Add Fitbit steps feature extraction

replace/5a54662dae646c78dea0f1e015592372cddfea2b
Echhit Joshi 2020-01-29 16:22:53 -05:00
parent db2f3dc50f
commit d82fa0d217
4 changed files with 122 additions and 0 deletions

View File

@ -44,6 +44,9 @@ rule all:
expand("data/raw/{pid}/fitbit_{fitbit_sensor}_with_datetime.csv", expand("data/raw/{pid}/fitbit_{fitbit_sensor}_with_datetime.csv",
pid=config["PIDS"], pid=config["PIDS"],
fitbit_sensor=config["FITBIT_SENSORS"]), fitbit_sensor=config["FITBIT_SENSORS"]),
expand("data/processed/{pid}/fitbit_step_{day_segment}.csv",
pid = config["PIDS"],
day_segment = config["STEP"]["DAY_SEGMENTS"]),
# Reports # Reports
expand("reports/figures/{pid}/{sensor}_heatmap_rows.html", pid=config["PIDS"], sensor=config["SENSORS"]), expand("reports/figures/{pid}/{sensor}_heatmap_rows.html", pid=config["PIDS"], sensor=config["SENSORS"]),
expand("reports/figures/{pid}/compliance_heatmap.html", pid=config["PIDS"]), expand("reports/figures/{pid}/compliance_heatmap.html", pid=config["PIDS"]),

View File

@ -91,3 +91,11 @@ LIGHT:
ACCELEROMETER: ACCELEROMETER:
DAY_SEGMENTS: *day_segments DAY_SEGMENTS: *day_segments
METRICS: ["maxmagnitude", "minmagnitude", "avgmagnitude", "medianmagnitude", "stdmagnitude", "ratioexertionalactivityepisodes", "sumexertionalactivityepisodes", "longestexertionalactivityepisode", "longestnonexertionalactivityepisode", "countexertionalactivityepisodes", "countnonexertionalactivityepisodes"] METRICS: ["maxmagnitude", "minmagnitude", "avgmagnitude", "medianmagnitude", "stdmagnitude", "ratioexertionalactivityepisodes", "sumexertionalactivityepisodes", "longestexertionalactivityepisode", "longestnonexertionalactivityepisode", "countexertionalactivityepisodes", "countnonexertionalactivityepisodes"]
STEP:
DAY_SEGMENTS: *day_segments
METRICS:
ALL_STEPS: ["sumallsteps", "maxallsteps", "minallsteps", "avgallsteps", "stdallsteps"]
SEDENTARY_BOUT: ["countsedentarybout", "maxdurationsedentarybout", "mindurationsedentarybout", "avgdurationsedentarybout", "stddurationsedentarybout"]
ACTIVE_BOUT: ["countactivebout", "maxdurationactivebout", "mindurationactivebout", "avgdurationactivebout", "stddurationactivebout"]
THRESHOLD_ACTIVE_BOUT: 10 # steps

View File

@ -130,3 +130,17 @@ rule accelerometer_metrics:
"data/processed/{pid}/accelerometer_{day_segment}.csv" "data/processed/{pid}/accelerometer_{day_segment}.csv"
script: script:
"../src/features/accelerometer_metrics.py" "../src/features/accelerometer_metrics.py"
rule fitbit_step_metrics:
input:
steps_data = "data/raw/{pid}/fitbit_steps_with_datetime.csv",
params:
day_segment = "{day_segment}",
metrics_all_steps = config["STEP"]["METRICS"]["ALL_STEPS"],
metrics_sedentary_bout = config["STEP"]["METRICS"]["SEDENTARY_BOUT"],
metrics_active_bout = config["STEP"]["METRICS"]["ACTIVE_BOUT"],
threshold_active_bout = config["STEP"]["THRESHOLD_ACTIVE_BOUT"]
output:
"data/processed/{pid}/fitbit_step_{day_segment}.csv"
script:
"../src/features/fitbit_step_metrics.py"

