core.py 46.2 KB
Newer Older
Gregory Ashton's avatar
Gregory Ashton committed
1
""" The core tools used in pyfstat """
2 3
from __future__ import division, absolute_import, print_function

Gregory Ashton's avatar
Gregory Ashton committed
4 5 6 7
import os
import logging
import copy

8
import glob
Gregory Ashton's avatar
Gregory Ashton committed
9
import numpy as np
10 11 12 13 14
import scipy.special
import scipy.optimize

import lal
import lalpulsar
15
import pyfstat.helper_functions as helper_functions
16 17

# workaround for matplotlib on X-less remote logins
18
if 'DISPLAY' in os.environ:
19 20
    import matplotlib.pyplot as plt
else:
21 22
    logging.info('No $DISPLAY environment variable found, so importing \
                  matplotlib.pyplot with non-interactive "Agg" backend.')
23 24 25 26
    import matplotlib
    matplotlib.use('Agg')
    import matplotlib.pyplot as plt

Gregory Ashton's avatar
Gregory Ashton committed
27
helper_functions.set_up_matplotlib_defaults()
28
args, tqdm = helper_functions.set_up_command_line_arguments()
29
detector_colors = {'h1': 'C0', 'l1': 'C1'}
Gregory Ashton's avatar
Gregory Ashton committed
30 31


Gregory Ashton's avatar
Gregory Ashton committed
32
class Bunch(object):
33 34
    """ Turns dictionary into object with attribute-style access

35 36
    Parameters
    ----------
37 38 39 40 41 42 43 44 45 46 47 48 49 50
    dict
        Input dictionary

    Examples
    --------
    >>> data = Bunch(dict(x=1, y=[1, 2, 3], z=True))
    >>> print(data.x)
    1
    >>> print(data.y)
    [1, 2, 3]
    >>> print(data.z)
    True

    """
Gregory Ashton's avatar
Gregory Ashton committed
51 52 53 54 55
    def __init__(self, dictionary):
        self.__dict__.update(dictionary)


def read_par(filename=None, label=None, outdir=None, suffix='par',
56 57
             return_type='dict', comments=['%', '#'], raise_error=False):
    """ Read in a .par or .loudest file, returns a dict or Bunch of the data
58

Gregory Ashton's avatar
Gregory Ashton committed
59 60
    Parameters
    ----------
61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76
    filename : str
        Filename (path) containing rows of `key=val` data to read in.
    label, outdir, suffix : str, optional
        If filename is None, form the file to read as `outdir/label.suffix`.
    return_type : {'dict', 'bunch'}, optional
        If `dict`, return a dictionary, if 'bunch' return a Bunch
    comments : str or list of strings, optional
        Characters denoting that a row is a comment.
    raise_error : bool, optional
        If True, raise an error for lines which are not comments, but cannot
        be read.

    Notes
    -----
    This can also be used to read in .loudest files, or any file which has
    rows of `key=val` data (in which the val can be understood using eval(val)
Gregory Ashton's avatar
Gregory Ashton committed
77 78 79 80 81

    Returns
    -------
    d: Bunch or dict
        The par values as either a `Bunch` or dict type
82

83 84 85 86
    """
    if filename is None:
        filename = '{}/{}.{}'.format(outdir, label, suffix)
    if os.path.isfile(filename) is False:
87
        raise ValueError("No file {} found".format(filename))
Gregory Ashton's avatar
Gregory Ashton committed
88 89
    d = {}
    with open(filename, 'r') as f:
90
        d = _get_dictionary_from_lines(f, comments, raise_error)
Gregory Ashton's avatar
Gregory Ashton committed
91 92 93 94 95 96
    if return_type in ['bunch', 'Bunch']:
        return Bunch(d)
    elif return_type in ['dict', 'dictionary']:
        return d
    else:
        raise ValueError('return_type {} not understood'.format(return_type))
Gregory Ashton's avatar
Gregory Ashton committed
97 98


99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115
def _get_dictionary_from_lines(lines, comments, raise_error):
    """ Return dictionary of key=val pairs for each line in lines

    Parameters
    ----------
    comments : str or list of strings
        Characters denoting that a row is a comment.
    raise_error : bool
        If True, raise an error for lines which are not comments, but cannot
        be read.

    Returns
    -------
    d: Bunch or dict
        The par values as either a `Bunch` or dict type

    """
116 117
    d = {}
    for line in lines:
118
        if line[0] not in comments and len(line.split('=')) == 2:
119 120 121
            try:
                key, val = line.rstrip('\n').split('=')
                key = key.strip()
Gregory Ashton's avatar
Gregory Ashton committed
122 123 124 125
                try:
                    d[key] = np.float64(eval(val.rstrip('; ')))
                except NameError:
                    d[key] = val.rstrip('; ')
126
            except SyntaxError:
127 128
                if raise_error:
                    raise IOError('Line {} not understood'.format(line))
129 130 131 132 133
                pass
    return d


def predict_fstat(h0, cosi, psi, Alpha, Delta, Freq, sftfilepattern,
Gregory Ashton's avatar
Gregory Ashton committed
134 135
                  minStartTime, maxStartTime, IFO=None, assumeSqrtSX=None,
                  **kwargs):
136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155
    """ Wrapper to lalapps_PredictFstat

    Parameters
    ----------
    h0, cosi, psi, Alpha, Delta, Freq : float
        Signal properties, see `lalapps_PredictFstat --help` for more info.
    sftfilepattern : str
        Pattern matching the sftfiles to use.
    minStartTime, maxStartTime : int
    IFO : str
        See `lalapps_PredictFstat --help`
    assumeSqrtSX : float or None
        See `lalapps_PredictFstat --help`, if None this option is not used

    Returns
    -------
    twoF_expected, twoF_sigma : float
        The expectation and standard deviation of 2F

    """
156 157
    tempory_filename = 'fs.tmp'

158 159 160 161 162 163 164 165 166 167
    cl_pfs = []
    cl_pfs.append("lalapps_PredictFstat")
    cl_pfs.append("--h0={}".format(h0))
    cl_pfs.append("--cosi={}".format(cosi))
    cl_pfs.append("--psi={}".format(psi))
    cl_pfs.append("--Alpha={}".format(Alpha))
    cl_pfs.append("--Delta={}".format(Delta))
    cl_pfs.append("--Freq={}".format(Freq))

    cl_pfs.append("--DataFiles='{}'".format(sftfilepattern))
168
    if assumeSqrtSX:
169
        cl_pfs.append("--assumeSqrtSX={}".format(assumeSqrtSX))
170
    if IFO:
171 172 173 174 175
        if ',' in IFO:
            logging.warning('Multiple detector selection not available, using'
                            ' all available data')
        else:
            cl_pfs.append("--IFO={}".format(IFO))
176

177 178
    cl_pfs.append("--minStartTime={}".format(int(minStartTime)))
    cl_pfs.append("--maxStartTime={}".format(int(maxStartTime)))
179
    cl_pfs.append("--outputFstat={}".format(tempory_filename))
180

