def test_2(subject_list=[]):
#---DATA DIR
datadir = my.get_test_folder(foldername="e2_data") #
outdir = my.get_test_folder(foldername='e2_data_bva')
fileid_seq = ["alpha_eo_3.meta"]
# ["rest_ec_1.meta","rest_eo_2.meta","alpha_eo_3.meta", #b1
# "rest_ec_4.meta", "rest_eo_4.meta","breathingv6_ec_4.meta", "breathingv6_eo_4.meta","imageryv6_ec_4.meta", "imageryv6_eo_4.meta","alpha_ec_5.meta","alpha_eo_5.meta",#b2
# "rest_ec_6.meta", "rest_eo_6.meta","breathingv6_ec_6.meta", "breathingv6_eo_6.meta","imageryv6_ec_6.meta", "imageryv6_eo_6.meta","alpha_ec_7.meta","alpha_eo_7.meta",#b3
# "rest_ec_8.meta", "rest_eo_8.meta","breathingv6_ec_8.meta", "breathingv6_eo_8.meta","imageryv6_ec_8.meta", "imageryv6_eo_8.meta","alpha_ec_9.meta","alpha_eo_9.meta",#b4
# "rest_ec_10.meta", "rest_eo_10.meta","breathingv6_ec_10.meta", "breathingv6_eo_10.meta","imageryv6_ec_10.meta", "imageryv6_eo_10.meta","alpha_ec_11.meta","alpha_eo_11.meta",#b5
# "rest_ec_12.meta","rest_eo_13.meta","alpha_eo_14.meta"#b6
# ]
#Factorial design folder analysis
groupdir = datadir
group_l = os.listdir(groupdir)
for g in group_l:
subjectdir = os.path.join(datadir, g)
if not os.path.isdir(subjectdir): continue #test if is a folder
subject_l = os.listdir(subjectdir)
for s in subject_l:
taskdir = os.path.join(subjectdir, s)
if not os.path.isdir(taskdir): continue #test if is a folder
if subject_list and s not in subject_list: continue
task_l = os.listdir(taskdir)
for t in task_l:
filedir = os.path.join(taskdir, t)
if not os.path.isdir(filedir): continue #test if is a folder
file_l = [
name for name in os.listdir(filedir)
if os.path.isfile(os.path.join(filedir, name))
] #get only files
#PROCESSING
fnseq = get_filenamesequence(file_l,
fileid_seq) #dict as no sequence
true_fileid_seq = []
for dn in fileid_seq:
if dn in fnseq:
true_fileid_seq.append(dn.split(".")[0])
for k in fnseq:
f = fnseq[k] #f.meta
if f: #if file exists
filepath = os.path.join(filedir, f)
mushu2bva(filepath, outdir, manual_amp_ref=['Cz'])
def __init__(self,
simulate=False,
replayamp=False,
filetoreplay=None,
realtimereplay=True,
inlet_sleep_time=float(0.0005),
max_inlet_samples=1024,
inlet_block_time=None,
filelogger=False,
logfolder='logfolder'):
#Class logger
loggername = self.__class__.__name__
self.logger = logging.getLogger(loggername)
self.logger.setLevel(logging_level)
##file_logger
if filelogger:
logpath = my.get_test_folder(foldername=logfolder)
my.sethandlerfile(modulename=loggername,
setlevel=logging.INFO,
filepath=logpath)
#my.all_logs_enabler(disable=True) #disable all other logs
#INLET defs
self.max_inlet_samples = max_inlet_samples ##MAX INLET SAMPLES THAT WILL BE PULLED #1024 is pylsl pull_chunk standard of max samples pulled
self.inlet_block_time = inlet_block_time #s - directly implement block buffer in the amp.get_data() function of mushu
self.inlet_sleep_time = inlet_sleep_time #s - sleep time between pull chunks
#Replay data
self.replayamp = replayamp
self.filetoreplay = filetoreplay
self.realtimereplay = realtimereplay
self.replaytime = None
#SIMULATE AMPLIFIER in other process
self.simulate = simulate
if self.simulate:
import platform
if platform.system() == 'Windows':
self.logger.debug("#BUG windows multiprocessing error")
self.logger.debug(
"#BUG #TODO : Windows multiprocessing has some problems - use simulate=False, go to functions -> simulateActichamp and run the scripts for simulation"
)
raise RuntimeError("Windows Not Working the simulate")
self.p_data = multiprocessing.Process(
target=self.init_actichamp_data_simulation
) # can also pass parameters
self.p_marker = multiprocessing.Process(
target=self.init_actichamp_marker_simulation)
self.p_data.start() # start process
self.p_marker.start() # start process
#INIT VARS
self.init()
def init(self):
"""
Global Constants
"""
#1.INIT Parent Class
initbciclass.init(self)
#2.Alter or add other functions
#INIT SAVING
self.TASK = 'NFT' # NFT
self.subtask = "" #ALL TASKs in same FILE
#INIT PRESENTATION VARS
#Presentation PROTOCOL VARS- TODO: randomize protocol_feature
self.PROTOCOL_TYPE = "" #NFT or REST the functions will change it accordingly
self.PROTOCOL_DESIGN = "normal" #ABA or Normal -
#presentation init screen
self.INIT_TEXT = ""
self.STIM_TIME = 30 #s
##EXPERIMENT VARS
self.datatdir = my.get_test_folder(foldername="e2_data")
self.subjectdir = "EG/S001" #
self.fileid = "online_result" #id that identifies the file
#protocol features of NFT
self.PROTOCOL_FEATURES_L = ["SMR", "upper_alpha"] #List
self.PROTOCOL_FEATURE = "SMR" #SMR or upper_alpha
self.random_seed = None #None or no argument seeds from current time or from an operating system specific randomness source if available
