correlated_fields.py 3.31 KB
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# 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
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# 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 <http://www.gnu.org/licenses/>.
#
# Copyright(C) 2013-2018 Max-Planck-Society
#
# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik
# and financially supported by the Studienstiftung des deutschen Volkes.

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from __future__ import absolute_import, division, print_function
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from ..compat import *
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from ..domain_tuple import DomainTuple
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from ..multi_field import MultiField
from ..multi_domain import MultiDomain
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from ..operators.domain_distributor import DomainDistributor
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from ..operators.harmonic_operators import HarmonicTransformOperator
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from ..operators.power_distributor import PowerDistributor
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from ..operators.operator import Operator
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class CorrelatedField(Operator):
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    '''
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    Class for construction of correlated fields
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    Parameters
    ----------
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    s_space : Field domain
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    amplitude_model : model for correlation structure
    '''
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    def __init__(self, s_space, amplitude_model):
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        h_space = s_space.get_default_codomain()
        self._ht = HarmonicTransformOperator(h_space, s_space)
        p_space = amplitude_model.target[0]
        power_distributor = PowerDistributor(h_space, p_space)
        self._A = power_distributor(amplitude_model)
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        self._domain = MultiDomain.union(
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            (amplitude_model.domain, MultiDomain.make({"xi": h_space})))
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    def apply(self, x):
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        return self._ht(self._A(x)*x["xi"])
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# def make_mf_correlated_field(s_space_spatial, s_space_energy,
#                              amplitude_model_spatial, amplitude_model_energy):
#     '''
#     Method for construction of correlated multi-frequency fields
#     '''
#     h_space_spatial = s_space_spatial.get_default_codomain()
#     h_space_energy = s_space_energy.get_default_codomain()
#     h_space = DomainTuple.make((h_space_spatial, h_space_energy))
#     ht1 = HarmonicTransformOperator(h_space, space=0)
#     ht2 = HarmonicTransformOperator(ht1.target, space=1)
#     ht = ht2*ht1
#
#     p_space_spatial = amplitude_model_spatial.value.domain[0]
#     p_space_energy = amplitude_model_energy.value.domain[0]
#
#     pd_spatial = PowerDistributor(h_space, p_space_spatial, 0)
#     pd_energy = PowerDistributor(pd_spatial.domain, p_space_energy, 1)
#     pd = pd_spatial*pd_energy
#
#     dom_distr_spatial = DomainDistributor(pd.domain, 0)
#     dom_distr_energy = DomainDistributor(pd.domain, 1)
#
#     a_spatial = dom_distr_spatial(amplitude_model_spatial)
#     a_energy = dom_distr_energy(amplitude_model_energy)
#     a = a_spatial*a_energy
#     A = pd(a)
#
#     position = MultiField.from_dict(
#         {'xi': Field.from_random('normal', h_space)})
#     xi = Variable(position)['xi']
#     correlated_field_h = A*xi
#     correlated_field = ht(correlated_field_h)
#     return PointwiseExponential(correlated_field)