View File

@ -0,0 +1,97 @@
import pandas as pd
import numpy as np
import datetime as dt
from features_utils import splitOvernightEpisodes, splitMultiSegmentEpisodes
day_segment = snakemake.params["day_segment"]
all_steps = snakemake.params["metrics_all_steps"]
sedentary_bout = snakemake.params["metrics_sedentary_bout"]
active_bout = snakemake.params["metrics_active_bout"]
threshold_active_bout = snakemake.params['threshold_active_bout']
#Read csv into a pandas dataframe
data = pd.read_csv(snakemake.input['steps_data'],parse_dates=['local_date_time'])
columns = list("step_" + str(day_segment) + "_" + column for column in (all_steps + sedentary_bout + active_bout))
if (day_segment != 'daily'):
data = data.loc[data['local_day_segment'] == str(day_segment)]
if data.empty:
finalDataset = pd.DataFrame(columns = columns)
else:
finalDataset = pd.DataFrame()
#Preprocessing:
data.local_date_time = pd.to_datetime(data.local_date_time)
resampledData = data.set_index(data.local_date_time)
resampledData.index.names = ['datetime']
resampledData['time_diff_minutes'] = resampledData['local_date_time'].diff().fillna(pd.Timedelta(seconds=0)).dt.total_seconds().div(60).astype(int)
#Sedentary Bout when you have less than 10 steps in a minute
#Active Bout when you have greater or equal to 10 steps in a minute
resampledData['active_sedentary'] = np.where(resampledData['steps']<int(threshold_active_bout),'sedentary','active')
activeData = resampledData[resampledData['active_sedentary']=="active"]
sedentaryData = resampledData[resampledData['active_sedentary']=="sedentary"]
#Time Calculations of sedentary/active bouts:
resampledData['active_sedentary_groups'] = (resampledData.active_sedentary != resampledData.active_sedentary.shift()).cumsum().values
#Get the total minutes for each episode
minutesGroupedBy = resampledData.groupby(['local_date','active_sedentary','active_sedentary_groups'])['time_diff_minutes'].sum()
#Get Stats for all episodes in terms of minutes
statsMinutes = minutesGroupedBy.groupby(['local_date','active_sedentary']).agg([max,min,np.mean,np.std])
mux = pd.MultiIndex.from_product([statsMinutes.index.levels[0], statsMinutes.index.levels[1]],names=['local_date','active_sedentary'])
statsMinutes = statsMinutes.reindex(mux, fill_value=None).reset_index()
statsMinutes.set_index('local_date',inplace = True)
#Descriptive Statistics Features:
if("sumallsteps" in all_steps):
finalDataset["step_" + str(day_segment) + "_sumallsteps"] = resampledData['steps'].resample('D').sum()
if("maxallsteps" in all_steps):
finalDataset["step_" + str(day_segment) + "_maxallsteps"] = resampledData['steps'].resample('D').max()
if("minallsteps" in all_steps):
finalDataset["step_" + str(day_segment) + "_minallsteps"] = resampledData['steps'].resample('D').min()
if("avgallsteps" in all_steps):
finalDataset["step_" + str(day_segment) + "_avgallsteps"] = resampledData['steps'].resample('D').mean()
if("stdallsteps" in all_steps):
finalDataset["step_" + str(day_segment) + "_stdallsteps"] = resampledData['steps'].resample('D').std()
if("countsedentarybout" in sedentary_bout):
finalDataset["step_" + str(day_segment) + "_countsedentarybout"] = sedentaryData['active_sedentary'].resample('D').count()
if("countactivebout" in active_bout):
finalDataset["step_" + str(day_segment) + "_countactivebout"] = activeData['active_sedentary'].resample('D').count()
if("maxdurationsedentarybout" in sedentary_bout):
finalDataset["step_" + str(day_segment) + "_maxdurationsedentarybout"] = statsMinutes[statsMinutes['active_sedentary']=='sedentary']['max']
if("mindurationsedentarybout" in sedentary_bout):
finalDataset["step_" + str(day_segment) + "_mindurationsedentarybout"] = statsMinutes[statsMinutes['active_sedentary']=='sedentary']['min']
if("avgdurationsedentarybout" in sedentary_bout):
finalDataset["step_" + str(day_segment) + "_avgdurationsedentarybout"] = statsMinutes[statsMinutes['active_sedentary']=='sedentary']['mean']
if("stddurationsedentarybout" in sedentary_bout):
finalDataset["step_" + str(day_segment) + "_stddurationsedentarybout"] = statsMinutes[statsMinutes['active_sedentary']=='sedentary']['std']
if("maxdurationactivebout" in active_bout):
finalDataset["step_" + str(day_segment) + "_maxdurationactivebout"] = statsMinutes[statsMinutes['active_sedentary']== 'active']['max']
if("mindurationactivebout" in active_bout):
finalDataset["step_" + str(day_segment) + "_mindurationactivebout"] = statsMinutes[statsMinutes['active_sedentary']== 'active']['min']
if("avgdurationactivebout" in active_bout):
finalDataset["step_" + str(day_segment) + "_avgdurationactivebout"] = statsMinutes[statsMinutes['active_sedentary']== 'active']['mean']
if("stddurationactivebout" in active_bout):
finalDataset["step_" + str(day_segment) + "_stddurationactivebout"] = statsMinutes[statsMinutes['active_sedentary']== 'active']['std']
finalDataset.index.names = ['local_date']
finalDataset.to_csv(snakemake.output[0])