grid_based_searches.py 37.9 KB
Newer Older
Gregory Ashton's avatar
Gregory Ashton committed
1
""" Searches using grid-based methods """
2
from __future__ import division, absolute_import, print_function
Gregory Ashton's avatar
Gregory Ashton committed
3
4
5
6
7

import os
import logging
import itertools
from collections import OrderedDict
Gregory Ashton's avatar
Gregory Ashton committed
8
9
10
import datetime
import getpass
import socket
Gregory Ashton's avatar
Gregory Ashton committed
11
12
13
14

import numpy as np
import matplotlib
import matplotlib.pyplot as plt
15
from scipy.misc import logsumexp
Gregory Ashton's avatar
Gregory Ashton committed
16

17
18
19
import pyfstat.helper_functions as helper_functions
from pyfstat.core import (BaseSearchClass, ComputeFstat,
                          SemiCoherentGlitchSearch, SemiCoherentSearch, tqdm,
20
                          args, read_par)
Gregory Ashton's avatar
Gregory Ashton committed
21
22
import lalpulsar
import lal
Gregory Ashton's avatar
Gregory Ashton committed
23
24
25
26


class GridSearch(BaseSearchClass):
    """ Gridded search using ComputeFstat """
Gregory Ashton's avatar
Gregory Ashton committed
27
28
29
    tex_labels = {'F0': '$f$', 'F1': '$\dot{f}$', 'F2': '$\ddot{f}$',
                  'Alpha': r'$\alpha$', 'Delta': r'$\delta$'}
    tex_labels0 = {'F0': '$-f_0$', 'F1': '$-\dot{f}_0$', 'F2': '$-\ddot{f}_0$',
30
                   'Alpha': r'$-\alpha_0$', 'Delta': r'$-\delta_0$'}
Gregory Ashton's avatar
Gregory Ashton committed
31

Gregory Ashton's avatar
Gregory Ashton committed
32
    @helper_functions.initializer
Gregory Ashton's avatar
Gregory Ashton committed
33
34
35
36
    def __init__(self, label, outdir, sftfilepattern, F0s, F1s, F2s, Alphas,
                 Deltas, tref=None, minStartTime=None, maxStartTime=None,
                 nsegs=1, BSGL=False, minCoverFreq=None, maxCoverFreq=None,
                 detectors=None, SSBprec=None, injectSources=None,
David Keitel's avatar
David Keitel committed
37
                 input_arrays=False, assumeSqrtSX=None,
38
39
                 transientWindowType=None, t0Band=None, tauBand=None,
                 outputTransientFstatMap=False):
Gregory Ashton's avatar
Gregory Ashton committed
40
41
42
43
44
        """
        Parameters
        ----------
        label, outdir: str
            A label and directory to read/write data from/to
45
46
47
        sftfilepattern: str
            Pattern to match SFTs using wildcards (*?) and ranges [0-9];
            mutiple patterns can be given separated by colons.
Gregory Ashton's avatar
Gregory Ashton committed
48
49
        F0s, F1s, F2s, delta_F0s, delta_F1s, tglitchs, Alphas, Deltas: tuple
            Length 3 tuple describing the grid for each parameter, e.g
50
51
            [F0min, F0max, dF0], for a fixed value simply give [F0]. Unless
            input_arrays == True, then these are the values to search at.
Gregory Ashton's avatar
Gregory Ashton committed
52
53
        tref, minStartTime, maxStartTime: int
            GPS seconds of the reference time, start time and end time
54
55
        input_arrays: bool
            if true, use the F0s, F1s, etc as is
David Keitel's avatar
David Keitel committed
56
        transientWindowType: str
Gregory Ashton's avatar
Gregory Ashton committed
57
58
59
60
            If 'rect' or 'exp', compute atoms so that a transient (t0,tau) map
            can later be computed.  ('none' instead of None explicitly calls
            the transient-window function, but with the full range, for
            debugging). Currently only supported for nsegs=1.
David Keitel's avatar
David Keitel committed
61
62
63
64
65
        t0Band, tauBand: int
            if >0, search t0 in (minStartTime,minStartTime+t0Band)
                   and tau in (2*Tsft,2*Tsft+tauBand).
            if =0, only compute CW Fstat with t0=minStartTime,
                   tau=maxStartTime-minStartTime.
66
67
68
        outputTransientFstatMap: bool
            if true, write output files for (t0,tau) Fstat maps
            (one file for each doppler grid point!)
Gregory Ashton's avatar
Gregory Ashton committed
69
70
71
72
73
74

        For all other parameters, see `pyfstat.ComputeFStat` for details
        """

        if os.path.isdir(outdir) is False:
            os.mkdir(outdir)
75
        self.set_out_file()
Gregory Ashton's avatar
Gregory Ashton committed
76
        self.keys = ['_', '_', 'F0', 'F1', 'F2', 'Alpha', 'Delta']
Gregory Ashton's avatar
Gregory Ashton committed
77
78
79
        self.search_keys = [x+'s' for x in self.keys[2:]]
        for k in self.search_keys:
            setattr(self, k, np.atleast_1d(getattr(self, k)))
Gregory Ashton's avatar
Gregory Ashton committed
80
81
82

    def inititate_search_object(self):
        logging.info('Setting up search object')
83
84
        if self.nsegs == 1:
            self.search = ComputeFstat(
85
                tref=self.tref, sftfilepattern=self.sftfilepattern,
86
                minCoverFreq=self.minCoverFreq, maxCoverFreq=self.maxCoverFreq,
David Keitel's avatar
David Keitel committed
87
88
89
                detectors=self.detectors,
                transientWindowType=self.transientWindowType,
                t0Band=self.t0Band, tauBand=self.tauBand,
90
                minStartTime=self.minStartTime, maxStartTime=self.maxStartTime,
91
                BSGL=self.BSGL, SSBprec=self.SSBprec,
92
93
                injectSources=self.injectSources,
                assumeSqrtSX=self.assumeSqrtSX)
94
            self.search.get_det_stat = self.search.get_fullycoherent_twoF
95
96
97
        else:
            self.search = SemiCoherentSearch(
                label=self.label, outdir=self.outdir, tref=self.tref,
98
                nsegs=self.nsegs, sftfilepattern=self.sftfilepattern,
99
100
101
                BSGL=self.BSGL, minStartTime=self.minStartTime,
                maxStartTime=self.maxStartTime, minCoverFreq=self.minCoverFreq,
                maxCoverFreq=self.maxCoverFreq, detectors=self.detectors,
Gregory Ashton's avatar
Gregory Ashton committed
102
                injectSources=self.injectSources)
103
104

