monet.plots.mapgen

Map utilities.

Functions

draw_map(*[, crs, natural_earth, ...])

Draw a map with Cartopy.
monet.plots.mapgen.draw_map(*, crs=None, natural_earth=False, coastlines=True, states=False, counties=False, countries=True, resolution='10m', extent=None, figsize=(10, 5), linewidth=0.25, return_fig=False, **kwargs)

Draw a map with Cartopy.

Creates a map using Cartopy with configurable features like coastlines, borders, and natural earth elements. This function simplifies the process of creating maps for spatial visualization.

Parameters:

  • crs (cartopy.crs.Projection) – The map projection. If set, this takes precedence over the possible kwargs['subplot_kw']['projection']. If unset (None), defaults to ccrs.PlateCarree().

  • natural_earth (bool) – Add the Cartopy Natural Earth ocean, land, lakes, and rivers features.

  • coastlines (bool) – Add coastlines (linewidth applied).

  • states (bool) – Add states/provinces (linewidth applied).

  • counties (bool) – Add US counties (linewidth applied).

  • countries (bool) – Add country borders (linewidth applied).

  • resolution ({‘10m’, ‘50m’, ‘110m’}) – The resolution of the Natural Earth features for coastlines, states, and counties. Higher resolution (e.g., ‘10m’) provides more detail but may be slower to render.

  • extent (array-like) – Set the map extent with [lon_min,lon_max,lat_min,lat_max].

  • figsize (tuple) – Figure size (width, height), passed to plt.subplots(). This takes precedence over the possible kwargs['figsize'].

  • linewidth (float) – Line width for coastlines, states, counties, and countries.

  • return_fig (bool) – Return the figure and axes objects. By default (False), just the axes object is returned.

  • **kwargs – Arguments to pass to plt.subplots().

Returns:

By default, returns just the ax (cartopy.mpl.geoaxes.GeoAxes instance). If return_fig is true, returns a tuple of (fig, ax) where fig is the matplotlib Figure instance and ax is the GeoAxes instance.

Return type:

matplotlib.axes.Axes or tuple

Notes

The ‘10m’ resolution provides the most detailed features but can be slow for large or global maps. ‘50m’ is a good compromise for regional maps, while ‘110m’ works well for global views.

Examples

>>> # Create a simple map with coastlines
>>> ax = draw_map(coastlines=True, resolution='50m')

>>> # Create a detailed US map with states and counties
>>> ax = draw_map(
...     crs=ccrs.AlbersEqualArea(central_longitude=-95),
...     states=True,
...     counties=True,
...     resolution='10m',
...     extent=[-125, -65, 25, 50]
... )