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2862 lines
110 KiB
Python
2862 lines
110 KiB
Python
from __future__ import division, absolute_import, print_function
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import sys
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import pytest
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import numpy as np
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import numpy.core._multiarray_tests as _multiarray_tests
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from numpy import array, arange, nditer, all
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from numpy.testing import (
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assert_, assert_equal, assert_array_equal, assert_raises,
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HAS_REFCOUNT, suppress_warnings
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)
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def iter_multi_index(i):
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ret = []
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while not i.finished:
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ret.append(i.multi_index)
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i.iternext()
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return ret
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def iter_indices(i):
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ret = []
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while not i.finished:
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ret.append(i.index)
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i.iternext()
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return ret
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def iter_iterindices(i):
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ret = []
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while not i.finished:
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ret.append(i.iterindex)
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i.iternext()
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return ret
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@pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts")
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def test_iter_refcount():
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# Make sure the iterator doesn't leak
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# Basic
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a = arange(6)
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dt = np.dtype('f4').newbyteorder()
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rc_a = sys.getrefcount(a)
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rc_dt = sys.getrefcount(dt)
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with nditer(a, [],
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[['readwrite', 'updateifcopy']],
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casting='unsafe',
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op_dtypes=[dt]) as it:
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assert_(not it.iterationneedsapi)
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assert_(sys.getrefcount(a) > rc_a)
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assert_(sys.getrefcount(dt) > rc_dt)
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# del 'it'
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it = None
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assert_equal(sys.getrefcount(a), rc_a)
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assert_equal(sys.getrefcount(dt), rc_dt)
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# With a copy
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a = arange(6, dtype='f4')
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dt = np.dtype('f4')
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rc_a = sys.getrefcount(a)
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rc_dt = sys.getrefcount(dt)
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it = nditer(a, [],
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[['readwrite']],
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op_dtypes=[dt])
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rc2_a = sys.getrefcount(a)
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rc2_dt = sys.getrefcount(dt)
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it2 = it.copy()
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assert_(sys.getrefcount(a) > rc2_a)
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assert_(sys.getrefcount(dt) > rc2_dt)
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it = None
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assert_equal(sys.getrefcount(a), rc2_a)
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assert_equal(sys.getrefcount(dt), rc2_dt)
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it2 = None
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assert_equal(sys.getrefcount(a), rc_a)
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assert_equal(sys.getrefcount(dt), rc_dt)
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del it2 # avoid pyflakes unused variable warning
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def test_iter_best_order():
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# The iterator should always find the iteration order
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# with increasing memory addresses
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# Test the ordering for 1-D to 5-D shapes
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for shape in [(5,), (3, 4), (2, 3, 4), (2, 3, 4, 3), (2, 3, 2, 2, 3)]:
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a = arange(np.prod(shape))
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# Test each combination of positive and negative strides
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for dirs in range(2**len(shape)):
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dirs_index = [slice(None)]*len(shape)
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for bit in range(len(shape)):
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if ((2**bit) & dirs):
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dirs_index[bit] = slice(None, None, -1)
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dirs_index = tuple(dirs_index)
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aview = a.reshape(shape)[dirs_index]
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# C-order
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i = nditer(aview, [], [['readonly']])
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assert_equal([x for x in i], a)
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# Fortran-order
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i = nditer(aview.T, [], [['readonly']])
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assert_equal([x for x in i], a)
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# Other order
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if len(shape) > 2:
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i = nditer(aview.swapaxes(0, 1), [], [['readonly']])
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assert_equal([x for x in i], a)
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def test_iter_c_order():
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# Test forcing C order
