geocat.comp.spherical.decomposition#
- geocat.comp.spherical.decomposition(data, scale, theta, phi, max_harm=23, chunk_size='auto')#
Calculate the spherical harmonics of a dataset.
- Parameters:
data (
numpy.ndarray
,xarray.DataArray
) – 2-dimensional datasetscale (
numpy.ndarray
,xarray.DataArray
) – 2-dimensional array containing the weighting of each point in the data. This is usually the area of the voronoi cell centered on the corresponding datapoint. thegeocat.comp.spherical.scale_voronoi(theta,phi)
function can provide a scale array.theta (
numpy.ndarray
,xarray.DataArray
) – 2-dimensional array containing the theta (longitude in radians) values for each datapoint in data.phi (
numpy.ndarray
,xarray.DataArray
) – 2-dimensional array containing thetheta
(latitude in radians) values for each datapoint in data.Phi
is zero at the top of the sphere andpi
at the bottom,phi = (lat_degrees-90)*(-1)*pi/180
max_harm (
int
, optional) – The maximum harmonic value for both m and n. The total of harmonics calculated is(max_harm+1)*(max_harm+2)/2
Defaults to 23, for 300 total harmonics.chunk_size (
int
, optional) – The size of each edge of the dask chunks if using xarray.DataArray inputs. Some arrays will be 2d, and others 1d, and the final calculation operates on a 3d array. thus the chunks used in the largest calculation scale atchunk_size^3
A chunk size of 256 is recommended. Defaults to ‘auto’
- Returns:
decomposition (
numpy.ndarray
,xarray.DataArray
) – The spherical harmonic decomposition of the input data