def show_isi_stats(self, mesg='', run_len=[], tr=0, rest_file=''):
"""display ISI timing statistics
mesg : display the user message first
run_len : can be empty, length 1 or length nrows
tr : if > 0: show mean/stdev for stimuli within TRs
(so 0 <= mean < tr)
rest_file : if set, save all rest durations
display these statistics:
- total time, total stim time, total rest time
- total time per run
- total stim time per run
- total rest time per run
- pre-stim rest per run
- post-stim response rest per run (if run_len is given)
- total ISI rest per run
- min/mean/max (stdev) of stim duration
- min/mean/max (stdev) of ISI rest
"""
if not self.ready:
print '** M Timing: nothing to compute ISI stats from'
return 1
if not (self.mtype & LD.MTYPE_DUR):
print '** warning: computing stats without duration'
if self.nrows != len(self.data):
print '** bad MTiming, nrows=%d, datalen=%d, failing...' % \
(self.nrows, len(self.data))
return 1
# make a sorted copy
scopy = self.copy()
scopy.sort()
# make a copy of format run x stim x [start,end], i.e. is 3-D
tdata = scopy.get_start_end_timing()
# make an updated run lengths list
if len(run_len) == 0:
rlens = [0 for rind in range(self.nrows)]
elif len(run_len) == 1:
rlens = [run_len[0] for rind in range(self.nrows)]
elif len(run_len) == self.nrows:
rlens = run_len
else: # failure
print '** invalid len(run_len)=%d, must be one of 0,1,%d' % \
(len(run_len), self.nrows)
return 1
if self.verb > 1:
print '-- show_isi_stats, run_len = %s, tr = %s, rest_file = %s' \
% (run_len, tr, rest_file)
if self.verb > 3:
print scopy.make_data_string(nplaces=1, flag_empty=0, check_simple=0,
mesg='scopy data')
all_stim = [] # all stimulus durations (one row per run)
all_isi = [] # all isi times (one row per run)
pre_time = [] # pre-stim, per run
post_time = [] # pose-stim, per run
run_time = [] # total run time, per run
errs = 0 # allow a few errors before failing
max_errs = 10
for rind in range(self.nrows):
run = tdata[rind]
rlen = rlens[rind]
if len(run) == 0: # empty run
all_stim.append([])
all_isi.append([])
pre_time.append(rlen)
post_time.append(0.0)
run_time.append(rlen)
continue
# if no run len specified, use end of last stimulus
if rlen == 0.0: rlen = run[-1][1]
elif rlen < run[-1][1]:
print '** run %d: given length = %s, last stim ends at %s' % \
(rind+1, rlen, run[-1][1])
errs += 1
if errs > max_errs:
print '** bailing...'
return 1
# pre- and post-stim times are set
pre = run[0][0]
post = rlen - run[-1][1]
if pre < 0:
print '** ISI error: first stimulus of run %d at negative time %s'%\
(rind+1, run[0][0])
errs += 1
if errs > max_errs:
print '** bailing...'
return 1
# init accumulation vars
stimes = [run[0][1] - run[0][0]]
itimes = []
# for each following index, update stim and isi times
# (check for bad overlap)
for sind in range(1, len(run)):
if run[sind][0] < run[sind-1][1]:
print '** ISI error: stimuli overlap at run %d, time %s' % \
(rind+1, run[sind][0])
errs += 1
if errs > max_errs:
print '** bailing...'