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# Test the ordering for 1-D to 5-D shapes
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for shape in [(5,), (3, 4), (2, 3, 4), (2, 3, 4, 3), (2, 3, 2, 2, 3)]:
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a = arange(np.prod(shape))
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# Test each combination of positive and negative strides
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for dirs in range(2**len(shape)):
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dirs_index = [slice(None)]*len(shape)
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for bit in range(len(shape)):
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if ((2**bit) & dirs):
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dirs_index[bit] = slice(None, None, -1)
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dirs_index = tuple(dirs_index)
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aview = a.reshape(shape)[dirs_index]
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# C-order
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i = nditer(aview, order='C')
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assert_equal([x for x in i], aview.ravel(order='C'))
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# Fortran-order
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i = nditer(aview.T, order='C')
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assert_equal([x for x in i], aview.T.ravel(order='C'))
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# Other order
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if len(shape) > 2:
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i = nditer(aview.swapaxes(0, 1), order='C')
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assert_equal([x for x in i],
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aview.swapaxes(0, 1).ravel(order='C'))
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def test_iter_f_order():
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# Test forcing F order
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# Test the ordering for 1-D to 5-D shapes
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for shape in [(5,), (3, 4), (2, 3, 4), (2, 3, 4, 3), (2, 3, 2, 2, 3)]:
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a = arange(np.prod(shape))
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# Test each combination of positive and negative strides
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for dirs in range(2**len(shape)):
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dirs_index = [slice(None)]*len(shape)
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for bit in range(len(shape)):
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if ((2**bit) & dirs):
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dirs_index[bit] = slice(None, None, -1)
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dirs_index = tuple(dirs_index)
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aview = a.reshape(shape)[dirs_index]
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# C-order
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i = nditer(aview, order='F')
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assert_equal([x for x in i], aview.ravel(order='F'))
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# Fortran-order
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i = nditer(aview.T, order='F')
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assert_equal([x for x in i], aview.T.ravel(order='F'))
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# Other order
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if len(shape) > 2:
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i = nditer(aview.swapaxes(0, 1), order='F')
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assert_equal([x for x in i],
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aview.swapaxes(0, 1).ravel(order='F'))
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def test_iter_c_or_f_order():
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# Test forcing any contiguous (C or F) order
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# Test the ordering for 1-D to 5-D shapes
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for shape in [(5,), (3, 4), (2, 3, 4), (2, 3, 4, 3), (2, 3, 2, 2, 3)]:
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a = arange(np.prod(shape))
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# Test each combination of positive and negative strides
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for dirs in range(2**len(shape)):
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dirs_index = [slice(None)]*len(shape)
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for bit in range(len(shape)):
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if ((2**bit) & dirs):
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dirs_index[bit] = slice(None, None, -1)
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dirs_index = tuple(dirs_index)
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aview = a.reshape(shape)[dirs_index]
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# C-order
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i = nditer(aview, order='A')
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assert_equal([x for x in i], aview.ravel(order='A'))
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# Fortran-order
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i = nditer(aview.T, order='A')
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assert_equal([x for x in i], aview.T.ravel(order='A'))
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# Other order
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if len(shape) > 2:
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i = nditer(aview.swapaxes(0, 1), order='A')
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assert_equal([x for x in i],
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aview.swapaxes(0, 1).ravel(order='A'))
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def test_iter_best_order_multi_index_1d():
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# The multi-indices should be correct with any reordering
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a = arange(4)
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# 1D order
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i = nditer(a, ['multi_index'], [['readonly']])
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assert_equal(iter_multi_index(i), [(0,), (1,), (2,), (3,)])
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# 1D reversed order
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i = nditer(a[::-1], ['multi_index'], [['readonly']])
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assert_equal(iter_multi_index(i), [(3,), (2,), (1,), (0,)])
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def test_iter_best_order_multi_index_2d():
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# The multi-indices should be correct with any reordering
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a = arange(6)
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# 2D C-order
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i = nditer(a.reshape(2, 3), ['multi_index'], [['readonly']])
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assert_equal(iter_multi_index(i), [(0, 0), (0, 1), (0, 2), (1, 0), (1, 1), (1, 2)])
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# 2D Fortran-order
