Saravanan666/pypi-org huggingface dataset:
Package: planetary-coverage
Planetary coverage packageTheplanetary-coveragepackage is a toolbox to perform surface coverage analysis based on orbital trajectory calculations.
Its main intent is to provide an easy way to compute observation
opportunities of specific region of interest above the Galilean
satellites for the ESA-Juice mission but could be extended in the
future to other space mission.It is actively developed by theObservatoire des Sciences de l'Univers Nantes Atlantique(OSUNA, CNRS-UAR 3281) and theLaboratory of Planetology and Geosciences(LPG, CNRS-UMR 6112) at Nantes University (France), underESA-JuiceandCNESfounding support.📦 InstallationThe package is available onPyPIand can be installed very easily:If you are in aJupyter environnement, you can use the magic command%pipin a notebook cell and ▶️Runit:%pipinstallplanetary-coverageor, if you are using aterminal environment, you can do:pipinstallplanetary-coverageNote:If you plan to use this package with Juice and you want to enablePTR simulation with AGM.
You can add ajuiceextra parameter in thepipinstall command:pip install planetary-coverage[juice]The package is also available onconda-forgeand you can install it withconda:condaconfig--addchannelsconda-forge
condaconfig--setchannel_prioritystrict

condainstallplanetary-coverage✏️ How to cite this packageIf you use this package for your analyses, please consider using the following citation:Seignovert et al. 2023,
Planetary coverage package (1.1.0),planetary-coverage.org,swh:1:rel:8416d4a23e2d695ce68c35f22aace9281c25dbaaor can use this 📙BibTeX file.⚡️ Issues and 💬 feedbackIf you have any issue with this package, we highly recommend to take a look at:📚 ourextended documentation online.📓 the collection ofnotebook examples.If you did not find a solution there, feel free to:📝open an issue(if you have an account on theJuice Gitlab).✉️ send us an email atcontact@planetary-coverage.org🎨 Contribution and 🐛 fix bugsContributions are always welcome and appreciated.
An account on theJuice Giltabis required.
You also need to install the recent version ofPoetry(≥1.2), for example onLinux/macOS/Windows (WSL), you can run this command:curl-sSLhttps://install.python-poetry.org|python3-Then you are good to go!🍴Fork this project🐑 Clone and 📦 install the repository locally:gitclonehttps://juigitlab.esac.esa.int/<YOUR_USERNAME>/planetary-coveragecdplanetary-coverage

poetryinstall--extrasjuice✍️ Make your edits and 🚧 write the tests.🚦 Double-check that the linters are happy 😱 🤔 😃 :poetryrunflake8src/tests/docs/conf.py
poetryrunpylintsrc/tests/🛠 Check that your tests succeed 👍 and you have a coverage of 100% ✨ :poetryrunpytest📖 Complete and ⚙️ build the documentation (if needed):cddocs/
poetryrunmakedocs📤 Push your changes to your forked branch and 🚀 open anew merge requestexplaining what you changed 🙌 👏 💪.
