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Start empatica support

feature/plugin_sentimental
JulioV 2020-12-14 20:30:34 -05:00
parent 8b2f8c3ce1
commit 8c726f5d4f
13 changed files with 534 additions and 3 deletions
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63
Snakefile
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@ -288,6 +288,69 @@ for provider in config["FITBIT_STEPS_INTRADAY"]["PROVIDERS"].keys():
# files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"])) # files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"]))
# files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv") # files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv")
for provider in config["EMPATICA_ACCELEROMETER"]["PROVIDERS"].keys():
if config["EMPATICA_ACCELEROMETER"]["PROVIDERS"][provider]["COMPUTE"]:
files_to_compute.extend(expand("data/raw/{pid}/empatica_accelerometer_raw.csv", pid=config["PIDS"]))
files_to_compute.extend(expand("data/raw/{pid}/empatica_accelerometer_with_datetime.csv", pid=config["PIDS"]))
files_to_compute.extend(expand("data/interim/{pid}/empatica_accelerometer_features/empatica_accelerometer_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["EMPATICA_ACCELEROMETER"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower()))
files_to_compute.extend(expand("data/processed/features/{pid}/empatica_accelerometer.csv", pid=config["PIDS"]))
files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"]))
files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv")
for provider in config["EMPATICA_HEARTRATE"]["PROVIDERS"].keys():
if config["EMPATICA_HEARTRATE"]["PROVIDERS"][provider]["COMPUTE"]:
files_to_compute.extend(expand("data/raw/{pid}/empatica_heartrate_raw.csv", pid=config["PIDS"]))
files_to_compute.extend(expand("data/raw/{pid}/empatica_heartrate_with_datetime.csv", pid=config["PIDS"]))
files_to_compute.extend(expand("data/interim/{pid}/empatica_heartrate_features/empatica_heartrate_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["EMPATICA_HEARTRATE"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower()))
files_to_compute.extend(expand("data/processed/features/{pid}/empatica_heartrate.csv", pid=config["PIDS"]))
files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"]))
files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv")
for provider in config["EMPATICA_TEMPERATURE"]["PROVIDERS"].keys():
if config["EMPATICA_TEMPERATURE"]["PROVIDERS"][provider]["COMPUTE"]:
files_to_compute.extend(expand("data/raw/{pid}/empatica_temperature_raw.csv", pid=config["PIDS"]))
files_to_compute.extend(expand("data/raw/{pid}/empatica_temperature_with_datetime.csv", pid=config["PIDS"]))
files_to_compute.extend(expand("data/interim/{pid}/empatica_temperature_features/empatica_temperature_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["EMPATICA_TEMPERATURE"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower()))
files_to_compute.extend(expand("data/processed/features/{pid}/empatica_temperature.csv", pid=config["PIDS"]))
files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"]))
files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv")
for provider in config["EMPATICA_ELECTRODERMAL_ACTIVITY"]["PROVIDERS"].keys():
if config["EMPATICA_ELECTRODERMAL_ACTIVITY"]["PROVIDERS"][provider]["COMPUTE"]:
files_to_compute.extend(expand("data/raw/{pid}/empatica_electrodermal_activity_raw.csv", pid=config["PIDS"]))
files_to_compute.extend(expand("data/raw/{pid}/empatica_electrodermal_activity_with_datetime.csv", pid=config["PIDS"]))
files_to_compute.extend(expand("data/interim/{pid}/empatica_electrodermal_activity_features/empatica_electrodermal_activity_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["EMPATICA_ELECTRODERMAL_ACTIVITY"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower()))
files_to_compute.extend(expand("data/processed/features/{pid}/empatica_electrodermal_activity.csv", pid=config["PIDS"]))
files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"]))
files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv")
for provider in config["EMPATICA_BLOOD_VOLUME_PULSE"]["PROVIDERS"].keys():
if config["EMPATICA_BLOOD_VOLUME_PULSE"]["PROVIDERS"][provider]["COMPUTE"]:
files_to_compute.extend(expand("data/raw/{pid}/empatica_blood_volume_pulse_raw.csv", pid=config["PIDS"]))
files_to_compute.extend(expand("data/raw/{pid}/empatica_blood_volume_pulse_with_datetime.csv", pid=config["PIDS"]))
files_to_compute.extend(expand("data/interim/{pid}/empatica_blood_volume_pulse_features/empatica_blood_volume_pulse_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["EMPATICA_BLOOD_VOLUME_PULSE"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower()))
files_to_compute.extend(expand("data/processed/features/{pid}/empatica_blood_volume_pulse.csv", pid=config["PIDS"]))
files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"]))
files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv")
for provider in config["EMPATICA_INTER_BEAT_INTERVAL"]["PROVIDERS"].keys():
if config["EMPATICA_INTER_BEAT_INTERVAL"]["PROVIDERS"][provider]["COMPUTE"]:
files_to_compute.extend(expand("data/raw/{pid}/empatica_inter_beat_interval_raw.csv", pid=config["PIDS"]))
files_to_compute.extend(expand("data/raw/{pid}/empatica_inter_beat_interval_with_datetime.csv", pid=config["PIDS"]))
files_to_compute.extend(expand("data/interim/{pid}/empatica_inter_beat_interval_features/empatica_inter_beat_interval_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["EMPATICA_INTER_BEAT_INTERVAL"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower()))
files_to_compute.extend(expand("data/processed/features/{pid}/empatica_inter_beat_interval.csv", pid=config["PIDS"]))
files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"]))
files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv")
for provider in config["EMPATICA_TAGS"]["PROVIDERS"].keys():
if config["EMPATICA_TAGS"]["PROVIDERS"][provider]["COMPUTE"]:
files_to_compute.extend(expand("data/raw/{pid}/empatica_tags_raw.csv", pid=config["PIDS"]))
files_to_compute.extend(expand("data/raw/{pid}/empatica_tags_with_datetime.csv", pid=config["PIDS"]))
files_to_compute.extend(expand("data/interim/{pid}/empatica_tags_features/empatica_tags_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["EMPATICA_TAGS"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower()))
files_to_compute.extend(expand("data/processed/features/{pid}/empatica_tags.csv", pid=config["PIDS"]))
files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"]))
files_to_compute.append("data/processed/features/all_participants/all_sensor_features.csv")
# Visualization for Data Exploration # Visualization for Data Exploration
if config["HISTOGRAM_PHONE_DATA_YIELD"]["PLOT"]: if config["HISTOGRAM_PHONE_DATA_YIELD"]["PLOT"]:
files_to_compute.append("reports/data_exploration/histogram_phone_data_yield.html") files_to_compute.append("reports/data_exploration/histogram_phone_data_yield.html")

