# Copyright © 2021 United States Government as represented by the Administrator of the
# National Aeronautics and Space Administration.  All Rights Reserved.

"""
Example performing a sensitivity analysis on a new model.
"""

import numpy as np

# Deriv prog model was selected because the model can be described as x' = x + dx*dt
from progpy.models.thrown_object import ThrownObject


def run_example():
    # Demo model
    # Step 1: Create instance of model
    m = ThrownObject()

    # Step 2: Setup range on parameters considered
    thrower_height_range = np.arange(1.2, 2.1, 0.1)

    # Step 3: Sim for each
    event = "impact"
    eods = np.empty(len(thrower_height_range))
    for i, thrower_height in zip(
        range(len(thrower_height_range)), thrower_height_range
    ):
        m.parameters["thrower_height"] = thrower_height
        simulated_results = m.simulate_to_threshold(events=event, dt=1e-3, save_freq=10)
        eods[i] = simulated_results.times[-1]

    # Step 4: Analysis
    print(
        "For a reasonable range of heights, impact time is between {} and {}".format(
            round(eods[0], 3), round(eods[-1], 3)
        )
    )
    sensitivity = (eods[-1] - eods[0]) / (
        thrower_height_range[-1] - thrower_height_range[0]
    )
    print(
        "  - Average sensitivity: {} s per cm height".format(
            round(sensitivity / 100, 6)
        )
    )
    print("  - It seems impact time is not very sensitive to thrower's height")

    # Now lets repeat for throw speed
    throw_speed_range = np.arange(20, 40, 1)
    eods = np.empty(len(throw_speed_range))
    for i, throw_speed in zip(range(len(throw_speed_range)), throw_speed_range):
        m.parameters["throwing_speed"] = throw_speed
        simulated_results = m.simulate_to_threshold(
            events=event, options={"dt": 1e-3, "save_freq": 10}
        )
        eods[i] = simulated_results.times[-1]

    print(
        "\nFor a reasonable range of throwing speeds, impact time is between {} and {}".format(
            round(eods[0], 3), round(eods[-1], 3)
        )
    )
    sensitivity = (eods[-1] - eods[0]) / (throw_speed_range[-1] - throw_speed_range[0])
    print(
        "  - Average sensitivity: {} s per m/s speed".format(
            round(sensitivity / 100, 6)
        )
    )
    print("  - It seems impact time is much more dependent on throwing speed")


# This allows the module to be executed directly
if __name__ == "__main__":
    run_example()