def StimulusTiming(filename='.',
ind=None,
channels=0,
trigger='StimulusCode > 0',
msec=300,
offset_msec=0,
rectify=False,
threshold=0.1,
use_eo=False,
save=None,
**kwargs):
"""
In <filename> and <ind>, give it
- a directory and ind=None: for all .dat files in the directory, in session/run order
- a directory and ind=an index or list of indices: for selected .dat files in the directory
- a dat-file name and ind=anything: for that particular file
- a list of filenames and ind=anything: for certain explicitly-specified files
<channels> may be a 0-based index, list of indices, list of channel names, or space- or comma-
delimited string of channel names
<rectify> subtracts the median and takes the abs before doing anything else
<threshold> is on the normalized scale of min=0, max=1 within the resulting image
<use_eo> uses the EventOffset state to correct timings
"""###
if hasattr(filename, 'filename'): filename = filename.filename
if ind == None:
ind = -1
if os.path.isdir(filename): filename = ListDatFiles(filename)
if not isinstance(filename, (tuple, list)): filename = [filename]
if not isinstance(ind, (tuple, list)): ind = [ind]
n = max(len(filename), len(ind))
if len(filename) == 1: filename = list(filename) * n
if len(ind) == 1: ind = list(ind) * n
if isinstance(channels, str): channels = channels.replace(',', ' ').split()
if not isinstance(channels, (tuple, list)): channels = [channels]
out = [
SigTools.sstruct(
files=[],
events=[],
t=None,
channel=ch,
img=[],
edges=[],
threshold=None,
EventOffsets=[],
UseEventOffsets=False,
) for ch in channels
]
if len(filename) == 0: raise ValueError("no data files specified")
for f, i in zip(filename, ind):
b = bcistream(filename=f, ind=i)
nsamp = b.msec2samples(msec)
nsamp_offset = b.msec2samples(offset_msec)
sig, st = b.decode('all')
statenames = list(zip(*sorted([(-len(x), x) for x in st])))[1]
criterion = trigger
for x in statenames:
criterion = criterion.replace(x, "st['%s']" % x)
criterion = numpy.asarray(eval(criterion)).flatten()
startind = SigTools.edges(criterion)
print("%d events found in %s" % (len(startind), b.filename))
for s in out:
s.files.append(b.filename)
s.events.append(len(startind))
ch = s.channel
if isinstance(ch, str):
chn = [x.lower() for x in b.params['ChannelNames']]
if ch.lower() in chn: ch = chn.index(ch.lower())
else:
raise ValueError("could not find channel %s in %s" %
(ch, b.filename))
if len(b.params['ChannelNames']) == len(sig):
s.channel = b.params['ChannelNames'][ch]
xx = numpy.asarray(sig)[ch]
if rectify: xx = numpy.abs(xx - numpy.median(xx))
xx -= xx.min()
if xx.max(): xx /= xx.max()
s.threshold = threshold
for ind in startind:
if 'EventOffset' in st:
eo = st['EventOffset'].flat[ind]
if use_eo:
ind += eo - 2**(b.statedefs['EventOffset']['length'] -
1)
s.UseEventOffsets = True
else:
eo = 0
s.EventOffsets.append(eo)
x = xx[ind + nsamp_offset:ind + nsamp_offset + nsamp].tolist()
x += [0.0] * (nsamp - len(x))
s.img.append(x)
for s in out:
s.img = numpy.asarray(s.img)
s.edges = [
min(list(x.nonzero()[0]) + [numpy.nan])
for x in (s.img > s.threshold)
]
s.edges = b.samples2msec(numpy.asarray(s.edges + nsamp_offset))
s.t = b.samples2msec(numpy.arange(nsamp_offset, nsamp_offset + nsamp))
import pylab
pylab.clf()
ax = None
for i, s in enumerate(out):
ax = pylab.subplot(1, len(out), i + 1, sharex=ax, sharey=ax)
y = y = list(range(1, len(s.img) + 1))
SigTools.imagesc(s.img, x=s.t, y=y, aspect='auto', **kwargs)
xl, yl = pylab.xlim(), pylab.ylim()
pylab.plot(s.edges, y, 'w*', markersize=10)
for j, x in enumerate(s.edges.flat):
if not numpy.isnan(x):
pylab.text(x,
y[j],
str(y[j]) + '---',
ha='right',
va='center',
color='#00FF00',
clip_on=True)
pylab.xlim(xl)
pylab.ylim(yl)
pylab.grid('on')
#pylab.ylim([len(s.img)+0.5,0.5]) # this corrupts the image!!
pylab.draw()
if save:
pylab.gcf().savefig(save, orientation='portrait')
return out
