Maps.set_shape

class eomaps.eomaps.Maps.set_shape(m)

Set the plot-shape to represent the data-points.

By default, β€œellipses” is used for datasets smaller than 500k pixels and shading with β€œshade_raster” is used for larger datasets (if datashader is installed).

Possible shapes are: (check the individual docs for details!)

  • Projected ellipses

>>> m.set_shape.ellipses(radius, radius_crs)

  • Projected rectangles

>>> m.set_shape.rectangles(radius, radius_crs, mesh)

  • Projected geodetic circles

>>> m.set_shape.geod_circles(radius)

  • Voronoi diagram

>>> m.set_shape.voronoi_diagram(masked, mask_radius)

  • Delaunay triangulation

>>> m.set_shape.delaunay_triangulation(masked, mask_radius, mask_radius_crs, flat)

  • Point-based shading

>>> m.set_shape.shade_points(aggregator, shade_hook, agg_hook)

  • Raster-based shading

>>> m.set_shape.delaunay_triangulation(aggregator, shade_hook, agg_hook)
_radius_estimation_range

The number of datapoints to use for estimating the radius of a shape. (only relevant if the radius is not specified explicitly.) The default is 100000

Type:

int

Members

contour

Draw a contour-plot of the data.

delaunay_triangulation

Draw a Delaunay-Triangulation of the data.

ellipses

Draw projected ellipses with dimensions defined in units of a given crs.

geod_circles

Draw geodesic circles with a radius defined in meters.

hexbin

Draw a 2D hexagonal binning plot of the data.

raster

Draw the data as a rectangular raster (>> usable for very large datasets!)

rectangles

Draw projected rectangles with fixed dimensions (and possibly curved edges).

scatter_points

Draw each datapoint as a shape with a size defined in points**2.

shade_points

Shade the data as infinitesimal points (>> usable for very large datasets!).

shade_raster

Shade the data as a rectangular raster (>> usable for very large datasets!).

spherical_voronoi_diagram

Draw a Spherical Voronoi-Diagram of the data.

voronoi_diagram

Draw a Voronoi-Diagram of the data.