data_file_path = data_file_path[0]
dpath,dfile=os.path.split(data_file_path)
# Lets time how long processing takes
#
start_time=getTime()
# Create an instance of the ExperimentDataAccessUtility class
# for the selected DataStore file. This allows us to access data
# in the file based on Device Event names and attributes, as well
# as access the experiment session metadata saved with each session run.
dataAccessUtil=ExperimentDataAccessUtility(dpath,dfile, experimentCode=None,sessionCodes=[])
# Get a dict of all event types -> DataStore table info
# for the selected DataStore file.
eventTableMappings=dataAccessUtil.getEventMappingInformation()
# Get event tables that have data...
#
events_with_data=dataAccessUtil.getEventsByType()
duration=getTime()-start_time
# Select which event table to output by displaying a list of
# Event Class Names that have data available to the user...
event_class_selection=displayEventTableSelectionDialog("Select Event Type to Save", "Event Type:",
[eventTableMappings[event_id].class_name.decode('utf-8') for event_id in list(events_with_data.keys())])
if event_class_selection is None:
print("Event table Selection Cancelled, exiting...")
dataAccessUtil.close()
sys.exit(0)
def convertToText(self, dir, name, localtime):
# Select the hdf5 file to process.
#data_file_path= displayDataFileSelectionDialog(psychopy.iohub.module_directory(writeOutputFileHeader))
print(' this is dir')
print(dir)
data_file_path = dir + '\events.hdf5'
if data_file_path is None:
print("File Selection Cancelled, exiting...")
sys.exit(0)
dpath, dfile = os.path.split(data_file_path)
print('dpath')
print(dpath)
print('dfile')
print(dfile)
# Lets time how long processing takes
#
start_time = getTime()
# Create an instance of the ExperimentDataAccessUtility class
# for the selected DataStore file. This allows us to access data
# in the file based on Device Event names and attributes, as well
# as access the experiment session metadata saved with each session run.
dataAccessUtil = ExperimentDataAccessUtility(dpath,
dfile,
experimentCode=None,
sessionCodes=[])
print('this is dataaccessutil:')
print(dataAccessUtil)
# Get a dict of all event types -> DataStore table info
# for the selected DataStore file.
eventTableMappings = dataAccessUtil.getEventMappingInformation()
# Get event tables that have data...
#
events_with_data = dataAccessUtil.getEventsByType()
duration = getTime() - start_time
# Select which event table to output by displaying a list of
# Event Class Names that have data available to the user...
#event_class_selection=displayEventTableSelectionDialog("Select Event Type to Save", "Event Type:",
# [eventTableMappings[event_id].class_name for event_id in events_with_data.keys()])
event_class_selection = 'BinocularEyeSampleEvent'
print('event_class_selection')
print(event_class_selection)
if event_class_selection == None:
print("Event table Selection Cancelled, exiting...")
dataAccessUtil.close()
sys.exit(0)
# restart processing time calculation...
#
start_time = getTime()
# Lookup the correct event iterator fiven the event class name selected.
#
event_iterator_for_output = []
for event_id, mapping_info in eventTableMappings.items():
if mapping_info.class_name == event_class_selection:
event_iterator_for_output = events_with_data[event_id]
break
# Read the session metadata table for all sessions saved to the file.
#
session_metadata = dataAccessUtil.getSessionMetaData()
print('this is dataaccessutil getsession metadata')
print(session_metadata)
sesion_meta_data_dict = dict()
# Create a session_id -> session metadata mapping for use during
# file writing.
#
session_metadata_columns = []
if len(session_metadata):
session_metadata_columns = list(session_metadata[0]._fields[:-1])
session_uservar_columns = list(
session_metadata[0].user_variables.keys())
for s in session_metadata:
sesion_meta_data_dict[s.session_id] = s
# Open a file to save the tab delimited ouput to.
#
#log_file_name="%s.%s.txt"%(dfile[:-5],event_class_selection)
log_file_name = name + '_EyeSample' + localtime + '.txt'
with open(dir + '\\Exp Results\\' + log_file_name, 'w') as output_file:
# write column header
#
writeOutputFileHeader(
output_file, session_metadata_columns,
dataAccessUtil.getEventTable(
event_class_selection).cols._v_colnames[3:])
print('Writing Data to %s:\n' % (dir + log_file_name)),
i = 0
for i, event in enumerate(event_iterator_for_output):
# write out each row of the event data with session
# data as prepended columns.....
#
writeDataRow(output_file,
sesion_meta_data_dict[event['session_id']],
session_uservar_columns, event[:][3:])
if i % 100 == 0: print('.'),
duration = duration + (getTime() - start_time)
#print
print(
'\nOutput Complete. %d Events Saved to %s in %.3f seconds (%.2f events/seconds).\n'
% (i, log_file_name, duration, i / duration))
print('%s will be in the same directory as the selected .hdf5 file' %
(log_file_name))
# Lets time how long processing takes
#
start_time = getTime()
# Create an instance of the ExperimentDataAccessUtility class
# for the selected DataStore file. This allows us to access data
# in the file based on Device Event names and attributes, as well
# as access the experiment session metadata saved with each session run.
dataAccessUtil = ExperimentDataAccessUtility(dpath,
dfile,
experimentCode=None,
sessionCodes=[])
# Get a dict of all event types -> DataStore table info
# for the selected DataStore file.
eventTableMappings = dataAccessUtil.getEventMappingInformation()
# Get event tables that have data...
#
events_with_data = dataAccessUtil.getEventsByType()
duration = getTime() - start_time
# Select which event table to output by displaying a list of
# Event Class Names that have data available to the user...
event_class_selection = displayEventTableSelectionDialog(
"Select Event Type to Save", "Event Type:", [
eventTableMappings[event_id].class_name
for event_id in list(events_with_data.keys())
])
if event_class_selection is None:
