pyresample

Geospatial image resampling in Python

These details have not been verified by PyPI

Development Status
- 5 - Production/Stable
Intended Audience
- Science/Research
License
- OSI Approved :: GNU Lesser General Public License v3 or later (LGPLv3+)
Operating System
- OS Independent
Programming Language
- Python
Topic
- Scientific/Engineering

Project description

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

These details have not been verified by PyPI

Development Status
- 5 - Production/Stable
Intended Audience
- Science/Research
License
- OSI Approved :: GNU Lesser General Public License v3 or later (LGPLv3+)
Operating System
- OS Independent
Programming Language
- Python
Topic
- Scientific/Engineering

Release history Release notifications | RSS feed

1.31.0

Oct 25, 2024

1.30.0

Aug 28, 2024

1.29.0

Aug 1, 2024

1.28.4

Jul 1, 2024

1.28.3

Apr 15, 2024

1.28.2

Feb 29, 2024

1.28.1

Feb 16, 2024

1.28.0

Feb 14, 2024

1.27.1

Jun 22, 2023

1.27.0

May 17, 2023

1.26.1

Feb 7, 2023

1.26.0.post0

Nov 24, 2022

1.26.0

Nov 24, 2022

1.25.1

Aug 2, 2022

1.25.0

Jul 29, 2022

1.24.1

Jul 7, 2022

1.24.0

Jul 6, 2022

1.23.0

Mar 22, 2022

1.22.3

Dec 8, 2021

1.22.2

Dec 3, 2021

1.22.1

Nov 18, 2021

1.22.0

Oct 25, 2021

1.21.1

Sep 17, 2021

1.21.0

Aug 19, 2021

1.20.0

Jun 4, 2021

1.19.0

Apr 14, 2021

1.18.1

Mar 23, 2021

1.18.0

Mar 13, 2021

This version

1.17.0

Nov 12, 2020

1.16.0

Jun 10, 2020

1.15.0

Mar 20, 2020

1.14.0

Dec 22, 2019

1.13.2

Oct 8, 2019

1.13.1

Sep 26, 2019

1.13.0

Sep 13, 2019

1.12.3

May 17, 2019

1.12.2

May 10, 2019

1.12.1

Apr 25, 2019

1.12.0

Apr 7, 2019

1.11.2

Mar 19, 2019

1.11.0

Mar 15, 2019

1.10.3

Nov 23, 2018

1.10.2

Oct 1, 2018

1.10.1

Jul 3, 2018

1.10.0

Jun 25, 2018

1.9.3

Jun 8, 2018

1.9.2

May 13, 2018

1.9.1

May 3, 2018

1.9.0

Apr 27, 2018

1.8.3

Mar 19, 2018

1.8.2

Mar 1, 2018

1.8.1

Feb 22, 2018

1.7.1

Dec 21, 2017

1.7.0

Oct 13, 2017

1.6.1

Sep 18, 2017

1.6.0

Sep 12, 2017

1.5.0

May 2, 2017

1.4.1

Apr 7, 2017

1.4.0

Apr 2, 2017

1.3.1

Mar 22, 2017

1.3.0

Feb 7, 2017

1.2.9

Dec 13, 2016

1.2.8

Dec 6, 2016

1.2.7

Nov 15, 2016

1.2.6

Oct 19, 2016

1.2.5

Jul 21, 2016

1.2.4

Jun 27, 2016

1.2.3

Jun 21, 2016

1.2.2

Jun 21, 2016

1.2.1

Jun 21, 2016

1.2.0

Jun 21, 2016

1.1.6

Feb 25, 2016

1.1.4

Oct 8, 2015

1.1.3

Feb 3, 2015

1.1.2

Feb 3, 2015

1.1.1

Dec 12, 2014

1.1.0

Oct 23, 2013

1.0.0

Jul 3, 2013

0.8.0

Mar 20, 2013

0.7.13

Jan 23, 2013

0.7.12

Oct 18, 2012

0.7.11

Jul 3, 2012

0.7.10

May 14, 2012

Download files

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

Source Distribution

pyresample-1.17.0.tar.gz (6.0 MB view details)

