diff --git a/2021_01_31_avg b/2021_01_31_avg new file mode 100644 index 0000000..4c8721e --- /dev/null +++ b/2021_01_31_avg @@ -0,0 +1,21 @@ +time,heartrate_2,heartrate_5,heartrate_10,heartrate_15,movement_10,movement_30,movement_60 +2021-01-31 16:04:05.010676,nan,nan,nan,nan,48,48,48 +2021-01-31 16:04:35.476006,79,79,79,79,16,16,17 +2021-01-31 16:04:36.241533,79,79,79,79,16,16,17 +2021-01-31 16:04:37.005988,79,79,79,79,16,16,17 +2021-01-31 16:04:37.816041,nan,79,79,79,16,16,17 +2021-01-31 16:04:38.625689,nan,79,79,79,16,16,18 +2021-01-31 16:04:39.436024,nan,79,79,79,16,16,17 +2021-01-31 16:04:40.246131,nan,nan,79,79,16,16,17 +2021-01-31 16:04:41.011184,nan,nan,79,79,16,16,17 +2021-01-31 16:04:41.821067,nan,nan,79,79,16,16,17 +2021-01-31 16:04:42.631347,nan,nan,79,79,16,16,17 +2021-01-31 16:04:43.441469,nan,nan,79,79,16,16,17 +2021-01-31 16:04:44.251060,nan,nan,79,79,16,16,17 +2021-01-31 16:04:45.016751,nan,nan,79,79,16,16,17 +2021-01-31 16:04:45.825831,nan,nan,nan,79,16,16,17 +2021-01-31 16:04:46.680977,nan,nan,nan,79,16,16,17 +2021-01-31 16:04:47.446140,nan,nan,nan,79,15,16,17 +2021-01-31 16:04:48.210846,nan,nan,nan,79,15,16,17 +2021-01-31 16:04:49.021353,nan,nan,nan,79,15,16,17 +2021-01-31 16:04:49.831218,nan,nan,nan,79,15,16,17 diff --git a/2021_01_31_raw b/2021_01_31_raw new file mode 100644 index 0000000..e2eea27 --- /dev/null +++ b/2021_01_31_raw @@ -0,0 +1 @@ +time,heartrate_2,heartrate_5,heartrate_10,heartrate_15,movement_10,movement_30,movement_60 diff --git a/bluesleep.py b/bluesleep.py index ba4daaa..b75143e 100755 --- a/bluesleep.py +++ b/bluesleep.py @@ -114,8 +114,6 @@ def vibrate_random(duration): band.vibrate(vibrate_ms) time.sleep(vibro_delay) - - def sleep_monitor_callback(data): tick_time = time.time() if not sleepdata.last_tick_time: @@ -123,7 +121,7 @@ def sleep_monitor_callback(data): process_data(data, tick_time) average_data(tick_time) -def connect(mac_filename, auth_key_filename): +def connect(): global band success = False timeout = 3 @@ -179,7 +177,7 @@ def vibrate_rolling(): band.vibrate(x) if __name__ == "__main__": - connect(mac_filename, auth_key_filename) + connect() threading.Thread(target=start_data_pull).start() threading.Thread(target=timed_buzzing, args=([buzz_delay, 15])).start() #sleepdata.init_graph() diff --git a/sleepdata.py b/sleepdata.py index a01f51a..4ef2816 100644 --- a/sleepdata.py +++ b/sleepdata.py @@ -1,14 +1,10 @@ from datetime import datetime from os import path - import csv import matplotlib.pyplot as plt import matplotlib.animation as animation -#Todo: separate graph animation from data averaging -#Todo: log raw data separately from average data - sleep_data = { 'heartrate': { @@ -34,14 +30,9 @@ last_heartrate = 0 last_tick_time = None tick_seconds = 0.5 -csv_filename = "sleep_data.csv" - -fieldnames = ['time'] -for data_type in sleep_data: - periods = sleep_data[data_type]['periods'] - for period in periods: - fieldnames.append(data_type + str(period)) - +datestamp = datetime.now().strftime("%Y_%m_%d") +csv_header_name_format = '{}_{}' +csv_filename_format = '{}_{}.csv' plt.style.use('dark_background') graph_figure = plt.figure() @@ -49,17 +40,52 @@ graph_axes = graph_figure.add_subplot(1, 1, 1) graph_data = {} -def write_csv(data): - global fieldnames - global csv_filename + +class Average_Gyro_Data(): + gyro_last_x = 0 + gyro_last_y = 0 + gyro_last_z = 0 + # Each gyro reading from miband4 comes over as a group of three, + # each containing x,y,z values. This function summarizes the + # values into a single consolidated movement value. + def process(self, gyro_data): + gyro_movement = 0 + for gyro_datum in gyro_data: + gyro_delta_x = abs(gyro_datum['x'] - self.gyro_last_x) + self.gyro_last_x = gyro_datum['x'] + gyro_delta_y = abs(gyro_datum['y'] - self.gyro_last_y) + self.gyro_last_y = gyro_datum['y'] + gyro_delta_z = abs(gyro_datum['z'] - self.gyro_last_z) + self.gyro_last_z = gyro_datum['z'] + gyro_delta_sum = gyro_delta_x + gyro_delta_y + gyro_delta_z + gyro_movement += gyro_delta_sum + return gyro_movement + + + +def write_csv(data, name): + fieldnames = ['time'] + for fieldname in data[0]: + if fieldname != 'time': + fieldnames.append(fieldname) + if name == 'raw': + name = '{}_{}'.format(name, fieldname) + + csv_filename = csv_filename_format.format(datestamp, name) + if not path.exists(csv_filename): - with open(csv_filename, 'w', newline='') as csvfile: - csv_writer = csv.DictWriter(csvfile, fieldnames=fieldnames) - csv_writer.writeheader() - csv_writer.writerow(data) + open_handle = 'w' else: - with open(csv_filename, 'a', newline='') as csvfile: - csv_writer = csv.DictWriter(csvfile, fieldnames=fieldnames) + open_handle = 'a' + + with open(csv_filename, open_handle, newline='') as csvfile: + csv_writer = csv.DictWriter(csvfile, fieldnames=fieldnames) + if open_handle == 'w': + csv_writer.writeheader() + if type(data) is list: + for row in data: + csv_writer.writerow(row) + else: csv_writer.writerow(data) @@ -69,13 +95,18 @@ def flush_old_raw_data(tick_time): periods = s_data['periods'] cleaned_raw_data = [] + old_raw_data = [] for raw_datum in s_data['raw_data']: datum_age = tick_time - raw_datum['time'] if datum_age < max(periods): cleaned_raw_data.append(raw_datum) + else: + old_raw_data.append(raw_datum) s_data['raw_data'] = cleaned_raw_data + if old_raw_data: + write_csv(old_raw_data, 'raw') def average_raw_data(tick_time): global last_heartrate @@ -101,8 +132,6 @@ def average_raw_data(tick_time): if len(period_data) > 0: period_data_average = sum(period_data) / len(period_data) else: - print("({}) Period data empty: {}".format(data_type, - period_seconds)) if data_type == "heartrate" and period_seconds == min(periods): period_data_average = last_heartrate else: @@ -110,38 +139,19 @@ def average_raw_data(tick_time): period_averages_dict[period_seconds] = zero_to_nan(period_data_average) - csv_out[data_type + str(period_seconds)] = zero_to_nan(period_data_average) + csv_header_field_name = csv_header_name_format.format(data_type, period_seconds) + csv_out[csv_header_field_name] = zero_to_nan(period_data_average) s_data['averaged_data'].append(period_averages_dict) - write_csv(csv_out) + + write_csv([csv_out], 'avg') + def process_gyro_data(gyro_data, tick_time): - # Each gyro reading from miband4 comes over as a group of three, - # each containing x,y,z values. This function summarizes the - # values into a single consolidated movement value. - sleep_move = sleep_data['movement'] - sleep_workspace = sleep_move['workspace'] - - gyro_last_x = sleep_workspace['gyro_last_x'] - gyro_last_y = sleep_workspace['gyro_last_y'] - gyro_last_z = sleep_workspace['gyro_last_z'] value_name = sleep_move['value_name'] - gyro_movement = 0 - for gyro_datum in gyro_data: - gyro_delta_x = abs(gyro_datum['x'] - gyro_last_x) - gyro_last_x = gyro_datum['x'] - gyro_delta_y = abs(gyro_datum['y'] - gyro_last_y) - gyro_last_y = gyro_datum['y'] - gyro_delta_z = abs(gyro_datum['z'] - gyro_last_z) - gyro_last_z = gyro_datum['z'] - gyro_delta_sum = gyro_delta_x + gyro_delta_y + gyro_delta_z - gyro_movement += gyro_delta_sum - - sleep_workspace['gyro_last_x'] = gyro_last_x - sleep_workspace['gyro_last_y'] = gyro_last_y - sleep_workspace['gyro_last_z'] = gyro_last_z - + gyro_movement = average_gyro_data.process(gyro_data) + print("Gyro: {}".format(gyro_movement)) sleep_move['raw_data'].append({ 'time': tick_time, value_name: gyro_movement @@ -157,11 +167,13 @@ def process_heartrate_data(heartrate_data, tick_time): value_name: heartrate_data } ) + def zero_to_nan(value): if value == 0: return (float('nan')) return int(value) + def update_graph_data(): for data_type in sleep_data: s_data = sleep_data[data_type] # Re-referenced to shorten name @@ -175,7 +187,6 @@ def update_graph_data(): starting_index = max([(len(g_data['time']) - 1), 0]) ending_index = len(avg_data) - 1 - # Re-referenced to shorten name sleep_data_range = avg_data[starting_index:ending_index] for sleep_datum in sleep_data_range: @@ -184,6 +195,7 @@ def update_graph_data(): if g_data['data'][period] != 'nan': g_data['data'][period].append(sleep_datum[period]) + def init_graph_data(): for data_type in sleep_data: data_periods = sleep_data[data_type]['periods'] @@ -225,6 +237,11 @@ def graph_animation(i): if plotflag: plt.legend() + def init_graph(): ani = animation.FuncAnimation(graph_figure, graph_animation, interval=1000) plt.show() + + +if __name__ == 'sleepdata': + average_gyro_data = Average_Gyro_Data() \ No newline at end of file