def main(argv):
# Constructs a sample touchscreen device with keyboard at the bottom third of the device.
device = TouchScreenKeyboardDeviceDirector.construct('device', 'device', 0, 0, 2600, 1010, 0, 0)
# Create a human and associate it with the device, so that the device knows about any body part movements.
# human = Human.create_novice(device)
human = Human.create_expert(device) # TODO: to test your implementation with an expert user, uncomment this line and comment the one above it.
phrase_textbox = device.find_descendant('phrase_textbox')
space_key = device.find_descendant(' ')
transcription_textbox = device.find_descendant('transcription_textbox')
# Reset the thumb to the space before each phrase.
human.body_parts['thumb'].location_x = space_key.top_left_x + space_key.width/2
human.body_parts['thumb'].location_y = space_key.top_left_y + space_key.height/2
# Reset the eyes to the phrase text box.
human.body_parts['eyes'].fixation_x = phrase_textbox.top_left_x + phrase_textbox.width/2
human.body_parts['eyes'].fixation_y = phrase_textbox.top_left_y + phrase_textbox.height/2
# Visualize the device interface and the position of the thumb.
device_plot = plt.figure()
ax1 = device_plot.add_subplot(111, aspect='equal')
ax1.xaxis.set_ticks(range(device.top_left_x, device.width, 200))
ax1.yaxis.set_ticks(range(device.top_left_y, device.height, 200))
device.draw(ax1)
human.draw(ax1)
plt.ylim((0, device.height))
plt.xlim((0, device.width))
ax1.set_ylim(ax1.get_ylim()[::-1])
ax1.xaxis.tick_top()
plt.show(block=True)
plt.close()
# Variables for computing average typing speed.
total_characters_count = 0
total_duration = 0.0
phrase_typing_speeds = []
phrase_typing_timestamps = []
def main(argv):
# Constructs a sample touchscreen device with keyboard at the bottom third of the device.
device = TouchScreenKeyboardDeviceDirector.construct(
'device', 'device', 0, 0, 960, 2160, 30, 270)
# Create a human and associate it with the device, so that the device knows about any body part movements.
#human = Human.create_novice(device)
human = Human.create_expert(device)
phrase_textbox = device.find_descendant('phrase_textbox')
space_key = device.find_descendant(' ')
transcription_textbox = device.find_descendant('transcription_textbox')
# Reset the thumb to the space before each phrase.
human.body_parts[
'thumb'].location_x = space_key.top_left_x + space_key.width / 2
human.body_parts[
'thumb'].location_y = space_key.top_left_y + space_key.height / 2
# Reset the eyes to the phrase text box.
human.body_parts[
'eyes'].fixation_x = phrase_textbox.top_left_x + phrase_textbox.width / 2
human.body_parts[
'eyes'].fixation_y = phrase_textbox.top_left_y + phrase_textbox.height / 2
# Visualize the device interface and the position of the thumb.
device_plot = plt.figure()
ax1 = device_plot.add_subplot(111, aspect='equal')
ax1.xaxis.set_ticks(range(device.top_left_x, device.width, 200))
ax1.yaxis.set_ticks(range(device.top_left_y, device.height, 200))
device.draw(ax1)
human.draw(ax1)
plt.ylim((0, device.height))
plt.xlim((0, device.width))
ax1.set_ylim(ax1.get_ylim()[::-1])
ax1.xaxis.tick_top()
plt.show(block=True)
plt.close()
# Variables for computing average typing speed.
total_characters_count = 0
total_duration = 0.0
phrase_typing_speeds = []
phrase_typing_timestamps = []
# For each test phrase in the file compute the duration it takes to type that phrase.
with open('data/phrases.txt') as phrase_set:
for phrase in phrase_set:
phrase_typing_timestamps.append(
total_duration / (60.0 * 1000.0)
) # start time for this phrase since the fist time typing in minutes.
phrase = phrase.lower().rstrip()
phrase_textbox = device.get_descendant('phrase_textbox')
phrase_textbox.set_text(phrase)
transcription_textbox = device.get_descendant(
'transcription_textbox')
transcription_textbox.set_text('')
# Reset the thumb to the space before each phrase.
human.body_parts[
'thumb'].location_x = space_key.top_left_x + space_key.width / 2
human.body_parts[
'thumb'].location_y = space_key.top_left_y + space_key.height / 2
# Reset the eyes to the phrase text box.
human.body_parts[
'eyes'].fixation_x = phrase_textbox.top_left_x + phrase_textbox.width / 2
human.body_parts[
'eyes'].fixation_y = phrase_textbox.top_left_y + phrase_textbox.height / 2
schedule_chart = human.press(phrase)
duration = human.compute_duration(schedule_chart)
total_characters_count += len(phrase)
total_duration += duration
human.timestamp_offset = total_duration
current_speed_char_per_second = len(phrase) / (duration / 1000.0)
current_speed_words_per_minute = current_speed_char_per_second * 60 / 5
phrase_typing_speeds.append(current_speed_words_per_minute)
if len(phrase_typing_speeds) % 250 == 0:
human.draw_schedule_graph(phrase, schedule_chart)
# Visualize the typing speeds over time.
plt.scatter(phrase_typing_timestamps, phrase_typing_speeds)
plt.title('Typing speeds over time')
plt.xlabel('Time (min)')
plt.ylabel('Speed (WPM)')
plt.show(block=True)
plt.close()
# Convert total_duration from milliseconds to seconds.
total_duration /= 1000.0
speed_char_per_second = total_characters_count / total_duration
speed_words_per_minute = speed_char_per_second * 60 / 5
print("Typists can enter text at the speed of " +
str(speed_words_per_minute) + "WPM.")
