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refactor: no longer round walking metrics; avoid spamming console with hour-of-day metrics #122

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merged 2 commits into from
Jun 10, 2024
Merged

refactor: no longer round walking metrics; avoid spamming console with hour-of-day metrics #122

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9da38d2
refactor: no longer round walking metrics
chanshing Jun 10, 2024
47896fd
refactor: avoid spamming console with hour-of-day metrics
chanshing Jun 10, 2024
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20 changes: 11 additions & 9 deletions src/stepcount/stepcount.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,7 @@
import argparse
import json
import hashlib
import re
import numpy as np
import pandas as pd
import joblib
Expand Down Expand Up @@ -242,7 +243,11 @@ def main():

# Print
print("\nSummary\n-------")
print(json.dumps(info, indent=4, cls=NpEncoder))
print(json.dumps(
# exclude hour-of-day metrics to avoid spamming the console
{k: v for k, v in info.items() if not re.search(r'_Hour\d{2}', k)},
indent=4, cls=NpEncoder
))
print("\nEstimated Daily Stats\n---------------------")
print(daily.set_index('Date').drop(columns='Filename'))
print("\nEstimated Daily Stats (Adjusted)\n---------------------")
Expand Down Expand Up @@ -451,8 +456,9 @@ def _tdelta_to_str(tdelta):

# daily stats
daily = pd.concat([
daily_walk.round().astype(pd.Int64Dtype()),
daily_walk,
daily.round().astype(pd.Int64Dtype()),
# convert timedelta to human-friendly format
daily_ptile_at.rename(columns={
'p05_at': 'Steps5thAt',
'p25_at': 'Steps25thAt',
Expand All @@ -466,21 +472,17 @@ def _tdelta_to_str(tdelta):
hour_steps = hourly.groupby(hourly.index.hour).agg(_mean).reindex(range(24))
hour_walks = hourly_walk.groupby(hourly_walk.index.hour).agg(_mean).reindex(range(24))

# convert units
# round steps
total = nanint(np.round(total))
minutely = minutely.round().astype(pd.Int64Dtype())
hourly = hourly.round().astype(pd.Int64Dtype())
daily_avg = nanint(np.round(daily_avg))
daily_med = nanint(np.round(daily_med))
daily_min = nanint(np.round(daily_min))
daily_max = nanint(np.round(daily_max))
total_walk = nanint(np.round(total_walk))
daily_walk_avg = nanint(np.round(daily_walk_avg))
daily_walk_med = nanint(np.round(daily_walk_med))
daily_walk_min = nanint(np.round(daily_walk_min))
daily_walk_max = nanint(np.round(daily_walk_max))
daily_ptile_at_avg = daily_ptile_at_avg.map(_tdelta_to_str)
hour_steps = hour_steps.round().astype(pd.Int64Dtype())
# convert timedelta to human-friendly format
daily_ptile_at_avg = daily_ptile_at_avg.map(_tdelta_to_str)

return {
'total': total,
Expand Down
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