diabetes.py

import pandas as pd

eventsDictionary = {
    33: "Regular insulin dose",
    34: "NPH insulin dose",
    35: "UltraLente insulin dose",
    48: "Unspecified blood glucose measurement",
    57: "Unspecified blood glucose measurement",
    58: "Pre-breakfast blood glucose measurement",
    59: "Post-breakfast blood glucose measurement",
    60: "Pre-lunch blood glucose measurement",
    61: "Post-lunch blood glucose measurement",
    62: "Pre-supper blood glucose measurement",
    63: "Post-supper blood glucose measurement",
    64: "Pre-snack blood glucose measurement",
    65: "Hypoglycemic symptoms",
    66: "Typical meal ingestion",
    67: "More-than-usual meal ingestion",
    68: "Less-than-usual meal ingestion",
    69: "Typical exercise activity",
    70: "More-than-usual exercise activity",
    71: "Less-than-usual exercise activity",
    72: "Unspecified special event"
}

def prepareDataDiabetes(user):
    diabetes = readData(user)
    events, states = splitEventsStatesDiabetes(diabetes)
    return events, states

def readData(user):
    return pd.DataFrame(readCSV(user))

def readCSV(user):
    if user == -1:
        diabetes = pd.read_csv("./data/diabetes/diabetes_merged.csv", sep="\t", header = None, names=["date", "time", "code", "value"], parse_dates=[["date", "time"]])
    else:
        if user < 10:
            filename = 'data-0' + str(user)
        else:
            filename = 'data-' + str(user)
        diabetes = pd.read_csv("./data/diabetes/" + filename, sep="\t", header = None, names=["date", "time", "code", "value"], parse_dates=[["date", "time"]])
    diabetes = diabetes.sort_values(by = ["date_time"], ascending = True)
    return diabetes
    
def splitEventsStatesDiabetes(dataframe):
    code_mask = (dataframe["code"] >= 48) & (dataframe["code"] <= 64)
    events = dataframe[~code_mask]
    events.reset_index(drop=True, inplace=True)
    events = events.drop(columns="value")
    states = dataframe[code_mask]
    states.reset_index(drop=True, inplace=True)
    states = states.drop(columns="code")
    return events, states 

def describePatternsDiabetes(patterns):
    describedPatterns = []
    for pattern in patterns:
        describedPattern = []
        for elem in pattern:
            describedPattern.append(eventsDictionary[elem])
        describedPatterns.append(describedPattern)

    return describedPatterns