#OFFLINE PROCESSING -
#reward and inhibit bands - dict objects to buffer band features
self.initial_reward_bands, self.initial_inhibit_bands = {}, {
} #initial bands
self.reward_bands, self.inhibit_bands = {}, {
} #state bands - updated during online neurofeedback
###OFFLINE PIPELINE
self.off_rest_bci(markernumerate=markernumerate)
###LOG TIME
self.end_time = time.time()
self.elapsed_time = self.end_time - self.start_time
self.logger.info("!!ON_PLAY ELAPSED TIME!! : {}".format(
self.elapsed_time))
if __name__ == "__main__":
#1.Start Class
rest = restclass(inlet_block_time=None)
#save folder dir
test_folder_path = os.path.join(my.get_test_folder(),
'restclass') #folderpath
try:
#2.RE-INIT Vars
#SAVING - Reinitialize parameters
rest.SAVE = True
#Start dialogue
info = {
'SAVE': ['no', 'yes'],
'savefolder': test_folder_path,
'subject': 999,
'session': 999,
'exp_version': 2,
'group': ['EG', 'CG', 'PILOT'],
"technician": "Nuno Costa"
stream_server='lsl',
lsl_amp_name='HRV',
lsl_marker_name="PyffMarkerStream")
amp = hrv
while True:
if run.value:
amp.start()
amp = loop_get_data(amp) #update amp
#stop() amp to close files
amp.stop()
run.value = not run.value
if __name__ == "__main__":
#TEST FOLDER for files
test_folder_path = my.get_test_folder(foldername='temp_test')
#TEST save in multiprocessing (Something wrong in saving )
TEST_0 = True
if TEST_0:
data = {'signals': 'lool'}
#file
timestamp = time.strftime('%d%m%Y_%Hh%Mm', time.localtime())
datadir = test_folder_path
method = "pcl"
filepath = os.path.join(
datadir,
'e2_test_save_in_subprocess' + '_' + timestamp + '.' + method)
subsave = my.save_in_subprocess(data, filepath, method=method)
subsave.save()
self.end_time = time.time()
self.elapsed_time = self.end_time - self.start_time
self.logger.info("!!ON_PLAY ELAPSED TIME!! : {}".format(
self.elapsed_time))
if __name__ == "__main__":
#WARNING TO SIMULATE: USE Generated data or Replay data ( - Generated(outlet_actichamp.py,sine waves), Replay(PREFERABLY file_stream_player.py or class replayamp - does not simulate all)
replayamp = False
#replay sample data
filetoreplay = my.get_filetoreplay() #filepath
#save folder dir
test_folder_path = my.get_test_folder() #folderpath
#1.Start Class
prime = primeclass(replayamp=replayamp, filetoreplay=filetoreplay)
try:
#2.RE-INIT Vars
#SAVING - Reinitialize parameters
#Start dialogue
info = {
'SAVE': ['no', 'yes'],
'savefolder': test_folder_path,
'subject': 1,
'session': 1,
'exp_version': 2,
'group': ['EG', 'CG', 'PILOT'],
"technician": "Nuno Costa"
def test_1():
"""BUG: Report class is breaking next task
SOLVED:
"""
bci = initbciclass()
prime = primeclass()
report = reportclass()
#save folder dir
test_folder_path = os.path.join(my.get_test_folder(),
'test_class_problems') #folderpath
#1.Start Class
report = reportclass()
prime = primeclass()
try:
#2.RE-INIT Vars
#SAVING - Reinitialize parameters
bci.SAVE = prime.SAVE = False
report.SAVE = False #Nao grave
bci.SAVE_TASK = prime.SAVE_TASK = report.SAVE_TASK = True #report.SAVE_TASK
#Start dialogue
info = {
'savefolder': test_folder_path,
'subject': 1,
'session': 1,
'exp_version': 2,
'group': ['EG', 'CG', 'PILOT'],
"technician": "Nuno Costa"
}
title = 'test experiment'
fixed = ['exp_version']
newinfo = my.gui_dialogue(info=info, title=title, fixed=fixed)
#Save vars
bci.FOLDER_DATA = prime.FOLDER_DATA = newinfo['savefolder']
bci.GROUP = bci.FOLDER_DATA = prime.GROUP = newinfo['group'] #EG or CG
bci.SUBJECT_NR = prime.SUBJECT_NR = newinfo['subject']
bci.SESSION_NR = prime.SESSION_NR = newinfo['session']
#INIT Methods - Saving, Acquisition and Presentation
bci.on_init()
#1.PRESENTATION PATCHING
prime.pyff = bci.pyff
report.pyff = bci.pyff
#2.ACQUISITON PATCHING
prime.amp = bci.amp
report.amp = bci.amp
#Experiment Vars
prime.audiostimulus_l = ["imagery_v6.ogg"]
#random.shuffle(prime.audiostimulus_l)
#Task 1 report
report.START_WAIT_FOR_KEY = True
report.on_play_check()
#Task 2 stim
prime.STIM_TIME = 30 #s
prime.protocol_eyes = "eyes_open"
prime.START_WAIT_FOR_KEY = True
#PLAY
for i, stim in enumerate(prime.audiostimulus_l):
print("RUN STIMULUS:", stim)
prime.BLOCK_NR = i + 1 #BLOCK
prime.on_play(audiostimulus=stim,
videostimulus=None,
imagestimulus=None,
textstimulus=None,
markernumerate=prime.BLOCK_NR)
bci.on_quit()
except:
bci.on_quit()
@author: nm.costa
"""
from __future__ import (
absolute_import, division, print_function
) #unicode_literals - more info needed to addapt; absolute_import does not let you to import from current folder, need to specify from the main package phdproject...