181 182
    cl_pfs = " ".join(cl_pfs)
    helper_functions.run_commandline(cl_pfs)
183 184
    d = read_par(filename=tempory_filename)
    os.remove(tempory_filename)
185 186 187
    return float(d['twoF_expected']), float(d['twoF_sigma'])


Gregory Ashton's avatar
Gregory Ashton committed
188
class BaseSearchClass(object):
189
    """ The base search class providing parent methods to other searches """
Gregory Ashton's avatar
Gregory Ashton committed
190

191
    def _add_log_file(self):
Gregory Ashton's avatar
Gregory Ashton committed
192 193 194 195 196 197 198 199 200
        """ Log output to a file, requires class to have outdir and label """
        logfilename = '{}/{}.log'.format(self.outdir, self.label)
        fh = logging.FileHandler(logfilename)
        fh.setLevel(logging.INFO)
        fh.setFormatter(logging.Formatter(
            '%(asctime)s %(levelname)-8s: %(message)s',
            datefmt='%y-%m-%d %H:%M'))
        logging.getLogger().addHandler(fh)

201
    def _shift_matrix(self, n, dT):
Gregory Ashton's avatar
Gregory Ashton committed
202 203 204 205
        """ Generate the shift matrix

        Parameters
        ----------
206
        n : int
Gregory Ashton's avatar
Gregory Ashton committed
207
            The dimension of the shift-matrix to generate
208
        dT : float
Gregory Ashton's avatar
Gregory Ashton committed
209 210 211 212
            The time delta of the shift matrix

        Returns
        -------
213 214
        m : ndarray, shape (n,)
            The shift matrix.
Gregory Ashton's avatar
Gregory Ashton committed
215

216
        """
Gregory Ashton's avatar
Gregory Ashton committed
217 218 219 220 221 222 223 224 225 226 227 228 229 230 231
        m = np.zeros((n, n))
        factorial = np.math.factorial
        for i in range(n):
            for j in range(n):
                if i == j:
                    m[i, j] = 1.0
                elif i > j:
                    m[i, j] = 0.0
                else:
                    if i == 0:
                        m[i, j] = 2*np.pi*float(dT)**(j-i) / factorial(j-i)
                    else:
                        m[i, j] = float(dT)**(j-i) / factorial(j-i)
        return m

232
    def _shift_coefficients(self, theta, dT):
Gregory Ashton's avatar
Gregory Ashton committed
233 234 235 236
        """ Shift a set of coefficients by dT

        Parameters
        ----------
237 238
        theta : array-like, shape (n,)
            Vector of the expansion coefficients to transform starting from the
Gregory Ashton's avatar
Gregory Ashton committed
239
            lowest degree e.g [phi, F0, F1,...].
240 241
        dT : float
            Difference between the two reference times as tref_new - tref_old.
Gregory Ashton's avatar
Gregory Ashton committed
242 243 244

        Returns
        -------
245 246
        theta_new : ndarray, shape (n,)
            Vector of the coefficients as evaluated as the new reference time.
Gregory Ashton's avatar
Gregory Ashton committed
247 248
        """
        n = len(theta)
249
        m = self._shift_matrix(n, dT)
Gregory Ashton's avatar
Gregory Ashton committed
250 251
        return np.dot(m, theta)

252
    def _calculate_thetas(self, theta, delta_thetas, tbounds, theta0_idx=0):
253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276
        """ Calculates the set of thetas given delta_thetas, the jumps

        This is used when generating data containing glitches or timing noise.
        Specifically, the source parameters of the signal are not constant in
        time, but jump by `delta_theta` at `tbounds`.

        Parameters
        ----------
        theta : array_like
            The source parameters of size (n,).
        delta_thetas : array_like
            The jumps in the source parameters of size (m, n) where m is the
            number of jumps.
        tbounds : array_like
            Time boundaries of the jumps of size (m+2,).
        theta0_idx : int
            Index of the segment for which the theta are defined.

        Returns
        -------
        ndarray
            The set of thetas, shape (m+1, n).

        """
Gregory Ashton's avatar
Gregory Ashton committed
277 278 279
        thetas = [theta]
        for i, dt in enumerate(delta_thetas):
            if i < theta0_idx:
280
                pre_theta_at_ith_glitch = self._shift_coefficients(
Gregory Ashton's avatar
Gregory Ashton committed
281 282
                    thetas[0], tbounds[i+1] - self.tref)
                post_theta_at_ith_glitch = pre_theta_at_ith_glitch - dt
283
                thetas.insert(0, self._shift_coefficients(
Gregory Ashton's avatar
Gregory Ashton committed
284 285 286
                    post_theta_at_ith_glitch, self.tref - tbounds[i+1]))

            elif i >= theta0_idx:
287
                pre_theta_at_ith_glitch = self._shift_coefficients(
Gregory Ashton's avatar
Gregory Ashton committed
288 289
                    thetas[i], tbounds[i+1] - self.tref)
                post_theta_at_ith_glitch = pre_theta_at_ith_glitch + dt
290
                thetas.append(self._shift_coefficients(
Gregory Ashton's avatar
Gregory Ashton committed
291
                    post_theta_at_ith_glitch, self.tref - tbounds[i+1]))
292
        self.thetas_at_tref = thetas
Gregory Ashton's avatar
Gregory Ashton committed
293 294
        return thetas

295
    def _get_list_of_matching_sfts(self):
296
        """ Returns a list of sfts matching the attribute sftfilepattern """
297 298
        sftfilepatternlist = np.atleast_1d(self.sftfilepattern.split(';'))
        matches = [glob.glob(p) for p in sftfilepatternlist]
299
        matches = [item for sublist in matches for item in sublist]
300 301 302 303
        if len(matches) > 0:
            return matches
        else:
            raise IOError('No sfts found matching {}'.format(
304
                self.sftfilepattern))
305

306 307
    def set_ephemeris_files(self, earth_ephem=None, sun_ephem=None):
        """ Set the ephemeris files to use for the Earth and Sun
Gregory Ashton's avatar
Gregory Ashton committed
308

309 310 311 312 313
        Parameters
        ----------
        earth_ephem, sun_ephem: str
            Paths of the two files containing positions of Earth and Sun,
            respectively at evenly spaced times, as passed to CreateFstatInput
Gregory Ashton's avatar
Gregory Ashton committed
314

315 316 317 318 319 320 321 322 323 324 325 326 327 328 329
        Note: If not manually set, default values in ~/.pyfstat are used

        """

        earth_ephem_default, sun_ephem_default = (
                helper_functions.get_ephemeris_files())

        if earth_ephem is None:
            self.earth_ephem = earth_ephem_default
        if sun_ephem is None:
            self.sun_ephem = sun_ephem_default


class ComputeFstat(BaseSearchClass):
    """ Base class providing interface to `lalpulsar.ComputeFstat` """
Gregory Ashton's avatar
Gregory Ashton committed
330 331

