| Current File : //usr/lib64/python2.7/site-packages/numpy/core/tests/test_nditer.py |
import numpy as np
from numpy import array, arange, nditer, all
from numpy.compat import asbytes
from numpy.testing import *
import sys, warnings
import warnings
def iter_multi_index(i):
ret = []
while not i.finished:
ret.append(i.multi_index)
i.iternext()
return ret
def iter_indices(i):
ret = []
while not i.finished:
ret.append(i.index)
i.iternext()
return ret
def iter_iterindices(i):
ret = []
while not i.finished:
ret.append(i.iterindex)
i.iternext()
return ret
def test_iter_refcount():
# Make sure the iterator doesn't leak
# Basic
a = arange(6)
dt = np.dtype('f4').newbyteorder()
rc_a = sys.getrefcount(a)
rc_dt = sys.getrefcount(dt)
it = nditer(a, [],
[['readwrite','updateifcopy']],
casting='unsafe',
op_dtypes=[dt])
assert_(not it.iterationneedsapi)
assert_(sys.getrefcount(a) > rc_a)
assert_(sys.getrefcount(dt) > rc_dt)
it = None
assert_equal(sys.getrefcount(a), rc_a)
assert_equal(sys.getrefcount(dt), rc_dt)
# With a copy
a = arange(6, dtype='f4')
dt = np.dtype('f4')
rc_a = sys.getrefcount(a)
rc_dt = sys.getrefcount(dt)
it = nditer(a, [],
[['readwrite']],
op_dtypes=[dt])
rc2_a = sys.getrefcount(a)
rc2_dt = sys.getrefcount(dt)
it2 = it.copy()
assert_(sys.getrefcount(a) > rc2_a)
assert_(sys.getrefcount(dt) > rc2_dt)
it = None
assert_equal(sys.getrefcount(a), rc2_a)
assert_equal(sys.getrefcount(dt), rc2_dt)
it2 = None
assert_equal(sys.getrefcount(a), rc_a)
assert_equal(sys.getrefcount(dt), rc_dt)
def test_iter_best_order():
# The iterator should always find the iteration order
# with increasing memory addresses
# Test the ordering for 1-D to 5-D shapes
for shape in [(5,), (3,4), (2,3,4), (2,3,4,3), (2,3,2,2,3)]:
a = arange(np.prod(shape))
# Test each combination of positive and negative strides
for dirs in range(2**len(shape)):
dirs_index = [slice(None)]*len(shape)
for bit in range(len(shape)):
if ((2**bit)&dirs):
dirs_index[bit] = slice(None,None,-1)
dirs_index = tuple(dirs_index)
aview = a.reshape(shape)[dirs_index]
# C-order
i = nditer(aview, [], [['readonly']])
assert_equal([x for x in i], a)
# Fortran-order
i = nditer(aview.T, [], [['readonly']])
assert_equal([x for x in i], a)
# Other order
if len(shape) > 2:
i = nditer(aview.swapaxes(0,1), [], [['readonly']])
assert_equal([x for x in i], a)
def test_iter_c_order():
# Test forcing C order
# Test the ordering for 1-D to 5-D shapes
for shape in [(5,), (3,4), (2,3,4), (2,3,4,3), (2,3,2,2,3)]:
a = arange(np.prod(shape))
# Test each combination of positive and negative strides
for dirs in range(2**len(shape)):
dirs_index = [slice(None)]*len(shape)
for bit in range(len(shape)):
if ((2**bit)&dirs):
dirs_index[bit] = slice(None,None,-1)
dirs_index = tuple(dirs_index)
aview = a.reshape(shape)[dirs_index]
# C-order
i = nditer(aview, order='C')
assert_equal([x for x in i], aview.ravel(order='C'))
# Fortran-order
i = nditer(aview.T, order='C')
