Earth Engine to xarray interface

Navigation

Verified details

These details have been verified by PyPI
Project links
GitHub Statistics
Maintainers
Avatar for aazuspan from gravatar.com aazuspan

Unverified details

These details have not been verified by PyPI
Meta
Classifiers
Report project as malware

Project description

wxee .-- -..-

Earth Engine Python PyPI conda-forge Open in Colab Read the Docs Build status
Demo downloading weather data to xarray using wxee.

What is wxee?

wxee was built to make processing gridded, mesoscale time series data quick and easy by integrating the data catalog and processing power of Google Earth Engine with the flexibility of xarray, with no complicated setup required. To accomplish this, wxee implements convenient methods for data processing, aggregation, downloading, and ingestion.

wxee can be found in the Earth Engine Developer Resources!

Features

To see some of the capabilities of wxee and try it yourself, check out the interactive notebooks here!

Install

Pip

pip install wxee

Conda

conda install -c conda-forge wxee

Quickstart

Setup

Once you have access to Google Earth Engine, just import and initialize ee and wxee.

import ee
import wxee

wxee.Initialize()

Download Images

Download and conversion methods are extended to ee.Image and ee.ImageCollection using the wx accessor. Just import wxee and use the wx accessor.

xarray

ee.ImageCollection("IDAHO_EPSCOR/GRIDMET").wx.to_xarray()

GeoTIFF

ee.ImageCollection("IDAHO_EPSCOR/GRIDMET").wx.to_tif()

Create a Time Series

Additional methods for processing image collections in the time dimension are available through the TimeSeries subclass. A TimeSeries can be created from an existing ee.ImageCollection…

col = ee.ImageCollection("IDAHO_EPSCOR/GRIDMET")
ts = col.wx.to_time_series()

Or instantiated directly just like you would an ee.ImageCollection!

ts = wxee.TimeSeries("IDAHO_EPSCOR/GRIDMET")

Aggregate Daily Data

Many weather datasets are in daily or hourly resolution. These can be aggregated to coarser resolutions using the aggregate_time method of the TimeSeries class.

ts = wxee.TimeSeries("IDAHO_EPSCOR/GRIDMET")
monthly_max = ts.aggregate_time(frequency="month", reducer=ee.Reducer.max())

Calculate Climatological Means

Long-term climatological means can be calculated using the climatology_mean method of the TimeSeries class.

ts = wxee.TimeSeries("IDAHO_EPSCOR/GRIDMET")
mean_clim = ts.climatology_mean(frequency="month")

Contribute

Bugs or feature requests are always appreciated! They can be submitted here.

Code contributions are also welcome! Please open an issue to discuss implementation, then follow the steps below. Developer setup instructions can be found in the docs.

Project details

Verified details

These details have been verified by PyPI
Project links
GitHub Statistics
Maintainers
Avatar for aazuspan from gravatar.com aazuspan

Unverified details

These details have not been verified by PyPI
Meta
Classifiers

Release history Release notifications | RSS feed

This version

0.5.0

0.4.2

0.4.1

0.4.0

0.3.3

0.3.2

0.3.1

0.3.0

0.2.2

0.2.0

0.1.1

0.1.0

0.0.1

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

wxee-0.5.0.tar.gz (21.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

wxee-0.5.0-py3-none-any.whl (26.7 kB view details)

Uploaded Python 3

File details

Details for the file wxee-0.5.0.tar.gz.

File metadata

  • Download URL: wxee-0.5.0.tar.gz
  • Upload date:
  • Size: 21.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for wxee-0.5.0.tar.gz
Algorithm Hash digest
SHA256 5ad1f2e1c625e2b13ba81c50b84236bde35f7ab578791917a6c23ec0fe4e9f30
MD5 7f649180a59e8ca30a2e8080e2ab19d7
BLAKE2b-256 ceb250f6c923dddd1617a6e5329a74d61cf4408f6e435537f50b7e4b1e1a83f7

See more details on using hashes here.

Provenance

The following attestation bundles were made for wxee-0.5.0.tar.gz:

Publisher: publish.yaml on aazuspan/wxee

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file wxee-0.5.0-py3-none-any.whl.

File metadata

  • Download URL: wxee-0.5.0-py3-none-any.whl
  • Upload date:
  • Size: 26.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for wxee-0.5.0-py3-none-any.whl
Algorithm Hash digest
SHA256 9c56cf2178c23fac7d8775a6f2eb4181c001e1b345b52a636038e3d313c0d8e8
MD5 7be21fd7dd525f7d1da6664fa52fb9eb
BLAKE2b-256 8c6f0f6b6e860c11beecc409befceda09cc15dfadd893d43f1179cb260e063c1

See more details on using hashes here.

Provenance

The following attestation bundles were made for wxee-0.5.0-py3-none-any.whl:

Publisher: publish.yaml on aazuspan/wxee

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page