Get targets

Co-authored-by: JulioV <juliovhz@gmail.com>
pull/95/head
Meng Li 2020-03-26 17:27:23 -04:00
parent ac758e3776
commit ea46df63d5
3 changed files with 29 additions and 1 deletions

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@ -14,7 +14,9 @@ rule all:
days_before_surgery = config["METRICS_FOR_ANALYSIS"]["DAYS_BEFORE_SURGERY"], days_before_surgery = config["METRICS_FOR_ANALYSIS"]["DAYS_BEFORE_SURGERY"],
days_after_discharge= config["METRICS_FOR_ANALYSIS"]["DAYS_AFTER_DISCHARGE"], days_after_discharge= config["METRICS_FOR_ANALYSIS"]["DAYS_AFTER_DISCHARGE"],
days_in_hospital= config["METRICS_FOR_ANALYSIS"]["DAYS_IN_HOSPITAL"]), days_in_hospital= config["METRICS_FOR_ANALYSIS"]["DAYS_IN_HOSPITAL"]),
expand("data/processed/{pid}/targets_{summarised}.csv",
pid = config["PIDS"],
summarised = config["METRICS_FOR_ANALYSIS"]["SUMMARISED"]),
# Feature extraction # Feature extraction
expand("data/raw/{pid}/{sensor}_raw.csv", pid=config["PIDS"], sensor=config["SENSORS"]), expand("data/raw/{pid}/{sensor}_raw.csv", pid=config["PIDS"], sensor=config["SENSORS"]),
expand("data/raw/{pid}/{sensor}_raw.csv", pid=config["PIDS"], sensor=config["FITBIT_TABLE"]), expand("data/raw/{pid}/{sensor}_raw.csv", pid=config["PIDS"], sensor=config["FITBIT_TABLE"]),

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@ -9,3 +9,13 @@ rule days_to_analyse:
"data/interim/{pid}/days_to_analyse_{days_before_surgery}_{days_in_hospital}_{days_after_discharge}.csv" "data/interim/{pid}/days_to_analyse_{days_before_surgery}_{days_in_hospital}_{days_after_discharge}.csv"
script: script:
"../src/models/select_days_to_analyse.py" "../src/models/select_days_to_analyse.py"
rule get_targets:
input:
participant_info = "data/raw/{pid}/" + config["METRICS_FOR_ANALYSIS"]["GROUNDTRUTH_TABLE"] + "_raw.csv"
params:
summarised = "{summarised}"
output:
"data/processed/{pid}/targets_{summarised}.csv"
script:
"../src/models/get_targets.py"

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@ -0,0 +1,16 @@
import pandas as pd
participant_info = pd.read_csv(snakemake.input["participant_info"])
summarised = snakemake.params["summarised"]
pid = snakemake.input["participant_info"].split("/")[2]
targets = pd.DataFrame({"pid": [pid], "target": [None]})
if summarised == "summarised":
if not participant_info.empty:
cesds = participant_info.loc[0, ["preop_cesd_total", "inpatient_cesd_total", "postop_cesd_total", "3month_cesd_total"]]
# targets: 1 => 50% (ceiling) or more of available CESD scores were 16 or higher; 0 => otherwise
threshold_num = (cesds.count() + 1) // 2
threshold_cesd = 16
target = 1 if cesds.apply(lambda x : 1 if x >= threshold_cesd else 0).sum() >= threshold_num else 0
targets.loc[0, "target"] = target
targets.to_csv(snakemake.output[0], index=False)