assert_equal([x for x in i], aview.T.ravel(order='C'))
# Other order
if len(shape) > 2:
i = nditer(aview.swapaxes(0,1), order='C')
assert_equal([x for x in i],
aview.swapaxes(0,1).ravel(order='C'))
def test_iter_f_order():
# Test forcing F order
# Test the ordering for 1-D to 5-D shapes
for shape in [(5,), (3,4), (2,3,4), (2,3,4,3), (2,3,2,2,3)]:
a = arange(np.prod(shape))
# Test each combination of positive and negative strides
for dirs in range(2**len(shape)):
dirs_index = [slice(None)]*len(shape)
for bit in range(len(shape)):
if ((2**bit)&dirs):
dirs_index[bit] = slice(None,None,-1)
dirs_index = tuple(dirs_index)
aview = a.reshape(shape)[dirs_index]
# C-order
i = nditer(aview, order='F')
assert_equal([x for x in i], aview.ravel(order='F'))
# Fortran-order
i = nditer(aview.T, order='F')
assert_equal([x for x in i], aview.T.ravel(order='F'))
# Other order
if len(shape) > 2:
i = nditer(aview.swapaxes(0,1), order='F')
assert_equal([x for x in i],
aview.swapaxes(0,1).ravel(order='F'))
def test_iter_c_or_f_order():
# Test forcing any contiguous (C or F) order
# Test the ordering for 1-D to 5-D shapes
for shape in [(5,), (3,4), (2,3,4), (2,3,4,3), (2,3,2,2,3)]:
a = arange(np.prod(shape))
# Test each combination of positive and negative strides
for dirs in range(2**len(shape)):
dirs_index = [slice(None)]*len(shape)
for bit in range(len(shape)):
if ((2**bit)&dirs):
dirs_index[bit] = slice(None,None,-1)
dirs_index = tuple(dirs_index)
aview = a.reshape(shape)[dirs_index]
# C-order
i = nditer(aview, order='A')
assert_equal([x for x in i], aview.ravel(order='A'))
# Fortran-order
i = nditer(aview.T, order='A')
assert_equal([x for x in i], aview.T.ravel(order='A'))
# Other order
if len(shape) > 2:
i = nditer(aview.swapaxes(0,1), order='A')
assert_equal([x for x in i],
aview.swapaxes(0,1).ravel(order='A'))
def test_iter_best_order_multi_index_1d():
# The multi-indices should be correct with any reordering
a = arange(4)
# 1D order
i = nditer(a,['multi_index'],[['readonly']])
assert_equal(iter_multi_index(i), [(0,),(1,),(2,),(3,)])
# 1D reversed order
i = nditer(a[::-1],['multi_index'],[['readonly']])
assert_equal(iter_multi_index(i), [(3,),(2,),(1,),(0,)])
def test_iter_best_order_multi_index_2d():
# The multi-indices should be correct with any reordering
a = arange(6)
# 2D C-order
i = nditer(a.reshape(2,3),['multi_index'],[['readonly']])
assert_equal(iter_multi_index(i), [(0,0),(0,1),(0,2),(1,0),(1,1),(1,2)])
# 2D Fortran-order
i = nditer(a.reshape(2,3).copy(order='F'),['multi_index'],[['readonly']])
assert_equal(iter_multi_index(i), [(0,0),(1,0),(0,1),(1,1),(0,2),(1,2)])
# 2D reversed C-order
i = nditer(a.reshape(2,3)[::-1],['multi_index'],[['readonly']])
assert_equal(iter_multi_index(i), [(1,0),(1,1),(1,2),(0,0),(0,1),(0,2)])
i = nditer(a.reshape(2,3)[:,::-1],['multi_index'],[['readonly']])
assert_equal(iter_multi_index(i), [(0,2),(0,1),(0,0),(1,2),(1,1),(1,0)])
