def run(self):
experiment = self.pipeline.experiment
events = self.get_passed_object(experiment+'_events')
tal_info = self.get_passed_object('tal_info')
prob_pre = self.get_passed_object('prob_pre')
prob_diff = self.get_passed_object('prob_diff')
ctrl_prob_pre = self.get_passed_object('ctrl_prob_pre')
ctrl_prob_diff0 = self.get_passed_object('ctrl_prob_diff0')
ctrl_prob_diff250 = ctrl_prob_diff500 = ctrl_prob_diff1000 = None
try:
ctrl_prob_diff250 = self.get_passed_object('ctrl_prob_diff250')
except:
pass
try:
ctrl_prob_diff500 = self.get_passed_object('ctrl_prob_diff500')
except:
pass
try:
ctrl_prob_diff1000 = self.get_passed_object('ctrl_prob_diff1000')
except:
pass
sessions = np.unique(events.session)
self.pass_object('NUMBER_OF_SESSIONS', len(sessions))
self.pass_object('NUMBER_OF_ELECTRODES', len(tal_info))
session_data = []
all_durs_ev = np.array([])
all_amps_ev = np.array([])
all_freqs_ev = np.array([])
all_burfs_ev = np.array([])
all_durs = np.array([])
all_amps = np.array([])
all_freqs = np.array([])
all_burfs = np.array([])
session_summary_array = []
prob_array_idx = 0
for session in sessions:
session_summary = SessionSummary()
session_summary.sess_num = session
session_events = events[events.session == session]
n_sess_events = len(session_events)
timestamps = session_events.mstime
first_time_stamp = np.min(timestamps)
last_time_stamp = np.max(timestamps)
session_length = '%.2f' % ((last_time_stamp - first_time_stamp) / 60000.0)
session_date = time.strftime('%d-%b-%Y', time.localtime(last_time_stamp/1000))
session_data.append([session, session_date, session_length])
session_name = 'Sess%02d' % session
stim_tag = session_events[0].stimAnodeTag + '-' + session_events[0].stimCathodeTag
isi_min = np.nanmin(session_events.isi)
isi_max = np.nanmax(session_events.isi)
isi_mid = (isi_max+isi_min) / 2.0
isi_halfrange = isi_max - isi_mid
print 'Session =', session_name, ' StimTag =', stim_tag, ' ISI =', isi_mid, '+/-', isi_halfrange
durs_ev = session_events.pulse_duration
amps_ev = session_events.amplitude
freqs_ev = session_events.pulse_frequency
burfs_ev = session_events.burst_frequency
all_durs_ev = np.hstack((all_durs_ev, durs_ev))
all_amps_ev = np.hstack((all_amps_ev, amps_ev))
all_freqs_ev = np.hstack((all_freqs_ev, freqs_ev))
all_burfs_ev = np.hstack((all_burfs_ev, burfs_ev))
durs = np.unique(durs_ev)
amps = np.unique(amps_ev)
freqs = np.unique(freqs_ev)
burfs = np.unique(burfs_ev)
session_summary.name = session_name
session_summary.length = session_length
session_summary.date = session_date
session_summary.stimtag = stim_tag
session_summary.isi_mid = isi_mid
session_summary.isi_half_range = isi_halfrange
session_prob_pre = prob_pre[prob_array_idx:prob_array_idx+n_sess_events]
session_prob_diff = prob_diff[prob_array_idx:prob_array_idx+n_sess_events]
session_ctrl_prob_pre = ctrl_prob_pre
session_ctrl_prob_diff = ctrl_prob_diff1000 if durs[-1]==1000 else ctrl_prob_diff500 if durs[-1]==500 else ctrl_prob_diff250
all_durs = np.hstack((all_durs, durs))
all_amps = np.hstack((all_amps, amps))
all_freqs = np.hstack((all_freqs, freqs))
all_burfs = np.hstack((all_burfs, burfs))