from builtins import * #all the standard builtins python 3 style
import os
import scipy
import neuroprime.src.utils.myfunctions as my
dir_dataroot = 'C:/Users/admin.DDIAS4/Desktop/e2_data/EG/S001/REST'
filename = 'EG_S001_REST_ss01_b01_16102019_11h15m_rest_ec_1'
filepath = os.path.join(dir_dataroot, filename + '.meta')
#------
filedir, filenametype = os.path.split(filepath)
filename, filetype = os.path.splitext(filenametype)
#load mushu data to mne
raw, event_id = my.mushu_to_mne(filepath, ch_names=None, montage=None)
#TODO:add manually the ref
#Save in mne fif format
nfiledir = my.get_test_folder(foldername='e2_data_fif')
nfilename = filename + ".fif"
out_filepath = os.path.join(nfiledir, nfilename)
print('saving eeg fif', nfilename)
raw.save(out_filepath)
#save in mat event_id
event_id_filepath = os.path.join(nfiledir, filename + "_event_id.mat")
print('saving event_id', event_id_filepath)
scipy.io.savemat(event_id_filepath, event_id, oned_as='row')
def bci():
st = time.time()
bci = initbciclass(filelogger=FILELOGGER, logfolder='e2_data/')
rest = restclass(filelogger=FILELOGGER, logfolder='e2_data/')
nft = nftclass(filelogger=FILELOGGER, logfolder='e2_data/')
prime = primeclass(filelogger=FILELOGGER, logfolder='e2_data/')
report = reportclass()
et = time.time() - st
logger.info("!!ELAPSED TIME INIT CLASS BCICLASS!! : {}".format(et))
#RANDOM VARS
random.seed(
) #None or no argument seeds from current time or from an operating system specific randomness source if available
try: #catch errors and close
#2RE-INIT Vars
#Manual REF
bci.amp_ref_channels = rest.amp_ref_channels = nft.amp_ref_channels = prime.amp_ref_channels = AMP_MANUAL_REF
#SAVE BY TASK
bci.SAVE_TASK = rest.SAVE_TASK = nft.SAVE_TASK = prime.SAVE_TASK = report.SAVE_TASK = SAVE_BY_TASK #True, save file by task or False, by session (WARNING: ALL TASKS SHOULD RESPECK THE SAME METHOD)
folder_path = my.get_test_folder(foldername=SAVE_FOLDER) #folderpath
#Start dialogue (alphabetic order)
info = {
'EXP_VERSION': 'e2_bci',
'SAVE_FOLDER': folder_path,
'SAVE': ['yes', 'no'],
'NFT_PROCESS_CHS': str(NFT_PROCESS_CHS),
'subject': 1,
'session': 1,
'pg': ['EG', 'CG'], #['EG', 'CG', 'random'],
'feat': ['a', 's', 'd', 't', 'b', 'g'],
'eyes': ['ec', 'eo'],
'prime': ['BM', 'IM', 'WHM'],
"technician": "Nuno Costa"
}
title = 'experiment 2'
fixed = ['EXP_VERSION']
newinfo = my.gui_dialogue(info=info, title=title, fixed=fixed)
#random group choice - randomize EG and CG-not good because never know how it can end - using pseudo randomization in excel
# if newinfo['pg'] =="random":
# newinfo['pg'] = random.choice(['EG','CG'])
#SAVE VARS
bci.FOLDER_DATA = rest.FOLDER_DATA = nft.FOLDER_DATA = prime.FOLDER_DATA = newinfo[
'SAVE_FOLDER']
bci.GROUP = rest.GROUP = nft.GROUP = prime.GROUP = newinfo[
'pg'] #EG or CG
bci.SUBJECT_NR = rest.SUBJECT_NR = nft.SUBJECT_NR = prime.SUBJECT_NR = newinfo[
'subject']
bci.SESSION_NR = rest.SESSION_NR = nft.SESSION_NR = prime.SESSION_NR = newinfo[
'session']
bci.NFT_PROCESS_CHS = ast.literal_eval(newinfo['NFT_PROCESS_CHS'])
if newinfo['SAVE'] == 'yes':
bci.SAVE = rest.SAVE = nft.SAVE = prime.SAVE = True
if newinfo['SAVE'] == 'no':
bci.SAVE = rest.SAVE = nft.SAVE = prime.SAVE = False
report.SAVE = False #Nao grave
#TOTAL BLOCK NUMBER
bci.TOTAL_BLOCK_NR = rest.TOTAL_BLOCK_NR = nft.TOTAL_BLOCK_NR = prime.TOTAL_BLOCK_NR = TOTAL_BLOCK_NR
###INIT BCI
st = time.time()
#INIT SAVING
rest.init_io()
prime.init_io()
nft.init_io()
report.init_io()
#INIT PRESENTATION AND ACQUISITION, PATCH NFT AND prime CLASS WITH only one AMP and PYFF object
bci.on_init()
#add subprocess amps - limitation - using only the first filname - #TODO: add updates
if ADD_AMPS_ON:
#clean up any old process
import multiprocessing
for p in multiprocessing.active_children():
print("TERMINATING PROCESS: ", p.name, p.pid)
p.terminate() #force termination
p.join() #wait to terminate
if bci.SAVE: #add james folder to path
bci.TASK = "JAMES"
bci.update_file_path()
gsr = get_amp_subprocess(filepath=bci.FILENAME_EEG_PATH,
save_task=ADD_AMPS_SAVE_BY_TASK,
process_name='GSR')
gsr.configure(stream_type='GSR',
stream_server='lsl',
