correlated_fields.py 2.74 KB
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from __future__ import absolute_import, division, print_function
from ..compat import *
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from ..operators.fft_operator import FFTOperator
from ..field import Field
from ..multi.multi_field import MultiField
from ..models.local_nonlinearity import PointwiseExponential
from ..operators.power_distributor import PowerDistributor
from ..models.variable import Variable
from ..domain_tuple import DomainTuple
from ..operators.domain_distributor import DomainDistributor
from ..operators.harmonic_transform_operator \
    import HarmonicTransformOperator

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def make_correlated_field(s_space, amplitude_model):
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    '''
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    Method 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
    '''
    h_space = s_space.get_default_codomain()
    ht = FFTOperator(h_space, s_space)
    p_space = amplitude_model.value.domain[0]
    power_distributor = PowerDistributor(h_space, p_space)
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    position = MultiField.from_dict({
        'xi': Field.from_random('normal', h_space),
        'tau': amplitude_model.position['tau'],
        'phi': amplitude_model.position['phi']})
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    xi = Variable(position)['xi']
    A = power_distributor(amplitude_model)
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    correlated_field_h = A * xi
    correlated_field = ht(correlated_field_h)
    internals = {'correlated_field_h': correlated_field_h,
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                 'power_distributor': power_distributor,
                 'ht': ht}
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    return correlated_field, internals
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def make_mf_correlated_field(s_space_spatial, s_space_energy,
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                             amplitude_model_spatial, amplitude_model_energy):
    '''
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    Method for construction of correlated multi-frequency fields
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    '''
    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_0 = DomainDistributor(pd.domain, 0)
    dom_distr_1 = DomainDistributor(pd.domain, 1)
    a_spatial = dom_distr_1(amplitude_model_spatial)
    a_energy = dom_distr_0(amplitude_model_energy)
    a = a_spatial*a_energy
    A = pd(a)

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    position = MultiField.from_dict({'xi': Field.from_random('normal', h_space)})
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    xi = Variable(position)['xi']
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    correlated_field_h = A*xi
    correlated_field = ht(correlated_field_h)
    return PointwiseExponential(correlated_field)