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Add accelerometer features of RAPIDS provider

pull/103/head
Meng Li 2020-10-13 11:42:36 -04:00
parent 55c12fc83c
commit 29dcd1f284
4 changed files with 69 additions and 21 deletions
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10
Snakefile
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@ -104,10 +104,12 @@ for provider in config["LIGHT"]["PROVIDERS"].keys():
files_to_compute.extend(expand("data/interim/{pid}/{sensor_key}_features/{sensor_key}_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["LIGHT"]["PROVIDERS"][provider]["SRC_LANGUAGE"], provider_key=provider, sensor_key="LIGHT".lower()))
files_to_compute.extend(expand("data/processed/features/{pid}/{sensor_key}.csv", pid=config["PIDS"], sensor_key="LIGHT".lower()))
if config["ACCELEROMETER"]["COMPUTE"]:
files_to_compute.extend(expand("data/raw/{pid}/{sensor}_raw.csv", pid=config["PIDS"], sensor=config["ACCELEROMETER"]["DB_TABLE"]))
files_to_compute.extend(expand("data/raw/{pid}/{sensor}_with_datetime.csv", pid=config["PIDS"], sensor=config["ACCELEROMETER"]["DB_TABLE"]))
files_to_compute.extend(expand("data/processed/{pid}/accelerometer_{day_segment}.csv", pid = config["PIDS"], day_segment = config["ACCELEROMETER"]["DAY_SEGMENTS"]))
for provider in config["ACCELEROMETER"]["PROVIDERS"].keys():
if config["ACCELEROMETER"]["PROVIDERS"][provider]["COMPUTE"]:
files_to_compute.extend(expand("data/raw/{pid}/{sensor}_raw.csv", pid=config["PIDS"], sensor=config["ACCELEROMETER"]["DB_TABLE"]))
files_to_compute.extend(expand("data/raw/{pid}/{sensor}_with_datetime.csv", pid=config["PIDS"], sensor=config["ACCELEROMETER"]["DB_TABLE"]))
files_to_compute.extend(expand("data/interim/{pid}/{sensor_key}_features/{sensor_key}_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["ACCELEROMETER"]["PROVIDERS"][provider]["SRC_LANGUAGE"], provider_key=provider, sensor_key="ACCELEROMETER".lower()))
files_to_compute.extend(expand("data/processed/features/{pid}/{sensor_key}.csv", pid=config["PIDS"], sensor_key="ACCELEROMETER".lower()))
for provider in config["APPLICATIONS_FOREGROUND"]["PROVIDERS"].keys():
if config["APPLICATIONS_FOREGROUND"]["PROVIDERS"][provider]["COMPUTE"]:

14
config.yaml
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@ -158,16 +158,14 @@ LIGHT:
SRC_FOLDER: "rapids" # inside src/features/light
SRC_LANGUAGE: "python"
ACCELEROMETER:
COMPUTE: False
DB_TABLE: accelerometer
DAY_SEGMENTS: *day_segments
FEATURES:
MAGNITUDE: ["maxmagnitude", "minmagnitude", "avgmagnitude", "medianmagnitude", "stdmagnitude"]
EXERTIONAL_ACTIVITY_EPISODE: ["sumduration", "maxduration", "minduration", "avgduration", "medianduration", "stdduration"]
NONEXERTIONAL_ACTIVITY_EPISODE: ["sumduration", "maxduration", "minduration", "avgduration", "medianduration", "stdduration"]
VALID_SENSED_MINUTES: False
PROVIDERS:
RAPIDS:
COMPUTE: False
FEATURES: ["maxmagnitude", "minmagnitude", "avgmagnitude", "medianmagnitude", "stdmagnitude"]
SRC_FOLDER: "rapids" # inside src/features/accelerometer
SRC_LANGUAGE: "python"
APPLICATIONS_FOREGROUND:
DB_TABLE: applications_foreground

