Delete mystudy.snakefile and add all rules to models.snakefile
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8d71329e0e
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21c3251066
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@ -4,7 +4,6 @@ include: "rules/preprocessing.snakefile"
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include: "rules/features.snakefile"
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include: "rules/models.snakefile"
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include: "rules/reports.snakefile"
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include: "rules/mystudy.snakefile" # You can add snakfiles with rules tailored to your project
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import itertools
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@ -1,5 +1,41 @@
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ruleorder: nan_cells_ratio_of_cleaned_features > merge_features_and_targets
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rule days_to_analyse:
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input:
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participant_info = "data/raw/{pid}/" + config["PARAMS_FOR_ANALYSIS"]["GROUNDTRUTH_TABLE"] + "_raw.csv"
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params:
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days_before_surgery = "{days_before_surgery}",
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days_in_hospital = "{days_in_hospital}",
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days_after_discharge= "{days_after_discharge}"
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output:
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"data/interim/{pid}/days_to_analyse_{days_before_surgery}_{days_in_hospital}_{days_after_discharge}.csv"
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script:
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"../src/models/select_days_to_analyse.py"
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rule targets:
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input:
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participant_info = "data/raw/{pid}/" + config["PARAMS_FOR_ANALYSIS"]["GROUNDTRUTH_TABLE"] + "_raw.csv"
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params:
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pid = "{pid}",
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summarised = "{summarised}",
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targets_ratio_threshold = config["PARAMS_FOR_ANALYSIS"]["TARGETS_RATIO_THRESHOLD"],
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targets_value_threshold = config["PARAMS_FOR_ANALYSIS"]["TARGETS_VALUE_THRESHOLD"]
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output:
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"data/processed/{pid}/targets_{summarised}.csv"
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script:
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"../src/models/targets.py"
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rule demographic_features:
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input:
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participant_info = "data/raw/{pid}/" + config["PARAMS_FOR_ANALYSIS"]["GROUNDTRUTH_TABLE"] + "_raw.csv"
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params:
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pid = "{pid}",
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features = config["PARAMS_FOR_ANALYSIS"]["DEMOGRAPHIC_FEATURES"]
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output:
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"data/processed/{pid}/demographic_features.csv"
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script:
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"../src/features/demographic_features.py"
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def input_merge_features_of_single_participant(wildcards):
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if wildcards.source == "phone_fitbit_features":
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return expand("data/processed/{pid}/{features}_{day_segment}.csv", pid=wildcards.pid, features=config["PARAMS_FOR_ANALYSIS"]["PHONE_FEATURES"] + config["PARAMS_FOR_ANALYSIS"]["FITBIT_FEATURES"], day_segment=wildcards.day_segment)
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@ -1,35 +0,0 @@
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rule days_to_analyse:
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input:
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participant_info = "data/raw/{pid}/" + config["PARAMS_FOR_ANALYSIS"]["GROUNDTRUTH_TABLE"] + "_raw.csv"
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params:
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days_before_surgery = "{days_before_surgery}",
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days_in_hospital = "{days_in_hospital}",
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days_after_discharge= "{days_after_discharge}"
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output:
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"data/interim/{pid}/days_to_analyse_{days_before_surgery}_{days_in_hospital}_{days_after_discharge}.csv"
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script:
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"../src/models/select_days_to_analyse.py"
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rule targets:
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input:
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participant_info = "data/raw/{pid}/" + config["PARAMS_FOR_ANALYSIS"]["GROUNDTRUTH_TABLE"] + "_raw.csv"
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params:
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pid = "{pid}",
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summarised = "{summarised}",
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targets_ratio_threshold = config["PARAMS_FOR_ANALYSIS"]["TARGETS_RATIO_THRESHOLD"],
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targets_value_threshold = config["PARAMS_FOR_ANALYSIS"]["TARGETS_VALUE_THRESHOLD"]
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output:
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"data/processed/{pid}/targets_{summarised}.csv"
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script:
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"../src/models/targets.py"
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rule demographic_features:
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input:
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participant_info = "data/raw/{pid}/" + config["PARAMS_FOR_ANALYSIS"]["GROUNDTRUTH_TABLE"] + "_raw.csv"
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params:
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pid = "{pid}",
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features = config["PARAMS_FOR_ANALYSIS"]["DEMOGRAPHIC_FEATURES"]
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output:
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"data/processed/{pid}/demographic_features.csv"
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script:
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"../src/features/demographic_features.py"
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