power_space.py 8.38 KB
Newer Older
1
2
3
4
5
6
7
8
9
10
11
12
# 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/>.
Theo Steininger's avatar
Theo Steininger committed
13
14
15
16
17
#
# Copyright(C) 2013-2017 Max-Planck-Society
#
# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik
# and financially supported by the Studienstiftung des deutschen Volkes.
theos's avatar
theos committed
18

theos's avatar
theos committed
19
import numpy as np
Martin Reinecke's avatar
Martin Reinecke committed
20
from .space import Space
Martin Reinecke's avatar
Martin Reinecke committed
21
from functools import reduce
Martin Reinecke's avatar
Martin Reinecke committed
22
from .. import dobj
theos's avatar
theos committed
23
24


Theo Steininger's avatar
Theo Steininger committed
25
class PowerSpace(Space):
Theo Steininger's avatar
Theo Steininger committed
26
27
28
29
30
31
    """ NIFTY class for spaces of power spectra.

    Parameters
    ----------
    harmonic_partner : Space
        The harmonic Space of which this is the power space.
Martin Reinecke's avatar
Martin Reinecke committed
32
33
34
35
36
37
38
39
40
41
42
43
    binbounds: None, or tuple/array/list of float
        if None:
            There will be as many bins as there are distinct k-vector lengths
            in the harmonic partner space.
            The "binbounds" property of the PowerSpace will also be None.

        else:
            the bin bounds requested for this PowerSpace. The array
            must be sorted and strictly ascending. The first entry is the right
            boundary of the first bin, and the last entry is the left boundary
            of the last bin, i.e. thee will be len(binbounds)+1 bins in total,
            with the first and last bins reaching to -+infinity, respectively.
Theo Steininger's avatar
Theo Steininger committed
44
45
46
47
        (default : None)

    Attributes
    ----------
Martin Reinecke's avatar
Martin Reinecke committed
48
    pindex : data object
49
50
        This holds the information which pixel of the harmonic partner gets
        mapped to which power bin
Martin Reinecke's avatar
Martin Reinecke committed
51
    k_lengths : numpy.ndarray
52
53
54
55
        Sorted array of all k-modes.
    dim : np.int
        Total number of dimensionality, i.e. the number of pixels.
    harmonic : bool
56
        Always False for this space.
57
58
    shape : tuple of np.ints
        The shape of the space's data array.
Martin Reinecke's avatar
Martin Reinecke committed
59
60
61
    binbounds : tuple or None
        Boundaries between the power spectrum bins; None is used to indicate
        natural binning
Theo Steininger's avatar
Theo Steininger committed
62
63
64
65
66
67
68

    Notes
    -----
    A power space is the result of a projection of a harmonic space where
    k-modes of equal length get mapped to one power index.

    """
69

70
71
    _powerIndexCache = {}

72
73
    # ---Overwritten properties and methods---

Martin Reinecke's avatar
Martin Reinecke committed
74
    @staticmethod
Martin Reinecke's avatar
PEP8    
Martin Reinecke committed
75
    def linear_binbounds(nbin, first_bound, last_bound):
Martin Reinecke's avatar
Martin Reinecke committed
76
77
78
79
80
81
82
83
84
85
86
87
        """
        nbin: integer
            the number of bins
        first_bound, last_bound: float
            the k values for the right boundary of the first bin and the left
            boundary of the last bin, respectively. They are given in length
            units of the harmonic partner space.
        This will produce a binbounds array with nbin-1 entries with
        binbounds[0]=first_bound and binbounds[-1]=last_bound and the remaining
        values equidistantly spaced (in linear scale) between these two.
        """
        nbin = int(nbin)
Martin Reinecke's avatar
PEP8    
Martin Reinecke committed
88
89
        assert nbin >= 3, "nbin must be at least 3"
        return np.linspace(float(first_bound), float(last_bound), nbin-1)
Martin Reinecke's avatar
Martin Reinecke committed
90
91

    @staticmethod
Martin Reinecke's avatar
PEP8    
Martin Reinecke committed
92
    def logarithmic_binbounds(nbin, first_bound, last_bound):
Martin Reinecke's avatar
Martin Reinecke committed
93
94
95
96
97
98
99
100
101
102
103
104
        """
        nbin: integer
            the number of bins
        first_bound, last_bound: float
            the k values for the right boundary of the first bin and the left
            boundary of the last bin, respectively. They are given in length
            units of the harmonic partner space.
        This will produce a binbounds array with nbin-1 entries with
        binbounds[0]=first_bound and binbounds[-1]=last_bound and the remaining
        values equidistantly spaced (in natural logarithmic scale)
        between these two.
        """
Martin Reinecke's avatar
Martin Reinecke committed
105
        nbin = int(nbin)
Martin Reinecke's avatar
PEP8    
Martin Reinecke committed
106
        assert nbin >= 3, "nbin must be at least 3"
Martin Reinecke's avatar
Martin Reinecke committed
107
108
109
        return np.logspace(np.log(float(first_bound)),
                           np.log(float(last_bound)),
                           nbin-1, base=np.e)
Martin Reinecke's avatar
Martin Reinecke committed
110

