Saravanan666/pypi-org huggingface dataset:
Package: earth-distances
earth_distances packageDescription.
The package earth_distances is used to:Distance:
	- Calculate and returns distances between two points on the surface of
	the Earth, or another sphere, provided its radius, rounded to the third 
	decimal place
Map_Plotting:	
	- Plot the points on a map of our planet, alongside the distance line
	in a desired colorInstallationUse the package managerpipto install earth_distancespipinstallearth_distancesUsagefromearth_distances.distance_calculationimportharvesini# Calculating the distance between Paris and Beijingprint(harvesini.harvesini_distance(48.856613,2.352222,39.904202,116.407394))>>>8216984.310fromearth_distances.map_plottingimportworld_map_plot# Plotting the map related to Paris and Beijingworld_map_plot.plot_world_map(48.856613,2.352222,39.904202,116.407394)AuthorGabriel Vinicius SebastiÃ£oLicenseMIT
Package: earthengine-jupyter
earthengine-jupyterNOTICE: This is an experimental project and is not an officially
supported Google project. You are welcome to use it, but we do not
guarantee stability.Setuptry:importee_jupyterprint('ee_jupyter was already installed.')exceptModuleNotFoundError:print('ee_jupyter was not found. Installing now...')importosresult=os.system('pip -q install earthengine-jupyter')Make sure that the earthengine-jupyter package is installed...How to useThis lib contains aMapclass that can be used to display an interactive map.importeefromee_jupyter.coreimportauthenticate_if_neededfromee_jupyter.ipyleafletimportMapauthenticate_if_needed()✓ Authentication credentials were found.# Intialize the Earth Engine client library.ee.Initialize()map1=Map(center=(37.5924,-122.09),zoom=8)map1Map(center=[37.5924, -122.09], controls=(ZoomControl(options=['position', 'zoom_in_text', 'zoom_in_title', 'zo…Define an Earth Engine image layer, and add it to the interactive map.img1=ee.Image("LANDSAT/LC09/C02/T1_L2/LC09_044034_20220127")visualization={'bands':['SR_B4','SR_B3','SR_B2'],'min':0.2/0.0000275,'max':0.4/0.0000275,}map1.addLayer(eeObject=img1,visParams=visualization,name='Landsat scene')We can also create an inspector object and associate it with the
previously created map.fromee_jupyter.ipyleafletimportInspectorinspector1=Inspector(map_object=map1)inspector1Inspector(layout=Layout(border_bottom='solid', border_left='solid', border_right='solid', border_top='solid', …Typically when you create a inspector object, you will want to display
it near the map.fromipywidgetsimportHBoxdisplay(HBox([map1,inspector1]))HBox(children=(Map(center=[37.5924, -122.09], controls=(ZoomControl(options=['position', 'zoom_in_text', 'zoom…Tip With CaptionNote that when viewed on GitHub Pages you can manipulate Jupyter
widgets independently, but the widgets do not interact with each
other. To experience the cross-widget interactivity, open up this
notebook in a Jupyter environment.Displaying a Map ImageIf you want to display a static (non-interactive) image, you can do that
as well. Theembed=Trueparameter will allow the image to be saved
within the notebook.fromIPython.displayimportImagevisualization['dimensions']=400# maximum dimension for the imageurl=img1.getThumbUrl(visualization)Image(url=url,format='png',embed=True)
Package: earthformer
EarthformerA Python package for Earth forecasting transformerFree software: Apache License, Version 2.0 (Apache-2.0)Documentation:https://opengeos.github.io/earthformerIntroductionThis repository turns theamazon-science/earth-forecasting-transformerrepository into a Python package, making it easier to install and use. To learn more about Earthformer, please refer to the NeurIPS 2022 paper:Earthformer: Exploring Space-Time Transformers for Earth System Forecasting. Credits to the authors and theirrepositoryfor the original implementation.InstallationTheearthformerpackage is available onPyPI. To install it, run:pipinstallearthformerTheearthformerpackage is also available onconda-forge. To install it, run:condacreate-nearthformerpython=3.10
condaactivateearthformer
condainstall-cconda-forgemamba
mambainstall-cconda-forgeearthformer
Package: earthing
EarthingA python library for design of earthing networks in electrical substations.FeaturesEarth grid design as per IEEE 80/ ENA_ER_S34Numerical earth network calculations using using boundary descretisation method.Evaluation of earth resistance of various earth electrode geometries.3D plotting of electrode geometry used for design.3D plotting of current density distribution for the earth network.2D/3D plotting of surface potential distribution.Ploting and evaluation of mesh and step potentials.UsagePackage is available on PyPI for installation (https://pypi.org/project/earthing). Usepip install earthingto install.Program source includes detailed usage instructions for various functions and classes. Alternately project page has ipython notebooks covering typical use cases.Dependencies:Python 3NumpyMatplotlib