30
rules/features.smk
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@ -28,19 +28,31 @@ rule resample_episodes_with_datetime:
script:
"../src/data/readable_datetime.R"
rule accelerometer_features:
rule accelerometer_r_features:
input:
expand("data/raw/{{pid}}/{sensor}_with_datetime.csv", sensor=config["ACCELEROMETER"]["DB_TABLE"]),
sensor_data = expand("data/raw/{{pid}}/{sensor}_with_datetime.csv", sensor=config["ACCELEROMETER"]["DB_TABLE"])[0],
day_segments_labels = "data/interim/day_segments/{pid}_day_segments_labels.csv"
params:
day_segment = "{day_segment}",
magnitude = config["ACCELEROMETER"]["FEATURES"]["MAGNITUDE"],
exertional_activity_episode = config["ACCELEROMETER"]["FEATURES"]["EXERTIONAL_ACTIVITY_EPISODE"],
nonexertional_activity_episode = config["ACCELEROMETER"]["FEATURES"]["NONEXERTIONAL_ACTIVITY_EPISODE"],
valid_sensed_minutes = config["ACCELEROMETER"]["FEATURES"]["VALID_SENSED_MINUTES"],
provider = lambda wildcards: config["ACCELEROMETER"]["PROVIDERS"][wildcards.provider_key],
provider_key = "{provider_key}",
sensor_key = "accelerometer"
output:
"data/processed/{pid}/accelerometer_{day_segment}.csv"
"data/interim/{pid}/accelerometer_features/accelerometer_r_{provider_key}.csv"
script:
"../src/features/accelerometer_features.py"
"../src/features/entry.R"
rule accelerometer_python_features:
input:
sensor_data = expand("data/raw/{{pid}}/{sensor}_with_datetime.csv", sensor=config["ACCELEROMETER"]["DB_TABLE"])[0],
day_segments_labels = "data/interim/day_segments/{pid}_day_segments_labels.csv"
params:
provider = lambda wildcards: config["ACCELEROMETER"]["PROVIDERS"][wildcards.provider_key],
provider_key = "{provider_key}",
sensor_key = "accelerometer"
output:
"data/interim/{pid}/accelerometer_features/accelerometer_python_{provider_key}.csv"
script:
"../src/features/entry.py"
rule activity_recognition_episodes:
input:

36
src/features/accelerometer/rapids/main.py 100644
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@ -0,0 +1,36 @@
import pandas as pd
import numpy as np
def rapids_features(sensor_data_files, day_segment, provider, filter_data_by_segment, *args, **kwargs):
acc_data = pd.read_csv(sensor_data_files["sensor_data"])
requested_features = provider["FEATURES"]
# name of the features this function can compute
base_features_names = ["maxmagnitude", "minmagnitude", "avgmagnitude", "medianmagnitude", "stdmagnitude"]
# the subset of requested features this function can compute
features_to_compute = list(set(requested_features) & set(base_features_names))
acc_features = pd.DataFrame(columns=["local_segment"] + ["acc_rapids_" + x for x in features_to_compute])
if not acc_data.empty:
acc_data = filter_data_by_segment(acc_data, day_segment)
if not acc_data.empty:
acc_features = pd.DataFrame()
# get magnitude related features: magnitude = sqrt(x^2+y^2+z^2)
magnitude = acc_data.apply(lambda row: np.sqrt(row["double_values_0"] ** 2 + row["double_values_1"] ** 2 + row["double_values_2"] ** 2), axis=1)
acc_data = acc_data.assign(magnitude = magnitude.values)
if "maxmagnitude" in features_to_compute:
acc_features["acc_rapids_maxmagnitude"] = acc_data.groupby(["local_segment"])["magnitude"].max()
if "minmagnitude" in features_to_compute:
acc_features["acc_rapids_minmagnitude"] = acc_data.groupby(["local_segment"])["magnitude"].min()
if "avgmagnitude" in features_to_compute:
acc_features["acc_rapids_avgmagnitude"] = acc_data.groupby(["local_segment"])["magnitude"].mean()
if "medianmagnitude" in features_to_compute:
acc_features["acc_rapids_medianmagnitude"] = acc_data.groupby(["local_segment"])["magnitude"].median()
if "stdmagnitude" in features_to_compute:
acc_features["acc_rapids_stdmagnitude"] = acc_data.groupby(["local_segment"])["magnitude"].std()
acc_features = acc_features.reset_index()
return acc_features