def _construct_stimulus(self, stimulus, pos, line_color, fill_color,
stimuli_type):
if stimuli_type == FeedbackType.IMAGE:
image_stim = visual.ImageStim(win=self.display,
image=stimulus,
mask=None,
pos=pos,
ori=0.0)
image_stim.size = resize_image(stimulus, self.display.size,
self.height_stim)
return image_stim
if stimuli_type == FeedbackType.TEXT:
return visual.TextStim(win=self.display,
font=self.font_stim,
text=stimulus,
height=self.height_stim,
pos=pos,
color=fill_color)
if stimuli_type == FeedbackType.SHAPE:
return visual.Rect(fillColor=fill_color,
win=self.display,
width=self.width_stim,
height=self.height_stim,
lineColor=line_color,
pos=(self.pos_stim),
lineWidth=self.feedback_line_width,
ori=0.0)
def _generate_inquiry(self):
"""Generate inquiry.
Generate stimuli for next RSVP inquiry.
"""
stim_info = []
for idx in range(len(self.stimuli_inquiry)):
current_stim = {}
# turn ms timing into frames! Much more accurate!
current_stim['time_to_present'] = int(self.stimuli_timing[idx] *
self.refresh_rate)
# check if stimulus needs to use a non-default size
if self.size_list_sti:
this_stimuli_size = self.size_list_sti[idx]
else:
this_stimuli_size = self.stimuli_height
# Set the Stimuli attrs
if self.stimuli_inquiry[idx].endswith('.png'):
current_stim['sti'] = self.create_stimulus(
mode='image', height_int=this_stimuli_size)
current_stim['sti'].image = self.stimuli_inquiry[idx]
current_stim['sti'].size = resize_image(
current_stim['sti'].image, current_stim['sti'].win.size,
this_stimuli_size)
current_stim['sti_label'] = path.splitext(
path.basename(self.stimuli_inquiry[idx]))[0]
else:
# text stimulus
current_stim['sti'] = self.create_stimulus(
mode='text', height_int=this_stimuli_size)
txt = self.stimuli_inquiry[idx]
# customize presentation of space char.
current_stim[
'sti'].text = txt if txt != SPACE_CHAR else self.space_char
current_stim['sti'].color = self.stimuli_colors[idx]
current_stim['sti_label'] = txt
# test whether the word will be too big for the screen
text_width = current_stim['sti'].boundingBox[0]
if text_width > self.window.size[0]:
monitor_width, monitor_height = get_screen_resolution()
text_height = current_stim['sti'].boundingBox[1]
# If we are in full-screen, text size in Psychopy norm units
# is monitor width/monitor height
if self.window.size[0] == monitor_width:
new_text_width = monitor_width / monitor_height
else:
# If not, text width is calculated relative to both
# monitor size and window size
new_text_width = (self.window.size[1] / monitor_height
) * (monitor_width / monitor_height)
new_text_height = (text_height *
new_text_width) / text_width
current_stim['sti'].height = new_text_height
stim_info.append(current_stim)
return stim_info
def update_task_state(
self,
image_path,
task_height,
rect_color,
window_size,
is_word):
""" Updates task state of Icon to Icon/Word Matching Task by changing the
image or text displayed at the top of the screen.
Also updates rectangle size.
Args:
image_path(str): the path to the image to be displayed
task_height(int): the height of the task image
rect_color(str): the color of the rectangle
window_size(tuple): The size of the window
is_word(bool): word matching task
"""
if is_word:
# Display text at top of screen if we are matching icons to words
txt = image_path if len(image_path) > 0 else ' '
tmp2 = visual.TextStim(
win=self.window, font=self.task.font, text=txt)
x_task_pos = (tmp2.boundingBox[0] * 2.2) / self.window.size[0] - 1
self.task_pos = (x_task_pos, self.task_pos[1])
self.update_task(text=txt, color_list=['white'], pos=self.task_pos)
else:
# Otherwise, display an image at the top of the screen
self.task.image = image_path
image_width, image_height = resize_image(
image_path,
window_size,
task_height)
self.target_text.pos = (
self.stim_pos[0] - image_width - 0.5,
self.stim_pos[1])
self.task.pos = (
self.task_pos[0] + image_width * 2,
self.task_pos[1] - image_width / 2)
self.task.size = (image_width * 2, image_height * 2)
self.rect_drawn_frames = 0
self.rect.width = image_width / task_height * self.stim_height
self.rect.height = image_height / task_height * self.stim_height
self.rect.lineColor = rect_color
def wait_screen(self, message, color):
"""Wait Screen.
Args:
message(string): message to be displayed while waiting
"""
# Construct the wait message
wait_message = visual.TextStim(win=self.window,
font=self.stimuli_font,
text=message,
height=.1,
color=color,
pos=(0, -.5),
wrapWidth=2,
colorSpace='rgb',
opacity=1,
depth=-6.0)
# Try adding our BCI logo. Pass if not found.
try:
wait_logo = visual.ImageStim(
self.window,
image='bcipy/static/images/gui_images/bci_cas_logo.png',
pos=(0, .5),
mask=None,
ori=0.0)
wait_logo.size = resize_image(
'bcipy/static/images/gui_images/bci_cas_logo.png',
self.window.size, 1)
wait_logo.draw()
except Exception:
self.logger.debug('Cannot load logo image')
pass
# Draw and flip the screen.
wait_message.draw()
self.window.flip()
def _calibration_trigger(experiment_clock: core.Clock,
trigger_type: str='sound',
trigger_name: str='calibration_trigger',
display=None,
on_trigger=None) -> List[tuple]:
"""Calibration Trigger.