Uploaded Nov 12, 2020 Source

Built Distributions

pyresample-1.17.0-cp39-cp39-win_amd64.whl (2.1 MB view details)

Uploaded Nov 12, 2020 CPython 3.9 Windows x86-64

pyresample-1.17.0-cp39-cp39-win32.whl (2.1 MB view details)

Uploaded Nov 12, 2020 CPython 3.9 Windows x86

pyresample-1.17.0-cp39-cp39-manylinux2010_x86_64.whl (3.4 MB view details)

Uploaded Nov 12, 2020 CPython 3.9 manylinux: glibc 2.12+ x86-64

pyresample-1.17.0-cp39-cp39-manylinux2010_i686.whl (3.3 MB view details)

Uploaded Nov 12, 2020 CPython 3.9 manylinux: glibc 2.12+ i686

pyresample-1.17.0-cp39-cp39-manylinux1_x86_64.whl (3.4 MB view details)

Uploaded Nov 12, 2020 CPython 3.9

pyresample-1.17.0-cp39-cp39-manylinux1_i686.whl (3.3 MB view details)

Uploaded Nov 12, 2020 CPython 3.9

pyresample-1.17.0-cp39-cp39-macosx_10_9_x86_64.whl (2.1 MB view details)

Uploaded Nov 12, 2020 CPython 3.9 macOS 10.9+ x86-64

pyresample-1.17.0-cp38-cp38-win_amd64.whl (2.1 MB view details)

Uploaded Nov 12, 2020 CPython 3.8 Windows x86-64

pyresample-1.17.0-cp38-cp38-win32.whl (2.1 MB view details)

Uploaded Nov 12, 2020 CPython 3.8 Windows x86

pyresample-1.17.0-cp38-cp38-manylinux2010_x86_64.whl (3.4 MB view details)

Uploaded Nov 12, 2020 CPython 3.8 manylinux: glibc 2.12+ x86-64

pyresample-1.17.0-cp38-cp38-manylinux2010_i686.whl (3.4 MB view details)

Uploaded Nov 12, 2020 CPython 3.8 manylinux: glibc 2.12+ i686

pyresample-1.17.0-cp38-cp38-manylinux1_x86_64.whl (3.4 MB view details)

Uploaded Nov 12, 2020 CPython 3.8

pyresample-1.17.0-cp38-cp38-manylinux1_i686.whl (3.4 MB view details)

Uploaded Nov 12, 2020 CPython 3.8

pyresample-1.17.0-cp38-cp38-macosx_10_9_x86_64.whl (2.1 MB view details)

Uploaded Nov 12, 2020 CPython 3.8 macOS 10.9+ x86-64

pyresample-1.17.0-cp37-cp37m-win_amd64.whl (2.1 MB view details)

Uploaded Nov 12, 2020 CPython 3.7m Windows x86-64

pyresample-1.17.0-cp37-cp37m-win32.whl (2.1 MB view details)

Uploaded Nov 12, 2020 CPython 3.7m Windows x86

pyresample-1.17.0-cp37-cp37m-manylinux2010_x86_64.whl (3.2 MB view details)

Uploaded Nov 12, 2020 CPython 3.7m manylinux: glibc 2.12+ x86-64

pyresample-1.17.0-cp37-cp37m-manylinux2010_i686.whl (3.2 MB view details)

Uploaded Nov 12, 2020 CPython 3.7m manylinux: glibc 2.12+ i686

pyresample-1.17.0-cp37-cp37m-manylinux1_x86_64.whl (3.2 MB view details)

Uploaded Nov 12, 2020 CPython 3.7m

pyresample-1.17.0-cp37-cp37m-manylinux1_i686.whl (3.2 MB view details)

Uploaded Nov 12, 2020 CPython 3.7m

pyresample-1.17.0-cp37-cp37m-macosx_10_9_x86_64.whl (2.1 MB view details)

Uploaded Nov 12, 2020 CPython 3.7m macOS 10.9+ x86-64

pyresample-1.17.0-cp36-cp36m-win_amd64.whl (2.1 MB view details)

Uploaded Nov 12, 2020 CPython 3.6m Windows x86-64

pyresample-1.17.0-cp36-cp36m-win32.whl (2.1 MB view details)

