from __future__ import division, absolute_import, print_function

import sys, warnings

import numpy as np
from numpy import array, arange, nditer, all
from numpy.compat import asbytes, sixu
from numpy.testing import *



def iter_multi_index(i):
    ret = []
    while not i.finished:
        ret.append(i.multi_index)
        i.iternext()
    return ret

def iter_indices(i):
    ret = []
    while not i.finished:
        ret.append(i.index)
        i.iternext()
    return ret

def iter_iterindices(i):
    ret = []
    while not i.finished:
        ret.append(i.iterindex)
        i.iternext()
    return ret

def test_iter_refcount():
    # Make sure the iterator doesn't leak

    # Basic
    a = arange(6)
    dt = np.dtype('f4').newbyteorder()
    rc_a = sys.getrefcount(a)
    rc_dt = sys.getrefcount(dt)
    it = nditer(a, [],
                [['readwrite','updateifcopy']],
                casting='unsafe',
                op_dtypes=[dt])
    assert_(not it.iterationneedsapi)
    assert_(sys.getrefcount(a) > rc_a)
    assert_(sys.getrefcount(dt) > rc_dt)
    it = None
    assert_equal(sys.getrefcount(a), rc_a)
    assert_equal(sys.getrefcount(dt), rc_dt)

    # With a copy
    a = arange(6, dtype='f4')
    dt = np.dtype('f4')
    rc_a = sys.getrefcount(a)
    rc_dt = sys.getrefcount(dt)
    it = nditer(a, [],
                [['readwrite']],
                op_dtypes=[dt])
    rc2_a = sys.getrefcount(a)
    rc2_dt = sys.getrefcount(dt)
    it2 = it.copy()
    assert_(sys.getrefcount(a) > rc2_a)
    assert_(sys.getrefcount(dt) > rc2_dt)
    it = None
    assert_equal(sys.getrefcount(a), rc2_a)
    assert_equal(sys.getrefcount(dt), rc2_dt)
    it2 = None
    assert_equal(sys.getrefcount(a), rc_a)
    assert_equal(sys.getrefcount(dt), rc_dt)

def test_iter_best_order():
    # The iterator should always find the iteration order
    # with increasing memory addresses

    # Test the ordering for 1-D to 5-D shapes
    for shape in [(5,), (3,4), (2,3,4), (2,3,4,3), (2,3,2,2,3)]:
        a = arange(np.prod(shape))
        # Test each combination of positive and negative strides
        for dirs in range(2**len(shape)):
            dirs_index = [slice(None)]*len(shape)
            for bit in range(len(shape)):
                if ((2**bit)&dirs):
                    dirs_index[bit] = slice(None,None,-1)
            dirs_index = tuple(dirs_index)

            aview = a.reshape(shape)[dirs_index]
            # C-order
            i = nditer(aview, [], [['readonly']])
            assert_equal([x for x in i], a)
            # Fortran-order
            i = nditer(aview.T, [], [['readonly']])
            assert_equal([x for x in i], a)
            # Other order
            if len(shape) > 2:
                i = nditer(aview.swapaxes(0,1), [], [['readonly']])
                assert_equal([x for x in i], a)

def test_iter_c_order():
    # Test forcing C order

    # Test the ordering for 1-D to 5-D shapes
    for shape in [(5,), (3,4), (2,3,4), (2,3,4,3), (2,3,2,2,3)]:
        a = arange(np.prod(shape))
        # Test each combination of positive and negative strides
        for dirs in range(2**len(shape)):
            dirs_index = [slice(None)]*len(shape)
            for bit in range(len(shape)):
                if ((2**bit)&dirs):
                    dirs_index[bit] = slice(None,None,-1)
            dirs_index = tuple(dirs_index)

            aview = a.reshape(shape)[dirs_index]
            # C-order
            i = nditer(aview, order='C')
            assert_equal([x for x in i], aview.ravel(order='C'))
            # Fortran-order
            i = nditer(aview.T, order='C')
            assert_equal([x for x in i], aview.T.ravel(order='C'))
            # Other order
            if len(shape) > 2:
                i = nditer(aview.swapaxes(0,1), order='C')
                assert_equal([x for x in i],
                                    aview.swapaxes(0,1).ravel(order='C'))

def test_iter_f_order():
    # Test forcing F order

    # Test the ordering for 1-D to 5-D shapes
    for shape in [(5,), (3,4), (2,3,4), (2,3,4,3), (2,3,2,2,3)]:
        a = arange(np.prod(shape))
        # Test each combination of positive and negative strides
        for dirs in range(2**len(shape)):
            dirs_index = [slice(None)]*len(shape)
            for bit in range(len(shape)):
                if ((2**bit)&dirs):
                    dirs_index[bit] = slice(None,None,-1)
            dirs_index = tuple(dirs_index)

            aview = a.reshape(shape)[dirs_index]
            # C-order
            i = nditer(aview, order='F')
            assert_equal([x for x in i], aview.ravel(order='F'))
            # Fortran-order
            i = nditer(aview.T, order='F')
            assert_equal([x for x in i], aview.T.ravel(order='F'))
            # Other order
            if len(shape) > 2:
                i = nditer(aview.swapaxes(0,1), order='F')
                assert_equal([x for x in i],
                                    aview.swapaxes(0,1).ravel(order='F'))

def test_iter_c_or_f_order():
    # Test forcing any contiguous (C or F) order

    # Test the ordering for 1-D to 5-D shapes
    for shape in [(5,), (3,4), (2,3,4), (2,3,4,3), (2,3,2,2,3)]:
        a = arange(np.prod(shape))
        # Test each combination of positive and negative strides
        for dirs in range(2**len(shape)):
            dirs_index = [slice(None)]*len(shape)
            for bit in range(len(shape)):
                if ((2**bit)&dirs):
                    dirs_index[bit] = slice(None,None,-1)
            dirs_index = tuple(dirs_index)

            aview = a.reshape(shape)[dirs_index]
            # C-order
            i = nditer(aview, order='A')
            assert_equal([x for x in i], aview.ravel(order='A'))
            # Fortran-order
            i = nditer(aview.T, order='A')
            assert_equal([x for x in i], aview.T.ravel(order='A'))
            # Other order
            if len(shape) > 2:
                i = nditer(aview.swapaxes(0,1), order='A')
                assert_equal([x for x in i],
                                    aview.swapaxes(0,1).ravel(order='A'))

def test_iter_best_order_multi_index_1d():
    # The multi-indices should be correct with any reordering

    a = arange(4)
    # 1D order
    i = nditer(a,['multi_index'],[['readonly']])
    assert_equal(iter_multi_index(i), [(0,),(1,),(2,),(3,)])
    # 1D reversed order
    i = nditer(a[::-1],['multi_index'],[['readonly']])
    assert_equal(iter_multi_index(i), [(3,),(2,),(1,),(0,)])

def test_iter_best_order_multi_index_2d():
    # The multi-indices should be correct with any reordering

    a = arange(6)
    # 2D C-order
    i = nditer(a.reshape(2,3),['multi_index'],[['readonly']])
    assert_equal(iter_multi_index(i), [(0,0),(0,1),(0,2),(1,0),(1,1),(1,2)])
    # 2D Fortran-order
    i = nditer(a.reshape(2,3).copy(order='F'),['multi_index'],[['readonly']])
    assert_equal(iter_multi_index(i), [(0,0),(1,0),(0,1),(1,1),(0,2),(1,2)])
    # 2D reversed C-order
    i = nditer(a.reshape(2,3)[::-1],['multi_index'],[['readonly']])
    assert_equal(iter_multi_index(i), [(1,0),(1,1),(1,2),(0,0),(0,1),(0,2)])
    i = nditer(a.reshape(2,3)[:,::-1],['multi_index'],[['readonly']])
    assert_equal(iter_multi_index(i), [(0,2),(0,1),(0,0),(1,2),(1,1),(1,0)])
    i = nditer(a.reshape(2,3)[::-1,::-1],['multi_index'],[['readonly']])
    assert_equal(iter_multi_index(i), [(1,2),(1,1),(1,0),(0,2),(0,1),(0,0)])
    # 2D reversed Fortran-order
    i = nditer(a.reshape(2,3).copy(order='F')[::-1],['multi_index'],[['readonly']])
    assert_equal(iter_multi_index(i), [(1,0),(0,0),(1,1),(0,1),(1,2),(0,2)])
    i = nditer(a.reshape(2,3).copy(order='F')[:,::-1],
                                                   ['multi_index'],[['readonly']])
    assert_equal(iter_multi_index(i), [(0,2),(1,2),(0,1),(1,1),(0,0),(1,0)])
    i = nditer(a.reshape(2,3).copy(order='F')[::-1,::-1],
                                                   ['multi_index'],[['readonly']])
    assert_equal(iter_multi_index(i), [(1,2),(0,2),(1,1),(0,1),(1,0),(0,0)])

def test_iter_best_order_multi_index_3d():
    # The multi-indices should be correct with any reordering

    a = arange(12)
    # 3D C-order
    i = nditer(a.reshape(2,3,2),['multi_index'],[['readonly']])
    assert_equal(iter_multi_index(i),
                            [(0,0,0),(0,0,1),(0,1,0),(0,1,1),(0,2,0),(0,2,1),
                             (1,0,0),(1,0,1),(1,1,0),(1,1,1),(1,2,0),(1,2,1)])
    # 3D Fortran-order
    i = nditer(a.reshape(2,3,2).copy(order='F'),['multi_index'],[['readonly']])
    assert_equal(iter_multi_index(i),
                            [(0,0,0),(1,0,0),(0,1,0),(1,1,0),(0,2,0),(1,2,0),
                             (0,0,1),(1,0,1),(0,1,1),(1,1,1),(0,2,1),(1,2,1)])
    # 3D reversed C-order
    i = nditer(a.reshape(2,3,2)[::-1],['multi_index'],[['readonly']])
    assert_equal(iter_multi_index(i),
                            [(1,0,0),(1,0,1),(1,1,0),(1,1,1),(1,2,0),(1,2,1),
                             (0,0,0),(0,0,1),(0,1,0),(0,1,1),(0,2,0),(0,2,1)])
    i = nditer(a.reshape(2,3,2)[:,::-1],['multi_index'],[['readonly']])
    assert_equal(iter_multi_index(i),
                            [(0,2,0),(0,2,1),(0,1,0),(0,1,1),(0,0,0),(0,0,1),
                             (1,2,0),(1,2,1),(1,1,0),(1,1,1),(1,0,0),(1,0,1)])
    i = nditer(a.reshape(2,3,2)[:,:,::-1],['multi_index'],[['readonly']])
    assert_equal(iter_multi_index(i),
                            [(0,0,1),(0,0,0),(0,1,1),(0,1,0),(0,2,1),(0,2,0),
                             (1,0,1),(1,0,0),(1,1,1),(1,1,0),(1,2,1),(1,2,0)])
    # 3D reversed Fortran-order
    i = nditer(a.reshape(2,3,2).copy(order='F')[::-1],
                                                    ['multi_index'],[['readonly']])
    assert_equal(iter_multi_index(i),
                            [(1,0,0),(0,0,0),(1,1,0),(0,1,0),(1,2,0),(0,2,0),
                             (1,0,1),(0,0,1),(1,1,1),(0,1,1),(1,2,1),(0,2,1)])
    i = nditer(a.reshape(2,3,2).copy(order='F')[:,::-1],
                                                    ['multi_index'],[['readonly']])
    assert_equal(iter_multi_index(i),
                            [(0,2,0),(1,2,0),(0,1,0),(1,1,0),(0,0,0),(1,0,0),
                             (0,2,1),(1,2,1),(0,1,1),(1,1,1),(0,0,1),(1,0,1)])
    i = nditer(a.reshape(2,3,2).copy(order='F')[:,:,::-1],
                                                    ['multi_index'],[['readonly']])
    assert_equal(iter_multi_index(i),
                            [(0,0,1),(1,0,1),(0,1,1),(1,1,1),(0,2,1),(1,2,1),
                             (0,0,0),(1,0,0),(0,1,0),(1,1,0),(0,2,0),(1,2,0)])

def test_iter_best_order_c_index_1d():
    # The C index should be correct with any reordering

    a = arange(4)
    # 1D order
    i = nditer(a,['c_index'],[['readonly']])
    assert_equal(iter_indices(i), [0,1,2,3])
    # 1D reversed order
    i = nditer(a[::-1],['c_index'],[['readonly']])
    assert_equal(iter_indices(i), [3,2,1,0])

def test_iter_best_order_c_index_2d():
    # The C index should be correct with any reordering

    a = arange(6)
    # 2D C-order
    i = nditer(a.reshape(2,3),['c_index'],[['readonly']])
    assert_equal(iter_indices(i), [0,1,2,3,4,5])
    # 2D Fortran-order
    i = nditer(a.reshape(2,3).copy(order='F'),
                                    ['c_index'],[['readonly']])
    assert_equal(iter_indices(i), [0,3,1,4,2,5])
    # 2D reversed C-order
    i = nditer(a.reshape(2,3)[::-1],['c_index'],[['readonly']])
    assert_equal(iter_indices(i), [3,4,5,0,1,2])
    i = nditer(a.reshape(2,3)[:,::-1],['c_index'],[['readonly']])
    assert_equal(iter_indices(i), [2,1,0,5,4,3])
    i = nditer(a.reshape(2,3)[::-1,::-1],['c_index'],[['readonly']])
    assert_equal(iter_indices(i), [5,4,3,2,1,0])
    # 2D reversed Fortran-order
    i = nditer(a.reshape(2,3).copy(order='F')[::-1],
                                    ['c_index'],[['readonly']])
    assert_equal(iter_indices(i), [3,0,4,1,5,2])
    i = nditer(a.reshape(2,3).copy(order='F')[:,::-1],
                                    ['c_index'],[['readonly']])
    assert_equal(iter_indices(i), [2,5,1,4,0,3])
    i = nditer(a.reshape(2,3).copy(order='F')[::-1,::-1],
                                    ['c_index'],[['readonly']])
    assert_equal(iter_indices(i), [5,2,4,1,3,0])

