Add new target: stressfulness_period.
parent
35c1a762e7
commit
5e8174dd41
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@ -241,7 +241,7 @@ PHONE_ESM:
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PROVIDERS:
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PROVIDERS:
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STRAW:
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STRAW:
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COMPUTE: True
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COMPUTE: True
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SCALES: ["PANAS_positive_affect", "PANAS_negative_affect", "JCQ_job_demand", "JCQ_job_control", "JCQ_supervisor_support", "JCQ_coworker_support"]
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SCALES: ["PANAS_positive_affect", "PANAS_negative_affect", "JCQ_job_demand", "JCQ_job_control", "JCQ_supervisor_support", "JCQ_coworker_support", "appraisal_stressfulness_period"]
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FEATURES: [mean]
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FEATURES: [mean]
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SRC_SCRIPT: src/features/phone_esm/straw/main.py
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SRC_SCRIPT: src/features/phone_esm/straw/main.py
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@ -732,4 +732,4 @@ PARAMS_FOR_ANALYSIS:
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TARGET:
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TARGET:
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COMPUTE: True
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COMPUTE: True
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LABEL: PANAS_negative_affect_mean
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LABEL: PANAS_negative_affect_mean
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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"]
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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"]
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@ -42,7 +42,7 @@ def straw_features(sensor_data_files, time_segment, provider, filter_data_by_seg
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requested_features = provider["FEATURES"]
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requested_features = provider["FEATURES"]
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# name of the features this function can compute
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# name of the features this function can compute
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requested_scales = provider["SCALES"]
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requested_scales = provider["SCALES"]
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base_features_names = ["PANAS_positive_affect", "PANAS_negative_affect", "JCQ_job_demand", "JCQ_job_control", "JCQ_supervisor_support", "JCQ_coworker_support"]
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base_features_names = ["PANAS_positive_affect", "PANAS_negative_affect", "JCQ_job_demand", "JCQ_job_control", "JCQ_supervisor_support", "JCQ_coworker_support", "appraisal_stressfulness_period"]
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#TODO Check valid questionnaire and feature names.
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#TODO Check valid questionnaire and feature names.
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# the subset of requested features this function can compute
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# the subset of requested features this function can compute
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features_to_compute = list(set(requested_features) & set(base_features_names))
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features_to_compute = list(set(requested_features) & set(base_features_names))
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