smooth_sky.py 2.59 KB
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def make_smooth_sky_model(s_space, amplitude_model):
    '''
    Method for construction of correlated sky model

    Parameters
    ----------
    s_space : domain of sky model

    amplitude_model : model for correlation structure
    '''
    from .. import (FFTOperator, Field, MultiField, PointwiseExponential,
                    PowerDistributor, Variable)
    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)
    position = {}
    position['xi'] = Field.from_random('normal', h_space)
    position['tau'] = amplitude_model.position['tau']
    position['phi'] = amplitude_model.position['phi']
    position = MultiField(position)

    xi = Variable(position)['xi']
    A = power_distributor(amplitude_model)
    logsky_h = A * xi
    logsky = ht(logsky_h)
    internals = {'logsky_h': logsky_h,
                 'power_distributor': power_distributor,
                 'ht': ht}
    return PointwiseExponential(logsky), internals


def make_smooth_mf_sky_model(s_space_spatial, s_space_energy,
                             amplitude_model_spatial, amplitude_model_energy):
    '''
    Method for construction of correlated sky model

    Parameters
    ----------
    s_space : domain of sky model

    amplitude_model : model for correlation structure
    '''
    from .. import (DomainTuple, Field, HarmonicTransformOperator, MultiField,
                    PointwiseExponential, PowerDistributor, Variable)
    from ..linear_operators import DomainDistributor
    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)

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