ev_vals = None
param_grid = None
if experiment == 'PS1':
ev_vals = [freqs_ev, durs_ev]
param_grid = [freqs, durs]
session_summary.constant_name = 'Amplitude'
session_summary.constant_value = amps[0]
session_summary.constant_unit = 'mA'
session_summary.parameter1 = 'Pulse Frequency'
session_summary.parameter2 = 'Duration'
elif experiment == 'PS2':
ev_vals = [freqs_ev, amps_ev]
param_grid = [freqs, amps]
session_summary.constant_name = 'Duration'
session_summary.constant_value = durs[-1]
session_summary.constant_unit = 'ms'
session_summary.parameter1 = 'Pulse Frequency'
session_summary.parameter2 = 'Amplitude'
elif experiment == 'PS3':
ev_vals = [freqs_ev, burfs_ev]
param_grid = [freqs, burfs]
session_summary.constant_name = 'Amplitude'
session_summary.constant_value = amps[0]
session_summary.constant_unit = 'mA'
session_summary.parameter1 = 'Pulse Frequency'
session_summary.parameter2 = 'Burst Frequency'
delta_stats = DeltaStats(2, ev_vals, param_grid, session_prob_pre, session_prob_diff, session_ctrl_prob_pre, session_ctrl_prob_diff, 1.0/3.0)
delta_stats.run()
anova = anova_test(ev_vals, param_grid, session_prob_diff)
if anova is not None:
session_summary.anova_fvalues = anova[0]
session_summary.anova_pvalues = anova[1]
data_point_indexes_left = np.arange(1,len(param_grid[0])+2)
data_point_indexes_right = np.arange(1,len(param_grid[1])+2)
# computting y axis limits
min_plot, max_plot = delta_stats.y_range()
ylim = [min_plot-0.1*(max_plot-min_plot), max_plot+0.1*(max_plot-min_plot)]
x_tick_labels = ['CONTROL'] + [x if x>0 else 'PULSE' for x in param_grid[0]]
session_summary.plot_data_dict[(0,0)] = PlotData(x=data_point_indexes_left, y=delta_stats.mean_all[0], yerr=delta_stats.stdev_all[0], x_tick_labels=x_tick_labels, ylim=ylim)
session_summary.plot_data_dict[(1,0)] = PlotData(x=data_point_indexes_left, y=delta_stats.mean_low[0], yerr=delta_stats.stdev_low[0], x_tick_labels=x_tick_labels, ylim=ylim)
session_summary.plot_data_dict[(2,0)] = PlotData(x=data_point_indexes_left, y=delta_stats.mean_high[0], yerr=delta_stats.stdev_high[0], x_tick_labels=x_tick_labels, ylim=ylim)
x_tick_labels = ['CONTROL'] + list(param_grid[1])
session_summary.plot_data_dict[(0,1)] = PlotData(x=data_point_indexes_right, y=delta_stats.mean_all[1], yerr=delta_stats.stdev_all[1], x_tick_labels=x_tick_labels, ylim=ylim)
session_summary.plot_data_dict[(1,1)] = PlotData(x=data_point_indexes_right, y=delta_stats.mean_low[1], yerr=delta_stats.stdev_low[1], x_tick_labels=x_tick_labels, ylim=ylim)
session_summary.plot_data_dict[(2,1)] = PlotData(x=data_point_indexes_right, y=delta_stats.mean_high[1], yerr=delta_stats.stdev_high[1], x_tick_labels=x_tick_labels, ylim=ylim)
session_summary_array.append(session_summary)
prob_array_idx += len(session_events)
self.pass_object('SESSION_DATA', session_data)
self.pass_object('session_summary_array', session_summary_array)
isi_min = np.nanmin(events.isi)
isi_max = np.nanmax(events.isi)
isi_mid = (isi_max+isi_min) / 2.0
isi_halfrange = isi_max - isi_mid
print 'ISI =', isi_mid, '+/-', isi_halfrange
self.pass_object('CUMULATIVE_ISI_MID',isi_mid)