i = nditer(a.reshape(2,3)[::-1,::-1],['multi_index'],[['readonly']])
assert_equal(iter_multi_index(i), [(1,2),(1,1),(1,0),(0,2),(0,1),(0,0)])
# 2D reversed Fortran-order
i = nditer(a.reshape(2,3).copy(order='F')[::-1],['multi_index'],[['readonly']])
assert_equal(iter_multi_index(i), [(1,0),(0,0),(1,1),(0,1),(1,2),(0,2)])
i = nditer(a.reshape(2,3).copy(order='F')[:,::-1],
['multi_index'],[['readonly']])
assert_equal(iter_multi_index(i), [(0,2),(1,2),(0,1),(1,1),(0,0),(1,0)])
i = nditer(a.reshape(2,3).copy(order='F')[::-1,::-1],
['multi_index'],[['readonly']])
assert_equal(iter_multi_index(i), [(1,2),(0,2),(1,1),(0,1),(1,0),(0,0)])
def test_iter_best_order_multi_index_3d():
# The multi-indices should be correct with any reordering
a = arange(12)
# 3D C-order
i = nditer(a.reshape(2,3,2),['multi_index'],[['readonly']])
assert_equal(iter_multi_index(i),
[(0,0,0),(0,0,1),(0,1,0),(0,1,1),(0,2,0),(0,2,1),
(1,0,0),(1,0,1),(1,1,0),(1,1,1),(1,2,0),(1,2,1)])
# 3D Fortran-order
i = nditer(a.reshape(2,3,2).copy(order='F'),['multi_index'],[['readonly']])
assert_equal(iter_multi_index(i),
[(0,0,0),(1,0,0),(0,1,0),(1,1,0),(0,2,0),(1,2,0),
(0,0,1),(1,0,1),(0,1,1),(1,1,1),(0,2,1),(1,2,1)])
# 3D reversed C-order
i = nditer(a.reshape(2,3,2)[::-1],['multi_index'],[['readonly']])
assert_equal(iter_multi_index(i),
[(1,0,0),(1,0,1),(1,1,0),(1,1,1),(1,2,0),(1,2,1),
(0,0,0),(0,0,1),(0,1,0),(0,1,1),(0,2,0),(0,2,1)])
i = nditer(a.reshape(2,3,2)[:,::-1],['multi_index'],[['readonly']])
assert_equal(iter_multi_index(i),
[(0,2,0),(0,2,1),(0,1,0),(0,1,1),(0,0,0),(0,0,1),
(1,2,0),(1,2,1),(1,1,0),(1,1,1),(1,0,0),(1,0,1)])
i = nditer(a.reshape(2,3,2)[:,:,::-1],['multi_index'],[['readonly']])
assert_equal(iter_multi_index(i),
[(0,0,1),(0,0,0),(0,1,1),(0,1,0),(0,2,1),(0,2,0),
(1,0,1),(1,0,0),(1,1,1),(1,1,0),(1,2,1),(1,2,0)])
# 3D reversed Fortran-order
i = nditer(a.reshape(2,3,2).copy(order='F')[::-1],
['multi_index'],[['readonly']])
assert_equal(iter_multi_index(i),
[(1,0,0),(0,0,0),(1,1,0),(0,1,0),(1,2,0),(0,2,0),
(1,0,1),(0,0,1),(1,1,1),(0,1,1),(1,2,1),(0,2,1)])
i = nditer(a.reshape(2,3,2).copy(order='F')[:,::-1],
['multi_index'],[['readonly']])
assert_equal(iter_multi_index(i),
[(0,2,0),(1,2,0),(0,1,0),(1,1,0),(0,0,0),(1,0,0),
(0,2,1),(1,2,1),(0,1,1),(1,1,1),(0,0,1),(1,0,1)])
i = nditer(a.reshape(2,3,2).copy(order='F')[:,:,::-1],
['multi_index'],[['readonly']])
assert_equal(iter_multi_index(i),
[(0,0,1),(1,0,1),(0,1,1),(1,1,1),(0,2,1),(1,2,1),
(0,0,0),(1,0,0),(0,1,0),(1,1,0),(0,2,0),(1,2,0)])
def test_iter_best_order_c_index_1d():
# The C index should be correct with any reordering
a = arange(4)
# 1D order
i = nditer(a,['c_index'],[['readonly']])
assert_equal(iter_indices(i), [0,1,2,3])
# 1D reversed order
i = nditer(a[::-1],['c_index'],[['readonly']])
assert_equal(iter_indices(i), [3,2,1,0])
def test_iter_best_order_c_index_2d():
# The C index should be correct with any reordering
a = arange(6)
