# fmt: off
# type: ignore
from numpy.linalg import norm

from ase.calculators.turbomole import Turbomole
from ase.collections import s22


def test_turbomole_2h2o(turbomole_factory):
    """Water dimer calculation in which each molecule is calculated quantum
    mechanically and the interaction between the molecules is electrostatic.
    The process is repeated until self consitence. """

    def polarization_cycle(partition_1, partition_2, charges_2=None):
        """Performs an iteration of a polarization calculation."""
        properties = {}
        calc = Turbomole(atoms=partition_1, **params)
        if charges_2 is not None:
            calc.embed(charges=charges_2, positions=partition_2.positions)
        properties['e1'] = partition_1.get_potential_energy()
        properties['c1'] = partition_1.get_charges()
        calc = Turbomole(atoms=partition_2, **params)
        calc.embed(charges=properties['c1'], positions=partition_1.positions)
        properties['e2'] = partition_2.get_potential_energy()
        properties['c2'] = partition_2.get_charges()
        return properties

    params = {'esp fit': 'kollman', 'multiplicity': 1}
    dimer = s22['Water_dimer']

    # system partitioning
    part1 = dimer[0:3]
    part2 = dimer[3:6]

    new = polarization_cycle(part1, part2)
    prop = {'e1': [], 'e2': [], 'c1': [], 'c2': []}
    for key in prop:
        prop[key].append(new[key])

    # start values and convergence criteria
    conv = {'e': [1.0], 'c': [1.0]}
    thres = {'e': 1e-4, 'c': 1e-2}
    iteration = 0
    while any(conv[key][-1] > thres[key] for key in conv):
        iteration += 1
        new = polarization_cycle(part1, part2, charges_2=prop['c2'][-1])
        for key in prop:
            prop[key].append(new[key])

        (new1, old1) = (prop['e1'][-1], prop['e1'][-2])
        (new2, old2) = (prop['e2'][-1], prop['e2'][-2])
        conv['e'].append((abs(new1 - old1) + abs(new2 - old2)) /
                         (abs(old1) + abs(old2)))
        (new1, old1) = (prop['c1'][-1], prop['c1'][-2])
        (new2, old2) = (prop['c2'][-1], prop['c2'][-2])
        conv['c'].append((norm(new1 - old1) + norm(new2 - old2)) /
                         (norm(old1) + norm(old2)))
        fmt = ('iteration {0:d}: convergence of energy {1:10e}; '
               'of charges {2:10e}')
        print(fmt.format(iteration, conv['e'][-1], norm(conv['c'][-1])))

    # check the result
    ref = {
        'e1': -2077.7082947500003,
        'e2': -2077.3347674372353,
        'c1': [-0.133033, 0.238218, -0.105186],
        'c2': [-0.844336, 0.422151, 0.422184]
    }

    dev = {}
    for key in ref:
        val = prop[key][-1]
        measurement = val if isinstance(val, float) else norm(val)
        reference = ref[key] if isinstance(ref[key], float) else norm(ref[key])
        dev[key] = (measurement - reference) / reference
        print(f'Deviation of {key} is {dev[key]:10f}')

    # allow deviations of up to 5%
    assert all(dev[key] < 5e-2 for key in dev), 'deviation too large'
