def get_list_amount_activities_RescueTime_interval_with_mindwave(
self, session_id, statistic_type):
result_x = []
result_y = []
datetime_from_session, datetime_to_session = self.dasession.get_dates_session(
session_id)
list_dates = self.rescuetimeDataProcessing.get_dates_list(
datetime_from_session, datetime_to_session)
mindwave_data_list = Mindwave_data_processing.get_mindwave_data_filtered_smoothed(
datetime_from_session, datetime_to_session, 10)
for interval in list_dates:
rescueTime_data = self.darescuetime.get_data_specific_period(
interval[0], interval[1])
result_x.append(len(rescueTime_data))
sublist = Mindwave_data_processing.get_sublist(
mindwave_data_list, datetime_from_session, datetime_to_session)
if statistic_type == Calculate_statistics_enumeration.AVG:
attention, meditation = Mindwave_data_processing.calculate_avg_attention_meditation(
sublist)
elif statistic_type == Calculate_statistics_enumeration.STD:
attention, meditation = Mindwave_data_processing.calculate_std_attention_meditation(
sublist)
else:
raise Exception.UnknownID("The statistic_type is unknown")
result_y.append(attention)
print "rescuetime amount"
print "result_x"
print result_x
print "result_y"
print result_y
return result_x, result_y
def get_list_amount_activities_RescueTime_interval_with_mindwave(self,session_id,statistic_type):
result_x = []
result_y = []
datetime_from_session, datetime_to_session = self.dasession.get_dates_session(session_id)
list_dates = self.rescuetimeDataProcessing.get_dates_list(datetime_from_session, datetime_to_session)
mindwave_data_list = Mindwave_data_processing.get_mindwave_data_filtered_smoothed(datetime_from_session,datetime_to_session,10)
for interval in list_dates:
rescueTime_data = self.darescuetime.get_data_specific_period(interval[0], interval[1])
result_x.append(len(rescueTime_data))
sublist = Mindwave_data_processing.get_sublist(mindwave_data_list,datetime_from_session,datetime_to_session)
if statistic_type == Calculate_statistics_enumeration.AVG:
attention, meditation = Mindwave_data_processing.calculate_avg_attention_meditation(sublist)
elif statistic_type == Calculate_statistics_enumeration.STD:
attention, meditation = Mindwave_data_processing.calculate_std_attention_meditation(sublist)
else:
raise Exception.UnknownID("The statistic_type is unknown")
result_y.append(attention)
print "rescuetime amount"
print "result_x"
print result_x
print "result_y"
print result_y
return result_x, result_y
def test_merge_buckets(self):
dates = []
dates.append(datetime.datetime.strptime("2013-12-28 08:00:00","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:01","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:02","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:03","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:04","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:05","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:06","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:07","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:08","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:09","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:10","%Y-%m-%d %H:%M:%S"))
mindwave_data = []
mindwave_data.append([dates[0],dates[1],0.2,0.2,0,0])
mindwave_data.append([dates[1],dates[2],0.4,0.5,0,0])
mindwave_data.append([dates[2],dates[3],0.8,0.2,0,0])
mindwave_data.append([dates[3],dates[4],0.1,0.5,0,0])
mindwave_data.append([dates[4],dates[5],0.9,0.1,0,0])
mindwave_data.append([dates[5],dates[6],0.4,0.8,0,0])
mindwave_data.append([dates[6],dates[7],0.8,0.3,0,0])
mindwave_data.append([dates[7],dates[8],0.2,0.6,0,0])
mindwave_data.append([dates[8],dates[9],0.0,1.0,0,0])
mindwave_data.append([dates[9],dates[10],0.4,0.5,0,0])
datetime_from = datetime.datetime.strptime("2013-12-28 08:00:00","%Y-%m-%d %H:%M:%S")
datetime_to = datetime.datetime.strptime("2013-12-28 08:30:00","%Y-%m-%d %H:%M:%S")
attention_bucket, meditation_bucket = Mindwave_data_processing.get_attention_meditation_buckets(datetime_from,datetime_to,mindwave_data)
attention_bucket_array = [attention_bucket, attention_bucket]
meditation_bucket_array = [meditation_bucket, meditation_bucket]
attention_bucket_result, meditation_bucket_result = Mindwave_data_processing.merge_buckets(attention_bucket_array, meditation_bucket_array)
self.assertEqual(attention_bucket_result[0],0.20)
self.assertEqual(attention_bucket_result[1],0.20)
self.assertEqual(attention_bucket_result[2],0.30)
self.assertEqual(attention_bucket_result[3],0.0)
self.assertEqual(attention_bucket_result[4],0.3)
self.assertEqual(meditation_bucket_result[0],0.1)
self.assertEqual(meditation_bucket_result[1],0.3)
self.assertEqual(meditation_bucket_result[2],0.3)
self.assertEqual(meditation_bucket_result[3],0.1)
self.assertEqual(meditation_bucket_result[4],0.2)
print str("attention_bucket")
print attention_bucket_result
print str("meditation_bucket")
print meditation_bucket_result
def get_mindwave_data_avg_per_RescueTime_interval(self, datetime_from, datetime_to):
#datetime_from, datetime_to = self.daSession.get_dates_session(session_id)
list_mindwave_data = self.get_mindwave_data_smoothened(datetime_from, datetime_to)
list_dates_Rescuetime = self.daRescueTime.get_dates(datetime_from, datetime_to)
x_axis, attention_data, meditation_data = Mindwave_data_processing.convert_mindwave_data_to_RescueTime_intervals(
list_mindwave_data, list_dates_Rescuetime)
x_axis_converted = []
attention_data_converted = []
meditation_data_converted = []
mindwave_data_converted = []
for index in range(0, len(list_mindwave_data)):
try:
datetime_from_mindwave = datetime.datetime.strptime(list_mindwave_data[index][1],
"%Y-%m-%d %H:%M:%S.%f")
except:
datetime_from_mindwave = datetime.datetime.strptime(list_mindwave_data[index][1], "%Y-%m-%d %H:%M:%S")
try:
datetime_to_mindwave = datetime.datetime.strptime(list_mindwave_data[index][2],
"%Y-%m-%d %H:%M:%S.%f")
except:
datetime_to_mindwave = datetime.datetime.strptime(list_mindwave_data[index][2], "%Y-%m-%d %H:%M:%S")
for index_m_c in range(0, len(x_axis)):
if datetime_from_mindwave >= x_axis[index_m_c][0] and datetime_from_mindwave < x_axis[index_m_c][1]:
x_axis_converted.append(datetime_from_mindwave)
attention_data_converted.append(attention_data[index_m_c])
meditation_data_converted.append(meditation_data[index_m_c])
mindwave_data_converted.append([datetime_from_mindwave,datetime_to_mindwave,attention_data[index_m_c],meditation_data[index_m_c]])
mindwave_data_specific_period = [mindwave_data_converted, x_axis_converted, attention_data_converted, meditation_data_converted]
return mindwave_data_specific_period
def get_mindwave_data_avg_per_manualLog_interval(self, list_manual_log):
datetime_from = list_manual_log[0][0]
datetime_to = list_manual_log[len(list_manual_log) - 1][1]
list_mindwave_data = self.get_mindwave_data_smoothened(datetime_from, datetime_to)
x_axis, attention_data, meditation_data = Mindwave_data_processing.convert_mindwave_data_to_manualLog_intervals(
list_mindwave_data, list_manual_log)
x_axis_converted = []
attention_data_converted = []
meditation_data_converted = []
mindwave_data_converted = []
for index in range(0, len(list_mindwave_data)):
try:
datetime_from_mindwave = datetime.datetime.strptime(list_mindwave_data[index][1],
"%Y-%m-%d %H:%M:%S.%f")
except:
datetime_from_mindwave = datetime.datetime.strptime(list_mindwave_data[index][1], "%Y-%m-%d %H:%M:%S")
try:
datetime_to_mindwave = datetime.datetime.strptime(list_mindwave_data[index][2],
"%Y-%m-%d %H:%M:%S.%f")
except:
datetime_to_mindwave = datetime.datetime.strptime(list_mindwave_data[index][2], "%Y-%m-%d %H:%M:%S")
for index_m_c in range(0, len(x_axis)):
if datetime_from_mindwave >= x_axis[index_m_c][0] and datetime_from_mindwave < x_axis[index_m_c][1]:
x_axis_converted.append(datetime_from_mindwave)
attention_data_converted.append(attention_data[index_m_c])
meditation_data_converted.append(meditation_data[index_m_c])
mindwave_data_converted.append([datetime_from_mindwave,datetime_to_mindwave,attention_data[index_m_c],meditation_data[index_m_c]])
return mindwave_data_converted, x_axis_converted, attention_data_converted, meditation_data_converted
def test_get_sublist(self):