# 2D C-order
i = nditer(a.reshape(2,3),['c_index'],[['readonly']])
assert_equal(iter_indices(i), [0,1,2,3,4,5])
# 2D Fortran-order
i = nditer(a.reshape(2,3).copy(order='F'),
['c_index'],[['readonly']])
assert_equal(iter_indices(i), [0,3,1,4,2,5])
# 2D reversed C-order
i = nditer(a.reshape(2,3)[::-1],['c_index'],[['readonly']])
assert_equal(iter_indices(i), [3,4,5,0,1,2])
i = nditer(a.reshape(2,3)[:,::-1],['c_index'],[['readonly']])
assert_equal(iter_indices(i), [2,1,0,5,4,3])
i = nditer(a.reshape(2,3)[::-1,::-1],['c_index'],[['readonly']])
assert_equal(iter_indices(i), [5,4,3,2,1,0])
# 2D reversed Fortran-order
i = nditer(a.reshape(2,3).copy(order='F')[::-1],
['c_index'],[['readonly']])
assert_equal(iter_indices(i), [3,0,4,1,5,2])
i = nditer(a.reshape(2,3).copy(order='F')[:,::-1],
['c_index'],[['readonly']])
assert_equal(iter_indices(i), [2,5,1,4,0,3])
i = nditer(a.reshape(2,3).copy(order='F')[::-1,::-1],
['c_index'],[['readonly']])
assert_equal(iter_indices(i), [5,2,4,1,3,0])
def test_iter_best_order_c_index_3d():
# The C index should be correct with any reordering
a = arange(12)
# 3D C-order
i = nditer(a.reshape(2,3,2),['c_index'],[['readonly']])
assert_equal(iter_indices(i),
[0,1,2,3,4,5,6,7,8,9,10,11])
# 3D Fortran-order
i = nditer(a.reshape(2,3,2).copy(order='F'),
['c_index'],[['readonly']])
assert_equal(iter_indices(i),
[0,6,2,8,4,10,1,7,3,9,5,11])
# 3D reversed C-order
i = nditer(a.reshape(2,3,2)[::-1],['c_index'],[['readonly']])
assert_equal(iter_indices(i),
[6,7,8,9,10,11,0,1,2,3,4,5])
i = nditer(a.reshape(2,3,2)[:,::-1],['c_index'],[['readonly']])
assert_equal(iter_indices(i),
[4,5,2,3,0,1,10,11,8,9,6,7])
i = nditer(a.reshape(2,3,2)[:,:,::-1],['c_index'],[['readonly']])
assert_equal(iter_indices(i),
[1,0,3,2,5,4,7,6,9,8,11,10])
# 3D reversed Fortran-order
i = nditer(a.reshape(2,3,2).copy(order='F')[::-1],
['c_index'],[['readonly']])
assert_equal(iter_indices(i),
[6,0,8,2,10,4,7,1,9,3,11,5])
i = nditer(a.reshape(2,3,2).copy(order='F')[:,::-1],
['c_index'],[['readonly']])
assert_equal(iter_indices(i),
[4,10,2,8,0,6,5,11,3,9,1,7])
i = nditer(a.reshape(2,3,2).copy(order='F')[:,:,::-1],
['c_index'],[['readonly']])
assert_equal(iter_indices(i),
[1,7,3,9,5,11,0,6,2,8,4,10])
def test_iter_best_order_f_index_1d():
# The Fortran index should be correct with any reordering
a = arange(4)
# 1D order
i = nditer(a,['f_index'],[['readonly']])
assert_equal(iter_indices(i), [0,1,2,3])
# 1D reversed order
i = nditer(a[::-1],['f_index'],[['readonly']])
assert_equal(iter_indices(i), [3,2,1,0])
def test_iter_best_order_f_index_2d():
# The Fortran index should be correct with any reordering
a = arange(6)
# 2D C-order
i = nditer(a.reshape(2,3),['f_index'],[['readonly']])
assert_equal(iter_indices(i), [0,2,4,1,3,5])
# 2D Fortran-order
i = nditer(a.reshape(2,3).copy(order='F'),
['f_index'],[['readonly']])
assert_equal(iter_indices(i), [0,1,2,3,4,5])
# 2D reversed C-order
i = nditer(a.reshape(2,3)[::-1],['f_index'],[['readonly']])
