Skip to content
GitLab
Commit 63396a6c authored by Marius Kriegerowski's avatar Marius Kriegerowski
Browse files

Merge branch 'master' of gitext.gfz-potsdam.de:heimann/lassie

parents 0fd6549e 91a98533
Hide whitespace changes
Inline Side-by-side
src/config.py
View file @ 63396a6c
import logging
import os.path as op
from pyrocko.guts import String, Float, Timestamp, List, Bool
from pyrocko.guts import String, Float, Timestamp, List, Bool, Int
from pyrocko import model, guts
from pyrocko.io import stationxml
from pyrocko.gf import TPDef
......@@ -120,6 +120,18 @@ class Config(HasPaths):
default='lassie_phases.cache',
help='directory where lassie stores tabulated phases etc.')
stacking_blocksize = Int.T(
optional=True,
help='enable chunked stacking to reduce memory usage. Setting this to '
'e.g. 64 will use ngridpoints * 64 * 8 bytes of memory to hold '
'the stacking results, instead of computing the whole processing '
'time window in one shot. Setting this to a very small number '
'may lead to bad performance. If this is enabled together with '
'plotting, the cutout of the image function seen in the map '
'image must be stacked again just for plotting (redundantly and '
'memory greedy) because it may intersect more than one '
'processing chunk.')
def __init__(self, *args, **kwargs):
HasPaths.__init__(self, *args, **kwargs)
self._receivers = None
......@@ -131,8 +143,8 @@ class Config(HasPaths):
'''
Post-init setup of image function contributors.
'''
for ifc in self.image_function_contributions:
ifc.setup(self)
for ifc_ in self.image_function_contributions:
ifc_.setup(self)
def set_config_name(self, config_name):
self._config_name = config_name
......
src/core.py
View file @ 63396a6c
......@@ -2,6 +2,7 @@ import math
import logging
import os.path as op
import shutil
import time
from collections import defaultdict
......@@ -309,10 +310,14 @@ def search(
if config.fill_incomplete_with_zeros:
trs = zero_fill(trs, wmin - tpad, wmax + tpad)
frames = None
t0 = math.floor(wmin / deltat_cf) * deltat_cf
iwmin = int(round((wmin-tpeaksearch-t0) / deltat_cf))
iwmax = int(round((wmax+tpeaksearch-t0) / deltat_cf))
lengthout = iwmax - iwmin + 1
pdata = []
trs_debug = []
shift_maxs = []
parstack_params = []
for iifc, ifc in enumerate(ifcs):
dataset = ifc.preprocess(
trs, wmin-tpeaksearch, wmax+tpeaksearch,
......@@ -329,8 +334,6 @@ def search(
trs_debug.extend(trs + list(trs_selected))
t0 = (wmin / deltat_cf) * deltat_cf
istations_selected = num.array(
[station_index[nsl] for nsl in nsls_selected],
dtype=num.int)
......@@ -362,35 +365,58 @@ def search(
pdata.append((list(trs_selected), shift_table, ifc))
iwmin = int(round((wmin-tpeaksearch-t0) / deltat_cf))
iwmax = int(round((wmax+tpeaksearch-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,
nparallel=nparallel,
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]
if config.ifc_count_normalization:
frames *= 1.0 / len(ifcs)
frame_maxs = frames.max(axis=0)
tmin_frames = t0 + ioff * deltat_cf
parstack_params.append((arrays, offsets, shifts, weights))
if config.stacking_blocksize is not None:
ipstep = config.stacking_blocksize
frames = None
else:
ipstep = lengthout
frames = num.zeros((ngridpoints, lengthout))
twall_start = time.time()
frame_maxs = num.zeros(lengthout)
frame_argmaxs = num.zeros(lengthout, dtype=num.int)
ipmin = iwmin
while ipmin < iwmin+lengthout:
ipsize = min(ipstep, iwmin + lengthout - ipmin)
if ipstep == lengthout:
frames_p = frames
else:
frames_p = num.zeros((ngridpoints, ipsize))
for (arrays, offsets, shifts, weights) in parstack_params:
frames_p, _ = parstack(
arrays, offsets, shifts, weights, 0,
offsetout=ipmin,
lengthout=ipsize,
result=frames_p,
nparallel=nparallel,
impl='openmp')
if config.sharpness_normalization:
frame_p_maxs = frames_p.max(axis=0)
frame_p_means = num.abs(frames_p).mean(axis=0)