78
config.yaml
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@ -7,7 +7,7 @@ TIMEZONE: &timezone
America/New_York America/New_York
# See https://www.rapids.science/latest/setup/configuration/#participant-files # See https://www.rapids.science/latest/setup/configuration/#participant-files
PIDS: [test01] PIDS: [e01]
# See https://www.rapids.science/latest/setup/configuration/#automatic-creation-of-participant-files # See https://www.rapids.science/latest/setup/configuration/#automatic-creation-of-participant-files
CREATE_PARTICIPANT_FILES: CREATE_PARTICIPANT_FILES:
@ -408,6 +408,82 @@ FITBIT_STEPS_INTRADAY:
# FEATURES: [] # FEATURES: []
########################################################################################################################
# EMPATICA #
########################################################################################################################
EMPATICA_DATA_CONFIGURATION:
SOURCE:
TYPE: FILE
TIMEZONE:
TYPE: SINGLE # Fitbit devices don't support time zones so we read this data in the timezone indicated by VALUE
VALUE: *timezone
# Sensors ------
# See https://www.rapids.science/latest/features/fitbit-heartrate-summary/
EMPATICA_ACCELEROMETER:
TABLE: acc
PROVIDERS:
DBDP:
COMPUTE: True
FEATURES: []
SRC_FOLDER: "dbdp" # inside src/features/empatica_accelerometer
SRC_LANGUAGE: "python"
EMPATICA_HEARTRATE:
TABLE: hr
PROVIDERS:
DBDP:
COMPUTE: True
FEATURES: []
SRC_FOLDER: "dbdp" # inside src/features/empatica_heartrate
SRC_LANGUAGE: "python"
EMPATICA_TEMPERATURE:
TABLE: temp
PROVIDERS:
DBDP:
COMPUTE: True
FEATURES: []
SRC_FOLDER: "dbdp" # inside src/features/empatica_heartrate
SRC_LANGUAGE: "python"
EMPATICA_ELECTRODERMAL_ACTIVITY:
TABLE: temp
PROVIDERS:
DBDP:
COMPUTE: True
FEATURES: []
SRC_FOLDER: "dbdp" # inside src/features/empatica_heartrate
SRC_LANGUAGE: "python"
EMPATICA_BLOOD_VOLUME_PULSE:
TABLE: bvp
PROVIDERS:
DBDP:
COMPUTE: True
FEATURES: []
SRC_FOLDER: "dbdp" # inside src/features/empatica_heartrate
SRC_LANGUAGE: "python"
EMPATICA_INTER_BEAT_INTERVAL:
TABLE: ibi
PROVIDERS:
DBDP:
COMPUTE: True
FEATURES: []
SRC_FOLDER: "dbdp" # inside src/features/empatica_heartrate
SRC_LANGUAGE: "python"
EMPATICA_TAGS:
TABLE: tags
PROVIDERS:
DBDP:
COMPUTE: True
FEATURES: []
SRC_FOLDER: "dbdp" # inside src/features/empatica_heartrate
SRC_LANGUAGE: "python"
######################################################################################################################## ########################################################################################################################
# PLOTS # # PLOTS #