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i = nditer(a.reshape(2, 3).copy(order='F'), ['multi_index'], [['readonly']])
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assert_equal(iter_multi_index(i), [(0, 0), (1, 0), (0, 1), (1, 1), (0, 2), (1, 2)])
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# 2D reversed C-order
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i = nditer(a.reshape(2, 3)[::-1], ['multi_index'], [['readonly']])
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assert_equal(iter_multi_index(i), [(1, 0), (1, 1), (1, 2), (0, 0), (0, 1), (0, 2)])
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i = nditer(a.reshape(2, 3)[:, ::-1], ['multi_index'], [['readonly']])
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assert_equal(iter_multi_index(i), [(0, 2), (0, 1), (0, 0), (1, 2), (1, 1), (1, 0)])
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i = nditer(a.reshape(2, 3)[::-1, ::-1], ['multi_index'], [['readonly']])
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assert_equal(iter_multi_index(i), [(1, 2), (1, 1), (1, 0), (0, 2), (0, 1), (0, 0)])
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# 2D reversed Fortran-order
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i = nditer(a.reshape(2, 3).copy(order='F')[::-1], ['multi_index'], [['readonly']])
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assert_equal(iter_multi_index(i), [(1, 0), (0, 0), (1, 1), (0, 1), (1, 2), (0, 2)])
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i = nditer(a.reshape(2, 3).copy(order='F')[:, ::-1],
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['multi_index'], [['readonly']])
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assert_equal(iter_multi_index(i), [(0, 2), (1, 2), (0, 1), (1, 1), (0, 0), (1, 0)])
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i = nditer(a.reshape(2, 3).copy(order='F')[::-1, ::-1],
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['multi_index'], [['readonly']])
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assert_equal(iter_multi_index(i), [(1, 2), (0, 2), (1, 1), (0, 1), (1, 0), (0, 0)])
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def test_iter_best_order_multi_index_3d():
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# The multi-indices should be correct with any reordering
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a = arange(12)
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# 3D C-order
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i = nditer(a.reshape(2, 3, 2), ['multi_index'], [['readonly']])
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assert_equal(iter_multi_index(i),
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[(0, 0, 0), (0, 0, 1), (0, 1, 0), (0, 1, 1), (0, 2, 0), (0, 2, 1),
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(1, 0, 0), (1, 0, 1), (1, 1, 0), (1, 1, 1), (1, 2, 0), (1, 2, 1)])
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# 3D Fortran-order
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i = nditer(a.reshape(2, 3, 2).copy(order='F'), ['multi_index'], [['readonly']])
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assert_equal(iter_multi_index(i),
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[(0, 0, 0), (1, 0, 0), (0, 1, 0), (1, 1, 0), (0, 2, 0), (1, 2, 0),
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(0, 0, 1), (1, 0, 1), (0, 1, 1), (1, 1, 1), (0, 2, 1), (1, 2, 1)])
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# 3D reversed C-order
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i = nditer(a.reshape(2, 3, 2)[::-1], ['multi_index'], [['readonly']])
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assert_equal(iter_multi_index(i),
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[(1, 0, 0), (1, 0, 1), (1, 1, 0), (1, 1, 1), (1, 2, 0), (1, 2, 1),
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(0, 0, 0), (0, 0, 1), (0, 1, 0), (0, 1, 1), (0, 2, 0), (0, 2, 1)])
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i = nditer(a.reshape(2, 3, 2)[:, ::-1], ['multi_index'], [['readonly']])
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assert_equal(iter_multi_index(i),
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[(0, 2, 0), (0, 2, 1), (0, 1, 0), (0, 1, 1), (0, 0, 0), (0, 0, 1),
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(1, 2, 0), (1, 2, 1), (1, 1, 0), (1, 1, 1), (1, 0, 0), (1, 0, 1)])
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i = nditer(a.reshape(2, 3, 2)[:,:, ::-1], ['multi_index'], [['readonly']])
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assert_equal(iter_multi_index(i),
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[(0, 0, 1), (0, 0, 0), (0, 1, 1), (0, 1, 0), (0, 2, 1), (0, 2, 0),
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(1, 0, 1), (1, 0, 0), (1, 1, 1), (1, 1, 0), (1, 2, 1), (1, 2, 0)])
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# 3D reversed Fortran-order
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i = nditer(a.reshape(2, 3, 2).copy(order='F')[::-1],
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['multi_index'], [['readonly']])
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assert_equal(iter_multi_index(i),
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[(1, 0, 0), (0, 0, 0), (1, 1, 0), (0, 1, 0), (1, 2, 0), (0, 2, 0),
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(1, 0, 1), (0, 0, 1), (1, 1, 1), (0, 1, 1), (1, 2, 1), (0, 2, 1)])
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i = nditer(a.reshape(2, 3, 2).copy(order='F')[:, ::-1],
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['multi_index'], [['readonly']])
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assert_equal(iter_multi_index(i),
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[(0, 2, 0), (1, 2, 0), (0, 1, 0), (1, 1, 0), (0, 0, 0), (1, 0, 0),
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(0, 2, 1), (1, 2, 1), (0, 1, 1), (1, 1, 1), (0, 0, 1), (1, 0, 1)])
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i = nditer(a.reshape(2, 3, 2).copy(order='F')[:,:, ::-1],
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['multi_index'], [['readonly']])
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assert_equal(iter_multi_index(i),
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[(0, 0, 1), (1, 0, 1), (0, 1, 1), (1, 1, 1), (0, 2, 1), (1, 2, 1),
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(0, 0, 0), (1, 0, 0), (0, 1, 0), (1, 1, 0), (0, 2, 0), (1, 2, 0)])
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def test_iter_best_order_c_index_1d():
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# The C index should be correct with any reordering
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a = arange(4)
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# 1D order
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i = nditer(a, ['c_index'], [['readonly']])
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assert_equal(iter_indices(i), [0, 1, 2, 3])
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# 1D reversed order
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i = nditer(a[::-1], ['c_index'], [['readonly']])
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assert_equal(iter_indices(i), [3, 2, 1, 0])
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def test_iter_best_order_c_index_2d():
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# The C index should be correct with any reordering
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a = arange(6)