            def cut_out_tstart_tend(*vals):
105
                return self.search.get_semicoherent_twoF(*vals[2:])
106
            self.search.get_det_stat = cut_out_tstart_tend
Gregory Ashton's avatar
Gregory Ashton committed
107
108
109
110

    def get_array_from_tuple(self, x):
        if len(x) == 1:
            return np.array(x)
111
        elif len(x) == 3 and self.input_arrays is False:
Gregory Ashton's avatar
Gregory Ashton committed
112
            return np.arange(x[0], x[1], x[2])
Gregory Ashton's avatar
Gregory Ashton committed
113
        else:
Gregory Ashton's avatar
Gregory Ashton committed
114
115
            logging.info('Using tuple as is')
            return np.array(x)
Gregory Ashton's avatar
Gregory Ashton committed
116
117

    def get_input_data_array(self):
Gregory Ashton's avatar
Gregory Ashton committed
118
        logging.info("Generating input data array")
119
        coord_arrays = []
Gregory Ashton's avatar
Gregory Ashton committed
120
121
        for tup in ([self.minStartTime], [self.maxStartTime], self.F0s,
                    self.F1s, self.F2s, self.Alphas, self.Deltas):
122
            coord_arrays.append(self.get_array_from_tuple(tup))
Gregory Ashton's avatar
Gregory Ashton committed
123

124
125
126
127
        input_data = []
        for vals in itertools.product(*coord_arrays):
                input_data.append(vals)
        self.input_data = np.array(input_data)
128
        self.coord_arrays = coord_arrays
Gregory Ashton's avatar
Gregory Ashton committed
129
130
131
132
133

    def check_old_data_is_okay_to_use(self):
        if args.clean:
            return False
        if os.path.isfile(self.out_file) is False:
134
135
136
            logging.info(
                'No old data found in "{:s}", continuing with grid search'
                .format(self.out_file))
Gregory Ashton's avatar
Gregory Ashton committed
137
            return False
138
        if self.sftfilepattern is not None:
139
140
141
142
143
144
            oldest_sft = min([os.path.getmtime(f) for f in
                              self._get_list_of_matching_sfts()])
            if os.path.getmtime(self.out_file) < oldest_sft:
                logging.info('Search output data outdates sft files,'
                             + ' continuing with grid search')
                return False
145

146
        data = np.atleast_2d(np.genfromtxt(self.out_file, delimiter=' '))
147
148
        if np.all(data[:, 0: len(self.coord_arrays)] ==
                  self.input_data[:, 0:len(self.coord_arrays)]):
149
            logging.info(
150
151
                'Old data found in "{:s}" with matching input, no search '
                'performed'.format(self.out_file))
152
153
154
            return data
        else:
            logging.info(
155
156
                'Old data found in "{:s}", input differs, continuing with '
                'grid search'.format(self.out_file))
157
            return False
158
        return False
Gregory Ashton's avatar
Gregory Ashton committed
159
160
161
162
163
164
165
166

    def run(self, return_data=False):
        self.get_input_data_array()
        old_data = self.check_old_data_is_okay_to_use()
        if old_data is not False:
            self.data = old_data
            return

Gregory Ashton's avatar
Gregory Ashton committed
167
168
        if hasattr(self, 'search') is False:
            self.inititate_search_object()
Gregory Ashton's avatar
Gregory Ashton committed
169
170

        data = []
171
        for vals in tqdm(self.input_data):
172
173
174
            detstat = self.search.get_det_stat(*vals)
            windowRange = getattr(self.search, 'windowRange', None)
            FstatMap = getattr(self.search, 'FstatMap', None)
175
            thisCand = list(vals) + [detstat]
Gregory Ashton's avatar
Gregory Ashton committed
176
            if getattr(self, 'transientWindowType', None):
177
178
179
180
181
182
183
184
185
186
                if self.outputTransientFstatMap:
                    tCWfile = os.path.splitext(self.out_file)[0]+'_tCW_%.16f_%.16f_%.16f_%.16g_%.16g.dat' % (vals[2],vals[5],vals[6],vals[3],vals[4]) # freq alpha delta f1dot f2dot
                    fo = lal.FileOpen(tCWfile, 'w')
                    lalpulsar.write_transientFstatMap_to_fp ( fo, FstatMap, windowRange, None )
                    del fo # instead of lal.FileClose() which is not SWIG-exported
                Fmn = FstatMap.F_mn.data
                maxidx = np.unravel_index(Fmn.argmax(), Fmn.shape)
                thisCand += [windowRange.t0+maxidx[0]*windowRange.dt0,
                             windowRange.tau+maxidx[1]*windowRange.dtau]
            data.append(thisCand)
Gregory Ashton's avatar
Gregory Ashton committed
187

188
        data = np.array(data, dtype=np.float)
Gregory Ashton's avatar
Gregory Ashton committed
189
190
191
        if return_data:
            return data
        else:
192
            self.save_array_to_disk(data)
Gregory Ashton's avatar
Gregory Ashton committed
193
194
            self.data = data

195
196
197
198
199
200
201
202
203
204
205
206
    def get_header(self):
        header = ';'.join(['date:{}'.format(str(datetime.datetime.now())),
                           'user:{}'.format(getpass.getuser()),
                           'hostname:{}'.format(socket.gethostname())])
        header += '\n' + ' '.join(self.keys)
        return header

    def save_array_to_disk(self, data):
        logging.info('Saving data to {}'.format(self.out_file))
        header = self.get_header()
        np.savetxt(self.out_file, data, delimiter=' ', header=header)

Gregory Ashton's avatar
Gregory Ashton committed
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
    def convert_F0_to_mismatch(self, F0, F0hat, Tseg):
        DeltaF0 = F0[1] - F0[0]
        m_spacing = (np.pi*Tseg*DeltaF0)**2 / 12.
        N = len(F0)
        return np.arange(-N*m_spacing/2., N*m_spacing/2., m_spacing)

    def convert_F1_to_mismatch(self, F1, F1hat, Tseg):
        DeltaF1 = F1[1] - F1[0]
        m_spacing = (np.pi*Tseg**2*DeltaF1)**2 / 720.
        N = len(F1)
        return np.arange(-N*m_spacing/2., N*m_spacing/2., m_spacing)

    def add_mismatch_to_ax(self, ax, x, y, xkey, ykey, xhat, yhat, Tseg):
        axX = ax.twiny()
        axX.zorder = -10
        axY = ax.twinx()
        axY.zorder = -10

        if xkey == 'F0':
            m = self.convert_F0_to_mismatch(x, xhat, Tseg)
            axX.set_xlim(m[0], m[-1])

        if ykey == 'F1':
            m = self.convert_F1_to_mismatch(y, yhat, Tseg)
            axY.set_ylim(m[0], m[-1])

