider.log(current directory)
in WARNING level, you can customize by-dand-loptions.-dto enable debug mode-lspecify customized log filegeo-spider -d -l new-geo-spider.log <sub-command>platformsplatforms denovo crawlinggeo-spider platforms -o platforms.jlplatforms incremental crawlingIf you have a crawled platforms jsonlines file:geo-spider platforms -cf platforms.jl -o new-platforms.jlIf you have multiple platforms jsonlines files:geo-spider platforms -cd platforms -o new-platforms.jlplatforms missed crawlingSpecify-cfor-cdlike incremental crawling, add a-moption.geo-spider platforms -cf platforms.jl -m missed -o new-platforms.jlsamplessamples denovo crawlinggeo-spider samples -o samples.jlsamples incremental crawlinggeo-spider samples -pcf platforms.jl -cf samples.jl -o new-samples.jlsamples missed crawlinggeo-spider samples -pcf platforms.jl -cf samples.jl -m missed -o new-samples.jlseriesseries denovo crawlinggeo-spider series -o series.jlseries incremental crawlinggeo-spider series -pcf platforms.jl -scf samples.jl -cf series.jl -o new-series.jlseries missed crawlinggeo-spider series -pcf platforms.jl -scf samples.jl -cf series.jl -m missed -o new-series.jl
Package: geospin-utilities
Utility functions for Geo Spatial Data Science.Package requirementsgeospin-utilities requires Python >= 3.6.numpy>=1.18.1
scikit-learn>=0.22.1
shapely>=1.7.0
pyproj>=2.4.2.post1
pandas>=1.0.1
folium>=0.10.1
matplotlib>=3.1.3
geopandas>=0.7.0
fiona>=1.8.13
h3>=3.6.3
branca>=0.3.1
geojson>=2.5.0
sqlalchemy>=1.3.12
psycopg2-binary>=2.8.4
mlflow>=1.11.0InstallationInstallgeospin-utilitiesvia pip withpip install geospin-utilitiesDocumentationLink to the documentation will follow.