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# 2D C-order
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i = nditer(a.reshape(2, 3), ['c_index'], [['readonly']])
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assert_equal(iter_indices(i), [0, 1, 2, 3, 4, 5])
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# 2D Fortran-order
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i = nditer(a.reshape(2, 3).copy(order='F'),
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['c_index'], [['readonly']])
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assert_equal(iter_indices(i), [0, 3, 1, 4, 2, 5])
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# 2D reversed C-order
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i = nditer(a.reshape(2, 3)[::-1], ['c_index'], [['readonly']])
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assert_equal(iter_indices(i), [3, 4, 5, 0, 1, 2])
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i = nditer(a.reshape(2, 3)[:, ::-1], ['c_index'], [['readonly']])
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assert_equal(iter_indices(i), [2, 1, 0, 5, 4, 3])
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i = nditer(a.reshape(2, 3)[::-1, ::-1], ['c_index'], [['readonly']])
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assert_equal(iter_indices(i), [5, 4, 3, 2, 1, 0])
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# 2D reversed Fortran-order
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i = nditer(a.reshape(2, 3).copy(order='F')[::-1],
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['c_index'], [['readonly']])
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assert_equal(iter_indices(i), [3, 0, 4, 1, 5, 2])
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i = nditer(a.reshape(2, 3).copy(order='F')[:, ::-1],
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['c_index'], [['readonly']])
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assert_equal(iter_indices(i), [2, 5, 1, 4, 0, 3])
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i = nditer(a.reshape(2, 3).copy(order='F')[::-1, ::-1],
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['c_index'], [['readonly']])
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assert_equal(iter_indices(i), [5, 2, 4, 1, 3, 0])
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def test_iter_best_order_c_index_3d():
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# The C index should be correct with any reordering
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a = arange(12)
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# 3D C-order
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i = nditer(a.reshape(2, 3, 2), ['c_index'], [['readonly']])
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assert_equal(iter_indices(i),
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[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11])
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# 3D Fortran-order
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i = nditer(a.reshape(2, 3, 2).copy(order='F'),
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['c_index'], [['readonly']])
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assert_equal(iter_indices(i),
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[0, 6, 2, 8, 4, 10, 1, 7, 3, 9, 5, 11])
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# 3D reversed C-order
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i = nditer(a.reshape(2, 3, 2)[::-1], ['c_index'], [['readonly']])
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assert_equal(iter_indices(i),
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[6, 7, 8, 9, 10, 11, 0, 1, 2, 3, 4, 5])
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i = nditer(a.reshape(2, 3, 2)[:, ::-1], ['c_index'], [['readonly']])
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assert_equal(iter_indices(i),
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[4, 5, 2, 3, 0, 1, 10, 11, 8, 9, 6, 7])
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i = nditer(a.reshape(2, 3, 2)[:,:, ::-1], ['c_index'], [['readonly']])
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assert_equal(iter_indices(i),
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[1, 0, 3, 2, 5, 4, 7, 6, 9, 8, 11, 10])
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# 3D reversed Fortran-order
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i = nditer(a.reshape(2, 3, 2).copy(order='F')[::-1],
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['c_index'], [['readonly']])
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assert_equal(iter_indices(i),
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[6, 0, 8, 2, 10, 4, 7, 1, 9, 3, 11, 5])
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i = nditer(a.reshape(2, 3, 2).copy(order='F')[:, ::-1],
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['c_index'], [['readonly']])
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assert_equal(iter_indices(i),
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[4, 10, 2, 8, 0, 6, 5, 11, 3, 9, 1, 7])
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i = nditer(a.reshape(2, 3, 2).copy(order='F')[:,:, ::-1],
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['c_index'], [['readonly']])
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assert_equal(iter_indices(i),
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[1, 7, 3, 9, 5, 11, 0, 6, 2, 8, 4, 10])
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def test_iter_best_order_f_index_1d():
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# The Fortran index should be correct with any reordering
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a = arange(4)
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# 1D order
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i = nditer(a, ['f_index'], [['readonly']])
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assert_equal(iter_indices(i), [0, 1, 2, 3])
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# 1D reversed order
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i = nditer(a[::-1], ['f_index'], [['readonly']])
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assert_equal(iter_indices(i), [3, 2, 1, 0])
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def test_iter_best_order_f_index_2d():
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# The Fortran index should be correct with any reordering
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a = arange(6)
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# 2D C-order
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i = nditer(a.reshape(2, 3), ['f_index'], [['readonly']])
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assert_equal(iter_indices(i), [0, 2, 4, 1, 3, 5])
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# 2D Fortran-order
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i = nditer(a.reshape(2, 3).copy(order='F'),
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['f_index'], [['readonly']])
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assert_equal(iter_indices(i), [0, 1, 2, 3, 4, 5])
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# 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:
|
|
nditer([arange(2).reshape(1, 2, 1),
|
|
arange(3).reshape(1, 3),
|
|
arange(6).reshape(2, 3)],
|
|
[],
|
|
[['readonly'], ['readonly'], ['writeonly', 'no_broadcast']])
|
|
raise AssertionError('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:
|
|
