bolides.BolideDataFrame.plot_density#
- BolideDataFrame.plot_density(crs=None, bandwidth=5, coastlines=True, style='ggplot', boundary=None, boundary_style={}, kde_params={}, lat_resolution=100, lon_resolution=50, n_levels=100, figsize=(8, 8), **kwargs)[source]#
Plot bolide detection density.
Density is computed using scikit-learn’s
KernelDensityusing the haversine distance metric (as the data is in longitude and latitude) and gaussian kernel by default. It is then gridded, projected, and plotted.- Parameters
- crs
CRS The map projection to use. Refer to https://scitools.org.uk/cartopy/docs/latest/reference/projections.html.
- bandwidthfloat
The bandwidth of the Kernel Density Estimator, in degrees.
- boundarystr or list of str
The boundaries to plot and clip the density by. Refer to
get_boundary.- n_levelsint
Number of discrete density levels to plot.
- lat_resolution, lon_resolutionints
The number of discrete latitude and longitude levels when gridding the density.
- **kwargs
Keyword arguments passed through to
contourf.
- crs
- Returns
- fig
figure - ax
GeoAxesSubplot
- fig
- Other Parameters
- coastlinesbool
Whether or not to draw coastlines.
- stylestr
The matplotlib style to use. Refer to https://matplotlib.org/stable/gallery/style_sheets/style_sheets_reference.html
- boundary_styledict
The kwargs to use when plotting the boundary. Refer to
add_geometries.- kde_paramsdict
The kwargs to pass to
KernelDensity. Note that ‘metric’ is not allowed to be specified, as haversine is the only valid metric.- figsizetuple
The size (width, height) of the plotted figure.