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: >= 3.0.3
numpy: >= 2.4.1
scipy: >= 1.17.0
matplotlib: >= 3.10.8
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.
1 maintainer
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distributions
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file gma-3.0.3-cp314-cp314-win_amd64.whl.
File metadata
- Download URL: gma-3.0.3-cp314-cp314-win_amd64.whl
- Upload date:
- Size: 25.0 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
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
afaf329105c0244b3e384799fb757ee6b60e2f8cd0f7d73ad1f2c83ef57f0954
|
|
| MD5 |
07c3058c3aaa2131aa2130ad1559fc33
|
|
| BLAKE2b-256 |
a1eea275012c283f0595b0b789ca5ee8da3bd7299f41b3ed2092f330e3db661f
|
File details
Details for the file gma-3.0.3-cp313-cp313-win_amd64.whl.
File metadata
- Download URL: gma-3.0.3-cp313-cp313-win_amd64.whl
- Upload date:
- Size: 25.3 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
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f8797fa1a8fbf183bd45d0cc9b9addf2c8ee1bdfadb03ef5ca0944d860dfc158
|
|
| MD5 |
1577226e128acd07e880f0db5417653c
|
|
| BLAKE2b-256 |
d1e51cc8c6cbfe0fa2cb640fd0b758a51665af2631dedd4c671c702ed3b6ec44
|
File details
Details for the file gma-3.0.3-cp312-cp312-win_amd64.whl.
File metadata
- Download URL: gma-3.0.3-cp312-cp312-win_amd64.whl
- Upload date:
- Size: 24.9 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
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
675b7e7a5b029eec6c5eeab61d494668bcb4de396d7253122b57d5cec0cda86e
|
|
| MD5 |
c4df8e48c3b54ce57708b57f6dde6a5e
|
|
| BLAKE2b-256 |
52c1203e8ea81bccd5800c51ba29b9e790b480de0653b2bd7a60f8fac8840c60
|