lsl_amp_name='GSR',
lsl_marker_name="PyffMarkerStream")
hr = get_amp_subprocess(filepath=bci.FILENAME_EEG_PATH,
save_task=ADD_AMPS_SAVE_BY_TASK,
process_name='HR')
hr.configure(stream_type='HR',
stream_server='lsl',
lsl_amp_name='HR',
lsl_marker_name="PyffMarkerStream")
time.sleep(10)
if bci.SAVE: #go to james folder to path
bci.TASK = ""
bci.update_file_path()
#1.PRESENTATION PATCHING
rest.pyff = bci.pyff
prime.pyff = bci.pyff
nft.pyff = bci.pyff
report.pyff = bci.pyff
#2.ACQUISITON PATCHING
rest.amp = bci.amp
prime.amp = bci.amp
nft.amp = bci.amp
report.amp = bci.amp
##DEFINE VARS
#bci vars
bci.thresholdbuffer_eo = []
bci.thresholdbuffer_ec = []
#TASK protocol eyes
if newinfo['eyes'] == "eo":
bci.protocol_eyes_l = [
"eyes_closed_v2", "eyes_open_v2", "eyes_open", "eyes_open",
"eyes_open", "eyes_closed", "eyes_closed", "eyes_closed",
"eyes_closed", "eyes_open", "eyes_open", "eyes_closed_v2",
"eyes_open_v2", "eyes_open"
]
if newinfo['eyes'] == "ec":
bci.protocol_eyes_l = [
"eyes_closed_v2", "eyes_open_v2", "eyes_open", "eyes_closed",
"eyes_closed", "eyes_open", "eyes_open", "eyes_open",
"eyes_open", "eyes_closed", "eyes_closed", "eyes_closed_v2",
"eyes_open_v2", "eyes_open"
]
#rest vars
rest.PROTOCOL_TYPE = "REST" #
rest.PROTOCOL_DESIGN = "normal"
#prime VARS
if newinfo['prime'] == "BM":
prime.audiostimulus_l = [
"breathingv6.ogg", "imageryv6.ogg", "breathingv6.ogg",
"imageryv6.ogg"
]
if newinfo['prime'] == "IM":
prime.audiostimulus_l = [
"imageryv6.ogg", "breathingv6.ogg", "imageryv6.ogg",
"breathingv6.ogg"
]
if newinfo['prime'] == "WHM":
prime.audiostimulus_l = [
"imageryv6.ogg", "whmv1.ogg", "whmv1.ogg", "whmv1.ogg"
]
prime.PROTOCOL_TYPE = "PRIME" #
prime.PROTOCOL_DESIGN = "normal" #normal, test
#REPORT VARS
#None
#NFT VARS
if newinfo['feat'] == "a": nft.PROTOCOL_FEATURE = "alpha"
if newinfo['feat'] == "s": nft.PROTOCOL_FEATURE = "SMR"
nft.PROTOCOL_TYPE = "NFT" #
nft.PROTOCOL_DESIGN = "normal" # Normal
#online vars (advanced: change in nftclass)
nft.adaptative_threshold_aftertask = MASTER_UPDATE_THRESHOLD_AFTERTASK
nft.select_chs = bci.NFT_PROCESS_CHS #chs used throught the processing #NOTE: Include Fp1 and Fp2 for rejection of blinks and saccades
nft.ref_channels = RE_REFERENCE
nft.threshold_reward_level = THRESHOLD_REWARD_LEVEL
#INIT NFT ALGORITHM
nft.init_processing_algorithm(feature=nft.PROTOCOL_FEATURE)
et = time.time() - st
logger.info("!!ELAPSED TIME INIT METHODS BCICLASS!! : {}".format(et))
###EXPERIMENT SESSION
bci.start_time = time.time()
#class initial stae
nft.serialize(objectname="nftclass_init_state"
) #BUG: #Solved puttingin init state
prime.serialize(objectname="primeclass_init_state")
rest.serialize(objectname="restclass_init_state")
bci.serialize(objectname="bci_init_state")
#master stim time for tasks
master_stim_1 = MASTER_STIMULUS_TIME #s #rest eo & ec
master_stim_2 = 2 * master_stim_1 #s #rest, prime and nft full task
#raise RuntimeError("END EXPERIMENT")
#1. BLOCK IN
bci.BLOCK_NR = 1
rest.BLOCK_NR = prime.BLOCK_NR = nft.BLOCK_NR = bci.BLOCK_NR
#task 1: rest olhos fechados
bci.TASK_NR = 1
rest.TASK_NR = prime.TASK_NR = nft.TASK_NR = bci.TASK_NR
rest.STIM_TIME = master_stim_1 #s
rest.protocol_eyes = bci.protocol_eyes_l[bci.TASK_NR - 1]
rest.START_WAIT_FOR_KEY = True
if ADD_AMPS_ON:
gsr.start()
hr.start()
rest.on_play_check(
markernumerate=bci.TASK_NR
) #rest.on_play(markernumerate=bci.TASK_NR) #or nft.off_rest_bci
if ADD_AMPS_ON:
gsr.stop()
hr.stop()
baseline_data = np.array(
rest.amp.amp.samples_buffer
) #mushu format: numpy array samples X channels
baseline_markers = rest.amp.amp.markers_buffer_mushu #mushu format: list #timecorrected
#initial bands thresholds eyes closed(ec)
initial_reward_bands_ec, initial_inhibit_bands_ec = nft.baseline_thresholds(
data=baseline_data,
markers=baseline_markers,
markernumerate=bci.TASK_NR)
update_reward_bands_ec, update_inhibit_bands_ec = initial_reward_bands_ec, initial_inhibit_bands_ec
bci.thresholdbuffer_ec.append(
update_reward_bands_ec[nft.PROTOCOL_FEATURE]['threshold'])
#task 2: rest olhos abertos
bci.TASK_NR = 2
rest.TASK_NR = prime.TASK_NR = nft.TASK_NR = bci.TASK_NR