2
rules/common.smk
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@ -15,7 +15,7 @@ def optional_steps_sleep_input(wildcards):
def input_merge_sensor_features_for_individual_participants(wildcards): def input_merge_sensor_features_for_individual_participants(wildcards):
feature_files = [] feature_files = []
for config_key in config.keys(): for config_key in config.keys():
if config_key.startswith(("PHONE", "FITBIT")) and "PROVIDERS" in config[config_key] and isinstance(config[config_key]["PROVIDERS"], dict): if config_key.startswith(("PHONE", "FITBIT", "EMPATICA")) and "PROVIDERS" in config[config_key] and isinstance(config[config_key]["PROVIDERS"], dict):
for provider_key, provider in config[config_key]["PROVIDERS"].items(): for provider_key, provider in config[config_key]["PROVIDERS"].items():
if "COMPUTE" in provider.keys() and provider["COMPUTE"]: if "COMPUTE" in provider.keys() and provider["COMPUTE"]:
feature_files.append("data/processed/features/{pid}/" + config_key.lower() + ".csv") feature_files.append("data/processed/features/{pid}/" + config_key.lower() + ".csv")

184
rules/features.smk
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@ -2,7 +2,7 @@ rule join_features_from_providers:
input: input:
sensor_features = find_features_files sensor_features = find_features_files
wildcard_constraints: wildcard_constraints:
sensor_key = '(phone|fitbit).*' sensor_key = '(phone|fitbit|empatica).*'
output: output:
"data/processed/features/{pid}/{sensor_key}.csv" "data/processed/features/{pid}/{sensor_key}.csv"
script: script:
@ -675,3 +675,185 @@ rule merge_sensor_features_for_all_participants:
"data/processed/features/all_participants/all_sensor_features.csv" "data/processed/features/all_participants/all_sensor_features.csv"
script: script:
"../src/features/utils/merge_sensor_features_for_all_participants.R" "../src/features/utils/merge_sensor_features_for_all_participants.R"
rule empatica_accelerometer_python_features:
input:
sensor_data = "data/raw/{pid}/empatica_accelerometer_with_datetime.csv",
time_segments_labels = "data/interim/time_segments/{pid}_time_segments_labels.csv"
params:
provider = lambda wildcards: config["EMPATICA_ACCELEROMETER"]["PROVIDERS"][wildcards.provider_key.upper()],
provider_key = "{provider_key}",
sensor_key = "empatica_accelerometer"
output:
"data/interim/{pid}/empatica_accelerometer_features/empatica_accelerometer_python_{provider_key}.csv"
script:
"../src/features/entry.py"
rule empatica_accelerometer_r_features:
input:
sensor_data = "data/raw/{pid}/empatica_accelerometer_with_datetime.csv",
time_segments_labels = "data/interim/time_segments/{pid}_time_segments_labels.csv"
params:
provider = lambda wildcards: config["EMPATICA_ACCELEROMETER"]["PROVIDERS"][wildcards.provider_key.upper()],
provider_key = "{provider_key}",
sensor_key = "empatica_accelerometer"
output:
"data/interim/{pid}/empatica_accelerometer_features/empatica_accelerometer_r_{provider_key}.csv"
script:
"../src/features/entry.R"
rule empatica_heartrate_python_features:
input:
sensor_data = "data/raw/{pid}/empatica_heartrate_with_datetime.csv",
time_segments_labels = "data/interim/time_segments/{pid}_time_segments_labels.csv"
