"""unit tests for sparse utility functions"""

from __future__ import division, print_function, absolute_import

import numpy as np
from numpy.testing import assert_equal
from pytest import raises as assert_raises
from scipy.sparse import sputils
from scipy.sparse.sputils import matrix
from scipy._lib._numpy_compat import suppress_warnings


class TestSparseUtils(object):

    def test_upcast(self):
        assert_equal(sputils.upcast('intc'), np.intc)
        assert_equal(sputils.upcast('int32', 'float32'), np.float64)
        assert_equal(sputils.upcast('bool', complex, float), np.complex128)
        assert_equal(sputils.upcast('i', 'd'), np.float64)

    def test_getdtype(self):
        A = np.array([1], dtype='int8')

        assert_equal(sputils.getdtype(None, default=float), float)
        assert_equal(sputils.getdtype(None, a=A), np.int8)

    def test_isscalarlike(self):
        assert_equal(sputils.isscalarlike(3.0), True)
        assert_equal(sputils.isscalarlike(-4), True)
        assert_equal(sputils.isscalarlike(2.5), True)
        assert_equal(sputils.isscalarlike(1 + 3j), True)
        assert_equal(sputils.isscalarlike(np.array(3)), True)
        assert_equal(sputils.isscalarlike("16"), True)

        assert_equal(sputils.isscalarlike(np.array([3])), False)
        assert_equal(sputils.isscalarlike([[3]]), False)
        assert_equal(sputils.isscalarlike((1,)), False)
        assert_equal(sputils.isscalarlike((1, 2)), False)

    def test_isintlike(self):
        assert_equal(sputils.isintlike(-4), True)
        assert_equal(sputils.isintlike(np.array(3)), True)
        assert_equal(sputils.isintlike(np.array([3])), False)
        with suppress_warnings() as sup:
            sup.filter(DeprecationWarning,
                       "Inexact indices into sparse matrices are deprecated")
            assert_equal(sputils.isintlike(3.0), True)

        assert_equal(sputils.isintlike(2.5), False)
        assert_equal(sputils.isintlike(1 + 3j), False)
        assert_equal(sputils.isintlike((1,)), False)
        assert_equal(sputils.isintlike((1, 2)), False)

    def test_isshape(self):
        assert_equal(sputils.isshape((1, 2)), True)
        assert_equal(sputils.isshape((5, 2)), True)

        assert_equal(sputils.isshape((1.5, 2)), False)
        assert_equal(sputils.isshape((2, 2, 2)), False)
        assert_equal(sputils.isshape(([2], 2)), False)
        assert_equal(sputils.isshape((-1, 2), nonneg=False),True)
        assert_equal(sputils.isshape((2, -1), nonneg=False),True)
        assert_equal(sputils.isshape((-1, 2), nonneg=True),False)
        assert_equal(sputils.isshape((2, -1), nonneg=True),False)

    def test_issequence(self):
        assert_equal(sputils.issequence((1,)), True)
        assert_equal(sputils.issequence((1, 2, 3)), True)
        assert_equal(sputils.issequence([1]), True)
        assert_equal(sputils.issequence([1, 2, 3]), True)
        assert_equal(sputils.issequence(np.array([1, 2, 3])), True)

        assert_equal(sputils.issequence(np.array([[1], [2], [3]])), False)
        assert_equal(sputils.issequence(3), False)

    def test_ismatrix(self):
        assert_equal(sputils.ismatrix(((),)), True)
        assert_equal(sputils.ismatrix([[1], [2]]), True)
        assert_equal(sputils.ismatrix(np.arange(3)[None]), True)

        assert_equal(sputils.ismatrix([1, 2]), False)
        assert_equal(sputils.ismatrix(np.arange(3)), False)
        assert_equal(sputils.ismatrix([[[1]]]), False)
        assert_equal(sputils.ismatrix(3), False)

    def test_isdense(self):
        assert_equal(sputils.isdense(np.array([1])), True)
        assert_equal(sputils.isdense(matrix([1])), True)

    def test_validateaxis(self):
        assert_raises(TypeError, sputils.validateaxis, (0, 1))
        assert_raises(TypeError, sputils.validateaxis, 1.5)
        assert_raises(ValueError, sputils.validateaxis, 3)

        # These function calls should not raise errors
        for axis in (-2, -1, 0, 1, None):
            sputils.validateaxis(axis)

    def test_get_index_dtype(self):
        imax = np.iinfo(np.int32).max
        too_big = imax + 1

        # Check that uint32's with no values too large doesn't return
        # int64
        a1 = np.ones(90, dtype='uint32')
        a2 = np.ones(90, dtype='uint32')
        assert_equal(
            np.dtype(sputils.get_index_dtype((a1, a2), check_contents=True)),
            np.dtype('int32')
        )

        # Check that if we can not convert but all values are less than or
        # equal to max that we can just convert to int32
        a1[-1] = imax
        assert_equal(
            np.dtype(sputils.get_index_dtype((a1, a2), check_contents=True)),
            np.dtype('int32')
        )

        # Check that if it can not convert directly and the contents are
        # too large that we return int64
        a1[-1] = too_big
        assert_equal(
            np.dtype(sputils.get_index_dtype((a1, a2), check_contents=True)),
            np.dtype('int64')
        )

        # test that if can not convert and didn't specify to check_contents
        # we return int64
        a1 = np.ones(89, dtype='uint32')
        a2 = np.ones(89, dtype='uint32')
        assert_equal(
            np.dtype(sputils.get_index_dtype((a1, a2))),
            np.dtype('int64')
        )

        # Check that even if we have arrays that can be converted directly
        # that if we specify a maxval directly it takes precedence
        a1 = np.ones(12, dtype='uint32')
        a2 = np.ones(12, dtype='uint32')
        assert_equal(
            np.dtype(sputils.get_index_dtype(
                (a1, a2), maxval=too_big, check_contents=True
            )),
            np.dtype('int64')
        )

        # Check that an array with a too max size and maxval set
        # still returns int64
        a1[-1] = too_big
        assert_equal(
            np.dtype(sputils.get_index_dtype((a1, a2), maxval=too_big)),
            np.dtype('int64')
        )