dates = []
dates.append(datetime.datetime.strptime("2013-12-28 08:00:00","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:01.630000","%Y-%m-%d %H:%M:%S.%f"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:02.630000","%Y-%m-%d %H:%M:%S.%f"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:03","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:04","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:05","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:06","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:07","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:08","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:09","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:10","%Y-%m-%d %H:%M:%S"))
mindwave_data = []
mindwave_data.append([dates[0],dates[1],0.2,0.2])
mindwave_data.append([dates[1],dates[2],0.4,0.5])
mindwave_data.append([dates[2],dates[3],0.8,0.2])
mindwave_data.append([dates[3],dates[4],0.1,0.5])
mindwave_data.append([dates[4],dates[5],0.9,0.1])
mindwave_data.append([dates[5],dates[6],0.4,0.8])
mindwave_data.append([dates[6],dates[7],0.8,0.3])
mindwave_data.append([dates[7],dates[8],0.2,0.6])
mindwave_data.append([dates[8],dates[9],0.0,1.0])
mindwave_data.append([dates[9],dates[10],0.4,0.5])
datetime_from = datetime.datetime.strptime("2013-12-28 08:00:02","%Y-%m-%d %H:%M:%S")
datetime_to = datetime.datetime.strptime("2013-12-28 08:00:10","%Y-%m-%d %H:%M:%S")
sublist = Mindwave_data_processing.get_sublist(mindwave_data,datetime_from,datetime_to)
self.assertEqual(sublist[0][0],dates[2])
self.assertEqual(sublist[len(sublist)-1][1],dates[10])
self.assertEqual(len(sublist),8)
def test_calculate_avg_attention_meditation(self):
dates = []
dates.append(datetime.datetime.strptime("2013-12-28 08:00:00","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:01.630000","%Y-%m-%d %H:%M:%S.%f"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:02.630000","%Y-%m-%d %H:%M:%S.%f"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:03","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:04","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:05","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:06","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:07","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:08","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:09","%Y-%m-%d %H:%M:%S"))
dates.append(datetime.datetime.strptime("2013-12-28 08:00:10","%Y-%m-%d %H:%M:%S"))
mindwave_data = []
mindwave_data.append([dates[0],dates[1],0.2,0.2])
mindwave_data.append([dates[1],dates[2],0.4,0.5])
mindwave_data.append([dates[2],dates[3],0.8,0.2])
mindwave_data.append([dates[3],dates[4],0.1,0.5])
mindwave_data.append([dates[4],dates[5],0.9,0.1])
mindwave_data.append([dates[5],dates[6],0.4,0.8])
attention_avg, meditation_avg = Mindwave_data_processing.calculate_avg_attention_meditation(mindwave_data)
self.assertEqual(round(attention_avg,2),0.47)
self.assertEqual(round(meditation_avg,2),0.38)
def test_get_sublist(self):
dates = []
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:00",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:01.630000",
"%Y-%m-%d %H:%M:%S.%f"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:02.630000",
"%Y-%m-%d %H:%M:%S.%f"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:03",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:04",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:05",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:06",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:07",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:08",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:09",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:10",
"%Y-%m-%d %H:%M:%S"))
mindwave_data = []
mindwave_data.append([dates[0], dates[1], 0.2, 0.2])
mindwave_data.append([dates[1], dates[2], 0.4, 0.5])
mindwave_data.append([dates[2], dates[3], 0.8, 0.2])
mindwave_data.append([dates[3], dates[4], 0.1, 0.5])
mindwave_data.append([dates[4], dates[5], 0.9, 0.1])
mindwave_data.append([dates[5], dates[6], 0.4, 0.8])
mindwave_data.append([dates[6], dates[7], 0.8, 0.3])
mindwave_data.append([dates[7], dates[8], 0.2, 0.6])
mindwave_data.append([dates[8], dates[9], 0.0, 1.0])
mindwave_data.append([dates[9], dates[10], 0.4, 0.5])
datetime_from = datetime.datetime.strptime("2013-12-28 08:00:02",
"%Y-%m-%d %H:%M:%S")
datetime_to = datetime.datetime.strptime("2013-12-28 08:00:10",
"%Y-%m-%d %H:%M:%S")
sublist = Mindwave_data_processing.get_sublist(mindwave_data,
datetime_from,
datetime_to)
self.assertEqual(sublist[0][0], dates[2])
self.assertEqual(sublist[len(sublist) - 1][1], dates[10])
self.assertEqual(len(sublist), 8)
def getListUnimportantActivities_V2_buckets(datetime_from,datetime_to,link_to_main):
daRescueTime = DARescueTime_SQLite.RescueTime(link_to_main)
unimportant_activities_list = daRescueTime.get_data_unimportant_activities_specific_period_group_by_activity(datetime_from,datetime_to)
result = []
previous_datetime_to = None
for activity in unimportant_activities_list:
activity_details = daRescueTime.get_data_unimportant_activities_specific_period_activity(datetime_from,datetime_to,activity[1])
attention_bucket_total = []
meditation_bucket_total = []
gemiddelde_reading = 0.0
totaal_reading = 0.0
for activity_detail in activity_details:
start_datetime = datetime.datetime.strptime(activity_detail[1],"%Y-%m-%d %H:%M:%S")
end_datetime = start_datetime + datetime.timedelta(minutes=5)
# Mindwave, gemiddelde berekenen
list_mindwave_data = Mindwave_data_processing.get_mindwave_data_filtered_smoothed(datetime_from,datetime_to,10)
# Mindwave, gemiddelde berekenen
attention_bucket, meditation_bucket = Mindwave_data_processing.get_attention_meditation_buckets(start_datetime,end_datetime,list_mindwave_data)
attention_bucket_total.append(attention_bucket)
meditation_bucket_total.append(meditation_bucket)
# reading
reading_temp = Read_detection_processing.get_average_reading_specific_period(start_datetime,end_datetime)
if reading_temp > 0:
gemiddelde_reading += reading_temp
totaal_reading += 1
# moet refereren naar item in lijst activity_details, niet naar end_datetime
previous_datetime_to = datetime.datetime.strptime(activity_detail[1],"%Y-%m-%d %H:%M:%S") + datetime.timedelta(minutes=5)
if len(attention_bucket_total) > 0:
attention_bucket_avg, meditation_bucket_avg = Mindwave_data_processing.merge_buckets(attention_bucket_total, meditation_bucket_total)
if totaal_reading > 0:
gemiddelde_reading = float(gemiddelde_reading / totaal_reading)
result.append([activity[1],activity[0],attention_bucket_avg, meditation_bucket_avg,gemiddelde_reading])
return result
def get_list_concentration_time_spent_activity(self,manual_log_list,mindwave_data,activity,type_statistics):
result_x = []
result_y = []
for item in manual_log_list:
difference = (item[1] - item[0]).seconds
if item[2] == activity and difference >= self.treshold_activity_duration:
try:
sublist = Mindwave_data_processing.get_sublist(mindwave_data,item[0],item[1])
if type_statistics == Calculate_statistics_enumeration.AVG:
attention, meditation = Mindwave_data_processing.calculate_avg_attention_meditation(sublist)
elif type_statistics == Calculate_statistics_enumeration.STD:
attention, meditation = Mindwave_data_processing.calculate_std_attention_meditation(sublist)
result_x.append(difference)
result_y.append(attention)
except Exception,e:
print str(e)
def get_statistics_attention_userstates(self,activities,manual_log_list, mindwave_data_list,statistic_type):
result_x = []
result_y = []
for activity in activities:
try:
sublist_mindwave_activity = []
for item in manual_log_list:
if item[2] == activity:
sublist_mindwave_activity += Mindwave_data_processing.get_sublist(mindwave_data_list,item[0],item[1])
if statistic_type == Calculate_statistics_enumeration.AVG:
attention, meditation = Mindwave_data_processing.calculate_avg_attention_meditation(sublist_mindwave_activity)
elif statistic_type == Calculate_statistics_enumeration.STD:
attention, meditation = Mindwave_data_processing.calculate_std_attention_meditation(sublist_mindwave_activity)
else:
raise Exception.UnknownID("The type_statistics ID is unknown")