Package: earthkit
earthkitDISCLAIMERThis project isBETAand will beExperimentalfor the foreseeable future. Interfaces and functionality are likely to change, and the project itself may be scrapped.DO NOTuse this software in any project/software that is operational.earthkitis a project led by ECMWF, providing powerful tools for speeding up weather and climate science workflows by simplifying data access, processing, analysis, visualisation and much more.DocumentationThe documentation can be found athttps://earthkit.readthedocs.io/.LicenseApache License 2.0In applying this license, ECMWF does not waive the privileges and immunities
granted to it by virtue of its status as an intergovernmental organisation nor does it submit to any jurisdiction.
Package: earthkit-aggregate
earthkit-climateA toolkit for statistical analysis of temporal-geospatial data.DISCLAIMERThis project isBETAand will beExperimentalfor the foreseeable future.
Interfaces and functionality are likely to change, and the project itself may be scrapped.DO NOTuse this software in any project/software that is operational.Quick Start>>>fromearthkit.climateimportaggregateWorkflow for developers/contributorsFor best experience create a new conda environment (e.g. DEVELOP) with Python 3.10:conda create -n DEVELOP -c conda-forge python=3.10
conda activate DEVELOPBefore pushing to GitHub, run the following commands:Update conda environment:make conda-env-updateInstall this package:pip install -e .Sync with the latesttemplate(optional):make template-updateRun quality assurance checks:make qaRun tests:make unit-testsBuild the documentation (seeSphinx tutorial):make docs-buildLicenseCopyright 2022, European Centre for Medium Range Weather Forecasts.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Package: earthkit-climate
earthkit-climateA toolkit for statistical analysis of temporal-geospatial data.DISCLAIMERThis project isBETAand will beExperimentalfor the foreseeable future.
Interfaces and functionality are likely to change, and the project itself may be scrapped.DO NOTuse this software in any project/software that is operational.Quick Start>>>fromearthkit.climateimportaggregateDetailed documentationPlease refer theearthkit-climate readthedocs pagefor more detailed documentation, example notebooks and the API reference guide.Workflow for developers/contributorsFor best experience create a new conda environment (e.g. DEVELOP) with Python 3.10:conda create -n DEVELOP -c conda-forge python=3.10
conda activate DEVELOPBefore pushing to GitHub, run the following commands:Update conda environment:make conda-env-updateInstall this package:pip install -e .Sync with the latesttemplate(optional):make template-updateRun quality assurance checks:make qaRun tests:make unit-testsBuild the documentation (seeSphinx tutorial):make docs-buildLicenseCopyright 2022, European Centre for Medium Range Weather Forecasts.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Package: earthkit-data
earthkit-dataDISCLAIMERThis project is in theBETAstage of development. Please be aware that interfaces and functionality may change as the project develops. If this software is to be used in operational systems you arestrongly advised to use a released tag in your system configuration, and you should be willing to accept incoming changes and bug fixes that require adaptations on your part. ECMWFdoes usethis software in operations and abides by the same caveats.A format-agnostic interface for geospatial data with a focus on meteorology and
climate science.DocumentationThe documentation can be found athttps://earthkit-data.readthedocs.io/.InstallInstall viapipwith:$ pip install earthkit-dataMore details, such as how to install any necessary binaries, can be found  athttps://earthkit-data.readthedocs.io/en/latest/install.html.Alternatively, install viacondawith:$ conda install earthkit-data -c conda-forgeThis will bring in some necessary binary dependencies for you.LicenseCopyright 2022, European Centre for Medium Range Weather Forecasts.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

In applying this licence, ECMWF does not waive the privileges and immunities
granted to it by virtue of its status as an intergovernmental organisation
nor does it submit to any jurisdiction.