Gregory Ashton's avatar
Gregory Ashton committed
233
234
    def plot_1D(self, xkey, ax=None, x0=None, xrescale=1, savefig=True,
                xlabel=None, ylabel='$\widetilde{2\mathcal{F}}$'):
Gregory Ashton's avatar
Gregory Ashton committed
235
236
        if ax is None:
            fig, ax = plt.subplots()
Gregory Ashton's avatar
Gregory Ashton committed
237
238
        xidx = self.keys.index(xkey)
        x = np.unique(self.data[:, xidx])
239
240
        if x0:
            x = x - x0
Gregory Ashton's avatar
Gregory Ashton committed
241
        x = x * xrescale
Gregory Ashton's avatar
Gregory Ashton committed
242
        z = self.data[:, -1]
Gregory Ashton's avatar
Gregory Ashton committed
243
244
245
246
247
        ax.plot(x, z)
        if x0:
            ax.set_xlabel(self.tex_labels[xkey]+self.tex_labels0[xkey])
        else:
            ax.set_xlabel(self.tex_labels[xkey])
Gregory Ashton's avatar
Gregory Ashton committed
248
249
250
251
252

        if xlabel:
            ax.set_xlabel(xlabel)

        ax.set_ylabel(ylabel)
Gregory Ashton's avatar
Gregory Ashton committed
253
        if savefig:
Gregory Ashton's avatar
Gregory Ashton committed
254
            fig.tight_layout()
Gregory Ashton's avatar
Gregory Ashton committed
255
256
            fig.savefig('{}/{}_1D.png'.format(self.outdir, self.label))
        else:
257
            return ax
Gregory Ashton's avatar
Gregory Ashton committed
258
259
260

    def plot_2D(self, xkey, ykey, ax=None, save=True, vmin=None, vmax=None,
                add_mismatch=None, xN=None, yN=None, flat_keys=[],
Gregory Ashton's avatar
Gregory Ashton committed
261
                rel_flat_idxs=[], flatten_method=np.max, title=None,
Gregory Ashton's avatar
Gregory Ashton committed
262
263
                predicted_twoF=None, cm=None, cbarkwargs={}, x0=None, y0=None,
                colorbar=False):
Gregory Ashton's avatar
Gregory Ashton committed
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
        """ Plots a 2D grid of 2F values

        Parameters
        ----------
        add_mismatch: tuple (xhat, yhat, Tseg)
            If not None, add a secondary axis with the metric mismatch from the
            point xhat, yhat with duration Tseg
        flatten_method: np.max
            Function to use in flattening the flat_keys
        """
        if ax is None:
            fig, ax = plt.subplots()
        xidx = self.keys.index(xkey)
        yidx = self.keys.index(ykey)
        flat_idxs = [self.keys.index(k) for k in flat_keys]

        x = np.unique(self.data[:, xidx])
281
282
        if x0:
            x = x-x0
Gregory Ashton's avatar
Gregory Ashton committed
283
        y = np.unique(self.data[:, yidx])
284
285
        if y0:
            y = y-y0
Gregory Ashton's avatar
Gregory Ashton committed
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
        flat_vals = [np.unique(self.data[:, j]) for j in flat_idxs]
        z = self.data[:, -1]

        Y, X = np.meshgrid(y, x)
        shape = [len(x), len(y)] + [len(v) for v in flat_vals]
        Z = z.reshape(shape)

        if len(rel_flat_idxs) > 0:
            Z = flatten_method(Z, axis=tuple(rel_flat_idxs))

        if predicted_twoF:
            Z = (predicted_twoF - Z) / (predicted_twoF + 4)
            if cm is None:
                cm = plt.cm.viridis_r
        else:
            if cm is None:
                cm = plt.cm.viridis

        pax = ax.pcolormesh(X, Y, Z, cmap=cm, vmin=vmin, vmax=vmax)
Gregory Ashton's avatar
Gregory Ashton committed
305
306
307
        if colorbar:
            cb = plt.colorbar(pax, ax=ax, **cbarkwargs)
            cb.set_label('$2\mathcal{F}$')
Gregory Ashton's avatar
Gregory Ashton committed
308
309
310
311
312
313

        if add_mismatch:
            self.add_mismatch_to_ax(ax, x, y, xkey, ykey, *add_mismatch)

        ax.set_xlim(x[0], x[-1])
        ax.set_ylim(y[0], y[-1])
314
        if x0:
Gregory Ashton's avatar
Gregory Ashton committed
315
            ax.set_xlabel(self.tex_labels[xkey]+self.tex_labels0[xkey])
316
        else:
Gregory Ashton's avatar
Gregory Ashton committed
317
            ax.set_xlabel(self.tex_labels[xkey])
318
        if y0:
Gregory Ashton's avatar
Gregory Ashton committed
319
            ax.set_ylabel(self.tex_labels[ykey]+self.tex_labels0[ykey])
320
        else:
Gregory Ashton's avatar
Gregory Ashton committed
321
            ax.set_ylabel(self.tex_labels[ykey])
Gregory Ashton's avatar
Gregory Ashton committed
322

Gregory Ashton's avatar
Gregory Ashton committed
323
324
325
        if title:
            ax.set_title(title)

Gregory Ashton's avatar
Gregory Ashton committed
326
327
328
329
330
331
332
333
334
335
336
337
        if xN:
            ax.xaxis.set_major_locator(matplotlib.ticker.MaxNLocator(xN))
        if yN:
            ax.yaxis.set_major_locator(matplotlib.ticker.MaxNLocator(yN))

        if save:
            fig.tight_layout()
            fig.savefig('{}/{}_2D.png'.format(self.outdir, self.label))
        else:
            return ax

    def get_max_twoF(self):
Gregory Ashton's avatar
Gregory Ashton committed
338
339
340
341
342
343
344
345
346
347
        """ Get the maximum twoF over the grid

        Returns
        -------
        d: dict
            Dictionary containing, 'minStartTime', 'maxStartTime', 'F0', 'F1',
            'F2', 'Alpha', 'Delta' and 'twoF' of maximum

        """