result_y.append(attention)
result_x.append(activity)
except Exception, e:
str(e)
def mindwave_data_raw(self, session_id):
datetime_from, datetime_to = self.dasession.get_dates_session(
session_id)
attention_data, x, y_attention, y_meditation = Mindwave_data_processing.get_mindwave_data_raw(
datetime_from, datetime_to)
title = "session_ID: " + str(session_id) + "mindwave data raw"
self.plot_data(attention_data, x, y_attention, y_meditation, None,
None, None, title, self.x_label, self.y_label)
def get_list_amount_used_programs_concentration_per_interval(self,mindwave_data,manual_log, list_dates_interval,type_statistic):
result_x = []
result_y = []
for i in range(0,len(list_dates_interval)):
datetime_from = list_dates_interval[i][0]
datetime_to = list_dates_interval[i][1]
sublist = Mindwave_data_processing.get_sublist(mindwave_data,datetime_from,datetime_to)
try:
if type_statistic==Calculate_statistics_enumeration.AVG:
attention, meditation = Mindwave_data_processing.calculate_avg_attention_meditation(sublist)
elif type_statistic==Calculate_statistics_enumeration.STD:
attention, meditation = Mindwave_data_processing.calculate_std_attention_meditation(sublist)
else:
raise Exception.UnknownID("The type_statistics ID is unknown")
amount = self.count_activities(manual_log,datetime_from,datetime_to)
result_x.append(amount)
result_y.append(attention)
except Exception, e:
str(e)
def get_list_impact_concentration_manual_logs(self,manual_log_list,mindwave_data):
activities,manual_log_testpersoon_B = Manual_log.get_manual_logfile_Testpersoon_B_enkel_programmas_websites()
datetime_from = manual_log_testpersoon_B[0][0]
datetime_to = manual_log_testpersoon_B[len(manual_log_testpersoon_B) - 1][1]
mindwave_data_list = Mindwave_data_processing.get_mindwave_data_filtered_smoothed(datetime_from,datetime_to,10)
result_x, result_y = self.get_list_concentration_differences_manual_log(manual_log_testpersoon_B,mindwave_data_list)
return result_x, result_y
def mindwave_userfeedback_data(self, session_id):
datetime_from, datetime_to = self.dasession.get_dates_session(
session_id)
attention_data, x, y_attention, y_meditation, y_userfeedback = Mindwave_data_processing.get_mindwave_userfeedback_data(
datetime_from, datetime_to, self.window_RescueTime)
title = "mindwave data per user estimated concentration"
self.plot_data(attention_data, x, y_attention, y_meditation,
y_userfeedback, None, None, title, self.x_label,
self.y_label)
print str("function 'mindwave_userfeedback_data' for session_Id: " +
str(session_id) + " completed")
def test_calculate_avg_attention_meditation(self):
dates = []
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:00",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:01.630000",
"%Y-%m-%d %H:%M:%S.%f"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:02.630000",
"%Y-%m-%d %H:%M:%S.%f"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:03",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:04",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:05",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:06",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:07",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:08",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:09",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:10",
"%Y-%m-%d %H:%M:%S"))
mindwave_data = []
mindwave_data.append([dates[0], dates[1], 0.2, 0.2])
mindwave_data.append([dates[1], dates[2], 0.4, 0.5])
mindwave_data.append([dates[2], dates[3], 0.8, 0.2])
mindwave_data.append([dates[3], dates[4], 0.1, 0.5])
mindwave_data.append([dates[4], dates[5], 0.9, 0.1])
mindwave_data.append([dates[5], dates[6], 0.4, 0.8])
attention_avg, meditation_avg = Mindwave_data_processing.calculate_avg_attention_meditation(
mindwave_data)
self.assertEqual(round(attention_avg, 2), 0.47)
self.assertEqual(round(meditation_avg, 2), 0.38)
def get_mindwave_data_avg_per_RescueTime_interval(self, datetime_from,
datetime_to):
#datetime_from, datetime_to = self.daSession.get_dates_session(session_id)
list_mindwave_data = self.get_mindwave_data_smoothened(
datetime_from, datetime_to)
list_dates_Rescuetime = self.daRescueTime.get_dates(
datetime_from, datetime_to)
x_axis, attention_data, meditation_data = Mindwave_data_processing.convert_mindwave_data_to_RescueTime_intervals(
list_mindwave_data, list_dates_Rescuetime)
x_axis_converted = []
attention_data_converted = []
meditation_data_converted = []
mindwave_data_converted = []
for index in range(0, len(list_mindwave_data)):
try:
datetime_from_mindwave = datetime.datetime.strptime(
list_mindwave_data[index][1], "%Y-%m-%d %H:%M:%S.%f")
except:
datetime_from_mindwave = datetime.datetime.strptime(
list_mindwave_data[index][1], "%Y-%m-%d %H:%M:%S")
try:
datetime_to_mindwave = datetime.datetime.strptime(
list_mindwave_data[index][2], "%Y-%m-%d %H:%M:%S.%f")
except:
datetime_to_mindwave = datetime.datetime.strptime(
list_mindwave_data[index][2], "%Y-%m-%d %H:%M:%S")
for index_m_c in range(0, len(x_axis)):
if datetime_from_mindwave >= x_axis[index_m_c][
0] and datetime_from_mindwave < x_axis[index_m_c][1]:
x_axis_converted.append(datetime_from_mindwave)
attention_data_converted.append(attention_data[index_m_c])
meditation_data_converted.append(
meditation_data[index_m_c])
mindwave_data_converted.append([
datetime_from_mindwave, datetime_to_mindwave,
attention_data[index_m_c], meditation_data[index_m_c]
])
mindwave_data_specific_period = [
mindwave_data_converted, x_axis_converted,
attention_data_converted, meditation_data_converted
]
return mindwave_data_specific_period
def mindwave_userfeedback_data_per_activity(self, session_id, activity):
datetime_from, datetime_to = self.get_dates_session(session_id)
activity_details = self.daRescueTime.gat_sum_time_secnds_specific_activity_with_treshold(
datetime_from, datetime_to, activity)
attention_data, x, y_attention, y_meditation, y_activityDuration = Mindwave_data_processing.get_mindwave_activity_data(
datetime_from, datetime_to, activity_details, self.window_other)
dates_activity = self.convert_activityDetailsList_to_datesList(
activity_details)
self.modify_per_dates(attention_data, y_attention, y_meditation,
y_activityDuration, dates_activity)
title = "session_ID: " + str(
session_id) + "mindwave data for activity: " + str(activity)
self.plot_data(attention_data, x, y_attention, y_meditation,
y_activityDuration, None, None, title, self.x_label,
self.y_label)
def get_mindwave_data_avg_per_manualLog_interval(self, list_manual_log):
datetime_from = list_manual_log[0][0]
datetime_to = list_manual_log[len(list_manual_log) - 1][1]
list_mindwave_data = self.get_mindwave_data_smoothened(
datetime_from, datetime_to)
x_axis, attention_data, meditation_data = Mindwave_data_processing.convert_mindwave_data_to_manualLog_intervals(
list_mindwave_data, list_manual_log)
x_axis_converted = []
attention_data_converted = []
meditation_data_converted = []
mindwave_data_converted = []
for index in range(0, len(list_mindwave_data)):
try:
datetime_from_mindwave = datetime.datetime.strptime(
list_mindwave_data[index][1], "%Y-%m-%d %H:%M:%S.%f")
except:
datetime_from_mindwave = datetime.datetime.strptime(
list_mindwave_data[index][1], "%Y-%m-%d %H:%M:%S")
try:
datetime_to_mindwave = datetime.datetime.strptime(
list_mindwave_data[index][2], "%Y-%m-%d %H:%M:%S.%f")
except:
datetime_to_mindwave = datetime.datetime.strptime(
list_mindwave_data[index][2], "%Y-%m-%d %H:%M:%S")
for index_m_c in range(0, len(x_axis)):
if datetime_from_mindwave >= x_axis[index_m_c][
0] and datetime_from_mindwave < x_axis[index_m_c][1]:
x_axis_converted.append(datetime_from_mindwave)
attention_data_converted.append(attention_data[index_m_c])
meditation_data_converted.append(
meditation_data[index_m_c])
mindwave_data_converted.append([
datetime_from_mindwave, datetime_to_mindwave,
attention_data[index_m_c], meditation_data[index_m_c]
])
return mindwave_data_converted, x_axis_converted, attention_data_converted, meditation_data_converted
def test_convert_mindwave_data_to_RescueTime_intervals(self):
list_dates_Rescuetime = [["2014-04-24 14:00:00"],["2014-04-24 14:05:00"],["2014-04-24 14:10:00"]]
list_mindwave_data = []