    @helper_functions.initializer
332
    def __init__(self, tref, sftfilepattern=None, minStartTime=None,
David Keitel's avatar
David Keitel committed
333 334
                 maxStartTime=None, binary=False, BSGL=False,
                 transientWindowType=None, t0Band=None, tauBand=None,
335
                 dt0=None, dtau=None,
336
                 detectors=None, minCoverFreq=None, maxCoverFreq=None,
337 338
                 injectSources=None, injectSqrtSX=None, assumeSqrtSX=None,
                 SSBprec=None):
Gregory Ashton's avatar
Gregory Ashton committed
339 340 341
        """
        Parameters
        ----------
342
        tref : int
Gregory Ashton's avatar
Gregory Ashton committed
343
            GPS seconds of the reference time.
344
        sftfilepattern : str
345 346
            Pattern to match SFTs using wildcards (*?) and ranges [0-9];
            mutiple patterns can be given separated by colons.
347
        minStartTime, maxStartTime : float GPStime
Gregory Ashton's avatar
Gregory Ashton committed
348 349
            Only use SFTs with timestemps starting from (including, excluding)
            this epoch
350
        binary : bool
Gregory Ashton's avatar
Gregory Ashton committed
351
            If true, search of binary parameters.
Gregory Ashton's avatar
Gregory Ashton committed
352 353
        BSGL : bool
            If true, compute the BSGL rather than the twoF value.
David Keitel's avatar
David Keitel committed
354 355 356
        transientWindowType: str
            If 'rect' or 'exp',
            allow for the Fstat to be computed over a transient range.
Gregory Ashton's avatar
Gregory Ashton committed
357 358
            ('none' instead of None explicitly calls the transient-window
            function, but with the full range, for debugging)
359 360 361 362 363
        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.
364 365 366
        dt0, dtau: int
            grid resolutions in transient start-time and duration,
            both default to Tsft
367
        detectors : str
Gregory Ashton's avatar
Gregory Ashton committed
368
            Two character reference to the data to use, specify None for no
369
            contraint. If multiple-separate by comma.
370
        minCoverFreq, maxCoverFreq : float
Gregory Ashton's avatar
Gregory Ashton committed
371 372 373
            The min and max cover frequency passed to CreateFstatInput, if
            either is None the range of frequencies in the SFT less 1Hz is
            used.
374
        injectSources : dict or str
375 376
            Either a dictionary of the values to inject, or a string pointing
            to the .cff file to inject
377
        injectSqrtSX :
378
            Not yet implemented
379
        assumeSqrtSX : float
380 381 382
            Don't estimate noise-floors but assume (stationary) per-IFO
            sqrt{SX} (if single value: use for all IFOs). If signal only,
            set sqrtSX=1
383
        SSBprec : int
384 385
            Flag to set the SSB calculation: 0=Newtonian, 1=relativistic,
            2=relativisitic optimised, 3=DMoff, 4=NO_SPIN
Gregory Ashton's avatar
Gregory Ashton committed
386 387 388

        """

389
        self.set_ephemeris_files()
Gregory Ashton's avatar
Gregory Ashton committed
390 391
        self.init_computefstatistic_single_point()

392 393 394 395 396 397 398 399 400 401 402
    def _get_SFTCatalog(self):
        """ Load the SFTCatalog

        If sftfilepattern is specified, load the data. If not, attempt to
        create data on the fly.

        Returns
        -------
        SFTCatalog: lalpulsar.SFTCatalog

        """
Gregory Ashton's avatar
Gregory Ashton committed
403 404
        if hasattr(self, 'SFTCatalog'):
            return
405
        if self.sftfilepattern is None:
406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426
            for k in ['minStartTime', 'maxStartTime', 'detectors']:
                if getattr(self, k) is None:
                    raise ValueError('You must provide "{}" to injectSources'
                                     .format(k))
            C1 = getattr(self, 'injectSources', None) is None
            C2 = getattr(self, 'injectSqrtSX', None) is None
            if C1 and C2:
                raise ValueError('You must specify either one of injectSources'
                                 ' or injectSqrtSX')
            SFTCatalog = lalpulsar.SFTCatalog()
            Tsft = 1800
            Toverlap = 0
            Tspan = self.maxStartTime - self.minStartTime
            detNames = lal.CreateStringVector(
                *[d for d in self.detectors.split(',')])
            multiTimestamps = lalpulsar.MakeMultiTimestamps(
                self.minStartTime, Tspan, Tsft, Toverlap, detNames.length)
            SFTCatalog = lalpulsar.MultiAddToFakeSFTCatalog(
                SFTCatalog, detNames, multiTimestamps)
            return SFTCatalog

Gregory Ashton's avatar
Gregory Ashton committed
427 428
        logging.info('Initialising SFTCatalog')
        constraints = lalpulsar.SFTConstraints()
429
        if self.detectors:
430
            if ',' in self.detectors:
431 432
                logging.warning('Multiple detector selection not available,'
                                ' using all available data')
433 434
            else:
                constraints.detector = self.detectors
Gregory Ashton's avatar
Gregory Ashton committed
435 436 437 438 439
        if self.minStartTime:
            constraints.minStartTime = lal.LIGOTimeGPS(self.minStartTime)
        if self.maxStartTime:
            constraints.maxStartTime = lal.LIGOTimeGPS(self.maxStartTime)
        logging.info('Loading data matching pattern {}'.format(
440 441
                     self.sftfilepattern))
        SFTCatalog = lalpulsar.SFTdataFind(self.sftfilepattern, constraints)
442

Gregory Ashton's avatar
Gregory Ashton committed
443
        SFT_timestamps = [d.header.epoch for d in SFTCatalog.data]
Gregory Ashton's avatar
Gregory Ashton committed
444
        self.SFT_timestamps = [float(s) for s in SFT_timestamps]
445 446
        if len(SFT_timestamps) == 0:
            raise ValueError('Failed to load any data')
Gregory Ashton's avatar
Gregory Ashton committed
447 448 449 450 451
        if args.quite is False and args.no_interactive is False:
            try:
                from bashplotlib.histogram import plot_hist
                print('Data timestamps histogram:')
                plot_hist(SFT_timestamps, height=5, bincount=50)
Gregory Ashton's avatar
Gregory Ashton committed
452
            except ImportError:
Gregory Ashton's avatar
Gregory Ashton committed
453
                pass
454

455
        cl_tconv1 = 'lalapps_tconvert {}'.format(int(SFT_timestamps[0]))
456 457
        output = helper_functions.run_commandline(cl_tconv1,
                                                  log_level=logging.DEBUG)
458 459
        tconvert1 = output.rstrip('\n')
        cl_tconv2 = 'lalapps_tconvert {}'.format(int(SFT_timestamps[-1]))
460 461
        output = helper_functions.run_commandline(cl_tconv2,
                                                  log_level=logging.DEBUG)
462
        tconvert2 = output.rstrip('\n')
Gregory Ashton's avatar
Gregory Ashton committed
463 464
        logging.info('Data spans from {} ({}) to {} ({})'.format(
            int(SFT_timestamps[0]),
465
            tconvert1,
Gregory Ashton's avatar
Gregory Ashton committed
466
            int(SFT_timestamps[-1]),
467
            tconvert2))
468 469 470 471 472 473 474 475 476 477 478 479 480

        if self.minStartTime is None:
            self.minStartTime = int(SFT_timestamps[0])
        if self.maxStartTime is None:
            self.maxStartTime = int(SFT_timestamps[-1])

        detector_names = list(set([d.header.name for d in SFTCatalog.data]))
        self.detector_names = detector_names
        if len(detector_names) == 0:
            raise ValueError('No data loaded.')
        logging.info('Loaded {} data files from detectors {}'.format(
            len(SFT_timestamps), detector_names))