return 1
stimes.append(run[sind][1]-run[sind][0])
itimes.append(run[sind][0]-run[sind-1][1])
# store results
all_stim.append(stimes)
all_isi.append(itimes)
pre_time.append(pre)
post_time.append(post)
run_time.append(rlen)
if errs > 0: return 1
# tally the results
rtot_stim = [] ; rtot_isi = [] ; rtot_rest = []
stim_list = [] ; isi_list = [] ; nstim_list = []
for rind in range(self.nrows):
rtot_stim.append(UTIL.loc_sum(all_stim[rind]))
rtot_rest.append(pre_time[rind] + UTIL.loc_sum(all_isi[rind]) +
post_time[rind])
rtot_isi.append(UTIL.loc_sum(all_isi[rind]))
stim_list.extend(all_stim[rind])
isi_list.extend(all_isi[rind])
nstim_list.append(len(all_stim[rind]))
if mesg: mstr = '(%s) ' % mesg
else: mstr = ''
print '\nISI statistics %s:\n' % mstr
print ' total per run'
print ' ------ ------------------------------'
print ' total time %6.1f %s' % \
(UTIL.loc_sum(run_time), float_list_string(run_time, ndec=1))
print ' total time: stim %6.1f %s' % \
(UTIL.loc_sum(rtot_stim),float_list_string(rtot_stim,7,ndec=1))
print ' total time: rest %6.1f %s' % \
(UTIL.loc_sum(rtot_rest),float_list_string(rtot_rest,7,ndec=1))
print ''
print ' rest: total isi %6.1f %s' % \
(UTIL.loc_sum(rtot_isi), float_list_string(rtot_isi,7,ndec=1))
print ' rest: pre stim %6.1f %s' % \
(UTIL.loc_sum(pre_time), float_list_string(pre_time,7,ndec=1))
print ' rest: post stim %6.1f %s' % \
(UTIL.loc_sum(post_time),float_list_string(post_time,7,ndec=1))
print ''
print ' num stimuli %6d %s' % \
(UTIL.loc_sum(nstim_list), float_list_string(nstim_list,7,ndec=0))
print '\n'
print ' min mean max stdev'
print ' ------- ------- ------- -------'
print ' rest: pre-stim %7.3f %7.3f %7.3f %7.3f' % \
(UTIL.min_mean_max_stdev(pre_time))
print ' rest: post-stim %7.3f %7.3f %7.3f %7.3f' % \
(UTIL.min_mean_max_stdev(post_time))
print ''
for ind in range(self.nrows):
m0, m1, m2, s = UTIL.min_mean_max_stdev(all_isi[ind])
print ' rest: run #%d ISI %7.3f %7.3f %7.3f %7.3f' % \
(ind, m0, m1, m2, s)
print ''
print ' all runs: ISI %7.3f %7.3f %7.3f %7.3f' % \
(UTIL.min_mean_max_stdev(isi_list))
print ' all runs: stimuli %7.3f %7.3f %7.3f %7.3f' % \
(UTIL.min_mean_max_stdev(stim_list))
print ''
# and possibly print out offset info
if tr > 0: self.show_TR_offset_stats(tr, '')
# maybe write all rest durations
if rest_file:
all_rest = copy.deepcopy(all_isi)
for run, rest in enumerate(all_rest):
rest[:0] = [pre_time[run]]
rest.append(post_time[run])
UTIL.write_to_timing_file(all_rest, rest_file)
# clean up, just to be kind
del(all_stim); del(all_isi); del(pre_time); del(post_time); del(run_time)
del(rtot_stim); del(rtot_isi); del(rtot_rest); del(stim_list)
del(isi_list); del(nstim_list)
del(scopy)
del(tdata)
def show_isi_stats(self, mesg='', run_len=[], tr=0, rest_file=''):
"""display ISI timing statistics
mesg : display the user message first
run_len : can be empty, length 1 or length nrows
tr : if > 0: show mean/stdev for stimuli within TRs
(so 0 <= mean < tr)
rest_file : if set, save all rest durations
display these statistics:
- total time, total stim time, total rest time
- total time per run
- total stim time per run
- total rest time per run
- pre-stim rest per run
- post-stim response rest per run (if run_len is given)
- total ISI rest per run
- min/mean/max (stdev) of stim duration
- min/mean/max (stdev) of ISI rest
"""
if not self.ready:
print '** M Timing: nothing to compute ISI stats from'
return 1
if not (self.mtype & LD.MTYPE_DUR):
print '** warning: computing stats without duration'
if self.nrows != len(self.data):
print '** bad MTiming, nrows=%d, datalen=%d, failing...' % \
(self.nrows, len(self.data))
return 1
# make a sorted copy
scopy = self.copy()
scopy.sort()
# make a copy of format run x stim x [start,end], i.e. is 3-D
tdata = scopy.get_start_end_timing()
# make an updated run lengths list
if len(run_len) == 0:
rlens = [0 for rind in range(self.nrows)]
elif len(run_len) == 1:
rlens = [run_len[0] for rind in range(self.nrows)]
elif len(run_len) == self.nrows:
rlens = run_len
else: # failure
print '** invalid len(run_len)=%d, must be one of 0,1,%d' % \
(len(run_len), self.nrows)
return 1
if self.verb > 1:
print '-- show_isi_stats, run_len = %s, tr = %s, rest_file = %s' \
% (run_len, tr, rest_file)
if self.verb > 3:
print scopy.make_data_string(nplaces=1,
flag_empty=0,
check_simple=0,
mesg='scopy data')
all_stim = [] # all stimulus durations (one row per run)
all_isi = [] # all isi times (one row per run)
pre_time = [] # pre-stim, per run
post_time = [] # pose-stim, per run
run_time = [] # total run time, per run
errs = 0 # allow a few errors before failing
max_errs = 10
for rind in range(self.nrows):
run = tdata[rind]
rlen = rlens[rind]
if len(run) == 0: # empty run
all_stim.append([])
all_isi.append([])
pre_time.append(rlen)
post_time.append(0.0)
run_time.append(rlen)
continue
# if no run len specified, use end of last stimulus
if rlen == 0.0: rlen = run[-1][1]
elif rlen < run[-1][1]:
print '** run %d: given length = %s, last stim ends at %s' % \
(rind+1, rlen, run[-1][1])
errs += 1
if errs > max_errs:
print '** bailing...'
