core.py 6.33 KB
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import sys
import os
import logging
import os.path as op

import numpy as num

from pyrocko import pile, trace, util, io
from pyrocko.parstack import parstack

from lassie import common, plot, grid as gridmod

logger = logging.getLogger('lassie.core')


def scan(
        config,
        show_detections=False,
        show_movie=False,
        force=False,
        stop_after_first=False):

    if config.detections_path:
        if op.exists(config.detections_path):
            if force:
                os.unlink(config.detections_path)
            else:
                raise common.LassieError(
                    'detections file already exists: %s' % config.detections_path)

        util.ensuredirs(config.detections_path)

    grid = config.get_grid()
    receivers = config.get_receivers()

    norm_map = gridmod.geometrical_normalization(grid, receivers)

    shift_tables = []
    tshift_maxs = []
    for ifc in config.ifcs:
        shift_tables.append(ifc.shifter.get_table(grid, receivers))
        tshift_maxs.append(shift_tables[-1].max())

    tshift_max = max(tshift_maxs) * 1.0

    tinc = tshift_max * 10

    tpad = max(ifc.get_tpad() for ifc in config.ifcs) + tshift_max

    fsmooth_min = min(ifc.get_fsmooth() for ifc in config.ifcs)

    blacklist = set(tuple(s.split('.')) for s in config.blacklist)

    station_index = dict(
        (rec.codes, i) for (i, rec) in enumerate(receivers)
        if rec.codes not in blacklist)

    p = pile.make_pile(config.data_paths, fileformat='detect')

    ngridpoints = grid.size()

    idetection = 0

    station_weights = {}

    tmin = config.tmin
    tmax = config.tmax
    for trs in p.chopper(
            tmin=tmin, tmax=tmax, tinc=tinc, tpad=tpad,
            want_incomplete=False,
            trace_selector=lambda tr: tr.nslc_id[:3] in station_index):

        if not trs:
            continue

        logger.info('processing time window %s - %s' % (
            util.time_to_str(trs[0].wmin),
            util.time_to_str(trs[0].wmax)))

        wmin = trs[0].wmin
        wmax = trs[0].wmax

        frames = None
        pdata = []
        trs_debug = []
        shift_maxs = []
        for iifc, ifc in enumerate(config.ifcs):
            dataset = ifc.preprocess(trs, wmin, wmax, tshift_max)
            if not dataset:
                continue

            nstations_selected = len(dataset)

            nsls_selected, trs_selected = zip(*dataset)

            trs_debug.extend(trs + list(trs_selected))

            deltat_cf = trs_selected[0].deltat

            t0 = (wmin / deltat_cf) * deltat_cf

            istations_selected = num.array(
                [station_index[nsl] for nsl in nsls_selected], dtype=num.int)

            arrays = [tr.ydata.astype(num.float) for tr in trs_selected]

            offsets = num.array(
                [int(round((tr.tmin-t0) / deltat_cf)) for tr in trs_selected],
                dtype=num.int32)

            w = num.array(
                [station_weights.get(nsl, 1.0) for nsl in nsls_selected],
                dtype=num.float)


            weights = num.ones((ngridpoints, nstations_selected))
            weights *= w[num.newaxis, :]
            weights *= ifc.weight

            shift_table = shift_tables[iifc]

            shifts = -num.round(
                shift_table[:, istations_selected] /
                deltat_cf).astype(num.int32)

            pdata.append((list(trs_selected), shift_table, ifc))

            iwmin = int(round((wmin-t0) / deltat_cf))
            iwmax = int(round((wmax-t0) / deltat_cf))

            lengthout = iwmax - iwmin + 1

            shift_maxs.append(num.max(-shifts) * deltat_cf)

            frames, ioff = parstack(
                arrays, offsets, shifts, weights, 0,
                offsetout=iwmin,
                lengthout=lengthout,
                result=frames,
                impl='openmp')

        shift_max = max(shift_maxs)

        if config.sharpness_normalization:
            frame_maxs = frames.max(axis=0)
            frame_means = num.abs(frames).mean(axis=0)
            frames *= (frame_maxs / frame_means)[num.newaxis, :]
            frames *= norm_map[:, num.newaxis]

        frame_maxs = frames.max(axis=0)

        tmin_frames = t0 + ioff * deltat_cf

        tr_stackmax = trace.Trace(
            '', 'SMAX', '', '',
            tmin=tmin_frames,
            deltat=deltat_cf,
            ydata=frame_maxs)

        trs_debug.append(tr_stackmax)

        # trace.snuffle(trs_debug)

        ydata_window = tr_stackmax.chop(wmin, wmax, inplace=False).get_ydata()

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        logger.info('CF stats: min %g, max %g, median %g' % (
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            num.min(ydata_window),
            num.max(ydata_window),
            num.median(ydata_window)))

        tpeaks, apeaks = tr_stackmax.peaks(
            config.detector_threshold, shift_max + 1.0/fsmooth_min)

        for (tpeak, apeak) in zip(tpeaks, apeaks):
            if not (wmin <= tpeak and tpeak < wmax):
                continue

            logger.info('detection: %s %g' % (
                util.time_to_str(tpeak),
                apeak))

            iframe = int(round(((tpeak-t0) - ioff*deltat_cf) / deltat_cf))
            frame = frames[:, iframe]
            imax = num.argmax(frame)

            latpeak, lonpeak, xpeak, ypeak, zpeak = grid.index_to_location(imax)

            idetection += 1

            if config.detections_path:
                f = open(config.detections_path, 'a')
                f.write('%06i %s %g %g %g %g %g %g\n' % (
                    idetection,
                    util.time_to_str(tpeak, format='%Y-%m-%d %H:%M:%S.6FRAC'),
                    apeak,
                    latpeak, lonpeak, xpeak, ypeak, zpeak))

                f.close()

            if show_detections:
                fmin = min(ifc.fmin for ifc in config.ifcs)
                fmax = min(ifc.fmax for ifc in config.ifcs)
                plot.plot_detection(
                    grid, receivers, frames, tmin_frames,
                    deltat_cf, imax, iframe, fsmooth_min, xpeak, ypeak, zpeak,
                    tr_stackmax, tpeaks, apeaks, config.detector_threshold,
                    pdata, trs, fmin, fmax, idetection,
                    grid_station_shift_max=shift_max,
                    movie=show_movie)

            if stop_after_first:
                return

        tr_stackmax.chop(wmin, wmax)
        io.save([tr_stackmax], 'stackmax/trace_%(tmin)s.mseed')


__all__ = [
    'scan',
]