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# Licensed under a 3-clause BSD style license - see LICENSE.rst
from __future__ import (absolute_import, division, print_function,
                        unicode_literals)
import numpy as np
from numpy.testing import assert_allclose
from astropy.tests.helper import pytest
from .. import calculate_total_error

SHAPE = (5, 5)
DATAVAL = 2.
DATA = np.ones(SHAPE) * DATAVAL
MASK = np.zeros_like(DATA, dtype=bool)
MASK[2, 2] = True
ERROR = np.ones(SHAPE)
EFFGAIN = np.ones(SHAPE) * DATAVAL
BACKGROUND = np.ones(SHAPE)
WRONG_SHAPE = np.ones((2, 2))


class TestCalculateTotalError(object):
    def test_error_shape(self):
        with pytest.raises(ValueError):
            calculate_total_error(DATA, error=WRONG_SHAPE,
                                  effective_gain=EFFGAIN)

    def test_gain_shape(self):
        with pytest.raises(ValueError):
            calculate_total_error(DATA, error=ERROR,
                                  effective_gain=WRONG_SHAPE)

    @pytest.mark.parametrize('effective_gain', (0, -1))
    def test_gain_le_zero(self, effective_gain):
        with pytest.raises(ValueError):
            calculate_total_error(DATA, error=ERROR,
                                  effective_gain=effective_gain)

    def test_gain_scalar(self):
        error_tot = calculate_total_error(DATA, error=ERROR,
                                          effective_gain=2.)
        assert_allclose(error_tot, np.sqrt(2.) * ERROR)

    def test_gain_array(self):
        error_tot = calculate_total_error(DATA, error=ERROR,
                                          effective_gain=EFFGAIN)
        assert_allclose(error_tot, np.sqrt(2.) * ERROR)