gl_space.py 5.4 KB
Newer Older
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
# NIFTy
# Copyright (C) 2017  Theo Steininger
#
# Author: Theo Steininger
#
# 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/>.

csongor's avatar
csongor committed
19
20
from __future__ import division

Jait Dixit's avatar
Jait Dixit committed
21
import itertools
csongor's avatar
csongor committed
22
23
import numpy as np

24
from nifty.spaces.space import Space
25
from nifty.config import dependency_injector as gdi
26

Theo Steininger's avatar
Theo Steininger committed
27
28
29
pyHealpix = gdi.get('pyHealpix')


Theo Steininger's avatar
Theo Steininger committed
30
class GLSpace(Space):
csongor's avatar
csongor committed
31
32
33
34
35
36
37
38
39
40
    """
        ..                 __
        ..               /  /
        ..     ____ __  /  /
        ..   /   _   / /  /
        ..  /  /_/  / /  /_
        ..  \___   /  \___/  space class
        .. /______/

        NIFTY subclass for Gauss-Legendre pixelizations [#]_ of the two-sphere.
41
42
            
        Attributes
csongor's avatar
csongor committed
43
        ----------
44
45
46
47
        dim : np.int
            Total number of dimensionality, i.e. the number of pixels.
        harmonic : bool
            Specifies whether the space is a signal or harmonic space.
csongor's avatar
csongor committed
48
        nlat : int
49
50
            Number of latitudinal bins (or rings) that are used for this
            pixelization.
51
        nlon : int, *optional*
52
53
54
55
56
            Number of longditudinal bins that are used for this pixelization.
        total_volume : np.float
            The total volume of the space.
        shape : tuple of np.ints
            The shape of the space's data array.
csongor's avatar
csongor committed
57

Theo Steininger's avatar
Theo Steininger committed
58
59
60
61
62
63
64
        Raises
        ------
        ValueError
            If input `nlat` or `nlon` is invalid.
        ImportError
            If the pyHealpix module is not available

csongor's avatar
csongor committed
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
        See Also
        --------
        hp_space : A class for the HEALPix discretization of the sphere [#]_.
        lm_space : A class for spherical harmonic components.

        References
        ----------
        .. [#] M. Reinecke and D. Sverre Seljebotn, 2013, "Libsharp - spherical
               harmonic transforms revisited";
               `arXiv:1303.4945 <http://www.arxiv.org/abs/1303.4945>`_
        .. [#] K.M. Gorski et al., 2005, "HEALPix: A Framework for
               High-Resolution Discretization and Fast Analysis of Data
               Distributed on the Sphere", *ApJ* 622..759G.

    """

81
82
    # ---Overwritten properties and methods---

Martin Reinecke's avatar
Martin Reinecke committed
83
    def __init__(self, nlat, nlon=None):
Theo Steininger's avatar
Theo Steininger committed
84
85
86
        if 'pyHealpix' not in gdi:
            raise ImportError(
                "The module pyHealpix is needed but not available.")
87

Martin Reinecke's avatar
Martin Reinecke committed
88
        super(GLSpace, self).__init__()
csongor's avatar
csongor committed
89

90
91
        self._nlat = self._parse_nlat(nlat)
        self._nlon = self._parse_nlon(nlon)
csongor's avatar
csongor committed
92

93
    # ---Mandatory properties and methods---
csongor's avatar
csongor committed
94

95
96
97
    @property
    def harmonic(self):
        return False
csongor's avatar
csongor committed
98
99
100

    @property
    def shape(self):
101
        return (np.int((self.nlat * self.nlon)),)
csongor's avatar
csongor committed
102

103
    @property
104
    def dim(self):
105
        return np.int((self.nlat * self.nlon))
106
107
108
109

    @property
    def total_volume(self):
        return 4 * np.pi
110

111
112
    def copy(self):
        return self.__class__(nlat=self.nlat,
Martin Reinecke's avatar
Martin Reinecke committed
113
                              nlon=self.nlon)
114

Jait Dixit's avatar
Jait Dixit committed
115
    def weight(self, x, power=1, axes=None, inplace=False):
116
117
        nlon = self.nlon
        nlat = self.nlat
Theo Steininger's avatar
Theo Steininger committed
118
        vol = pyHealpix.GL_weights(nlat, nlon) ** power
119
        weight = np.array(list(itertools.chain.from_iterable(
Theo Steininger's avatar
Theo Steininger committed
120
                          itertools.repeat(x, nlon) for x in vol)))
Jait Dixit's avatar
Jait Dixit committed
121
122
123

        if axes is not None:
            # reshape the weight array to match the input shape
124
            new_shape = np.ones(len(x.shape), dtype=np.int)
125
126
            # we know len(axes) is always 1
            new_shape[axes[0]] = len(weight)
Jait Dixit's avatar
Jait Dixit committed
127
128
129
130
131
            weight = weight.reshape(new_shape)

        if inplace:
            x *= weight
            result_x = x
csongor's avatar
csongor committed
132
        else:
Jait Dixit's avatar
Jait Dixit committed
133
            result_x = x * weight
csongor's avatar
csongor committed
134

Jait Dixit's avatar
Jait Dixit committed
135
        return result_x
136

137
    def get_distance_array(self, distribution_strategy):
Theo Steininger's avatar
Theo Steininger committed
138
        raise NotImplementedError
139

140
    def get_fft_smoothing_kernel_function(self, sigma):
Theo Steininger's avatar
Theo Steininger committed
141
        raise NotImplementedError
142

143
144
145
146
    # ---Added properties and methods---

    @property
    def nlat(self):
Theo Steininger's avatar
Theo Steininger committed
147
148
        """ Number of latitudinal bins (or rings) that are used for this
        pixelization.
149
        """
Theo Steininger's avatar
Theo Steininger committed
150

151
152
153
154
        return self._nlat

    @property
    def nlon(self):
Theo Steininger's avatar
Theo Steininger committed
155
        """ Number of longditudinal bins that are used for this pixelization.
156
        """
Theo Steininger's avatar
Theo Steininger committed
157

158
159
160
161
        return self._nlon

    def _parse_nlat(self, nlat):
        nlat = int(nlat)
162
163
164
        if nlat < 1:
            raise ValueError(
                "nlat must be a positive number.")
165
166
167
168
169
170
171
        return nlat

    def _parse_nlon(self, nlon):
        if nlon is None:
            nlon = 2 * self.nlat - 1
        else:
            nlon = int(nlon)
172
173
            if nlon < 1:
                raise ValueError("nlon must be a positive number.")
174
        return nlon
175
176
177
178

    # ---Serialization---

    def _to_hdf5(self, hdf5_group):
Jait Dixit's avatar
Jait Dixit committed
179
180
181
        hdf5_group['nlat'] = self.nlat
        hdf5_group['nlon'] = self.nlon

182
183
184
        return None

    @classmethod
Theo Steininger's avatar
Theo Steininger committed
185
    def _from_hdf5(cls, hdf5_group, repository):
186
        result = cls(
Jait Dixit's avatar
Jait Dixit committed
187
188
189
190
            nlat=hdf5_group['nlat'][()],
            nlon=hdf5_group['nlon'][()],
            )

191
        return result