Package: earthkit-maps
earthkit.mapsDISCLAIMERThis project is in theBETAstage of development. Please be aware that interfaces and functionality may change as the project develops. If this software is to be used in operational systems you arestrongly advised to use a released tag in your system configuration, and you should be willing to accept incoming changes and bug fixes that require adaptations on your part. ECMWFdoes usethis software in operations and abides by the same caveats.Format-agnostics geospatial visualisation tools and templates.DocumentationThe documentation can be found athttps://earthkit-maps.readthedocs.io/.InstallInstall viapipwith:$ pip install earthkit-mapsMore details, such optional additional dependencies, can be found  athttps://earthkit-data.readthedocs.io/en/latest/install.html.LicenseCopyright 2023, European Centre for Medium Range Weather Forecasts.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Package: earthkit-meteo
earthkit-meteoMeteorological computations.DISCLAIMERThis project isBETAand will beExperimentalfor the foreseeable future.
Interfaces and functionality are likely to change, and the project itself may be scrapped.DO NOTuse this software in any project/software that is operational.DocumentationThe documentation can be found athttps://earthkit-meteo.readthedocs.io/.InstallInstall viapipwith:$ pip install earthkit-meteoMore details, such as how to install any necessary binaries, can be found  athttps://earthkit-meteo.readthedocs.io/en/latest/install.html.Alternatively, install viacondawith:$ conda install earthkit-meteo -c conda-forgeThis will bring in some necessary binary dependencies for you.LicenseCopyright 2022, European Centre for Medium Range Weather Forecasts.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

In applying this licence, ECMWF does not waive the privileges and immunities
granted to it by virtue of its status as an intergovernmental organisation
nor does it submit to any jurisdiction.
Package: earthkit-regrid
earthkit-regridDISCLAIMERThis project is BETA and will be Experimental for the foreseeable future. Interfaces and functionality are likely to change, and the project itself may be scrapped. DO NOT use this software in any project/software that is operational.ECMWF Python regridding toolkit.DocumentationThe documentation can be found athttps://earthkit-regrid.readthedocs.io/.LicenseCopyright 2022, European Centre for Medium Range Weather Forecasts.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

In applying this licence, ECMWF does not waive the privileges and immunities
granted to it by virtue of its status as an intergovernmental organisation
nor does it submit to any jurisdiction.
Package: earthml
EarthML: Geospatial Data Analysis Made EasyEarthML is an advanced Python library engineered to streamline the analysis of geospatial and remote sensing data. Developed with a vision to encompass a wide array of functionalities, EarthML currently supports geospatial data conversion into geohashes, and pre-processing of Synthetic Aperture Radar (SAR) datasets from Sentinel-1, ALOSPALSAR, and TerraSAR-X. EarthML is committed to expanding its functionalities to include other remote sensing sensors such as LiDAR, Hyperspectral, and Multispectral Optical in the near future.GoalThe primary objective of EarthML is to simplify and expedite the geospatial and SAR data analysis process. It is designed to handle diverse file formats, automatically compute geohashes that encapsulate the entire study area, and conduct essential pre-processing steps on SAR data.FeaturesSupport for Multiple Formats: Facilitates the conversion of geospatial data in various formats such as Shapefile, GeoJSON, GeoTIFF, LAS, and images.Geohash Calculation: Automatically computes the geohash that optimally represents the geographical bounds of the dataset.SAR Data Pre-Processing: Offers functionalities for crucial pre-processing steps on SAR datasets from Sentinel-1, ALOSPALSAR, and TerraSAR-X. This includes radiometric calibration, speckle filtering, and geometric correction.Future-Ready: EarthML is actively developed with a roadmap that includes the integration of other remote sensing sensors such as LiDAR, Hyperspectral, and Multispectral Optical.InstallationTo install EarthML, you can use pip:pip install earthmlLicenseThis project is licensed under the MIT License. See the LICENSE file for details.AuthorAkhil ChhibberNoteThis README provides a concise overview of the library, elucidates its objectives, highlights key features, and outlines simple installation instructions.EarthML is under active development. We welcome contributions and suggestions for new features and improvements.