Gregory Ashton's avatar
Gregory Ashton committed
348
349
350
351
352
353
354
355
356
357
358
359
360
        twoF = self.data[:, -1]
        idx = np.argmax(twoF)
        v = self.data[idx, :]
        d = OrderedDict(minStartTime=v[0], maxStartTime=v[1], F0=v[2], F1=v[3],
                        F2=v[4], Alpha=v[5], Delta=v[6], twoF=v[7])
        return d

    def print_max_twoF(self):
        d = self.get_max_twoF()
        print('Max twoF values for {}:'.format(self.label))
        for k, v in d.iteritems():
            print('  {}={}'.format(k, v))

361
    def set_out_file(self, extra_label=None):
362
363
364
365
        if self.detectors:
            dets = self.detectors.replace(',', '')
        else:
            dets = 'NA'
366
367
368
369
370
371
372
373
        if extra_label:
            self.out_file = '{}/{}_{}_{}_{}.txt'.format(
                self.outdir, self.label, dets, type(self).__name__,
                extra_label)
        else:
            self.out_file = '{}/{}_{}_{}.txt'.format(
                self.outdir, self.label, dets, type(self).__name__)

Gregory Ashton's avatar
Gregory Ashton committed
374

Gregory Ashton's avatar
Gregory Ashton committed
375
376
377
class SliceGridSearch(GridSearch):
    """ Slice gridded search using ComputeFstat """
    @helper_functions.initializer
Gregory Ashton's avatar
Gregory Ashton committed
378
379
380
381
382
    def __init__(self, label, outdir, sftfilepattern, F0s, F1s, F2s, Alphas,
                 Deltas, tref=None, minStartTime=None, maxStartTime=None,
                 nsegs=1, BSGL=False, minCoverFreq=None, maxCoverFreq=None,
                 detectors=None, SSBprec=None, injectSources=None,
                 input_arrays=False, assumeSqrtSX=None, Lambda0=None):
Gregory Ashton's avatar
Gregory Ashton committed
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
        """
        Parameters
        ----------
        label, outdir: str
            A label and directory to read/write data from/to
        sftfilepattern: str
            Pattern to match SFTs using wildcards (*?) and ranges [0-9];
            mutiple patterns can be given separated by colons.
        F0s, F1s, F2s, delta_F0s, delta_F1s, tglitchs, Alphas, Deltas: tuple
            Length 3 tuple describing the grid for each parameter, e.g
            [F0min, F0max, dF0], for a fixed value simply give [F0]. Unless
            input_arrays == True, then these are the values to search at.
        tref, minStartTime, maxStartTime: int
            GPS seconds of the reference time, start time and end time
        input_arrays: bool
            if true, use the F0s, F1s, etc as is

        For all other parameters, see `pyfstat.ComputeFStat` for details
        """

        if os.path.isdir(outdir) is False:
            os.mkdir(outdir)
        self.set_out_file()
        self.keys = ['_', '_', 'F0', 'F1', 'F2', 'Alpha', 'Delta']
Gregory Ashton's avatar
Gregory Ashton committed
407
408
409
        self.ndim = 0
        self.thetas = [F0s, F1s, Alphas, Deltas]
        self.ndim = 4
Gregory Ashton's avatar
Gregory Ashton committed
410

Gregory Ashton's avatar
Gregory Ashton committed
411
        self.search_keys = ['F0', 'F1', 'Alpha', 'Delta']
412
413
        if self.Lambda0 is None:
            raise ValueError('Lambda0 undefined')
Gregory Ashton's avatar
Gregory Ashton committed
414
        if len(self.Lambda0) != len(self.search_keys):
Gregory Ashton's avatar
Gregory Ashton committed
415
            raise ValueError(
Gregory Ashton's avatar
Gregory Ashton committed
416
                'Lambda0 must be of length {}'.format(len(self.search_keys)))
417
        self.Lambda0 = np.array(Lambda0)
Gregory Ashton's avatar
Gregory Ashton committed
418

419
420
    def run(self, factor=2, max_n_ticks=4, whspace=0.07, save=True,
            **kwargs):
Gregory Ashton's avatar
Gregory Ashton committed
421
        lbdim = 0.5 * factor   # size of left/bottom margin
422
        trdim = 0.4 * factor   # size of top/right margin
Gregory Ashton's avatar
Gregory Ashton committed
423
424
425
426
427
428
429
430
431
432
433
434
435
436
        plotdim = factor * self.ndim + factor * (self.ndim - 1.) * whspace
        dim = lbdim + plotdim + trdim

        fig, axes = plt.subplots(self.ndim, self.ndim, figsize=(dim, dim))

        # Format the figure.
        lb = lbdim / dim
        tr = (lbdim + plotdim) / dim
        fig.subplots_adjust(left=lb, bottom=lb, right=tr, top=tr,
                            wspace=whspace, hspace=whspace)

        search = GridSearch(
            self.label, self.outdir, self.sftfilepattern,
            F0s=self.Lambda0[0], F1s=self.Lambda0[1], F2s=self.F2s[0],
437
438
            Alphas=self.Lambda0[2], Deltas=self.Lambda0[3], tref=self.tref,
            minStartTime=self.minStartTime, maxStartTime=self.maxStartTime)
Gregory Ashton's avatar
Gregory Ashton committed
439
440
441

        for i, ikey in enumerate(self.search_keys):
            setattr(search, ikey+'s', self.thetas[i])
442
443
            search.label = '{}_{}'.format(self.label, ikey)
            search.set_out_file()
Gregory Ashton's avatar
Gregory Ashton committed
444
            search.run()
445
446
447
            axes[i, i] = search.plot_1D(ikey, ax=axes[i, i], savefig=False,
                                        x0=self.Lambda0[i]
                                        )
Gregory Ashton's avatar
Gregory Ashton committed
448
            setattr(search, ikey+'s', [self.Lambda0[i]])
449
450
451
            axes[i, i].yaxis.tick_right()
            axes[i, i].yaxis.set_label_position("right")
            axes[i, i].set_xlabel('')
Gregory Ashton's avatar
Gregory Ashton committed
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478

            for j, jkey in enumerate(self.search_keys):
                ax = axes[i, j]

                if j > i:
                    ax.set_frame_on(False)
                    ax.set_xticks([])
                    ax.set_yticks([])
                    continue

                ax.get_shared_x_axes().join(axes[self.ndim-1, j], ax)
                if i < self.ndim - 1:
                    ax.set_xticklabels([])
                if j < i:
                    ax.get_shared_y_axes().join(axes[i, i-1], ax)
                    if j > 0:
                        ax.set_yticklabels([])
                if j == i:
                    continue

                ax.xaxis.set_major_locator(
                    matplotlib.ticker.MaxNLocator(max_n_ticks, prune="upper"))
                ax.yaxis.set_major_locator(
                    matplotlib.ticker.MaxNLocator(max_n_ticks, prune="upper"))

                setattr(search, ikey+'s', self.thetas[i])
                setattr(search, jkey+'s', self.thetas[j])
479
480
                search.label = '{}_{}'.format(self.label, ikey+jkey)
                search.set_out_file()
Gregory Ashton's avatar
Gregory Ashton committed
481
                search.run()
482
                ax = search.plot_2D(jkey, ikey, ax=ax, save=False,
483
484
                                    y0=self.Lambda0[i], x0=self.Lambda0[j],
                                    **kwargs)
Gregory Ashton's avatar
Gregory Ashton committed
485
486
487
                setattr(search, ikey+'s', [self.Lambda0[i]])
                setattr(search, jkey+'s', [self.Lambda0[j]])