assert_equal(iter_indices(i), [1,3,5,0,2,4])
i = nditer(a.reshape(2,3)[:,::-1],['f_index'],[['readonly']])
assert_equal(iter_indices(i), [4,2,0,5,3,1])
i = nditer(a.reshape(2,3)[::-1,::-1],['f_index'],[['readonly']])
assert_equal(iter_indices(i), [5,3,1,4,2,0])
# 2D reversed Fortran-order
i = nditer(a.reshape(2,3).copy(order='F')[::-1],
['f_index'],[['readonly']])
assert_equal(iter_indices(i), [1,0,3,2,5,4])
i = nditer(a.reshape(2,3).copy(order='F')[:,::-1],
['f_index'],[['readonly']])
assert_equal(iter_indices(i), [4,5,2,3,0,1])
i = nditer(a.reshape(2,3).copy(order='F')[::-1,::-1],
['f_index'],[['readonly']])
assert_equal(iter_indices(i), [5,4,3,2,1,0])
def test_iter_best_order_f_index_3d():
# The Fortran index should be correct with any reordering
a = arange(12)
# 3D C-order
i = nditer(a.reshape(2,3,2),['f_index'],[['readonly']])
assert_equal(iter_indices(i),
[0,6,2,8,4,10,1,7,3,9,5,11])
# 3D Fortran-order
i = nditer(a.reshape(2,3,2).copy(order='F'),
['f_index'],[['readonly']])
assert_equal(iter_indices(i),
[0,1,2,3,4,5,6,7,8,9,10,11])
# 3D reversed C-order
i = nditer(a.reshape(2,3,2)[::-1],['f_index'],[['readonly']])
assert_equal(iter_indices(i),
[1,7,3,9,5,11,0,6,2,8,4,10])
i = nditer(a.reshape(2,3,2)[:,::-1],['f_index'],[['readonly']])
assert_equal(iter_indices(i),
[4,10,2,8,0,6,5,11,3,9,1,7])
i = nditer(a.reshape(2,3,2)[:,:,::-1],['f_index'],[['readonly']])
assert_equal(iter_indices(i),
[6,0,8,2,10,4,7,1,9,3,11,5])
# 3D reversed Fortran-order
i = nditer(a.reshape(2,3,2).copy(order='F')[::-1],
['f_index'],[['readonly']])
assert_equal(iter_indices(i),
[1,0,3,2,5,4,7,6,9,8,11,10])
i = nditer(a.reshape(2,3,2).copy(order='F')[:,::-1],
['f_index'],[['readonly']])
assert_equal(iter_indices(i),
[4,5,2,3,0,1,10,11,8,9,6,7])
i = nditer(a.reshape(2,3,2).copy(order='F')[:,:,::-1],
['f_index'],[['readonly']])
assert_equal(iter_indices(i),
[6,7,8,9,10,11,0,1,2,3,4,5])
def test_iter_no_inner_full_coalesce():
# Check no_inner iterators which coalesce into a single inner loop
for shape in [(5,), (3,4), (2,3,4), (2,3,4,3), (2,3,2,2,3)]:
size = np.prod(shape)
a = arange(size)
# Test each combination of forward and backwards indexing
for dirs in range(2**len(shape)):
dirs_index = [slice(None)]*len(shape)
for bit in range(len(shape)):
if ((2**bit)&dirs):
dirs_index[bit] = slice(None,None,-1)
dirs_index = tuple(dirs_index)
aview = a.reshape(shape)[dirs_index]
# C-order
i = nditer(aview, ['external_loop'], [['readonly']])
assert_equal(i.ndim, 1)
assert_equal(i[0].shape, (size,))
# Fortran-order
i = nditer(aview.T, ['external_loop'], [['readonly']])
assert_equal(i.ndim, 1)
assert_equal(i[0].shape, (size,))
# Other order
if len(shape) > 2:
i = nditer(aview.swapaxes(0,1),
['external_loop'], [['readonly']])
assert_equal(i.ndim, 1)
assert_equal(i[0].shape, (size,))
def test_iter_no_inner_dim_coalescing():