Uploaded Nov 12, 2020 CPython 3.6m Windows x86

pyresample-1.17.0-cp36-cp36m-manylinux2010_x86_64.whl (3.2 MB view details)

Uploaded Nov 12, 2020 CPython 3.6m manylinux: glibc 2.12+ x86-64

pyresample-1.17.0-cp36-cp36m-manylinux2010_i686.whl (3.2 MB view details)

Uploaded Nov 12, 2020 CPython 3.6m manylinux: glibc 2.12+ i686

pyresample-1.17.0-cp36-cp36m-manylinux1_x86_64.whl (3.2 MB view details)

Uploaded Nov 12, 2020 CPython 3.6m

pyresample-1.17.0-cp36-cp36m-manylinux1_i686.whl (3.2 MB view details)

Uploaded Nov 12, 2020 CPython 3.6m

pyresample-1.17.0-cp36-cp36m-macosx_10_9_x86_64.whl (2.1 MB view details)

Uploaded Nov 12, 2020 CPython 3.6m macOS 10.9+ x86-64

File details

Details for the file pyresample-1.17.0.tar.gz.

File metadata

Download URL: pyresample-1.17.0.tar.gz
Upload date: Nov 12, 2020
Size: 6.0 MB
Tags: Source
Uploaded using Trusted Publishing? No
Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/49.2.1 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.9.0

File hashes

Hashes for pyresample-1.17.0.tar.gz
Algorithm	Hash digest
SHA256	`6b3d76194bbf2147d279d9bb2f687f1f5a4516813b7025ab2b3f676d11dc573e`
MD5	`c83262c57ffcd265ad1291aedf52ad54`
BLAKE2b-256	`164ced6215923e9d52dbbdfa8cc92d2c7ecbc4febf285cf0b0f672f6020f09c8`

Algorithm	Hash digest
SHA256	`5c9f88985fbb33abf03a0676f44f2a02e3ab58f9c9dbc2b7e14cccbe83990826`
MD5	`168ff7ca0f37ddf398847747f8d08ac5`
BLAKE2b-256	`d75b66de53d4566d8e10c50b5463255546a9d840770c1186ae74b929297dbd32`

Algorithm	Hash digest
SHA256	`10a2db4aae4ec4c67107041d3e3a495a6464a172a4e2459a0475f3d966fe4d75`
MD5	`4babbf179440c651900d4195ddc29883`
BLAKE2b-256	`72dac645f9dc11cf9c10800f964ae1792c7965c78de9240393dd6a03b653a2e9`

Algorithm	Hash digest
SHA256	`4bf9944b7c9a397e0e21581e192865e9f654c7d6e0a670937ebaa3bd6a360cb7`
MD5	`d27a5e6dfe4e6f1d929208792c11002a`
BLAKE2b-256	`59e7b256bd4eeca90549f96e5c729d93508cdc7e898aa530e50f691031be21ae`

Algorithm	Hash digest
SHA256	`093466f75c91f041e08322b706f2954334684f9d0c4ecd4376df621e0ce1b691`
MD5	`d51a0daf91888dd422f320f66bccb9b6`
BLAKE2b-256	`26c7d7b7adb5225a62f19670937f78a954509a5c98730a2fb7f0a0080b531343`

Algorithm	Hash digest
SHA256	`4331f5b233d1f35bc8d6d75704df286d75fb2b905c40e9fed00f4386d0a8ee11`
MD5	`3dbb56065adf0c381546abf410cd221c`
BLAKE2b-256	`b680cb0562eaae693e230656053c41e146bc5a996e4fd1db782111938c66ce67`

Algorithm	Hash digest
SHA256	`44296a65519379cb7cd517d7ab780b7e8e2b4fc9d89799f5ba4bb49aa214b393`
MD5	`7107e98c1fc3acbe77546cda849af99a`
BLAKE2b-256	`e09d30239f456b43b1e1d20d5b3eda38fd30a6b96d6c668dfef5be65b0660851`

