"""
Optimize a Model
=================================

This example shows how to optimize model parameters to match a chosen statistic
from a reference inventory using PYBOBYQA.
"""

# %%
import numpy as np
from spatiocoexistence import Model, Inventory
from spatiocoexistence.data import inventory_file, parameter_file

# %%
# Initialize the model, the initial inventory is used as reference.
reference_inv = Inventory.from_data(inventory_file)
model = Model(
    initial_inventory=reference_inv,
    parameters=parameter_file,
    threads=4,
)

stat_funcs = [
    (Inventory.get_CI_HS_distribution, Inventory.CI_HS),
]
print(type(stat_funcs))
result = model.optimize_parameters(
    start_params=np.array([0.26]),
    lower=np.array([0.25]),
    upper=np.array([0.27]),
    rhobeg=0.01,
    rhoend=0.001,
    param_names=["mean_reproduction"],
    methods_to_evaluate=stat_funcs,
    stat_indices=[slice(0, 20)],
    n_init=100,
    n_iter=15,
    maxfun=100,
)

print(result)