params:
provider = lambda wildcards: config["EMPATICA_HEARTRATE"]["PROVIDERS"][wildcards.provider_key.upper()],
provider_key = "{provider_key}",
sensor_key = "empatica_heartrate"
output:
"data/interim/{pid}/empatica_heartrate_features/empatica_heartrate_python_{provider_key}.csv"
script:
"../src/features/entry.py"
rule empatica_heartrate_r_features:
input:
sensor_data = "data/raw/{pid}/empatica_heartrate_with_datetime.csv",
time_segments_labels = "data/interim/time_segments/{pid}_time_segments_labels.csv"
params:
provider = lambda wildcards: config["EMPATICA_HEARTRATE"]["PROVIDERS"][wildcards.provider_key.upper()],
provider_key = "{provider_key}",
sensor_key = "empatica_heartrate"
output:
"data/interim/{pid}/empatica_heartrate_features/empatica_heartrate_r_{provider_key}.csv"
script:
"../src/features/entry.R"
rule empatica_temperature_python_features:
input:
sensor_data = "data/raw/{pid}/empatica_temperature_with_datetime.csv",
time_segments_labels = "data/interim/time_segments/{pid}_time_segments_labels.csv"
params:
provider = lambda wildcards: config["EMPATICA_TEMPERATURE"]["PROVIDERS"][wildcards.provider_key.upper()],
provider_key = "{provider_key}",
sensor_key = "empatica_temperature"
output:
"data/interim/{pid}/empatica_temperature_features/empatica_temperature_python_{provider_key}.csv"
script:
"../src/features/entry.py"
rule empatica_temperature_r_features:
input:
sensor_data = "data/raw/{pid}/empatica_temperature_with_datetime.csv",
time_segments_labels = "data/interim/time_segments/{pid}_time_segments_labels.csv"
params:
provider = lambda wildcards: config["EMPATICA_TEMPERATURE"]["PROVIDERS"][wildcards.provider_key.upper()],
provider_key = "{provider_key}",
sensor_key = "empatica_temperature"
output:
"data/interim/{pid}/empatica_temperature_features/empatica_temperature_r_{provider_key}.csv"
script:
"../src/features/entry.R"
rule empatica_electrodermal_activity_python_features:
input:
sensor_data = "data/raw/{pid}/empatica_electrodermal_activity_with_datetime.csv",
time_segments_labels = "data/interim/time_segments/{pid}_time_segments_labels.csv"
params:
provider = lambda wildcards: config["EMPATICA_ELECTRODERMAL_ACTIVITY"]["PROVIDERS"][wildcards.provider_key.upper()],
provider_key = "{provider_key}",
sensor_key = "empatica_electrodermal_activity"
output:
"data/interim/{pid}/empatica_electrodermal_activity_features/empatica_electrodermal_activity_python_{provider_key}.csv"
script:
"../src/features/entry.py"
rule empatica_electrodermal_activity_r_features:
input:
sensor_data = "data/raw/{pid}/empatica_electrodermal_activity_with_datetime.csv",
time_segments_labels = "data/interim/time_segments/{pid}_time_segments_labels.csv"
params:
provider = lambda wildcards: config["EMPATICA_ELECTRODERMAL_ACTIVITY"]["PROVIDERS"][wildcards.provider_key.upper()],
provider_key = "{provider_key}",
sensor_key = "empatica_electrodermal_activity"
output:
"data/interim/{pid}/empatica_electrodermal_activity_features/empatica_electrodermal_activity_r_{provider_key}.csv"
script:
"../src/features/entry.R"
rule empatica_blood_volume_pulse_python_features:
input:
