# Licensed under a 3-clause BSD style license - see LICENSE.rst
from __future__ import (absolute_import, unicode_literals, division,
                        print_function)

import pytest
import numpy as np
from numpy.testing.utils import assert_allclose, assert_array_equal

from ..fitting import LevMarLSQFitter
from ..models import Shift, Rotation2D, Gaussian1D, Identity, Mapping
from ...utils import NumpyRNGContext

try:
    from scipy import optimize  # pylint: disable=W0611
    HAS_SCIPY = True
except ImportError:
    HAS_SCIPY = False


def test_swap_axes():
    x = np.zeros((2, 3))
    y = np.ones((2, 3))

    mapping = Mapping((1, 0))
    assert(mapping(1, 2) == (2.0, 1.0))
    assert(mapping.inverse(2, 1) == (1, 2))
    assert_array_equal(mapping(x, y), (y, x))
    assert_array_equal(mapping.inverse(y, x), (x, y))


def test_duplicate_axes():
    mapping = Mapping((0, 1, 0, 1))
    assert(mapping(1, 2) == (1.0, 2., 1., 2))
    assert(mapping.inverse(1, 2, 1, 2) == (1, 2))
    assert(mapping.inverse.n_inputs == 4)
    assert(mapping.inverse.n_outputs == 2)


def test_drop_axes_1():
    mapping = Mapping((0,), n_inputs=2)
    assert(mapping(1, 2) == (1.))


def test_drop_axes_2():
    mapping = Mapping((1, ))
    assert(mapping(1, 2) == (2.))
    with pytest.raises(NotImplementedError):
        mapping.inverse


def test_drop_axes_3():
    mapping = Mapping((1,), n_inputs=2)
    assert(mapping.n_inputs == 2)
    rotation = Rotation2D(60)
    model = rotation | mapping
    assert_allclose(model(1, 2), 1.86602540378)


def test_identity():
    x = np.zeros((2, 3))
    y = np.ones((2, 3))

    ident1 = Identity(1)
    shift = Shift(1)
    rotation = Rotation2D(angle=60)
    model = ident1 & shift | rotation
    assert_allclose(model(1, 2), (-2.098076211353316, 2.3660254037844393))
    res_x, res_y = model(x, y)
    assert_allclose((res_x, res_y),
                    (np.array([[-1.73205081, -1.73205081, -1.73205081],
                               [-1.73205081, -1.73205081, -1.73205081]]),
                     np.array([[1., 1., 1.],
                               [1., 1., 1.]])))
    assert_allclose(model.inverse(res_x, res_y), (x, y), atol=1.e-10)


# https://github.com/astropy/astropy/pull/6018
@pytest.mark.skipif('not HAS_SCIPY')
def test_fittable_compound():
    m = Identity(1) | Mapping((0, )) | Gaussian1D(1, 5, 4)
    x = np.arange(10)
    y_real = m(x)
    dy = 0.005
    with NumpyRNGContext(1234567):
        n = np.random.normal(0., dy, x.shape)
    y_noisy = y_real + n
    pfit = LevMarLSQFitter()
    new_model = pfit(m, x, y_noisy)
    y_fit = new_model(x)
    assert_allclose(y_fit, y_real, atol=dy)
