hp_space.py 6.33 KB
Newer Older
csongor's avatar
csongor committed
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
# NIFTY (Numerical Information Field Theory) has been developed at the
# Max-Planck-Institute for Astrophysics.
#
# Copyright (C) 2015 Max-Planck-Society
#
# Author: Marco Selig
# Project homepage: <http://www.mpa-garching.mpg.de/ift/nifty/>
#
# 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/>.

"""
    ..                  __   ____   __
    ..                /__/ /   _/ /  /_
    ..      __ ___    __  /  /_  /   _/  __   __
    ..    /   _   | /  / /   _/ /  /   /  / /  /
    ..   /  / /  / /  / /  /   /  /_  /  /_/  /
    ..  /__/ /__/ /__/ /__/    \___/  \___   /  lm
    ..                               /______/

    NIFTY submodule for grids on the two-sphere.

"""
from __future__ import division

import numpy as np
37

38
import d2o
39
from keepers import Versionable
40

41
from nifty.spaces.space import Space
42
from nifty.config import nifty_configuration as gc, \
csongor's avatar
csongor committed
43
44
45
46
                         dependency_injector as gdi

hp = gdi.get('healpy')

47

48
class HPSpace(Versionable, Space):
csongor's avatar
csongor committed
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
    """
        ..        __
        ..      /  /
        ..     /  /___    ______
        ..    /   _   | /   _   |
        ..   /  / /  / /  /_/  /
        ..  /__/ /__/ /   ____/  space class
        ..           /__/

        NIFTY subclass for HEALPix discretizations of the two-sphere [#]_.

        Parameters
        ----------
        nside : int
            Resolution parameter for the HEALPix discretization, resulting in
            ``12*nside**2`` pixels.

        See Also
        --------
        gl_space : A class for the Gauss-Legendre discretization of the
            sphere [#]_.
        lm_space : A class for spherical harmonic components.

        Notes
        -----
        Only powers of two are allowed for `nside`.

        References
        ----------
        .. [#] 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.
        .. [#] M. Reinecke and D. Sverre Seljebotn, 2013, "Libsharp - spherical
               harmonic transforms revisited";
               `arXiv:1303.4945 <http://www.arxiv.org/abs/1303.4945>`_

        Attributes
        ----------
        para : numpy.ndarray
            Array containing the number `nside`.
        dtype : numpy.dtype
            Data type of the field values, which is always numpy.float64.
        discrete : bool
            Whether or not the underlying space is discrete, always ``False``
            for spherical spaces.
        vol : numpy.ndarray
            An array with one element containing the pixel size.
    """

98
99
    # ---Overwritten properties and methods---

100
    def __init__(self, nside=2, dtype=np.dtype('float')):
csongor's avatar
csongor committed
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
        """
            Sets the attributes for a hp_space class instance.

            Parameters
            ----------
            nside : int
                Resolution parameter for the HEALPix discretization, resulting
                in ``12*nside**2`` pixels.

            Returns
            -------
            None

            Raises
            ------
            ImportError
                If the healpy module is not available.
            ValueError
                If input `nside` is invaild.

        """
        # check imports
        if not gc['use_healpy']:
124
            raise ImportError("healpy not available or not loaded.")
csongor's avatar
csongor committed
125

126
        super(HPSpace, self).__init__(dtype)
csongor's avatar
csongor committed
127

128
        self._nside = self._parse_nside(nside)
csongor's avatar
csongor committed
129

130
131
132
133
134
    # ---Mandatory properties and methods---

    @property
    def harmonic(self):
        return False
csongor's avatar
csongor committed
135
136
137

    @property
    def shape(self):
138
        return (np.int(12 * self.nside ** 2),)
csongor's avatar
csongor committed
139
140

    @property
Jait Dixit's avatar
Jait Dixit committed
141
    def dim(self):
142
        return np.int(12 * self.nside ** 2)
csongor's avatar
csongor committed
143

144
145
146
    @property
    def total_volume(self):
        return 4 * np.pi
147

148
149
150
151
    def copy(self):
        return self.__class__(nside=self.nside,
                              dtype=self.dtype)

152
    def weight(self, x, power=1, axes=None, inplace=False):
153
        weight = ((4*np.pi) / (12 * self.nside**2)) ** power
154
155
156
157
158
159
160
161

        if inplace:
            x *= weight
            result_x = x
        else:
            result_x = x * weight

        return result_x
162

163
    def get_distance_array(self, distribution_strategy):
theos's avatar
theos committed
164
165
166
167
168
169
170
171
172
173
174
        """
        Calculates distance from center to all the points on the sphere

        Parameters
        ----------
        distribution_strategy: Result d2o's distribution strategy

        Returns
        -------
        dists: distributed_data_object
        """
175
        dists = d2o.arange(
176
            start=0, stop=self.shape[0],
theos's avatar
theos committed
177
178
179
            distribution_strategy=distribution_strategy
        )

180
181
182
        # translate distances to 3D unit vectors on a sphere,
        # extract the first entry (simulates the scalar product with (1,0,0))
        # and apply arccos
theos's avatar
theos committed
183
        dists = dists.apply_scalar_function(
184
185
                    lambda z: np.arccos(hp.pix2vec(self.nside, z)[0]),
                    dtype=np.float)
theos's avatar
theos committed
186
187
188

        return dists

189
    def get_fft_smoothing_kernel_function(self, sigma):
Jait Dixit's avatar
Jait Dixit committed
190
        if sigma is None:
191
            sigma = np.sqrt(2) * np.pi
Jait Dixit's avatar
Jait Dixit committed
192
193

        return lambda x: np.exp((-0.5 * x**2) / sigma**2)
theos's avatar
theos committed
194

195
196
197
198
199
200
201
202
203
    # ---Added properties and methods---

    @property
    def nside(self):
        return self._nside

    def _parse_nside(self, nside):
        nside = int(nside)
        if nside & (nside - 1) != 0 or nside < 2:
204
205
            raise ValueError(
                "nside must be positive and a multiple of 2.")
206
        return nside
207
208
209
210

    # ---Serialization---

    def _to_hdf5(self, hdf5_group):
Jait Dixit's avatar
Jait Dixit committed
211
        hdf5_group['nside'] = self.nside
212
        hdf5_group['dtype'] = self.dtype.name
213
214
215
216
217
        return None

    @classmethod
    def _from_hdf5(cls, hdf5_group, loopback_get):
        result = cls(
Jait Dixit's avatar
Jait Dixit committed
218
            nside=hdf5_group['nside'][()],
219
            dtype=np.dtype(hdf5_group['dtype'][()])
Jait Dixit's avatar
Jait Dixit committed
220
            )
221
        return result