488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
                ax.grid(lw=0.2, ls='--', zorder=10)
                ax.set_xlabel('')
                ax.set_ylabel('')

        for i, ikey in enumerate(self.search_keys):
            axes[-1, i].set_xlabel(
                self.tex_labels[ikey]+self.tex_labels0[ikey])
            if i > 0:
                axes[i, 0].set_ylabel(
                    self.tex_labels[ikey]+self.tex_labels0[ikey])
            axes[i, i].set_ylabel("$2\mathcal{F}$")

        if save:
            fig.savefig(
                '{}/{}_slice_projection.png'.format(self.outdir, self.label))
        else:
            return fig, axes
Gregory Ashton's avatar
Gregory Ashton committed
505
506


Gregory Ashton's avatar
Gregory Ashton committed
507
class GridUniformPriorSearch():
508
    @helper_functions.initializer
509
    def __init__(self, theta_prior, NF0, NF1, label, outdir, sftfilepattern,
510
                 tref, minStartTime, maxStartTime, minCoverFreq=None,
511
                 maxCoverFreq=None, BSGL=False, detectors=None, nsegs=1,
512
                 SSBprec=None, injectSources=None):
Gregory Ashton's avatar
Gregory Ashton committed
513
514
515
516
        dF0 = (theta_prior['F0']['upper'] - theta_prior['F0']['lower'])/NF0
        dF1 = (theta_prior['F1']['upper'] - theta_prior['F1']['lower'])/NF1
        F0s = [theta_prior['F0']['lower'], theta_prior['F0']['upper'], dF0]
        F1s = [theta_prior['F1']['lower'], theta_prior['F1']['upper'], dF1]
517
        self.search = GridSearch(
518
            label, outdir, sftfilepattern, F0s=F0s, F1s=F1s, tref=tref,
Gregory Ashton's avatar
Gregory Ashton committed
519
520
            Alphas=[theta_prior['Alpha']], Deltas=[theta_prior['Delta']],
            minStartTime=minStartTime, maxStartTime=maxStartTime, BSGL=BSGL,
521
            detectors=detectors, minCoverFreq=minCoverFreq,
522
523
            injectSources=injectSources, maxCoverFreq=maxCoverFreq,
            nsegs=nsegs, SSBprec=SSBprec)
524

525
    def run(self):
526
        self.search.run()
527
528

    def get_2D_plot(self, **kwargs):
529
        return self.search.plot_2D('F0', 'F1', **kwargs)
Gregory Ashton's avatar
Gregory Ashton committed
530
531


Gregory Ashton's avatar
Gregory Ashton committed
532
533
534
class GridGlitchSearch(GridSearch):
    """ Grid search using the SemiCoherentGlitchSearch """
    @helper_functions.initializer
535
    def __init__(self, label, outdir='data', sftfilepattern=None, F0s=[0],
Gregory Ashton's avatar
Gregory Ashton committed
536
537
538
                 F1s=[0], F2s=[0], delta_F0s=[0], delta_F1s=[0], tglitchs=None,
                 Alphas=[0], Deltas=[0], tref=None, minStartTime=None,
                 maxStartTime=None, minCoverFreq=None, maxCoverFreq=None,
539
                 detectors=None):
Gregory Ashton's avatar
Gregory Ashton committed
540
        """
541
542
        Run a single-glitch grid search

Gregory Ashton's avatar
Gregory Ashton committed
543
544
545
546
        Parameters
        ----------
        label, outdir: str
            A label and directory to read/write data from/to
547
548
549
        sftfilepattern: str
            Pattern to match SFTs using wildcards (*?) and ranges [0-9];
            mutiple patterns can be given separated by colons.
Gregory Ashton's avatar
Gregory Ashton committed
550
551
        F0s, F1s, F2s, delta_F0s, delta_F1s, tglitchs, Alphas, Deltas: tuple
            Length 3 tuple describing the grid for each parameter, e.g
552
553
            [F0min, F0max, dF0], for a fixed value simply give [F0]. Note that
            tglitchs is referenced to zero at minStartTime.
Gregory Ashton's avatar
Gregory Ashton committed
554
555
556
557
558
        tref, minStartTime, maxStartTime: int
            GPS seconds of the reference time, start time and end time

        For all other parameters, see pyfstat.ComputeFStat.
        """
559
560

        self.BSGL = False
561
        self.input_arrays = False
Gregory Ashton's avatar
Gregory Ashton committed
562
        if tglitchs is None:
563
            raise ValueError('You must specify `tglitchs`')
Gregory Ashton's avatar
Gregory Ashton committed
564
565

        self.search = SemiCoherentGlitchSearch(
566
            label=label, outdir=outdir, sftfilepattern=self.sftfilepattern,
Gregory Ashton's avatar
Gregory Ashton committed
567
568
569
            tref=tref, minStartTime=minStartTime, maxStartTime=maxStartTime,
            minCoverFreq=minCoverFreq, maxCoverFreq=maxCoverFreq,
            BSGL=self.BSGL)
570
        self.search.get_det_stat = self.search.get_semicoherent_nglitch_twoF
Gregory Ashton's avatar
Gregory Ashton committed
571
572
573

        if os.path.isdir(outdir) is False:
            os.mkdir(outdir)
574
        self.set_out_file()
Gregory Ashton's avatar
Gregory Ashton committed
575
576
577
578
        self.keys = ['F0', 'F1', 'F2', 'Alpha', 'Delta', 'delta_F0',
                     'delta_F1', 'tglitch']

    def get_input_data_array(self):
579
580
        logging.info("Generating input data array")
        coord_arrays = []
Gregory Ashton's avatar
Gregory Ashton committed
581
582
        for tup in (self.F0s, self.F1s, self.F2s, self.Alphas, self.Deltas,
                    self.delta_F0s, self.delta_F1s, self.tglitchs):
583
            coord_arrays.append(self.get_array_from_tuple(tup))
Gregory Ashton's avatar
Gregory Ashton committed
584
585

        input_data = []
586
        for vals in itertools.product(*coord_arrays):
Gregory Ashton's avatar
Gregory Ashton committed
587
588
            input_data.append(vals)
        self.input_data = np.array(input_data)
589
        self.coord_arrays = coord_arrays
Gregory Ashton's avatar
Gregory Ashton committed
590
591


