visualize2d

giant.coverage.visualizer:

giant.coverage.visualizer.visualize2d(cov, patches, stat_set='v_count', label=None, reduction_function=<function percent_below_threshold_reducer.<locals>.percent_below_threshold>, fig=None, ax=None, cmap='hot')[source]

This function provides a simplified interface to generate a 2D, lat/lon projected map of the statistics.

For more advanced usage, use this function as a template and use the UpdateableColorScale directly.

Parameters:

  • cov (Coverage) – the coverage object containing the coverage results

  • patches (None | Sequence[Polygon]) – an option list of Polygons to use (if None, they’ll be created for you)

  • stat_set (Literal['v_count', 'd_albedo', 'd_x_slope', 'd_y_slope', 'd_total']) – a string specifying what stat to show

  • label (str | None) – the label to visualize (if labeled analysis was performed)

  • reduction_function (Callable[[ndarray[tuple[Any, ...], dtype[float64]]], float]) – a callabe to reduce all the DOP values for a facet to a single value for display

  • fig (Figure | None) – the matplitlib Figure to add the plot to (if None a new figure will be created)

  • ax (Axes | None) – the matplitlib Axes to add the plot to (if None a new Axes will be created)

  • cmap (str) – The color map to use to color the results.

Returns:

A UpdateableColorScale object set for display

Return type:

UpdateableColorScale