self.pass_object('CUMULATIVE_ISI_HALF_RANGE',isi_halfrange)
durs = np.unique(all_durs)
amps = np.unique(all_amps)
freqs = np.unique(all_freqs)
burfs = np.unique(all_burfs)
ctrl_prob_diff = ctrl_prob_diff1000 if durs[-1]==1000 else ctrl_prob_diff500 if durs[-1]==500 else ctrl_prob_diff250
ev_vals = None
param_grid = None
if experiment == 'PS1':
ev_vals = [all_freqs_ev, all_durs_ev]
param_grid = [freqs, durs]
self.pass_object('CUMULATIVE_PARAMETER1', 'Pulse Frequency')
self.pass_object('CUMULATIVE_PARAMETER2', 'Duration')
elif experiment == 'PS2':
ev_vals = [all_freqs_ev, all_amps_ev]
param_grid = [freqs, amps]
self.pass_object('CUMULATIVE_PARAMETER1', 'Pulse Frequency')
self.pass_object('CUMULATIVE_PARAMETER2', 'Amplitude')
elif experiment == 'PS3':
ev_vals = [all_freqs_ev, all_burfs_ev]
param_grid = [freqs, burfs]
self.pass_object('CUMULATIVE_PARAMETER1', 'Pulse Frequency')
self.pass_object('CUMULATIVE_PARAMETER2', 'Burst Frequency')
delta_stats = DeltaStats(2, ev_vals, param_grid, prob_pre, prob_diff, ctrl_prob_pre, ctrl_prob_diff, 1.0/3.0)
delta_stats.run()
data_point_indexes_left = np.arange(1,len(param_grid[0])+2)
data_point_indexes_right = np.arange(1,len(param_grid[1])+2)
# computing y axis limits
min_plot, max_plot = delta_stats.y_range()
ylim = [min_plot-0.1*(max_plot-min_plot), max_plot+0.1*(max_plot-min_plot)]
cumulative_plot_data_dict = OrderedDict()
x_tick_labels = ['CONTROL'] + [x if x>0 else 'PULSE' for x in param_grid[0]]
cumulative_plot_data_dict[(0,0)] = PlotData(x=data_point_indexes_left, y=delta_stats.mean_all[0], yerr=delta_stats.stdev_all[0], x_tick_labels=x_tick_labels, ylim=ylim)
cumulative_plot_data_dict[(1,0)] = PlotData(x=data_point_indexes_left, y=delta_stats.mean_low[0], yerr=delta_stats.stdev_low[0], x_tick_labels=x_tick_labels, ylim=ylim)
cumulative_plot_data_dict[(2,0)] = PlotData(x=data_point_indexes_left, y=delta_stats.mean_high[0], yerr=delta_stats.stdev_high[0], x_tick_labels=x_tick_labels, ylim=ylim)
x_tick_labels = ['CONTROL'] + list(param_grid[1])
cumulative_plot_data_dict[(0,1)] = PlotData(x=data_point_indexes_right, y=delta_stats.mean_all[1], yerr=delta_stats.stdev_all[1], x_tick_labels=x_tick_labels, ylim=ylim)
cumulative_plot_data_dict[(1,1)] = PlotData(x=data_point_indexes_right, y=delta_stats.mean_low[1], yerr=delta_stats.stdev_low[1], x_tick_labels=x_tick_labels, ylim=ylim)
cumulative_plot_data_dict[(2,1)] = PlotData(x=data_point_indexes_right, y=delta_stats.mean_high[1], yerr=delta_stats.stdev_high[1], x_tick_labels=x_tick_labels, ylim=ylim)
self.pass_object('cumulative_plot_data_dict', cumulative_plot_data_dict)
def run(self):
subject = self.pipeline.subject
experiment = self.pipeline.experiment
channels = self.get_passed_object('channels')
tal_info = self.get_passed_object('tal_info')
loc_info = self.get_passed_object('loc_info')
xval_output = self.get_passed_object('xval_output')
ps_table = self.get_passed_object('ps_table')
sessions = sorted(ps_table.session.unique())
self.pass_object('NUMBER_OF_SESSIONS', len(sessions))
self.pass_object('NUMBER_OF_ELECTRODES', len(channels))
thresh = xval_output[-1].jstat_thresh
