Skip to main content

Geospatial image resampling in Python

Project description

Build Status Build status Coverage Status

Pyresample

Pyresample is a python package for resampling geospatial image data. It is the primary method for resampling in the Satpy library, but can also be used as a standalone library. Resampling or reprojection is the process of mapping input geolocated data points to a new target geographic projection and area.

Pyresample can operate on both fixed grids of data and geolocated swath data. To describe these data Pyresample uses various "geometry" objects including the AreaDefinition and SwathDefinition classes.

Pyresample offers multiple resampling algorithms including:

  • Nearest Neighbor
  • Elliptical Weighted Average (EWA)
  • Bilinear

For nearest neighbor and bilinear interpolation pyresample uses a kd-tree approach by using the fast KDTree implementation provided by the pykdtree library. Pyresample works with numpy arrays and numpy masked arrays. Interfaces to XArray objects (including dask array support) are provided in separate Resampler class interfaces and are in active development. Utility functions are available to easily plot data using Cartopy.

Pyresample is tested with Python 2.7 and 3.6, but should additionally work on Python 3.4+. Pyresample will drop Python 2.7 at the end of 2019.

Documentation

See pytroll.github.io for more information on the PyTroll group and related packages.

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distribution

pyresample-1.14.0.tar.gz (4.5 MB view details)

Uploaded Source

File details

Details for the file pyresample-1.14.0.tar.gz.

File metadata

  • Download URL: pyresample-1.14.0.tar.gz
  • Upload date:
  • Size: 4.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2.post20191201 requests-toolbelt/0.9.1 tqdm/4.41.0 CPython/2.7.15

File hashes

Hashes for pyresample-1.14.0.tar.gz
Algorithm Hash digest
SHA256 92c418f164957d9d497e314ab1de5cec7bd75744fa391781bb8965bb4fd3142e
MD5 0ea4b534c5577f38fe9f38d42145fdbd
BLAKE2b-256 64fed19af918c8ea4f1e8c43595a01e0909a3a351776f13cc552f70800eab7b3

See more details on using hashes here.

Supported by

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