Package: planetaryimage
NOTEThis is Alpha quality software that is being actively developed, use
at your own risk.Planetary image parserFree software: BSD licenseDocumentation:https://planetaryimage.readthedocs.org.FeaturesReads in PDS Images as NumPy arrays.Supports GZIP and BZ2 compressed PDS Images.Supports writing out PDS3 images.Reads in Isis Cube Files as NumPy arrays.Check out a few simple examples ofopening and viewing PDS and Isis CubeFiles in an IPython notebook.QuickstartThe example below will walk you through setting up a Python virtual
environment and installing the necessary software as well as a few handy
extras.  It then downloads a sample Pancam PDS image, opens and displays that
image in your web browser in anIPython Notebook.  The example assumes
you havePython,virtualenv, andpipinstalled on your system.  If you
don’t, don’t know what this means or aren’t thrilled by the opportunity to
learn what this means, this software may be a little too immature for you to
use at this point.Create and activate a virtual environment:virtualenv venv
source venv/bin/activateUpgrade pip, then pip install the package and IPython notebook and matplotlib
to help display the image:pip install -U pip
pip install planetaryimage matplotlib ipython[notebook]This quick example will show how to open and display a Pancam PDS image using
this module.  First, grab a sample image:wget http://pds-imaging.jpl.nasa.gov/data/mer/opportunity/mer1po_0xxx/data/sol2840/edr/1p380322615effbr43p2443l1m1.imgNow run python in an IPython Notebook (a browser window should pop up after
entering the following command):$ ipython notebookCreate a new notebook in your web browser and then paste the following code
into a cell and execute it by pressing Shift+ENTER.  This will load and display
the image:%matplotlib inline
import matplotlib.pyplot as plt
from planetaryimage import PDS3Image
image = PDS3Image.open('1p380322615effbr43p2443l1m1.img')
plt.imshow(image.image, cmap='gray')SeeUsagefor
full documentation on how to use planetaryiamge.History0.5.0 (2016-04-13)Added ability to generate PDS3Image objects from NumPy arrays.0.4.1 (2016-03-26)Fixes to saving PDS3 images files after modification of the data.0.4.0 (2016-03-05)Added basic support for saving PDS3 images.0.3.0 (2015-09-29)Added support for opening PDS images that are gzip or bz2 compressed.0.2.0 (2015-06-17)Improved support for float type PDS3 image types.  Many types still not
supported.0.1.0 (2015-06-03)First release on PyPI.  Basic PDS and Isis Cube File parsing works.
Package: planetary-spip
SPiP : Spacecraft Pixel footprint ProjectionProjection of the pixel footprint from an instrument onboard an orbital spacecraft on a planetary surface.Installation & UpdateMethod 1: from PyPI (recommended)Installation:pip3 install planetary-spipUpdate:pip3 install planetary-spip --upgradeMethod 2: from the GitHub repository (development version)Installation:Clone the repository and install with pip:gitclonehttps://github.com/NAU-PIXEL/spip.gitcdspip
pip3install.Update:Go to the previously cloned repository, pull the last updates, and install them with pip:cdspip
gitpull
pip3install.Usage# Package importationimportspipimportnumpyasnp# Genaration of a longitude/latitude grid to project the footprintlon_array=np.arange(0.25,360,0.5)# 0° -> 360°, 2 points per degreelat_array=np.arange(-89.75,90,0.5)# -90° -> 90°, 2 points per degreelon_grid,lat_grid=np.meshgrid(lon_array,lat_array)# Pixel parameterslon_px,lat_px=58.2,79.3# Longitude/Latitude of the pixel center [deg]emer=61.7# Emergence angle of the pixel on the surface [deg]lon_subsc,lat_subsc=28.0,24.9# Longitude/Latitude sub-spacecraft [deg]d_Mars_sc=27212# Distance aeroid-spacraft [km]Rmars=spip.emm_emirs.Rmars# 3390 [km]ifov=spip.emm_emirs.ifov_emirs# 2.7e-3 [rad]# Generation of the mask map of the pixel footprint#-- EMM/EMIRS spacecraftmask_footprint=spip.emm_emirs.emirs_ifov_px_projection(lon_grid,lat_grid,lon_px,lat_px,emer,lon_subsc,lat_subsc,d_Mars_sc,Rmars,ifov)# To easily handle multiple pixels, there is the spip.emm_emirs.emirs_ifov_multi_px_projection() function.#-- General case, cirular pixela,b,θ=spip.circular_pixels.params_ellipse_fov(lon_px,lat_px,emer,lon_subsc,lat_subsc,d_Mars_sc,ifov)mask_footprint=spip.circular_pixels.in_ellipse_spherical(lon_grid,lat_grid,Rmars,a,b,lon_px,lat_px,θ)*1.# > mask_footprint# For each point of the longitude/latitude grid:#   | 1 -> Within the pixel footprint ellipse.#   | 0 -> Outside.DocumentationPlanetary Data Workshop 2023:abstract&posterCredits© Aurélien Stcherbinine (2023) NAU-PIXELDepartment of Astronomy and Planetary Science, Northern Arizona University, Flagstaff, AZ, USALicenseThis package is released under a MIT open source license. SeeLICENSEfor more details.
