44 lines
1.8 KiB
Python
44 lines
1.8 KiB
Python
import numpy as np
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import pandas as pd
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from datetime import timedelta
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def appendDaysInRange(days_to_analyse, start_date, end_date, day_type):
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num_of_days = (end_date - start_date).days
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if np.isnan(num_of_days):
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return days_to_analyse
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for day in range(num_of_days + 1):
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if day_type == -1:
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day_idx = (num_of_days - day + 1) * day_type
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elif day_type == 1:
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day_idx = day + 1
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else:
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day_idx = 0
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days_to_analyse = days_to_analyse.append({"local_date": start_date + timedelta(days = day), "day_idx": day_idx}, ignore_index=True)
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return days_to_analyse
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days_before_surgery = int(snakemake.params["days_before_surgery"])
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days_in_hospital = str(snakemake.params["days_in_hospital"])
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days_after_discharge = int(snakemake.params["days_after_discharge"])
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participant_info = pd.read_csv(snakemake.input["participant_info"], parse_dates=["surgery_date", "discharge_date"])
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days_to_analyse = pd.DataFrame(columns = ["local_date", "day_idx"])
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try:
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surgery_date, discharge_date = participant_info["surgery_date"].iloc[0].date(), participant_info["discharge_date"].iloc[0].date()
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except:
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pass
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else:
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start_date = surgery_date - timedelta(days = days_before_surgery)
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end_date = discharge_date + timedelta(days = days_after_discharge)
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# days before surgery: -1; in hospital: 0; after discharge: 1
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days_to_analyse = appendDaysInRange(days_to_analyse, start_date, surgery_date - timedelta(days = 1), -1)
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if days_in_hospital == "T":
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days_to_analyse = appendDaysInRange(days_to_analyse, surgery_date, discharge_date, 0)
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days_to_analyse = appendDaysInRange(days_to_analyse, discharge_date + timedelta(days = 1), end_date, 1)
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days_to_analyse.to_csv(snakemake.output[0], index=False)
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