nditer([arange(6).reshape(2, 3), arange(2)],
|
|
[],
|
|
[['readonly'], ['readonly']],
|
|
op_axes=[[0, 1], [0, np.newaxis]],
|
|
itershape=(4, 3))
|
|
raise AssertionError('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:
|
|
nditer([np.zeros((2, 1, 1)), np.zeros((2,))],
|
|
[],
|
|
[['writeonly', 'no_broadcast'], ['readonly']])
|
|
raise AssertionError('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'])
|
|
with i:
|
|
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_assign_mapping():
|
|
a = np.arange(24, dtype='f8').reshape(2, 3, 4).T
|
|
it = np.nditer(a, [], [['readwrite', 'updateifcopy']],
|
|
casting='same_kind', op_dtypes=[np.dtype('f4')])
|
|
with it:
|
|
it.operands[0][...] = 3
|
|
it.operands[0][...] = 14
|
|
assert_equal(a, 14)
|
|
it = np.nditer(a, [], [['readwrite', 'updateifcopy']],
|
|
casting='same_kind', op_dtypes=[np.dtype('f4')])
|
|
with it:
|
|
x = it.operands[0][-1:1]
|
|
x[...] = 14
|
|
it.operands[0][...] = -1234
|
|
assert_equal(a, -1234)
|
|
# check for no warnings on dealloc
|
|
x = None
|
|
it = None
|
|
|
|
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')])
|
|
with i:
|
|
# context manager triggers UPDATEIFCOPY on i at exit
|
|
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
|
|
assert_equal(au, [2]*6)
|
|
del i # should not raise a warning
|
|
# Byte order change by requesting NBO
|
|
a = np.arange(6, dtype='f4')
|
|
au = a.byteswap().newbyteorder()
|
|
assert_(a.dtype.byteorder != au.dtype.byteorder)
|
|
with nditer(au, [], [['readwrite', 'updateifcopy', 'nbo']],
|
|
casting='equiv') as i:
|
|
# context manager triggers UPDATEIFCOPY on i at exit
|
|
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][:] = 12345
|
|
i.operands[0][:] = 2
|
|
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
|
|
with nditer(a, [], [['readwrite', 'updateifcopy', 'aligned']]) as i:
|
|
assert_(i.operands[0].flags.aligned)
|
|
# context manager triggers UPDATEIFCOPY on i at exit
|
|
assert_equal(i.operands[0], a)
|
|
i.operands[0][:] = 3
|
|
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')])
|
|
with i:
|
|
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)
|
|
with nditer(a, [], [['readwrite', 'updateifcopy']],
|
|
casting='equiv',
|
|
op_dtypes=[np.dtype('>f4')]) as i:
|
|
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
|
|
with nditer(a, [],
|
|
[['readwrite', 'updateifcopy']],
|
|
casting='same_kind',
|
|
op_dtypes=[np.dtype('f4')]) as i:
|
|
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 WRITEBACKIFCOPY is activated at exit
|
|
i.operands[0][2, 1, 1] = -12.5
|
|
assert_(a[2, 1, 1] != -12.5)
|
|
assert_equal(a[2, 1, 1], -12.5)
|
|
|
|
a = np.arange(6, dtype='i4')[::-2]
|
|
with nditer(a, [],
|
|
[['writeonly', 'updateifcopy']],
|
|
casting='unsafe',
|
|
op_dtypes=[np.dtype('f4')]) as i:
|
|
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]
|
|
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')
|
|
if HAS_REFCOUNT:
|
|
rc = sys.getrefcount(obj)
|
|
|
|
# Need to allow references for object arrays
|
|
assert_raises(TypeError, nditer, a)
|
|
if HAS_REFCOUNT:
|
|
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
|
|
if HAS_REFCOUNT:
|
|
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
|
|
if HAS_REFCOUNT:
|
|
assert_equal(sys.getrefcount(obj), rc)
|
|
|
|
i = nditer(a.reshape(2, 2).T, ['refs_ok', 'buffered'],
|
|
['readwrite'], order='C')
|
|
with i:
|
|
for x in i:
|
|
x[...] = None
|
|
vals, i, x = [None]*3
|
|
if HAS_REFCOUNT:
|
|
assert_(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')
|
|
with i:
|
|
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')
|
|
with i:
|
|
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')
|
|
with i:
|
|
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')
|
|
with i:
|
|
ob = i[0][()]
|
|
if HAS_REFCOUNT:
|
|
rc = sys.getrefcount(ob)
|
|
for x in i:
|
|
x[...] += 1
|
|
if HAS_REFCOUNT:
|
|
assert_(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_copy_if_overlap():
|
|
# Ensure the iterator makes copies on read/write overlap, if requested
|
|
|
|
# Copy not needed, 1 op
|
|
for flag in ['readonly', 'writeonly', 'readwrite']:
|
|
a = arange(10)
|
|
i = nditer([a], ['copy_if_overlap'], [[flag]])
|
|
with i:
|
|
assert_(i.operands[0] is a)
|
|
|
|
# Copy needed, 2 ops, read-write overlap
|
|
x = arange(10)
|
|
a = x[1:]
|
|
b = x[:-1]
|
|
with nditer([a, b], ['copy_if_overlap'], [['readonly'], ['readwrite']]) as i:
|
|
assert_(not np.shares_memory(*i.operands))
|
|
|
|
# Copy not needed with elementwise, 2 ops, exactly same arrays
|
|
x = arange(10)
|
|
a = x
|
|
b = x
|
|
i = nditer([a, b], ['copy_if_overlap'], [['readonly', 'overlap_assume_elementwise'],
|
|
['readwrite', 'overlap_assume_elementwise']])
|
|
with i:
|
|
assert_(i.operands[0] is a and i.operands[1] is b)
|
|
with nditer([a, b], ['copy_if_overlap'], [['readonly'], ['readwrite']]) as i:
|
|
assert_(i.operands[0] is a and not np.shares_memory(i.operands[1], b))
|
|
|
|
# Copy not needed, 2 ops, no overlap
|
|
x = arange(10)
|
|
a = x[::2]
|
|
b = x[1::2]
|
|
i = nditer([a, b], ['copy_if_overlap'], [['readonly'], ['writeonly']])
|
|
assert_(i.operands[0] is a and i.operands[1] is b)
|
|
|
|
# Copy needed, 2 ops, read-write overlap
|
|
x = arange(4, dtype=np.int8)
|
|
a = x[3:]
|
|
b = x.view(np.int32)[:1]
|
|
with nditer([a, b], ['copy_if_overlap'], [['readonly'], ['writeonly']]) as i:
|
|
assert_(not np.shares_memory(*i.operands))
|
|
|
|
# Copy needed, 3 ops, read-write overlap
|
|
for flag in ['writeonly', 'readwrite']:
|
|
x = np.ones([10, 10])
|
|
a = x
|
|
b = x.T
|
|
c = x
|
|
with nditer([a, b, c], ['copy_if_overlap'],
|
|
[['readonly'], ['readonly'], [flag]]) as i:
|
|
a2, b2, c2 = i.operands
|
|
assert_(not np.shares_memory(a2, c2))
|
|
assert_(not np.shares_memory(b2, c2))
|
|
|
|
# Copy not needed, 3 ops, read-only overlap
|
|
x = np.ones([10, 10])
|
|
a = x
|
|
b = x.T
|
|
c = x
|
|
i = nditer([a, b, c], ['copy_if_overlap'],
|
|
[['readonly'], ['readonly'], ['readonly']])
|
|
a2, b2, c2 = i.operands
|
|
assert_(a is a2)
|
|
assert_(b is b2)
|
|
assert_(c is c2)
|
|
|
|
# Copy not needed, 3 ops, read-only overlap
|
|
x = np.ones([10, 10])
|
|
a = x
|
|
b = np.ones([10, 10])
|
|
c = x.T
|
|
i = nditer([a, b, c], ['copy_if_overlap'],
|
|
[['readonly'], ['writeonly'], ['readonly']])
|
|
a2, b2, c2 = i.operands
|
|
assert_(a is a2)
|
|
assert_(b is b2)
|
|
assert_(c is c2)
|
|
|
|
# Copy not needed, 3 ops, write-only overlap
|
|
x = np.arange(7)
|
|
a = x[:3]
|
|
b = x[3:6]
|
|
c = x[4:7]
|
|
i = nditer([a, b, c], ['copy_if_overlap'],
|
|
[['readonly'], ['writeonly'], ['writeonly']])
|
|
a2, b2, c2 = i.operands
|
|
assert_(a is a2)
|
|
assert_(b is b2)
|
|
assert_(c is c2)
|
|
|
|
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
|
|
with nditer(a, ['buffered'], order='F', casting='unsafe',
|
|
op_dtypes='f8', buffersize=5) as i:
|
|
j = i.copy()
|
|
assert_equal([x[()] for x in j], a.ravel(order='F'))
|
|
|
|
a = arange(24, dtype='<i4').reshape(2, 3, 4)
|
|
with nditer(a, ['buffered'], order='F', casting='unsafe',
|
|
op_dtypes='>f8', buffersize=5) as i:
|
|
j = i.copy()
|
|
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']])
|
|
with i:
|
|
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():
|
|
# Specifying 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
|
|
class MyNDArray(np.ndarray):
|
|
__array_priority__ = 15
|
|
|
|
# subclass vs ndarray
|
|
a = np.array([[1, 2], [3, 4]]).view(MyNDArray)
|
|
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) is not type(i.operands[2]))
|
|
assert_equal(i.operands[2].shape, (2, 2))