def test_iter_best_order_c_index_3d():
    # The C index should be correct with any reordering

    a = arange(12)
    # 3D C-order
    i = nditer(a.reshape(2,3,2),['c_index'],[['readonly']])
    assert_equal(iter_indices(i),
                            [0,1,2,3,4,5,6,7,8,9,10,11])
    # 3D Fortran-order
    i = nditer(a.reshape(2,3,2).copy(order='F'),
                                    ['c_index'],[['readonly']])
    assert_equal(iter_indices(i),
                            [0,6,2,8,4,10,1,7,3,9,5,11])
    # 3D reversed C-order
    i = nditer(a.reshape(2,3,2)[::-1],['c_index'],[['readonly']])
    assert_equal(iter_indices(i),
                            [6,7,8,9,10,11,0,1,2,3,4,5])
    i = nditer(a.reshape(2,3,2)[:,::-1],['c_index'],[['readonly']])
    assert_equal(iter_indices(i),
                            [4,5,2,3,0,1,10,11,8,9,6,7])
    i = nditer(a.reshape(2,3,2)[:,:,::-1],['c_index'],[['readonly']])
    assert_equal(iter_indices(i),
                            [1,0,3,2,5,4,7,6,9,8,11,10])
    # 3D reversed Fortran-order
    i = nditer(a.reshape(2,3,2).copy(order='F')[::-1],
                                    ['c_index'],[['readonly']])
    assert_equal(iter_indices(i),
                            [6,0,8,2,10,4,7,1,9,3,11,5])
    i = nditer(a.reshape(2,3,2).copy(order='F')[:,::-1],
                                    ['c_index'],[['readonly']])
    assert_equal(iter_indices(i),
                            [4,10,2,8,0,6,5,11,3,9,1,7])
    i = nditer(a.reshape(2,3,2).copy(order='F')[:,:,::-1],
                                    ['c_index'],[['readonly']])
    assert_equal(iter_indices(i),
                            [1,7,3,9,5,11,0,6,2,8,4,10])

def test_iter_best_order_f_index_1d():
    # The Fortran index should be correct with any reordering

    a = arange(4)
    # 1D order
    i = nditer(a,['f_index'],[['readonly']])
    assert_equal(iter_indices(i), [0,1,2,3])
    # 1D reversed order
    i = nditer(a[::-1],['f_index'],[['readonly']])
    assert_equal(iter_indices(i), [3,2,1,0])

def test_iter_best_order_f_index_2d():
    # The Fortran index should be correct with any reordering

    a = arange(6)
    # 2D C-order
    i = nditer(a.reshape(2,3),['f_index'],[['readonly']])
    assert_equal(iter_indices(i), [0,2,4,1,3,5])
    # 2D Fortran-order
    i = nditer(a.reshape(2,3).copy(order='F'),
                                    ['f_index'],[['readonly']])
    assert_equal(iter_indices(i), [0,1,2,3,4,5])
    # 2D reversed C-order
    i = nditer(a.reshape(2,3)[::-1],['f_index'],[['readonly']])
    assert_equal(iter_indices(i), [1,3,5,0,2,4])
    i = nditer(a.reshape(2,3)[:,::-1],['f_index'],[['readonly']])
    assert_equal(iter_indices(i), [4,2,0,5,3,1])
    i = nditer(a.reshape(2,3)[::-1,::-1],['f_index'],[['readonly']])
    assert_equal(iter_indices(i), [5,3,1,4,2,0])
    # 2D reversed Fortran-order
    i = nditer(a.reshape(2,3).copy(order='F')[::-1],
                                    ['f_index'],[['readonly']])
    assert_equal(iter_indices(i), [1,0,3,2,5,4])
    i = nditer(a.reshape(2,3).copy(order='F')[:,::-1],
                                    ['f_index'],[['readonly']])
    assert_equal(iter_indices(i), [4,5,2,3,0,1])
    i = nditer(a.reshape(2,3).copy(order='F')[::-1,::-1],
                                    ['f_index'],[['readonly']])
    assert_equal(iter_indices(i), [5,4,3,2,1,0])

def test_iter_best_order_f_index_3d():
    # The Fortran index should be correct with any reordering

    a = arange(12)
    # 3D C-order
    i = nditer(a.reshape(2,3,2),['f_index'],[['readonly']])
    assert_equal(iter_indices(i),
                            [0,6,2,8,4,10,1,7,3,9,5,11])
    # 3D Fortran-order
    i = nditer(a.reshape(2,3,2).copy(order='F'),
                                    ['f_index'],[['readonly']])
    assert_equal(iter_indices(i),
                            [0,1,2,3,4,5,6,7,8,9,10,11])
    # 3D reversed C-order
    i = nditer(a.reshape(2,3,2)[::-1],['f_index'],[['readonly']])
    assert_equal(iter_indices(i),
                            [1,7,3,9,5,11,0,6,2,8,4,10])
    i = nditer(a.reshape(2,3,2)[:,::-1],['f_index'],[['readonly']])
    assert_equal(iter_indices(i),
                            [4,10,2,8,0,6,5,11,3,9,1,7])
    i = nditer(a.reshape(2,3,2)[:,:,::-1],['f_index'],[['readonly']])
    assert_equal(iter_indices(i),
                            [6,0,8,2,10,4,7,1,9,3,11,5])
    # 3D reversed Fortran-order
    i = nditer(a.reshape(2,3,2).copy(order='F')[::-1],
                                    ['f_index'],[['readonly']])
    assert_equal(iter_indices(i),
                            [1,0,3,2,5,4,7,6,9,8,11,10])
    i = nditer(a.reshape(2,3,2).copy(order='F')[:,::-1],
                                    ['f_index'],[['readonly']])
    assert_equal(iter_indices(i),
                            [4,5,2,3,0,1,10,11,8,9,6,7])
    i = nditer(a.reshape(2,3,2).copy(order='F')[:,:,::-1],
                                    ['f_index'],[['readonly']])
    assert_equal(iter_indices(i),
                            [6,7,8,9,10,11,0,1,2,3,4,5])

def test_iter_no_inner_full_coalesce():
    # Check no_inner iterators which coalesce into a single inner loop

    for shape in [(5,), (3,4), (2,3,4), (2,3,4,3), (2,3,2,2,3)]:
        size = np.prod(shape)
        a = arange(size)
        # Test each combination of forward and backwards indexing
        for dirs in range(2**len(shape)):
            dirs_index = [slice(None)]*len(shape)
            for bit in range(len(shape)):
                if ((2**bit)&dirs):
                    dirs_index[bit] = slice(None,None,-1)
            dirs_index = tuple(dirs_index)

            aview = a.reshape(shape)[dirs_index]
            # C-order
            i = nditer(aview, ['external_loop'], [['readonly']])
            assert_equal(i.ndim, 1)
            assert_equal(i[0].shape, (size,))
            # Fortran-order
            i = nditer(aview.T, ['external_loop'], [['readonly']])
            assert_equal(i.ndim, 1)
            assert_equal(i[0].shape, (size,))
            # Other order
            if len(shape) > 2:
                i = nditer(aview.swapaxes(0,1),
                                    ['external_loop'], [['readonly']])
                assert_equal(i.ndim, 1)
                assert_equal(i[0].shape, (size,))

def test_iter_no_inner_dim_coalescing():
    # Check no_inner iterators whose dimensions may not coalesce completely

    # Skipping the last element in a dimension prevents coalescing
    # with the next-bigger dimension
    a = arange(24).reshape(2,3,4)[:,:,:-1]
    i = nditer(a, ['external_loop'], [['readonly']])
    assert_equal(i.ndim, 2)
    assert_equal(i[0].shape, (3,))
    a = arange(24).reshape(2,3,4)[:,:-1,:]
    i = nditer(a, ['external_loop'], [['readonly']])
    assert_equal(i.ndim, 2)
    assert_equal(i[0].shape, (8,))
    a = arange(24).reshape(2,3,4)[:-1,:,:]
    i = nditer(a, ['external_loop'], [['readonly']])
    assert_equal(i.ndim, 1)
    assert_equal(i[0].shape, (12,))

    # Even with lots of 1-sized dimensions, should still coalesce
    a = arange(24).reshape(1,1,2,1,1,3,1,1,4,1,1)
    i = nditer(a, ['external_loop'], [['readonly']])
    assert_equal(i.ndim, 1)
    assert_equal(i[0].shape, (24,))

def test_iter_dim_coalescing():
    # Check that the correct number of dimensions are coalesced

    # Tracking a multi-index disables coalescing
    a = arange(24).reshape(2,3,4)
    i = nditer(a, ['multi_index'], [['readonly']])
    assert_equal(i.ndim, 3)

    # A tracked index can allow coalescing if it's compatible with the array
    a3d = arange(24).reshape(2,3,4)
    i = nditer(a3d, ['c_index'], [['readonly']])
    assert_equal(i.ndim, 1)
    i = nditer(a3d.swapaxes(0,1), ['c_index'], [['readonly']])
    assert_equal(i.ndim, 3)
    i = nditer(a3d.T, ['c_index'], [['readonly']])
    assert_equal(i.ndim, 3)
    i = nditer(a3d.T, ['f_index'], [['readonly']])
    assert_equal(i.ndim, 1)
    i = nditer(a3d.T.swapaxes(0,1), ['f_index'], [['readonly']])
    assert_equal(i.ndim, 3)

    # When C or F order is forced, coalescing may still occur
    a3d = arange(24).reshape(2,3,4)
    i = nditer(a3d, order='C')
    assert_equal(i.ndim, 1)
    i = nditer(a3d.T, order='C')
    assert_equal(i.ndim, 3)
    i = nditer(a3d, order='F')
    assert_equal(i.ndim, 3)
    i = nditer(a3d.T, order='F')
    assert_equal(i.ndim, 1)
    i = nditer(a3d, order='A')
    assert_equal(i.ndim, 1)
    i = nditer(a3d.T, order='A')
    assert_equal(i.ndim, 1)

def test_iter_broadcasting():
    # Standard NumPy broadcasting rules

    # 1D with scalar
    i = nditer([arange(6), np.int32(2)], ['multi_index'], [['readonly']]*2)
    assert_equal(i.itersize, 6)
    assert_equal(i.shape, (6,))

    # 2D with scalar
    i = nditer([arange(6).reshape(2,3), np.int32(2)],
                        ['multi_index'], [['readonly']]*2)
    assert_equal(i.itersize, 6)
    assert_equal(i.shape, (2,3))
    # 2D with 1D
    i = nditer([arange(6).reshape(2,3), arange(3)],
                        ['multi_index'], [['readonly']]*2)
    assert_equal(i.itersize, 6)
    assert_equal(i.shape, (2,3))
    i = nditer([arange(2).reshape(2,1), arange(3)],
                        ['multi_index'], [['readonly']]*2)
    assert_equal(i.itersize, 6)
    assert_equal(i.shape, (2,3))
    # 2D with 2D
    i = nditer([arange(2).reshape(2,1), arange(3).reshape(1,3)],
                        ['multi_index'], [['readonly']]*2)
    assert_equal(i.itersize, 6)
    assert_equal(i.shape, (2,3))

    # 3D with scalar
    i = nditer([np.int32(2), arange(24).reshape(4,2,3)],
                        ['multi_index'], [['readonly']]*2)
    assert_equal(i.itersize, 24)
    assert_equal(i.shape, (4,2,3))
    # 3D with 1D
    i = nditer([arange(3), arange(24).reshape(4,2,3)],
                        ['multi_index'], [['readonly']]*2)
    assert_equal(i.itersize, 24)
    assert_equal(i.shape, (4,2,3))
    i = nditer([arange(3), arange(8).reshape(4,2,1)],
                        ['multi_index'], [['readonly']]*2)
    assert_equal(i.itersize, 24)
    assert_equal(i.shape, (4,2,3))
    # 3D with 2D
    i = nditer([arange(6).reshape(2,3), arange(24).reshape(4,2,3)],
                        ['multi_index'], [['readonly']]*2)
    assert_equal(i.itersize, 24)
    assert_equal(i.shape, (4,2,3))
    i = nditer([arange(2).reshape(2,1), arange(24).reshape(4,2,3)],
                        ['multi_index'], [['readonly']]*2)
    assert_equal(i.itersize, 24)
    assert_equal(i.shape, (4,2,3))
    i = nditer([arange(3).reshape(1,3), arange(8).reshape(4,2,1)],
                        ['multi_index'], [['readonly']]*2)
    assert_equal(i.itersize, 24)
    assert_equal(i.shape, (4,2,3))
    # 3D with 3D
    i = nditer([arange(2).reshape(1,2,1), arange(3).reshape(1,1,3),
                        arange(4).reshape(4,1,1)],
                        ['multi_index'], [['readonly']]*3)
    assert_equal(i.itersize, 24)
    assert_equal(i.shape, (4,2,3))
    i = nditer([arange(6).reshape(1,2,3), arange(4).reshape(4,1,1)],
                        ['multi_index'], [['readonly']]*2)
    assert_equal(i.itersize, 24)
    assert_equal(i.shape, (4,2,3))
    i = nditer([arange(24).reshape(4,2,3), arange(12).reshape(4,1,3)],
                        ['multi_index'], [['readonly']]*2)
    assert_equal(i.itersize, 24)
    assert_equal(i.shape, (4,2,3))

def test_iter_itershape():
    # Check that allocated outputs work with a specified shape
    a = np.arange(6, dtype='i2').reshape(2,3)
    i = nditer([a, None], [], [['readonly'], ['writeonly','allocate']],
                            op_axes=[[0,1,None], None],
                            itershape=(-1,-1,4))
    assert_equal(i.operands[1].shape, (2,3,4))
    assert_equal(i.operands[1].strides, (24,8,2))

    i = nditer([a.T, None], [], [['readonly'], ['writeonly','allocate']],
                            op_axes=[[0,1,None], None],
                            itershape=(-1,-1,4))
    assert_equal(i.operands[1].shape, (3,2,4))
    assert_equal(i.operands[1].strides, (8,24,2))

    i = nditer([a.T, None], [], [['readonly'], ['writeonly','allocate']],
                            order='F',
                            op_axes=[[0,1,None], None],
                            itershape=(-1,-1,4))
    assert_equal(i.operands[1].shape, (3,2,4))
    assert_equal(i.operands[1].strides, (2,6,12))

    # If we specify 1 in the itershape, it shouldn't allow broadcasting
    # of that dimension to a bigger value
    assert_raises(ValueError, nditer, [a, None], [],
                            [['readonly'], ['writeonly','allocate']],
                            op_axes=[[0,1,None], None],
                            itershape=(-1,1,4))
    # Test bug that for no op_axes but itershape, they are NULLed correctly
    i = np.nditer([np.ones(2), None, None], itershape=(2,))

def test_iter_broadcasting_errors():
    # Check that errors are thrown for bad broadcasting shapes

    # 1D with 1D
    assert_raises(ValueError, nditer, [arange(2), arange(3)],
                    [], [['readonly']]*2)
    # 2D with 1D
    assert_raises(ValueError, nditer,
                    [arange(6).reshape(2,3), arange(2)],
                    [], [['readonly']]*2)
    # 2D with 2D
    assert_raises(ValueError, nditer,
                    [arange(6).reshape(2,3), arange(9).reshape(3,3)],
                    [], [['readonly']]*2)
    assert_raises(ValueError, nditer,
                    [arange(6).reshape(2,3), arange(4).reshape(2,2)],
                    [], [['readonly']]*2)
    # 3D with 3D
    assert_raises(ValueError, nditer,
                    [arange(36).reshape(3,3,4), arange(24).reshape(2,3,4)],
                    [], [['readonly']]*2)
    assert_raises(ValueError, nditer,
                    [arange(8).reshape(2,4,1), arange(24).reshape(2,3,4)],
                    [], [['readonly']]*2)

    # Verify that the error message mentions the right shapes
    try:
        i = nditer([arange(2).reshape(1,2,1),
                     arange(3).reshape(1,3),
                     arange(6).reshape(2,3)],
                    [],
                    [['readonly'], ['readonly'], ['writeonly','no_broadcast']])
        assert_(False, 'Should have raised a broadcast error')
    except ValueError as e:
        msg = str(e)
        # The message should contain the shape of the 3rd operand
        assert_(msg.find('(2,3)') >= 0,
                'Message "%s" doesn\'t contain operand shape (2,3)' % msg)
        # The message should contain the broadcast shape
        assert_(msg.find('(1,2,3)') >= 0,
                'Message "%s" doesn\'t contain broadcast shape (1,2,3)' % msg)

    try:
        i = nditer([arange(6).reshape(2,3), arange(2)], [],
                    [['readonly'],['readonly']],
                    op_axes=[[0,1], [0,np.newaxis]],
                    itershape=(4,3))
        assert_(False, 'Should have raised a broadcast error')
    except ValueError as e:
        msg = str(e)
        # The message should contain "shape->remappedshape" for each operand
        assert_(msg.find('(2,3)->(2,3)') >= 0,
            'Message "%s" doesn\'t contain operand shape (2,3)->(2,3)' % msg)
        assert_(msg.find('(2)->(2,newaxis)') >= 0,
                ('Message "%s" doesn\'t contain remapped operand shape' +
                '(2)->(2,newaxis)') % msg)
        # The message should contain the itershape parameter
        assert_(msg.find('(4,3)') >= 0,
                'Message "%s" doesn\'t contain itershape parameter (4,3)' % msg)

    try:
        i = nditer([np.zeros((2,1,1)), np.zeros((2,))],
                    [],
                    [['writeonly','no_broadcast'], ['readonly']])
        assert_(False, 'Should have raised a broadcast error')
    except ValueError as e:
        msg = str(e)
        # The message should contain the shape of the bad operand
        assert_(msg.find('(2,1,1)') >= 0,
            'Message "%s" doesn\'t contain operand shape (2,1,1)' % msg)
        # The message should contain the broadcast shape
        assert_(msg.find('(2,1,2)') >= 0,
                'Message "%s" doesn\'t contain the broadcast shape (2,1,2)' % msg)

def test_iter_flags_errors():
    # Check that bad combinations of flags produce errors

    a = arange(6)

    # Not enough operands
    assert_raises(ValueError, nditer, [], [], [])
    # Too many operands
    assert_raises(ValueError, nditer, [a]*100, [], [['readonly']]*100)
    # Bad global flag
    assert_raises(ValueError, nditer, [a], ['bad flag'], [['readonly']])
    # Bad op flag
    assert_raises(ValueError, nditer, [a], [], [['readonly','bad flag']])
    # Bad order parameter
    assert_raises(ValueError, nditer, [a], [], [['readonly']], order='G')
    # Bad casting parameter
    assert_raises(ValueError, nditer, [a], [], [['readonly']], casting='noon')
    # op_flags must match ops
    assert_raises(ValueError, nditer, [a]*3, [], [['readonly']]*2)
    # Cannot track both a C and an F index
    assert_raises(ValueError, nditer, a,
                ['c_index','f_index'], [['readonly']])
    # Inner iteration and multi-indices/indices are incompatible
    assert_raises(ValueError, nditer, a,
                ['external_loop','multi_index'], [['readonly']])
    assert_raises(ValueError, nditer, a,
                ['external_loop','c_index'], [['readonly']])
    assert_raises(ValueError, nditer, a,
                ['external_loop','f_index'], [['readonly']])
    # Must specify exactly one of readwrite/readonly/writeonly per operand
    assert_raises(ValueError, nditer, a, [], [[]])
    assert_raises(ValueError, nditer, a, [], [['readonly','writeonly']])
    assert_raises(ValueError, nditer, a, [], [['readonly','readwrite']])
    assert_raises(ValueError, nditer, a, [], [['writeonly','readwrite']])
    assert_raises(ValueError, nditer, a,
                [], [['readonly','writeonly','readwrite']])
    # Python scalars are always readonly
    assert_raises(TypeError, nditer, 1.5, [], [['writeonly']])
    assert_raises(TypeError, nditer, 1.5, [], [['readwrite']])
    # Array scalars are always readonly
    assert_raises(TypeError, nditer, np.int32(1), [], [['writeonly']])
    assert_raises(TypeError, nditer, np.int32(1), [], [['readwrite']])
    # Check readonly array
    a.flags.writeable = False
    assert_raises(ValueError, nditer, a, [], [['writeonly']])
    assert_raises(ValueError, nditer, a, [], [['readwrite']])
    a.flags.writeable = True
    # Multi-indices available only with the multi_index flag
    i = nditer(arange(6), [], [['readonly']])
    assert_raises(ValueError, lambda i:i.multi_index, i)
    # Index available only with an index flag
    assert_raises(ValueError, lambda i:i.index, i)
    # GotoCoords and GotoIndex incompatible with buffering or no_inner
    def assign_multi_index(i):
        i.multi_index = (0,)
    def assign_index(i):
        i.index = 0
    def assign_iterindex(i):
        i.iterindex = 0;
    def assign_iterrange(i):
        i.iterrange = (0,1);
    i = nditer(arange(6), ['external_loop'])
    assert_raises(ValueError, assign_multi_index, i)
    assert_raises(ValueError, assign_index, i)
    assert_raises(ValueError, assign_iterindex, i)
    assert_raises(ValueError, assign_iterrange, i)
    i = nditer(arange(6), ['buffered'])
    assert_raises(ValueError, assign_multi_index, i)
    assert_raises(ValueError, assign_index, i)
    assert_raises(ValueError, assign_iterrange, i)
    # Can't iterate if size is zero
    assert_raises(ValueError, nditer, np.array([]))

def test_iter_slice():
    a, b, c = np.arange(3), np.arange(3), np.arange(3.)
    i = nditer([a,b,c], [], ['readwrite'])
    i[0:2] = (3,3)
    assert_equal(a, [3,1,2])
    assert_equal(b, [3,1,2])
    assert_equal(c, [0,1,2])
    i[1] = 12
    assert_equal(i[0:2], [3,12])

def test_iter_nbo_align_contig():
    # Check that byte order, alignment, and contig changes work

    # Byte order change by requesting a specific dtype
    a = np.arange(6, dtype='f4')
    au = a.byteswap().newbyteorder()
    assert_(a.dtype.byteorder != au.dtype.byteorder)
    i = nditer(au, [], [['readwrite','updateifcopy']],
                        casting='equiv',
                        op_dtypes=[np.dtype('f4')])
    assert_equal(i.dtypes[0].byteorder, a.dtype.byteorder)
    assert_equal(i.operands[0].dtype.byteorder, a.dtype.byteorder)
    assert_equal(i.operands[0], a)
    i.operands[0][:] = 2
    i = None
    assert_equal(au, [2]*6)

    # Byte order change by requesting NBO
    a = np.arange(6, dtype='f4')
    au = a.byteswap().newbyteorder()
    assert_(a.dtype.byteorder != au.dtype.byteorder)
    i = nditer(au, [], [['readwrite','updateifcopy','nbo']], casting='equiv')
    assert_equal(i.dtypes[0].byteorder, a.dtype.byteorder)
    assert_equal(i.operands[0].dtype.byteorder, a.dtype.byteorder)
    assert_equal(i.operands[0], a)
    i.operands[0][:] = 2
    i = None
    assert_equal(au, [2]*6)

    # Unaligned input
    a = np.zeros((6*4+1,), dtype='i1')[1:]
    a.dtype = 'f4'
    a[:] = np.arange(6, dtype='f4')
    assert_(not a.flags.aligned)
    # Without 'aligned', shouldn't copy
    i = nditer(a, [], [['readonly']])
    assert_(not i.operands[0].flags.aligned)
    assert_equal(i.operands[0], a);
    # With 'aligned', should make a copy
    i = nditer(a, [], [['readwrite','updateifcopy','aligned']])
    assert_(i.operands[0].flags.aligned)
    assert_equal(i.operands[0], a);
    i.operands[0][:] = 3
    i = None
    assert_equal(a, [3]*6)

    # Discontiguous input
    a = arange(12)
    # If it is contiguous, shouldn't copy
    i = nditer(a[:6], [], [['readonly']])
    assert_(i.operands[0].flags.contiguous)
    assert_equal(i.operands[0], a[:6]);
    # If it isn't contiguous, should buffer
    i = nditer(a[::2], ['buffered','external_loop'],
                        [['readonly','contig']],
                        buffersize=10)
    assert_(i[0].flags.contiguous)
    assert_equal(i[0], a[::2])

def test_iter_array_cast():
    # Check that arrays are cast as requested

    # No cast 'f4' -> 'f4'
    a = np.arange(6, dtype='f4').reshape(2,3)
    i = nditer(a, [], [['readwrite']], op_dtypes=[np.dtype('f4')])
    assert_equal(i.operands[0], a)
    assert_equal(i.operands[0].dtype, np.dtype('f4'))

    # Byte-order cast '<f4' -> '>f4'
    a = np.arange(6, dtype='<f4').reshape(2,3)
    i = nditer(a, [], [['readwrite','updateifcopy']],
            casting='equiv',
            op_dtypes=[np.dtype('>f4')])
    assert_equal(i.operands[0], a)
    assert_equal(i.operands[0].dtype, np.dtype('>f4'))

    # Safe case 'f4' -> 'f8'
    a = np.arange(24, dtype='f4').reshape(2,3,4).swapaxes(1,2)
    i = nditer(a, [], [['readonly','copy']],
            casting='safe',
            op_dtypes=[np.dtype('f8')])
    assert_equal(i.operands[0], a)
    assert_equal(i.operands[0].dtype, np.dtype('f8'))
    # The memory layout of the temporary should match a (a is (48,4,16))
    # except negative strides get flipped to positive strides.
    assert_equal(i.operands[0].strides, (96,8,32))
    a = a[::-1,:,::-1]
    i = nditer(a, [], [['readonly','copy']],
            casting='safe',
            op_dtypes=[np.dtype('f8')])
    assert_equal(i.operands[0], a)
    assert_equal(i.operands[0].dtype, np.dtype('f8'))
    assert_equal(i.operands[0].strides, (96,8,32))

    # Same-kind cast 'f8' -> 'f4' -> 'f8'
    a = np.arange(24, dtype='f8').reshape(2,3,4).T
    i = nditer(a, [],
            [['readwrite','updateifcopy']],
            casting='same_kind',
            op_dtypes=[np.dtype('f4')])
    assert_equal(i.operands[0], a)
    assert_equal(i.operands[0].dtype, np.dtype('f4'))
    assert_equal(i.operands[0].strides, (4, 16, 48))
    # Check that UPDATEIFCOPY is activated
    i.operands[0][2,1,1] = -12.5
    assert_(a[2,1,1] != -12.5)
    i = None
    assert_equal(a[2,1,1], -12.5)

    a = np.arange(6, dtype='i4')[::-2]
    i = nditer(a, [],
            [['writeonly','updateifcopy']],
            casting='unsafe',
            op_dtypes=[np.dtype('f4')])
    assert_equal(i.operands[0].dtype, np.dtype('f4'))
    # Even though the stride was negative in 'a', it
    # becomes positive in the temporary
    assert_equal(i.operands[0].strides, (4,))
    i.operands[0][:] = [1,2,3]
    i = None
    assert_equal(a, [1,2,3])

def test_iter_array_cast_errors():
    # Check that invalid casts are caught

    # Need to enable copying for casts to occur
    assert_raises(TypeError, nditer, arange(2,dtype='f4'), [],
                [['readonly']], op_dtypes=[np.dtype('f8')])
    # Also need to allow casting for casts to occur
    assert_raises(TypeError, nditer, arange(2,dtype='f4'), [],
                [['readonly','copy']], casting='no',
                op_dtypes=[np.dtype('f8')])
    assert_raises(TypeError, nditer, arange(2,dtype='f4'), [],
                [['readonly','copy']], casting='equiv',
                op_dtypes=[np.dtype('f8')])
    assert_raises(TypeError, nditer, arange(2,dtype='f8'), [],
                [['writeonly','updateifcopy']],
                casting='no',
                op_dtypes=[np.dtype('f4')])
    assert_raises(TypeError, nditer, arange(2,dtype='f8'), [],
                [['writeonly','updateifcopy']],
                casting='equiv',
                op_dtypes=[np.dtype('f4')])
    # '<f4' -> '>f4' should not work with casting='no'
    assert_raises(TypeError, nditer, arange(2,dtype='<f4'), [],
                [['readonly','copy']], casting='no',
                op_dtypes=[np.dtype('>f4')])
    # 'f4' -> 'f8' is a safe cast, but 'f8' -> 'f4' isn't
    assert_raises(TypeError, nditer, arange(2,dtype='f4'), [],
                [['readwrite','updateifcopy']],
                casting='safe',
                op_dtypes=[np.dtype('f8')])
    assert_raises(TypeError, nditer, arange(2,dtype='f8'), [],
                [['readwrite','updateifcopy']],
                casting='safe',
                op_dtypes=[np.dtype('f4')])
    # 'f4' -> 'i4' is neither a safe nor a same-kind cast
    assert_raises(TypeError, nditer, arange(2,dtype='f4'), [],
                [['readonly','copy']],
                casting='same_kind',
                op_dtypes=[np.dtype('i4')])
    assert_raises(TypeError, nditer, arange(2,dtype='i4'), [],
                [['writeonly','updateifcopy']],
                casting='same_kind',
                op_dtypes=[np.dtype('f4')])

def test_iter_scalar_cast():
    # Check that scalars are cast as requested

    # No cast 'f4' -> 'f4'
    i = nditer(np.float32(2.5), [], [['readonly']],
                    op_dtypes=[np.dtype('f4')])
    assert_equal(i.dtypes[0], np.dtype('f4'))
    assert_equal(i.value.dtype, np.dtype('f4'))
    assert_equal(i.value, 2.5)
    # Safe cast 'f4' -> 'f8'
    i = nditer(np.float32(2.5), [],
                    [['readonly','copy']],
                    casting='safe',
                    op_dtypes=[np.dtype('f8')])
    assert_equal(i.dtypes[0], np.dtype('f8'))
    assert_equal(i.value.dtype, np.dtype('f8'))
    assert_equal(i.value, 2.5)
    # Same-kind cast 'f8' -> 'f4'
    i = nditer(np.float64(2.5), [],
                    [['readonly','copy']],
                    casting='same_kind',
                    op_dtypes=[np.dtype('f4')])
    assert_equal(i.dtypes[0], np.dtype('f4'))
    assert_equal(i.value.dtype, np.dtype('f4'))
    assert_equal(i.value, 2.5)
    # Unsafe cast 'f8' -> 'i4'
    i = nditer(np.float64(3.0), [],
                    [['readonly','copy']],
                    casting='unsafe',
                    op_dtypes=[np.dtype('i4')])
    assert_equal(i.dtypes[0], np.dtype('i4'))
    assert_equal(i.value.dtype, np.dtype('i4'))
    assert_equal(i.value, 3)
    # Readonly scalars may be cast even without setting COPY or BUFFERED
    i = nditer(3, [], [['readonly']], op_dtypes=[np.dtype('f8')])
    assert_equal(i[0].dtype, np.dtype('f8'))
    assert_equal(i[0], 3.)

def test_iter_scalar_cast_errors():
    # Check that invalid casts are caught

    # Need to allow copying/buffering for write casts of scalars to occur
    assert_raises(TypeError, nditer, np.float32(2), [],
                [['readwrite']], op_dtypes=[np.dtype('f8')])
    assert_raises(TypeError, nditer, 2.5, [],
                [['readwrite']], op_dtypes=[np.dtype('f4')])
    # 'f8' -> 'f4' isn't a safe cast if the value would overflow
    assert_raises(TypeError, nditer, np.float64(1e60), [],
                [['readonly']],
                casting='safe',
                op_dtypes=[np.dtype('f4')])
    # 'f4' -> 'i4' is neither a safe nor a same-kind cast
    assert_raises(TypeError, nditer, np.float32(2), [],
                [['readonly']],
                casting='same_kind',
                op_dtypes=[np.dtype('i4')])

def test_iter_object_arrays_basic():
    # Check that object arrays work

    obj = {'a':3,'b':'d'}
    a = np.array([[1,2,3], None, obj, None], dtype='O')
    rc = sys.getrefcount(obj)

    # Need to allow references for object arrays
    assert_raises(TypeError, nditer, a)
    assert_equal(sys.getrefcount(obj), rc)

    i = nditer(a, ['refs_ok'], ['readonly'])
    vals = [x[()] for x in i]
    assert_equal(np.array(vals, dtype='O'), a)
    vals, i, x = [None]*3
    assert_equal(sys.getrefcount(obj), rc)

    i = nditer(a.reshape(2,2).T, ['refs_ok','buffered'],
                        ['readonly'], order='C')
    assert_(i.iterationneedsapi)
    vals = [x[()] for x in i]
    assert_equal(np.array(vals, dtype='O'), a.reshape(2,2).ravel(order='F'))
    vals, i, x = [None]*3
    assert_equal(sys.getrefcount(obj), rc)

    i = nditer(a.reshape(2,2).T, ['refs_ok','buffered'],
                        ['readwrite'], order='C')
    for x in i:
        x[...] = None
    vals, i, x = [None]*3
    assert_equal(sys.getrefcount(obj), rc-1)
    assert_equal(a, np.array([None]*4, dtype='O'))

def test_iter_object_arrays_conversions():
    # Conversions to/from objects
    a = np.arange(6, dtype='O')
    i = nditer(a, ['refs_ok','buffered'], ['readwrite'],
                    casting='unsafe', op_dtypes='i4')
    for x in i:
        x[...] += 1
    assert_equal(a, np.arange(6)+1)

    a = np.arange(6, dtype='i4')
    i = nditer(a, ['refs_ok','buffered'], ['readwrite'],
                    casting='unsafe', op_dtypes='O')
    for x in i:
        x[...] += 1
    assert_equal(a, np.arange(6)+1)

    # Non-contiguous object array
    a = np.zeros((6,), dtype=[('p','i1'),('a','O')])
    a = a['a']
    a[:] = np.arange(6)
    i = nditer(a, ['refs_ok','buffered'], ['readwrite'],
                    casting='unsafe', op_dtypes='i4')
    for x in i:
        x[...] += 1
    assert_equal(a, np.arange(6)+1)

    #Non-contiguous value array
    a = np.zeros((6,), dtype=[('p','i1'),('a','i4')])
    a = a['a']
    a[:] = np.arange(6) + 98172488
    i = nditer(a, ['refs_ok','buffered'], ['readwrite'],
                    casting='unsafe', op_dtypes='O')
    ob = i[0][()]
    rc = sys.getrefcount(ob)
    for x in i:
        x[...] += 1
    assert_equal(sys.getrefcount(ob), rc-1)
    assert_equal(a, np.arange(6)+98172489)

def test_iter_common_dtype():
    # Check that the iterator finds a common data type correctly

    i = nditer([array([3],dtype='f4'),array([0],dtype='f8')],
                    ['common_dtype'],
                    [['readonly','copy']]*2,
                    casting='safe')
    assert_equal(i.dtypes[0], np.dtype('f8'));
    assert_equal(i.dtypes[1], np.dtype('f8'));
    i = nditer([array([3],dtype='i4'),array([0],dtype='f4')],
                    ['common_dtype'],
                    [['readonly','copy']]*2,
                    casting='safe')
    assert_equal(i.dtypes[0], np.dtype('f8'));
    assert_equal(i.dtypes[1], np.dtype('f8'));
    i = nditer([array([3],dtype='f4'),array(0,dtype='f8')],
                    ['common_dtype'],
                    [['readonly','copy']]*2,
                    casting='same_kind')
    assert_equal(i.dtypes[0], np.dtype('f4'));
    assert_equal(i.dtypes[1], np.dtype('f4'));
    i = nditer([array([3],dtype='u4'),array(0,dtype='i4')],
                    ['common_dtype'],
                    [['readonly','copy']]*2,
                    casting='safe')
    assert_equal(i.dtypes[0], np.dtype('u4'));
    assert_equal(i.dtypes[1], np.dtype('u4'));
    i = nditer([array([3],dtype='u4'),array(-12,dtype='i4')],
                    ['common_dtype'],
                    [['readonly','copy']]*2,
                    casting='safe')
    assert_equal(i.dtypes[0], np.dtype('i8'));
    assert_equal(i.dtypes[1], np.dtype('i8'));
    i = nditer([array([3],dtype='u4'),array(-12,dtype='i4'),
                 array([2j],dtype='c8'),array([9],dtype='f8')],
                    ['common_dtype'],
                    [['readonly','copy']]*4,
                    casting='safe')
    assert_equal(i.dtypes[0], np.dtype('c16'));
    assert_equal(i.dtypes[1], np.dtype('c16'));
    assert_equal(i.dtypes[2], np.dtype('c16'));
    assert_equal(i.dtypes[3], np.dtype('c16'));
    assert_equal(i.value, (3,-12,2j,9))

    # When allocating outputs, other outputs aren't factored in
    i = nditer([array([3],dtype='i4'),None,array([2j],dtype='c16')], [],
                    [['readonly','copy'],
                     ['writeonly','allocate'],
                     ['writeonly']],
                    casting='safe')
    assert_equal(i.dtypes[0], np.dtype('i4'));
    assert_equal(i.dtypes[1], np.dtype('i4'));
    assert_equal(i.dtypes[2], np.dtype('c16'));
    # But, if common data types are requested, they are
    i = nditer([array([3],dtype='i4'),None,array([2j],dtype='c16')],
                    ['common_dtype'],
                    [['readonly','copy'],
                     ['writeonly','allocate'],
                     ['writeonly']],
                    casting='safe')
    assert_equal(i.dtypes[0], np.dtype('c16'));
    assert_equal(i.dtypes[1], np.dtype('c16'));
    assert_equal(i.dtypes[2], np.dtype('c16'));

def test_iter_op_axes():
    # Check that custom axes work

    # Reverse the axes
    a = arange(6).reshape(2,3)
    i = nditer([a,a.T], [], [['readonly']]*2, op_axes=[[0,1],[1,0]])
    assert_(all([x==y for (x,y) in i]))
    a = arange(24).reshape(2,3,4)
    i = nditer([a.T,a], [], [['readonly']]*2, op_axes=[[2,1,0],None])
    assert_(all([x==y for (x,y) in i]))

    # Broadcast 1D to any dimension
    a = arange(1,31).reshape(2,3,5)
    b = arange(1,3)
    i = nditer([a,b], [], [['readonly']]*2, op_axes=[None,[0,-1,-1]])
    assert_equal([x*y for (x,y) in i], (a*b.reshape(2,1,1)).ravel())
    b = arange(1,4)
    i = nditer([a,b], [], [['readonly']]*2, op_axes=[None,[-1,0,-1]])
    assert_equal([x*y for (x,y) in i], (a*b.reshape(1,3,1)).ravel())
    b = arange(1,6)
    i = nditer([a,b], [], [['readonly']]*2,
                            op_axes=[None,[np.newaxis,np.newaxis,0]])
    assert_equal([x*y for (x,y) in i], (a*b.reshape(1,1,5)).ravel())

    # Inner product-style broadcasting
    a = arange(24).reshape(2,3,4)
    b = arange(40).reshape(5,2,4)
    i = nditer([a,b], ['multi_index'], [['readonly']]*2,
                            op_axes=[[0,1,-1,-1],[-1,-1,0,1]])
    assert_equal(i.shape, (2,3,5,2))

    # Matrix product-style broadcasting
    a = arange(12).reshape(3,4)
    b = arange(20).reshape(4,5)
    i = nditer([a,b], ['multi_index'], [['readonly']]*2,
                            op_axes=[[0,-1],[-1,1]])
    assert_equal(i.shape, (3,5))

def test_iter_op_axes_errors():
    # Check that custom axes throws errors for bad inputs

    # Wrong number of items in op_axes
    a = arange(6).reshape(2,3)
    assert_raises(ValueError, nditer, [a,a], [], [['readonly']]*2,
                                    op_axes=[[0],[1],[0]])
    # Out of bounds items in op_axes
    assert_raises(ValueError, nditer, [a,a], [], [['readonly']]*2,
                                    op_axes=[[2,1],[0,1]])
    assert_raises(ValueError, nditer, [a,a], [], [['readonly']]*2,
                                    op_axes=[[0,1],[2,-1]])
    # Duplicate items in op_axes
    assert_raises(ValueError, nditer, [a,a], [], [['readonly']]*2,
                                    op_axes=[[0,0],[0,1]])
    assert_raises(ValueError, nditer, [a,a], [], [['readonly']]*2,
                                    op_axes=[[0,1],[1,1]])

    # Different sized arrays in op_axes
    assert_raises(ValueError, nditer, [a,a], [], [['readonly']]*2,
                                    op_axes=[[0,1],[0,1,0]])

    # Non-broadcastable dimensions in the result
    assert_raises(ValueError, nditer, [a,a], [], [['readonly']]*2,
                                    op_axes=[[0,1],[1,0]])

def test_iter_copy():
    # Check that copying the iterator works correctly
    a = arange(24).reshape(2,3,4)

    # Simple iterator
    i = nditer(a)
    j = i.copy()
    assert_equal([x[()] for x in i], [x[()] for x in j])

    i.iterindex = 3
    j = i.copy()
    assert_equal([x[()] for x in i], [x[()] for x in j])

    # Buffered iterator
    i = nditer(a, ['buffered','ranged'], order='F', buffersize=3)
    j = i.copy()
    assert_equal([x[()] for x in i], [x[()] for x in j])

    i.iterindex = 3
    j = i.copy()
    assert_equal([x[()] for x in i], [x[()] for x in j])

    i.iterrange = (3,9)
    j = i.copy()
    assert_equal([x[()] for x in i], [x[()] for x in j])

    i.iterrange = (2,18)
    next(i)
    next(i)
    j = i.copy()
    assert_equal([x[()] for x in i], [x[()] for x in j])

    # Casting iterator
    i = nditer(a, ['buffered'], order='F', casting='unsafe',
                op_dtypes='f8', buffersize=5)
    j = i.copy()
    i = None
    assert_equal([x[()] for x in j], a.ravel(order='F'))

    a = arange(24, dtype='<i4').reshape(2,3,4)
    i = nditer(a, ['buffered'], order='F', casting='unsafe',
                op_dtypes='>f8', buffersize=5)
    j = i.copy()
    i = None
    assert_equal([x[()] for x in j], a.ravel(order='F'))

def test_iter_allocate_output_simple():
    # Check that the iterator will properly allocate outputs

    # Simple case
    a = arange(6)
    i = nditer([a,None], [], [['readonly'],['writeonly','allocate']],
                        op_dtypes=[None,np.dtype('f4')])
    assert_equal(i.operands[1].shape, a.shape)
    assert_equal(i.operands[1].dtype, np.dtype('f4'))

def test_iter_allocate_output_buffered_readwrite():
    # Allocated output with buffering + delay_bufalloc

    a = arange(6)
    i = nditer([a,None], ['buffered','delay_bufalloc'],
                        [['readonly'],['allocate','readwrite']])
    i.operands[1][:] = 1
    i.reset()
    for x in i:
        x[1][...] += x[0][...]
    assert_equal(i.operands[1], a+1)

def test_iter_allocate_output_itorder():
    # The allocated output should match the iteration order

    # C-order input, best iteration order
    a = arange(6, dtype='i4').reshape(2,3)
    i = nditer([a,None], [], [['readonly'],['writeonly','allocate']],
                        op_dtypes=[None,np.dtype('f4')])
    assert_equal(i.operands[1].shape, a.shape)
    assert_equal(i.operands[1].strides, a.strides)
    assert_equal(i.operands[1].dtype, np.dtype('f4'))
    # F-order input, best iteration order
    a = arange(24, dtype='i4').reshape(2,3,4).T
    i = nditer([a,None], [], [['readonly'],['writeonly','allocate']],
                        op_dtypes=[None,np.dtype('f4')])
    assert_equal(i.operands[1].shape, a.shape)
    assert_equal(i.operands[1].strides, a.strides)
    assert_equal(i.operands[1].dtype, np.dtype('f4'))
    # Non-contiguous input, C iteration order
    a = arange(24, dtype='i4').reshape(2,3,4).swapaxes(0,1)
    i = nditer([a,None], [],
                        [['readonly'],['writeonly','allocate']],
                        order='C',
                        op_dtypes=[None,np.dtype('f4')])
    assert_equal(i.operands[1].shape, a.shape)
    assert_equal(i.operands[1].strides, (32,16,4))
    assert_equal(i.operands[1].dtype, np.dtype('f4'))

def test_iter_allocate_output_opaxes():
    # Specifing op_axes should work

    a = arange(24, dtype='i4').reshape(2,3,4)
    i = nditer([None,a], [], [['writeonly','allocate'],['readonly']],
                        op_dtypes=[np.dtype('u4'),None],
                        op_axes=[[1,2,0],None]);
    assert_equal(i.operands[0].shape, (4,2,3))
    assert_equal(i.operands[0].strides, (4,48,16))
    assert_equal(i.operands[0].dtype, np.dtype('u4'))

def test_iter_allocate_output_types_promotion():
    # Check type promotion of automatic outputs

    i = nditer([array([3],dtype='f4'),array([0],dtype='f8'),None], [],
                    [['readonly']]*2+[['writeonly','allocate']])
    assert_equal(i.dtypes[2], np.dtype('f8'));
    i = nditer([array([3],dtype='i4'),array([0],dtype='f4'),None], [],
                    [['readonly']]*2+[['writeonly','allocate']])
    assert_equal(i.dtypes[2], np.dtype('f8'));
    i = nditer([array([3],dtype='f4'),array(0,dtype='f8'),None], [],
                    [['readonly']]*2+[['writeonly','allocate']])
    assert_equal(i.dtypes[2], np.dtype('f4'));
    i = nditer([array([3],dtype='u4'),array(0,dtype='i4'),None], [],
                    [['readonly']]*2+[['writeonly','allocate']])
    assert_equal(i.dtypes[2], np.dtype('u4'));
    i = nditer([array([3],dtype='u4'),array(-12,dtype='i4'),None], [],
                    [['readonly']]*2+[['writeonly','allocate']])
    assert_equal(i.dtypes[2], np.dtype('i8'));

def test_iter_allocate_output_types_byte_order():
    # Verify the rules for byte order changes

    # When there's just one input, the output type exactly matches
    a = array([3],dtype='u4').newbyteorder()
    i = nditer([a,None], [],
                    [['readonly'],['writeonly','allocate']])
    assert_equal(i.dtypes[0], i.dtypes[1]);
    # With two or more inputs, the output type is in native byte order
    i = nditer([a,a,None], [],
                    [['readonly'],['readonly'],['writeonly','allocate']])
    assert_(i.dtypes[0] != i.dtypes[2]);
    assert_equal(i.dtypes[0].newbyteorder('='), i.dtypes[2])

def test_iter_allocate_output_types_scalar():
    # If the inputs are all scalars, the output should be a scalar

    i = nditer([None,1,2.3,np.float32(12),np.complex128(3)],[],
                [['writeonly','allocate']] + [['readonly']]*4)
    assert_equal(i.operands[0].dtype, np.dtype('complex128'))
    assert_equal(i.operands[0].ndim, 0)

def test_iter_allocate_output_subtype():
    # Make sure that the subtype with priority wins

    # matrix vs ndarray
    a = np.matrix([[1,2], [3,4]])
    b = np.arange(4).reshape(2,2).T
    i = nditer([a,b,None], [],
                    [['readonly'],['readonly'],['writeonly','allocate']])
    assert_equal(type(a), type(i.operands[2]))
    assert_(type(b) != type(i.operands[2]))
    assert_equal(i.operands[2].shape, (2,2))

    # matrix always wants things to be 2D
    b = np.arange(4).reshape(1,2,2)
    assert_raises(RuntimeError, nditer, [a,b,None], [],
                    [['readonly'],['readonly'],['writeonly','allocate']])
    # but if subtypes are disabled, the result can still work
    i = nditer([a,b,None], [],
            [['readonly'],['readonly'],['writeonly','allocate','no_subtype']])
    assert_equal(type(b), type(i.operands[2]))
    assert_(type(a) != type(i.operands[2]))
    assert_equal(i.operands[2].shape, (1,2,2))

def test_iter_allocate_output_errors():
    # Check that the iterator will throw errors for bad output allocations

    # Need an input if no output data type is specified
    a = arange(6)
    assert_raises(TypeError, nditer, [a,None], [],
                        [['writeonly'],['writeonly','allocate']])
    # Allocated output should be flagged for writing
    assert_raises(ValueError, nditer, [a,None], [],
                        [['readonly'],['allocate','readonly']])
    # Allocated output can't have buffering without delayed bufalloc
    assert_raises(ValueError, nditer, [a,None], ['buffered'],
                                            ['allocate','readwrite'])
    # Must specify at least one input
    assert_raises(ValueError, nditer, [None,None], [],
                        [['writeonly','allocate'],
                         ['writeonly','allocate']],
                        op_dtypes=[np.dtype('f4'),np.dtype('f4')])
    # If using op_axes, must specify all the axes
    a = arange(24, dtype='i4').reshape(2,3,4)
    assert_raises(ValueError, nditer, [a,None], [],
                        [['readonly'],['writeonly','allocate']],
                        op_dtypes=[None,np.dtype('f4')],
                        op_axes=[None,[0,np.newaxis,1]])
    # If using op_axes, the axes must be within bounds
    assert_raises(ValueError, nditer, [a,None], [],
                        [['readonly'],['writeonly','allocate']],
                        op_dtypes=[None,np.dtype('f4')],
                        op_axes=[None,[0,3,1]])
    # If using op_axes, there can't be duplicates
    assert_raises(ValueError, nditer, [a,None], [],
                        [['readonly'],['writeonly','allocate']],
                        op_dtypes=[None,np.dtype('f4')],
                        op_axes=[None,[0,2,1,0]])

def test_iter_remove_axis():
    a = arange(24).reshape(2,3,4)

    i = nditer(a,['multi_index'])
    i.remove_axis(1)
    assert_equal([x for x in i], a[:,0,:].ravel())

    a = a[::-1,:,:]
    i = nditer(a,['multi_index'])
    i.remove_axis(0)
    assert_equal([x for x in i], a[0,:,:].ravel())

def test_iter_remove_multi_index_inner_loop():
    # Check that removing multi-index support works

    a = arange(24).reshape(2,3,4)

    i = nditer(a,['multi_index'])
    assert_equal(i.ndim, 3)
    assert_equal(i.shape, (2,3,4))
    assert_equal(i.itviews[0].shape, (2,3,4))

    # Removing the multi-index tracking causes all dimensions to coalesce
    before = [x for x in i]
    i.remove_multi_index()
    after = [x for x in i]

    assert_equal(before, after)
    assert_equal(i.ndim, 1)
    assert_raises(ValueError, lambda i:i.shape, i)
    assert_equal(i.itviews[0].shape, (24,))

    # Removing the inner loop means there's just one iteration
    i.reset()
    assert_equal(i.itersize, 24)
    assert_equal(i[0].shape, tuple())
    i.enable_external_loop()
    assert_equal(i.itersize, 24)
    assert_equal(i[0].shape, (24,))
    assert_equal(i.value, arange(24))

def test_iter_iterindex():
    # Make sure iterindex works

    buffersize = 5
    a = arange(24).reshape(4,3,2)
    for flags in ([], ['buffered']):
        i = nditer(a, flags, buffersize=buffersize)
        assert_equal(iter_iterindices(i), list(range(24)))
        i.iterindex = 2
        assert_equal(iter_iterindices(i), list(range(2,24)))

        i = nditer(a, flags, order='F', buffersize=buffersize)
        assert_equal(iter_iterindices(i), list(range(24)))
        i.iterindex = 5
        assert_equal(iter_iterindices(i), list(range(5,24)))

        i = nditer(a[::-1], flags, order='F', buffersize=buffersize)
        assert_equal(iter_iterindices(i), list(range(24)))
        i.iterindex = 9
        assert_equal(iter_iterindices(i), list(range(9,24)))

        i = nditer(a[::-1,::-1], flags, order='C', buffersize=buffersize)
        assert_equal(iter_iterindices(i), list(range(24)))
        i.iterindex = 13
        assert_equal(iter_iterindices(i), list(range(13,24)))

        i = nditer(a[::1,::-1], flags, buffersize=buffersize)
        assert_equal(iter_iterindices(i), list(range(24)))
        i.iterindex = 23
        assert_equal(iter_iterindices(i), list(range(23,24)))
        i.reset()
        i.iterindex = 2
        assert_equal(iter_iterindices(i), list(range(2,24)))

def test_iter_iterrange():
    # Make sure getting and resetting the iterrange works

    buffersize = 5
    a = arange(24, dtype='i4').reshape(4,3,2)
    a_fort = a.ravel(order='F')

    i = nditer(a, ['ranged'], ['readonly'], order='F',
                buffersize=buffersize)
    assert_equal(i.iterrange, (0,24))
    assert_equal([x[()] for x in i], a_fort)
    for r in [(0,24), (1,2), (3,24), (5,5), (0,20), (23,24)]:
        i.iterrange = r
        assert_equal(i.iterrange, r)
        assert_equal([x[()] for x in i], a_fort[r[0]:r[1]])

    i = nditer(a, ['ranged','buffered'], ['readonly'], order='F',
                op_dtypes='f8', buffersize=buffersize)
    assert_equal(i.iterrange, (0,24))
    assert_equal([x[()] for x in i], a_fort)
    for r in [(0,24), (1,2), (3,24), (5,5), (0,20), (23,24)]:
        i.iterrange = r
        assert_equal(i.iterrange, r)
        assert_equal([x[()] for x in i], a_fort[r[0]:r[1]])

    def get_array(i):
        val = np.array([], dtype='f8')
        for x in i:
            val = np.concatenate((val, x))
        return val

    i = nditer(a, ['ranged','buffered','external_loop'],
                ['readonly'], order='F',
                op_dtypes='f8', buffersize=buffersize)
    assert_equal(i.iterrange, (0,24))
    assert_equal(get_array(i), a_fort)
    for r in [(0,24), (1,2), (3,24), (5,5), (0,20), (23,24)]:
        i.iterrange = r
        assert_equal(i.iterrange, r)
        assert_equal(get_array(i), a_fort[r[0]:r[1]])

def test_iter_buffering():
    # Test buffering with several buffer sizes and types
    arrays = []
    # F-order swapped array
    arrays.append(np.arange(24,
                    dtype='c16').reshape(2,3,4).T.newbyteorder().byteswap())
    # Contiguous 1-dimensional array
    arrays.append(np.arange(10, dtype='f4'))
    # Unaligned array
    a = np.zeros((4*16+1,), dtype='i1')[1:]
    a.dtype = 'i4'
    a[:] = np.arange(16,dtype='i4')
    arrays.append(a)
    # 4-D F-order array
    arrays.append(np.arange(120,dtype='i4').reshape(5,3,2,4).T)
    for a in arrays:
        for buffersize in (1,2,3,5,8,11,16,1024):
            vals = []
            i = nditer(a, ['buffered','external_loop'],
                           [['readonly','nbo','aligned']],
                           order='C',
                           casting='equiv',
                           buffersize=buffersize)
            while not i.finished:
                assert_(i[0].size <= buffersize)
                vals.append(i[0].copy())
                i.iternext()
            assert_equal(np.concatenate(vals), a.ravel(order='C'))

def test_iter_write_buffering():
    # Test that buffering of writes is working

    # F-order swapped array
    a = np.arange(24).reshape(2,3,4).T.newbyteorder().byteswap()
    i = nditer(a, ['buffered'],
                   [['readwrite','nbo','aligned']],
                   casting='equiv',
                   order='C',
                   buffersize=16)
    x = 0
    while not i.finished:
        i[0] = x
        x += 1
        i.iternext()
    assert_equal(a.ravel(order='C'), np.arange(24))

def test_iter_buffering_delayed_alloc():
    # Test that delaying buffer allocation works

    a = np.arange(6)
    b = np.arange(1, dtype='f4')
    i = nditer([a,b], ['buffered','delay_bufalloc','multi_index','reduce_ok'],
                    ['readwrite'],
                    casting='unsafe',
                    op_dtypes='f4')
    assert_(i.has_delayed_bufalloc)
    assert_raises(ValueError, lambda i:i.multi_index, i)
    assert_raises(ValueError, lambda i:i[0], i)
    assert_raises(ValueError, lambda i:i[0:2], i)
    def assign_iter(i):
        i[0] = 0
    assert_raises(ValueError, assign_iter, i)

    i.reset()
    assert_(not i.has_delayed_bufalloc)
    assert_equal(i.multi_index, (0,))
    assert_equal(i[0], 0)
    i[1] = 1
    assert_equal(i[0:2], [0,1])
    assert_equal([[x[0][()],x[1][()]] for x in i], list(zip(range(6), [1]*6)))

def test_iter_buffered_cast_simple():
    # Test that buffering can handle a simple cast

    a = np.arange(10, dtype='f4')
    i = nditer(a, ['buffered','external_loop'],
                   [['readwrite','nbo','aligned']],
                   casting='same_kind',
                   op_dtypes=[np.dtype('f8')],
                   buffersize=3)
    for v in i:
        v[...] *= 2

    assert_equal(a, 2*np.arange(10, dtype='f4'))

def test_iter_buffered_cast_byteswapped():
    # Test that buffering can handle a cast which requires swap->cast->swap

    a = np.arange(10, dtype='f4').newbyteorder().byteswap()
    i = nditer(a, ['buffered','external_loop'],
                   [['readwrite','nbo','aligned']],
                   casting='same_kind',
                   op_dtypes=[np.dtype('f8').newbyteorder()],
                   buffersize=3)
    for v in i:
        v[...] *= 2

    assert_equal(a, 2*np.arange(10, dtype='f4'))

    try:
        warnings.simplefilter("ignore", np.ComplexWarning)

        a = np.arange(10, dtype='f8').newbyteorder().byteswap()
        i = nditer(a, ['buffered','external_loop'],
                       [['readwrite','nbo','aligned']],
                       casting='unsafe',
                       op_dtypes=[np.dtype('c8').newbyteorder()],
                       buffersize=3)
        for v in i:
            v[...] *= 2

        assert_equal(a, 2*np.arange(10, dtype='f8'))
    finally:
        warnings.simplefilter("default", np.ComplexWarning)

def test_iter_buffered_cast_byteswapped_complex():
    # Test that buffering can handle a cast which requires swap->cast->copy

    a = np.arange(10, dtype='c8').newbyteorder().byteswap()
    a += 2j
    i = nditer(a, ['buffered','external_loop'],
                   [['readwrite','nbo','aligned']],
                   casting='same_kind',
                   op_dtypes=[np.dtype('c16')],
                   buffersize=3)
    for v in i:
        v[...] *= 2
    assert_equal(a, 2*np.arange(10, dtype='c8') + 4j)

    a = np.arange(10, dtype='c8')
    a += 2j
    i = nditer(a, ['buffered','external_loop'],
                   [['readwrite','nbo','aligned']],
                   casting='same_kind',
                   op_dtypes=[np.dtype('c16').newbyteorder()],
                   buffersize=3)
    for v in i:
        v[...] *= 2
    assert_equal(a, 2*np.arange(10, dtype='c8') + 4j)

    a = np.arange(10, dtype=np.clongdouble).newbyteorder().byteswap()
    a += 2j
    i = nditer(a, ['buffered','external_loop'],
                   [['readwrite','nbo','aligned']],
                   casting='same_kind',
                   op_dtypes=[np.dtype('c16')],
                   buffersize=3)
    for v in i:
        v[...] *= 2
    assert_equal(a, 2*np.arange(10, dtype=np.clongdouble) + 4j)

    a = np.arange(10, dtype=np.longdouble).newbyteorder().byteswap()
    i = nditer(a, ['buffered','external_loop'],
                   [['readwrite','nbo','aligned']],
                   casting='same_kind',
                   op_dtypes=[np.dtype('f4')],
                   buffersize=7)
    for v in i:
        v[...] *= 2
    assert_equal(a, 2*np.arange(10, dtype=np.longdouble))

def test_iter_buffered_cast_structured_type():
    # Tests buffering of structured types

    # simple -> struct type (duplicates the value)
    sdt = [('a', 'f4'), ('b', 'i8'), ('c', 'c8', (2,3)), ('d', 'O')]
    a = np.arange(3, dtype='f4') + 0.5
    i = nditer(a, ['buffered','refs_ok'], ['readonly'],
                    casting='unsafe',
                    op_dtypes=sdt)
    vals = [np.array(x) for x in i]
    assert_equal(vals[0]['a'], 0.5)
    assert_equal(vals[0]['b'], 0)
    assert_equal(vals[0]['c'], [[(0.5)]*3]*2)
    assert_equal(vals[0]['d'], 0.5)
    assert_equal(vals[1]['a'], 1.5)
    assert_equal(vals[1]['b'], 1)
    assert_equal(vals[1]['c'], [[(1.5)]*3]*2)
    assert_equal(vals[1]['d'], 1.5)
    assert_equal(vals[0].dtype, np.dtype(sdt))

    # object -> struct type
    sdt = [('a', 'f4'), ('b', 'i8'), ('c', 'c8', (2,3)), ('d', 'O')]
    a = np.zeros((3,), dtype='O')
    a[0] = (0.5,0.5,[[0.5,0.5,0.5],[0.5,0.5,0.5]],0.5)
    a[1] = (1.5,1.5,[[1.5,1.5,1.5],[1.5,1.5,1.5]],1.5)
    a[2] = (2.5,2.5,[[2.5,2.5,2.5],[2.5,2.5,2.5]],2.5)
    rc = sys.getrefcount(a[0])
    i = nditer(a, ['buffered','refs_ok'], ['readonly'],
                    casting='unsafe',
                    op_dtypes=sdt)
    vals = [x.copy() for x in i]
    assert_equal(vals[0]['a'], 0.5)
    assert_equal(vals[0]['b'], 0)
    assert_equal(vals[0]['c'], [[(0.5)]*3]*2)
    assert_equal(vals[0]['d'], 0.5)
    assert_equal(vals[1]['a'], 1.5)
    assert_equal(vals[1]['b'], 1)
    assert_equal(vals[1]['c'], [[(1.5)]*3]*2)
    assert_equal(vals[1]['d'], 1.5)
    assert_equal(vals[0].dtype, np.dtype(sdt))
    vals, i, x = [None]*3
    assert_equal(sys.getrefcount(a[0]), rc)

    # struct type -> simple (takes the first value)
    sdt = [('a', 'f4'), ('b', 'i8'), ('d', 'O')]
    a = np.array([(5.5,7,'test'),(8,10,11)], dtype=sdt)
    i = nditer(a, ['buffered','refs_ok'], ['readonly'],
                    casting='unsafe',
                    op_dtypes='i4')
    assert_equal([x[()] for x in i], [5, 8])

    # struct type -> struct type (field-wise copy)
    sdt1 = [('a', 'f4'), ('b', 'i8'), ('d', 'O')]
    sdt2 = [('d', 'u2'), ('a', 'O'), ('b', 'f8')]
    a = np.array([(1,2,3),(4,5,6)], dtype=sdt1)
    i = nditer(a, ['buffered','refs_ok'], ['readonly'],
                    casting='unsafe',
                    op_dtypes=sdt2)
    assert_equal(i[0].dtype, np.dtype(sdt2))
    assert_equal([np.array(x) for x in i],
                    [np.array((3,1,2), dtype=sdt2),
                     np.array((6,4,5), dtype=sdt2)])

    # struct type -> struct type (field gets discarded)
    sdt1 = [('a', 'f4'), ('b', 'i8'), ('d', 'O')]
    sdt2 = [('b', 'O'), ('a', 'f8')]
    a = np.array([(1,2,3),(4,5,6)], dtype=sdt1)
    i = nditer(a, ['buffered','refs_ok'], ['readwrite'],
                    casting='unsafe',
                    op_dtypes=sdt2)
    assert_equal(i[0].dtype, np.dtype(sdt2))
    vals = []
    for x in i:
        vals.append(np.array(x))
        x['a'] = x['b']+3
    assert_equal(vals, [np.array((2,1), dtype=sdt2),
                     np.array((5,4), dtype=sdt2)])
    assert_equal(a, np.array([(5,2,None),(8,5,None)], dtype=sdt1))

    # struct type -> struct type (structured field gets discarded)
    sdt1 = [('a', 'f4'), ('b', 'i8'), ('d', [('a', 'i2'),('b','i4')])]
    sdt2 = [('b', 'O'), ('a', 'f8')]
    a = np.array([(1,2,(0,9)),(4,5,(20,21))], dtype=sdt1)
    i = nditer(a, ['buffered','refs_ok'], ['readwrite'],
                    casting='unsafe',
                    op_dtypes=sdt2)
    assert_equal(i[0].dtype, np.dtype(sdt2))
    vals = []
    for x in i:
        vals.append(np.array(x))
        x['a'] = x['b']+3
    assert_equal(vals, [np.array((2,1), dtype=sdt2),
                     np.array((5,4), dtype=sdt2)])
    assert_equal(a, np.array([(5,2,(0,0)),(8,5,(0,0))], dtype=sdt1))

    # struct type -> struct type (structured field w/ ref gets discarded)
    sdt1 = [('a', 'f4'), ('b', 'i8'), ('d', [('a', 'i2'),('b','O')])]
    sdt2 = [('b', 'O'), ('a', 'f8')]
    a = np.array([(1,2,(0,9)),(4,5,(20,21))], dtype=sdt1)
    i = nditer(a, ['buffered','refs_ok'], ['readwrite'],
                    casting='unsafe',
                    op_dtypes=sdt2)
    assert_equal(i[0].dtype, np.dtype(sdt2))
    vals = []
    for x in i:
        vals.append(np.array(x))
        x['a'] = x['b']+3
    assert_equal(vals, [np.array((2,1), dtype=sdt2),
                     np.array((5,4), dtype=sdt2)])
    assert_equal(a, np.array([(5,2,(0,None)),(8,5,(0,None))], dtype=sdt1))

    # struct type -> struct type back (structured field w/ ref gets discarded)
    sdt1 = [('b', 'O'), ('a', 'f8')]
    sdt2 = [('a', 'f4'), ('b', 'i8'), ('d', [('a', 'i2'),('b','O')])]
    a = np.array([(1,2),(4,5)], dtype=sdt1)
    i = nditer(a, ['buffered','refs_ok'], ['readwrite'],
                    casting='unsafe',
                    op_dtypes=sdt2)
    assert_equal(i[0].dtype, np.dtype(sdt2))
    vals = []
    for x in i:
        vals.append(np.array(x))
        assert_equal(x['d'], np.array((0, None), dtype=[('a','i2'),('b','O')]))
        x['a'] = x['b']+3
    assert_equal(vals, [np.array((2,1,(0,None)), dtype=sdt2),
                     np.array((5,4,(0,None)), dtype=sdt2)])
    assert_equal(a, np.array([(1,4),(4,7)], dtype=sdt1))

def test_iter_buffered_cast_subarray():
    # Tests buffering of subarrays

    # one element -> many (copies it to all)
    sdt1 = [('a', 'f4')]
    sdt2 = [('a', 'f8', (3,2,2))]
    a = np.zeros((6,), dtype=sdt1)
    a['a'] = np.arange(6)
    i = nditer(a, ['buffered','refs_ok'], ['readonly'],
                    casting='unsafe',
                    op_dtypes=sdt2)
    assert_equal(i[0].dtype, np.dtype(sdt2))
    for x, count in zip(i, list(range(6))):
        assert_(np.all(x['a'] == count))

    # one element -> many -> back (copies it to all)
    sdt1 = [('a', 'O', (1,1))]
    sdt2 = [('a', 'O', (3,2,2))]
    a = np.zeros((6,), dtype=sdt1)
    a['a'][:,0,0] = np.arange(6)
    i = nditer(a, ['buffered','refs_ok'], ['readwrite'],
                    casting='unsafe',
                    op_dtypes=sdt2)
    assert_equal(i[0].dtype, np.dtype(sdt2))
    count = 0
    for x in i:
        assert_(np.all(x['a'] == count))
        x['a'][0] += 2
        count += 1
    assert_equal(a['a'], np.arange(6).reshape(6,1,1)+2)

    # many -> one element -> back (copies just element 0)
    sdt1 = [('a', 'O', (3,2,2))]
    sdt2 = [('a', 'O', (1,))]
    a = np.zeros((6,), dtype=sdt1)
    a['a'][:,0,0,0] = np.arange(6)
    i = nditer(a, ['buffered','refs_ok'], ['readwrite'],
                    casting='unsafe',
                    op_dtypes=sdt2)
    assert_equal(i[0].dtype, np.dtype(sdt2))
    count = 0
    for x in i:
        assert_equal(x['a'], count)
        x['a'] += 2
        count += 1
    assert_equal(a['a'], np.arange(6).reshape(6,1,1,1)*np.ones((1,3,2,2))+2)

    # many -> one element -> back (copies just element 0)
    sdt1 = [('a', 'f8', (3,2,2))]
    sdt2 = [('a', 'O', (1,))]
    a = np.zeros((6,), dtype=sdt1)
    a['a'][:,0,0,0] = np.arange(6)
    i = nditer(a, ['buffered','refs_ok'], ['readonly'],
                    casting='unsafe',
                    op_dtypes=sdt2)
    assert_equal(i[0].dtype, np.dtype(sdt2))
    count = 0
    for x in i:
        assert_equal(x['a'], count)
        count += 1

    # many -> one element (copies just element 0)
    sdt1 = [('a', 'O', (3,2,2))]
    sdt2 = [('a', 'f4', (1,))]
    a = np.zeros((6,), dtype=sdt1)
    a['a'][:,0,0,0] = np.arange(6)
    i = nditer(a, ['buffered','refs_ok'], ['readonly'],
                    casting='unsafe',
                    op_dtypes=sdt2)
    assert_equal(i[0].dtype, np.dtype(sdt2))
    count = 0
    for x in i:
        assert_equal(x['a'], count)
        count += 1

    # many -> matching shape (straightforward copy)
    sdt1 = [('a', 'O', (3,2,2))]
    sdt2 = [('a', 'f4', (3,2,2))]
    a = np.zeros((6,), dtype=sdt1)
    a['a'] = np.arange(6*3*2*2).reshape(6,3,2,2)
    i = nditer(a, ['buffered','refs_ok'], ['readonly'],
                    casting='unsafe',
                    op_dtypes=sdt2)
    assert_equal(i[0].dtype, np.dtype(sdt2))
    count = 0
    for x in i:
        assert_equal(x['a'], a[count]['a'])
        count += 1

    # vector -> smaller vector (truncates)
    sdt1 = [('a', 'f8', (6,))]
    sdt2 = [('a', 'f4', (2,))]
    a = np.zeros((6,), dtype=sdt1)
    a['a'] = np.arange(6*6).reshape(6,6)
    i = nditer(a, ['buffered','refs_ok'], ['readonly'],
                    casting='unsafe',
                    op_dtypes=sdt2)
    assert_equal(i[0].dtype, np.dtype(sdt2))
    count = 0
    for x in i:
        assert_equal(x['a'], a[count]['a'][:2])
        count += 1

    # vector -> bigger vector (pads with zeros)
    sdt1 = [('a', 'f8', (2,))]
    sdt2 = [('a', 'f4', (6,))]
    a = np.zeros((6,), dtype=sdt1)
    a['a'] = np.arange(6*2).reshape(6,2)
    i = nditer(a, ['buffered','refs_ok'], ['readonly'],
                    casting='unsafe',
                    op_dtypes=sdt2)
    assert_equal(i[0].dtype, np.dtype(sdt2))
    count = 0
    for x in i:
        assert_equal(x['a'][:2], a[count]['a'])
        assert_equal(x['a'][2:], [0,0,0,0])
        count += 1

    # vector -> matrix (broadcasts)
    sdt1 = [('a', 'f8', (2,))]
    sdt2 = [('a', 'f4', (2,2))]
    a = np.zeros((6,), dtype=sdt1)
    a['a'] = np.arange(6*2).reshape(6,2)
    i = nditer(a, ['buffered','refs_ok'], ['readonly'],
                    casting='unsafe',
                    op_dtypes=sdt2)
    assert_equal(i[0].dtype, np.dtype(sdt2))
    count = 0
    for x in i:
        assert_equal(x['a'][0], a[count]['a'])
        assert_equal(x['a'][1], a[count]['a'])
        count += 1

    # vector -> matrix (broadcasts and zero-pads)
    sdt1 = [('a', 'f8', (2,1))]
    sdt2 = [('a', 'f4', (3,2))]
    a = np.zeros((6,), dtype=sdt1)
    a['a'] = np.arange(6*2).reshape(6,2,1)
    i = nditer(a, ['buffered','refs_ok'], ['readonly'],
                    casting='unsafe',
                    op_dtypes=sdt2)
    assert_equal(i[0].dtype, np.dtype(sdt2))
    count = 0
    for x in i:
        assert_equal(x['a'][:2,0], a[count]['a'][:,0])
        assert_equal(x['a'][:2,1], a[count]['a'][:,0])
        assert_equal(x['a'][2,:], [0,0])
        count += 1

    # matrix -> matrix (truncates and zero-pads)
    sdt1 = [('a', 'f8', (2,3))]
    sdt2 = [('a', 'f4', (3,2))]
    a = np.zeros((6,), dtype=sdt1)
    a['a'] = np.arange(6*2*3).reshape(6,2,3)
    i = nditer(a, ['buffered','refs_ok'], ['readonly'],
                    casting='unsafe',
                    op_dtypes=sdt2)
    assert_equal(i[0].dtype, np.dtype(sdt2))
    count = 0
    for x in i:
        assert_equal(x['a'][:2,0], a[count]['a'][:,0])
        assert_equal(x['a'][:2,1], a[count]['a'][:,1])
        assert_equal(x['a'][2,:], [0,0])
        count += 1

def test_iter_buffering_badwriteback():
    # Writing back from a buffer cannot combine elements

    # a needs write buffering, but had a broadcast dimension
    a = np.arange(6).reshape(2,3,1)
    b = np.arange(12).reshape(2,3,2)
    assert_raises(ValueError,nditer,[a,b],
                        ['buffered','external_loop'],
                        [['readwrite'],['writeonly']],
                        order='C')

    # But if a is readonly, it's fine
    i = nditer([a,b],['buffered','external_loop'],
                        [['readonly'],['writeonly']],
                        order='C')

    # If a has just one element, it's fine too (constant 0 stride, a reduction)
    a = np.arange(1).reshape(1,1,1)
    i = nditer([a,b],['buffered','external_loop','reduce_ok'],
                        [['readwrite'],['writeonly']],
                        order='C')

    # check that it fails on other dimensions too
    a = np.arange(6).reshape(1,3,2)
    assert_raises(ValueError,nditer,[a,b],
                        ['buffered','external_loop'],
                        [['readwrite'],['writeonly']],
                        order='C')
    a = np.arange(4).reshape(2,1,2)
    assert_raises(ValueError,nditer,[a,b],
                        ['buffered','external_loop'],
                        [['readwrite'],['writeonly']],
                        order='C')

def test_iter_buffering_string():
    # Safe casting disallows shrinking strings
    a = np.array(['abc', 'a', 'abcd'], dtype=np.bytes_)
    assert_equal(a.dtype, np.dtype('S4'));
    assert_raises(TypeError,nditer,a,['buffered'],['readonly'],
                    op_dtypes='S2')
    i = nditer(a, ['buffered'], ['readonly'], op_dtypes='S6')
    assert_equal(i[0], asbytes('abc'))
    assert_equal(i[0].dtype, np.dtype('S6'))

    a = np.array(['abc', 'a', 'abcd'], dtype=np.unicode)
    assert_equal(a.dtype, np.dtype('U4'));
    assert_raises(TypeError,nditer,a,['buffered'],['readonly'],
                    op_dtypes='U2')
    i = nditer(a, ['buffered'], ['readonly'], op_dtypes='U6')
    assert_equal(i[0], sixu('abc'))
    assert_equal(i[0].dtype, np.dtype('U6'))

def test_iter_buffering_growinner():
    # Test that the inner loop grows when no buffering is needed
    a = np.arange(30)
    i = nditer(a, ['buffered','growinner','external_loop'],
                           buffersize=5)
    # Should end up with just one inner loop here
    assert_equal(i[0].size, a.size)


@dec.slow
def test_iter_buffered_reduce_reuse():
    # large enough array for all views, including negative strides.
    a = np.arange(2*3**5)[3**5:3**5+1]
    flags = ['buffered', 'delay_bufalloc', 'multi_index', 'reduce_ok', 'refs_ok']
    op_flags = [('readonly',), ('readwrite','allocate')]
    op_axes_list = [[(0,1,2), (0,1,-1)], [(0,1,2), (0,-1,-1)]]
    # wrong dtype to force buffering
    op_dtypes = [np.float, a.dtype]

    def get_params():
        for xs in range(-3**2, 3**2 + 1):
            for ys in range(xs, 3**2 + 1):
                for op_axes in op_axes_list:
                    # last stride is reduced and because of that not
                    # important for this test, as it is the inner stride.
                    strides = (xs * a.itemsize, ys * a.itemsize, a.itemsize)
                    arr = np.lib.stride_tricks.as_strided(a, (3,3,3), strides)

                    for skip in [0, 1]:
                        yield arr, op_axes, skip

    for arr, op_axes, skip in get_params():
        nditer2 = np.nditer([arr.copy(), None],
                            op_axes=op_axes, flags=flags, op_flags=op_flags,
                            op_dtypes=op_dtypes)
        nditer2.operands[-1][...] = 0
        nditer2.reset()
        nditer2.iterindex = skip

        for (a2_in, b2_in) in nditer2:
            b2_in += a2_in.astype(np.int_)

        comp_res = nditer2.operands[-1]

        for bufsize in range(0, 3**3):
            nditer1 = np.nditer([arr, None],
                                op_axes=op_axes, flags=flags, op_flags=op_flags,
                                buffersize=bufsize, op_dtypes=op_dtypes)
            nditer1.operands[-1][...] = 0
            nditer1.reset()
            nditer1.iterindex = skip

            for (a1_in, b1_in) in nditer1:
                b1_in += a1_in.astype(np.int_)

            res = nditer1.operands[-1]
            assert_array_equal(res, comp_res)


def test_iter_no_broadcast():
    # Test that the no_broadcast flag works
    a = np.arange(24).reshape(2,3,4)
    b = np.arange(6).reshape(2,3,1)
    c = np.arange(12).reshape(3,4)

    i = nditer([a,b,c], [],
                    [['readonly','no_broadcast'],['readonly'],['readonly']])
    assert_raises(ValueError, nditer, [a,b,c], [],
                    [['readonly'],['readonly','no_broadcast'],['readonly']])
    assert_raises(ValueError, nditer, [a,b,c], [],
                    [['readonly'],['readonly'],['readonly','no_broadcast']])

def test_iter_nested_iters_basic():
    # Test nested iteration basic usage
    a = arange(12).reshape(2,3,2)

    i, j = np.nested_iters(a, [[0],[1,2]])
    vals = []
    for x in i:
        vals.append([y for y in j])
    assert_equal(vals, [[0,1,2,3,4,5],[6,7,8,9,10,11]])

    i, j = np.nested_iters(a, [[0,1],[2]])
    vals = []
    for x in i:
        vals.append([y for y in j])
    assert_equal(vals, [[0,1],[2,3],[4,5],[6,7],[8,9],[10,11]])

    i, j = np.nested_iters(a, [[0,2],[1]])
    vals = []
    for x in i:
        vals.append([y for y in j])
    assert_equal(vals, [[0,2,4],[1,3,5],[6,8,10],[7,9,11]])

def test_iter_nested_iters_reorder():
    # Test nested iteration basic usage
    a = arange(12).reshape(2,3,2)

    # In 'K' order (default), it gets reordered
    i, j = np.nested_iters(a, [[0],[2,1]])
    vals = []
    for x in i:
        vals.append([y for y in j])
    assert_equal(vals, [[0,1,2,3,4,5],[6,7,8,9,10,11]])

    i, j = np.nested_iters(a, [[1,0],[2]])
    vals = []
    for x in i:
        vals.append([y for y in j])
    assert_equal(vals, [[0,1],[2,3],[4,5],[6,7],[8,9],[10,11]])

    i, j = np.nested_iters(a, [[2,0],[1]])
    vals = []
    for x in i:
        vals.append([y for y in j])
    assert_equal(vals, [[0,2,4],[1,3,5],[6,8,10],[7,9,11]])

    # In 'C' order, it doesn't
    i, j = np.nested_iters(a, [[0],[2,1]], order='C')
    vals = []
    for x in i:
        vals.append([y for y in j])
    assert_equal(vals, [[0,2,4,1,3,5],[6,8,10,7,9,11]])

    i, j = np.nested_iters(a, [[1,0],[2]], order='C')
    vals = []
    for x in i:
        vals.append([y for y in j])
    assert_equal(vals, [[0,1],[6,7],[2,3],[8,9],[4,5],[10,11]])

    i, j = np.nested_iters(a, [[2,0],[1]], order='C')
    vals = []
    for x in i:
        vals.append([y for y in j])
    assert_equal(vals, [[0,2,4],[6,8,10],[1,3,5],[7,9,11]])

def test_iter_nested_iters_flip_axes():
    # Test nested iteration with negative axes
    a = arange(12).reshape(2,3,2)[::-1,::-1,::-1]

    # In 'K' order (default), the axes all get flipped
    i, j = np.nested_iters(a, [[0],[1,2]])
    vals = []
    for x in i:
        vals.append([y for y in j])
    assert_equal(vals, [[0,1,2,3,4,5],[6,7,8,9,10,11]])

    i, j = np.nested_iters(a, [[0,1],[2]])
    vals = []
    for x in i:
        vals.append([y for y in j])
    assert_equal(vals, [[0,1],[2,3],[4,5],[6,7],[8,9],[10,11]])

    i, j = np.nested_iters(a, [[0,2],[1]])
    vals = []
    for x in i:
        vals.append([y for y in j])
    assert_equal(vals, [[0,2,4],[1,3,5],[6,8,10],[7,9,11]])

    # In 'C' order, flipping axes is disabled
    i, j = np.nested_iters(a, [[0],[1,2]], order='C')
    vals = []
    for x in i:
        vals.append([y for y in j])
    assert_equal(vals, [[11,10,9,8,7,6],[5,4,3,2,1,0]])

    i, j = np.nested_iters(a, [[0,1],[2]], order='C')
    vals = []
    for x in i:
        vals.append([y for y in j])
    assert_equal(vals, [[11,10],[9,8],[7,6],[5,4],[3,2],[1,0]])

    i, j = np.nested_iters(a, [[0,2],[1]], order='C')
    vals = []
    for x in i:
        vals.append([y for y in j])
    assert_equal(vals, [[11,9,7],[10,8,6],[5,3,1],[4,2,0]])

def test_iter_nested_iters_broadcast():
    # Test nested iteration with broadcasting
    a = arange(2).reshape(2,1)
    b = arange(3).reshape(1,3)

    i, j = np.nested_iters([a,b], [[0],[1]])
    vals = []
    for x in i:
        vals.append([y for y in j])
    assert_equal(vals, [[[0,0],[0,1],[0,2]],[[1,0],[1,1],[1,2]]])

    i, j = np.nested_iters([a,b], [[1],[0]])
    vals = []
    for x in i:
        vals.append([y for y in j])
    assert_equal(vals, [[[0,0],[1,0]],[[0,1],[1,1]],[[0,2],[1,2]]])

def test_iter_nested_iters_dtype_copy():
    # Test nested iteration with a copy to change dtype

    # copy
    a = arange(6, dtype='i4').reshape(2,3)
    i, j = np.nested_iters(a, [[0],[1]],
                        op_flags=['readonly','copy'],
                        op_dtypes='f8')
    assert_equal(j[0].dtype, np.dtype('f8'))
    vals = []
    for x in i:
        vals.append([y for y in j])
    assert_equal(vals, [[0,1,2],[3,4,5]])
    vals = None

    # updateifcopy
    a = arange(6, dtype='f4').reshape(2,3)
    i, j = np.nested_iters(a, [[0],[1]],
                        op_flags=['readwrite','updateifcopy'],
                        casting='same_kind',
                        op_dtypes='f8')
    assert_equal(j[0].dtype, np.dtype('f8'))
    for x in i:
        for y in j:
            y[...] += 1
    assert_equal(a, [[0,1,2],[3,4,5]])
    i, j, x, y = (None,)*4 # force the updateifcopy
    assert_equal(a, [[1,2,3],[4,5,6]])

def test_iter_nested_iters_dtype_buffered():
    # Test nested iteration with buffering to change dtype

    a = arange(6, dtype='f4').reshape(2,3)
    i, j = np.nested_iters(a, [[0],[1]],
                        flags=['buffered'],
                        op_flags=['readwrite'],
                        casting='same_kind',
                        op_dtypes='f8')
    assert_equal(j[0].dtype, np.dtype('f8'))
    for x in i:
        for y in j:
            y[...] += 1
    assert_equal(a, [[1,2,3],[4,5,6]])

def test_iter_reduction_error():

    a = np.arange(6)
    assert_raises(ValueError, nditer, [a,None], [],
                    [['readonly'], ['readwrite','allocate']],
                    op_axes=[[0],[-1]])

    a = np.arange(6).reshape(2,3)
    assert_raises(ValueError, nditer, [a,None], ['external_loop'],
                    [['readonly'], ['readwrite','allocate']],
                    op_axes=[[0,1],[-1,-1]])

def test_iter_reduction():
    # Test doing reductions with the iterator

    a = np.arange(6)
    i = nditer([a,None], ['reduce_ok'],
                    [['readonly'], ['readwrite','allocate']],
                    op_axes=[[0],[-1]])
    # Need to initialize the output operand to the addition unit
    i.operands[1][...] = 0
    # Do the reduction
    for x, y in i:
        y[...] += x
    # Since no axes were specified, should have allocated a scalar
    assert_equal(i.operands[1].ndim, 0)
    assert_equal(i.operands[1], np.sum(a))

    a = np.arange(6).reshape(2,3)
    i = nditer([a,None], ['reduce_ok','external_loop'],
                    [['readonly'], ['readwrite','allocate']],
                    op_axes=[[0,1],[-1,-1]])
    # Need to initialize the output operand to the addition unit
    i.operands[1][...] = 0
    # Reduction shape/strides for the output
    assert_equal(i[1].shape, (6,))
    assert_equal(i[1].strides, (0,))
    # Do the reduction
    for x, y in i:
        y[...] += x
    # Since no axes were specified, should have allocated a scalar
    assert_equal(i.operands[1].ndim, 0)
    assert_equal(i.operands[1], np.sum(a))

    # This is a tricky reduction case for the buffering double loop
    # to handle
    a = np.ones((2,3,5))
    it1 = nditer([a,None], ['reduce_ok','external_loop'],
                    [['readonly'], ['readwrite','allocate']],
                    op_axes=[None,[0,-1,1]])
    it2 = nditer([a,None], ['reduce_ok','external_loop',
                            'buffered','delay_bufalloc'],
                    [['readonly'], ['readwrite','allocate']],
                    op_axes=[None,[0,-1,1]], buffersize=10)
    it1.operands[1].fill(0)
    it2.operands[1].fill(0)
    it2.reset()
    for x in it1:
        x[1][...] += x[0]
    for x in it2:
        x[1][...] += x[0]
    assert_equal(it1.operands[1], it2.operands[1])
    assert_equal(it2.operands[1].sum(), a.size)

def test_iter_buffering_reduction():
    # Test doing buffered reductions with the iterator

    a = np.arange(6)
    b = np.array(0., dtype='f8').byteswap().newbyteorder()
    i = nditer([a,b], ['reduce_ok', 'buffered'],
                    [['readonly'], ['readwrite','nbo']],
                    op_axes=[[0],[-1]])
    assert_equal(i[1].dtype, np.dtype('f8'))
    assert_(i[1].dtype != b.dtype)
    # Do the reduction
    for x, y in i:
        y[...] += x
    # Since no axes were specified, should have allocated a scalar
    assert_equal(b, np.sum(a))

    a = np.arange(6).reshape(2,3)
    b = np.array([0,0], dtype='f8').byteswap().newbyteorder()
    i = nditer([a,b], ['reduce_ok','external_loop', 'buffered'],
                    [['readonly'], ['readwrite','nbo']],
                    op_axes=[[0,1],[0,-1]])
    # Reduction shape/strides for the output
    assert_equal(i[1].shape, (3,))
    assert_equal(i[1].strides, (0,))
    # Do the reduction
    for x, y in i:
        y[...] += x
    assert_equal(b, np.sum(a, axis=1))

    # Iterator inner double loop was wrong on this one
    p = np.arange(2) + 1
    it = np.nditer([p,None],
            ['delay_bufalloc','reduce_ok','buffered','external_loop'],
            [['readonly'],['readwrite','allocate']],
            op_axes=[[-1,0],[-1,-1]],
            itershape=(2,2))
    it.operands[1].fill(0)
    it.reset()
    assert_equal(it[0], [1,2,1,2])

def test_iter_buffering_reduction_reuse_reduce_loops():
    # There was a bug triggering reuse of the reduce loop inappropriately,
    # which caused processing to happen in unnecessarily small chunks
    # and overran the buffer.

    a = np.zeros((2,7))
    b = np.zeros((1,7))
    it = np.nditer([a,b], flags=['reduce_ok', 'external_loop', 'buffered'],
                    op_flags=[['readonly'], ['readwrite']],
                    buffersize = 5)

    bufsizes = []
    for x, y in it:
        bufsizes.append(x.shape[0])
    assert_equal(bufsizes, [5,2,5,2])
    assert_equal(sum(bufsizes), a.size)

def test_iter_writemasked_badinput():
    a = np.zeros((2,3))
    b = np.zeros((3,))
    m = np.array([[True,True,False],[False,True,False]])
    m2 = np.array([True,True,False])
    m3 = np.array([0,1,1], dtype='u1')
    mbad1 = np.array([0,1,1], dtype='i1')
    mbad2 = np.array([0,1,1], dtype='f4')

    # Need an 'arraymask' if any operand is 'writemasked'
    assert_raises(ValueError, nditer, [a,m], [],
                    [['readwrite','writemasked'],['readonly']])

    # A 'writemasked' operand must not be readonly
    assert_raises(ValueError, nditer, [a,m], [],
                    [['readonly','writemasked'],['readonly','arraymask']])

    # 'writemasked' and 'arraymask' may not be used together
    assert_raises(ValueError, nditer, [a,m], [],
                    [['readonly'],['readwrite','arraymask','writemasked']])

    # 'arraymask' may only be specified once
    assert_raises(ValueError, nditer, [a,m, m2], [],
                    [['readwrite','writemasked'],
                     ['readonly','arraymask'],
                     ['readonly','arraymask']])

    # An 'arraymask' with nothing 'writemasked' also doesn't make sense
    assert_raises(ValueError, nditer, [a,m], [],
                    [['readwrite'],['readonly','arraymask']])

    # A writemasked reduction requires a similarly smaller mask
    assert_raises(ValueError, nditer, [a,b,m], ['reduce_ok'],
                    [['readonly'],
                     ['readwrite','writemasked'],
                     ['readonly','arraymask']])
    # But this should work with a smaller/equal mask to the reduction operand
    np.nditer([a,b,m2], ['reduce_ok'],
                    [['readonly'],
                     ['readwrite','writemasked'],
                     ['readonly','arraymask']])
    # The arraymask itself cannot be a reduction
    assert_raises(ValueError, nditer, [a,b,m2], ['reduce_ok'],
                    [['readonly'],
                     ['readwrite','writemasked'],
                     ['readwrite','arraymask']])

    # A uint8 mask is ok too
    np.nditer([a,m3], ['buffered'],
                    [['readwrite','writemasked'],
                     ['readonly','arraymask']],
                    op_dtypes=['f4',None],
                    casting='same_kind')
    # An int8 mask isn't ok
    assert_raises(TypeError, np.nditer, [a,mbad1], ['buffered'],
                    [['readwrite','writemasked'],
                     ['readonly','arraymask']],
                    op_dtypes=['f4',None],
                    casting='same_kind')
    # A float32 mask isn't ok
    assert_raises(TypeError, np.nditer, [a,mbad2], ['buffered'],
                    [['readwrite','writemasked'],
                     ['readonly','arraymask']],
                    op_dtypes=['f4',None],
                    casting='same_kind')

def test_iter_writemasked():
    a = np.zeros((3,), dtype='f8')
    msk = np.array([True,True,False])

    # When buffering is unused, 'writemasked' effectively does nothing.
    # It's up to the user of the iterator to obey the requested semantics.
    it = np.nditer([a,msk], [],
                [['readwrite','writemasked'],
                 ['readonly','arraymask']])
    for x, m in it:
        x[...] = 1
    # Because we violated the semantics, all the values became 1
    assert_equal(a, [1,1,1])

    # Even if buffering is enabled, we still may be accessing the array
    # directly.
    it = np.nditer([a,msk], ['buffered'],
                [['readwrite','writemasked'],
                 ['readonly','arraymask']])
    for x, m in it:
        x[...] = 2.5
    # Because we violated the semantics, all the values became 2.5
    assert_equal(a, [2.5,2.5,2.5])

    # If buffering will definitely happening, for instance because of
    # a cast, only the items selected by the mask will be copied back from
    # the buffer.
    it = np.nditer([a,msk], ['buffered'],
                [['readwrite','writemasked'],
                 ['readonly','arraymask']],
                op_dtypes=['i8',None],
                casting='unsafe')
    for x, m in it:
        x[...] = 3
    # Even though we violated the semantics, only the selected values
    # were copied back
    assert_equal(a, [3,3,2.5])

def test_iter_non_writable_attribute_deletion():
    it = np.nditer(np.ones(2))
    attr = ["value", "shape", "operands", "itviews", "has_delayed_bufalloc",
            "iterationneedsapi", "has_multi_index", "has_index", "dtypes",
            "ndim", "nop", "itersize", "finished"]

    if sys.version[:3] == '2.4':
        error = TypeError
    else:
        error = AttributeError

    for s in attr:
        assert_raises(error, delattr, it, s)


def test_iter_writable_attribute_deletion():
    it = np.nditer(np.ones(2))
    attr = [ "multi_index", "index", "iterrange", "iterindex"]
    for s in attr:
        assert_raises(AttributeError, delattr, it, s)


def test_iter_element_deletion():
    it = np.nditer(np.ones(3))
    try:
        del it[1]
        del it[1:2]
    except TypeError:
        pass
    except:
        raise AssertionError

def test_iter_allocated_array_dtypes():
    # If the dtype of an allocated output has a shape, the shape gets
    # tacked onto the end of the result.
    it = np.nditer(([1, 3, 20], None), op_dtypes=[None, ('i4', (2,))])
    for a, b in it:
        b[0] = a - 1
        b[1] = a + 1
    assert_equal(it.operands[1], [[0,2], [2,4], [19,21]])

    # Make sure this works for scalars too
    it = np.nditer((10, 2, None), op_dtypes=[None, None, ('i4', (2,2))])
    for a, b, c in it:
        c[0,0] = a - b
        c[0,1] = a + b
        c[1,0] = a * b
        c[1,1] = a / b
    assert_equal(it.operands[2], [[8, 12], [20, 5]])


def test_0d_iter():
    # Basic test for iteration of 0-d arrays:
    i = nditer([2, 3], ['multi_index'], [['readonly']]*2)
    assert_equal(i.ndim, 0)
    assert_equal(next(i), (2, 3))
    assert_equal(i.multi_index, ())
    assert_equal(i.iterindex, 0)
    assert_raises(StopIteration, next, i)
    # test reset:
    i.reset()
    assert_equal(next(i), (2, 3))
    assert_raises(StopIteration, next, i)

    # test forcing to 0-d
    i = nditer(np.arange(5), ['multi_index'], [['readonly']], op_axes=[()])
    assert_equal(i.ndim, 0)
    assert_equal(len(i), 1)
    # note that itershape=(), still behaves like None due to the conversions

    # Test a more complex buffered casting case (same as another test above)
    sdt = [('a', 'f4'), ('b', 'i8'), ('c', 'c8', (2,3)), ('d', 'O')]
    a = np.array(0.5, dtype='f4')
    i = nditer(a, ['buffered','refs_ok'], ['readonly'],
                    casting='unsafe', op_dtypes=sdt)
    vals = next(i)
    assert_equal(vals['a'], 0.5)
    assert_equal(vals['b'], 0)
    assert_equal(vals['c'], [[(0.5)]*3]*2)
    assert_equal(vals['d'], 0.5)


def test_0d_nested_iter():
    a = np.arange(12).reshape(2,3,2)
    i, j = np.nested_iters(a, [[],[1,0,2]])
    vals = []
    for x in i:
        vals.append([y for y in j])
    assert_equal(vals, [[0,1,2,3,4,5,6,7,8,9,10,11]])

    i, j = np.nested_iters(a, [[1,0,2],[]])
    vals = []
    for x in i:
        vals.append([y for y in j])
    assert_equal(vals, [[0],[1],[2],[3],[4],[5],[6],[7],[8],[9],[10],[11]])

    i, j, k = np.nested_iters(a, [[2,0], [] ,[1]])
    vals = []
    for x in i:
        for y in j:
            vals.append([z for z in k])
    assert_equal(vals, [[0,2,4],[1,3,5],[6,8,10],[7,9,11]])


if __name__ == "__main__":
    run_module_suite()