# Check no_inner iterators whose dimensions may not coalesce completely
# Skipping the last element in a dimension prevents coalescing
# with the next-bigger dimension
a = arange(24).reshape(2,3,4)[:,:,:-1]
i = nditer(a, ['external_loop'], [['readonly']])
assert_equal(i.ndim, 2)
assert_equal(i[0].shape, (3,))
a = arange(24).reshape(2,3,4)[:,:-1,:]
i = nditer(a, ['external_loop'], [['readonly']])
assert_equal(i.ndim, 2)
assert_equal(i[0].shape, (8,))
a = arange(24).reshape(2,3,4)[:-1,:,:]
i = nditer(a, ['external_loop'], [['readonly']])
assert_equal(i.ndim, 1)
assert_equal(i[0].shape, (12,))
# Even with lots of 1-sized dimensions, should still coalesce
a = arange(24).reshape(1,1,2,1,1,3,1,1,4,1,1)
i = nditer(a, ['external_loop'], [['readonly']])
assert_equal(i.ndim, 1)
assert_equal(i[0].shape, (24,))
def test_iter_dim_coalescing():
# Check that the correct number of dimensions are coalesced
# Tracking a multi-index disables coalescing
a = arange(24).reshape(2,3,4)
i = nditer(a, ['multi_index'], [['readonly']])
assert_equal(i.ndim, 3)
# A tracked index can allow coalescing if it's compatible with the array
a3d = arange(24).reshape(2,3,4)
i = nditer(a3d, ['c_index'], [['readonly']])
assert_equal(i.ndim, 1)
i = nditer(a3d.swapaxes(0,1), ['c_index'], [['readonly']])
assert_equal(i.ndim, 3)
i = nditer(a3d.T, ['c_index'], [['readonly']])
assert_equal(i.ndim, 3)
i = nditer(a3d.T, ['f_index'], [['readonly']])
assert_equal(i.ndim, 1)
i = nditer(a3d.T.swapaxes(0,1), ['f_index'], [['readonly']])
assert_equal(i.ndim, 3)
# When C or F order is forced, coalescing may still occur
a3d = arange(24).reshape(2,3,4)
i = nditer(a3d, order='C')
assert_equal(i.ndim, 1)
i = nditer(a3d.T, order='C')
assert_equal(i.ndim, 3)
i = nditer(a3d, order='F')
assert_equal(i.ndim, 3)
i = nditer(a3d.T, order='F')
assert_equal(i.ndim, 1)
i = nditer(a3d, order='A')
assert_equal(i.ndim, 1)
i = nditer(a3d.T, order='A')
assert_equal(i.ndim, 1)
def test_iter_broadcasting():
# Standard NumPy broadcasting rules
# 1D with scalar
i = nditer([arange(6), np.int32(2)], ['multi_index'], [['readonly']]*2)
assert_equal(i.itersize, 6)
assert_equal(i.shape, (6,))
# 2D with scalar
i = nditer([arange(6).reshape(2,3), np.int32(2)],
['multi_index'], [['readonly']]*2)
assert_equal(i.itersize, 6)
assert_equal(i.shape, (2,3))
# 2D with 1D
i = nditer([arange(6).reshape(2,3), arange(3)],
['multi_index'], [['readonly']]*2)
assert_equal(i.itersize, 6)
assert_equal(i.shape, (2,3))
i = nditer([arange(2).reshape(2,1), arange(3)],
['multi_index'], [['readonly']]*2)
assert_equal(i.itersize, 6)
assert_equal(i.shape, (2,3))
# 2D with 2D
i = nditer([arange(2).reshape(2,1), arange(3).reshape(1,3)],
['multi_index'], [['readonly']]*2)
assert_equal(i.itersize, 6)
assert_equal(i.shape, (2,3))
# 3D with scalar
i = nditer([np.int32(2), arange(24).reshape(4,2,3)],
['multi_index'], [['readonly']]*2)
assert_equal(i.itersize, 24)
assert_equal(i.shape, (4,2,3))
# 3D with 1D
i = nditer([arange(3), arange(24).reshape(4,2,3)],