Package: planetcantile
PlanetcantileAdds TileMatrixSets for other planets.
Aims to be home to a wide range of tilesets for the Moon, Mars, and more.Integrates withmorecantile, ideally should allow downstream projects to benefit from additional TMSs defined here.Definitions go into the generate.py script to have fine grain control, alternatively json files can just be added directly to the data directory.
Package: planet-generator-sdk
Planet Generator - Python SDKPlanet API is a2D planet sprite generator. Our internal process procedurally generate surfaces, map them to a true sphere, to finally render a planet at 1080x1080 with transparent background.
This SDK facilitate the interaction with the API and implement masks features to add lighting and solar effect to the planets.This API currently under development. During this phase, it can be accessed for free.See here how to get your key.Installationpipinstallplanet-generator-sdkQuickstartGenerate a 2D planet sprite with masks:fromplanet_generatorimportClient# Create a Planet API clientplanet_api=Client.from_api_key(api_key="YOUR API KEY HERE")# Generate a new planetplanet=planet_api.get_planet()sprite=planet.sprite.get_image(apply_masks=True)sprite# Contains the 2D planet sprite
Package: planetmapper
PlanetMapper is an open source Python package for visualising, navigating and mapping Solar System observations.DocumentationFor full documentation andAPI reference, visitplanetmapper.readthedocs.io.Installationpipinstallplanetmapper--upgradecondainstall-cconda-forgeplanetmapperRequires Python 3.10+Citing PlanetMapperIf you use PlanetMapper in your research, please cite the following paper:King et al., (2023). PlanetMapper: A Python package for visualising, navigating and mapping Solar System observations. Journal of Open Source Software, 8(90), 5728,https://doi.org/10.21105/joss.05728Citation BibTeX entry@article{king_2023_planetmapper,author={King, Oliver R. T. and Fletcher, Leigh N.},doi={10.21105/joss.05728},journal={Journal of Open Source Software},month=oct,number={90},pages={5728},title={{PlanetMapper: A Python package for visualising, navigating and mapping Solar System observations}},url={https://joss.theoj.org/papers/10.21105/joss.05728},volume={8},year={2023}}Each PlanetMapper version is also archived on Zenodo atdoi.org/10.5281/zenodo.7963121.Key featuresFit and map astronomical observations using a full featured user interfaceEasily visualise solar system observations with just a few lines of codebody=planetmapper.Body('saturn','2020-01-01')body.plot_wireframe_radec()plt.show()Convert coordinates, generate backplanes and project maps of telescope observationsContributingIf you spot a bug, or want contribute code to PlanetMapper, check out thecontributing guidelines.Help and supportIf you have any questions, suggestions or feedback, pleasevisit our support page and get in touch!
Package: planetmint
Planetmint ServerPlanetmint is the blockchain database. This repository is forPlanetmint Server.The BasicsTry the QuickstartRun and Test Planetmint Server from themasterBranchRunning and testing the latest version of Planetmint Server is easy. Make sure you have a recent version ofDocker Composeinstalled. When you are ready, fire up a terminal and run:git clone https://github.com/planetmint/planetmint.git
cd planetmint
make runPlanetmint should be reachable now onhttp://localhost:9984/.There are also other commands you can execute:make start: Run Planetmint from source and daemonize it (stop it withmake stop).make stop: Stop Planetmint.make logs: Attach to the logs.make lint: Lint the projectmake test: Run all unit and acceptance tests.make test-unit-watch: Run all tests and wait. Every time you change code, tests will be run again.make cov: Check code coverage and open the result in the browser.make docs: Generate HTML documentation and open it in the browser.make clean: Remove all build, test, coverage and Python artifacts.make reset: Stop and REMOVE all containers. WARNING: you will LOSE all data stored in Planetmint.To view all commands available, runmake.Links for EveryonePlanetmint.io- the main Planetmint website, including newsletter signupLinks for DevelopersAll Planetmint DocumentationCONTRIBUTING.md- how to contributeCommunity guidelinesOpen issuesOpen pull requestsGitter chatroomLegalLicenses- open source & open content
Package: planetmint-cryptoconditions
The cryptoconditions PackageA Python implementation of the Crypto-Conditions spec: a multi-algorithm, multi-level, multi-signature format for expressing conditions and fulfillments.This implementation doesn’t implement the entire Crypto-Conditions spec. It implements the conditions needed by Planetmint, and some others. It’s compliant withversion 02andversion 04of the spec.See also:therfcs/crypto-conditions repositoryPre-conditionsCryptoconditions require a Python version above 3.8.InstallationTo install latest release from PyPI:$pipinstallplanetmint-cryptoconditionsDocumentationPublic documentation is available athttps://docs.planetmint.io/projects/cryptoconditions/.DevelopmentThis project usespoetry <https://python-poetry.org/>for dependency management.
