gstools.transform

GStools subpackage providing transformations to post-process normal fields.

Wrapper

apply(fld, method[, field, store, process])

Apply field transformation.

Field Transformations

binary(fld[, divide, upper, lower, field, ...])	Binary transformation.
discrete(fld, values[, thresholds, field, ...])	Discrete transformation.
boxcox(fld[, lmbda, shift, field, store, ...])	(Inverse) Box-Cox transformation to denormalize data.
zinnharvey(fld[, conn, field, store, ...])	Zinn and Harvey transformation to connect low or high values.
normal_force_moments(fld[, field, store, ...])	Force moments of a normal distributed field.
normal_to_lognormal(fld[, field, store, ...])	Transform normal distribution to log-normal distribution.
normal_to_uniform(fld[, low, high, field, ...])	Transform normal distribution to uniform distribution on [0, 1].
normal_to_arcsin(fld[, a, b, field, store, ...])	Transform normal distribution to the bimodal arcsin distribution.
normal_to_uquad(fld[, a, b, field, store, ...])	Transform normal distribution to U-quadratic distribution.
apply_function(fld, function[, field, ...])	Apply function as field transformation.

Array Transformations

array_discrete(field, values[, thresholds, ...])	Discrete transformation.
array_boxcox(field[, lmbda, shift])	(Inverse) Box-Cox transformation to denormalize data.
array_zinnharvey(field[, conn, mean, var])	Zinn and Harvey transformation to connect low or high values.
array_force_moments(field[, mean, var])	Force moments of a normal distributed field.
array_to_lognormal(field)	Transform normal distribution to log-normal distribution.
array_to_uniform(field[, mean, var, low, high])	Transform normal distribution to uniform distribution on [low, high].
array_to_arcsin(field[, mean, var, a, b])	Transform normal distribution to arcsin distribution.
array_to_uquad(field[, mean, var, a, b])	Transform normal distribution to U-quadratic distribution.

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