rest.STIM_TIME = master_stim_1 #s
rest.protocol_eyes = bci.protocol_eyes_l[bci.TASK_NR - 1]
rest.START_WAIT_FOR_KEY = True
if ADD_AMPS_ON:
gsr.start()
hr.start()
rest.on_play_check(
markernumerate=bci.TASK_NR
) #rest.on_play(markernumerate=bci.TASK_NR) #or nft.off_rest_bci
if ADD_AMPS_ON:
gsr.stop()
hr.stop()
baseline_data = np.array(
rest.amp.amp.samples_buffer
) #mushu format: numpy array samples X channels
baseline_markers = rest.amp.amp.markers_buffer_mushu #mushu format: list #timecorrected
#initial bands thresholds eyes open(eo)
initial_reward_bands_eo, initial_inhibit_bands_eo = nft.baseline_thresholds(
data=baseline_data,
markers=baseline_markers,
markernumerate=bci.TASK_NR)
update_reward_bands_eo, update_inhibit_bands_eo = initial_reward_bands_eo, initial_inhibit_bands_eo
bci.thresholdbuffer_eo.append(
update_reward_bands_eo[nft.PROTOCOL_FEATURE]['threshold'])
#task 3: nft eyes open
bci.TASK_NR = 3
rest.TASK_NR = prime.TASK_NR = nft.TASK_NR = bci.TASK_NR
nft.STIM_TIME = master_stim_2 #s
nft.protocol_eyes = bci.protocol_eyes_l[bci.TASK_NR - 1]
nft.START_WAIT_FOR_KEY = False
nft.initial_reward_bands, nft.initial_inhibit_bands = update_reward_bands_eo, update_inhibit_bands_eo
if ADD_AMPS_ON:
gsr.start()
hr.start()
nft.on_play_check(markernumerate=bci.TASK_NR
) #nft.on_play(markernumerate=bci.TASK_NR)
if ADD_AMPS_ON:
gsr.stop()
hr.stop()
#update thresholds
if MASTER_UPDATE_THRESHOLD_AFTERTASK:
update_reward_bands_eo[
nft.PROTOCOL_FEATURE]['threshold'] = nft.new_threshold
bci.thresholdbuffer_eo.append(
update_reward_bands_eo[nft.PROTOCOL_FEATURE]['threshold'])
#task report: (dont update task_nr because files not saved)
report.START_WAIT_FOR_KEY = True
report.on_play_check()
#raise RuntimeError("Terminate Experiment") #for tests
#2.Block of stimulus ( FACTORIAL DESIGN)
for i, audio in enumerate(prime.audiostimulus_l):
#UPATE BLOCK
bci.BLOCK_NR += 1
rest.BLOCK_NR = prime.BLOCK_NR = nft.BLOCK_NR = bci.BLOCK_NR
#eyes protocol copy of previous update
irb_eo, iib_eo = copy.copy(update_reward_bands_eo), copy.copy(
update_inhibit_bands_eo)
irb_ec, iib_ec = copy.copy(update_reward_bands_ec), copy.copy(
update_inhibit_bands_ec)
#PLAY NEW BLOCK
if bci.GROUP == "EG":
#task 1:prime
bci.TASK_NR += 1
rest.TASK_NR = prime.TASK_NR = nft.TASK_NR = bci.TASK_NR
prime.STIM_TIME = master_stim_2 #s
prime.protocol_eyes = bci.protocol_eyes_l[bci.TASK_NR - 1]
prime.START_WAIT_FOR_KEY = True
if ADD_AMPS_ON:
gsr.start()
hr.start()
prime.on_play_check(audiostimulus=audio,
markernumerate=bci.TASK_NR)
if ADD_AMPS_ON:
gsr.stop()
hr.stop()
#task 2: NFT
bci.TASK_NR += 1
rest.TASK_NR = prime.TASK_NR = nft.TASK_NR = bci.TASK_NR
nft.STIM_TIME = master_stim_2 #s
nft.protocol_eyes = bci.protocol_eyes_l[bci.TASK_NR - 1]
nft.START_WAIT_FOR_KEY = False
nft.initial_reward_bands, nft.initial_inhibit_bands = irb_eo, iib_eo
if nft.protocol_eyes == "eyes_closed":
nft.initial_reward_bands, nft.initial_inhibit_bands = irb_ec, iib_ec
if ADD_AMPS_ON:
gsr.start()
hr.start()
nft.on_play_check(markernumerate=bci.TASK_NR
) #nft.on_play(markernumerate=bci.TASK_NR)
if ADD_AMPS_ON:
gsr.stop()
hr.stop()
#update nft thresholds
if nft.protocol_eyes == "eyes_open":
if MASTER_UPDATE_THRESHOLD_AFTERTASK:
update_reward_bands_eo[nft.PROTOCOL_FEATURE][
'threshold'] = nft.new_threshold
bci.thresholdbuffer_eo.append(update_reward_bands_eo[
nft.PROTOCOL_FEATURE]['threshold'])
if nft.protocol_eyes == "eyes_closed":
if MASTER_UPDATE_THRESHOLD_AFTERTASK:
update_reward_bands_ec[nft.PROTOCOL_FEATURE][
'threshold'] = nft.new_threshold
bci.thresholdbuffer_ec.append(update_reward_bands_ec[
nft.PROTOCOL_FEATURE]['threshold'])
elif bci.GROUP == "CG":
#task 1: rest
bci.TASK_NR += 1
rest.TASK_NR = prime.TASK_NR = nft.TASK_NR = bci.TASK_NR
rest.STIM_TIME = master_stim_1 #s
rest.protocol_eyes = bci.protocol_eyes_l[bci.TASK_NR - 1]
rest.START_WAIT_FOR_KEY = True
if ADD_AMPS_ON:
gsr.start()
hr.start()
rest.on_play_check(markernumerate=bci.TASK_NR)
if ADD_AMPS_ON:
gsr.stop()
hr.stop()
#task 2: nft
bci.TASK_NR += 1
rest.TASK_NR = prime.TASK_NR = nft.TASK_NR = bci.TASK_NR
nft.STIM_TIME = master_stim_2 #s