Runpoetry installto start local development.
Package: planetmint-ipld
py-ipldPython implementation of theIPLD specification.StatusFor TODOs, see:#1 <https://github.com/bigchaindb/py-ipld/issues/1>Installation$pipinstallipldUsageIn the Python REPL:>>>fromipldimportmarshal,multihash,unmarshal>>>>>>file={...'name':'hello.txt',...'size':11...}>>>>>>marshalled=marshal(file)>>>>>>multihash(marshalled)'QmQtX5JVbRa25LmQ1LHFChkXWW5GaWrp7JpymN4oPuBSmL'>>>>>>unmarshal(marshal(file))==fileTrueThat’s it. No readthedocs, no private methods :boom:.TestsOnly relevant, if you want to help developing.$pipinstall-e.[dev]$py.test-vAcknowledgementsThanks to thecontributorsover at BigchainDB for letting me take their setup structure.
Package: planetmint-multiaddr
py-multiaddrmultiaddrimplementation in PythonUsageSimplefrommultiaddrimportMultiaddr# construct from a stringm1=Multiaddr("/ip4/127.0.0.1/udp/1234")# construct from bytesm2=Multiaddr(bytes_addr=m1.to_bytes())assertstr(m1)=="/ip4/127.0.0.1/udp/1234"assertstr(m1)==str(m2)assertm1.to_bytes()==m2.to_bytes()assertm1==m2assertm2==m1assertnot(m1!=m2)assertnot(m2!=m1)ProtocolsfrommultiaddrimportMultiaddrm1=Multiaddr("/ip4/127.0.0.1/udp/1234")# get the multiaddr protocol description objectsm1.protocols()# [Protocol(code=4, name='ip4', size=32), Protocol(code=17, name='udp', size=16)]En/decapsulatefrommultiaddrimportMultiaddrm1=Multiaddr("/ip4/127.0.0.1/udp/1234")m1.encapsulate(Multiaddr("/sctp/5678"))# <Multiaddr /ip4/127.0.0.1/udp/1234/sctp/5678>m1.decapsulate(Multiaddr("/udp"))# <Multiaddr /ip4/127.0.0.1>TunnelingMultiaddr allows expressing tunnels very nicely.printer=Multiaddr("/ip4/192.168.0.13/tcp/80")proxy=Multiaddr("/ip4/10.20.30.40/tcp/443")printerOverProxy=proxy.encapsulate(printer)print(printerOverProxy)# /ip4/10.20.30.40/tcp/443/ip4/192.168.0.13/tcp/80proxyAgain=printerOverProxy.decapsulate(printer)print(proxyAgain)# /ip4/10.20.30.40/tcp/443MaintainersOriginal author:@sbuss.ContributeContributions welcome. Please check outthe issues.Check out ourcontributing documentfor more information on how we work, and about contributing in general.