list_mindwave_data.append([0,"2014-04-24 14:00:00",None,0.50,0.40,None,None])
list_mindwave_data.append([0,"2014-04-24 14:01:00",None,0.10,0.20,None,None])
list_mindwave_data.append([0,"2014-04-24 14:02:00",None,0.60,0.30,None,None])
list_mindwave_data.append([0,"2014-04-24 14:03:00",None,0.80,0.50,None,None])
list_mindwave_data.append([0,"2014-04-24 14:04:00",None,0.10,0.50,None,None])
list_mindwave_data.append([0,"2014-04-24 14:05:00",None,0.10,0.10,None,None])
list_mindwave_data.append([0,"2014-04-24 14:06:00",None,0.50,0.90,None,None])
list_mindwave_data.append([0,"2014-04-24 14:07:00",None,0.60,0.40,None,None])
list_mindwave_data.append([0,"2014-04-24 14:08:00",None,0.80,0.60,None,None])
list_mindwave_data.append([0,"2014-04-24 14:09:00",None,0.40,0.20,None,None])
list_mindwave_data.append([0,"2014-04-24 14:10:00",None,0.60,0.30,None,None])
list_mindwave_data.append([0,"2014-04-24 14:11:00",None,0.20,0.60,None,None])
list_mindwave_data.append([0,"2014-04-24 14:12:00",None,0.80,0.80,None,None])
list_mindwave_data.append([0,"2014-04-24 14:13:00",None,0.10,0.60,None,None])
list_mindwave_data.append([0,"2014-04-24 14:14:00",None,0.30,0.10,None,None])
list_mindwave_data.append([0,"2014-04-24 14:15:00",None,0.50,0.20,None,None])
attention_data_original = []
meditation_data_original = []
for item in list_mindwave_data:
attention_data_original.append(item[3])
meditation_data_original.append(item[4])
x_axix,attention_data,meditation_data = Mindwave_data_processing.convert_mindwave_data_to_RescueTime_intervals(list_mindwave_data, list_dates_Rescuetime)
self.assertEqual(round(attention_data[0],2),round(np.mean(attention_data_original[0:6]),2))
self.assertEqual(round(attention_data[1],2),round(np.mean(attention_data_original[6:11]),2))
self.assertEqual(round(attention_data[2],2),round(np.mean(attention_data_original[11:16]),2))
self.assertEqual(round(meditation_data[0],2),round(np.mean(meditation_data_original[0:6]),2))
self.assertEqual(round(meditation_data[1],2),round(np.mean(meditation_data_original[6:11]),2))
self.assertEqual(round(meditation_data[2],2),round(np.mean(meditation_data_original[11:16]),2))
def get_statistics_session_testpersoon_B(self):
session_id = 41
datetime_from_session, datetime_to_session = self.dasession.get_dates_session(
session_id)
activities, manual_log_testpersoon_B = Manual_log.get_manual_logfile_Testpersoon_B_enkel_programmas_websites(
)
datetime_from = manual_log_testpersoon_B[0][0]
datetime_to = manual_log_testpersoon_B[len(manual_log_testpersoon_B) -
1][1]
mindwave_data_list = Mindwave_data_processing.get_mindwave_data_filtered_smoothed_middle_moving_median(
datetime_from, datetime_to, self.window_mindwave)
list_dates = self.rescuetimeDataProcessing.get_dates_list(
datetime_from_session, datetime_to_session)
result_x_diff, result_y_diff = self.manualLogDataProcessing.get_list_concentration_differences_manual_log(
manual_log_testpersoon_B, mindwave_data_list)
result_x_amount_avg, result_y_amount_avg = self.manualLogDataProcessing.get_list_amount_used_programs_concentration_per_interval(
mindwave_data_list, manual_log_testpersoon_B, list_dates,
Calculate_statistics_enumeration.AVG)
result_x_amount_std, result_y_amount_std = self.manualLogDataProcessing.get_list_amount_used_programs_concentration_per_interval(
mindwave_data_list, manual_log_testpersoon_B, list_dates,
Calculate_statistics_enumeration.STD)
result_x_avg_rescuetime_amount, result_y_avg_rescuetime_amount = self.get_list_amount_activities_RescueTime_interval_with_mindwave(
session_id, Calculate_statistics_enumeration.AVG)
result_x_std_rescuetime_amount, result_y_std_rescuetime_amount = self.get_list_amount_activities_RescueTime_interval_with_mindwave(
session_id, Calculate_statistics_enumeration.STD)
activities_important = ["Wikipedia", "Latex"]
result_x_avg, result_y_avg = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(
manual_log_testpersoon_B, mindwave_data_list,
activities_important[0], Calculate_statistics_enumeration.AVG)
result_x_std, result_y_std = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(
manual_log_testpersoon_B, mindwave_data_list,
activities_important[0], Calculate_statistics_enumeration.STD)
resultTuple_avg = ResultTuple(result_x_avg, result_y_avg)
resultTuple_std = ResultTuple(result_x_std, result_y_std)
for i in range(1, len(activities_important)):
result_x_avg_temp, result_y_avg_temp = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(
manual_log_testpersoon_B, mindwave_data_list,
activities_important[i], Calculate_statistics_enumeration.AVG)
result_x_std_temp, result_y_std_temp = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(
manual_log_testpersoon_B, mindwave_data_list,
activities_important[i], Calculate_statistics_enumeration.STD)
resultTuple_avg.merge(
ResultTuple(result_x_avg_temp, result_y_avg_temp))
resultTuple_std.merge(
ResultTuple(result_x_std_temp, result_y_std_temp))
activity_from = "Latex"
activity_to = "Wikipedia"
result_x_diff_specific_switch, result_y_diff_specific_switch = self.manualLogDataProcessing.get_list_concentration_differences_manual_log_specific_switch(
manual_log_testpersoon_B, mindwave_data_list, activity_from,
activity_to)
resultTuple_diff_specific_switch = ResultTuple(
result_x_diff_specific_switch, result_y_diff_specific_switch)
# ////////////////////////////
# /// with all activities ////
# ////////////////////////////
result_x_avg_all_act, result_y_avg_all_act = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(
manual_log_testpersoon_B, mindwave_data_list, activities[0],
Calculate_statistics_enumeration.AVG)
result_x_std_all_act, result_y_std_all_act = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(
manual_log_testpersoon_B, mindwave_data_list, activities[0],
Calculate_statistics_enumeration.STD)
resultTuple_avg_all_act = ResultTuple(result_x_avg_all_act,
result_y_avg_all_act)
resultTuple_std_all_act = ResultTuple(result_x_std_all_act,
result_y_std_all_act)
for i in range(1, len(activities)):
try:
result_x_avg_temp, result_y_avg_temp = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(
manual_log_testpersoon_B, mindwave_data_list,
activities[i], Calculate_statistics_enumeration.AVG)
result_x_std_temp, result_y_std_temp = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(
manual_log_testpersoon_B, mindwave_data_list,
activities[i], Calculate_statistics_enumeration.STD)
resultTuple_avg_all_act.merge(
ResultTuple(result_x_avg_temp, result_y_avg_temp))
resultTuple_std_all_act.merge(
ResultTuple(result_x_std_temp, result_y_std_temp))
except:
pass
# ////////////////////////////
resultTuple_diff = ResultTuple(result_x_diff, result_y_diff)
resultTuple_amount_avg = ResultTuple(result_x_amount_avg,
result_y_amount_avg)
resultTuple_amount_std = ResultTuple(result_x_amount_std,
result_y_amount_std)
resultTuple_avg_rescuetime_amount = ResultTuple(
result_x_avg_rescuetime_amount, result_y_avg_rescuetime_amount)
resultTuple_std_rescuetime_amount = ResultTuple(
result_x_std_rescuetime_amount, result_y_std_rescuetime_amount)
filename = self.folder + "data_analysis_results/testpersoon_B/"
# //////////////////////
# /// all activities ///
# //////////////////////
self.generate_csv(
"Time_spent_seconds", "Concentration avg", resultTuple_avg_all_act,
filename +
"comparison time_spent_sec against average concentration all activities"
)
self.generate_csv(
"Time_spent_seconds", "Concentration std", resultTuple_std_all_act,
filename +
"comparison time_spent_sec against std concentration all activities"
)
# //////////////////////
self.generate_csv(
"Time_spent_seconds", "Concentration avg", resultTuple_avg,
filename +
"comparison time_spent_sec against average concentration")
self.generate_csv(
"Time_spent_seconds", "Concentration std", resultTuple_std,
filename + "comparison time_spent_sec against std concentration")
self.generate_csv(
"Switch ID", "Concentration avg", resultTuple_diff, filename +
"comparison concentration difference when switch between activities"
)
self.generate_csv(
"Switch ID", "Concentration avg", resultTuple_diff_specific_switch,
filename +
"comparison concentration difference specific switch between activities"
)
self.generate_csv(
"Amount", "Concentration avg", resultTuple_amount_avg, filename +