111
112
113
114
115
116
117
118
    @staticmethod
    def useful_binbounds(space, logarithmic, nbin=None):
        if not (isinstance(space, Space) and space.harmonic):
            raise ValueError("first argument must be a harmonic space.")
        if logarithmic is None and nbin is None:
            return None
        nbin = None if nbin is None else int(nbin)
        logarithmic = bool(logarithmic)
119
        dists = space.get_unique_k_lengths()
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
        if len(dists) < 3:
            raise ValueError("Space does not have enough unique k lengths")
        lbound = 0.5*(dists[0]+dists[1])
        rbound = 0.5*(dists[-2]+dists[-1])
        dists[0] = lbound
        dists[-1] = rbound
        if logarithmic:
            dists = np.log(dists)
        binsz_min = np.max(np.diff(dists))
        nbin_max = int((dists[-1]-dists[0])/binsz_min)+2
        if nbin is None:
            nbin = nbin_max
        assert nbin >= 3, "nbin must be at least 3"
        if nbin > nbin_max:
            raise ValueError("nbin is too large")
        if logarithmic:
            return PowerSpace.logarithmic_binbounds(nbin, lbound, rbound)
        else:
            return PowerSpace.linear_binbounds(nbin, lbound, rbound)

Martin Reinecke's avatar
Martin Reinecke committed
140
    def __init__(self, harmonic_partner, binbounds=None):
Martin Reinecke's avatar
Martin Reinecke committed
141
        super(PowerSpace, self).__init__()
142
        self._needed_for_hash += ['_harmonic_partner', '_binbounds']
143

Martin Reinecke's avatar
Martin Reinecke committed
144
145
146
        if not (isinstance(harmonic_partner, Space) and
                harmonic_partner.harmonic):
            raise ValueError("harmonic_partner must be a harmonic space.")
Martin Reinecke's avatar
Martin Reinecke committed
147
148
149
        if harmonic_partner.scalar_dvol() is None:
            raise ValueError("harmonic partner must have "
                             "scalar volume factors")
150
        self._harmonic_partner = harmonic_partner
Martin Reinecke's avatar
Martin Reinecke committed
151
        pdvol = harmonic_partner.scalar_dvol()
152

Martin Reinecke's avatar
Martin Reinecke committed
153
154
        if binbounds is not None:
            binbounds = tuple(binbounds)
155

Martin Reinecke's avatar
Martin Reinecke committed
156
        key = (harmonic_partner, binbounds)
157
        if self._powerIndexCache.get(key) is None:
158
            k_length_array = self.harmonic_partner.get_k_length_array()
159
            temp_pindex = self._compute_pindex(
160
                                harmonic_partner=self.harmonic_partner,
161
                                k_length_array=k_length_array,
Martin Reinecke's avatar
Martin Reinecke committed
162
                                binbounds=binbounds)
Martin Reinecke's avatar
Martin Reinecke committed
163
            temp_rho = dobj.bincount(temp_pindex.ravel())
Martin Reinecke's avatar
PEP8    
Martin Reinecke committed
164
            assert not np.any(temp_rho == 0), "empty bins detected"
Martin Reinecke's avatar
Martin Reinecke committed
165
            temp_k_lengths = np.bincount(temp_pindex.ravel(),
166
                                      weights=k_length_array.ravel()) \
167
                / temp_rho
Martin Reinecke's avatar
Martin Reinecke committed
168
            temp_dvol = temp_rho*pdvol
Martin Reinecke's avatar
Martin Reinecke committed
169
            self._powerIndexCache[key] = (binbounds,
170
                                          temp_pindex,
Martin Reinecke's avatar
Martin Reinecke committed
171
                                          temp_k_lengths,
Martin Reinecke's avatar
Martin Reinecke committed
172
                                          temp_dvol)
173

Martin Reinecke's avatar
Martin Reinecke committed
174
        (self._binbounds, self._pindex, self._k_lengths, self._dvol) = \
175
176
            self._powerIndexCache[key]

177
    @staticmethod
178
    def _compute_pindex(harmonic_partner, k_length_array, binbounds):
179
        if binbounds is None:
180
            tmp = harmonic_partner.get_unique_k_lengths()
181
            binbounds = 0.5*(tmp[:-1]+tmp[1:])
182
        return np.searchsorted(binbounds, k_length_array)
183

184
185
    # ---Mandatory properties and methods---

186
    def __repr__(self):
Martin Reinecke's avatar
stage1    
Martin Reinecke committed
187
188
        return ("PowerSpace(harmonic_partner=%r, binbounds=%r)"
                % (self.harmonic_partner, self._binbounds))
189

190
191
    @property
    def harmonic(self):
192
        return False
193

194
195
    @property
    def shape(self):
Martin Reinecke's avatar
Martin Reinecke committed
196
        return self.k_lengths.shape
197

198
199
200
201
    @property
    def dim(self):
        return self.shape[0]

202
    def scalar_dvol(self):
Martin Reinecke's avatar
Martin Reinecke committed
203
204
205
206
        return None

    def dvol(self):
        return self._dvol
207

208
209
210
    # ---Added properties and methods---

    @property
211
    def harmonic_partner(self):
Theo Steininger's avatar
Theo Steininger committed
212
        """ Returns the Space of which this is the power space.
213
214
        """
        return self._harmonic_partner
215
216

    @property
Martin Reinecke's avatar
Martin Reinecke committed
217
218
    def binbounds(self):
        return self._binbounds
219
220
221

    @property
    def pindex(self):
Martin Reinecke's avatar
Martin Reinecke committed
222
        """ A data object having the shape of the harmonic partner
Theo Steininger's avatar
Theo Steininger committed
223
224
        space containing the indices of the power bin a pixel belongs to.
        """
225
226
227
        return self._pindex

    @property
Martin Reinecke's avatar
Martin Reinecke committed
228
    def k_lengths(self):
Theo Steininger's avatar
Theo Steininger committed
229
230
        """ Sorted array of all k-modes.
        """
Martin Reinecke's avatar
Martin Reinecke committed
231
        return self._k_lengths