Function plot_predictions_at_points

utils/plot_results.py:69–126

convenience function to plot a scatter plot of values at lonlats

(spatialencoder, 
                               lonlats, 
                               #degrees_per_pixel = 1,
                               title=None, 
                               show=True, 
                               savepath=None, 
                               class_idx=None,
                               plot_kwargs={},
                               lonlatscrs="4326",
                               plot_crs="4326",
                               )

        fig.savefig(savepath, transparent=True, bbox_inches="tight", pad_inches=0)

def plot_predictions_at_points(spatialencoder, 
                               lonlats, 
                               #degrees_per_pixel = 1,
                               title=None, 
                               show=True, 
                               savepath=None, 
                               class_idx=None,
                               plot_kwargs={},
                               lonlatscrs="4326",
                               plot_crs="4326",
                               ):
    """
    convenience function to plot a scatter plot of values at lonlats
    """
    device = spatialencoder.device

    lons, lats = lonlats[0], lonlats[1]

    # ij indexing to xy indexing
    lons, lats = lons.T, lats.T

    lonlats = torch.Tensor(lonlats)

    with torch.no_grad():
        if spatialencoder.regression:
            Y = spatialencoder(lonlats)
        else:
            Y = torch.sigmoid(spatialencoder(lonlats))

    if class_idx is not None:
        Y = Y[:, class_idx].unsqueeze(-1)

    # if not binary show predictions instead of probabilities
    if not Y.size(-1) == 1:
        y = Y.argmax(-1)
    else:
        y = Y

    # geopandas dataframe of points
    df = pd.DataFrame(lonlats, columns=['longitude', 'latitude'])
    gdf = gpd.GeoDataFrame(df, geometry=gpd.points_from_xy(df.longitude, df.latitude), crs=lonlatscrs)
    # add predictions
    gdf['y'] = y
    
    if plot_crs != lonlatscrs:
        plot_gdf = gdf.to_crs(epsg=plot_crs) 
    else:
        plot_gdf = gdf
    
    fig = scatter_plot_gdf(plot_gdf, plot_key='y', plot_kwargs=plot_kwargs, title=title)

    if show or savepath is None:
        plt.show()

    if savepath is not None:
        os.makedirs(os.path.dirname(savepath), exist_ok=True)
        plt.tight_layout()
        fig.savefig(savepath, transparent=True, bbox_inches="tight", pad_inches=0)