"comparison amount used programs with avg concentration")
self.generate_csv(
"Amount", "Concentration std", resultTuple_amount_std, filename +
"comparison amount used programs with std concentration")
self.generate_csv(
"Amount", "Concentration avg", resultTuple_avg_rescuetime_amount,
filename + "comparision RescueTime amount concentration avg")
self.generate_csv(
"Amount", "Concentration std", resultTuple_std_rescuetime_amount,
filename + "comparision RescueTime amount concentration std")
resultObject = ResultObject()
resultObject.set_result_timeSpent_activity_avg(resultTuple_avg)
resultObject.set_result_timeSpent_activity_std(resultTuple_std)
resultObject.set_concentration_diff_activity_switch_avg(
resultTuple_diff)
resultObject.set_concentration_diff_specific_activity_switch_avg(
resultTuple_diff_specific_switch)
resultObject.set_result_amount_used_programs_avg(
resultTuple_amount_avg)
resultObject.set_result_amount_used_programs_std(
resultTuple_amount_std)
resultObject.set_amount_activities_RescueTime_interval_with_mindwave_avg(
resultTuple_avg_rescuetime_amount)
resultObject.set_amount_activities_RescueTime_interval_with_mindwave_std(
resultTuple_std_rescuetime_amount)
return resultObject
def get_statistics_session_testpersoon_D(self):
session_id = 11
datetime_from_session, datetime_to_session = self.dasession.get_dates_session(session_id)
activities,manual_log_testpersoon_D = Manual_log.get_manual_log_testpersoon_D_programms_and_extra_info()
activities_userstate,manual_log_testpersoon_D_userstate = Manual_log.get_manual_log_testpersoon_D_userstates()
datetime_from = manual_log_testpersoon_D[0][0]
datetime_to = manual_log_testpersoon_D[len(manual_log_testpersoon_D) - 1][1]
mindwave_data_list = Mindwave_data_processing.get_mindwave_data_filtered_smoothed_middle_moving_median(datetime_from,datetime_to,self.window_mindwave)
list_dates = self.rescuetimeDataProcessing.get_dates_list(datetime_from_session, datetime_to_session)
activities_important = ["pdf + toledovragen","powerpoint","wikipedia","toledovragen", "pdf"]
# With important activities
result_x_avg, result_y_avg = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(manual_log_testpersoon_D,mindwave_data_list,activities_important[0],Calculate_statistics_enumeration.AVG)
result_x_std, result_y_std = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(manual_log_testpersoon_D,mindwave_data_list,activities_important[0],Calculate_statistics_enumeration.STD)
resultTuple_avg = ResultTuple(result_x_avg, result_y_avg)
resultTuple_std = ResultTuple(result_x_std, result_y_std)
for i in range(1,len(activities_important)):
result_x_avg_temp, result_y_avg_temp = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(manual_log_testpersoon_D,mindwave_data_list,activities_important[i],Calculate_statistics_enumeration.AVG)
result_x_std_temp, result_y_std_temp = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(manual_log_testpersoon_D,mindwave_data_list,activities_important[i],Calculate_statistics_enumeration.STD)
resultTuple_avg.merge(ResultTuple(result_x_avg_temp,result_y_avg_temp))
resultTuple_std.merge(ResultTuple(result_x_std_temp,result_y_std_temp))
result_x_diff, result_y_diff = self.manualLogDataProcessing.get_list_concentration_differences_manual_log(manual_log_testpersoon_D,mindwave_data_list)
# ////////////////////////////
# /// with all activities ////
# ////////////////////////////
result_x_avg_all_act, result_y_avg_all_act = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(manual_log_testpersoon_D,mindwave_data_list,activities[0],Calculate_statistics_enumeration.AVG)
result_x_std_all_act, result_y_std_all_act = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(manual_log_testpersoon_D,mindwave_data_list,activities[0],Calculate_statistics_enumeration.STD)
resultTuple_avg_all_act = ResultTuple(result_x_avg_all_act, result_y_avg_all_act)
resultTuple_std_all_act = ResultTuple(result_x_std_all_act, result_y_std_all_act)
for i in range(1,len(activities)):
try:
result_x_avg_temp, result_y_avg_temp = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(manual_log_testpersoon_D,mindwave_data_list,activities[i],Calculate_statistics_enumeration.AVG)
result_x_std_temp, result_y_std_temp = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(manual_log_testpersoon_D,mindwave_data_list,activities[i],Calculate_statistics_enumeration.STD)
resultTuple_avg_all_act.merge(ResultTuple(result_x_avg_temp,result_y_avg_temp))
resultTuple_std_all_act.merge(ResultTuple(result_x_std_temp,result_y_std_temp))
except:
pass
# ////////////////////////////
result_x_amount_avg, result_y_amount_avg = self.manualLogDataProcessing.get_list_amount_used_programs_concentration_per_interval(mindwave_data_list,manual_log_testpersoon_D,list_dates,Calculate_statistics_enumeration.AVG)
result_x_amount_std, result_y_amount_std = self.manualLogDataProcessing.get_list_amount_used_programs_concentration_per_interval(mindwave_data_list,manual_log_testpersoon_D,list_dates,Calculate_statistics_enumeration.STD)
result_x_avg_rescuetime_amount, result_y_avg_rescuetime_amount = self.get_list_amount_activities_RescueTime_interval_with_mindwave(session_id,Calculate_statistics_enumeration.AVG)
result_x_std_rescuetime_amount, result_y_std_rescuetime_amount = self.get_list_amount_activities_RescueTime_interval_with_mindwave(session_id,Calculate_statistics_enumeration.STD)
result_x_avg_userstate, result_y_avg_userstate = self.manualLogDataProcessing.get_statistics_attention_userstates(activities_userstate,manual_log_testpersoon_D_userstate,mindwave_data_list,Calculate_statistics_enumeration.AVG)
result_x_std_userstate, result_y_std_userstate = self.manualLogDataProcessing.get_statistics_attention_userstates(activities_userstate,manual_log_testpersoon_D_userstate,mindwave_data_list,Calculate_statistics_enumeration.STD)
resultTuple_diff = ResultTuple(result_x_diff, result_y_diff)
resultTuple_amount_avg = ResultTuple(result_x_amount_avg, result_y_amount_avg)
resultTuple_amount_std = ResultTuple(result_x_amount_std, result_y_amount_std)
resultTuple_avg_rescuetime_amount = ResultTuple(result_x_avg_rescuetime_amount, result_y_avg_rescuetime_amount)
resultTuple_std_rescuetime_amount = ResultTuple(result_x_std_rescuetime_amount, result_y_std_rescuetime_amount)
resultTuple_avg_userstate = ResultTuple(result_x_avg_userstate,result_y_avg_userstate)
resultTuple_std_userstate = ResultTuple(result_x_std_userstate,result_y_std_userstate)
filename = self.folder + "data_analysis_results/testpersoon_D/"
self.generate_csv("Time_spent_seconds","Concentration avg",resultTuple_avg,filename + "comparison time_spent_sec against average concentration")
self.generate_csv("Time_spent_seconds","Concentration std",resultTuple_std,filename + "comparison time_spent_sec against std concentration")
# //////////////////////
# /// all activities ///
# //////////////////////
self.generate_csv("Time_spent_seconds","Concentration avg",resultTuple_avg_all_act,filename + "comparison time_spent_sec against average concentration all activities")
self.generate_csv("Time_spent_seconds","Concentration std",resultTuple_std_all_act,filename + "comparison time_spent_sec against std concentration all activities")
# //////////////////////
self.generate_csv("Unknown","Concentration std",resultTuple_diff,filename + "comparison concentration difference when switch between activities")
self.generate_csv("Amount","Concentration avg",resultTuple_amount_avg,filename + "comparison amount used programs with avg concentration")
self.generate_csv("Amount","Concentration std",resultTuple_amount_std,filename + "comparison amount used programs with std concentration")
self.generate_csv("Amount","Concentration avg",resultTuple_avg_rescuetime_amount,filename + "comparision RescueTime amount concentration avg")
self.generate_csv("Amount","Concentration std",resultTuple_std_rescuetime_amount,filename + "comparision RescueTime amount concentration std")
self.generate_csv("Userstate","Concentration avg",resultTuple_avg_userstate,filename + "comparision userstates concentration avg")
self.generate_csv("Amount","Concentration std",resultTuple_std_userstate,filename + "comparision userstates concentration std")