Algorithm	Hash digest
SHA256	`b119ac72a173a91fd2cb140f25f8f279c044c7f2076a8a0f1271f0768d3a137f`
MD5	`d5b2e3d384d838ab4476c96341ccba6e`
BLAKE2b-256	`6371fe3f823914ccfad0138ab7012f431168958ca6a3e16acb70a4c7e9df97fe`

Algorithm	Hash digest
SHA256	`cbabf2c7b44154dadbf80609f31cabab8cec3332c2ac1719f920080d7d45cdc0`
MD5	`e8d14290179fe074f55316a8feea11ce`
BLAKE2b-256	`74a4765e85cd9457ee3dcef86aac9d8cf90c8ea02b87a5bc6ffb3e7a3f2bfc0c`

Algorithm	Hash digest
SHA256	`6dcd2b8b9f26f946376fb03a38c247ec3fa45eb34f79218a04baa66c2618a3a1`
MD5	`e18b2bf4d253bc2b0da4696bd5fd4efd`
BLAKE2b-256	`c3e3197ca2fda89761aa65d701dc0c58a7d7b5ddd1f08916e08e676df7afeaaa`

Algorithm	Hash digest
SHA256	`71688364ef552b72f765a115a0d7e041d68234389d57e4d9ec09453925cff3b2`
MD5	`8812a2d45b762c540fa278f4073bd361`
BLAKE2b-256	`d9799dece7eceb442f97c255aa73fa16a0cefefacc95fb97a045cba1819bc061`

Algorithm	Hash digest
SHA256	`dd59f4876cb9fae3c24b8a6745ca6082274a27cfb2700c4c40a75b8f53275b4a`
MD5	`102440c9c586d5c2c20337bce073c86d`
BLAKE2b-256	`4874b3dff79d3628958489a5a44029a04c1e80df7af6c8897882fe5866d9cf6b`

Algorithm	Hash digest
SHA256	`3bb691fa5b51495cad5f4ae0ae8749bb0a93a25ac24bace00b4e5440c62e8b47`
MD5	`3423e15f39486e0685654b2000377164`
BLAKE2b-256	`6629157db7f56349d3eab04551362c902337fd413acae154863c161b2f11e71b`

Algorithm	Hash digest
SHA256	`4acf05aa8722d3799096439cf9e6693078c774a608c326b1f309bf486c734223`
MD5	`2a01c9c97cd184eaf3604cbc59c75d87`
BLAKE2b-256	`599630348a10a31ff3f26d04e14fc1de3605315ecb16691ec71cbebaf203713d`

Algorithm	Hash digest
SHA256	`975638933f11b707df485b6a5a7b84229ec2eb1d41424cbf5296f2153cd9b5e3`
MD5	`85cbece52580c09bf446b9632a40055e`
BLAKE2b-256	`9a3559777bb7a86a32cb5b3fa9477b576d3846e458ff6b99907aea41b4ee0853`

Algorithm	Hash digest
SHA256	`16dd2af26efb8e9ce3c1996832f2024524cffe43fb132d3f4eefe7af74ea3b4a`
MD5	`4b9c9b358f34f884fe887aaf264e83a9`
BLAKE2b-256	`d5d233457c992cb46182f0629335e9b56a56b220638e7a17e11e5dd79c6bf07d`

Algorithm	Hash digest
SHA256	`92cbcc9bfcaff06752b24ae41d73b954fc84025b3f9c726e77b75904ec1bf833`
MD5	`2cb1b96fc697df48b4acec6f2366542c`
BLAKE2b-256	`fd4204b8a690bcb2a8d287dd48a1d07efe2f8a1052e08cb11510faa1cea896bf`

Algorithm	Hash digest
SHA256	`0123ef5e1322ce1146cc7d0afea10e95534ac6e6bf68266b9d5474a91f4afad1`
MD5	`9d9dc357cf8ee30142772c17bb966ef9`
BLAKE2b-256	`235812dbacc5287126aaf483975f01a85ab9811663ae1bd845bec683eb2a7d9a`

Algorithm	Hash digest
SHA256	`0929a4af2b1ee37503e8f1118bd216c900115f895c3681367a7b27c4e33443c7`
MD5	`e5baa9df71465a2f4a1d972157c34c2c`
BLAKE2b-256	`07045f5e551b8783876f038d6544fcfd90150df0c65faa9c82f6b32eaec36ffd`