sensor_data = "data/raw/{pid}/empatica_blood_volume_pulse_with_datetime.csv",
time_segments_labels = "data/interim/time_segments/{pid}_time_segments_labels.csv"
params:
provider = lambda wildcards: config["EMPATICA_BLOOD_VOLUME_PULSE"]["PROVIDERS"][wildcards.provider_key.upper()],
provider_key = "{provider_key}",
sensor_key = "empatica_blood_volume_pulse"
output:
"data/interim/{pid}/empatica_blood_volume_pulse_features/empatica_blood_volume_pulse_python_{provider_key}.csv"
script:
"../src/features/entry.py"
rule empatica_blood_volume_pulse_r_features:
input:
sensor_data = "data/raw/{pid}/empatica_blood_volume_pulse_with_datetime.csv",
time_segments_labels = "data/interim/time_segments/{pid}_time_segments_labels.csv"
params:
provider = lambda wildcards: config["EMPATICA_BLOOD_VOLUME_PULSE"]["PROVIDERS"][wildcards.provider_key.upper()],
provider_key = "{provider_key}",
sensor_key = "empatica_blood_volume_pulse"
output:
"data/interim/{pid}/empatica_blood_volume_pulse_features/empatica_blood_volume_pulse_r_{provider_key}.csv"
script:
"../src/features/entry.R"
rule empatica_inter_beat_interval_python_features:
input:
sensor_data = "data/raw/{pid}/empatica_inter_beat_interval_with_datetime.csv",
time_segments_labels = "data/interim/time_segments/{pid}_time_segments_labels.csv"
params:
provider = lambda wildcards: config["EMPATICA_INTER_BEAT_INTERVAL"]["PROVIDERS"][wildcards.provider_key.upper()],
provider_key = "{provider_key}",
sensor_key = "empatica_inter_beat_interval"
output:
"data/interim/{pid}/empatica_inter_beat_interval_features/empatica_inter_beat_interval_python_{provider_key}.csv"
script:
"../src/features/entry.py"
rule empatica_inter_beat_interval_r_features:
input:
sensor_data = "data/raw/{pid}/empatica_inter_beat_interval_with_datetime.csv",
time_segments_labels = "data/interim/time_segments/{pid}_time_segments_labels.csv"
params:
provider = lambda wildcards: config["EMPATICA_INTER_BEAT_INTERVAL"]["PROVIDERS"][wildcards.provider_key.upper()],
provider_key = "{provider_key}",
sensor_key = "empatica_inter_beat_interval"
output:
"data/interim/{pid}/empatica_inter_beat_interval_features/empatica_inter_beat_interval_r_{provider_key}.csv"
script:
"../src/features/entry.R"
rule empatica_tags_python_features:
input:
sensor_data = "data/raw/{pid}/empatica_tags_with_datetime.csv",
time_segments_labels = "data/interim/time_segments/{pid}_time_segments_labels.csv"
params:
provider = lambda wildcards: config["EMPATICA_TAGS"]["PROVIDERS"][wildcards.provider_key.upper()],
provider_key = "{provider_key}",
sensor_key = "empatica_tags"
output:
"data/interim/{pid}/empatica_tags_features/empatica_tags_python_{provider_key}.csv"
script:
"../src/features/entry.py"
rule empatica_tags_r_features:
input:
sensor_data = "data/raw/{pid}/empatica_tags_with_datetime.csv",
time_segments_labels = "data/interim/time_segments/{pid}_time_segments_labels.csv"
params:
provider = lambda wildcards: config["EMPATICA_TAGS"]["PROVIDERS"][wildcards.provider_key.upper()],
provider_key = "{provider_key}",
sensor_key = "empatica_tags"
output:
"data/interim/{pid}/empatica_tags_features/empatica_tags_r_{provider_key}.csv"
script:
"../src/features/entry.R"

