huracanpy.calc.density

huracanpy.calc.density(lon, lat, method='histogram', bin_size=5, lon_range=None, lat_range=(-90, 90), crop=False, spherical=False, function_kws=None, **kwargs)

Function to compute the track density, based on a simple 2D histogram.

Parameters:

• lon (array_like) – longitude series

• lat (array_like) – latitude series

• method (str, default="histogram") – The method used to calculate the density, currently “histogram” or “kde”, which gives a 2d histogram using np.histogram2d

• bin_size (int or float, default=5) – When using histogram, defines the size (in degrees) of the bins.

• lon_range (tuple, default) – The maximum and minimum longitude to calculate the density over. If None, then it is set to global: (-180, 180) or (0, 360) depending on the input data

• lat_range (tuple, default=(-90, 90)) – The maximum and minimum latitude to calculate the density over.

• crop (bool, default=False) – If True crop the result to remove any outer bounds that only have zero density

• spherical (bool, default=False) – Account for the spherical Earth

• function_kws (dict) –

  Keyword arguments passed to the function used for calculating density

  • If method=”histogram”, numpy.histogram2d()

  • If method=”kde” and spherical=`True`, sklearn.neighbors.KernelDensity. Note that the bandwidth argument is set to “scott” rather than the default of 1.0

  • If method=”kde” and spherical=`False`, scipy.stats.gaussian_kde

• **kwargs – Alternative way to specify function_kws

Raises:

NotImplementedError – If method given is not ‘histogram’ or ‘kde’

Returns:

Track density as a 2D map.

Return type:

xarray.DataArray