Gregory Ashton's avatar
Gregory Ashton committed
592
593
594
class FrequencySlidingWindow(GridSearch):
    """ A sliding-window search over the Frequency """
    @helper_functions.initializer
595
    def __init__(self, label, outdir, sftfilepattern, F0s, F1, F2,
Gregory Ashton's avatar
Gregory Ashton committed
596
597
598
                 Alpha, Delta, tref, minStartTime=None,
                 maxStartTime=None, window_size=10*86400, window_delta=86400,
                 BSGL=False, minCoverFreq=None, maxCoverFreq=None,
599
                 detectors=None, SSBprec=None, injectSources=None):
Gregory Ashton's avatar
Gregory Ashton committed
600
601
602
603
604
        """
        Parameters
        ----------
        label, outdir: str
            A label and directory to read/write data from/to
605
606
607
        sftfilepattern: str
            Pattern to match SFTs using wildcards (*?) and ranges [0-9];
            mutiple patterns can be given separated by colons.
Gregory Ashton's avatar
Gregory Ashton committed
608
609
610
611
612
613
614
615
616
617
        F0s: array
            Frequency range
        F1, F2, Alpha, Delta: float
            Fixed values to compute twoF(F) over
        tref, minStartTime, maxStartTime: int
            GPS seconds of the reference time, start time and end time

        For all other parameters, see `pyfstat.ComputeFStat` for details
        """

618
619
620
621
        self.transientWindowType = None
        self.t0Band = None
        self.tauBand = None

Gregory Ashton's avatar
Gregory Ashton committed
622
623
        if os.path.isdir(outdir) is False:
            os.mkdir(outdir)
624
        self.set_out_file()
Gregory Ashton's avatar
Gregory Ashton committed
625
626
627
628
629
        self.nsegs = 1
        self.F1s = [F1]
        self.F2s = [F2]
        self.Alphas = [Alpha]
        self.Deltas = [Delta]
630
        self.input_arrays = False
631
        self.keys = ['_', '_', 'F0', 'F1', 'F2', 'Alpha', 'Delta']
Gregory Ashton's avatar
Gregory Ashton committed
632

Gregory Ashton's avatar
Gregory Ashton committed
633
634
635
    def inititate_search_object(self):
        logging.info('Setting up search object')
        self.search = ComputeFstat(
636
            tref=self.tref, sftfilepattern=self.sftfilepattern,
Gregory Ashton's avatar
Gregory Ashton committed
637
            minCoverFreq=self.minCoverFreq, maxCoverFreq=self.maxCoverFreq,
David Keitel's avatar
David Keitel committed
638
            detectors=self.detectors, transientWindowType=self.transientWindowType,
Gregory Ashton's avatar
Gregory Ashton committed
639
            minStartTime=self.minStartTime, maxStartTime=self.maxStartTime,
Gregory Ashton's avatar
Gregory Ashton committed
640
641
            BSGL=self.BSGL, SSBprec=self.SSBprec,
            injectSources=self.injectSources)
Gregory Ashton's avatar
Gregory Ashton committed
642
        self.search.get_det_stat = (
643
            self.search.get_fullycoherent_twoF)
Gregory Ashton's avatar
Gregory Ashton committed
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666

    def get_input_data_array(self):
        arrays = []
        tstarts = [self.minStartTime]
        while tstarts[-1] + self.window_size < self.maxStartTime:
            tstarts.append(tstarts[-1]+self.window_delta)
        arrays = [tstarts]
        for tup in (self.F0s, self.F1s, self.F2s,
                    self.Alphas, self.Deltas):
            arrays.append(self.get_array_from_tuple(tup))

        input_data = []
        for vals in itertools.product(*arrays):
            input_data.append(vals)

        input_data = np.array(input_data)
        input_data = np.insert(
            input_data, 1, input_data[:, 0] + self.window_size, axis=1)

        self.arrays = arrays
        self.input_data = np.array(input_data)

    def plot_sliding_window(self, F0=None, ax=None, savefig=True,
667
                            colorbar=True, timestamps=False):
Gregory Ashton's avatar
Gregory Ashton committed
668
669
670
671
672
673
674
675
676
677
678
        data = self.data
        if ax is None:
            ax = plt.subplot()
        tstarts = np.unique(data[:, 0])
        tends = np.unique(data[:, 1])
        frequencies = np.unique(data[:, 2])
        twoF = data[:, -1]
        tmids = (tstarts + tends) / 2.0
        dts = (tmids - self.minStartTime) / 86400.
        if F0:
            frequencies = frequencies - F0
679
            ax.set_ylabel('Frequency - $f_0$ [Hz] \n $f_0={:0.2f}$'.format(F0))
Gregory Ashton's avatar
Gregory Ashton committed
680
681
682
683
684
685
686
687
688
        else:
            ax.set_ylabel('Frequency [Hz]')
        twoF = twoF.reshape((len(tmids), len(frequencies)))
        Y, X = np.meshgrid(frequencies, dts)
        pax = ax.pcolormesh(X, Y, twoF)
        if colorbar:
            cb = plt.colorbar(pax, ax=ax)
            cb.set_label('$2\mathcal{F}$')
        ax.set_xlabel(
689
690
            r'Mid-point (days after $t_\mathrm{{start}}$={})'.format(
                self.minStartTime))
Gregory Ashton's avatar
Gregory Ashton committed
691
692
        ax.set_title(
            'Sliding window length = {} days in increments of {} days'
693
694
695
696
697
698
699
            .format(self.window_size/86400, self.window_delta/86400),
            )
        if timestamps:
            axT = ax.twiny()
            axT.set_xlim(tmids[0]*1e-9, tmids[-1]*1e-9)
            axT.set_xlabel('Mid-point timestamp [GPS $10^{9}$ s]')
            ax.set_title(ax.get_title(), y=1.18)
Gregory Ashton's avatar
Gregory Ashton committed
700
701
702
703
704
705
        if savefig:
            plt.tight_layout()
            plt.savefig(
                '{}/{}_sliding_window.png'.format(self.outdir, self.label))
        else:
            return ax
706
707