nft.protocol_eyes = bci.protocol_eyes_l[bci.TASK_NR - 1]
nft.START_WAIT_FOR_KEY = False
nft.initial_reward_bands, nft.initial_inhibit_bands = irb_eo, iib_eo
if nft.protocol_eyes == "eyes_closed":
nft.initial_reward_bands, nft.initial_inhibit_bands = irb_ec, iib_ec
if ADD_AMPS_ON:
gsr.start()
hr.start()
nft.on_play_check(markernumerate=bci.TASK_NR
) #nft.on_play(markernumerate=bci.TASK_NR)
if ADD_AMPS_ON:
gsr.stop()
hr.stop()
#update nft thresholds
if nft.protocol_eyes == "eyes_open":
if MASTER_UPDATE_THRESHOLD_AFTERTASK:
update_reward_bands_eo[nft.PROTOCOL_FEATURE][
'threshold'] = nft.new_threshold
bci.thresholdbuffer_eo.append(update_reward_bands_eo[
nft.PROTOCOL_FEATURE]['threshold'])
if nft.protocol_eyes == "eyes_closed":
if MASTER_UPDATE_THRESHOLD_AFTERTASK:
update_reward_bands_ec[nft.PROTOCOL_FEATURE][
'threshold'] = nft.new_threshold
bci.thresholdbuffer_ec.append(update_reward_bands_ec[
nft.PROTOCOL_FEATURE]['threshold'])
#3. BLOCK OUT
bci.BLOCK_NR += 1
rest.BLOCK_NR = prime.BLOCK_NR = nft.BLOCK_NR = bci.BLOCK_NR
#task 1: rest olhos fechados
bci.TASK_NR += 1
rest.TASK_NR = prime.TASK_NR = nft.TASK_NR = bci.TASK_NR
rest.STIM_TIME = master_stim_1 #s
rest.protocol_eyes = bci.protocol_eyes_l[bci.TASK_NR - 1]
rest.START_WAIT_FOR_KEY = True
if ADD_AMPS_ON:
gsr.start()
hr.start()
rest.on_play_check(markernumerate=bci.TASK_NR)
if ADD_AMPS_ON:
gsr.stop()
hr.stop()
#task 2: rest olhos abertos
bci.TASK_NR += 1
rest.TASK_NR = prime.TASK_NR = nft.TASK_NR = bci.TASK_NR
rest.STIM_TIME = master_stim_1 #s
rest.protocol_eyes = bci.protocol_eyes_l[bci.TASK_NR - 1]
rest.START_WAIT_FOR_KEY = True
if ADD_AMPS_ON:
gsr.start()
hr.start()
rest.on_play_check(markernumerate=bci.TASK_NR)
if ADD_AMPS_ON:
gsr.stop()
hr.stop()
#task 3: nft
bci.TASK_NR += 1
rest.TASK_NR = prime.TASK_NR = nft.TASK_NR = bci.TASK_NR
nft.STIM_TIME = master_stim_2 #s
nft.protocol_eyes = bci.protocol_eyes_l[bci.TASK_NR - 1]
nft.START_WAIT_FOR_KEY = False
nft.initial_reward_bands, nft.initial_inhibit_bands = update_reward_bands_eo, update_inhibit_bands_eo #or self.reward_bands, self.inhibit_bands - last calculated reward and inhibit bands
if ADD_AMPS_ON:
gsr.start()
hr.start()
nft.on_play_check(markernumerate=bci.TASK_NR
) #nft.on_play(markernumerate=bci.TASK_NR)
if ADD_AMPS_ON:
gsr.stop()
hr.stop()
#task report
report.START_WAIT_FOR_KEY = True
report.on_play_check()
bci.elapsed_time = time.time() - bci.start_time
logger.info("!!ELAPSED TIME INIT METHODS BCICLASS!! : {}".format(
bci.elapsed_time))
bci.on_quit()
if ADD_AMPS_ON:
gsr.on_quit()
hr.on_quit()
except Exception as e:
logger.error("!!!!SOMETHING WENT WRONG DURING BCI : {}".format(e))
bci.on_quit()
if ADD_AMPS_ON:
gsr.on_quit()
hr.on_quit()
def test_1():
dir_dataroot = 'C:/Users/admin.DDIAS4/Desktop/e2_data/EG/S001/REST'
filename = 'EG_S001_REST_ss01_b01_16102019_11h15m_rest_ec_1'
filepath = os.path.join(dir_dataroot, filename + '.meta')
outdir = my.get_test_folder(foldername='e2_data_bva')
mushu2bva(filepath, outdir)
def bci():
st = time.time()
bci = initbciclass()
rest = restclass()
nft = nftclass()
prime = primeclass()
report = reportclass()
et = time.time() - st
logger.info("!!ELAPSED TIME INIT CLASS BCICLASS!! : {}".format(et))
#RANDOM VARS
random.seed(
) #None or no argument seeds from current time or from an operating system specific randomness source if available
try: #catch and close
#2RE-INIT Vars
#SAVE
bci.SAVE = rest.SAVE = nft.SAVE = prime.SAVE = False
bci.SAVE_TASK = rest.SAVE_TASK = nft.SAVE_TASK = prime.SAVE_TASK = False #True, save file by task or False, by session
folder_path = my.get_test_folder(foldername='e2_bci_v1') #folderpath
#Start dialogue
info = {
'savefolder': folder_path,
'subject': 1,
'session': 1,
'exp_version': 'e2_v1',
'pg': ['EG', 'CG', 'random'],
'prime': ['BM', 'IM'],
'feat': ['a', 's', 'd', 't', 'b', 'g'],
"technician": "Nuno Costa"
} #'pg': ['EG', 'CG', 'PILOT', 'TEST','random']
title = 'experiment 2'
fixed = ['exp_version']
newinfo = my.gui_dialogue(info=info, title=title, fixed=fixed)
#random group choice - randomize EG and CG-not good because never know how it can end - using pseudo randomization in excel