Package: earthnet
EarthNet ToolkitThe EarthNet2021 Toolkit.DocumentationFind more information onhttps://www.earthnet.tech.Installpip install earthnetDownloading new dataset EarthNet2021xEnsure you have enough free disk space! We recommend 1TB.import earthnet as en
en.download(dataset = "earthnet2021x", split = "train", save_directory = "data_dir")Wheredata_diris the directory where EarthNet2021 shall be saved andsplitsis"all"or a subset of["train","iid","ood","extreme","seasonal"].Scoring new dataset EarthNet2021xSave your predictions for one test set in one folder in the following way:{pred_dir/region/cubename.nc}Name your NDVI prediction variable as"ndvi_pred".Then use thedata_dir/dataset/splitas the targets.Then compute the normalized NSE over the full dataset:import earthnet as en
scores = en.score_over_dataset(Path/to/targets, Path/to/predictions)
print(scores["veg_macro_score"])Alternatively you can score a single minicube:import earthnet as en
df = en.normalized_NSE(Path/to/target_minicube, Path/to/prediction_minicube)
print(df.describe())DownloadEnsure you have enough free disk space! We recommend 1TB.import earthnet as en
en.Downloader.get(data_dir, splits)Wheredata_diris the directory where EarthNet2021 shall be saved andsplitsis"all"or a subset of["train","iid","ood","extreme","seasonal"].Alternatively if package was installed locally:cd earthnet-toolkit/earthnet/
python download.py -h
python download.py "Path/To/Download/To" "all"For using in the commandline.Use EarthNetScoreSave your predictions for one test set in one folder in one of the following ways:{pred_dir/tile/cubename.npz, pred_dir/tile/experiment_cubename.npz}Then use the Path/To/Download/To/TestSet as the targets.Then use the EarthNetScore:import earthnet as en
en.EarthNetScore.get_ENS(Path/to/predictions, Path/to/targets, data_output_file = Path/to/data.json, ens_output_file = Path/to/ens.json)Get Coordinates for a cubeGetting Lon-Lat-coordinates for a cube or tile is as simple as:import earthnet as en
en.get_coords_from_cube(cubename, return_meso = False)
en.get_coords_from_tile(tilename)Plotting a cubeCreating a gallery view for a cube is done as follows:import earthnet as en
import matplotlib.pyplot as plt
fig = en.cube_gallery(cubepath, variable = "ndvi")
plt.show()Creating a NDVI timeseries view for a cube is done as follows:import earthnet as en
import matplotlib.pyplot as plt
fig = en.cube_ndvi_timeseries(predpath, targpath)
plt.show()
Package: earth-osm
earth-osm. Python tool to extract large-amounts of OpenStreetMap dataearth-osm is a python package that provides an end-to-end solution to extract & standardizepower infrastructuredata from OpenStreetmap (OSM).FeaturesExtracts power infrastructure data from OSMCleans and Standardizes the data(coming soon)No API rate limits (data served from GeoFabrik)Provides a Python APISupports multiprocessingOutputs .csv and .geojson filesAggregate data per feature or per regionEasy to use CLI interfaceGetting StartedInstall earth-osm with pip:pipinstallearth-osmOr with conda:condainstall--channel=conda-forgeearth-osmExtract osm data# Example CLI commandearth_osmextractpower--regionsbeninmonaco--featuressubstationlineThis will extractprimary feature = powerfor theregions = beninandmonacoand thesecondary features = substationandline.