Gregory Ashton's avatar
Gregory Ashton committed
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
class EarthTest(GridSearch):
    """ """
    tex_labels = {'deltaRadius': '$\Delta R$ [m]',
                  'phaseOffset': 'phase-offset [rad]',
                  'deltaPspin': '$\Delta P_\mathrm{spin}$ [s]'}

    @helper_functions.initializer
    def __init__(self, label, outdir, sftfilepattern, deltaRadius,
                 phaseOffset, deltaPspin, F0, F1, F2, Alpha,
                 Delta, tref=None, minStartTime=None, maxStartTime=None,
                 BSGL=False, minCoverFreq=None, maxCoverFreq=None,
                 detectors=None, injectSources=None,
                 assumeSqrtSX=None):
        """
        Parameters
        ----------
        label, outdir: str
            A label and directory to read/write data from/to
        sftfilepattern: str
            Pattern to match SFTs using wildcards (*?) and ranges [0-9];
            mutiple patterns can be given separated by colons.
        F0, F1, F2, Alpha, Delta: float
        tref, minStartTime, maxStartTime: int
            GPS seconds of the reference time, start time and end time

        For all other parameters, see `pyfstat.ComputeFStat` for details
        """
735
736
737
738
        self.transientWindowType = None
        self.t0Band = None
        self.tauBand = None

739
740
        if os.path.isdir(outdir) is False:
            os.mkdir(outdir)
Gregory Ashton's avatar
Gregory Ashton committed
741
742
743
744
745
746
        self.nsegs = 1
        self.F0s = [F0]
        self.F1s = [F1]
        self.F2s = [F2]
        self.Alphas = [Alpha]
        self.Deltas = [Delta]
747
        self.duration = maxStartTime - minStartTime
Gregory Ashton's avatar
Gregory Ashton committed
748
749
        self.deltaRadius = np.atleast_1d(deltaRadius)
        self.phaseOffset = np.atleast_1d(phaseOffset)
750
        self.phaseOffset = self.phaseOffset + 1e-12  # Hack to stop cached data being used
Gregory Ashton's avatar
Gregory Ashton committed
751
752
753
754
755
        self.deltaPspin = np.atleast_1d(deltaPspin)
        self.set_out_file()
        self.SSBprec = lalpulsar.SSBPREC_RELATIVISTIC
        self.keys = ['deltaRadius', 'phaseOffset', 'deltaPspin']

756
757
758
759
760
761
762
763
        self.prior_widths = [
            np.max(self.deltaRadius)-np.min(self.deltaRadius),
            np.max(self.phaseOffset)-np.min(self.phaseOffset),
            np.max(self.deltaPspin)-np.min(self.deltaPspin)]

        if hasattr(self, 'search') is False:
            self.inititate_search_object()

Gregory Ashton's avatar
Gregory Ashton committed
764
765
766
767
768
769
770
771
772
    def get_input_data_array(self):
        logging.info("Generating input data array")
        coord_arrays = [self.deltaRadius, self.phaseOffset, self.deltaPspin]
        input_data = []
        for vals in itertools.product(*coord_arrays):
                input_data.append(vals)
        self.input_data = np.array(input_data)
        self.coord_arrays = coord_arrays

773
774
775
776
777
778
779
780
781
782
783
784
    def run_special(self):
        vals = [self.minStartTime, self.maxStartTime, self.F0, self.F1,
                self.F2, self.Alpha, self.Delta]
        self.special_data = {'zero': [0, 0, 0]}
        for key, (dR, dphi, dP) in self.special_data.iteritems():
            rescaleRadius = (1 + dR / lal.REARTH_SI)
            rescalePeriod = (1 + dP / lal.DAYSID_SI)
            lalpulsar.BarycenterModifyEarthRotation(
                rescaleRadius, dphi, rescalePeriod, self.tref)
            FS = self.search.get_det_stat(*vals)
            self.special_data[key] = list([dR, dphi, dP]) + [FS]

Gregory Ashton's avatar
Gregory Ashton committed
785
    def run(self):
786
        self.run_special()
Gregory Ashton's avatar
Gregory Ashton committed
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
        self.get_input_data_array()
        old_data = self.check_old_data_is_okay_to_use()
        if old_data is not False:
            self.data = old_data
            return

        data = []
        vals = [self.minStartTime, self.maxStartTime, self.F0, self.F1,
                self.F2, self.Alpha, self.Delta]
        for (dR, dphi, dP) in tqdm(self.input_data):
            rescaleRadius = (1 + dR / lal.REARTH_SI)
            rescalePeriod = (1 + dP / lal.DAYSID_SI)
            lalpulsar.BarycenterModifyEarthRotation(
                rescaleRadius, dphi, rescalePeriod, self.tref)
            FS = self.search.get_det_stat(*vals)
            data.append(list([dR, dphi, dP]) + [FS])

        data = np.array(data, dtype=np.float)
        logging.info('Saving data to {}'.format(self.out_file))
        np.savetxt(self.out_file, data, delimiter=' ')
        self.data = data

809
810
811
812
    def marginalised_bayes_factor(self, prior_widths=None):
        if prior_widths is None:
            prior_widths = self.prior_widths

813
        ndims = self.data.shape[1] - 1
814
        params = np.array([np.unique(self.data[:, j]) for j in range(ndims)])
815
816
817
818
819
        twoF = self.data[:, -1].reshape(tuple([len(p) for p in params]))
        F = twoF / 2.0
        for i, x in enumerate(params[::-1]):
            if len(x) > 1:
                dx = x[1] - x[0]
820
                F = logsumexp(F, axis=-1)+np.log(dx)-np.log(prior_widths[-1-i])
821
822
            else:
                F = np.squeeze(F, axis=-1)
823
824
825
826
827
828
829
830
831
832
833
        marginalised_F = np.atleast_1d(F)[0]
        F_at_zero = self.special_data['zero'][-1]/2.0

        max_idx = np.argmax(self.data[:, -1])
        max_F = self.data[max_idx, -1]/2.0
        max_F_params = self.data[max_idx, :-1]
        logging.info('F at zero = {:.1f}, marginalised_F = {:.1f},'
                     ' max_F = {:.1f} ({})'.format(
                         F_at_zero, marginalised_F, max_F, max_F_params))
        return F_at_zero - marginalised_F, (F_at_zero - max_F) / F_at_zero

