def start_recording_btn_ressed(self):
if not (len(self.parent.LSL_data_buffer_dicts.keys()) >= 1 or len(self.parent.cam_workers) >= 1):
dialog_popup('You need at least one LSL Stream or Capture opened to start recording!')
return
self.save_path = self.generate_save_path() # get a new save path
self.save_stream = RNStream(self.save_path)
self.recording_buffer = {} # clear buffer
self.is_recording = True
self.StartRecordingBtn.setEnabled(False)
self.StopRecordingBtn.setEnabled(True)
self.recording_byte_count = 0
self.timer.start()
def create_test_stream(test_stream_length, test_stream_mean,
test_stream_variance):
temp_dir_path = tempfile.mkdtemp()
stream = RNStream(os.path.join(temp_dir_path, 'test.dats'))
data_ts = [
gauss(test_stream_mean, math.sqrt(test_stream_variance))
for i in range(test_stream_length)
]
return stream, temp_dir_path, data_ts
class RecordingsTab(QtWidgets.QWidget):
def __init__(self, parent):
"""
:param lsl_data_buffer: dict, passed by reference. Do not modify, as modifying it makes a copy.
:rtype: object
"""
super().__init__()
self.ui = uic.loadUi("ui/RecordingsTab.ui", self)
self.recording_buffer = {}
self.is_recording = False
self.StartRecordingBtn.clicked.connect(self.start_recording_btn_ressed)
self.StopRecordingBtn.clicked.connect(self.stop_recording_btn_pressed)
self.SelectDataDirBtn.clicked.connect(self.select_data_dir_btn_pressed)
self.StopRecordingBtn.setEnabled(False)
self.parent = parent
self.data_dir = config.DEFAULT_DATA_DIR
self.save_path = ''
self.save_stream = None
self.saveRootTextEdit.setText(self.data_dir + '/')
self.timer = QTimer()
self.timer.setInterval(config.EVICTION_INTERVAL)
self.timer.timeout.connect(self.evict_buffer)
self.recording_byte_count = 0
def select_data_dir_btn_pressed(self):
selected_data_dir = str(QFileDialog.getExistingDirectory(self.widget_3, "Select Directory"))
if selected_data_dir != '':
self.data_dir = selected_data_dir
print("Selected data dir: ", self.data_dir)
self.saveRootTextEdit.setText(self.data_dir + '/')
def start_recording_btn_ressed(self):
if not (len(self.parent.LSL_data_buffer_dicts.keys()) >= 1 or len(self.parent.cam_workers) >= 1):
dialog_popup('You need at least one LSL Stream or Capture opened to start recording!')
return
self.save_path = self.generate_save_path() # get a new save path
self.save_stream = RNStream(self.save_path)
self.recording_buffer = {} # clear buffer
self.is_recording = True
self.StartRecordingBtn.setEnabled(False)
self.StopRecordingBtn.setEnabled(True)
self.recording_byte_count = 0
self.timer.start()
def stop_recording_btn_pressed(self):
self.is_recording = False
self.StopRecordingBtn.setEnabled(False)
self.StartRecordingBtn.setEnabled(True)
self.evict_buffer()
self.timer.stop()
self.recording_byte_count = 0
self.update_file_size_label()
dialog_popup('Saved to {0}'.format(self.save_path), title='Info')
def update_buffers(self, data_dict: dict):
if self.is_recording:
lsl_data_type = data_dict['lsl_data_type'] # get the type of the newly-come data
if lsl_data_type not in self.recording_buffer.keys():
self.recording_buffer[lsl_data_type] = [np.empty(shape=(data_dict['frames'].shape[0], 0)),
np.empty(shape=(0,))] # data first, timestamps second
buffered_data = self.recording_buffer[data_dict['lsl_data_type']][0]
buffered_timestamps = self.recording_buffer[data_dict['lsl_data_type']][1]
self.recording_buffer[lsl_data_type][0] = np.concatenate([buffered_data, data_dict['frames']], axis=-1)
self.recording_buffer[lsl_data_type][1] = np.concatenate([buffered_timestamps, data_dict['timestamps']])
pass
def update_camera_screen_buffer(self, cam_id, new_frame, timestamp):
if self.is_recording:
if cam_id not in self.recording_buffer.keys(): # note array data type is uint8 0~255
self.recording_buffer[cam_id] = [np.empty(shape=new_frame.shape + (0,), dtype=np.uint8),
np.empty(shape=(0,)), np.empty(shape=(0,))]
_new_frame = np.expand_dims(new_frame, axis=-1)
buffered_data = self.recording_buffer[cam_id][0]
buffered_timestamps = self.recording_buffer[cam_id][1]
self.recording_buffer[cam_id][0] = np.concatenate([buffered_data, _new_frame.astype(np.uint8)], axis=-1)
self.recording_buffer[cam_id][1] = np.concatenate([buffered_timestamps, [timestamp]])
self.recording_buffer[cam_id][2] = np.concatenate([self.recording_buffer[cam_id][2], [time.time()]])