resultObject = ResultObject()
resultObject.set_result_timeSpent_activity_avg(resultTuple_avg)
resultObject.set_result_timeSpent_activity_std(resultTuple_std)
resultObject.set_concentration_diff_activity_switch_avg(resultTuple_diff)
resultObject.set_result_amount_used_programs_avg(resultTuple_amount_avg)
resultObject.set_result_amount_used_programs_std(resultTuple_amount_std)
resultObject.set_amount_activities_RescueTime_interval_with_mindwave_avg(resultTuple_avg_rescuetime_amount)
resultObject.set_amount_activities_RescueTime_interval_with_mindwave_std(resultTuple_std_rescuetime_amount)
return resultObject
def get_statistics_session_testpersoon_B(self):
session_id = 41
datetime_from_session, datetime_to_session = self.dasession.get_dates_session(session_id)
activities,manual_log_testpersoon_B = Manual_log.get_manual_logfile_Testpersoon_B_enkel_programmas_websites()
datetime_from = manual_log_testpersoon_B[0][0]
datetime_to = manual_log_testpersoon_B[len(manual_log_testpersoon_B) - 1][1]
mindwave_data_list = Mindwave_data_processing.get_mindwave_data_filtered_smoothed_middle_moving_median(datetime_from,datetime_to,self.window_mindwave)
list_dates = self.rescuetimeDataProcessing.get_dates_list(datetime_from_session, datetime_to_session)
result_x_diff, result_y_diff = self.manualLogDataProcessing.get_list_concentration_differences_manual_log(manual_log_testpersoon_B,mindwave_data_list)
result_x_amount_avg, result_y_amount_avg = self.manualLogDataProcessing.get_list_amount_used_programs_concentration_per_interval(mindwave_data_list,manual_log_testpersoon_B,list_dates,Calculate_statistics_enumeration.AVG)
result_x_amount_std, result_y_amount_std = self.manualLogDataProcessing.get_list_amount_used_programs_concentration_per_interval(mindwave_data_list,manual_log_testpersoon_B,list_dates,Calculate_statistics_enumeration.STD)
result_x_avg_rescuetime_amount, result_y_avg_rescuetime_amount = self.get_list_amount_activities_RescueTime_interval_with_mindwave(session_id,Calculate_statistics_enumeration.AVG)
result_x_std_rescuetime_amount, result_y_std_rescuetime_amount = self.get_list_amount_activities_RescueTime_interval_with_mindwave(session_id,Calculate_statistics_enumeration.STD)
activities_important = ["Wikipedia","Latex"]
result_x_avg, result_y_avg = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(manual_log_testpersoon_B,mindwave_data_list,activities_important[0],Calculate_statistics_enumeration.AVG)
result_x_std, result_y_std = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(manual_log_testpersoon_B,mindwave_data_list,activities_important[0],Calculate_statistics_enumeration.STD)
resultTuple_avg = ResultTuple(result_x_avg, result_y_avg)
resultTuple_std = ResultTuple(result_x_std, result_y_std)
for i in range(1,len(activities_important)):
result_x_avg_temp, result_y_avg_temp = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(manual_log_testpersoon_B,mindwave_data_list,activities_important[i],Calculate_statistics_enumeration.AVG)
result_x_std_temp, result_y_std_temp = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(manual_log_testpersoon_B,mindwave_data_list,activities_important[i],Calculate_statistics_enumeration.STD)
resultTuple_avg.merge(ResultTuple(result_x_avg_temp,result_y_avg_temp))
resultTuple_std.merge(ResultTuple(result_x_std_temp,result_y_std_temp))
activity_from = "Latex"
activity_to = "Wikipedia"
result_x_diff_specific_switch, result_y_diff_specific_switch = self.manualLogDataProcessing.get_list_concentration_differences_manual_log_specific_switch(manual_log_testpersoon_B,mindwave_data_list,activity_from,activity_to)
resultTuple_diff_specific_switch = ResultTuple(result_x_diff_specific_switch,result_y_diff_specific_switch)
# ////////////////////////////
# /// with all activities ////
# ////////////////////////////
result_x_avg_all_act, result_y_avg_all_act = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(manual_log_testpersoon_B,mindwave_data_list,activities[0],Calculate_statistics_enumeration.AVG)
result_x_std_all_act, result_y_std_all_act = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(manual_log_testpersoon_B,mindwave_data_list,activities[0],Calculate_statistics_enumeration.STD)
resultTuple_avg_all_act = ResultTuple(result_x_avg_all_act, result_y_avg_all_act)
resultTuple_std_all_act = ResultTuple(result_x_std_all_act, result_y_std_all_act)
for i in range(1,len(activities)):
try:
result_x_avg_temp, result_y_avg_temp = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(manual_log_testpersoon_B,mindwave_data_list,activities[i],Calculate_statistics_enumeration.AVG)
result_x_std_temp, result_y_std_temp = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(manual_log_testpersoon_B,mindwave_data_list,activities[i],Calculate_statistics_enumeration.STD)
resultTuple_avg_all_act.merge(ResultTuple(result_x_avg_temp,result_y_avg_temp))
resultTuple_std_all_act.merge(ResultTuple(result_x_std_temp,result_y_std_temp))
except:
pass
# ////////////////////////////
resultTuple_diff = ResultTuple(result_x_diff, result_y_diff)
resultTuple_amount_avg = ResultTuple(result_x_amount_avg, result_y_amount_avg)
resultTuple_amount_std = ResultTuple(result_x_amount_std, result_y_amount_std)
resultTuple_avg_rescuetime_amount = ResultTuple(result_x_avg_rescuetime_amount, result_y_avg_rescuetime_amount)
resultTuple_std_rescuetime_amount = ResultTuple(result_x_std_rescuetime_amount, result_y_std_rescuetime_amount)
filename = self.folder + "data_analysis_results/testpersoon_B/"
# //////////////////////
# /// all activities ///
# //////////////////////
self.generate_csv("Time_spent_seconds","Concentration avg",resultTuple_avg_all_act,filename + "comparison time_spent_sec against average concentration all activities")
self.generate_csv("Time_spent_seconds","Concentration std",resultTuple_std_all_act,filename + "comparison time_spent_sec against std concentration all activities")
# //////////////////////
self.generate_csv("Time_spent_seconds","Concentration avg",resultTuple_avg,filename + "comparison time_spent_sec against average concentration")
self.generate_csv("Time_spent_seconds","Concentration std",resultTuple_std,filename + "comparison time_spent_sec against std concentration")
self.generate_csv("Switch ID","Concentration avg",resultTuple_diff,filename + "comparison concentration difference when switch between activities")
self.generate_csv("Switch ID","Concentration avg",resultTuple_diff_specific_switch,filename + "comparison concentration difference specific switch between activities")
self.generate_csv("Amount","Concentration avg",resultTuple_amount_avg,filename + "comparison amount used programs with avg concentration")
self.generate_csv("Amount","Concentration std",resultTuple_amount_std,filename + "comparison amount used programs with std concentration")
self.generate_csv("Amount","Concentration avg",resultTuple_avg_rescuetime_amount,filename + "comparision RescueTime amount concentration avg")
self.generate_csv("Amount","Concentration std",resultTuple_std_rescuetime_amount,filename + "comparision RescueTime amount concentration std")
resultObject = ResultObject()
resultObject.set_result_timeSpent_activity_avg(resultTuple_avg)
resultObject.set_result_timeSpent_activity_std(resultTuple_std)
resultObject.set_concentration_diff_activity_switch_avg(resultTuple_diff)
resultObject.set_concentration_diff_specific_activity_switch_avg(resultTuple_diff_specific_switch)
resultObject.set_result_amount_used_programs_avg(resultTuple_amount_avg)
resultObject.set_result_amount_used_programs_std(resultTuple_amount_std)
resultObject.set_amount_activities_RescueTime_interval_with_mindwave_avg(resultTuple_avg_rescuetime_amount)
resultObject.set_amount_activities_RescueTime_interval_with_mindwave_std(resultTuple_std_rescuetime_amount)
return resultObject
def test_convert_mindwave_data_to_RescueTime_intervals(self):
list_dates_Rescuetime = [["2014-04-24 14:00:00"],
["2014-04-24 14:05:00"],
["2014-04-24 14:10:00"]]
list_mindwave_data = []
list_mindwave_data.append(
[0, "2014-04-24 14:00:00", None, 0.50, 0.40, None, None])
list_mindwave_data.append(
[0, "2014-04-24 14:01:00", None, 0.10, 0.20, None, None])
