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Add new target: stressfulness_period.

imputation_and_cleaning
Primoz 2022-11-03 13:52:45 +00:00
parent 35c1a762e7
commit 5e8174dd41
2 changed files with 3 additions and 3 deletions
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4
config.yaml
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@ -241,7 +241,7 @@ PHONE_ESM:
PROVIDERS:
STRAW:
COMPUTE: True
SCALES: ["PANAS_positive_affect", "PANAS_negative_affect", "JCQ_job_demand", "JCQ_job_control", "JCQ_supervisor_support", "JCQ_coworker_support"]
SCALES: ["PANAS_positive_affect", "PANAS_negative_affect", "JCQ_job_demand", "JCQ_job_control", "JCQ_supervisor_support", "JCQ_coworker_support", "appraisal_stressfulness_period"]
FEATURES: [mean]
SRC_SCRIPT: src/features/phone_esm/straw/main.py
@ -732,4 +732,4 @@ PARAMS_FOR_ANALYSIS:
TARGET:
COMPUTE: True
LABEL: PANAS_negative_affect_mean
ALL_LABELS: [PANAS_positive_affect_mean, PANAS_negative_affect_mean, "JCQ_job_demand_mean", "JCQ_job_control_mean", "JCQ_supervisor_support_mean", "JCQ_coworker_support_mean"]
ALL_LABELS: [PANAS_positive_affect_mean, PANAS_negative_affect_mean, "JCQ_job_demand_mean", "JCQ_job_control_mean", "JCQ_supervisor_support_mean", "JCQ_coworker_support_mean", "appraisal_stressfulness_period_mean"]

2
src/features/phone_esm/straw/main.py
View File

@ -42,7 +42,7 @@ def straw_features(sensor_data_files, time_segment, provider, filter_data_by_seg
requested_features = provider["FEATURES"]
# name of the features this function can compute
requested_scales = provider["SCALES"]
base_features_names = ["PANAS_positive_affect", "PANAS_negative_affect", "JCQ_job_demand", "JCQ_job_control", "JCQ_supervisor_support", "JCQ_coworker_support"]
base_features_names = ["PANAS_positive_affect", "PANAS_negative_affect", "JCQ_job_demand", "JCQ_job_control", "JCQ_supervisor_support", "JCQ_coworker_support", "appraisal_stressfulness_period"]
#TODO Check valid questionnaire and feature names.
# the subset of requested features this function can compute
features_to_compute = list(set(requested_features) & set(base_features_names))