if newinfo['pg'] == "random":
newinfo['pg'] = random.choice(['EG', 'CG'])
#SAVE VARS
bci.FOLDER_DATA = rest.FOLDER_DATA = nft.FOLDER_DATA = prime.FOLDER_DATA = newinfo[
'savefolder']
bci.GROUP = rest.GROUP = nft.GROUP = prime.GROUP = newinfo[
'pg'] #EG or CG
bci.SUBJECT_NR = rest.SUBJECT_NR = nft.SUBJECT_NR = prime.SUBJECT_NR = newinfo[
'subject']
bci.SESSION_NR = rest.SESSION_NR = nft.SESSION_NR = prime.SESSION_NR = newinfo[
'session']
###INIT BCI
st = time.time()
#INIT SAVING
rest.init_io()
prime.init_io()
nft.init_io()
report.init_io()
#INIT PRESENTATION AND ACQUISITION, PATCH NFT AND prime CLASS WITH only one AMP and PYFF object
bci.on_init()
#1.PRESENTATION PATCHING
rest.pyff = bci.pyff
prime.pyff = bci.pyff
nft.pyff = bci.pyff
report.pyff = bci.pyff
#2.ACQUISITON PATCHING
rest.amp = bci.amp
prime.amp = bci.amp
nft.amp = bci.amp
report.amp = bci.amp
##DEFINE VARS
#bci vars
bci.thresholdbuffer_eo = []
bci.thresholdbuffer_ec = []
#rest vars
nft.PROTOCOL_TYPE = "REST" #
rest.PROTOCOL_DESIGN = "normal"
#prime VARS
if newinfo['prime'] == "BM":
prime.audiostimulus_l = ["breathingv6.ogg", "imageryv6.ogg"]
if newinfo['prime'] == "IM":
prime.audiostimulus_l = ["imageryv6.ogg", "breathingv6.ogg"]
prime.PROTOCOL_TYPE = "PRIME" #
prime.PROTOCOL_DESIGN = "normal" #normal, test
#NFT VARS
if newinfo['feat'] == "a": nft.PROTOCOL_FEATURE = "alpha"
if newinfo['feat'] == "s": nft.PROTOCOL_FEATURE = "SMR"
nft.PROTOCOL_TYPE = "NFT" #
nft.PROTOCOL_DESIGN = "normal" # Normal
#online vars (change in nftclass)
#INIT NFT ALGORITHM
nft.init_processing_algorithm(feature=nft.PROTOCOL_FEATURE)
et = time.time() - st
logger.info("!!ELAPSED TIME INIT METHODS BCICLASS!! : {}".format(et))
###EXPERIMENT SESSION
bci.start_time = time.time()
#master stim time for tasks
master_stim_1 = 10 #s #rest eo & ec
master_stim_2 = 2 * master_stim_1 #s #rest, prime and nft full task
#1. BLOCK IN
bci.BLOCK_NR = 1
prime.BLOCK_NR = nft.BLOCK_NR = bci.BLOCK_NR
#task 1: rest olhos fechados
bci.TASK_NR = 1
rest.TASK_NR = prime.TASK_NR = nft.TASK_NR = bci.TASK_NR
rest.STIM_TIME = master_stim_1 #s
rest.protocol_eyes = "eyes_closed_v2"
rest.START_WAIT_FOR_KEY = True
rest.on_play_check(
markernumerate=bci.TASK_NR
) #rest.on_play(markernumerate=bci.TASK_NR) #or nft.off_rest_bci
baseline_data = np.array(
rest.amp.amp.samples_buffer
) #mushu format: numpy array samples X channels
baseline_markers = rest.amp.amp.markers_buffer_mushu #mushu format: list #timecorrected
#initial bands thresholds eyes closed(ec)
initial_reward_bands_ec, initial_inhibit_bands_ec = nft.baseline_thresholds(
data=baseline_data,
markers=baseline_markers,
markernumerate=bci.TASK_NR)
update_reward_bands_ec, update_inhibit_bands_ec = initial_reward_bands_ec, initial_inhibit_bands_ec
bci.thresholdbuffer_ec.append(
update_reward_bands_ec[nft.PROTOCOL_FEATURE]['threshold'])
#task 2: rest olhos abertos
bci.TASK_NR = 2
rest.TASK_NR = prime.TASK_NR = nft.TASK_NR = bci.TASK_NR
rest.STIM_TIME = master_stim_1 #s
rest.protocol_eyes = "eyes_open_v2"
rest.START_WAIT_FOR_KEY = True
rest.on_play_check(
markernumerate=bci.TASK_NR
) #rest.on_play(markernumerate=bci.TASK_NR) #or nft.off_rest_bci
baseline_data = np.array(
rest.amp.amp.samples_buffer
) #mushu format: numpy array samples X channels
baseline_markers = rest.amp.amp.markers_buffer_mushu #mushu format: list #timecorrected
#initial bands thresholds eyes open(eo)
initial_reward_bands_eo, initial_inhibit_bands_eo = nft.baseline_thresholds(
data=baseline_data,
markers=baseline_markers,
markernumerate=bci.TASK_NR)
update_reward_bands_eo, update_inhibit_bands_eo = initial_reward_bands_eo, initial_inhibit_bands_eo
bci.thresholdbuffer_eo.append(
update_reward_bands_eo[nft.PROTOCOL_FEATURE]['threshold'])
#task 3: nft eyes open
bci.TASK_NR = 3
rest.TASK_NR = prime.TASK_NR = nft.TASK_NR = bci.TASK_NR
nft.STIM_TIME = master_stim_2 #s
nft.protocol_eyes = "eyes_open"
nft.START_WAIT_FOR_KEY = False
nft.initial_reward_bands, nft.initial_inhibit_bands = update_reward_bands_eo, update_inhibit_bands_eo
nft.on_play_check(markernumerate=bci.TASK_NR
) #nft.on_play(markernumerate=bci.TASK_NR)
