def demo_copy_phrase_wrapper():
# We need to train a dummy model
num_x_p = 100
num_x_n = 900
x_p = mean_pos + var_pos * np.random.randn(num_ch, num_x_p, dim_x)
x_n = mean_neg + var_neg * np.random.randn(num_ch, num_x_n, dim_x)
y_p = [1] * num_x_p
y_n = [0] * num_x_n
train_x = np.concatenate((x_p, x_n), 1)
train_y = np.concatenate((y_p, y_n), 0)
permutation = np.random.permutation(train_x.shape[1])
train_x = train_x[:, permutation, :]
train_y = train_y[permutation]
train_x = train_x[list(np.where(np.asarray(channel_map) == 1)[0]), :, :]
k_folds = 10
model = train_pca_rda_kde_model(train_x, train_y, k_folds=k_folds)
# Define task and operate
task_list = [('I_LOVE_COOKIES', 'I_LOVE_'),
('THIS_IS_A_DEMO', 'THIS_IS_A_')]
task = CopyPhraseWrapper(model, fs=dim_x * 2, k=1, alp=alphabet(),
task_list=task_list)
print(task)
def __init__(self, win, daq, parameters, file_save, classifier, lmodel,
fake):
self.window = win
self.frame_rate = self.window.getActualFrameRate()
self.parameters = parameters
self.daq = daq
self.static_clock = core.StaticPeriod(screenHz=self.frame_rate)
self.experiment_clock = core.Clock()
self.buffer_val = parameters['task_buffer_len']
self.alp = alphabet(parameters)
self.rsvp = _init_copy_phrase_display(self.parameters, self.window,
self.daq, self.static_clock,
self.experiment_clock)
self.file_save = file_save
trigger_save_location = f"{self.file_save}/{parameters['triggers_file_name']}"
self.trigger_file = open(trigger_save_location, 'w')
self.session_save_location = f"{self.file_save}/{parameters['session_file_name']}"
self.wait_screen_message = parameters['wait_screen_message']
self.wait_screen_message_color = parameters[
'wait_screen_message_color']
self.num_sti = parameters['num_sti']
self.len_sti = parameters['len_sti']
self.timing = [
parameters['time_target'], parameters['time_cross'],
parameters['time_flash']
]
self.color = [
parameters['target_letter_color'], parameters['fixation_color'],
parameters['stimuli_color']
]
self.task_info_color = parameters['task_color']
self.stimuli_height = parameters['sti_height']
self.is_txt_sti = parameters['is_txt_sti']
self.eeg_buffer = parameters['eeg_buffer_len']
self.copy_phrase = parameters['text_task']
self.spelled_letters_count = int(parameters['spelled_letters_count'])
if self.spelled_letters_count > len(self.copy_phrase):
logging.debug("Already spelled letters exceeds phrase length.")
self.spelled_letters_count = 0
self.max_seq_length = parameters['max_seq_len']
self.max_seconds = parameters['max_minutes'] * 60 # convert to seconds
self.fake = fake
self.lmodel = lmodel
self.classifier = classifier
self.down_sample_rate = parameters['down_sampling_rate']
def test_alphabet_text(self):
parameters_used = 'bcipy/parameters/parameters.json'
parameters = load_json_parameters(parameters_used, value_cast=True)
parameters['is_txt_sti'] = True
alp = alphabet(parameters)
self.assertEqual(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',
'<', '_'
])
def test_alphabet_images(self):
parameters_used = 'bcipy/parameters/parameters.json'
parameters = load_json_parameters(parameters_used, value_cast=True)
parameters['is_txt_sti'] = False
parameters['path_to_presentation_images'] = ('bcipy/static/images/'
'rsvp_images/')
alp = alphabet(parameters)
self.assertNotEqual(alp, [
'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M',
'N', 'O', 'P', 'R', 'S', 'T', 'U', 'V', 'Y', 'Z', '<', '_'
])
def __init__(self, win, daq, parameters, file_save, fake):
super(RSVPCopyPhraseCalibrationTask, self).__init__()
self.window = win
self.frame_rate = self.window.getActualFrameRate()
self.parameters = parameters
self.daq = daq
self.static_clock = core.StaticPeriod(screenHz=self.frame_rate)
self.experiment_clock = core.Clock()
self.buffer_val = parameters['task_buffer_len']
self.alp = alphabet(parameters)
self.rsvp = _init_copy_phrase_display_task(self.parameters,
self.window, self.daq,
self.static_clock,
self.experiment_clock)
self.file_save = file_save
trigger_save_location = f"{self.file_save}/{parameters['triggers_file_name']}"
self.session_save_location = f"{self.file_save}/{parameters['session_file_name']}"
self.trigger_file = open(trigger_save_location, 'w')
self.wait_screen_message = parameters['wait_screen_message']
self.wait_screen_message_color = parameters[
'wait_screen_message_color']
self.num_sti = parameters['num_sti']
self.len_sti = parameters['len_sti']
self.timing = [
parameters['time_target'], parameters['time_cross'],
parameters['time_flash']
]
self.color = [
parameters['target_letter_color'], parameters['fixation_color'],