481
        return SFTCatalog
Gregory Ashton's avatar
Gregory Ashton committed
482 483 484 485

    def init_computefstatistic_single_point(self):
        """ Initilisation step of run_computefstatistic for a single point """

486
        SFTCatalog = self._get_SFTCatalog()
Gregory Ashton's avatar
Gregory Ashton committed
487 488 489 490 491 492

        logging.info('Initialising ephems')
        ephems = lalpulsar.InitBarycenter(self.earth_ephem, self.sun_ephem)

        logging.info('Initialising FstatInput')
        dFreq = 0
David Keitel's avatar
David Keitel committed
493
        if self.transientWindowType:
Gregory Ashton's avatar
Gregory Ashton committed
494 495 496 497 498 499
            self.whatToCompute = lalpulsar.FSTATQ_ATOMS_PER_DET
        else:
            self.whatToCompute = lalpulsar.FSTATQ_2F

        FstatOAs = lalpulsar.FstatOptionalArgs()
        FstatOAs.randSeed = lalpulsar.FstatOptionalArgsDefaults.randSeed
500 501 502 503 504
        if self.SSBprec:
            logging.info('Using SSBprec={}'.format(self.SSBprec))
            FstatOAs.SSBprec = self.SSBprec
        else:
            FstatOAs.SSBprec = lalpulsar.FstatOptionalArgsDefaults.SSBprec
Gregory Ashton's avatar
Gregory Ashton committed
505 506 507
        FstatOAs.Dterms = lalpulsar.FstatOptionalArgsDefaults.Dterms
        FstatOAs.runningMedianWindow = lalpulsar.FstatOptionalArgsDefaults.runningMedianWindow
        FstatOAs.FstatMethod = lalpulsar.FstatOptionalArgsDefaults.FstatMethod
508 509 510 511 512 513 514 515
        if self.assumeSqrtSX is None:
            FstatOAs.assumeSqrtSX = lalpulsar.FstatOptionalArgsDefaults.assumeSqrtSX
        else:
            mnf = lalpulsar.MultiNoiseFloor()
            assumeSqrtSX = np.atleast_1d(self.assumeSqrtSX)
            mnf.sqrtSn[:len(assumeSqrtSX)] = assumeSqrtSX
            mnf.length = len(assumeSqrtSX)
            FstatOAs.assumeSqrtSX = mnf
Gregory Ashton's avatar
Gregory Ashton committed
516 517 518
        FstatOAs.prevInput = lalpulsar.FstatOptionalArgsDefaults.prevInput
        FstatOAs.collectTiming = lalpulsar.FstatOptionalArgsDefaults.collectTiming

Gregory Ashton's avatar
Gregory Ashton committed
519
        if hasattr(self, 'injectSources') and type(self.injectSources) == dict:
Gregory Ashton's avatar
Gregory Ashton committed
520 521 522 523 524 525 526 527 528 529
            logging.info('Injecting source with params: {}'.format(
                self.injectSources))
            PPV = lalpulsar.CreatePulsarParamsVector(1)
            PP = PPV.data[0]
            PP.Amp.h0 = self.injectSources['h0']
            PP.Amp.cosi = self.injectSources['cosi']
            PP.Amp.phi0 = self.injectSources['phi0']
            PP.Amp.psi = self.injectSources['psi']
            PP.Doppler.Alpha = self.injectSources['Alpha']
            PP.Doppler.Delta = self.injectSources['Delta']
Gregory Ashton's avatar
Gregory Ashton committed
530 531 532 533 534 535
            if 'fkdot' in self.injectSources:
                PP.Doppler.fkdot = np.array(self.injectSources['fkdot'])
            else:
                PP.Doppler.fkdot = np.zeros(lalpulsar.PULSAR_MAX_SPINS)
                for i, key in enumerate(['F0', 'F1', 'F2']):
                    PP.Doppler.fkdot[i] = self.injectSources[key]
Gregory Ashton's avatar
Gregory Ashton committed
536 537 538 539
            PP.Doppler.refTime = self.tref
            if 't0' not in self.injectSources:
                PP.Transient.type = lalpulsar.TRANSIENT_NONE
            FstatOAs.injectSources = PPV
Gregory Ashton's avatar
Gregory Ashton committed
540
        elif hasattr(self, 'injectSources') and type(self.injectSources) == str:
541 542 543 544
            logging.info('Injecting source from param file: {}'.format(
                self.injectSources))
            PPV = lalpulsar.PulsarParamsFromFile(self.injectSources, self.tref)
            FstatOAs.injectSources = PPV
Gregory Ashton's avatar
Gregory Ashton committed
545 546
        else:
            FstatOAs.injectSources = lalpulsar.FstatOptionalArgsDefaults.injectSources
547 548 549 550
        if hasattr(self, 'injectSqrtSX') and self.injectSqrtSX is not None:
            raise ValueError('injectSqrtSX not implemented')
        else:
            FstatOAs.InjectSqrtSX = lalpulsar.FstatOptionalArgsDefaults.injectSqrtSX
Gregory Ashton's avatar
Gregory Ashton committed
551
        if self.minCoverFreq is None or self.maxCoverFreq is None:
552
            fAs = [d.header.f0 for d in SFTCatalog.data]
Gregory Ashton's avatar
Gregory Ashton committed
553
            fBs = [d.header.f0 + (d.numBins-1)*d.header.deltaF
554
                   for d in SFTCatalog.data]
Gregory Ashton's avatar
Gregory Ashton committed
555 556 557 558 559 560
            self.minCoverFreq = np.min(fAs) + 0.5
            self.maxCoverFreq = np.max(fBs) - 0.5
            logging.info('Min/max cover freqs not provided, using '
                         '{} and {}, est. from SFTs'.format(
                             self.minCoverFreq, self.maxCoverFreq))

561
        self.FstatInput = lalpulsar.CreateFstatInput(SFTCatalog,
Gregory Ashton's avatar
Gregory Ashton committed
562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581
                                                     self.minCoverFreq,
                                                     self.maxCoverFreq,
                                                     dFreq,
                                                     ephems,
                                                     FstatOAs
                                                     )

        logging.info('Initialising PulsarDoplerParams')
        PulsarDopplerParams = lalpulsar.PulsarDopplerParams()
        PulsarDopplerParams.refTime = self.tref
        PulsarDopplerParams.Alpha = 1
        PulsarDopplerParams.Delta = 1
        PulsarDopplerParams.fkdot = np.array([0, 0, 0, 0, 0, 0, 0])
        self.PulsarDopplerParams = PulsarDopplerParams

        logging.info('Initialising FstatResults')
        self.FstatResults = lalpulsar.FstatResults()

        if self.BSGL:
            if len(self.detector_names) < 2:
582
                raise ValueError("Can't use BSGL with single detectors data")
Gregory Ashton's avatar
Gregory Ashton committed
583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608
            else:
                logging.info('Initialising BSGL')

