def return_bar_values(nd, lickstart, lickstop, resolution):
# local function, determines lists of times of entry and exit for plot
session = initiate_lickwell_network(nd) # Initialize session
speed_list = []
spike_rate_list = []
for lick in session.licks:
if lick.lickwell == 1:
speeds = []
spike_rates = []
timeslice = session[int(lick.time + lickstart):int(lick.time +
lickstop)]
# determine what percentage of licks are in range for histogram
for i in range(0, len(timeslice.position_x), resolution):
interval = timeslice[i:i + resolution]
speed = np.average(interval.speed)
speeds.append(speed)
spikes = [a for li in interval.spikes
for a in li] # flatten all spikes in time range
spike_rates.append(len(spikes) / nd.n_neurons)
spike_rate_list.append(spike_rates)
speed_list.append(speeds)
speed_list = np.average(speed_list, axis=0)
spike_rate_list = np.average(spike_rate_list, axis=0)
return speed_list, spike_rate_list
def timehistogram_bar_values(nd,lickstart,lickstop,searchradius,interval):
# Determines lists of times of entry and exit for plot
entry_list = []
exit_list = []
lickids = []
session = initiate_lickwell_network(nd) # Initialize session
for lick in session.licks:
if lick.lickwell == 1:
timeslice = session[int(lick.time+lickstart):int(lick.time+lickstop)]
enter_time = None
exit_time = None
for time, position in enumerate(timeslice.position_x):
is_before_lick = (time<-lickstart) # determines if current time is before lick event
if not is_before_lick and enter_time is None: # sets time when rat enters vicinity of well 1
enter_time = 0
print("Warning: there seems to be a problem with the position of the rat during a lick at well 1")
if (position < searchradius or time == lickstart) and enter_time is None: # determine when rat enters area
enter_time = time
if position>searchradius and exit_time is None:
if is_before_lick: # rat leaves area before lick
enter_time = None
else: # set exit time
exit_time = time
if exit_time is None and time == lickstop-lickstart-1:
print("Warning: the rat does not leave the vicinity inside the given time range")
exit_time = lickstop-lickstart
if enter_time is not None and exit_time is not None:
entry_list.append(enter_time+lickstart)
exit_list.append(exit_time+lickstart)
lickids.append(lick.lick_id)
break
# determine what percentage of licks are in range for histogram
counter_list = []
ind_labels = []
for i in range(lickstart,lickstop+1,interval):
counter = 0
for j in range(0,len(lickids)):
if i>=entry_list[j] and i<=exit_list[j]:
counter += 1
counter_list.append(counter/len(lickids))
ind_labels.append(i)
return lickids,entry_list,exit_list,counter_list,ind_labels
number_of_bins=10,
)
print_metric_details(
"C:/Users/NN/Desktop/Master/experiments/Experiments for thesis 2/well decoding/hc/",
1)
print_metric_details(
"C:/Users/NN/Desktop/Master/experiments/Experiments for thesis 2/well decoding/hc/",
-1)
print_metric_details(
"C:/Users/NN/Desktop/Master/experiments/Experiments for thesis 2/well decoding/pfc/",
1)
print_metric_details(
"C:/Users/NN/Desktop/Master/experiments/Experiments for thesis 2/well decoding/pfc/",
-1)
session = initiate_lickwell_network(nd) # Initialize session
X, y, nd, session, = lickwells_io(session,
nd,
excluded_wells=[1],
shift=nd.initial_timeshift,
target_is_phase=True,
lickstart=0,
lickstop=5000)
# counts = [0,0,0,0,0]
# for lick in y:
# counts[lick.target-1] +=1
# print("&",counts[1], "&", counts[2], "&", counts[3], "&", counts[4], "&", max(counts), "\\\ \hline")
#
# print("&",counts[1]*40, "&", counts[2]*40, "&", counts[3]*40, "&", counts[4]*40, "&", max(counts)*40, "\\\ \hline")
def guiRun_network():
nd = Net_data(
model_path=tbx_model_path.value,
raw_data_path=tbx_raw_data_path.value,
dropout=float(tbx_dropout.value),
filtered_data_path=tbx_filtered_data_path.value,
stride=int(tbx_stride.value),
epochs=int(tbx_epochs.value),
from_raw_data=bool(cbo_from_raw_data.value == "True"),
evaluate_training=bool(cbo_evaluate_training.value == "True"),
session_filter=Filter(func=hann,
search_radius=int(tbx_search_radius.value),
step_size=int(tbx_step_size.value)),
time_shift_steps=int(tbx_time_shift_steps.value),
shuffle_data=bool(cbo_shuffle_data.value == "True"),
shuffle_factor=int(tbx_shuffle_factor.value),
time_shift_iter=int(tbx_time_shift_iter.value),
initial_timeshift=int(tbx_initial_timeshift.value),
metric_iter=int(tbx_metric_iter.value),
batch_size=int(tbx_batch_size.value),
slice_size=int(tbx_slice_size.value),
x_max=int(tbx_x_max.value),
y_max=int(tbx_y_max.value),
x_min=int(tbx_x_min.value),
y_min=int(tbx_y_min.value),
x_step=int(tbx_x_step.value),
y_step=int(tbx_y_step.value),
early_stopping=bool(cbo_early_stopping.value == "True"),
naive_test=bool(cbo_naive_test.value == "True"),
valid_ratio=float(tbx_valid_ratio.value),
testing_ratio=float(tbx_testing_ratio.value),
k_cross_validation=int(tbx_k_cross_validation.value),
load_model=bool(cbo_load_model.value == "True"),
train_model=bool(cbo_train_model.value == "True"),
keep_neurons=-1,
neurons_kept_factor=float(tbx_neurons_kept_factor.value),
lw_classifications=None
if not tbx_lw_classifications.value.isnumeric() else int(
tbx_lw_classifications.value),
lw_normalize=bool(cboLw_normalize.value == "True"),
lw_differentiate_false_licks=bool(
cbo_lw_differentiate_false_licks.value == "True"),
num_wells=int(tbx_num_wells.value),
metric=tbx_metric.value,
valid_licks=None
if tbx_valid_licks.value == 'None' else tbx_valid_licks.value,
filter_tetrodes=None
if tbx_filter_tetrodes.value == 'None' else tbx_filter_tetrodes.value,
phases=None if tbx_phases.value == 'None' else tbx_phases.value,
phase_change_ids=None if tbx_phase_change_ids.value == 'None' else
tbx_phase_change_ids.value,
number_of_bins=int(tbx_number_of_bins.value),
start_time_by_lick_id=None
if not tbx_start_time_by_lick_id.value.isnumeric() else int(
tbx_start_time_by_lick_id.value),
behavior_component_filter=None if cbo_behavior_component.value
== 'None' else cbo_behavior_component.value)
if tbx_metric.value == "map":
session = initiate_network(nd)
run_network(nd, session)
else:
session = initiate_lickwell_network(nd) # Initialize session
X, y, nd, session, = lickwells_io(session,
nd,
_excluded_wells=[1],
shift=nd.initial_timeshift,
target_is_phase=False,
lickstart=0,
lickstop=5000)
pass