|
|
|
|
# If subtypes are disabled, we should get back an ndarray.
|
|
i = nditer([a, b, None], [],
|
|
[['readonly'], ['readonly'],
|
|
['writeonly', 'allocate', 'no_subtype']])
|
|
assert_equal(type(b), type(i.operands[2]))
|
|
assert_(type(a) is not type(i.operands[2]))
|
|
assert_equal(i.operands[2].shape, (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
|
|
with i:
|
|
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,))
|
|
with i:
|
|
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)
|
|
with i:
|
|
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)
|
|
with i:
|
|
for v in i:
|
|
v[...] *= 2
|
|
|
|
assert_equal(a, 2*np.arange(10, dtype='f4'))
|
|
|
|
with suppress_warnings() as sup:
|
|
sup.filter(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)
|
|
with i:
|
|
for v in i:
|
|
v[...] *= 2
|
|
|
|
assert_equal(a, 2*np.arange(10, dtype='f8'))
|
|
|
|
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)
|
|
with i:
|
|
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)
|
|
with i:
|
|
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)
|
|
with i:
|
|
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)
|
|
with i:
|
|
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)
|
|
if HAS_REFCOUNT:
|
|
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
|
|
if HAS_REFCOUNT:
|
|
assert_equal(sys.getrefcount(a[0]), rc)
|
|
|
|
# single-field struct type -> simple
|
|
sdt = [('a', 'f4')]
|
|
a = np.array([(5.5,), (8,)], dtype=sdt)
|
|
i = nditer(a, ['buffered', 'refs_ok'], ['readonly'],
|
|
casting='unsafe',
|
|
op_dtypes='i4')
|
|
assert_equal([x_[()] for x_ in i], [5, 8])
|
|
|
|
# make sure multi-field struct type -> simple doesn't work
|
|
sdt = [('a', 'f4'), ('b', 'i8'), ('d', 'O')]
|
|
a = np.array([(5.5, 7, 'test'), (8, 10, 11)], dtype=sdt)
|
|
assert_raises(ValueError, lambda: (
|
|
nditer(a, ['buffered', 'refs_ok'], ['readonly'],
|
|
casting='unsafe',
|
|
op_dtypes='i4')))
|
|
|
|
# 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((1, 2, 3), dtype=sdt2),
|
|
np.array((4, 5, 6), dtype=sdt2)])
|
|
|
|
# make sure struct type -> struct type with different
|
|
# number of fields fails
|
|
sdt1 = [('a', 'f4'), ('b', 'i8'), ('d', 'O')]
|
|
sdt2 = [('b', 'O'), ('a', 'f8')]
|
|
a = np.array([(1, 2, 3), (4, 5, 6)], dtype=sdt1)
|
|
|
|
assert_raises(ValueError, lambda : (
|
|
nditer(a, ['buffered', 'refs_ok'], ['readwrite'],
|
|
casting='unsafe',
|
|
op_dtypes=sdt2)))
|
|
|
|
|
|
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)
|
|
with i:
|
|
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)
|
|
with i:
|
|
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
|
|
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)
|
|
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], b'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], u'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)
|
|
|
|
|
|
@pytest.mark.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 = [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)
|
|
with nditer2:
|
|
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)
|
|
with nditer1:
|
|
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)
|
|
|
|
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']])
|
|
|
|
|
|
class TestIterNested(object):
|
|
|
|
def test_basic(self):
|
|
# Test nested iteration basic usage
|
|
a = arange(12).reshape(2, 3, 2)
|
|
|
|
i, j = np.nested_iters(a, [[0], [1, 2]])
|
|
vals = [list(j) for _ in i]
|
|
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 = [list(j) for _ in i]
|
|
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 = [list(j) for _ in i]
|
|
assert_equal(vals, [[0, 2, 4], [1, 3, 5], [6, 8, 10], [7, 9, 11]])
|
|
|
|
def test_reorder(self):
|
|
# 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 = [list(j) for _ in i]
|
|
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 = [list(j) for _ in i]
|
|
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 = [list(j) for _ in i]
|
|
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 = [list(j) for _ in i]
|
|
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 = [list(j) for _ in i]
|
|
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 = [list(j) for _ in i]
|
|
assert_equal(vals, [[0, 2, 4], [6, 8, 10], [1, 3, 5], [7, 9, 11]])
|
|
|
|
def test_flip_axes(self):
|
|
# 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 = [list(j) for _ in i]
|
|
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 = [list(j) for _ in i]
|
|
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 = [list(j) for _ in i]
|
|
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 = [list(j) for _ in i]
|
|
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 = [list(j) for _ in i]
|
|
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 = [list(j) for _ in i]
|
|
assert_equal(vals, [[11, 9, 7], [10, 8, 6], [5, 3, 1], [4, 2, 0]])
|
|
|
|
def test_broadcast(self):
|
|
# 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 = [list(j) for _ in i]
|
|
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 = [list(j) for _ in i]
|
|
assert_equal(vals, [[[0, 0], [1, 0]], [[0, 1], [1, 1]], [[0, 2], [1, 2]]])
|
|
|
|
def test_dtype_copy(self):
|
|
# 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 = [list(j) for _ in i]
|
|
assert_equal(vals, [[0, 1, 2], [3, 4, 5]])
|
|
vals = None
|
|
|
|
# writebackifcopy - using conext manager
|
|
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')
|
|
with i, j:
|
|
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]])
|
|
assert_equal(a, [[1, 2, 3], [4, 5, 6]])
|
|
|
|
# writebackifcopy - using close()
|
|
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.close()
|
|
j.close()
|
|
assert_equal(a, [[1, 2, 3], [4, 5, 6]])
|
|
|
|
def test_dtype_buffered(self):
|
|
# 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_0d(self):
|
|
a = np.arange(12).reshape(2, 3, 2)
|
|
i, j = np.nested_iters(a, [[], [1, 0, 2]])
|
|
vals = [list(j) for _ in i]
|
|
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 = [list(j) for _ in i]
|
|
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]])
|
|
|
|
def test_iter_nested_iters_dtype_buffered(self):
|
|
# 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')
|
|
with i, j:
|
|
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
|
|
with i:
|
|
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
|
|
with i:
|
|
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:
|
|
# Use a for loop instead of ``y[...] += x``
|
|
# (equivalent to ``y[...] = y[...].copy() + x``),
|
|
# because y has zero strides we use for the reduction
|
|
for j in range(len(y)):
|
|
y[j] += x[j]
|
|
# 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)
|
|
with it1, it2:
|
|
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]])
|
|
with i:
|
|
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
|
|
with i:
|
|
assert_equal(i[1].shape, (3,))
|
|
assert_equal(i[1].strides, (0,))
|
|
# Do the reduction
|
|
for x, y in i:
|
|
# Use a for loop instead of ``y[...] += x``
|
|
# (equivalent to ``y[...] = y[...].copy() + x``),
|
|
# because y has zero strides we use for the reduction
|
|
for j in range(len(y)):
|
|
y[j] += x[j]
|
|
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))
|
|
with it:
|
|
it.operands[1].fill(0)
|
|
it.reset()
|
|
assert_equal(it[0], [1, 2, 1, 2])
|
|
|
|
# Iterator inner loop should take argument contiguity into account
|
|
x = np.ones((7, 13, 8), np.int8)[4:6,1:11:6,1:5].transpose(1, 2, 0)
|
|
x[...] = np.arange(x.size).reshape(x.shape)
|
|
y_base = np.arange(4*4, dtype=np.int8).reshape(4, 4)
|
|
y_base_copy = y_base.copy()
|
|
y = y_base[::2,:,None]
|
|
|
|
it = np.nditer([y, x],
|
|
['buffered', 'external_loop', 'reduce_ok'],
|
|
[['readwrite'], ['readonly']])
|
|
with it:
|
|
for a, b in it:
|
|
a.fill(2)
|
|
|
|
assert_equal(y_base[1::2], y_base_copy[1::2])
|
|
assert_equal(y_base[::2], 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)
|
|
|
|
with it:
|
|
bufsizes = [x.shape[0] for x, y in it]
|
|
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']])
|
|
with it:
|
|
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']])
|
|
with it:
|
|
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')
|
|
with it:
|
|
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"]
|
|
|
|
for s in attr:
|
|
assert_raises(AttributeError, 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 Exception:
|
|
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_iter_too_large():
|
|
# The total size of the iterator must not exceed the maximum intp due
|
|
# to broadcasting. Dividing by 1024 will keep it small enough to
|
|
# give a legal array.
|
|
size = np.iinfo(np.intp).max // 1024
|
|
arr = np.lib.stride_tricks.as_strided(np.zeros(1), (size,), (0,))
|
|
assert_raises(ValueError, nditer, (arr, arr[:, None]))
|
|
# test the same for multiindex. That may get more interesting when
|
|
# removing 0 dimensional axis is allowed (since an iterator can grow then)
|
|
assert_raises(ValueError, nditer,
|
|
(arr, arr[:, None]), flags=['multi_index'])
|
|
|
|
|
|
def test_iter_too_large_with_multiindex():
|
|
# When a multi index is being tracked, the error is delayed this
|
|
# checks the delayed error messages and getting below that by
|
|
# removing an axis.
|
|
base_size = 2**10
|
|
num = 1
|
|
while base_size**num < np.iinfo(np.intp).max:
|
|
num += 1
|
|
|
|
shape_template = [1, 1] * num
|
|
arrays = []
|
|
for i in range(num):
|
|
shape = shape_template[:]
|
|
shape[i * 2] = 2**10
|
|
arrays.append(np.empty(shape))
|
|
arrays = tuple(arrays)