            # Tuning parameters - to be reviewed
            numDetectors = 2
            if hasattr(self, 'nsegs'):
                p_val_threshold = 1e-6
                Fstar0s = np.linspace(0, 1000, 10000)
                p_vals = scipy.special.gammaincc(2*self.nsegs, Fstar0s)
                Fstar0 = Fstar0s[np.argmin(np.abs(p_vals - p_val_threshold))]
                if Fstar0 == Fstar0s[-1]:
                    raise ValueError('Max Fstar0 exceeded')
            else:
                Fstar0 = 15.
            logging.info('Using Fstar0 of {:1.2f}'.format(Fstar0))
            oLGX = np.zeros(10)
            oLGX[:numDetectors] = 1./numDetectors
            self.BSGLSetup = lalpulsar.CreateBSGLSetup(numDetectors,
                                                       Fstar0,
                                                       oLGX,
                                                       True,
                                                       1)
            self.twoFX = np.zeros(10)
            self.whatToCompute = (self.whatToCompute +
                                  lalpulsar.FSTATQ_2F_PER_DET)

David Keitel's avatar
David Keitel committed
609
        if self.transientWindowType:
Gregory Ashton's avatar
Gregory Ashton committed
610 611
            logging.info('Initialising transient parameters')
            self.windowRange = lalpulsar.transientWindowRange_t()
David Keitel's avatar
David Keitel committed
612 613 614 615 616 617
            transientWindowTypes = {'none': lalpulsar.TRANSIENT_NONE,
                                    'rect': lalpulsar.TRANSIENT_RECTANGULAR,
                                    'exp':  lalpulsar.TRANSIENT_EXPONENTIAL}
            if self.transientWindowType in transientWindowTypes:
                self.windowRange.type = transientWindowTypes[self.transientWindowType]
            else:
Gregory Ashton's avatar
Gregory Ashton committed
618 619 620 621
                raise ValueError(
                    'Unknown window-type ({}) passed as input, [{}] allows.'
                    .format(self.transientWindowType,
                            ', '.join(transientWindowTypes)))
David Keitel's avatar
David Keitel committed
622

623
            # default spacing
David Keitel's avatar
David Keitel committed
624
            self.Tsft = int(1.0/SFTCatalog.data[0].header.deltaF)
625 626 627 628 629 630
            self.windowRange.dt0 = self.Tsft
            self.windowRange.dtau = self.Tsft

            # special treatment of window_type = none ==> replace by rectangular window spanning all the data
            if self.windowRange.type == lalpulsar.TRANSIENT_NONE:
                self.windowRange.t0 = int(self.minStartTime)
Gregory Ashton's avatar
Gregory Ashton committed
631
                self.windowRange.t0Band = 0
632
                self.windowRange.tau = int(self.maxStartTime-self.minStartTime)
David Keitel's avatar
David Keitel committed
633
                self.windowRange.tauBand = 0
634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654
            else: # user-set bands and spacings
                if self.t0Band is None:
                    self.windowRange.t0Band = 0
                else:
                    if not isinstance(self.t0Band, int):
                        logging.warn('Casting non-integer t0Band={} to int...'
                                     .format(self.t0Band))
                        self.t0Band = int(self.t0Band)
                    self.windowRange.t0Band = self.t0Band
                    if self.dt0:
                        self.windowRange.dt0 = self.dt0
                if self.tauBand is None:
                    self.windowRange.tauBand = 0
                else:
                    if not isinstance(self.tauBand, int):
                        logging.warn('Casting non-integer tauBand={} to int...'
                                     .format(self.tauBand))
                        self.tauBand = int(self.tauBand)
                    self.windowRange.tauBand = self.tauBand
                    if self.dtau:
                        self.windowRange.dtau = self.dtau
Gregory Ashton's avatar
Gregory Ashton committed
655

656 657 658
    def get_fullycoherent_twoF(self, tstart, tend, F0, F1, F2, Alpha, Delta,
                               asini=None, period=None, ecc=None, tp=None,
                               argp=None):
Gregory Ashton's avatar
Gregory Ashton committed
659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676
        """ Returns twoF or ln(BSGL) fully-coherently at a single point """
        self.PulsarDopplerParams.fkdot = np.array([F0, F1, F2, 0, 0, 0, 0])
        self.PulsarDopplerParams.Alpha = Alpha
        self.PulsarDopplerParams.Delta = Delta
        if self.binary:
            self.PulsarDopplerParams.asini = asini
            self.PulsarDopplerParams.period = period
            self.PulsarDopplerParams.ecc = ecc
            self.PulsarDopplerParams.tp = tp
            self.PulsarDopplerParams.argp = argp

        lalpulsar.ComputeFstat(self.FstatResults,
                               self.FstatInput,
                               self.PulsarDopplerParams,
                               1,
                               self.whatToCompute
                               )

David Keitel's avatar
David Keitel committed
677
        if not self.transientWindowType:
Gregory Ashton's avatar
Gregory Ashton committed
678 679 680 681 682 683 684 685 686 687 688
            if self.BSGL is False:
                return self.FstatResults.twoF[0]

            twoF = np.float(self.FstatResults.twoF[0])
            self.twoFX[0] = self.FstatResults.twoFPerDet(0)
            self.twoFX[1] = self.FstatResults.twoFPerDet(1)
            log10_BSGL = lalpulsar.ComputeBSGL(twoF, self.twoFX,
                                               self.BSGLSetup)
            return log10_BSGL/np.log10(np.exp(1))

        self.windowRange.t0 = int(tstart)  # TYPE UINT4
David Keitel's avatar
David Keitel committed
689 690 691 692 693
        if self.windowRange.tauBand == 0:
            # true single-template search also in transient params:
            # actual (t0,tau) window was set with tstart, tend before
            self.windowRange.tau = int(tend - tstart)  # TYPE UINT4
        else:
Gregory Ashton's avatar
Gregory Ashton committed
694 695
            # grid search: start at minimum tau required for nondegenerate
            # F-stat computation
David Keitel's avatar
David Keitel committed
696
            self.windowRange.tau = int(2*self.Tsft)
Gregory Ashton's avatar
Gregory Ashton committed
697

698
        self.FstatMap = lalpulsar.ComputeTransientFstatMap(
Gregory Ashton's avatar
Gregory Ashton committed
699
            self.FstatResults.multiFatoms[0], self.windowRange, False)
700
        F_mn = self.FstatMap.F_mn.data
Gregory Ashton's avatar
Gregory Ashton committed
701