frames_p *= (frame_p_maxs / frame_p_means)[num.newaxis, :]
frames_p *= norm_map[:, num.newaxis]
if config.ifc_count_normalization:
frames_p *= 1.0 / len(ifcs)
frame_maxs[ipmin-iwmin:ipmin-iwmin+ipsize] = \
frames_p.max(axis=0)
frame_argmaxs[ipmin-iwmin:ipmin-iwmin+ipsize] = \
pargmax(frames_p)
ipmin += ipstep
del frames_p
twall_end = time.time()
logger.info('wallclock time for stacking: %g s' % (
twall_end - twall_start))
tmin_frames = t0 + iwmin * deltat_cf
tr_stackmax = trace.Trace(
'', 'SMAX', '', '',
......@@ -418,17 +444,13 @@ def search(
wmin <= tpeak and tpeak < wmax])) or ([], [])
tr_stackmax_indx = tr_stackmax.copy(data=False)
imaxs = pargmax(frames)
tr_stackmax_indx.set_ydata(imaxs.astype(num.int32))
tr_stackmax_indx.set_ydata(frame_argmaxs.astype(num.int32))
tr_stackmax_indx.set_location('i')
for (tpeak, apeak) in zip(tpeaks, apeaks):
iframe = int(round(((tpeak-t0) - ioff*deltat_cf) / deltat_cf))
frame = frames[:, iframe]
imax = imaxs[iframe]
iframe = int(round((tpeak - tmin_frames) / deltat_cf))
imax = frame_argmaxs[iframe]
latpeak, lonpeak, xpeak, ypeak, zpeak = \
grid.index_to_location(imax)
......@@ -477,23 +499,60 @@ def search(
util.ensuredirs(fn)
try:
plot.plot_detection(
grid, receivers, frames, tmin_frames,
deltat_cf, imax, iframe, fsmooth_min, xpeak, ypeak,
zpeak,
tr_stackmax, tpeaks, apeaks,
config.detector_threshold,
wmin, wmax,
pdata, trs, fmin, fmax, idetection,
grid_station_shift_max=shift_max,
movie=show_movie,
show=show_detections,
save_filename=fn)
except AttributeError as e:
logger.warn(e)
del frame
if frames is not None:
frames_p = frames
tmin_frames_p = tmin_frames
iframe_p = iframe
else:
iframe_min = max(
0,
int(round(iframe - tpeaksearch/deltat_cf)))
iframe_max = min(
lengthout-1,
int(round(iframe + tpeaksearch/deltat_cf)))
ipsize = iframe_max - iframe_min + 1
frames_p = num.zeros((ngridpoints, ipsize))
tmin_frames_p = tmin_frames + iframe_min*deltat_cf
iframe_p = iframe - iframe_min
for (arrays, offsets, shifts, weights) \
in parstack_params:
frames_p, _ = parstack(
arrays, offsets, shifts, weights, 0,
offsetout=iwmin+iframe_min,
lengthout=ipsize,
result=frames_p,
nparallel=nparallel,
impl='openmp')
if config.sharpness_normalization:
frame_p_maxs = frames_p.max(axis=0)
frame_p_means = num.abs(frames_p).mean(axis=0)
frames_p *= (
frame_p_maxs/frame_p_means)[num.newaxis, :]
frames_p *= norm_map[:, num.newaxis]
if config.ifc_count_normalization:
frames_p *= 1.0 / len(ifcs)
plot.plot_detection(
grid, receivers, frames_p, tmin_frames_p,
deltat_cf, imax, iframe_p, xpeak, ypeak,
zpeak,
tr_stackmax, tpeaks, apeaks,
config.detector_threshold,
wmin, wmax,
pdata, trs, fmin, fmax, idetection,
tpeaksearch,
movie=show_movie,
show=show_detections,
save_filename=fn)
del frames_p
if stop_after_first:
return
......
src/plot.py
View file @ 63396a6c
......@@ -108,9 +108,9 @@ def plot_geometry_carthesian(grid, receivers):
def plot_detection(
grid, receivers, frames, tmin_frames, deltat_cf, imax, iframe,
fsmooth_min, xpeak, ypeak, zpeak, tr_stackmax, tpeaks, apeaks,
xpeak, ypeak, zpeak, tr_stackmax, tpeaks, apeaks,
detector_threshold, wmin, wmax, pdata, trs_raw, fmin, fmax,
idetection, grid_station_shift_max,
idetection, tpeaksearch,
movie=False, save_filename=None, show=True):
from matplotlib import pyplot as plt
......@@ -123,11 +123,10 @@ def plot_detection(
distances = grid.distances(receivers)
plot.mpl_init()
plot.mpl_init(fontsize=9)
fig = plt.figure(figsize=plot.mpl_papersize('a4', 'landscape'))
axes = plt.subplot2grid((2, 3), (0, 2), aspect=1.0)
plot.mpl_labelspace(axes)
......@@ -161,7 +160,7 @@ def plot_detection(
tpeak_current = tmin_frames + deltat_cf * iframe
t0 = tpeak_current
tduration = 2.0*grid_station_shift_max + 1./fsmooth_min
tduration = 2.0*tpeaksearch
axes2.axvspan(
tr_stackmax.tmin - t0, wmin - t0,
......
Supports Markdown
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment