Geospatial image resampling in Python

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for dhoese from gravatar.com dhoese Avatar for Martin.Raspaud from gravatar.com Martin.Raspaud Avatar for storpipfugl from gravatar.com storpipfugl

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: GNU Lesser General Public License v3 or later (LGPLv3+)
  • Author: Thomas Lavergne
  • Requires: Python >=3.8
Classifiers

Project description

Build Status Coverage Status DOI

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.

Citation

Hoese, D., Raspaud, M., Lahtinen, P., Roberts, W., Lavergne, et al. (2020). pytroll/pyresample: Version 1.16.0. Zenodo. https://doi.org/10.5281/zenodo.3372769

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for dhoese from gravatar.com dhoese Avatar for Martin.Raspaud from gravatar.com Martin.Raspaud Avatar for storpipfugl from gravatar.com storpipfugl

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: GNU Lesser General Public License v3 or later (LGPLv3+)
  • Author: Thomas Lavergne
  • Requires: Python >=3.8
Classifiers

Release history Release notifications | RSS feed

1.31.0

1.30.0

1.29.0

1.28.4

1.28.3

1.28.2

1.28.1

1.28.0

1.27.1

1.27.0

1.26.1

1.26.0.post0

1.26.0

1.25.1

This version

1.25.0

1.24.1

1.24.0

1.23.0

1.22.3

1.22.2

1.22.1

1.22.0

1.21.1

1.21.0

1.20.0

1.19.0

1.18.1

1.18.0

1.17.0

1.16.0

1.15.0

1.14.0

1.13.2

1.13.1

1.13.0

1.12.3

1.12.2

1.12.1

1.12.0

1.11.2

1.11.0

1.10.3

1.10.2

1.10.1

1.10.0

1.9.3

1.9.2

1.9.1

1.9.0

1.8.3

1.8.2

1.8.1

1.7.1

1.7.0

1.6.1

1.6.0

1.5.0

1.4.1

1.4.0

1.3.1

1.3.0

1.2.9

1.2.8

1.2.7

1.2.6

1.2.5

1.2.4

1.2.3

1.2.2

1.2.1

1.2.0

1.1.6

1.1.4

1.1.3

1.1.2

1.1.1

1.1.0

1.0.0

0.8.0

0.7.13

0.7.12

0.7.11

0.7.10

Download files

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

Source Distribution

pyresample-1.25.0.tar.gz (6.4 MB view details)

Uploaded Source

Built Distributions

pyresample-1.25.0-cp310-cp310-win_amd64.whl (2.2 MB view details)

Uploaded CPython 3.10 Windows x86-64

pyresample-1.25.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.0 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

pyresample-1.25.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (3.9 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

pyresample-1.25.0-cp310-cp310-macosx_10_15_x86_64.whl (2.3 MB view details)

Uploaded CPython 3.10 macOS 10.15+ x86-64

pyresample-1.25.0-cp39-cp39-win_amd64.whl (2.2 MB view details)

Uploaded CPython 3.9 Windows x86-64

pyresample-1.25.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.1 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

pyresample-1.25.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (4.0 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

pyresample-1.25.0-cp39-cp39-macosx_10_15_x86_64.whl (2.3 MB view details)

Uploaded CPython 3.9 macOS 10.15+ x86-64

pyresample-1.25.0-cp38-cp38-win_amd64.whl (2.2 MB view details)

Uploaded CPython 3.8 Windows x86-64

pyresample-1.25.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.1 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

pyresample-1.25.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (4.0 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

pyresample-1.25.0-cp38-cp38-macosx_10_15_x86_64.whl (2.3 MB view details)

Uploaded CPython 3.8 macOS 10.15+ x86-64

File details

Details for the file pyresample-1.25.0.tar.gz.

File metadata

  • Download URL: pyresample-1.25.0.tar.gz
  • Upload date:
  • Size: 6.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.13

File hashes

Hashes for pyresample-1.25.0.tar.gz
Algorithm Hash digest
SHA256 82a7bac79f28160161dd6f99d09fd47f6cd6f5195d9063394002a8bc75b06a17
MD5 5a070500a569ee05099ffbfb2ae6d388
BLAKE2b-256 9a8688ba63c039266e1831db6a51f38389da50c59e4e74e9b083d039225f38c4

See more details on using hashes here.

File details

Details for the file pyresample-1.25.0-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for pyresample-1.25.0-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 83a791893b5252051f6d93b36a1ee3d71fd255ee90b79ffc7082e64dfe1aeb05
MD5 3117beadf77f0533eeedc0a57d723a68
BLAKE2b-256 6d25c150a72f4627ac8fc06b92b42a2bc81aefd6a188b1582239e2b7186797c5

See more details on using hashes here.

File details

Details for the file pyresample-1.25.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyresample-1.25.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 35ff9c1764d2276153770dcace675e73285e30d2c1289b34ad034c38794bf06b
MD5 d03f42cc01d857c659b5af5716433ddd
BLAKE2b-256 7eab872d851becb459f79f4a2b2e61b6440ebb68522266c19343cc1c7b20a2bd

See more details on using hashes here.

File details

Details for the file pyresample-1.25.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pyresample-1.25.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 6997ea6c6bb8c6987ce5726f1d3595061b71d1c56e0cef9d1cf0e4c00ded4a5b
MD5 881e1d88a09c3a0198d3ca6aa809cb91
BLAKE2b-256 4977c5dafb0c43ab08e767e2a7756ce2828bef9002f28c8c3bbf3d23bcd2313b

See more details on using hashes here.

File details

Details for the file pyresample-1.25.0-cp310-cp310-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for pyresample-1.25.0-cp310-cp310-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 24536b01107b94571b2aa3465cc4b565f7f05df049b6bfde24bf9416d908179c
MD5 70d01e1e6cb1064000d10c6c011e497d
BLAKE2b-256 c425c54efaf5561de901f51f98b60bc878cb4726910b0e14c3d6d3e6eeeb8e48

See more details on using hashes here.

File details

Details for the file pyresample-1.25.0-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for pyresample-1.25.0-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 5a19a85329aa746c35eb5ec6d8557373fe7c66f05a7a08fb57081a107b351317
MD5 ea02cd8619390eca4501829852186d46
BLAKE2b-256 f33f5aa98188666305a04708c6a31f317e5f105532605497738db94526e01854

See more details on using hashes here.

File details

Details for the file pyresample-1.25.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyresample-1.25.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 c0f944369589b10abd68d118819e46b616df25864168bb96b6ab8e859c5cef90
MD5 5976efa45870b8ee7109b7eb34b6116b
BLAKE2b-256 6c304c0d4b77ad772a2045169946e89d9f82fae10d9631e3c63ffd2de87ba990

See more details on using hashes here.

File details

Details for the file pyresample-1.25.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pyresample-1.25.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 fec3ce33e2a6ee3037270ba61e8431aee510bdcd408d7767c76902de6466bb73
MD5 0af4d8f2e5b0fbab7d0604b90e3f348c
BLAKE2b-256 06f1bedf60cb3adf0cddc821786d60b5be040d56c60c102b15ae09ad598f1f70

See more details on using hashes here.

File details

Details for the file pyresample-1.25.0-cp39-cp39-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for pyresample-1.25.0-cp39-cp39-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 a0abd913078c613013f425d2b0d5347bc34400583130a2af9a070b6380db36b0
MD5 07bb5e6cc0133f0e6639de9e4a4c860f
BLAKE2b-256 b4089134b984bec6a7d5a1b3bd7767a142a9c169d91f438aa7351d1ac83c1072

See more details on using hashes here.

File details

Details for the file pyresample-1.25.0-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for pyresample-1.25.0-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 d7ac0f1e0d534ce123d3565e438cf1c9da7a30026d7ca0f743028013b1426d66
MD5 2bb55f28968a0174641c139ed8c8ea12
BLAKE2b-256 bb85c38c16ecd4300f64bfa3320831417e7cf3d02c42b26bec3116a546a05384

See more details on using hashes here.

File details

Details for the file pyresample-1.25.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyresample-1.25.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 b41ec5d3c561978f78d0bd2998bb81e17f5b440372f5f45f65a799a89bfc2145
MD5 26bcb4ac9f3ea581635a423d6019a1ac
BLAKE2b-256 cc32865eef8e3d1698c705bc12081207f944432b8e26b870c334394b084751bf

See more details on using hashes here.

File details

Details for the file pyresample-1.25.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pyresample-1.25.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 81f36b0747e663cb154108344c9e68403cb00b8b541403766e0a77eb81883670
MD5 d2d02a93f1a1aa7c752938d83ff5ae7c
BLAKE2b-256 69c4ba3cb6b24ded981689dc98bc20449f3a41b0b02e855ed85b0c38c81ac5b7

See more details on using hashes here.

File details

Details for the file pyresample-1.25.0-cp38-cp38-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for pyresample-1.25.0-cp38-cp38-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 59d65ed6117a606f37a5659a3ebf91500117a5b1ff95e1c3483e82af86d60e78
MD5 fcf6a0a66a5c9e6d0ae6e9363a223942
BLAKE2b-256 761e005d34dcab744dd40955df9b71ea6b78de6e16818e698e01e1434bdb7cd6

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