parameters['stimuli_color']
]
self.task_info_color = parameters['task_color']
self.stimuli_height = parameters['sti_height']
self.is_txt_sti = parameters['is_txt_sti']
self.eeg_buffer = parameters['eeg_buffer_len']
self.copy_phrase = parameters['text_task']
self.max_seq_length = parameters['max_seq_len']
self.fake = fake
self.enable_breaks = parameters['enable_breaks']
def __init__(self, win, daq, parameters, file_save, signal_model,
language_model, fake, is_word, auc_filename):
super(RSVPIconToIconTask, self).__init__()
self.window = win
self.frame_rate = self.window.getActualFrameRate()
self.parameters = parameters
self.daq = daq
self.static_clock = core.StaticPeriod(screenHz=self.frame_rate)
self.experiment_clock = core.Clock()
self.buffer_val = parameters['task_buffer_len']
self.alp = alphabet(parameters)
self.rsvp = _init_icon_to_icon_display_task(self.parameters,
self.window, self.daq,
self.static_clock,
self.experiment_clock,
is_word)
self.file_save = file_save
self.is_word = is_word
trigger_save_location = f"{self.file_save}/{parameters['triggers_file_name']}"
self.trigger_file = open(trigger_save_location, 'w+')
self.session_save_location = f"{self.file_save}/{parameters['session_file_name']}"
self.wait_screen_message = parameters['wait_screen_message']
self.wait_screen_message_color = parameters[
'wait_screen_message_color']
self.num_sti = parameters['num_sti']
self.len_sti = parameters['len_sti']
self.timing = [
parameters['time_target'], parameters['time_cross'],
parameters['time_flash']
]
self.color = [
parameters['target_letter_color'], parameters['fixation_color'],
parameters['stimuli_color']
]
self.task_info_color = parameters['task_color']
self.stimuli_height = parameters['sti_height']
self.eeg_buffer = parameters['eeg_buffer_len']
self.max_seconds = parameters['max_minutes'] * 60 # convert to seconds
self.max_seq_length = parameters['max_seq_len']
self.fake = fake
self.language_model = language_model
self.signal_model = signal_model
self.auc_filename = auc_filename
self.image_path = parameters['path_to_presentation_images']
self.task_height = parameters['height_task']
self.is_txt_sti = False
self.min_num_seq = parameters['min_seq_len']
self.word_matching_text_size = parameters['word_matching_text_size']
self.collection_window_len = parameters[
'collection_window_after_trial_length']
self.data_save_path = parameters['data_save_loc']
def __init__(self, path2eeg):
self.abc = alphabet()
self.samples = eegs(path2eeg)
import os
import docker
import requests
import time
import re
import logging
import unittest
from errors import ConnectionErr, StatusCodeError, DockerDownError
from bcipy.helpers.bci_task_related import alphabet
from subprocess import Popen, PIPE
import platform
ALPHABET = alphabet()
class LangModel:
def __init__(self,
localpath2fst,
host="127.0.0.1",
port="5000",
logfile="log"):
"""
Initiate the langModel class. Primarly initializing
is aimed at establishing the tcp/ip connection
between the host (local machine) and its server
(the docker machine)
Establishing the connection and running the server
are done in a single operartion
Input:
localpath2fst (str) - the local path to the fst file
host (str) - host machine ip address
def __init__(self,
window,
clock,
experiment_clock,
color_task='white',
font_task='Times',
pos_task=(-.75, .75),
task_height=0.1,
grid_rows=6,
grid_columns=6,
time_flash=.25,
text_task='1/100',
color_text=['white'],
font_text='Times',
height_text=0.25,
font_sti='Times',
pos_sti=(0, .0),
sti_height=0.25,
is_txt_sti=True,
alp=None):
self.win = window
self.logger = logging
# TASK TEXT
self.font_task_text = font_task
self.task_height = task_height
self.pos_task_text = pos_task
self.text_task = text_task
self.color_task = color_task
# STIM / GRID
self.is_txt_sti = is_txt_sti
self.stimuli = []
self.rows = grid_rows
self.font = font_sti
self.columns = grid_columns
self.sti_height = sti_height
self.stim_number = grid_rows + grid_columns
self.max_height_grid = -1 + sti_height
self.max_width_grid = 1 - sti_height
self.uniform_grid_values_row = sorted(
np.linspace(start=self.max_height_grid,
stop=self.max_width_grid,
num=self.rows))
self.uniform_grid_values_col = sorted(np.linspace(
start=self.max_height_grid,
stop=self.max_width_grid - .25,
num=self.columns),
reverse=True)
if not alp:
self.alp = alphabet()
else:
self.alp = alp
self.flash = time_flash
# Clocks
self.trialClock = clock
self.expClock = experiment_clock
# Length of the stimuli (number of stimuli on screen)
self.len_sti = len(self.stimuli)