Outputs triggers for the purpose of calibrating data and stimuli.
This is an ongoing difficulty between OS, DAQ devices and stimuli type. This
code aims to operationalize the approach to finding the correct DAQ samples in
relation to our trigger code.
PARAMETERS
---------
experiment_clock(clock): clock with getTime() method, which is used in the code
to report timing of stimuli
trigger_type(string): type of trigger that is desired (sound, image, etc)
display(DisplayWindow): a window that can display stimuli. Currently, a Psychopy window.
on_trigger(function): optional callback; if present gets called
when the calibration trigger is fired; accepts a single
parameter for the timing information.
Return:
timing(array): timing values for the calibration triggers to be written to trigger file or
used to calculate offsets.
"""
trigger_callback = TriggerCallback()
# If sound trigger is selected, output calibration tones
if trigger_type == SOUND_TYPE:
import sounddevice as sd
import soundfile as sf
play_sound(
sound_file_path='bcipy/static/sounds/1k_800mV_20ms_stereo.wav',
dtype='float32',
track_timing=True,
sound_callback=trigger_callback,
sound_load_buffer_time=0.5,
experiment_clock=experiment_clock,
trigger_name='calibration_trigger')
elif trigger_type == IMAGE_TYPE:
if display:
calibration_box = visual.ImageStim(
win=display,
image='bcipy/static/images/testing_images/white.png',
pos=(-.5, -.5),
mask=None,
ori=0.0)
calibration_box.size = resize_image(
'bcipy/static/images/testing_images/white.png',
display.size, 0.75)
display.callOnFlip(trigger_callback.callback, experiment_clock, trigger_name)
if on_trigger is not None:
display.callOnFlip(on_trigger, trigger_name)
presentation_time = int(1 * display.getActualFrameRate())
for num_frames in range(presentation_time):
calibration_box.draw()
display.flip()
else:
raise Exception(
'Display object required for calibration with images!')
else:
raise Exception('Trigger type not implemented for Calibration yet!')
return trigger_callback.timing
def do_sequence(self):
"""Do Sequence.
Animates a sequence of flashing letters to achieve RSVP.
"""
# init an array for timing information
timing = []
if self.first_run:
# play a sequence start sound to help orient triggers
first_stim_timing = _calibration_trigger(
self.experiment_clock,
trigger_type=self.trigger_type, display=self.window,
on_trigger=self.marker_writer.push_marker)
timing.append(first_stim_timing)
self.first_stim_time = first_stim_timing[-1]
self.first_run = False
# do the sequence
for idx in range(len(self.stimuli_sequence)):
# set a static period to do all our stim setting.
# will warn if ISI value is violated.
self.staticPeriod.start(self.static_time)
# turn ms timing into frames! Much more accurate!
self.time_to_present = int(self.stimuli_timing[idx] * self.refresh_rate)
# check if stimulus needs to use a non-default size
if self.size_list_sti:
this_stimuli_size = self.size_list_sti[idx]
else:
this_stimuli_size = self.stimuli_height
# Set the Stimuli attrs
if self.stimuli_sequence[idx].endswith('.png'):
self.sti = self.create_stimulus(mode='image', height_int=this_stimuli_size)
self.sti.image = self.stimuli_sequence[idx]
self.sti.size = resize_image(self.sti.image, self.sti.win.size, this_stimuli_size)
sti_label = path.splitext(
path.basename(self.stimuli_sequence[idx]))[0]
else:
# text stimulus
self.sti = self.create_stimulus(mode='text', height_int=this_stimuli_size)
txt = self.stimuli_sequence[idx]
# customize presentation of space char.
self.sti.text = txt if txt != SPACE_CHAR else self.space_char
self.sti.color = self.stimuli_colors[idx]
sti_label = txt
# test whether the word will be too big for the screen
text_width = self.sti.boundingBox[0]
if text_width > self.window.size[0]:
info = get_system_info()
text_height = self.sti.boundingBox[1]
# If we are in full-screen, text size in Psychopy norm units
# is monitor width/monitor height
if self.window.size[0] == info['RESOLUTION'][0]:
new_text_width = info['RESOLUTION'][0] / info['RESOLUTION'][1]
else:
# If not, text width is calculated relative to both
# monitor size and window size
new_text_width = (
self.window.size[1] / info['RESOLUTION'][1]) * (
info['RESOLUTION'][0] / info['RESOLUTION'][1])
new_text_height = (text_height * new_text_width) / text_width
self.sti.height = new_text_height
# End static period
self.staticPeriod.complete()
# Reset the timing clock to start presenting
self.window.callOnFlip(self.trigger_callback.callback, self.experiment_clock, sti_label)
self.window.callOnFlip(self.marker_writer.push_marker, sti_label)
if idx == 0 and callable(self.first_stim_callback):
self.first_stim_callback(self.sti)
# Draw stimulus for n frames
for _n_frames in range(self.time_to_present):
self.sti.draw()
self.draw_static()
self.window.flip()
# append timing information
if self.is_txt_stim:
timing.append(self.trigger_callback.timing)
else:
timing.append(self.trigger_callback.timing)
self.trigger_callback.reset()
# draw in static and flip once more
self.draw_static()
self.window.flip()
return timing