return 1
# pre- and post-stim times are set
pre = run[0][0]
post = rlen - run[-1][1]
if pre < 0:
print '** ISI error: first stimulus of run %d at negative time %s'%\
(rind+1, run[0][0])
errs += 1
if errs > max_errs:
print '** bailing...'
return 1
# init accumulation vars
stimes = [run[0][1] - run[0][0]]
itimes = []
# for each following index, update stim and isi times
# (check for bad overlap)
for sind in range(1, len(run)):
if run[sind][0] < run[sind - 1][1]:
print '** ISI error: stimuli overlap at run %d, time %s' % \
(rind+1, run[sind][0])
errs += 1
if errs > max_errs:
print '** bailing...'
return 1
stimes.append(run[sind][1] - run[sind][0])
itimes.append(run[sind][0] - run[sind - 1][1])
# store results
all_stim.append(stimes)
all_isi.append(itimes)
pre_time.append(pre)
post_time.append(post)
run_time.append(rlen)
if errs > 0: return 1
# tally the results
rtot_stim = []
rtot_isi = []
rtot_rest = []
stim_list = []
isi_list = []
nstim_list = []
for rind in range(self.nrows):
rtot_stim.append(UTIL.loc_sum(all_stim[rind]))
rtot_rest.append(pre_time[rind] + UTIL.loc_sum(all_isi[rind]) +
post_time[rind])
rtot_isi.append(UTIL.loc_sum(all_isi[rind]))
stim_list.extend(all_stim[rind])
isi_list.extend(all_isi[rind])
nstim_list.append(len(all_stim[rind]))
if mesg: mstr = '(%s) ' % mesg
else: mstr = ''
print '\nISI statistics %s:\n' % mstr
print ' total per run'
print ' ------ ------------------------------'
print ' total time %6.1f %s' % \
(UTIL.loc_sum(run_time), float_list_string(run_time, ndec=1))
print ' total time: stim %6.1f %s' % \
(UTIL.loc_sum(rtot_stim),float_list_string(rtot_stim,7,ndec=1))
print ' total time: rest %6.1f %s' % \
(UTIL.loc_sum(rtot_rest),float_list_string(rtot_rest,7,ndec=1))
print ''
print ' rest: total isi %6.1f %s' % \
(UTIL.loc_sum(rtot_isi), float_list_string(rtot_isi,7,ndec=1))
print ' rest: pre stim %6.1f %s' % \
(UTIL.loc_sum(pre_time), float_list_string(pre_time,7,ndec=1))
print ' rest: post stim %6.1f %s' % \
(UTIL.loc_sum(post_time),float_list_string(post_time,7,ndec=1))
print ''
print ' num stimuli %6d %s' % \
(UTIL.loc_sum(nstim_list), float_list_string(nstim_list,7,ndec=0))
print '\n'
print ' min mean max stdev'
print ' ------- ------- ------- -------'
print ' rest: pre-stim %7.3f %7.3f %7.3f %7.3f' % \
(UTIL.min_mean_max_stdev(pre_time))
print ' rest: post-stim %7.3f %7.3f %7.3f %7.3f' % \
(UTIL.min_mean_max_stdev(post_time))
print ''
for ind in range(self.nrows):
m0, m1, m2, s = UTIL.min_mean_max_stdev(all_isi[ind])
print ' rest: run #%d ISI %7.3f %7.3f %7.3f %7.3f' % \
(ind, m0, m1, m2, s)
print ''
print ' all runs: ISI %7.3f %7.3f %7.3f %7.3f' % \
(UTIL.min_mean_max_stdev(isi_list))
print ' all runs: stimuli %7.3f %7.3f %7.3f %7.3f' % \
(UTIL.min_mean_max_stdev(stim_list))
print ''
# and possibly print out offset info
if tr > 0: self.show_TR_offset_stats(tr, '')
# maybe write all rest durations
if rest_file:
all_rest = copy.deepcopy(all_isi)
for run, rest in enumerate(all_rest):
rest[:0] = [pre_time[run]]
rest.append(post_time[run])
UTIL.write_to_timing_file(all_rest, rest_file)
# clean up, just to be kind
del (all_stim)
del (all_isi)
del (pre_time)
del (post_time)
del (run_time)
del (rtot_stim)
del (rtot_isi)
del (rtot_rest)
del (stim_list)
del (isi_list)
del (nstim_list)
del (scopy)
del (tdata)