def generate_stimuli(self):
"""Generates the sequences to be presented.
Returns:
--------
tuple(
samples[list[list[str]]]: list of sequences
timing(list[list[float]]): list of timings
color(list(list[str])): list of colors)
"""
return random_rsvp_calibration_seq_gen(self.alp,
stim_number=self.stim_number,
stim_length=self.stim_length,
timing=self.timing,
is_txt=self.rsvp.is_txt_stim,
color=self.color)
def test_random_sequence_gen(self):
"""Test generation of random sequences"""
alp = [
'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M',
'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z',
'<', '_'
]
num_sti = 10
len_sti = 10
seqs, seq_timings, seq_colors = random_rsvp_calibration_seq_gen(
alp,
timing=[0.5, 1, 0.2],
color=['green', 'red', 'white'],
num_sti=num_sti,
len_sti=len_sti,
is_txt=True)
self.assertEqual(
len(seqs), num_sti,
'Should have produced the correct number of sequences')
self.assertEqual(len(seq_timings), num_sti)
self.assertEqual(len(seq_colors), num_sti)
seq_strings = []
for seq in seqs:
self.assertEqual(
len(seq), len_sti + 2,
('Sequence should include the correct number of choices as ',
'well as the target and cross.'))
choices = seq[2:]
self.assertEqual(len_sti, len(set(choices)),
'All choices should be unique')
# create a string of the options
seq_strings.append(''.join(choices))
self.assertEqual(len(seqs), len(set(seq_strings)),
'All sequences should be different')
def execute(self):
self.logger.debug(f'Starting {self.name()}!')
run = True
# Check user input to make sure we should be going
if not get_user_input(self.rsvp,
self.wait_screen_message,
self.wait_screen_message_color,
first_run=True):
run = False
# Begin the Experiment
while run:
# Get random sequence information given stimuli parameters
(stimuli_elements, timing_sti,
color_sti) = random_rsvp_calibration_seq_gen(
self.alp,
stim_number=self.stim_number,
stim_length=self.stim_length,
timing=self.timing,
is_txt=self.is_txt_stim,
color=self.color)
import pdb
pdb.set_trace()
(task_text, task_color) = get_task_info(self.stim_number,
self._task.task_info_color)
# Execute the RSVP sequences
for sequence_idx in range(len(task_text)):
# check user input to make sure we should be going
if not get_user_input(self.rsvp, self.wait_screen_message,
self.wait_screen_message_color):
break
if self.enable_breaks:
pause_calibration(self.window, self.rsvp, sequence_idx,
self.parameters)
# update task state
self.rsvp.update_task_state(
text=task_text[sequence_idx],
color_list=task_color[sequence_idx])
# Draw and flip screen
self.rsvp.draw_static()
self.window.flip()
# Get height
self.rsvp.sti.height = self.stimuli_height
# Schedule a sequence
self.rsvp.stimuli_sequence = stimuli_elements[sequence_idx]
# check if text stimuli or not for color information
if self.is_txt_stim:
self.rsvp.stimuli_colors = color_sti[sequence_idx]
self.rsvp.stimuli_timing = timing_sti[sequence_idx]
# Wait for a time
core.wait(self._task.buffer_val)
# Do the sequence
last_sequence_timing = self.rsvp.do_sequence()
# Write triggers for the sequence
_write_triggers_from_sequence_calibration(
last_sequence_timing, self._task.trigger_file)
self.logger.info('[Feedback] Getting Decision')
position = self._get_feedback_decision(last_sequence_timing)
self.logger.info(
f'[Feedback] Administering feedback position {position}')
timing = self.visual_feedback.administer(position=position)
# Wait for a time
core.wait(self._task.buffer_val)
# Set run to False to stop looping
run = False
# Say Goodbye!
self.rsvp.text = trial_complete_message(self.window, self.parameters)
self.rsvp.draw_static()
self.window.flip()
# Give the system time to process
core.wait(self._task.buffer_val)
if self.daq.is_calibrated:
_write_triggers_from_sequence_calibration(
['offset', self.daq.offset],
self._task.trigger_file,
offset=True)
# Close this sessions trigger file and return some data
self._task.trigger_file.close()
# Wait some time before exiting so there is trailing eeg data saved
core.wait(self._task.eeg_buffer)
return self.file_save