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Testing files change and remove standardization from hrv sensors main files.

sociality-task
Primoz 2022-07-06 07:35:39 +00:00
parent a5480f1369
commit 2d5d23b615
4 changed files with 48 additions and 39 deletions
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6
src/features/empatica_blood_volume_pulse/cr/main.py
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@ -66,14 +66,8 @@ def cr_features(sensor_data_files, time_segment, provider, filter_data_by_segmen
requested_window_length, time_segment, filter_data_by_segment)
if calc_windows:
if provider["WINDOWS"].get("STANDARDIZE_FEATURES", False):
fo_columns = bvp_intraday_features.columns.values[2:]
fo_columns_z_score = [col + "_zscore" for col in fo_columns]
bvp_intraday_features[fo_columns_z_score] = StandardScaler().fit_transform(bvp_intraday_features[fo_columns])
so_features_names = provider["WINDOWS"]["SECOND_ORDER_FEATURES"]
bvp_second_order_features = extract_second_order_features(bvp_intraday_features, so_features_names)
return bvp_intraday_features, bvp_second_order_features
return bvp_intraday_features

5
src/features/empatica_inter_beat_interval/cr/main.py
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@ -71,11 +71,6 @@ def cr_features(sensor_data_files, time_segment, provider, filter_data_by_segmen
requested_window_length, time_segment, filter_data_by_segment)
if calc_windows:
if provider["WINDOWS"].get("STANDARDIZE_FEATURES", False):
fo_columns = ibi_intraday_features.columns.values[2:]
fo_columns_z_score = [col + "_zscore" for col in fo_columns]
ibi_intraday_features[fo_columns_z_score] = StandardScaler().fit_transform(ibi_intraday_features[fo_columns])
so_features_names = provider["WINDOWS"]["SECOND_ORDER_FEATURES"]
ibi_second_order_features = extract_second_order_features(ibi_intraday_features, so_features_names)

25
tests/scripts/missing_vals.py
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@ -2,14 +2,25 @@ import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
participant = "p02"
# path = "/rapids/data/processed/features/all_participants/all_sensor_features.csv" # all features all participants
# path = "/rapids/data/interim/p03/empatica_accelerometer_features/empatica_accelerometer_python_cr_windows.csv"
participant = "p02"
all_sensors = ["ibi", "bvp"]#["eda", "bvp", "ibi", "temp", "acc"]
for sensor in all_sensors:
if sensor == "eda":
path = f"/rapids/data/interim/{participant}/empatica_electrodermal_activity_features/empatica_electrodermal_activity_python_cr_windows.csv"
# path = "/rapids/data/interim/p02/empatica_inter_beat_interval_features/empatica_inter_beat_interval_python_cr_windows.csv"
# path = "/rapids/data/interim/p02/empatica_blood_volume_pulse_features/empatica_blood_volume_pulse_python_cr_windows.csv"
# path = "/rapids/data/interim/p02/empatica_temperature_features/empatica_temperature_python_cr_windows.csv"
elif sensor == "bvp":
path = f"/rapids/data/interim/{participant}/empatica_blood_volume_pulse_features/empatica_blood_volume_pulse_python_cr_windows.csv"
elif sensor == "ibi":
path = f"/rapids/data/interim/{participant}/empatica_inter_beat_interval_features/empatica_inter_beat_interval_python_cr_windows.csv"
elif sensor == "acc":
path = f"/rapids/data/interim/{participant}/empatica_accelerometer_features/empatica_accelerometer_python_cr_windows.csv"
elif sensor == "temp":
path = f"/rapids/data/interim/{participant}/empatica_temperature_features/empatica_temperature_python_cr_windows.csv"
else:
path = "/rapids/data/processed/features/all_participants/all_sensor_features.csv" # all features all participants
df = pd.read_csv(path)
print(df)
@ -23,6 +34,6 @@ print("\nDf mean:")
print(df.mean())
sns.heatmap(df.isna(), cbar=False)
plt.savefig(f'eda_{participant}_windows_NaN.png', bbox_inches='tight')
plt.savefig(f'{sensor}_{participant}_windows_NaN.png', bbox_inches='tight')

21
tests/scripts/zero_vals.py
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@ -3,14 +3,23 @@ import seaborn as sns
import matplotlib.pyplot as plt
from itertools import compress
participant = "p02"
# path = "/rapids/data/processed/features/all_participants/all_sensor_features.csv" # all features all participants
# path = "/rapids/data/interim/p03/empatica_accelerometer_features/empatica_accelerometer_python_cr_windows.csv"
participant = "p031"
sensor = "eda"
if sensor == "eda":
path = f"/rapids/data/interim/{participant}/empatica_electrodermal_activity_features/empatica_electrodermal_activity_python_cr_windows.csv"
# path = "/rapids/data/interim/p02/empatica_inter_beat_interval_features/empatica_inter_beat_interval_python_cr_windows.csv"
# path = "/rapids/data/interim/p02/empatica_blood_volume_pulse_features/empatica_blood_volume_pulse_python_cr_windows.csv"
# path = "/rapids/data/interim/p02/empatica_temperature_features/empatica_temperature_python_cr_windows.csv"
elif sensor == "bvp":
path = f"/rapids/data/interim/{participant}/empatica_blood_volume_pulse_features/empatica_blood_volume_pulse_python_cr_windows.csv"
elif sensor == "ibi":
path = f"/rapids/data/interim/{participant}/empatica_inter_beat_interval_features/empatica_inter_beat_interval_python_cr_windows.csv"
elif sensor == "acc":
path = f"/rapids/data/interim/{participant}/empatica_accelerometer_features/empatica_accelerometer_python_cr_windows.csv"
elif sensor == "temp":
path = f"/rapids/data/interim/{participant}/empatica_temperature_features/empatica_temperature_python_cr_windows.csv"
else:
path = "/rapids/data/processed/features/all_participants/all_sensor_features.csv" # all features all participants"
df = pd.read_csv(path)
df_num_peaks_zero = df[df["empatica_electrodermal_activity_cr_numPeaks"] == 0]