702
        twoF = 2*np.max(F_mn)
Gregory Ashton's avatar
Gregory Ashton committed
703
        if self.BSGL is False:
704 705 706 707
            if np.isnan(twoF):
                return 0
            else:
                return twoF
Gregory Ashton's avatar
Gregory Ashton committed
708 709 710 711 712 713 714 715 716 717

        FstatResults_single = copy.copy(self.FstatResults)
        FstatResults_single.lenth = 1
        FstatResults_single.data = self.FstatResults.multiFatoms[0].data[0]
        FS0 = lalpulsar.ComputeTransientFstatMap(
            FstatResults_single.multiFatoms[0], self.windowRange, False)
        FstatResults_single.data = self.FstatResults.multiFatoms[0].data[1]
        FS1 = lalpulsar.ComputeTransientFstatMap(
            FstatResults_single.multiFatoms[0], self.windowRange, False)

718 719 720 721 722
        # for now, use the Doppler parameter with
        # multi-detector F maximised over t0,tau
        # to return BSGL
        # FIXME: should we instead compute BSGL over the whole F_mn
        # and return the maximum of that?
723
        idx_maxTwoF = np.argmax(F_mn)
724 725 726

        self.twoFX[0] = 2*FS0.F_mn.data[idx_maxTwoF]
        self.twoFX[1] = 2*FS1.F_mn.data[idx_maxTwoF]
Gregory Ashton's avatar
Gregory Ashton committed
727
        log10_BSGL = lalpulsar.ComputeBSGL(
728
                twoF, self.twoFX, self.BSGLSetup)
Gregory Ashton's avatar
Gregory Ashton committed
729 730 731 732 733 734

        return log10_BSGL/np.log10(np.exp(1))

    def calculate_twoF_cumulative(self, F0, F1, F2, Alpha, Delta, asini=None,
                                  period=None, ecc=None, tp=None, argp=None,
                                  tstart=None, tend=None, npoints=1000,
735 736
                                  ):
        """ Calculate the cumulative twoF along the obseration span
737 738 739

        Parameters
        ----------
740 741
        F0, F1, F2, Alpha, Delta: float
            Parameters at which to compute the cumulative twoF
742 743
        asini, period, ecc, tp, argp: float, optional
            Binary parameters at which to compute the cumulative 2F
744 745 746 747 748 749
        tstart, tend: int
            GPS times to restrict the range of data used - automatically
            truncated to the span of data available
        npoints: int
            Number of points to compute twoF along the span

750 751 752
        Notes
        -----
        The minimum cumulatibe twoF is hard-coded to be computed over
753 754 755 756 757 758
        the first 6 hours from either the first timestampe in the data (if
        tstart is smaller than it) or tstart.

        """
        SFTminStartTime = self.SFT_timestamps[0]
        SFTmaxStartTime = self.SFT_timestamps[-1]
Gregory Ashton's avatar
Gregory Ashton committed
759
        tstart = np.max([SFTminStartTime, tstart])
760 761 762
        min_tau = np.max([SFTminStartTime - tstart, 0]) + 3600*6
        max_tau = SFTmaxStartTime - tstart
        taus = np.linspace(min_tau, max_tau, npoints)
Gregory Ashton's avatar
Gregory Ashton committed
763
        twoFs = []
David Keitel's avatar
David Keitel committed
764 765 766
        if not self.transientWindowType:
            # still call the transient-Fstat-map function, but using the full range
            self.transientWindowType = 'none'
Gregory Ashton's avatar
Gregory Ashton committed
767 768
            self.init_computefstatistic_single_point()
        for tau in taus:
769
            detstat = self.get_fullycoherent_twoF(
Gregory Ashton's avatar
Gregory Ashton committed
770 771
                tstart=tstart, tend=tstart+tau, F0=F0, F1=F1, F2=F2,
                Alpha=Alpha, Delta=Delta, asini=asini, period=period, ecc=ecc,
772 773
                tp=tp, argp=argp)
            twoFs.append(detstat)
Gregory Ashton's avatar
Gregory Ashton committed
774 775 776

        return taus, np.array(twoFs)

777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796
    def _calculate_predict_fstat_cumulative(self, N, label=None, outdir=None,
                                            IFO=None, pfs_input=None):
        """ Calculates the predicted 2F and standard deviation cumulatively

        Parameters
        ----------
        N : int
            Number of timesteps to use between minStartTime and maxStartTime.
        label, outdir : str, optional
            The label and directory to read in the .loudest file from
        IFO : str
        pfs_input : dict, optional
            Input kwargs to predict_fstat (alternative to giving label and
            outdir).

        Returns
        -------
        times, pfs, pfs_sigma : ndarray, size (N,)

        """
Gregory Ashton's avatar
Gregory Ashton committed
797 798 799 800 801

        if pfs_input is None:
            if os.path.isfile('{}/{}.loudest'.format(outdir, label)) is False:
                raise ValueError(
                    'Need a loudest file to add the predicted Fstat')
802
            loudest = read_par(label=label, outdir=outdir, suffix='loudest')
Gregory Ashton's avatar
Gregory Ashton committed
803 804
            pfs_input = {key: loudest[key] for key in
                         ['h0', 'cosi', 'psi', 'Alpha', 'Delta', 'Freq']}
805 806 807
        times = np.linspace(self.minStartTime, self.maxStartTime, N+1)[1:]
        times = np.insert(times, 0, self.minStartTime + 86400/2.)
        out = [predict_fstat(minStartTime=self.minStartTime, maxStartTime=t,
808
                             sftfilepattern=self.sftfilepattern, IFO=IFO,
809 810 811 812
                             **pfs_input) for t in times]
        pfs, pfs_sigma = np.array(out).T
        return times, pfs, pfs_sigma

813 814
    def plot_twoF_cumulative(self, label, outdir, add_pfs=False, N=15,
                             injectSources=None, ax=None, c='k', savefig=True,
815
                             title=None, plt_label=None, **kwargs):
816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832
        """ Plot the twoF value cumulatively

        Parameters
        ----------
        label, outdir : str
        add_pfs : bool
            If true, plot the predicted 2F and standard deviation
        N : int
            Number of points to use
        injectSources : dict
            See `ComputeFstat`
        ax : matplotlib.axes._subplots_AxesSubplot, optional
            Axis to add the plot to.
        c : str
            Colour
        savefig : bool
            If true, save the figure in outdir
833 834
        title, plt_label: str
            Figure title and label
835 836 837 838 839 840 841 842 843

        Returns
        -------
        tauS, tauF : ndarray shape (N,)
            If savefig, the times and twoF (cumulative) values
        ax : matplotlib.axes._subplots_AxesSubplot, optional
            If savefig is False