Algorithm	Hash digest
SHA256	`3896bbe0bd3c160ce356fb0b90ccfa956e40684ac17fc5006cc1e95f5f08317e`
MD5	`6a4bb008aac71c398e7d73d41baa5ad0`
BLAKE2b-256	`1878d5e2abff31cf16117e084d2b958deca541c23fc5b2a02840027e47b51b33`

Algorithm	Hash digest
SHA256	`5b7c30eb203bcfba08c4c9f2277ce6ebdf97f1593fcf18a26239f83e0455c212`
MD5	`9db13b042c0221d37edbcb7baf0b5b18`
BLAKE2b-256	`9ad758e7a36c7b9a155876cb3dae2c6799a2362ef54c29c6352dacdf4f41d7b1`

pyresample 1.17.0

Navigation

Verified details

Maintainers

Unverified details

Meta

Classifiers

Project description

Pyresample

Project details

Verified details

Maintainers

Unverified details

Meta

Classifiers

Release history Release notifications | RSS feed

Download files

Source Distribution

Built Distributions

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

Algorithm	Hash digest
SHA256	`88bd6ebbb595b7173096e19bae9bc35f959c1b4f4fafac6e8d0199d5fe93c38d`
MD5	`35fda7bafd4bbb5c7082b5dfeecf9578`
BLAKE2b-256	`e86c25918b0f265463a87d827c142dcaa14d11b5d740387c0e96a6610aed366c`

Algorithm	Hash digest
SHA256	`0a82f809bea7c1a637cba0c0908892f7da049bf95812ea7e972f16bcef588739`
MD5	`771251798ab543e702c5a0ece69d5794`
BLAKE2b-256	`0797c4277f34828f10abf8ea279016f840aadecd5c634f48ac8b03b737ead825`

Algorithm	Hash digest
SHA256	`0129656e9e5ac0fa8942a899d0cba8c182d217b3acc0ca2de37913550b0580fd`
MD5	`1726e9ae82d09a0e803d9407d48f83fa`
BLAKE2b-256	`102e9063bd38b156d8bc2c688d39c17b4010e8437bf946d387082401368506d4`

Algorithm	Hash digest
SHA256	`78a668252028c3498e13678f05ee3937adf5ebfb90726b850093201be7a2092b`
MD5	`c7fbba27e5d0c07500f3fd8c7f9e63ee`
BLAKE2b-256	`de0a3c26602dd990811fd78397c690474ede00759e2dc362a1f1d9263186a70e`

Algorithm	Hash digest
SHA256	`a700162b8efa097f78445e2f9ec85cead5e32171be002f72543f2f3387ea3ab0`
MD5	`eb93bd6e44c9c9a81ffe0962d0873f90`
BLAKE2b-256	`8f9fd8dadb5f51bf9665e97c9e88c5dbc2d6eaca54fdbc37a072d7d87851eca2`

Algorithm	Hash digest
SHA256	`ab4f51f3a570f4bb87b546c79d06090bb9fcd6dfe97f85ac3feeb7d80957c41a`
MD5	`b7a2a4fd400cc0a8f9f63a1e75749d69`
BLAKE2b-256	`9ae99302227c1063a7958588ffcfcd4bac0ec6bdc010fd162003a1ca0c2aa313`

Algorithm	Hash digest
SHA256	`1fc9f8d619c80a79b145f17963232b1fca6bcd237fba09334c5d6530fc3a4390`
MD5	`12ad18ec816e99617834d1b70dada9d9`
BLAKE2b-256	`61ff42d4d56538ab6c3e0b1ceede98e915b675d6b29666dafaca7f0901875ee0`

Algorithm	Hash digest
SHA256	`02d363e5a511bb3fa21cfc5576da42465de0c089bd668f87d3a578d421886718`
MD5	`8e55120a5fd6e5e85dafc94678ed2d91`
BLAKE2b-256	`59951a3136a9487bc253da7baf2fbd1c73e70549ad3efeacad9c40131049cabd`