31
rules/preprocessing.smk
View File

@ -242,3 +242,34 @@ rule fitbit_readable_datetime:
"data/raw/{pid}/fitbit_{sensor}_{fitbit_data_type}_parsed_with_datetime.csv" "data/raw/{pid}/fitbit_{sensor}_{fitbit_data_type}_parsed_with_datetime.csv"
script: script:
"../src/data/readable_datetime.R" "../src/data/readable_datetime.R"
def empatica_input(wildcards):
return expand("data/external/empatica/{{pid}}/{filename}.csv", filename=config["EMPATICA_" + str(wildcards.sensor).upper()]["TABLE"])
rule extract_empatica_data:
input:
input_file = empatica_input,
participant_file = "data/external/participant_files/{pid}.yaml"
params:
data_configuration = config["EMPATICA_DATA_CONFIGURATION"],
sensor = "{sensor}",
table = lambda wildcards: config["EMPATICA_" + str(wildcards.sensor).upper()]["TABLE"],
output:
sensor_output = "data/raw/{pid}/empatica_{sensor}_raw.csv"
script:
"../src/data/empatica/extract_empatica_data.py"
rule empatica_readable_datetime:
input:
sensor_input = "data/raw/{pid}/empatica_{sensor}_raw.csv",
time_segments = "data/interim/time_segments/{pid}_time_segments.csv"
params:
timezones = config["PHONE_DATA_CONFIGURATION"]["TIMEZONE"]["TYPE"],
fixed_timezone = config["PHONE_DATA_CONFIGURATION"]["TIMEZONE"]["VALUE"],
time_segments_type = config["TIME_SEGMENTS"]["TYPE"],
include_past_periodic_segments = config["TIME_SEGMENTS"]["INCLUDE_PAST_PERIODIC_SEGMENTS"]
output:
"data/raw/{pid}/empatica_{sensor}_with_datetime.csv"
script:
"../src/data/readable_datetime.R"

32
src/data/empatica/extract_empatica_data.py 100644
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@ -0,0 +1,32 @@
import pandas as pd
from pandas.core import indexing
import yaml
def extract_empatica_data(sensor_data_file, output_file, start_date, end_date, timezone, sensor):
print(sensor_data_file)
print(output_file)
print(start_date)
print(end_date)
print(timezone)
print(sensor)
data = pd.read_csv(sensor_data_file)
print(data)
# extract
print(output_file)
data.to_csv(output_file, index = False)
sensor_data_file = snakemake.input[0]
output_file = snakemake.output[0]
with open(snakemake.input[1], "r", encoding="utf-8") as f:
participant_file = yaml.safe_load(f)
start_date = participant_file["EMPATICA"]["START_DATE"]
end_date = participant_file["EMPATICA"]["END_DATE"]
timezone = snakemake.params["data_configuration"]["TIMEZONE"]["VALUE"]
sensor = snakemake.params["sensor"]
extract_empatica_data(sensor_data_file, output_file, start_date, end_date, timezone, sensor)