        """
Gregory Ashton's avatar
Gregory Ashton committed
844 845
        if ax is None:
            fig, ax = plt.subplots()
Gregory Ashton's avatar
Gregory Ashton committed
846 847 848 849 850 851 852
        if injectSources:
            pfs_input = dict(
                h0=injectSources['h0'], cosi=injectSources['cosi'],
                psi=injectSources['psi'], Alpha=injectSources['Alpha'],
                Delta=injectSources['Delta'], Freq=injectSources['fkdot'][0])
        else:
            pfs_input = None
853 854

        taus, twoFs = self.calculate_twoF_cumulative(**kwargs)
855
        ax.plot(taus/86400., twoFs, label=plt_label, color=c)
856
        if len(self.detector_names) > 1:
857 858
            detector_names = self.detector_names
            detectors = self.detectors
859 860 861 862
            for d in self.detector_names:
                self.detectors = d
                self.init_computefstatistic_single_point()
                taus, twoFs = self.calculate_twoF_cumulative(**kwargs)
863 864 865 866 867 868
                ax.plot(taus/86400., twoFs, label='{}'.format(d),
                        color=detector_colors[d.lower()])
            self.detectors = detectors
            self.detector_names = detector_names

        if add_pfs:
869 870
            times, pfs, pfs_sigma = self._calculate_predict_fstat_cumulative(
                N=N, label=label, outdir=outdir, pfs_input=pfs_input)
871 872
            ax.fill_between(
                (times-self.minStartTime)/86400., pfs-pfs_sigma, pfs+pfs_sigma,
Gregory Ashton's avatar
Gregory Ashton committed
873
                color=c,
874 875
                label=(r'Predicted $\langle 2\mathcal{F} '
                       r'\rangle\pm $ 1-$\sigma$ band'),
876 877 878
                zorder=-10, alpha=0.2)
            if len(self.detector_names) > 1:
                for d in self.detector_names:
879 880 881 882
                    out = self._calculate_predict_fstat_cumulative(
                        N=N, label=label, outdir=outdir, IFO=d.upper(),
                        pfs_input=pfs_input)
                    times, pfs, pfs_sigma = out
883 884 885 886 887 888 889 890
                    ax.fill_between(
                        (times-self.minStartTime)/86400., pfs-pfs_sigma,
                        pfs+pfs_sigma, color=detector_colors[d.lower()],
                        alpha=0.5,
                        label=(
                            'Predicted $2\mathcal{{F}}$ 1-$\sigma$ band ({})'
                            .format(d.upper())),
                        zorder=-10)
891

Gregory Ashton's avatar
Gregory Ashton committed
892 893 894 895 896 897 898
        ax.set_xlabel(r'Days from $t_{{\rm start}}={:.0f}$'.format(
            kwargs['tstart']))
        if self.BSGL:
            ax.set_ylabel(r'$\log_{10}(\mathrm{BSGL})_{\rm cumulative}$')
        else:
            ax.set_ylabel(r'$\widetilde{2\mathcal{F}}_{\rm cumulative}$')
        ax.set_xlim(0, taus[-1]/86400)
899 900
        if plt_label:
            ax.legend(frameon=False, loc=2, fontsize=6)
Gregory Ashton's avatar
Gregory Ashton committed
901 902 903 904 905 906 907 908 909
        if title:
            ax.set_title(title)
        if savefig:
            plt.tight_layout()
            plt.savefig('{}/{}_twoFcumulative.png'.format(outdir, label))
            return taus, twoFs
        else:
            return ax

910 911 912 913 914 915 916 917 918 919 920 921
    def write_atoms_to_file(self, fnamebase=''):
        multiFatoms = getattr(self.FstatResults, 'multiFatoms', None)
        if multiFatoms and multiFatoms[0]:
            dopplerName = lalpulsar.PulsarDopplerParams2String ( self.PulsarDopplerParams )
            #fnameAtoms = os.path.join(self.outdir,'Fstatatoms_%s.dat' % dopplerName)
            fnameAtoms = fnamebase + '_Fstatatoms_%s.dat' % dopplerName
            fo = lal.FileOpen(fnameAtoms, 'w')
            lalpulsar.write_MultiFstatAtoms_to_fp ( fo, multiFatoms[0] )
            del fo # instead of lal.FileClose() which is not SWIG-exported
        else:
            raise RuntimeError('Cannot print atoms vector to file: no FstatResults.multiFatoms, or it is None!')

Gregory Ashton's avatar
Gregory Ashton committed
922

923
class SemiCoherentSearch(ComputeFstat):
Gregory Ashton's avatar
Gregory Ashton committed
924 925 926
    """ A semi-coherent search """

    @helper_functions.initializer
927
    def __init__(self, label, outdir, tref, nsegs=None, sftfilepattern=None,
Gregory Ashton's avatar
Gregory Ashton committed
928 929
                 binary=False, BSGL=False, minStartTime=None,
                 maxStartTime=None, minCoverFreq=None, maxCoverFreq=None,
930 931
                 detectors=None, injectSources=None, assumeSqrtSX=None,
                 SSBprec=None):
Gregory Ashton's avatar
Gregory Ashton committed
932 933 934 935 936 937 938 939 940
        """
        Parameters
        ----------
        label, outdir: str
            A label and directory to read/write data from/to.
        tref, minStartTime, maxStartTime: int
            GPS seconds of the reference time, and start and end of the data.
        nsegs: int
            The (fixed) number of segments
941 942 943
        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
944 945 946 947 948

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

        self.fs_file_name = "{}/{}_FS.dat".format(self.outdir, self.label)
949
        self.set_ephemeris_files()
David Keitel's avatar
David Keitel committed
950 951 952
        self.transientWindowType = 'rect'
        self.t0Band  = None
        self.tauBand = None
Gregory Ashton's avatar
Gregory Ashton committed
953 954 955 956 957 958 959
        self.init_computefstatistic_single_point()
        self.init_semicoherent_parameters()

    def init_semicoherent_parameters(self):
        logging.info(('Initialising semicoherent parameters from {} to {} in'
                      ' {} segments').format(
            self.minStartTime, self.maxStartTime, self.nsegs))
David Keitel's avatar
David Keitel committed
960
        self.transientWindowType = 'rect'
Gregory Ashton's avatar
Gregory Ashton committed
961 962 963
        self.whatToCompute = lalpulsar.FSTATQ_2F+lalpulsar.FSTATQ_ATOMS_PER_DET
        self.tboundaries = np.linspace(self.minStartTime, self.maxStartTime,
                                       self.nsegs+1)
964
        self.Tcoh = self.tboundaries[1] - self.tboundaries[0]
Gregory Ashton's avatar
Gregory Ashton committed
965

966 967 968 969 970 971 972 973 974
        if hasattr(self, 'SFT_timestamps'):
            if self.tboundaries[0] < self.SFT_timestamps[0]:
                logging.debug(
                    'Semi-coherent start time {} before first SFT timestamp {}'
                    .format(self.tboundaries[0], self.SFT_timestamps[0]))
            if self.tboundaries[-1] > self.SFT_timestamps[-1]:
                logging.debug(
                    'Semi-coherent end time {} after last SFT timestamp {}'
                    .format(self.tboundaries[-1], self.SFT_timestamps[-1]))
Gregory Ashton's avatar
Gregory Ashton committed
975

