Skip to main content

Geographic and Meteorological Analysis.

Project description

Preface

For most scholars of geosciences or meteorology, data processing is a big project, which can take several hours or days of data processing. Without good tools or methods, it will be extremely difficult to analyze and research data with multiple time series (such as time series remote sensing data) and large-scale (such as nationwide), because data processing itself is very time-consuming and labor-intensive.

In order to solve these problems, gma (Geographic and Meteorological Analysis) encapsulates the data processing process.

Requires

  • pandas: >= 3.0.0

  • numpy: >= 2.0.0

  • scipy: >= 1.14.0

  • matplotlib: >= 3.8.0

Included features

  • Climate and meteorology(gma.climet): e.g. SPEI, SPI, ET0, etc.

  • Remote sensing indices(gma.rsvi): e.g. NDVI, EVI, TVDI, etc.

  • Mathematical operations(gma.math): e.g. data smoothing, evaluation, filtering, stretching, enhancement transformations, etc.

  • Spatial miscellany(gma.smc): e.g. spatial distance calculation, area calculation, coordinate transformation, spatial interpolation, etc.

  • Geographic formats(gma.driver): e.g. creating and modifying raster/vector driven formats.

  • Raster/Vector reading, writing and conversion(gma.gio): e.g. raster mosaicking, resampling, etc. vector clipping, erasing, intersection, merging, reprojection, etc.

  • Coordinate reference system(gma.crs): e.g. creating projections, ellipsoids, datum, etc.

  • Cartographic tool(gma.carto): e.g. raster and vector data plotting, generating north arrow, scale bar, defining coordinate systems, etc.

Due to the limited level, there will be more or less problems in the function. Looking forward to your feedback and corrections.

More functions will be added later. We hope you can provide valuable comments.

Project details


Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

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

gma-3.0.0a15-cp314-cp314-win_amd64.whl (40.6 MB view details)

Uploaded CPython 3.14Windows x86-64

gma-3.0.0a15-cp313-cp313-win_amd64.whl (41.0 MB view details)

Uploaded CPython 3.13Windows x86-64

gma-3.0.0a15-cp312-cp312-win_amd64.whl (40.6 MB view details)

Uploaded CPython 3.12Windows x86-64

gma-3.0.0a15-cp311-cp311-win_amd64.whl (41.2 MB view details)

Uploaded CPython 3.11Windows x86-64

File details

Details for the file gma-3.0.0a15-cp314-cp314-win_amd64.whl.

File metadata

  • Download URL: gma-3.0.0a15-cp314-cp314-win_amd64.whl
  • Upload date:
  • Size: 40.6 MB
  • Tags: CPython 3.14, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.3

File hashes

Hashes for gma-3.0.0a15-cp314-cp314-win_amd64.whl
Algorithm Hash digest
SHA256 fc715716864cddca35090c7cb1dca2f5423012ac2cb0c2ad809ed20d77267100
MD5 2c523f26a32aafaad1ee4aa838e8c2f8
BLAKE2b-256 31211d54d9734114be4f1586f980caad1bcda4e2ee68e631fa6655412e1af914

See more details on using hashes here.

File details

Details for the file gma-3.0.0a15-cp313-cp313-win_amd64.whl.

File metadata

  • Download URL: gma-3.0.0a15-cp313-cp313-win_amd64.whl
  • Upload date:
  • Size: 41.0 MB
  • Tags: CPython 3.13, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.3

File hashes

Hashes for gma-3.0.0a15-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 bad2850f7bd481200938cc364717652ce27886838b27fd5a9de3d881549c4242
MD5 d19e2e45ba0f8a857d0b230b034613e9
BLAKE2b-256 3eab20c64769ef7a3e02976c3da0814c1e69ea875f3c79788562ad6931c3f887

See more details on using hashes here.

File details

Details for the file gma-3.0.0a15-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: gma-3.0.0a15-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 40.6 MB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.3

File hashes

Hashes for gma-3.0.0a15-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 4552d7f2d693da46b4bb44558952581c377571a76f26420b13be644ea4512096
MD5 13b3e198745b52826a9abe61375db078
BLAKE2b-256 f7e8051e877018fa8fd1ce08e43ae40aa3c5cf76bea1b11183df76217be3837e

See more details on using hashes here.

File details

Details for the file gma-3.0.0a15-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: gma-3.0.0a15-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 41.2 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.3

File hashes

Hashes for gma-3.0.0a15-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 5d27968a525c01baaca8b497305c34920fe512c68acfbf6d9eea2405ea95466f
MD5 6ddb616ccb1e6a57e0ee10c4b978e1ed
BLAKE2b-256 8730aa0aff7b89b307c69e8043e8240919803f411f58a090c6f1750bb6423f2f

See more details on using hashes here.

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