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数据与研究 · SKILL.md

pygmt

pygmt

【数据与研究】Make geographic maps and process geospatial grids with PyGMT and GMT, including projection, regions, grid registration and vector/raster export. Use for GMT cartography and map-ready scientific data; check the separate GMT shared library before plotting.

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技能说明

GitHub

name: pygmt description: Make geographic maps and process geospatial grids with PyGMT and GMT, including projection, regions, grid registration and vector/raster export. Use for GMT cartography and map-ready scientific data; check the separate GMT shared library before plotting. license: MIT metadata: version: "1.0.0" author: Geoscience Skills skill_type: domain tags: '["Cartography", "GMT", "Maps", "Grids"]' dependencies: '["pygmt==0.19.0"]' complements: '["xarray", "verde", "boule"]' workflow_role: visualization

PyGMT

Produce a map whose projection, coordinate units and data coverage are explicit. PyGMT 0.19 requires Python 3.12+ and GMT 6.5+; the Python package alone does not install the GMT shared library. Use the documented isolated conda-forge setup with Ghostscript when exporting figures. Record PyGMT and GMT versions separately.

Inputs and map design

Establish geographic versus projected coordinates, horizontal CRS, longitude convention and vertical datum. Choose region [west, east, south, north] and projection deliberately. Decide pixel versus gridline registration and verify coordinate ordering, spacing and NaN masks before gridding or image display. Do not reinterpret projected metres as longitude/latitude degrees.

Offline map with synthetic locations

This example requires output_pdf to name a new output file. It uses no remote relief or coastline dataset; the three locations are illustrative, not a survey.

# example: synthetic-map
import pygmt

figure = pygmt.Figure()
figure.basemap(region=[5, 10, 44, 48], projection="M10c",
               frame=["af", "+tSynthetic locations"])
figure.plot(x=[6, 7.5, 9], y=[45, 46, 47], style="c0.18c",
            fill="navy", pen="0.4p,black")
figure.savefig(output_pdf)

For actual gridded data, inspect spacing/registration before grdimage; choose interpolation and color limits appropriate to units and scientific comparison. Remote datasets such as Earth relief require documented resolution, cache, license and download size. A cropped map does not prove the source data only cover that region.

Validate and deliver

Reopen the exported file, check bounds, labels, orientation, missing-data areas and color scale. Compare control-point coordinates with the input, and sample known grid nodes through GMT when grid operations are involved. Provide the source data references, script, CRS/projection and export settings with the map.

See installation, tutorials and GMT grid conventions.

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