import indiesolver
import numpy as np


def evaluate(solution):
    x = solution["parameters"]

    m = 5
    lamdt = -100.0
    coll = CollGaussRadau_Right(num_nodes=m, tleft=0.0, tright=1.0)
    Q = coll.Qmat[1:, 1:]

    var = [x['x' + str(j)] for j in range(1, m + 1)]

    Qd = np.diag(var)

    R = lamdt * np.linalg.inv(np.eye(m) - lamdt * Qd).dot(Q - Qd)

    obj_val = max(abs(np.linalg.eigvals(R)))

    solution["metrics"] = {}
    solution["metrics"]["rho"] = obj_val
    return solution


# y = [5.8054876, 8.46779587, 17.72188108, 6.75505219, 5.53129906]
y = [1.0, 1.0, 1.0, 1.0, 1.0]
ymax = 20.0
ymin = 0.0
params = {}
params['x1'] = {'type': 'float', 'space': 'decision', 'min': ymin, 'max': ymax, 'init': y[0]}
params['x2'] = {'type': 'float', 'space': 'decision', 'min': ymin, 'max': ymax, 'init': y[1]}
params['x3'] = {'type': 'float', 'space': 'decision', 'min': ymin, 'max': ymax, 'init': y[2]}
params['x4'] = {'type': 'float', 'space': 'decision', 'min': ymin, 'max': ymax, 'init': y[3]}
params['x5'] = {'type': 'float', 'space': 'decision', 'min': ymin, 'max': ymax, 'init': y[4]}

problem = {
    'problem_name': 'Qdelta_target',
    'parameters': params,
    'metrics': {'rho': {'type': 'objective', 'goal': 'minimize'}},
}

worker = indiesolver.indiesolver()
worker.initialize("indiesolver.com", 8080, "dg8f5a0dd9ed")
reply = worker.create_problem(problem)

if reply["status"] != "success":
    print(reply)
    exit()

curr_min = 99
for iteration in range(0, 10000):
    reply = worker.ask_new_solutions(1)
    solutions = {}
    solutions["solutions"] = []
    if reply["status"] == "success":
        for solution in reply["solutions"]:
            solutions["solutions"].append(evaluate(solution))
        worker.tell_metrics(solutions)
        rho = reply["solutions"][0]["metrics"]["rho"]
        curr_min = min(curr_min, rho)
        print(iteration, rho, curr_min)
    else:
        print(reply)
        exit()
