Commit eccb2cbf authored by Philipp Frank's avatar Philipp Frank

new mf correlated fields with normalized amplitudes and separate variance

parent 2708cfd6
Pipeline #62438 passed with stages
in 6 minutes and 57 seconds
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <>.
# Copyright(C) 2013-2019 Max-Planck-Society
# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
import nifty5 as ift
from functools import reduce
from operator import mul
class FullExpander(ift.LinearOperator):
def __init__(self,target):
self._domain = ift.makeDomain(ift.UnstructuredDomain(1))
self._target = ift.makeDomain(target)
self._capability = self.TIMES | self.ADJOINT_TIMES
def apply(self,x,mode):
x = x.to_global_data()
if mode == self.TIMES:
res = x[0]
res = x.sum()
return ift.full(self._tgt(mode),res)
def CorrelatedFieldNormAmplitude(target, amplitudes,
"""Constructs an operator which turns white Gaussian excitation fields
into a correlated field defined on a DomainTuple with n entries and n
separate correlation structures.
This operator may be used as a model for multi-frequency reconstructions
with a correlation structure in both spatial and energy direction.
target : Domain, DomainTuple or tuple of Domain
Target of the operator. Must contain exactly n spaces.
amplitudes: Opertor, iterable of Operator
Amplitude operator if n = 1 or list of n amplitude operators.
stdmean : float
Prior mean of the overall standart deviation.
stdstd : float
Prior standart deviation of the overall standart deviation.
names : iterable of string
:class:`MultiField` keys for xi-field and std-field.
Correlated field
In NIFTy, non-harmonic RGSpaces are by definition periodic. Therefore
the operator constructed by this method will output a correlated field
with *periodic* boundary conditions. If a non-periodic field is needed,
one needs to combine this operator with a :class:`FieldZeroPadder` or even
two (one for the energy and one for the spatial subdomain)
amps = [amplitudes,] if isinstance(amplitudes,ift.Operator) else amplitudes
tgt = ift.DomainTuple.make(target)
if len(tgt) != len(amps):
raise ValueError
stdmean, stdstd = float(stdmean), float(stdstd)
if stdstd <= 0:
raise ValueError
psp = [[0] for aa in amplitudes]
hsp = ift.DomainTuple.make([tt.get_default_codomain() for tt in tgt])
ht = ift.HarmonicTransformOperator(hsp, target=tgt[0], space=0)
pd = ift.PowerDistributor(hsp, psp[0], 0)
for i in range(1,len(amps)):
ht = ift.HarmonicTransformOperator(,target=tgt[i], space=i) @ ht
pd = pd @ ift.PowerDistributor(pd.domain, psp[i], space = i)
spaces = tuple(range(len(amps)))
a = ift.ContractionOperator(pd.domain, spaces[1:]).adjoint @ amps[0]
for i in range(1,len(amps)):
a = a * (ift.ContractionOperator(pd.domain,
spaces[:i] + spaces[(i+1):]).adjoint @ amps[i])
expander = FullExpander(
fstdstd = ift.full(expander.domain,stdstd)
fstdmean = ift.full(expander.domain,stdmean)
Std = ift.makeOp(fstdstd) @ ift.ducktape(expander.domain, None, names[1])
Std = expander @ (ift.Adder(fstdmean)@Std).exp()
A = pd @ (Std * a)
# For `vol` see comment in `CorrelatedField`
vol = reduce(mul, [sp.scalar_dvol**-0.5 for sp in hsp])
return ht(vol*A*ift.ducktape(hsp, None, names[0]))
if __name__ == '__main__':
import numpy as np
from normalized_amplitude import NormalizedAmplitude
nspecs = 2
a = []
spaces = []
for _ in range(nspecs):
ndim = 2
sspace = ift.RGSpace(
np.linspace(16, 20, num=ndim).astype(,
np.linspace(2.3, 7.99, num=ndim))
hspace = sspace.get_default_codomain()
target = ift.PowerSpace(hspace)
a.append(NormalizedAmplitude(target, 16, 1, 1, -3, 1, 0, 1, 0, 1))
tgt = ift.makeDomain(tuple(spaces))
op = CorrelatedFieldNormAmplitude(tgt,a,0.,1.)
fld = ift.from_random('normal', op.domain)
ift.extra.check_jacobian_consistency(op, fld)
\ No newline at end of file
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