pass
def generate_save_path(self):
os.makedirs(self.saveRootTextEdit.toPlainText(), exist_ok=True)
# datetime object containing current date and time
now = datetime.now()
dt_string = now.strftime("%m_%d_%Y_%H_%M_%S")
return os.path.join(self.saveRootTextEdit.toPlainText(),
'{0}-Exp_{1}-Sbj_{2}-Ssn_{3}.dats'.format(dt_string,
self.experimentNameTextEdit.toPlainText(),
self.subjectTagTextEdit.toPlainText(),
self.sessionTagTextEdit.toPlainText()))
def evict_buffer(self):
self.recording_byte_count += self.save_stream.stream_out(self.recording_buffer)
self.recording_buffer = {}
self.update_file_size_label()
def update_file_size_label(self):
self.parent.recordingFileSizeLabel. \
setText(' Recording file size: {0} Mb'.format(str(round(self.recording_byte_count / 10 ** 6, 2))))
import pickle
import time
from utils.data_utils import RNStream
# recording_buffer = pickle.load(open('C:/Recordings/03_21_2021_22_48_25-Exp_Unity.RealityNavigationHotel.EventMarkers-Sbj_someone-Ssn_0.p', 'rb'))
# rns.stream_out(recording_buffer)
rns = RNStream(
'C:/Users/S-Vec/Dropbox/research/RealityNavigation/Data/Pilot/03_22_2021_17_13_28-Exp_realitynavigation-Sbj_0-Ssn_3.dats'
)
print('String names are {0}'.format(str(rns.get_stream_names())))
start_time = time.time()
reloaded_buffer = rns.stream_in(only_stream=('BioSemi', ))
print('reload with only took {0}'.format(time.time() - start_time))
#
# start_time = time.time()
# reloaded_buffer = rns.stream_in(ignore_stream=('monitor1', '0'))
# print('reload with ignore took {0}'.format(time.time() - start_time))
#
#
# start_time = time.time()
# reloaded_buffer = rns.stream_in()
# print('reload all took {0}'.format(time.time() - start_time))
rns.generate_video(video_stream_name='monitor1')
import os
import numpy as np
import cv2
import config
from utils.data_utils import RNStream
import matplotlib.pyplot as plt
data_root = 'C:/Users/S-Vec/Dropbox/research/RealityNavigation/Data/Pilot/'
data_fn = '03_22_2021_17_03_52-Exp_realitynavigation-Sbj_0-Ssn_2.dats'
video_stream_label = 'monitor1'
rns = RNStream(os.path.join(data_root, data_fn))
data = rns.stream_in(ignore_stream=('0'))
video_frame_stream = data[video_stream_label][0]
frame_count = video_frame_stream.shape[-1]
frame_size = (data[video_stream_label][0].shape[1],
data[video_stream_label][0].shape[0])
out_path = os.path.join(
data_root, '{0}_{1}.avi'.format(data_fn.split('.')[0], video_stream_label))
out = cv2.VideoWriter(out_path, cv2.VideoWriter_fourcc(*'DIVX'),
1 / config.CAMERA_SCREENCAPTURE_REFRESH_INTERVAL,
frame_size)
for i in range(frame_count):
print('Creating video progress {}%'.format(
str(round(100 * i / frame_count, 2))),
sep=' ',
import numpy as np
from utils.data_utils import RNStream
import matplotlib.pyplot as plt
from matplotlib.pyplot import figure
file_path = 'C:/Users/S-Vec/Dropbox/research/RealityNavigation/Data/Pilot/03_22_2021_16_52_54-Exp_realitynavigation-Sbj_0-Ssn_1.dats'
em_stream_name = 'Unity.RotationWheel.EventMarkers'
rns = RNStream(file_path)
data = rns.stream_in(ignore_stream=('monitor1', '0'))
data_stream = data[em_stream_name][0]
timestamps_stream = data[em_stream_name][1]
event_label_stream = data_stream[-1, :]
item_count = 5
offset = 2
trial_count = 24
trial_started_index = 0
for target_label in range(offset, offset + 5):
target_onset_em = np.logical_and(
event_label_stream == target_label,
np.concatenate([np.array([0]),
np.diff(event_label_stream)]) != 0)
started_em = event_label_stream >= 1
started = False
target_count = 0
target_indices = []
clean_count = 0
trial_count = 0
for i in range(1, len(target_onset_em)):
from utils.data_utils import RNStream
test_rns = RNStream('C:/Recordings/test.dats')
test_reloaded_data = test_rns.stream_in()
another_rns = RNStream(
'C:/Recordings/03_22_2021_00_00_55-Exp_myexperiment-Sbj_someone-Ssn_0.dats'
)
another_reloaded_data = another_rns.stream_in()
result_rns = RNStream('C:/Recordings/results.dats')
result_rns.stream_out(test_reloaded_data)
result_rns.stream_out(another_reloaded_data)
results_reloaded_data = result_rns.stream_in()
from utils.data_utils import RNStream
test_rns = RNStream(
'/Users/Leo/Dropbox/research/RealityNavigation/Data/Pilot/03_22_2021_17_03_52-Exp_realitynavigation-Sbj_0-Ssn_2.dats'
)
reloaded_data = test_rns.stream_in(ignore_stream=('monitor1', '0'))