Please be aware that all interactions related to multiformats are subject to the IPFSCode of Conduct.LicenseDual-licensed:MIT© 2014 Steven BussApache 2© 2014 Steven BussHistory0.0.10 (2022-9-9)forked and applied dependency cleanup to support more recent projects0.0.7 (2019-5-8)include subpackagerefactor util and codec0.0.5 (2019-5-7)unhexilified bytesnew exceptionsmiscellaneous improvements [viaalexander255#42]0.0.2 (2016-5-4)Fix a bug in decapsulate that threw an IndexError instead of a copy of the
Multiaddr when the original multiaddr does not contain the multiaddr to
decapsulate. [viafredthomsen#9]Increase test coverage [viafredthomsen#9]0.0.1 (2016-1-22)First release on PyPI.
Package: planetmint-multiformat-multihash
Multihash implementation in PythonFree software: MIT licenseDocumentation:https://multihash.readthedocs.io.Python versions: Python 3.6, 3.7, 3.8, 3.9History2.1.0 (forked master)remove crazy version range limits for dependencies which cause major headaches
for downstream projects with multiple confluent indirect dependencies on this library0.2.3 (2018-10-20)Fix issue with decoding breaking with app codesFix issue with invalid varint decoding0.1.0 (2018-10-19)First release on PyPI.
Package: planetmint-py-cid
CID (Content IDentifier)What is CID ?CIDis a format for referencing content in distributed information systems,
likeIPFS.
It leveragescontent addressing,cryptographic hashing, andself-describing formats.It is the core identifier used byIPFSandIPLD.CID is a self-describing content-addressed identifier.It uses cryptographic hashes to achieve content addressing.It uses severalmultiformatsto achieve flexible self-description,
namelymultihashfor hashes,multicodecfor data content
types, andmultibaseto encode the CID itself into strings.Sample Usage>>>fromcidimportmake_cid>>>make_cid('QmaozNR7DZHQK1ZcU9p7QdrshMvXqWK6gpu5rmrkPdT3L4')CIDv0(version=0,codec=dag-pb,multihash=b"\x12\xb9M'\xb9\x93M>\x08\xa5.R\xd7\xda}\xab\xfa\xc4\x84..")>>>cid=make_cid('QmaozNR7DZHQK1ZcU9p7QdrshMvXqWK6gpu5rmrkPdT3L4')>>>print(cid.version,cid.codec,cid.multihash)>>>print(cid.encode())QmaozNR7DZHQK1ZcU9p7QdrshMvXqWK6gpu5rmrkPdT3L4>>>str(cid)'QmaozNR7DZHQK1ZcU9p7QdrshMvXqWK6gpu5rmrkPdT3L4'InstallationStable releaseTo install CID, run this command in your terminal:$pipinstallpy-cidThis is the preferred method to install CID, as it will always install the most recent stable release.If you don’t havepipinstalled, thisPython installation guidecan guide
you through the process.From sourcesThe sources for CID can be downloaded from theGithub repo.You can either clone the public repository:$gitclonegit://github.com/ipld/py-cidOr download thetarball:$curl-OLhttps://github.com/ipld/py-cid/tarball/masterOnce you have a copy of the source, you can install it with:$pythonsetup.pyinstallOther infoFree software: MIT licenseDocumentation:https://py-cid.readthedocs.io.Python versions: 3.5, 3.6History0.4.1 (2022-09-08, forked master)made the package deployable increased version number and blackified the files0.4.0 (forked master)remove crazy version range limits for dependencies which cause major headaches
for downstream projects with multiple confluent indirect dependencies on this library0.2.1 (2018-10-20)Fix edge cases with multibase and multihash decodingAdded hypothesis tests while verifying CIDs0.1.5 (2018-10-12)Handle the case where an incorrect base58 encoded value is provided tomake_cid0.1.0 (2017-09-05)First release on PyPI.
Package: planetmint-pymultihash
This is an implementation of themultihashspecification in Python.
The main component in the module is theMultihashclass, a named tuple that
represents a hash function and a digest created with it, with extended
abilities to work with hashlib-compatible hash functions, verify the integrity
of data, and encode itself to a byte string in the binary format described in
the specification (possibly ASCII-encoded).  Thedecode()function can be
used for the inverse operation, i.e. converting a (possibly ASCII-encoded)
byte string into aMultihashobject.For more information, please see the documentation under thedocsdirectory and the docstrings in themultihashpackage.  Ready-to-read
documentation is also available inhttps://pymultihash.readthedocs.io/.This package requires at least Python 3.4.