list_mindwave_data.append(
[0, "2014-04-24 14:02:00", None, 0.60, 0.30, None, None])
list_mindwave_data.append(
[0, "2014-04-24 14:03:00", None, 0.80, 0.50, None, None])
list_mindwave_data.append(
[0, "2014-04-24 14:04:00", None, 0.10, 0.50, None, None])
list_mindwave_data.append(
[0, "2014-04-24 14:05:00", None, 0.10, 0.10, None, None])
list_mindwave_data.append(
[0, "2014-04-24 14:06:00", None, 0.50, 0.90, None, None])
list_mindwave_data.append(
[0, "2014-04-24 14:07:00", None, 0.60, 0.40, None, None])
list_mindwave_data.append(
[0, "2014-04-24 14:08:00", None, 0.80, 0.60, None, None])
list_mindwave_data.append(
[0, "2014-04-24 14:09:00", None, 0.40, 0.20, None, None])
list_mindwave_data.append(
[0, "2014-04-24 14:10:00", None, 0.60, 0.30, None, None])
list_mindwave_data.append(
[0, "2014-04-24 14:11:00", None, 0.20, 0.60, None, None])
list_mindwave_data.append(
[0, "2014-04-24 14:12:00", None, 0.80, 0.80, None, None])
list_mindwave_data.append(
[0, "2014-04-24 14:13:00", None, 0.10, 0.60, None, None])
list_mindwave_data.append(
[0, "2014-04-24 14:14:00", None, 0.30, 0.10, None, None])
list_mindwave_data.append(
[0, "2014-04-24 14:15:00", None, 0.50, 0.20, None, None])
attention_data_original = []
meditation_data_original = []
for item in list_mindwave_data:
attention_data_original.append(item[3])
meditation_data_original.append(item[4])
x_axix, attention_data, meditation_data = Mindwave_data_processing.convert_mindwave_data_to_RescueTime_intervals(
list_mindwave_data, list_dates_Rescuetime)
self.assertEqual(round(attention_data[0], 2),
round(np.mean(attention_data_original[0:6]), 2))
self.assertEqual(round(attention_data[1], 2),
round(np.mean(attention_data_original[6:11]), 2))
self.assertEqual(round(attention_data[2], 2),
round(np.mean(attention_data_original[11:16]), 2))
self.assertEqual(round(meditation_data[0], 2),
round(np.mean(meditation_data_original[0:6]), 2))
self.assertEqual(round(meditation_data[1], 2),
round(np.mean(meditation_data_original[6:11]), 2))
self.assertEqual(round(meditation_data[2], 2),
round(np.mean(meditation_data_original[11:16]), 2))
def test_get_attention_meditation_buckets(self):
dates = []
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:00",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:01",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:02",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:03",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:04",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:05",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:06",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:07",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:08",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:09",
"%Y-%m-%d %H:%M:%S"))
dates.append(
datetime.datetime.strptime("2013-12-28 08:00:10",
"%Y-%m-%d %H:%M:%S"))
mindwave_data = []
mindwave_data.append([dates[0], dates[1], 0.2, 0.2, 0, 0])
mindwave_data.append([dates[1], dates[2], 0.4, 0.5, 0, 0])
mindwave_data.append([dates[2], dates[3], 0.8, 0.2, 0, 0])
mindwave_data.append([dates[3], dates[4], 0.1, 0.5, 0, 0])
mindwave_data.append([dates[4], dates[5], 0.9, 0.1, 0, 0])
mindwave_data.append([dates[5], dates[6], 0.4, 0.8, 0, 0])
mindwave_data.append([dates[6], dates[7], 0.8, 0.3, 0, 0])
mindwave_data.append([dates[7], dates[8], 0.2, 0.6, 0, 0])
mindwave_data.append([dates[8], dates[9], 0.0, 1.0, 0, 0])
mindwave_data.append([dates[9], dates[10], 0.4, 0.5, 0, 0])
datetime_from = datetime.datetime.strptime("2013-12-28 08:00:00",
"%Y-%m-%d %H:%M:%S")
datetime_to = datetime.datetime.strptime("2013-12-28 08:30:00",
"%Y-%m-%d %H:%M:%S")
attention_bucket, meditation_bucket = Mindwave_data_processing.get_attention_meditation_buckets(
datetime_from, datetime_to, mindwave_data)
self.assertEqual(attention_bucket[0], 0.20)
self.assertEqual(attention_bucket[1], 0.20)
self.assertEqual(attention_bucket[2], 0.30)
self.assertEqual(attention_bucket[3], 0.0)
self.assertEqual(attention_bucket[4], 0.3)
self.assertEqual(meditation_bucket[0], 0.1)
self.assertEqual(meditation_bucket[1], 0.3)
self.assertEqual(meditation_bucket[2], 0.3)
self.assertEqual(meditation_bucket[3], 0.1)
self.assertEqual(meditation_bucket[4], 0.2)
print str("attention_bucket")
print attention_bucket
print str("meditation_bucket")
print meditation_bucket
def mindwave_data_important_unimportant_activity(self, session_id):
datetime_from, datetime_to = self.dasession.get_dates_session(
session_id)
attention_data, x, y_attention, y_meditation, y_userGoneNotStudying, y_userGoneStudying = Mindwave_data_processing.get_mindwave_dataa_important_unimportant_activity(
datetime_from, datetime_to, self.window_RescueTime)
title = "mindwave data important / unimportant activities"
self.plot_data(attention_data, x, y_attention, y_meditation, None,
y_userGoneNotStudying, y_userGoneStudying, title,
self.x_label, self.y_label)
def mindwave_data_per_worksession(self, session_id):
datetime_from, datetime_to = self.dasession.get_dates_session(
session_id)
attention_data, x, y_attention, y_meditation, y_userGoneNotStudying, y_userGoneStudying = Mindwave_data_processing.get_mindwave_worksession_data(
datetime_from, datetime_to, self.window_other)
title = "session_ID: " + str(
session_id) + "mindwave data for worksession"
self.plot_data(attention_data, x, y_attention, y_meditation, None,
y_userGoneNotStudying, y_userGoneStudying, title,
self.x_label, self.y_label)
result_html = add_table_workSession_gem_min_max(datetime_from,datetime_to,options_reason,treshold_important_unimportant,result_html)
# tabel worksessies
result_html = add_table_workSession(datetime_from,datetime_to,options_reason,treshold_important_unimportant,result_html)
result_html += "<h2>Some additional information:</h2>"
result_html += '<p>' + 'average eyes detected = ' + percentage_layout(User_gone_processing.get_eyes_detected_specific_period(datetime_from,datetime_to)) + '</p>' + '\n'
try:
avg_concentration_userfeedback = Userfeedback_processing.get_average_userfeedback_specific_period(datetime_from, datetime_to)
except Exception.ListEmpty, e:
avg_concentration_userfeedback = -1
avg_reading = Read_detection_processing.get_average_reading_specific_period(datetime_from, datetime_to)
result_html += '<p>' + 'average concentration userfeedback = ' + percentage_layout(avg_concentration_userfeedback) + '</p>' + '\n'
attention_mindwave, meditation_mindwave = Mindwave_data_processing.get_average_attention_meditation_specific_period(datetime_from,datetime_to)
result_html += '<p>' + 'average concentration mindwave = ' + percentage_layout(attention_mindwave) + '\n'
result_html += '<p>' + 'average meditation mindwave = ' + percentage_layout(meditation_mindwave) + '</p>' + '\n'
result_html += '<p>' + 'average read = ' + percentage_layout(avg_reading) + '</p>' + '\n'
#print df['Date'].unique()
#df.to_csv('rt_data_interval_activity_20120901.csv', index=False)
result_html += "</body>" + "\n"
result_html += "</html>" + "\n"
result_page = open("result_page.htm","wb")
result_page.write(result_html)
result_page.close()
def getListImportantActivities_V2_buckets(datetime_from, datetime_to,options_reason,link_to_main):
daRescueTime = DARescueTime_SQLite.RescueTime(link_to_main)
#result_rescueTime = DARescueTime_SQLite.get_data_important_activities_specific_period(datetime_from,datetime_to)
important_activities_list = daRescueTime.get_data_important_activities_specific_period_group_by_activity(datetime_from,datetime_to)
# hier komt het resultaat in per activity. Dus gemiddelde concentratie met tijd activiteit geopend
result = []
# Itereren over elke belangrijke activitieit
for activity in important_activities_list :
#[DateTime, Time_sec,ActivityDetail, Category, isImportant, ActivityGeneral, Subject_ID]
activity_details = daRescueTime.get_data_important_activities_specific_period_activity(datetime_from,datetime_to,activity[1])
# Dan per belangrijke activitieit, in die 5 minuten tijdspanne gaan kijken hoeveel de gebruiker naar het scherm keek
mindwave_data_list = Mindwave_data_processing.get_mindwave_data_filtered_smoothed(datetime_from,datetime_to,10)
attention_bucket_total = []
meditation_bucket_total = []