21
src/features/empatica_accelerometer/dbdp/main.py 100644
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@ -0,0 +1,21 @@
import pandas as pd
import numpy as np
def dbdp_features(sensor_data_files, time_segment, provider, filter_data_by_segment, *args, **kwargs):
sensor_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))
features = pd.DataFrame(columns=["local_segment"] + features_to_compute)
if not sensor_data.empty:
sensor_data = filter_data_by_segment(sensor_data, time_segment)
if not sensor_data.empty:
features = pd.DataFrame()
return features

21
src/features/empatica_blood_volume_pulse/dbdp/main.py 100644
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import pandas as pd
import numpy as np
def dbdp_features(sensor_data_files, time_segment, provider, filter_data_by_segment, *args, **kwargs):
sensor_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))
features = pd.DataFrame(columns=["local_segment"] + features_to_compute)
if not sensor_data.empty:
sensor_data = filter_data_by_segment(sensor_data, time_segment)
if not sensor_data.empty:
features = pd.DataFrame()
return features

21
src/features/empatica_electrodermal_activity/dbdp/main.py 100644
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import pandas as pd
import numpy as np
def dbdp_features(sensor_data_files, time_segment, provider, filter_data_by_segment, *args, **kwargs):
sensor_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))
features = pd.DataFrame(columns=["local_segment"] + features_to_compute)
if not sensor_data.empty:
sensor_data = filter_data_by_segment(sensor_data, time_segment)
if not sensor_data.empty:
features = pd.DataFrame()
return features

21
src/features/empatica_heartrate/dbdp/main.py 100644
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import pandas as pd
import numpy as np
def dbdp_features(sensor_data_files, time_segment, provider, filter_data_by_segment, *args, **kwargs):
sensor_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))
features = pd.DataFrame(columns=["local_segment"] + features_to_compute)
if not sensor_data.empty:
sensor_data = filter_data_by_segment(sensor_data, time_segment)
if not sensor_data.empty:
features = pd.DataFrame()
return features

21
src/features/empatica_inter_beat_interval/dbdp/main.py 100644
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import pandas as pd
import numpy as np
def dbdp_features(sensor_data_files, time_segment, provider, filter_data_by_segment, *args, **kwargs):
sensor_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))
features = pd.DataFrame(columns=["local_segment"] + features_to_compute)
if not sensor_data.empty:
sensor_data = filter_data_by_segment(sensor_data, time_segment)
if not sensor_data.empty:
features = pd.DataFrame()
return features

21
src/features/empatica_tags/dbdp/main.py 100644
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import pandas as pd
import numpy as np
def dbdp_features(sensor_data_files, time_segment, provider, filter_data_by_segment, *args, **kwargs):
sensor_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))
features = pd.DataFrame(columns=["local_segment"] + features_to_compute)
if not sensor_data.empty:
sensor_data = filter_data_by_segment(sensor_data, time_segment)
if not sensor_data.empty:
features = pd.DataFrame()
return features

21
src/features/empatica_temperature/dbdp/main.py 100644
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import pandas as pd
import numpy as np
def dbdp_features(sensor_data_files, time_segment, provider, filter_data_by_segment, *args, **kwargs):
sensor_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))
features = pd.DataFrame(columns=["local_segment"] + features_to_compute)
if not sensor_data.empty:
sensor_data = filter_data_by_segment(sensor_data, time_segment)
if not sensor_data.empty:
features = pd.DataFrame()
return features