def get_laser_train_psth_by_trial(h5, clu, bin_size,
amplitude='',
onset_delay=None,
n_pulses=-1,
time_window_ms=1000,
pre_pad_ms=500,
include_odor_trials=False,
skip_last_trials=0,
*args, **kwargs):
"""
:param h5:
:param clu:
:param amplitude:
:param onset_delay:
:param time_window_ms:
:param pre_pad_ms:
:param args:
:param kwargs:
:return: this is returning both the psth and the baseline psths!!
"""
rstrs = get_laser_train_rasters(h5, clu, amplitude=amplitude, onset_delay=onset_delay, n_pulses=n_pulses,
time_window_ms=time_window_ms, pre_pad_ms=pre_pad_ms,
include_odor_trials=include_odor_trials, skip_last_trials=skip_last_trials,
*args, **kwargs)
time_arrays = []
spike_arrays = []
for ras in rstrs:
spike_array, time_array = make_spike_array(ras, bin_size, -pre_pad_ms, time_window_ms-pre_pad_ms)
spike_arrays.append(spike_array)
time_arrays.append(time_array)
return spike_arrays, time_arrays
def get_pre_odor_baseline_psths(h5, clu, odor, bin_size, n_sniffs=5,
include_laser_trials=False,
time_window_ms=1000,
pre_pad_ms=0,
skip_last_trials=0):
"""
Gets the first inhalations before every finalvalve opening and averages them all to get a baseline psth.
:param h5:
:param clu:
:param bin_size:
:param time_window_ms:
:param pre_pad_ms:
:return:
"""
pre_pad_samples = np.int(pre_pad_ms * h5.root.events._v_attrs['sample_rate_Hz'] / 1000.)
sniff_events = h5.root.events.sniff.inh_events
sniff_starts = sniff_events[:, 0]
fv_events = find_odor_events(h5, odor,
include_laser_trials=include_laser_trials,
skip_last_trials=skip_last_trials)
starts = []
for fv_ev in fv_events:
fv_start = fv_ev[0]
for i_sn in xrange(1, n_sniffs + 1):
last_inh = sniff_starts[sniff_starts < fv_start][-i_sn]
starts.append(last_inh)
starts = np.array(starts)
rasters = get_rasters(h5, clu, starts - pre_pad_samples, time_window_ms, convert_to_ms=True)
rasters -= pre_pad_ms
spike_array, time_array = make_spike_array(rasters, bin_size, -pre_pad_ms, time_window_ms-pre_pad_ms)
# psths = np.sum(spike_array, axis=1)
n_trials = len(starts)
psths_hz = (1000 / bin_size) * spike_array
return psths_hz, time_array, n_trials
def get_odor_psth(h5, clu, odor, odor_conc, bin_size,
time_window_ms=1000,
pre_pad_ms=0,
skip_last_trials=0,
*args, **kwargs):
"""
Returns psth for all trials in which odor and concentration are met. Raster time 0 is the start of the first
inhalation following odor onset.
PSTH is not normalized or smoothed (ie it is simply a sum of the total number of spikes that for each bin across
all odor events in the h5.
:param h5:
:param clu:
:param odor:
:param odor_conc:
:param bin_size:
:param time_window_ms:
:param pre_pad_ms:
:return:
"""
rasters = get_odor_rasters(h5, clu, odor, odor_conc,
time_window_ms=time_window_ms,
pre_pad_ms=pre_pad_ms,
skip_last_trials=skip_last_trials,
*args, **kwargs)
spike_array, time_array = make_spike_array(rasters, bin_size, -pre_pad_ms, time_window_ms-pre_pad_ms)
psth = np.sum(spike_array, axis=1)
n_trials = spike_array.shape[1]
psth_hz = (1000 / bin_size) * psth / n_trials
return psth_hz, time_array, n_trials
def get_laser_train_psth(h5,
clu,
bin_size,
amplitude='',
onset_delay=None,
n_pulses=-1,
time_window_ms=1000,
pre_pad_ms=500,
include_odor_trials=False,
skip_last_trials=0,
*args,
**kwargs):
"""
:param h5:
:param clu:
:param amplitude:
:param onset_delay:
:param time_window_ms:
:param pre_pad_ms:
:param args:
:param kwargs:
:return: this is returning both the psth and the baseline psths!!
"""
rstrs = get_laser_train_rasters(h5,
clu,
amplitude=amplitude,
onset_delay=onset_delay,
n_pulses=n_pulses,
time_window_ms=time_window_ms,
pre_pad_ms=pre_pad_ms,
include_odor_trials=include_odor_trials,
skip_last_trials=skip_last_trials,
*args,
**kwargs)
time_arrays = []
spike_arrays = []
n_trialss = []
psths = []
for ras in rstrs:
spike_array, time_array = make_spike_array(ras, bin_size, -pre_pad_ms,
time_window_ms - pre_pad_ms)
spike_arrays.append(spike_array)
time_arrays.append(time_array)
n_trials = spike_array.shape[1]
n_trialss.append(n_trials)
psth = np.sum(spike_array, axis=1)
psth_hz = (1000 / bin_size) * psth / n_trials
psths.append(psth_hz)
return psths, time_arrays, n_trialss