Skip to main content

gmpas

DOI tests PyPI python license

import gmpas

ds = gmpas.open_mpas("diag.2019-09-01_00.00.00.nc", mesh="maritime.region.nc")

ds.mpas.plot("mslp")        # cell field, filled Voronoi polygons
ds.mpas.plot("u")           # edge field, drawn on the cell faces themselves
ds.mpas.plot_mesh()         # where the mesh actually refines, in km

mesh= may be omitted when the file carries its own mesh information, or when a mesh file with a matching cell count sits beside it.

Installation

pip install gmpas            # core: geometry, caching, remap weights
pip install "gmpas[plot]"    # + matplotlib and cartopy, for plotting
conda env create -f environment.yml && conda activate gmpas && pip install -e . --no-deps

Mesh generation requires JIGSAW, MPI and PnetCDF.

gmpas --version

From a source install, pytest -q runs the test suite.

Full detail, including the extras and what each one pulls in: docs/installation.md.

Usage

gmpas info          history.2012-02-25_12.00.00.nc
gmpas plot          history.2012-02-25_12.00.00.nc precipw -o pw.png
gmpas view          /path/to/run/
gmpas remap         history.*.nc -o out/
gmpas prep view     mesh.nc
gmpas prep hfun     hfun.py --check
gmpas prep generate hfun.py -o mesh/     # needs $JIGSAWDIR and $MKGRIDFILE

Documentation

Why gmpas exists the problem with lat-lon tooling, and why this is fast
Installation conda, pip, extras, and the external programs
Command line every command and its flags
In a notebook the accessor, and using the pieces directly
Preprocessing prep view, prep hfun, prep generate — mesh design and JIGSAW
Conservative remapping the whole terminal workflow, and two MPAS traps
On a cluster port forwarding, and the two variables that matter
Configuration GMPAS_CACHE_DIR and GMPAS_DATA_DIR
Examples ready-to-edit hfun.py templates
Tests what the suite covers
Layout what lives in which module
Differences from the MCP server what changed on the way to a package
Status what is implemented and what is not

This document is generated using LLM (Claude)

Release files for gmpas 0.4.9

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for gmpas 0.4.9
File Size Uploaded
gmpas-0.4.9.tar.gz 257.4 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for gmpas 0.4.9
File Interpreter ABI Platform
gmpas-0.4.9-py3-none-any.whl Python 3 none any Details

Total release size: 428.8 kB

Release files / gmpas-0.4.9.tar.gz

Download URL gmpas-0.4.9.tar.gz
Size 257.4 kB
Tags Source
SHA-256 checksum
How to use checksums
1695882182168c9f13cdb11c24eb3233e2474741b5f051ce4b5ae0284bb8cfe7
BLAKE2b-256 checksum
How to use checksums
51d8b4c47dab914eb9ed31ae75cc326796e0e132f6e75cd74047b6cd6d887971
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Sep 14, 2026.

Transparency log

Release files / gmpas-0.4.9-py3-none-any.whl

Download URL gmpas-0.4.9-py3-none-any.whl
Size 171.4 kB
Tags Python 3
SHA-256 checksum
How to use checksums
01c6ab8058d7651bbe78f7e4a63e440945bfa45bfbb727dbd673c405bb936517
BLAKE2b-256 checksum
How to use checksums
3dc7865ea75dbe055b25012c9a9ed1e32cebb5ae6d6e7f9376eb24ee82b5add3
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Sep 14, 2026.

Transparency log

Release history Release notifications | RSS feed

0.5.7

2 release files

0.5.6

2 release files

0.5.0

2 release files

This release

0.4.9 This release

2 release files

0.4.8

2 release files

0.4.7

2 release files

0.4.3

2 release files

0.4.2

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page