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Refactor to standardized naming conventions for PR#1

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Rob MacKinnon 2021-01-26 23:00:00 -08:00 committed by GitHub
parent 5e6bb15d1c
commit 0a616243cc
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1 changed files with 24 additions and 24 deletions
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bluesleep.py
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@ -156,17 +156,17 @@ def flush_old_raw_data(tick_time):
global sleep_data global sleep_data
for data_type in sleep_data: for data_type in sleep_data:
s_datum = sleep_data[data_type] s_data = sleep_data[data_type]
periods = s_datum['periods'] periods = s_datum['periods']
cleaned_raw_data = [] cleaned_raw_data = []
for raw_datum in s_datum['raw_data']: for raw_datum in s_data['raw_data']:
datum_age = tick_time - raw_datum['time'] datum_age = tick_time - raw_datum['time']
if datum_age < max(periods): if datum_age < max(periods):
cleaned_raw_data.append(raw_datum) cleaned_raw_data.append(raw_datum)
s_datum['raw_data'] = cleaned_raw_data s_data['raw_data'] = cleaned_raw_data
def average_raw_data(tick_time): def average_raw_data(tick_time):
@ -176,10 +176,10 @@ def average_raw_data(tick_time):
csv_out = {'time': timestamp } csv_out = {'time': timestamp }
for data_type in sleep_data: for data_type in sleep_data:
s_datum = sleep_data[data_type] s_data = sleep_data[data_type]
period_averages_dict = {'time': timestamp} period_averages_dict = {'time': timestamp}
periods = s_datum['periods'] periods = s_data['periods']
value_name = s_datum['value_name'] value_name = s_data['value_name']
flush_old_raw_data(tick_time) flush_old_raw_data(tick_time)
@ -202,7 +202,7 @@ def average_raw_data(tick_time):
csv_out[data_type + str(period_seconds)] = zero_to_nan(period_data_average) csv_out[data_type + str(period_seconds)] = zero_to_nan(period_data_average)
s_datum['averaged_data'].append(period_averages_dict) s_data['averaged_data'].append(period_averages_dict)
write_csv(csv_out) write_csv(csv_out)
@ -246,25 +246,25 @@ def update_graph_data():
global graph_data global graph_data
for data_type in sleep_data: for data_type in sleep_data:
s_datum = sleep_data[data_type] # Re-referenced to shorten name s_data = sleep_data[data_type] # Re-referenced to shorten name
avg_datum = s_datum['averaged_data'] avg_data = s_data['averaged_data']
if len(avg_datum) > 1: if len(avg_data) > 1:
g_datum = graph_data[data_type] # Re-referenced to short name g_data = graph_data[data_type] # Re-referenced to short name
data_periods = s_datum['periods'] data_periods = s_data['periods']
starting_index = max([(len(g_dataum['time']) - 1), 0]) starting_index = max([(len(g_data['time']) - 1), 0])
ending_index = len(avg_datum) - 1 ending_index = len(avg_data) - 1
# Re-referenced to shorten name # Re-referenced to shorten name
sleep_data_range = avg_datum[starting_index:ending_index] sleep_data_range = avg_data[starting_index:ending_index]
for sleep_datum in sleep_data_range: for sleep_datum in sleep_data_range:
g_datum['time'].append(sleep_datum['time']) g_data['time'].append(sleep_datum['time'])
for period in data_periods: for period in data_periods:
if g_datum['data'][period] != 'nan': if g_data['data'][period] != 'nan':
g_datum['data'][period].append(sleep_datum[period]) g_data['data'][period].append(sleep_datum[period])
def graph_animation(i): def graph_animation(i):
@ -284,15 +284,15 @@ def graph_animation(i):
break break
for data_type in sleep_data: for data_type in sleep_data:
s_datum = sleep_data[data_type] s_data = sleep_data[data_type]
g_datum = graph_data[data_type] g_data = graph_data[data_type]
if len(g_datum['time']) > 0: if len(g_datum['time']) > 0:
plotflag = True plotflag = True
data_periods = sleep_data[data_type]['periods'] data_periods = sleep_data[data_type]['periods']
for period in data_periods: for period in data_periods:
axis_label = "{} {} sec".format(s_datum['value_name'], period) axis_label = "{} {} sec".format(s_data['value_name'], period)
graph_axes.plot(g_datum['time'], graph_axes.plot(g_data['time'],
g_datum['data'][period], g_data['data'][period],
label=axis_label) label=axis_label)
if plotflag: if plotflag:
@ -346,4 +346,4 @@ if __name__ == "__main__":
# comfort_wav = 'comfort.wav' # comfort_wav = 'comfort.wav'
# wave_obj = sa.WaveObject.from_wave_file(comfort_wav) # wave_obj = sa.WaveObject.from_wave_file(comfort_wav)
# comfort_delay = 30 # comfort_delay = 30
# comfort_lasttime = time.time() # comfort_lasttime = time.time()