Package: planetoidAI
Planetoid APIPlanetoid's API official library to access free APIsAbout The APIPlanetoid's official library to access free APIs!Explore more »Built WithCore pythonGetting StartedPrerequisitesPython 3InstallationInstall pip packagepipinstallplanetoidAIUsageUseful examples of how a project can be used.Create a new python file anywhere, such as demo.py.
Add code in the demo.py file, the sample code is as follows:1. Object detectionfromplanetoidAIimportPlanetoidplanetoid1=Planetoid()# Get_objects_from_imageobject_list=planetoid1.get_objects_from_image("FILENAME.jpg")print(object_list)OUTPUT[{'name':'Object','class_name':'person','score':0.5407423377037048,'y':0.215625,'x':0.090625,'height':0.984375,'width':0.896875}]2. Get face location from imagefromplanetoidAIimportPlanetoidplanetoid1=Planetoid()# Get_face_location_from_imageface_276=planetoid1.get_face_location_from_image(filename="FILENAME.jpeg")print(face_276)OUTPUT[{'name':'Object','class_name':'face','score':0.9999943971633911,'y':0.30875,'x':0.32625,'height':0.65375,'width':0.67125}]3. Age and gender recognitionfromplanetoidAIimportPlanetoidplanetoid1=Planetoid()# Get_age_gender_from_imageage_gender=planetoid1.get_age_gender_from_image("FILENAME.jpeg")print(age_gender)OUTPUT[{'name':'Object','class_name':'male,Age: (15-17)','score':0.4520128,'y':0.30875,'x':0.32625,'height':0.65375,'width':0.67125}]4. Nationality recognition (Face race)fromplanetoidAIimportPlanetoidplanetoid1=Planetoid()# Get_face_race_from_imagenationality=planetoid1.get_face_race_from_image("FILEMNAME.jpeg")print(nationality)OUTPUT[{'name':'Object','class_name':'Indian','score':0.97603726,'y':0.30875,'x':0.32625,'height':0.65375,'width':0.67125}]5. Language translationfromplanetoidAIimportPlanetoidplanetoid1=Planetoid()# Get_translationtranslation=planetoid1.get_translation("hello",translate_to='gu')print(translation)OUTPUT{'translation':'નમસ્તે'}ContributingIf you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".
Don't forget to give the project a star! Thanks again!Fork the ProjectCreate your Feature Branch (git checkout -b feature/AmazingFeature)Commit your Changes (git commit -m 'Add some AmazingFeature')Push to the Branch (git push origin feature/AmazingFeature)Open a Pull RequestLicenseDistributed under the MIT License. SeeLICENSE.txtfor more information.ContactHimanshu MolyaProject Link:https://github.com/HimanshuMoliya/planetoidAcknowledgmentsGitHub Pages(back to top)
Package: planetpixel
A simple API for retrieving time series color data using the Planet API.(Because API’s don’t have to be complicated!)ExamplePlanetPixelmakes it fun and easy to plot the color of a single position on Earth as a function of time.  For example, you can use it to study when Matthes lake in Yosemite National Park froze in the winter of 2017:We can study this in a quantitative way as follows:PlanetPixelwas created at the first public Planet Labs Hack Day on October 14th, 2019, in San Francisco, to demonstrate that API’s can be simple and fun!InstallationpipinstallplanetpixelYou also need to set your Planet Labs API key as thePL_API_KEYenvironment variable for this package to work.UsagefromplanetpixelimportPlanetPixelPlanetPixel(lon,lat).plot()CaveatRight now, the example above takes 15+ minutes to run. 😬
Package: planetpy
Tools to work with planetary data.FeaturesPlanetary constants tables, web-scraped from NASA websitesPDS index table toolsFree software: ISC licenseFutureI will potentially use this repo to start the generalized
planetpy package under the framework of OpenPlanetary.History0.1.0 (2015-08-01)First release on PyPI.0.2.0 (2016-12-19)Add pdstools