976
    def get_semicoherent_twoF(
977 978 979 980 981
            self, F0, F1, F2, Alpha, Delta, asini=None,
            period=None, ecc=None, tp=None, argp=None,
            record_segments=False):
        """ Returns twoF or ln(BSGL) semi-coherently at a single point """

Gregory Ashton's avatar
Gregory Ashton committed
982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998
        self.PulsarDopplerParams.fkdot = np.array([F0, F1, F2, 0, 0, 0, 0])
        self.PulsarDopplerParams.Alpha = Alpha
        self.PulsarDopplerParams.Delta = Delta
        if self.binary:
            self.PulsarDopplerParams.asini = asini
            self.PulsarDopplerParams.period = period
            self.PulsarDopplerParams.ecc = ecc
            self.PulsarDopplerParams.tp = tp
            self.PulsarDopplerParams.argp = argp

        lalpulsar.ComputeFstat(self.FstatResults,
                               self.FstatInput,
                               self.PulsarDopplerParams,
                               1,
                               self.whatToCompute
                               )

David Keitel's avatar
David Keitel committed
999
        #if not self.transientWindowType:
1000 1001 1002 1003 1004 1005 1006 1007
        #    if self.BSGL is False:
        #        return self.FstatResults.twoF[0]
        #    twoF = np.float(self.FstatResults.twoF[0])
        #    self.twoFX[0] = self.FstatResults.twoFPerDet(0)
        #    self.twoFX[1] = self.FstatResults.twoFPerDet(1)
        #    log10_BSGL = lalpulsar.ComputeBSGL(twoF, self.twoFX,
        #                                       self.BSGLSetup)
        #    return log10_BSGL/np.log10(np.exp(1))
Gregory Ashton's avatar
Gregory Ashton committed
1008 1009

        detStat = 0
1010 1011
        if record_segments:
            self.detStat_per_segment = []
Gregory Ashton's avatar
Gregory Ashton committed
1012

1013 1014 1015
        self.windowRange.tau = int(self.Tcoh)  # TYPE UINT4
        for tstart in self.tboundaries[:-1]:
            d_detStat = self._get_per_segment_det_stat(tstart)
1016 1017 1018
            detStat += d_detStat
            if record_segments:
                self.detStat_per_segment.append(d_detStat)
Gregory Ashton's avatar
Gregory Ashton committed
1019 1020 1021

        return detStat

1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050
    def _get_per_segment_det_stat(self, tstart):
        self.windowRange.t0 = int(tstart)  # TYPE UINT4

        FS = lalpulsar.ComputeTransientFstatMap(
            self.FstatResults.multiFatoms[0], self.windowRange, False)

        if self.BSGL is False:
            d_detStat = 2*FS.F_mn.data[0][0]
        else:
            FstatResults_single = copy.copy(self.FstatResults)
            FstatResults_single.lenth = 1
            FstatResults_single.data = self.FstatResults.multiFatoms[0].data[0]
            FS0 = lalpulsar.ComputeTransientFstatMap(
                FstatResults_single.multiFatoms[0], self.windowRange, False)
            FstatResults_single.data = self.FstatResults.multiFatoms[0].data[1]
            FS1 = lalpulsar.ComputeTransientFstatMap(
                FstatResults_single.multiFatoms[0], self.windowRange, False)

            self.twoFX[0] = 2*FS0.F_mn.data[0][0]
            self.twoFX[1] = 2*FS1.F_mn.data[0][0]
            log10_BSGL = lalpulsar.ComputeBSGL(
                    2*FS.F_mn.data[0][0], self.twoFX, self.BSGLSetup)
            d_detStat = log10_BSGL/np.log10(np.exp(1))
        if np.isnan(d_detStat):
            logging.debug('NaNs in semi-coherent twoF treated as zero')
            d_detStat = 0

        return d_detStat

Gregory Ashton's avatar
Gregory Ashton committed
1051

1052
class SemiCoherentGlitchSearch(ComputeFstat):
Gregory Ashton's avatar
Gregory Ashton committed
1053 1054 1055 1056 1057 1058 1059 1060 1061 1062
    """ A semi-coherent glitch search

    This implements a basic `semi-coherent glitch F-stat in which the data
    is divided into segments either side of the proposed glitches and the
    fully-coherent F-stat in each segment is summed to give the semi-coherent
    F-stat
    """

    @helper_functions.initializer
    def __init__(self, label, outdir, tref, minStartTime, maxStartTime,
1063
                 nglitch=1, sftfilepattern=None, theta0_idx=0, BSGL=False,
1064
                 minCoverFreq=None, maxCoverFreq=None, assumeSqrtSX=None,
1065
                 detectors=None, SSBprec=None, injectSources=None):
Gregory Ashton's avatar
Gregory Ashton committed
1066 1067 1068 1069 1070 1071 1072 1073 1074 1075
        """
        Parameters
        ----------
        label, outdir: str
            A label and directory to read/write data from/to.
        tref, minStartTime, maxStartTime: int
            GPS seconds of the reference time, and start and end of the data.
        nglitch: int
            The (fixed) number of glitches; this can zero, but occasionally
            this causes issue (in which case just use ComputeFstat).
1076 1077 1078
        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
1079 1080 1081 1082 1083 1084 1085 1086 1087
        theta0_idx, int
            Index (zero-based) of which segment the theta refers to - uyseful
            if providing a tight prior on theta to allow the signal to jump
            too theta (and not just from)

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

        self.fs_file_name = "{}/{}_FS.dat".format(self.outdir, self.label)
1088
        self.set_ephemeris_files()
David Keitel's avatar
David Keitel committed
1089 1090 1091 1092
        self.transientWindowType = 'rect'
        self.t0Band  = None
        self.tauBand = None
        self.binary  = False
Gregory Ashton's avatar
Gregory Ashton committed
1093 1094
        self.init_computefstatistic_single_point()

1095
    def get_semicoherent_nglitch_twoF(self, F0, F1, F2, Alpha, Delta, *args):
Gregory Ashton's avatar
Gregory Ashton committed
1096 1097 1098 1099 1100 1101 1102 1103 1104 1105 1106 1107 1108
        """ Returns the semi-coherent glitch summed twoF """

        args = list(args)
        tboundaries = ([self.minStartTime] + args[-self.nglitch:]
                       + [self.maxStartTime])
        delta_F0s = args[-3*self.nglitch:-2*self.nglitch]
        delta_F1s = args[-2*self.nglitch:-self.nglitch]
        delta_F2 = np.zeros(len(delta_F0s))
        delta_phi = np.zeros(len(delta_F0s))
        theta = [0, F0, F1, F2]
        delta_thetas = np.atleast_2d(
                np.array([delta_phi, delta_F0s, delta_F1s, delta_F2]).T)

1109
        thetas = self._calculate_thetas(theta, delta_thetas, tboundaries,
1110
                                        theta0_idx=self.theta0_idx)
Gregory Ashton's avatar
Gregory Ashton committed
1111 1112 1113 1114

        twoFSum = 0
        for i, theta_i_at_tref in enumerate(thetas):
            ts, te = tboundaries[i], tboundaries[i+1]
1115
            if te - ts > 1800: