dubfi.fluxes.localization¶

Localization utilities.

Added in version 0.1.1.

Changed in version 0.1.2: (renamed some methods)

Attributes¶

`GASPARI_COHN_CUTOFF`	Cutoff scale of `gaspari_cohn()`.
`GASPARI_COHN_GAUSS_CUTOFF`	Cutoff scale of `gaspari_cohn_gauss()`.
`LOCALIZATION_FUNCTIONS`	Access localization functions by (lower case) name.

Classes¶

Localization

Localization class for in-situ observations.

Functions¶

`gaspari_cohn`(x)	Gaspari-Cohn function.
`gaspari_cohn_gauss`(x)	Gaspari-Cohn with scale adjusted to match Gaussian.
`gauss`(x)	Gaussian, \(\exp(-\tfrac{1}{2} x^2)\).

Module Contents¶

dubfi.fluxes.localization.gaspari_cohn(x)¶

Gaspari-Cohn function.

This function has compact support on [-2, 2].

See also

gaspari_cohn_gauss()

Parameters:: x (numpy.ndarray)
Return type:: numpy.ndarray

dubfi.fluxes.localization.GASPARI_COHN_GAUSS_CUTOFF = 3.6514837167011076¶

Cutoff scale of gaspari_cohn_gauss().

gaspari_cohn_gauss(x) == 0 for abs(x) > GASPARI_COHN_GAUSS_CUTOFF.

dubfi.fluxes.localization.gauss(x)¶

Gaussian, \(\exp(-\tfrac{1}{2} x^2)\).

Parameters:: x (numpy.ndarray)
Return type:: numpy.ndarray

dubfi.fluxes.localization.LOCALIZATION_FUNCTIONS¶: Access localization functions by (lower case) name.

class dubfi.fluxes.localization.Localization(func, hscale, vscale, tscale)¶

Localization class for in-situ observations.

Localization object allows creating localization matrices.

Parameters:

func (callable | {"Gauss", "Gaspari-Cohn", "Gaspari-Cohn-scaled"}) – localization function. This must take an array as argument and describe a positive, symmetric function f(x) that decreases monotonically from |x| from f(0)=1 to f(x)=0 (at least asymptotically) for large x. Names for known localization functions are allowed. Note that “Gaspari-Cohn-scaled” is an approximation of a Gaussian with compact support, see gaspari_cohn_gauss().
hscale (float) – horizontal scale in meters
vscale (float) – vertical scale in meters
tscale (np.timedelta64) – temporal scale

classmethod from_config(config)¶

Construct Localization from configuration.

Parameters:: config (dict)

property function¶: Localization function, requires normalized input.

rel_dist_horizontal(lon, lat, lon2=None, lat2=None)¶

Matrix of normalized horizontal distances.

Changed in version 0.1.2: (renamed, added optional variables)

Parameters:

lon (numpy.ndarray)
lat (numpy.ndarray)
lon2 (numpy.ndarray | None)
lat2 (numpy.ndarray | None)

Return type:

numpy.ndarray

weights_spatial(lon, lat, height, lon2=None, lat2=None, height2=None)¶

Spatial weights (localization) matrix.

Changed in version 0.1.2: (added optional variables)

Parameters:

lon (numpy.ndarray)
lat (numpy.ndarray)
height (numpy.ndarray)
lon2 (numpy.ndarray | None)
lat2 (numpy.ndarray | None)
height2 (numpy.ndarray | None)

Return type:

numpy.ndarray

weights_time(time, time2=None)¶

Temporal weights (localization) matrix.

Changed in version 0.1.2: (added optional variables)

Parameters:

time (numpy.ndarray)
time2 (numpy.ndarray | numpy.datetime64 | None)

Return type:

numpy.ndarray

rel_dist_horizontal_unique(lon, lat)¶

Return normalized horizontal distance matrix for unique coordinates.

Returns:

dist (np.ndarray) – distance matrix
indices (np.ndarray) – indices into dist along lon, lat coordinates
.. versionchanged:: 0.1.2 (renamed)

Parameters:

lon (numpy.ndarray)
lat (numpy.ndarray)

Return type:

tuple[numpy.ndarray, numpy.ndarray]

matrix(lon, lat, height, time)¶

Construct localization matrix based on coordinates.

All input arrays must be one-dimensional and aligned.

Parameters:

lon (np.ndarray) – longitude (degrees east)
lat (np.ndarray) – latitude (degrees east)
height (np.ndarray) – vertical coordinate in meters
time (np.ndarray) – time relative to localization time scale with arbitrary offset

Returns:

localization_weights – localization matrix specifying weights between each combination of coordiniates

Return type:

np.ndarray

matrix_sparse(lon, lat, height, time, threshold=1e-05, chunk=500)¶

Construct localization matrix based on coordinates, see matrix().

Parameters:

lon (numpy.ndarray)
lat (numpy.ndarray)
height (numpy.ndarray)
time (numpy.ndarray)
threshold (float)
chunk (int)

Return type:

scipy.sparse.csc_array