|
|
|
|
# arrays are now too large to be broadcast. The different modes test
|
|
# different nditer functionality with or without GIL.
|
|
for mode in range(6):
|
|
with assert_raises(ValueError):
|
|
_multiarray_tests.test_nditer_too_large(arrays, -1, mode)
|
|
# but if we do nothing with the nditer, it can be constructed:
|
|
_multiarray_tests.test_nditer_too_large(arrays, -1, 7)
|
|
|
|
# When an axis is removed, things should work again (half the time):
|
|
for i in range(num):
|
|
for mode in range(6):
|
|
# an axis with size 1024 is removed:
|
|
_multiarray_tests.test_nditer_too_large(arrays, i*2, mode)
|
|
# an axis with size 1 is removed:
|
|
with assert_raises(ValueError):
|
|
_multiarray_tests.test_nditer_too_large(arrays, i*2 + 1, mode)
|
|
|
|
def test_writebacks():
|
|
a = np.arange(6, dtype='f4')
|
|
au = a.byteswap().newbyteorder()
|
|
assert_(a.dtype.byteorder != au.dtype.byteorder)
|
|
it = nditer(au, [], [['readwrite', 'updateifcopy']],
|
|
casting='equiv', op_dtypes=[np.dtype('f4')])
|
|
with it:
|
|
it.operands[0][:] = 100
|
|
assert_equal(au, 100)
|
|
# do it again, this time raise an error,
|
|
it = nditer(au, [], [['readwrite', 'updateifcopy']],
|
|
casting='equiv', op_dtypes=[np.dtype('f4')])
|
|
try:
|
|
with it:
|
|
assert_equal(au.flags.writeable, False)
|
|
it.operands[0][:] = 0
|
|
raise ValueError('exit context manager on exception')
|
|
except:
|
|
pass
|
|
assert_equal(au, 0)
|
|
assert_equal(au.flags.writeable, True)
|
|
# cannot reuse i outside context manager
|
|
assert_raises(ValueError, getattr, it, 'operands')
|
|
|
|
it = nditer(au, [], [['readwrite', 'updateifcopy']],
|
|
casting='equiv', op_dtypes=[np.dtype('f4')])
|
|
with it:
|
|
x = it.operands[0]
|
|
x[:] = 6
|
|
assert_(x.flags.writebackifcopy)
|
|
assert_equal(au, 6)
|
|
assert_(not x.flags.writebackifcopy)
|
|
x[:] = 123 # x.data still valid
|
|
assert_equal(au, 6) # but not connected to au
|
|
|
|
it = nditer(au, [],
|
|
[['readwrite', 'updateifcopy']],
|
|
casting='equiv', op_dtypes=[np.dtype('f4')])
|
|
# reentering works
|
|
with it:
|
|
with it:
|
|
for x in it:
|
|
x[...] = 123
|
|
|
|
it = nditer(au, [],
|
|
[['readwrite', 'updateifcopy']],
|
|
casting='equiv', op_dtypes=[np.dtype('f4')])
|
|
# make sure exiting the inner context manager closes the iterator
|
|
with it:
|
|
with it:
|
|
for x in it:
|
|
x[...] = 123
|
|
assert_raises(ValueError, getattr, it, 'operands')
|
|
# do not crash if original data array is decrefed
|
|
it = nditer(au, [],
|
|
[['readwrite', 'updateifcopy']],
|
|
casting='equiv', op_dtypes=[np.dtype('f4')])
|
|
del au
|
|
with it:
|
|
for x in it:
|
|
x[...] = 123
|
|
# make sure we cannot reenter the closed iterator
|
|
enter = it.__enter__
|
|
assert_raises(RuntimeError, enter)
|
|
|
|
def test_close_equivalent():
|
|
''' using a context amanger and using nditer.close are equivalent
|
|
'''
|
|
def add_close(x, y, out=None):
|
|
addop = np.add
|
|
it = np.nditer([x, y, out], [],
|
|
[['readonly'], ['readonly'], ['writeonly','allocate']])
|
|
for (a, b, c) in it:
|
|
addop(a, b, out=c)
|
|
ret = it.operands[2]
|
|
it.close()
|
|
return ret
|
|
|
|
def add_context(x, y, out=None):
|
|
addop = np.add
|
|
it = np.nditer([x, y, out], [],
|
|
[['readonly'], ['readonly'], ['writeonly','allocate']])
|
|
with it:
|
|
for (a, b, c) in it:
|
|
addop(a, b, out=c)
|
|
return it.operands[2]
|
|
z = add_close(range(5), range(5))
|
|
assert_equal(z, range(0, 10, 2))
|
|
z = add_context(range(5), range(5))
|
|
assert_equal(z, range(0, 10, 2))
|
|
|
|
def test_close_raises():
|
|
it = np.nditer(np.arange(3))
|
|
assert_equal (next(it), 0)
|
|
it.close()
|
|
assert_raises(StopIteration, next, it)
|
|
assert_raises(ValueError, getattr, it, 'operands')
|
|
|
|
@pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts")
|
|
def test_warn_noclose():
|
|
a = np.arange(6, dtype='f4')
|
|
au = a.byteswap().newbyteorder()
|
|
with suppress_warnings() as sup:
|
|
sup.record(RuntimeWarning)
|
|
it = np.nditer(au, [], [['readwrite', 'updateifcopy']],
|
|
casting='equiv', op_dtypes=[np.dtype('f4')])
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del it
|
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assert len(sup.log) == 1
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