self.pass_object('AUC', xval_output[-1].auc)
param1_name = param2_name = None
const_param_name = const_unit = None
if experiment == 'PS1':
param1_name = 'Pulse Frequency'
param2_name = 'Duration'
const_param_name = 'Amplitude'
const_unit = 'mA'
elif experiment == 'PS2':
param1_name = 'Pulse Frequency'
param2_name = 'Amplitude'
const_param_name = 'Duration'
const_unit = 'ms'
elif experiment == 'PS3':
param1_name = 'Burst Frequency'
param2_name = 'Pulse Frequency'
const_param_name = 'Duration'
const_unit = 'ms'
self.pass_object('CUMULATIVE_PARAMETER1', param1_name)
self.pass_object('CUMULATIVE_PARAMETER2', param2_name)
session_data = []
session_summary_array = []
for session in sessions:
ps_session_table = ps_table[ps_table.session==session]
session_summary = SessionSummary()
session_summary.sess_num = session
first_time_stamp = ps_session_table.mstime.min()
last_time_stamp = ps_session_table.mstime.max()
session_length = '%.2f' % ((last_time_stamp - first_time_stamp) / 60000.0)
session_date = time.strftime('%d-%b-%Y', time.localtime(last_time_stamp/1000))
session_data.append([session, session_date, session_length])
session_name = 'Sess%02d' % session
stim_anode_tag = ps_session_table.stimAnodeTag.values[0]
stim_cathode_tag = ps_session_table.stimCathodeTag.values[0]
stim_tag = stim_anode_tag + '-' + stim_cathode_tag
if loc_info[stim_tag] != '':
stim_tag += ' (%s)' % loc_info[stim_anode_tag]
isi_min = ps_session_table.isi.min()
isi_max = ps_session_table.isi.max()
isi_mid = (isi_max+isi_min) / 2.0
isi_halfrange = isi_max - isi_mid
print 'Session =', session_name, ' StimTag =', stim_tag, ' ISI =', isi_mid, '+/-', isi_halfrange
session_summary.name = session_name
session_summary.length = session_length
session_summary.date = session_date
session_summary.stimtag = stim_tag
session_summary.isi_mid = isi_mid
session_summary.isi_half_range = isi_halfrange
session_summary.parameter1 = param1_name
session_summary.parameter2 = param2_name
session_summary.constant_name = const_param_name
session_summary.constant_value = ps_session_table[const_param_name].unique()[0]
session_summary.constant_unit = const_unit
anova = anova_test(ps_session_table, param1_name, param2_name)
if anova is not None:
session_summary.anova_fvalues = anova[0]
session_summary.anova_pvalues = anova[1]
joblib.dump(anova, self.get_path_to_resource_in_workspace(subject + '-' + experiment + '-anova.pkl'))
session_summary.plots = delta_plot_data(ps_session_table[ps_session_table['prob_pre']<thresh], param1_name, param2_name)
session_summary_array.append(session_summary)
self.pass_object('SESSION_DATA', session_data)
self.pass_object('session_summary_array', session_summary_array)
isi_min = ps_table.isi.min()
isi_max = ps_table.isi.max()
isi_mid = (isi_max+isi_min) / 2.0
isi_halfrange = isi_max - isi_mid
print 'ISI =', isi_mid, '+/-', isi_halfrange
self.pass_object('CUMULATIVE_ISI_MID', isi_mid)
self.pass_object('CUMULATIVE_ISI_HALF_RANGE', isi_halfrange)
cumulative_plots = delta_plot_data(ps_table[ps_table['prob_pre']<thresh], param1_name, param2_name)
self.pass_object('cumulative_plots', cumulative_plots)