starter-kit/summary.py at master · prescriptive-analytics/starter-kit · GitHub

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#!/usr/bin/env python
# coding: utf-8

# In[1]:


import pandas as pd
import os
import numpy as np


# In[2]:


columns = ['day', 'hospitalizeNum', 'isolateNum', 'quarantineNum', 'confineNum',
       'free', 'CurrentHealthy', 'CurrentInfected', 'CurrentEffective','CurrentSusceptible', 'CurrentIncubation', 'CurrentDiscovered', 'CurrentCritical', 'CurrentRecovered',
       'AccDiscovered', 'AccCritical', 'AccAcquaintance', 'AccStranger', 'measurement']

# Here are some consts for metrics
I_threshold = 500
Q_threshold = 10000
Q_weight = 1
time = 59 # The last day of our simulation


# In[3]:


def process_file(file):
    # Read data

    df = pd.read_csv(file, sep=',', engine='python', header=None)
    df.columns = columns

    # Accumulate
    for item in ['hospitalizeNum', 'isolateNum', 'quarantineNum', 'confineNum']:
        sum = 0
        list_sum = []
        ind = 0
        l = len(df[item])
        while ind < l:
            sum += df[item][ind]
            list_sum.append(sum)
            if df["day"][ind] == time:
                sum = 0
            ind += 1
        df["sum_"+item] = np.array(list_sum)
    return df


# In[4]:


def get_I_Q(df, time):
    # Get I and Q value at the given time

    df_sub = df[df["day"]==time]
    I = df_sub["CurrentInfected"].mean()

    inHospital_mean = df_sub["sum_hospitalizeNum"].mean()
    isolateNum_mean = df_sub["sum_isolateNum"].mean()
    confineNum_mean = df_sub["sum_confineNum"].mean()
    quarantineNum_mean = df_sub["sum_quarantineNum"].mean()
    Q = 1 *  inHospital_mean + 0.5 * isolateNum_mean+ 0.3 * quarantineNum_mean + 0.2 * confineNum_mean

    return I, Q


# In[5]:


def get_least_Q_score(I, Q, I_threshold):
    score = np.copy(Q)
    score[I > I_threshold] = 1e6

    return score


# In[6]:


def get_exp_score(I, Q, I_threshold, Q_threshold, Q_weight):
    I_score = np.exp(I/I_threshold)
    Q_score = Q_weight * (np.exp(Q/ Q_threshold))

    return I_score + Q_score


# In[7]:
def main():
    df = process_file("examples/test/cnt_test.txt")
    I, Q = get_I_Q(df, time)
    least_Q_score = get_least_Q_score(I, Q, I_threshold)
    exp_score = get_exp_score(I, Q, I_threshold, Q_threshold, Q_weight)
    print(least_Q_score, exp_score)