examine_calendar.py

import matplotlib.pyplot as plt
import json
import numpy as np


if __name__ == '__main__':
    scores = dict()
    jsons = list()
    for i in range(8):
        with open(f"calendar_data_{i}.json") as f:
            jsons.append(json.load(f))
    print(len(jsons))
    counter = 0
    for i in range(8):
        for item in jsons[i]:
            for output in item['calendar_outputs']:
                scores[output[0]] = scores.get(output[0], 0) + 1
                counter += 1
    sorted_keys = sorted(list(scores.keys()))
    running_values = [scores[sorted_keys[0]]]
    for i in range(1, len(sorted_keys)):
        running_values.append(running_values[-1] + scores[sorted_keys[0]])
    running_values = np.array(running_values)
    sorted_keys = np.array(sorted_keys)
    plt.plot(sorted_keys, (1.0 - (running_values/running_values[-1])) * counter)
    plt.xlabel("Score")
    plt.ylabel("examples left")
    plt.show()
    # Thresholds:
    # 0.25 = 10% 0.58 = 1% 0.075 = 50%
    # call it 0.25 for now