834
835
    def plot_corner(self, prior_widths=None, fig=None, axes=None,
                    projection='log_mean'):
836
837
838
839
840
841
842
843
844
845
846
847
        Bsa, FmaxMismatch = self.marginalised_bayes_factor(prior_widths)

        data = self.data[:, -1].reshape(
            (len(self.deltaRadius), len(self.phaseOffset),
             len(self.deltaPspin)))
        xyz = [self.deltaRadius/lal.REARTH_SI, self.phaseOffset/(np.pi),
               self.deltaPspin/60.]
        labels = [r'$\frac{\Delta R}{R_\mathrm{Earth}}$',
                  r'$\frac{\Delta \phi}{\pi}$',
                  r'$\Delta P_\mathrm{spin}$ [min]',
                  r'$2\mathcal{F}$']

848
849
850
851
852
853
        try:
            from gridcorner import gridcorner
        except ImportError:
            raise ImportError(
                "Python module 'gridcorner' not found, please install from "
                "https://gitlab.aei.uni-hannover.de/GregAshton/gridcorner")
854

855
856
        fig, axes = gridcorner(data, xyz, projection=projection, factor=1.6,
                               labels=labels)
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
        axes[-1][-1].axvline((lal.DAYJUL_SI - lal.DAYSID_SI)/60.0, color='C3')
        plt.suptitle(
            'T={:.1f} days, $f$={:.2f} Hz, $\log\mathcal{{B}}_{{S/A}}$={:.1f},'
            r' $\frac{{\mathcal{{F}}_0-\mathcal{{F}}_\mathrm{{max}}}}'
            r'{{\mathcal{{F}}_0}}={:.1e}$'
            .format(self.duration/86400, self.F0, Bsa, FmaxMismatch), y=0.99,
            size=14)
        fig.savefig('{}/{}_projection_matrix.png'.format(
            self.outdir, self.label))

    def plot(self, key, prior_widths=None):
        Bsa, FmaxMismatch = self.marginalised_bayes_factor(prior_widths)

        rescales_defaults = {'deltaRadius': 1/lal.REARTH_SI,
                             'phaseOffset': 1/np.pi,
                             'deltaPspin': 1}
        labels = {'deltaRadius': r'$\frac{\Delta R}{R_\mathrm{Earth}}$',
                  'phaseOffset': r'$\frac{\Delta \phi}{\pi}$',
                  'deltaPspin': r'$\Delta P_\mathrm{spin}$ [s]'
                  }

        fig, ax = self.plot_1D(key, xrescale=rescales_defaults[key],
                               xlabel=labels[key], savefig=False)
        ax.set_title(
            'T={} days, $f$={} Hz, $\log\mathcal{{B}}_{{S/A}}$={:.1f}'
            .format(self.duration/86400, self.F0, Bsa))
        fig.tight_layout()
        fig.savefig('{}/{}_1D.png'.format(self.outdir, self.label))
885

Gregory Ashton's avatar
Gregory Ashton committed
886

887
888
889
class DMoff_NO_SPIN(GridSearch):
    """ DMoff test using SSBPREC_NO_SPIN """
    @helper_functions.initializer
890
    def __init__(self, par, label, outdir, sftfilepattern, minStartTime=None,
891
                 maxStartTime=None, minCoverFreq=None, maxCoverFreq=None,
892
                 detectors=None, injectSources=None, assumeSqrtSX=None):
893
894
895
        """
        Parameters
        ----------
896
897
898
        par: dict, str
            Either a par dictionary (containing 'F0', 'F1', 'Alpha', 'Delta'
            and 'tref') or a path to a .par file to read in the F0, F1 etc
899
900
        label, outdir: str
            A label and directory to read/write data from/to
901
902
903
        sftfilepattern: str
            Pattern to match SFTs using wildcards (*?) and ranges [0-9];
            mutiple patterns can be given separated by colons.
904
905
906
907
908
909
910
911
912
        minStartTime, maxStartTime: int
            GPS seconds of the start time and end time

        For all other parameters, see `pyfstat.ComputeFStat` for details
        """

        if os.path.isdir(outdir) is False:
            os.mkdir(outdir)

913
914
915
916
        if type(par) == dict:
            self.par = par
        elif type(par) == str and os.path.isfile(par):
            self.par = read_par(filename=par)
917
918
919
920
921
922
923
924
925
926
927
928
929
        else:
            raise ValueError('The .par file does not exist')

        self.nsegs = 1
        self.BSGL = False

        self.tref = self.par['tref']
        self.F1s = [self.par.get('F1', 0)]
        self.F2s = [self.par.get('F2', 0)]
        self.Alphas = [self.par['Alpha']]
        self.Deltas = [self.par['Delta']]
        self.Re = 6.371e6
        self.c = 2.998e8
930
        a0 = self.Re/self.c  # *np.cos(self.par['Delta'])
931
        self.m0 = np.max([4, int(np.ceil(2*np.pi*self.par['F0']*a0))])
932
933
        logging.info(
            'Setting up DMoff_NO_SPIN search with m0 = {}'.format(self.m0))
934
935
936
937
938
939
940
941
942

    def get_results(self):
        """ Compute the three summed detection statistics

        Returns
        -------
            m0, twoF_SUM, twoFstar_SUM_SIDEREAL, twoFstar_SUM_TERRESTRIAL

        """
Gregory Ashton's avatar
Gregory Ashton committed
943
944
945
        self.SSBprec = lalpulsar.SSBPREC_RELATIVISTIC
        self.set_out_file('SSBPREC_RELATIVISTIC')
        self.F0s = [self.par['F0']+j/lal.DAYSID_SI for j in range(-4, 5)]
946
947
948
        self.run()
        twoF_SUM = np.sum(self.data[:, -1])

Gregory Ashton's avatar
Gregory Ashton committed
949
950
951
        self.SSBprec = lalpulsar.SSBPREC_NO_SPIN
        self.set_out_file('SSBPREC_NO_SPIN')
        self.F0s = [self.par['F0']+j/lal.DAYSID_SI
952
953
954
955
                    for j in range(-self.m0, self.m0+1)]
        self.run()
        twoFstar_SUM = np.sum(self.data[:, -1])

Gregory Ashton's avatar
Gregory Ashton committed
956
957
        self.set_out_file('SSBPREC_NO_SPIN_TERRESTRIAL')
        self.F0s = [self.par['F0']+j/lal.DAYJUL_SI
958
959
960
961
962
                    for j in range(-self.m0, self.m0+1)]
        self.run()
        twoFstar_SUM_terrestrial = np.sum(self.data[:, -1])

        return self.m0, twoF_SUM, twoFstar_SUM, twoFstar_SUM_terrestrial