log_rg_space.py 4.85 KB
Newer Older
Martin Reinecke's avatar
Martin Reinecke committed
1 2 3 4 5 6 7 8 9 10 11 12 13
# 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/>.
#
14
# Copyright(C) 2013-2019 Max-Planck-Society
Martin Reinecke's avatar
Martin Reinecke committed
15
#
16
# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
Philipp Arras's avatar
Philipp Arras committed
17

Martin Reinecke's avatar
Martin Reinecke committed
18
from functools import reduce
Philipp Arras's avatar
Philipp Arras committed
19

20
import numpy as np
Philipp Arras's avatar
Philipp Arras committed
21

22 23 24 25 26
from ..field import Field
from .structured_domain import StructuredDomain


class LogRGSpace(StructuredDomain):
Philipp Arras's avatar
Docs  
Philipp Arras committed
27
    '''Represents a logarithmic Cartesian grid.
28 29 30 31 32 33

    Parameters
    ----------
    shape : int or tuple of int
        Number of grid points or numbers of gridpoints along each axis.
    bindistances : float or tuple of float
Philipp Frank's avatar
docs  
Philipp Frank committed
34 35
        Logarithmic distance between two grid points along each axis.
        Equidistant spacing of bins on logarithmic scale is assumed.
36
    t_0 : float or tuple of float
Philipp Arras's avatar
Docs  
Philipp Arras committed
37
        Coordinate of pixel ndim*(1,).
38 39
    harmonic : bool, optional
        Whether the space represents a grid in position or harmonic space.
Philipp Arras's avatar
Philipp Arras committed
40
        Default: False.
Philipp Arras's avatar
Docs  
Philipp Arras committed
41
    '''
42 43 44 45 46 47 48 49 50 51 52
    _needed_for_hash = ['_shape', '_bindistances', '_t_0', '_harmonic']

    def __init__(self, shape, bindistances, t_0, harmonic=False):
        self._harmonic = bool(harmonic)

        if np.isscalar(shape):
            shape = (shape,)
        self._shape = tuple(int(i) for i in shape)

        self._bindistances = tuple(bindistances)
        self._t_0 = tuple(t_0)
53 54
        if min(self._bindistances) <= 0:
            raise ValueError('Non-positive bindistances encountered')
55

56 57
        self._dim = int(reduce(lambda x, y: x*y, self._shape))
        self._dvol = float(reduce(lambda x, y: x*y, self._bindistances))
58 59 60 61 62 63 64 65 66

    @property
    def harmonic(self):
        return self._harmonic

    @property
    def shape(self):
        return self._shape

Martin Reinecke's avatar
bug fix  
Martin Reinecke committed
67
    @property
68 69 70 71 72 73 74 75 76 77 78 79 80
    def scalar_dvol(self):
        return self._dvol

    @property
    def bindistances(self):
        return np.array(self._bindistances)

    @property
    def size(self):
        return np.prod(self._shape)

    @property
    def t_0(self):
Philipp Arras's avatar
Docs  
Philipp Arras committed
81
        """np.ndarray : array of coordinates of pixel ndim*(1,)."""
82 83 84
        return np.array(self._t_0)

    def __repr__(self):
85 86
        return ("LogRGSpace(shape={}, bindistances={}, t_0={}, harmonic={})".format(
            self.shape, self.bindistances, self.t_0, self.harmonic))
87 88

    def get_default_codomain(self):
Philipp Arras's avatar
Docs  
Philipp Arras committed
89 90 91 92 93 94 95
        """Returns a :class:`LogRGSpace` object representing the (position or
        harmonic) partner domain of `self`, depending on `self.harmonic`. The
        `bindistances` are transformed and `t_0` stays the same.

        Returns
        -------
        LogRGSpace
Martin Reinecke's avatar
typos  
Martin Reinecke committed
96
            The partner domain
Philipp Arras's avatar
Docs  
Philipp Arras committed
97
        """
98
        codomain_bindistances = 1./(self.bindistances*self.shape)
Philipp Haim's avatar
Philipp Haim committed
99
        return LogRGSpace(self.shape, codomain_bindistances, self._t_0, not self.harmonic)
100 101

    def get_k_length_array(self):
Philipp Arras's avatar
Docs  
Philipp Arras committed
102
        """Generates array of distances to origin of the space.
Philipp Frank's avatar
docs  
Philipp Frank committed
103 104 105

        Returns
        -------
Philipp Arras's avatar
Docs  
Philipp Arras committed
106 107 108 109
        numpy.ndarray
            Distances to origin of the space. If any index of the array is
            zero then the distance is np.nan if self.harmonic True.
            The dtype is float64, the shape is `self.shape`.
Philipp Frank's avatar
docs  
Philipp Frank committed
110 111 112

        Raises
        ------
Philipp Arras's avatar
Docs  
Philipp Arras committed
113 114
        NotImplementedError
            If `self.harmonic` is False.
Philipp Frank's avatar
docs  
Philipp Frank committed
115
        """
116 117 118 119 120 121
        if not self.harmonic:
            raise NotImplementedError
        ks = self.get_k_array()
        return Field.from_global_data(self, np.linalg.norm(ks, axis=0))

    def get_k_array(self):
Philipp Arras's avatar
Docs  
Philipp Arras committed
122
        """Generates coordinates of the space.
Philipp Frank's avatar
docs  
Philipp Frank committed
123 124 125

        Returns
        -------
Philipp Arras's avatar
Docs  
Philipp Arras committed
126 127 128 129 130
        numpy.ndarray
            Coordinates of the space. If one index of the array is zero the
            corresponding coordinate is -np.inf (np.nan) if self.harmonic is
            False (True).
            The dtype is float64 and shape: `(len(self.shape),) + self.shape`.
Philipp Frank's avatar
docs  
Philipp Frank committed
131
        """
132 133 134 135 136
        ndim = len(self.shape)
        k_array = np.zeros((ndim,) + self.shape)
        dist = self.bindistances
        for i in range(ndim):
            ks = np.zeros(self.shape[i])
Martin Reinecke's avatar
Martin Reinecke committed
137 138
            ks[1:] = np.minimum(self.shape[i] - 1 - np.arange(self.shape[i]-1),
                                np.arange(self.shape[i]-1)) * dist[i]
139 140 141 142 143
            if self.harmonic:
                ks[0] = np.nan
            else:
                ks[0] = -np.inf
                ks[1:] += self.t_0[i]
Martin Reinecke's avatar
Martin Reinecke committed
144 145
            k_array[i] += ks.reshape((1,)*i + (self.shape[i],)
                                     + (1,)*(ndim-i-1))
146
        return k_array