db_file = 'gadb_logics_test.db'


def test_database_logic(seed, testdir):
    from ase.ga.data import PrepareDB
    from ase.ga.data import DataConnection
    from ase.ga.startgenerator import StartGenerator
    from ase.ga.utilities import closest_distances_generator
    from ase.ga import set_raw_score
    import numpy as np
    from ase.build import fcc111
    from ase.constraints import FixAtoms

    # set up the random number generator
    rng = np.random.RandomState(seed)

    slab = fcc111('Au', size=(4, 4, 2), vacuum=10.0, orthogonal=True)
    slab.set_constraint(FixAtoms(mask=slab.positions[:, 2] <= 10.))

    # define the volume in which the adsorbed cluster is optimized
    # the volume is defined by a corner position (p0)
    # and three spanning vectors (v1, v2, v3)
    pos = slab.get_positions()
    cell = slab.get_cell()
    p0 = np.array([0., 0., max(pos[:, 2]) + 2.])
    v1 = cell[0, :] * 0.8
    v2 = cell[1, :] * 0.8
    v3 = cell[2, :]
    v3[2] = 3.

    # define the closest distance between two atoms of a given species
    blmin = closest_distances_generator(atom_numbers=[47, 79],
                                        ratio_of_covalent_radii=0.7)

    # Define the composition of the atoms to optimize
    atom_numbers = 2 * [47] + 2 * [79]

    # create the starting population
    sg = StartGenerator(slab=slab,
                        blocks=atom_numbers,
                        blmin=blmin,
                        box_to_place_in=[p0, [v1, v2, v3]],
                        rng=rng)

    # generate the starting population
    starting_population = [sg.get_new_candidate() for i in range(20)]

    d = PrepareDB(db_file_name=db_file,
                  simulation_cell=slab,
                  stoichiometry=atom_numbers)

    for a in starting_population:
        d.add_unrelaxed_candidate(a)

    # and now for the actual test
    dc = DataConnection(db_file)

    dc.get_slab()
    dc.get_atom_numbers_to_optimize()

    assert dc.get_number_of_unrelaxed_candidates() == 20

    a1 = dc.get_an_unrelaxed_candidate()
    dc.mark_as_queued(a1)

    assert dc.get_number_of_unrelaxed_candidates() == 19
    assert len(dc.get_all_candidates_in_queue()) == 1

    set_raw_score(a1, 0.0)
    dc.add_relaxed_step(a1)

    assert dc.get_number_of_unrelaxed_candidates() == 19
    assert len(dc.get_all_candidates_in_queue()) == 0

    assert len(dc.get_all_relaxed_candidates()) == 1

    a2 = dc.get_an_unrelaxed_candidate()
    dc.mark_as_queued(a2)
    confid = a2.info['confid']
    assert dc.get_all_candidates_in_queue()[0] == confid

    dc.remove_from_queue(confid)
    assert len(dc.get_all_candidates_in_queue()) == 0