gemiddelde_concentratie_userfeedback = 0.0
totaal_userfeedback = 0
gemiddelde_eyes_detected = 0.0
totaal_eyes_detected = 0
gemiddelde_attention_mindwave = 0.0
totaal_attention_mindwave = 0
gemiddelde_meditation_mindwave = 0.0
totaal_meditation_mindwave = 0
gemiddelde_reading = 0.0
totaal_reading = 0.0
# Bijhouden dat, per keer de gebruiker niet naar het scherm keek, wat was die dan wel aan het doen?
reason_array = []
for reason in options_reason:
reason_array.append([reason[0],0.0])
for activity_detail in activity_details:
start_datetime = datetime.datetime.strptime(activity_detail[1],"%Y-%m-%d %H:%M:%S")
end_datetime = start_datetime + datetime.timedelta(minutes=5)
# gemiddelde berekenen van de userfeedback gegevens voor de periodes van activity_detail
try:
concentratie = Userfeedback_processing.get_average_userfeedback_specific_period(start_datetime,end_datetime)
gemiddelde_concentratie_userfeedback += concentratie
totaal_userfeedback += 1
except Exception.ListEmpty, e:
source = "data_processing, function: get_average_userfeedback_specific_period(" + str(start_datetime) + "," + str(end_datetime) + ")"
DAErrorReport_SQLite.insert_row_action(datetime.datetime.today(),source,e.msg)
gemiddelde_eyes_detected += float(User_gone_processing.get_eyes_detected_specific_period(start_datetime,end_datetime))
totaal_eyes_detected += 1
# Mindwave, gemiddelde berekenen
attention_bucket, meditation_bucket = Mindwave_data_processing.get_attention_meditation_buckets(start_datetime,end_datetime,mindwave_data_list)
attention_bucket_total.append(attention_bucket)
meditation_bucket_total.append(meditation_bucket)
# reason_array opvullen:
teller_reason = 0
while(teller_reason < len(options_reason)):
reason_array[teller_reason][1] += User_gone_processing.get_average_reason(start_datetime,end_datetime,options_reason[teller_reason][0])
teller_reason += 1
# reading
reading_temp = Read_detection_processing.get_average_reading_specific_period(start_datetime,end_datetime)
if reading_temp > 0:
gemiddelde_reading += reading_temp
totaal_reading += 1
teller_reason = 0
while (teller_reason < len(reason_array)):
reason_array[teller_reason][1] = reason_array[teller_reason][1] / float(len(activity_details))
teller_reason += 1
if totaal_userfeedback > 0 :
gemiddelde_concentratie_userfeedback = float((gemiddelde_concentratie_userfeedback / totaal_userfeedback))
else:
gemiddelde_concentratie_userfeedback = -1
if totaal_eyes_detected > 0:
gemiddelde_eyes_detected = float((gemiddelde_eyes_detected / totaal_eyes_detected))
else:
gemiddelde_eyes_detected = 0
if len(attention_bucket_total) > 0:
attention_bucket_avg, meditation_bucket_avg = Mindwave_data_processing.merge_buckets(attention_bucket_total, meditation_bucket_total)
if totaal_reading > 0:
gemiddelde_reading = float(gemiddelde_reading / totaal_reading)
else:
gemiddelde_reading = 0
result.append([activity[1],activity[0],gemiddelde_concentratie_userfeedback,gemiddelde_eyes_detected,reason_array,attention_bucket_avg, meditation_bucket_avg,gemiddelde_reading,activity[2]])
def get_statistics_session_testpersoon_D(self):
session_id = 11
datetime_from_session, datetime_to_session = self.dasession.get_dates_session(
session_id)
activities, manual_log_testpersoon_D = Manual_log.get_manual_log_testpersoon_D_programms_and_extra_info(
)
activities_userstate, manual_log_testpersoon_D_userstate = Manual_log.get_manual_log_testpersoon_D_userstates(
)
datetime_from = manual_log_testpersoon_D[0][0]
datetime_to = manual_log_testpersoon_D[len(manual_log_testpersoon_D) -
1][1]
mindwave_data_list = Mindwave_data_processing.get_mindwave_data_filtered_smoothed_middle_moving_median(
datetime_from, datetime_to, self.window_mindwave)
list_dates = self.rescuetimeDataProcessing.get_dates_list(
datetime_from_session, datetime_to_session)
activities_important = [
"pdf + toledovragen", "powerpoint", "wikipedia", "toledovragen",
"pdf"
]
# With important activities
result_x_avg, result_y_avg = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(
manual_log_testpersoon_D, mindwave_data_list,
activities_important[0], Calculate_statistics_enumeration.AVG)
result_x_std, result_y_std = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(
manual_log_testpersoon_D, mindwave_data_list,
activities_important[0], Calculate_statistics_enumeration.STD)
resultTuple_avg = ResultTuple(result_x_avg, result_y_avg)
resultTuple_std = ResultTuple(result_x_std, result_y_std)
for i in range(1, len(activities_important)):
result_x_avg_temp, result_y_avg_temp = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(
manual_log_testpersoon_D, mindwave_data_list,
activities_important[i], Calculate_statistics_enumeration.AVG)
result_x_std_temp, result_y_std_temp = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(
manual_log_testpersoon_D, mindwave_data_list,
activities_important[i], Calculate_statistics_enumeration.STD)
resultTuple_avg.merge(
ResultTuple(result_x_avg_temp, result_y_avg_temp))
resultTuple_std.merge(
ResultTuple(result_x_std_temp, result_y_std_temp))
result_x_diff, result_y_diff = self.manualLogDataProcessing.get_list_concentration_differences_manual_log(
manual_log_testpersoon_D, mindwave_data_list)
# ////////////////////////////
# /// with all activities ////
# ////////////////////////////
result_x_avg_all_act, result_y_avg_all_act = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(
manual_log_testpersoon_D, mindwave_data_list, activities[0],
Calculate_statistics_enumeration.AVG)
result_x_std_all_act, result_y_std_all_act = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(
manual_log_testpersoon_D, mindwave_data_list, activities[0],
Calculate_statistics_enumeration.STD)
resultTuple_avg_all_act = ResultTuple(result_x_avg_all_act,
result_y_avg_all_act)
resultTuple_std_all_act = ResultTuple(result_x_std_all_act,
result_y_std_all_act)
for i in range(1, len(activities)):
try:
result_x_avg_temp, result_y_avg_temp = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(
manual_log_testpersoon_D, mindwave_data_list,
activities[i], Calculate_statistics_enumeration.AVG)
result_x_std_temp, result_y_std_temp = self.manualLogDataProcessing.get_list_concentration_time_spent_activity(
manual_log_testpersoon_D, mindwave_data_list,
activities[i], Calculate_statistics_enumeration.STD)
resultTuple_avg_all_act.merge(
ResultTuple(result_x_avg_temp, result_y_avg_temp))
resultTuple_std_all_act.merge(
ResultTuple(result_x_std_temp, result_y_std_temp))
except:
pass
# ////////////////////////////
result_x_amount_avg, result_y_amount_avg = self.manualLogDataProcessing.get_list_amount_used_programs_concentration_per_interval(
mindwave_data_list, manual_log_testpersoon_D, list_dates,
Calculate_statistics_enumeration.AVG)
result_x_amount_std, result_y_amount_std = self.manualLogDataProcessing.get_list_amount_used_programs_concentration_per_interval(
mindwave_data_list, manual_log_testpersoon_D, list_dates,
Calculate_statistics_enumeration.STD)
result_x_avg_rescuetime_amount, result_y_avg_rescuetime_amount = self.get_list_amount_activities_RescueTime_interval_with_mindwave(
session_id, Calculate_statistics_enumeration.AVG)
result_x_std_rescuetime_amount, result_y_std_rescuetime_amount = self.get_list_amount_activities_RescueTime_interval_with_mindwave(
session_id, Calculate_statistics_enumeration.STD)
result_x_avg_userstate, result_y_avg_userstate = self.manualLogDataProcessing.get_statistics_attention_userstates(
activities_userstate, manual_log_testpersoon_D_userstate,
mindwave_data_list, Calculate_statistics_enumeration.AVG)
result_x_std_userstate, result_y_std_userstate = self.manualLogDataProcessing.get_statistics_attention_userstates(
activities_userstate, manual_log_testpersoon_D_userstate,
mindwave_data_list, Calculate_statistics_enumeration.STD)
resultTuple_diff = ResultTuple(result_x_diff, result_y_diff)
resultTuple_amount_avg = ResultTuple(result_x_amount_avg,
result_y_amount_avg)
resultTuple_amount_std = ResultTuple(result_x_amount_std,
result_y_amount_std)
resultTuple_avg_rescuetime_amount = ResultTuple(
result_x_avg_rescuetime_amount, result_y_avg_rescuetime_amount)
resultTuple_std_rescuetime_amount = ResultTuple(
result_x_std_rescuetime_amount, result_y_std_rescuetime_amount)
resultTuple_avg_userstate = ResultTuple(result_x_avg_userstate,
result_y_avg_userstate)
resultTuple_std_userstate = ResultTuple(result_x_std_userstate,
result_y_std_userstate)
filename = self.folder + "data_analysis_results/testpersoon_D/"
self.generate_csv(
"Time_spent_seconds", "Concentration avg", resultTuple_avg,
filename +
"comparison time_spent_sec against average concentration")
self.generate_csv(
"Time_spent_seconds", "Concentration std", resultTuple_std,
filename + "comparison time_spent_sec against std concentration")
# //////////////////////
# /// all activities ///
# //////////////////////
self.generate_csv(
"Time_spent_seconds", "Concentration avg", resultTuple_avg_all_act,
filename +
"comparison time_spent_sec against average concentration all activities"
)
self.generate_csv(
"Time_spent_seconds", "Concentration std", resultTuple_std_all_act,
filename +
"comparison time_spent_sec against std concentration all activities"
)
# //////////////////////
self.generate_csv(
"Unknown", "Concentration std", resultTuple_diff, filename +
"comparison concentration difference when switch between activities"
)
self.generate_csv(
"Amount", "Concentration avg", resultTuple_amount_avg, filename +
"comparison amount used programs with avg concentration")
self.generate_csv(
"Amount", "Concentration std", resultTuple_amount_std, filename +
"comparison amount used programs with std concentration")
self.generate_csv(
"Amount", "Concentration avg", resultTuple_avg_rescuetime_amount,
filename + "comparision RescueTime amount concentration avg")
self.generate_csv(
"Amount", "Concentration std", resultTuple_std_rescuetime_amount,
filename + "comparision RescueTime amount concentration std")
self.generate_csv(
"Userstate", "Concentration avg", resultTuple_avg_userstate,
filename + "comparision userstates concentration avg")
self.generate_csv(
"Amount", "Concentration std", resultTuple_std_userstate,
filename + "comparision userstates concentration std")
resultObject = ResultObject()
resultObject.set_result_timeSpent_activity_avg(resultTuple_avg)
resultObject.set_result_timeSpent_activity_std(resultTuple_std)
resultObject.set_concentration_diff_activity_switch_avg(
resultTuple_diff)
resultObject.set_result_amount_used_programs_avg(
resultTuple_amount_avg)
resultObject.set_result_amount_used_programs_std(
resultTuple_amount_std)
resultObject.set_amount_activities_RescueTime_interval_with_mindwave_avg(
resultTuple_avg_rescuetime_amount)
resultObject.set_amount_activities_RescueTime_interval_with_mindwave_std(
resultTuple_std_rescuetime_amount)
return resultObject
