Source code for nifty7.operators.normal_operators

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# Copyright(C) 2013-2020 Max-Planck-Society
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# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.

import numpy as np

from ..domain_tuple import DomainTuple
from ..domains.unstructured_domain import UnstructuredDomain
from ..operators.adder import Adder
from ..operators.diagonal_operator import DiagonalOperator
from ..operators.simple_linear_operators import ducktape
from ..sugar import makeField
from ..utilities import lognormal_moments, value_reshaper


[docs]def NormalTransform(mean, sigma, key, N_copies=0): """Opchain that transforms standard normally distributed values to normally distributed values with given mean and standard deviation. Parameters ---------- mean : float Mean of the field sigma : float Standard deviation of the field key : string Name of the operators domain (Multidomain) N_copies : integer If == 0, target will be a scalar field. If >= 1, target will be an :class:`~nifty7.domains.unstructured_domain.UnstructuredDomain`. """ if N_copies == 0: domain = DomainTuple.scalar_domain() mean, sigma = np.asfarray(mean), np.asfarray(sigma) mean_adder = Adder(makeField(domain, mean)) return mean_adder @ (sigma * ducktape(domain, None, key)) domain = UnstructuredDomain(N_copies) mean, sigma = (value_reshaper(param, N_copies) for param in (mean, sigma)) mean_adder = Adder(makeField(domain, mean)) sigma_op = DiagonalOperator(makeField(domain, sigma)) return mean_adder @ sigma_op @ ducktape(domain, None, key)
[docs]def LognormalTransform(mean, sigma, key, N_copies): """Opchain that transforms standard normally distributed values to log-normally distributed values with given mean and standard deviation. Parameters ---------- mean : float Mean of the field sigma : float Standard deviation of the field key : string Name of the domain N_copies : integer If == 0, target will be a scalar field. If >= 1, target will be an :class:`~nifty7.domains.unstructured_domain.UnstructuredDomain`. """ logmean, logsigma = lognormal_moments(mean, sigma, N_copies) return NormalTransform(logmean, logsigma, key, N_copies).ptw("exp")