from __future__ import division, print_function, absolute_import

import numpy as np
from numpy.testing import assert_equal, assert_

from scipy._lib._util import _aligned_zeros


def test__aligned_zeros():
    niter = 10

    def check(shape, dtype, order, align):
        err_msg = repr((shape, dtype, order, align))
        x = _aligned_zeros(shape, dtype, order, align=align)
        if align is None:
            align = np.dtype(dtype).alignment
        assert_equal(x.__array_interface__['data'][0] % align, 0)
        if hasattr(shape, '__len__'):
            assert_equal(x.shape, shape, err_msg)
        else:
            assert_equal(x.shape, (shape,), err_msg)
        assert_equal(x.dtype, dtype)
        if order == "C":
            assert_(x.flags.c_contiguous, err_msg)
        elif order == "F":
            if x.size > 0:
                # Size-0 arrays get invalid flags on Numpy 1.5
                assert_(x.flags.f_contiguous, err_msg)
        elif order is None:
            assert_(x.flags.c_contiguous, err_msg)
        else:
            raise ValueError()

    # try various alignments
    for align in [1, 2, 3, 4, 8, 16, 32, 64, None]:
        for n in [0, 1, 3, 11]:
            for order in ["C", "F", None]:
                for dtype in [np.uint8, np.float64]:
                    for shape in [n, (1,2,3,n)]:
                        for j in range(niter):
                            check(shape, dtype, order, align)