By default the resulting .csv and .geojson are stored in./earth_data/outLoad the substation data for benin using pandas# For Pandasdf_substations=pd.read_csv('./earth_data/out/BJ_raw_substations.csv')# For GeoPandasgdf_substations=gpd.read_file('./earth_data/out/BJ_raw_substations.geojson')Other Argumentsusage: earth_osm extractprimary--regionsregion1, region2--featuresfeature1, feature2--data_dirDATA_DIR [--update] [--mp]primary(e.g power, water, road, etc) NOTE: currently only power is supported--regionsregion1 region2 ... (use either iso3166-1:alpha2 or iso3166-2 codes or full names as given by running 'earth_osm view regions')--featuresfeature1 feature2 ... (optional, use sub-features of primary feature, e.g. substation, line, etc)--update(optional, update existing data, default False)--mp(optional, use multiprocessing, default True)--data_dir(optional, path to data directory, default './earth_data')--out_format(optional, export format options csv or geojson, default csv)--out_aggregate(options, combine outputs per feature, default False)Advanced Usageimportearth_osmaseoeo.save_osm_data(primary_name='power',region_list=['benin','monaco'],feature_list=['substation','line'],update=False,mp=True,data_dir='./earth_data',out_format=['csv','geojson'],out_aggregate=False,)Development(Optional) Intstall a specific version of earth_osmpip install git+https://github.com/pypsa-meets-earth/earth-osm.git@<required-commit-hash>(Optional) Create a virtual environment for python>=3.10python3-mvenv.venvsource.venv/bin/activateRead theCONTRIBUTING.mdfile.pipinstallgit+https://github.com/pypsa-meets-earth/earth-osm.git
pipinstall-rrequirements-test.txt
Package: earthpic
Python script downloading Earth photos taken by Himawari-8 satelite.
Website:http://himawari8.nict.go.jp/Inspired by this reddit thread:https://www.reddit.com/r/programming/comments/441do9/i_made_a_windows_powershell_script_that_puts_a/Especially by european_impostor’s Powershell script:https://gist.github.com/MichaelPote/92fa6e65eacf26219022And most of all, its Python implementations:
by celoyd:https://gist.github.com/celoyd/39c53f824daef7d363dband by willwhitney:https://gist.github.com/willwhitney/e9e2c42885385c51843eThis script is Windows specific. Python 3.4+ only compatible.
Tested on Windows 7, Python 3.4.4 and Python 3.5.1InstallationTo install, download source or clone it with gitgit clonehttps://github.com/pywkm/earthpic.gitChange to eartpic/ directory and run setup.pycd earthpic/
python setup.py installThis should install all dependencies (Pillow,requests,pytzandclick).
If you have problem with installing Pillow package duringpython setup.py installand/or withpip install pillow, you can download wheel file fromhttp://www.lfd.uci.edu/~gohlke/pythonlibs/and install it with commandpip install <path/to/whl_file>.UsageCallearthpic –helpfrom command line to view this help:usage: earthpic [-h] [-d DATE] [-t TIME] [-s SCALE] [-w] [-v] [-l N_PHOTOS][-b] [-p PATH]Download satelite Earth photo(s)optional arguments:-h,--helpshow this help message and exit-dDATE,--dateDATEdate of the photo [format: YYYY-MM-DD] (default:
2016-02-09)-tTIME,--timeTIMEtime of the photo [fotmat: hh:mm] (default: 00:05)-sSCALE,--scaleSCALEscale of the photo, choices: 1, 2, 4, 8, 16 or 20
(default: 2)-w,--wallpaperset downloaded image as desktop wallpaper (default:
False)-v,--verboseincrease output verbosity (default: False)-lN_PHOTOS,--lastN_PHOTOSprocess N photos to given date (default: 1)-b,--batchrun batch downloading photos. To stop, press ctrl+c.
(default: False)-pPATH,--pathPATHpath where images will be saved (default: images)So, for instance calling justearthpicwithout arguments will download latest
satelite photo (current time minus ~20 minutes - delay of original service) and
save it to./images/directory, without setting it as desktop wallpaper.To specify date and time of picture write:earthpic -d 2016-02-01 -t 02:50.
All dates/times are considered as in UTC timezone.To set downloaded picture as wallpaper, write:earthpic -w -d 2016-02-01 -t 02:50.To change scale (size, quality of wallpaper):earthpic -w -s 4 -d 2016-02-01 -t 02:50.