time_series_test_case.py

import numpy as np


"""In this test case, every test instance is a 28 days by 1 channel array indicating the max temp on a day."""


def input_train_mean(_data):
    """Return overall mean temperature of 14."""
    return 14


def average_temperature_timeseries_with_1_cold_and_1_hot_day(cold_day_index, hot_day_index):
    """Creates a temperature time series of all 14s and a single cold (-2) and hot (30) day."""
    temperature_timeseries = np.expand_dims(np.zeros(28), axis=1) + 14
    temperature_timeseries[hot_day_index] = 30
    temperature_timeseries[cold_day_index] = -2
    return temperature_timeseries


def run_expert_model(data):
    """A simple model that classifies a batch of timeseries.

    All instances with an average above 14 are classified as summer (0) and the rest as winter (1).
    """
    # Make actual decision
    is_summer = np.mean(np.mean(data, axis=1), axis=1) > 14

    # Create the correct output format
    number_of_classes = 2
    number_of_instances = data.shape[0]
    result = np.zeros((number_of_instances, number_of_classes))
    result[is_summer] = [1.0, 0.0]
    result[~is_summer] = [0.0, 1.0]

    return result