From 3cee393470aa8f563504e8d7b0e9e2e7967f3681 Mon Sep 17 00:00:00 2001 From: Shing Chan Date: Wed, 31 Jan 2024 18:20:51 +0000 Subject: [PATCH] rename sunlight -> outdoor light --- src/axivity_outdoor_light/main.py | 72 +++++++++++++++---------------- 1 file changed, 36 insertions(+), 36 deletions(-) diff --git a/src/axivity_outdoor_light/main.py b/src/axivity_outdoor_light/main.py index 675166b..9c06b5e 100644 --- a/src/axivity_outdoor_light/main.py +++ b/src/axivity_outdoor_light/main.py @@ -64,7 +64,7 @@ def main(): # continue # sunlit.loc[g[~na].index] = predict_outdoor(g.loc[~na, 'light']) - print("Estimating sunlight...") + print("Estimating outdoor light...") na = data.isna().any(axis=1) sunlit.loc[~na] = predict_outdoor(data.loc[~na, 'light']) @@ -78,30 +78,30 @@ def mode(x): sunlit = sunlit.rolling(5, min_periods=1).apply(mode, raw=True) - fig = plot(sunlit, enmo=data['enmo'], label='Sunlight', title=basename) + fig = plot(sunlit, enmo=data['enmo'], label='Outdoor Light', title=basename) fig.savefig(f"{outdir}/{basename}-Plot.png") # Moderate to Vigorous Physical Activity mvpa = (data['enmo'] >= 100).astype('float') # 100 millig mvpa[na] = np.nan - # Moderate to Vigorous Physical Activity in Sunlight + # Moderate to Vigorous Physical Activity and Outdoor Light sunlit_and_mvpa = (sunlit.astype('bool') & mvpa.astype('bool')).astype('float') sunlit_and_mvpa[na] = np.nan pd.concat([ - sunlit.rename('Sunlight'), + sunlit.rename('Outdoor'), mvpa.rename('MVPA'), - sunlit_and_mvpa.rename('SunlightMVPA') + sunlit_and_mvpa.rename('OutdoorMVPA') ], axis=1).to_csv(f"{outdir}/{basename}-Minutes.csv") # Summary sunlit_summa = summarize(sunlit, adjust_estimates=False) - info['TotalSunlight(mins)'] = sunlit_summa['total'] - info['SunlightDayAvg(mins)'] = sunlit_summa['daily_avg'] - info['SunlightDayMed(mins)'] = sunlit_summa['daily_med'] - info['SunlightDayMin(mins)'] = sunlit_summa['daily_min'] - info['SunlightDayMax(mins)'] = sunlit_summa['daily_max'] + info['TotalOutdoorLight(mins)'] = sunlit_summa['total'] + info['OutdoorLightDayAvg(mins)'] = sunlit_summa['daily_avg'] + info['OutdoorLightDayMed(mins)'] = sunlit_summa['daily_med'] + info['OutdoorLightDayMin(mins)'] = sunlit_summa['daily_min'] + info['OutdoorLightDayMax(mins)'] = sunlit_summa['daily_max'] mvpa_summa = summarize(mvpa, adjust_estimates=False) info['TotalMVPA(mins)'] = mvpa_summa['total'] @@ -111,31 +111,31 @@ def mode(x): info['MVPADayMax(mins)'] = mvpa_summa['daily_max'] sunlit_and_mvpa_summa = summarize(sunlit_and_mvpa, adjust_estimates=False) - info['TotalSunlightMVPA(mins)'] = sunlit_and_mvpa_summa['total'] - info['SunlightMVPADayAvg(mins)'] = sunlit_and_mvpa_summa['daily_avg'] - info['SunlightMVPADayMed(mins)'] = sunlit_and_mvpa_summa['daily_med'] - info['SunlightMVPADayMin(mins)'] = sunlit_and_mvpa_summa['daily_min'] - info['SunlightMVPADayMax(mins)'] = sunlit_and_mvpa_summa['daily_max'] + info['TotalOutdoorMVPA(mins)'] = sunlit_and_mvpa_summa['total'] + info['OutdoorMVPADayAvg(mins)'] = sunlit_and_mvpa_summa['daily_avg'] + info['OutdoorMVPADayMed(mins)'] = sunlit_and_mvpa_summa['daily_med'] + info['OutdoorMVPADayMin(mins)'] = sunlit_and_mvpa_summa['daily_min'] + info['OutdoorMVPADayMax(mins)'] = sunlit_and_mvpa_summa['daily_max'] pd.concat([ - sunlit_summa['daily'].rename('Sunlight(mins)'), + sunlit_summa['daily'].rename('OutdoorLight(mins)'), mvpa_summa['daily'].rename('MVPA(mins)'), - sunlit_and_mvpa_summa['daily'].rename('SunlightMVPA(mins)') + sunlit_and_mvpa_summa['daily'].rename('OutdoorMVPA(mins)') ], axis=1).to_csv(f"{outdir}/{basename}-Daily.csv") pd.concat([ - sunlit_summa['hourly'].rename('Sunlight(mins)'), + sunlit_summa['hourly'].rename('OutdoorLight(mins)'), mvpa_summa['hourly'].rename('MVPA(mins)'), - sunlit_and_mvpa_summa['hourly'].rename('SunlightMVPA(mins)') + sunlit_and_mvpa_summa['hourly'].rename('OutdoorMVPA(mins)') ], axis=1).to_csv(f"{outdir}/{basename}-Hourly.csv") # Summary Adjusted sunlit_summa_adj = summarize(sunlit, adjust_estimates=True) - info['TotalSunlightAdjusted(mins)'] = sunlit_summa_adj['total'] - info['SunlightDayAvgAdjusted(mins)'] = sunlit_summa_adj['daily_avg'] - info['SunlightDayMedAdjusted(mins)'] = sunlit_summa_adj['daily_med'] - info['SunlightDayMinAdjusted(mins)'] = sunlit_summa_adj['daily_min'] - info['SunlightDayMaxAdjusted(mins)'] = sunlit_summa_adj['daily_max'] + info['TotalOutdoorLightAdjusted(mins)'] = sunlit_summa_adj['total'] + info['OutdoorLightDayAvgAdjusted(mins)'] = sunlit_summa_adj['daily_avg'] + info['OutdoorLightDayMedAdjusted(mins)'] = sunlit_summa_adj['daily_med'] + info['OutdoorLightDayMinAdjusted(mins)'] = sunlit_summa_adj['daily_min'] + info['OutdoorLightDayMaxAdjusted(mins)'] = sunlit_summa_adj['daily_max'] mvpa_summa_adj = summarize(mvpa, adjust_estimates=True) info['TotalMVPAAdjusted(mins)'] = mvpa_summa_adj['total'] @@ -145,22 +145,22 @@ def mode(x): info['MVPADayMaxAdjusted(mins)'] = mvpa_summa_adj['daily_max'] sunlit_and_mvpa_summa_adj = summarize(sunlit_and_mvpa, adjust_estimates=True) - info['TotalSunlightMVPAAdjusted(mins)'] = sunlit_and_mvpa_summa_adj['total'] - info['SunlightMVPADayAvgAdjusted(mins)'] = sunlit_and_mvpa_summa_adj['daily_avg'] - info['SunlightMVPADayMedAdjusted(mins)'] = sunlit_and_mvpa_summa_adj['daily_med'] - info['SunlightMVPADayMinAdjusted(mins)'] = sunlit_and_mvpa_summa_adj['daily_min'] - info['SunlightMVPADayMaxAdjusted(mins)'] = sunlit_and_mvpa_summa_adj['daily_max'] + info['TotalOutdoorMVPAAdjusted(mins)'] = sunlit_and_mvpa_summa_adj['total'] + info['OutdoorMVPADayAvgAdjusted(mins)'] = sunlit_and_mvpa_summa_adj['daily_avg'] + info['OutdoorMVPADayMedAdjusted(mins)'] = sunlit_and_mvpa_summa_adj['daily_med'] + info['OutdoorMVPADayMinAdjusted(mins)'] = sunlit_and_mvpa_summa_adj['daily_min'] + info['OutdoorMVPADayMaxAdjusted(mins)'] = sunlit_and_mvpa_summa_adj['daily_max'] pd.concat([ - sunlit_summa_adj['daily'].rename('SunlightAdjusted(mins)'), + sunlit_summa_adj['daily'].rename('OutdoorLightAdjusted(mins)'), mvpa_summa_adj['daily'].rename('MVPAAdjusted(mins)'), - sunlit_and_mvpa_summa_adj['daily'].rename('SunlightMVPAAdjusted(mins)') + sunlit_and_mvpa_summa_adj['daily'].rename('OutdoorMVPAAdjusted(mins)') ], axis=1).to_csv(f"{outdir}/{basename}-DailyAdjusted.csv") pd.concat([ - sunlit_summa_adj['hourly'].rename('SunlightAdjusted(mins)'), + sunlit_summa_adj['hourly'].rename('OutdoorLightAdjusted(mins)'), mvpa_summa_adj['hourly'].rename('MVPAAdjusted(mins)'), - sunlit_and_mvpa_summa_adj['hourly'].rename('SunlightMVPAAdjusted(mins)') + sunlit_and_mvpa_summa_adj['hourly'].rename('OutdoorMVPAAdjusted(mins)') ], axis=1).to_csv(f"{outdir}/{basename}-HourlyAdjusted.csv") # Save info @@ -170,10 +170,10 @@ def mode(x): # Print print("\nSummary\n-------") print(json.dumps(info, indent=4, cls=NpEncoder)) - print("\nEstimated Daily Sunlight\n---------------------") + print("\nEstimated Daily OutdoorLight\n---------------------") print(pd.concat([ - sunlit_summa['daily'].rename('Sunlight(mins)'), - sunlit_summa_adj['daily'].rename('SunlightAdjusted(mins)'), + sunlit_summa['daily'].rename('OutdoorLight(mins)'), + sunlit_summa_adj['daily'].rename('OutdoorLightAdjusted(mins)'), ], axis=1)) print(f"Done! ({time.time() - before:.2f}s)")