#update thresholds
update_reward_bands_eo[
nft.PROTOCOL_FEATURE]['threshold'] = nft.new_threshold
bci.thresholdbuffer_eo.append(
update_reward_bands_eo[nft.PROTOCOL_FEATURE]['threshold'])
#task report: (dont update task_nr because files not saved)
report.START_WAIT_FOR_KEY = True
report.on_play_check()
#raise RuntimeError("Terminate Experiment")
#2.Block of stimulus ( FACTORIAL DESIGN)
for i, audio in enumerate(prime.audiostimulus_l):
#UPATE BLOCK
bci.BLOCK_NR += 1
prime.BLOCK_NR = nft.BLOCK_NR = bci.BLOCK_NR
#eyes protocol
protocol_eyes = "eyes_open"
irb, iib = update_reward_bands_eo, update_inhibit_bands_eo
if bci.BLOCK_NR == 2 or bci.BLOCK_NR == 4:
protocol_eyes = "eyes_closed"
irb, iib = update_reward_bands_ec, update_inhibit_bands_ec
#PLAY NEW BLOCK
if bci.GROUP == "EG":
#task 1:prime
bci.TASK_NR += 1
rest.TASK_NR = prime.TASK_NR = nft.TASK_NR = bci.TASK_NR
prime.STIM_TIME = master_stim_2 #s
prime.protocol_eyes = protocol_eyes
prime.START_WAIT_FOR_KEY = True
prime.on_play_check(
audiostimulus=audio, markernumerate=bci.TASK_NR
) #prime.on_play(audiostimulus=audio, markernumerate=bci.TASK_NR)
#task 2: NFT
bci.TASK_NR += 1
rest.TASK_NR = prime.TASK_NR = nft.TASK_NR = bci.TASK_NR
nft.STIM_TIME = master_stim_2 #s
nft.protocol_eyes = protocol_eyes
nft.START_WAIT_FOR_KEY = False
nft.initial_reward_bands, nft.initial_inhibit_bands = irb, iib #or self.reward_bands, self.inhibit_bands - last calculated reward and inhibit bands
nft.on_play_check(markernumerate=bci.TASK_NR
) #nft.on_play(markernumerate=bci.TASK_NR)
elif bci.GROUP == "CG":
#task 1: rest
bci.TASK_NR += 1
rest.TASK_NR = prime.TASK_NR = nft.TASK_NR = bci.TASK_NR
rest.STIM_TIME = master_stim_1 #s
rest.protocol_eyes = protocol_eyes
rest.START_WAIT_FOR_KEY = True
rest.on_play_check(markernumerate=bci.TASK_NR)
#task 2: nft
bci.TASK_NR += 1
rest.TASK_NR = prime.TASK_NR = nft.TASK_NR = bci.TASK_NR
nft.STIM_TIME = master_stim_2 #s
nft.protocol_eyes = protocol_eyes
nft.START_WAIT_FOR_KEY = False
nft.initial_reward_bands, nft.initial_inhibit_bands = irb, iib #or self.reward_bands, self.inhibit_bands - last calculated reward and inhibit bands
nft.on_play_check(markernumerate=bci.TASK_NR
) #nft.on_play(markernumerate=bci.TASK_NR)
#update nft thresholds
if protocol_eyes == "eyes_open":
update_reward_bands_eo[
nft.PROTOCOL_FEATURE]['threshold'] = nft.new_threshold
bci.thresholdbuffer_eo.append(
update_reward_bands_eo[nft.PROTOCOL_FEATURE]['threshold'])
if protocol_eyes == "eyes_closed":
update_reward_bands_ec[
nft.PROTOCOL_FEATURE]['threshold'] = nft.new_threshold
bci.thresholdbuffer_ec.append(
update_reward_bands_ec[nft.PROTOCOL_FEATURE]['threshold'])
"""
#3. BLOCK OUT
bci.BLOCK_NR+1
prime.BLOCK_NR=nft.BLOCK_NR=bci.BLOCK_NR
#task 1: rest olhos fechados
bci.TASK_NR +=1
rest.TASK_NR=prime.TASK_NR=nft.TASK_NR=bci.TASK_NR
rest.STIM_TIME= master_stim_1 #s
rest.protocol_eyes="eyes_closed_v2"
rest.START_WAIT_FOR_KEY=True
rest.on_play_check(markernumerate=bci.TASK_NR)
#task 2: rest olhos abertos
bci.TASK_NR +=1
rest.TASK_NR=prime.TASK_NR=nft.TASK_NR=bci.TASK_NR
rest.STIM_TIME= master_stim_1 #s
rest.protocol_eyes="eyes_open_v2"
rest.START_WAIT_FOR_KEY=True
rest.on_play_check(markernumerate=bci.TASK_NR)
#task 3: nft
bci.TASK_NR+=1
rest.TASK_NR=prime.TASK_NR=nft.TASK_NR=bci.TASK_NR
nft.STIM_TIME= master_stim_2 #s
nft.protocol_eyes="eyes_open"
nft.START_WAIT_FOR_KEY=False
nft.initial_reward_bands, nft.initial_inhibit_bands = update_reward_bands_eo, update_inhibit_bands_eo #or self.reward_bands, self.inhibit_bands - last calculated reward and inhibit bands
nft.on_play_check( markernumerate=bci.TASK_NR)#nft.on_play(markernumerate=bci.TASK_NR)
#task report
report.START_WAIT_FOR_KEY=True
report.on_play_check()
"""
bci.elapsed_time = time.time() - bci.start_time
logger.info("!!ELAPSED TIME INIT METHODS BCICLASS!! : {}".format(
bci.elapsed_time))
nft.serialize(objectname="nftclass_finalstate")
prime.serialize(objectname="primeclass_finalstate")
bci.serialize(objectname="bci_finalstate")
bci.on_quit()
except Exception as e:
logger.error("!!!!SOMETHING WENT WRONG DURING BCI : {}".format(e))
bci.on_quit()