['multi_index'], [['readonly']]*2)
assert_equal(i.itersize, 24)
assert_equal(i.shape, (4,2,3))
i = nditer([arange(3), arange(8).reshape(4,2,1)],
['multi_index'], [['readonly']]*2)
assert_equal(i.itersize, 24)
assert_equal(i.shape, (4,2,3))
# 3D with 2D
i = nditer([arange(6).reshape(2,3), arange(24).reshape(4,2,3)],
['multi_index'], [['readonly']]*2)
assert_equal(i.itersize, 24)
assert_equal(i.shape, (4,2,3))
i = nditer([arange(2).reshape(2,1), arange(24).reshape(4,2,3)],
['multi_index'], [['readonly']]*2)
assert_equal(i.itersize, 24)
assert_equal(i.shape, (4,2,3))
i = nditer([arange(3).reshape(1,3), arange(8).reshape(4,2,1)],
['multi_index'], [['readonly']]*2)
assert_equal(i.itersize, 24)
assert_equal(i.shape, (4,2,3))
# 3D with 3D
i = nditer([arange(2).reshape(1,2,1), arange(3).reshape(1,1,3),
arange(4).reshape(4,1,1)],
['multi_index'], [['readonly']]*3)
assert_equal(i.itersize, 24)
assert_equal(i.shape, (4,2,3))
i = nditer([arange(6).reshape(1,2,3), arange(4).reshape(4,1,1)],
['multi_index'], [['readonly']]*2)
assert_equal(i.itersize, 24)
assert_equal(i.shape, (4,2,3))
i = nditer([arange(24).reshape(4,2,3), arange(12).reshape(4,1,3)],
['multi_index'], [['readonly']]*2)
assert_equal(i.itersize, 24)
assert_equal(i.shape, (4,2,3))
def test_iter_itershape():
# Check that allocated outputs work with a specified shape
a = np.arange(6, dtype='i2').reshape(2,3)
i = nditer([a, None], [], [['readonly'], ['writeonly','allocate']],
op_axes=[[0,1,None], None],
itershape=(-1,-1,4))
assert_equal(i.operands[1].shape, (2,3,4))
assert_equal(i.operands[1].strides, (24,8,2))
i = nditer([a.T, None], [], [['readonly'], ['writeonly','allocate']],
op_axes=[[0,1,None], None],
itershape=(-1,-1,4))
assert_equal(i.operands[1].shape, (3,2,4))
assert_equal(i.operands[1].strides, (8,24,2))
i = nditer([a.T, None], [], [['readonly'], ['writeonly','allocate']],
order='F',
op_axes=[[0,1,None], None],
itershape=(-1,-1,4))
assert_equal(i.operands[1].shape, (3,2,4))
assert_equal(i.operands[1].strides, (2,6,12))
# If we specify 1 in the itershape, it shouldn't allow broadcasting
# of that dimension to a bigger value
assert_raises(ValueError, nditer, [a, None], [],
[['readonly'], ['writeonly','allocate']],
op_axes=[[0,1,None], None],
itershape=(-1,1,4))
# Test bug that for no op_axes but itershape, they are NULLed correctly
i = np.nditer([np.ones(2), None, None], itershape=(2,))
def test_iter_broadcasting_errors():
# Check that errors are thrown for bad broadcasting shapes
# 1D with 1D
assert_raises(ValueError, nditer, [arange(2), arange(3)],
[], [['readonly']]*2)
# 2D with 1D
assert_raises(ValueError, nditer,
[arange(6).reshape(2,3), arange(2)],
[], [['readonly']]*2)
# 2D with 2D
assert_raises(ValueError, nditer,
[arange(6).reshape(2,3), arange(9).reshape(3,3)],
[], [['readonly']]*2)
assert_raises(ValueError, nditer,
[arange(6).reshape(2,3), arange(4).reshape(2,2)],
[], [['readonly']]*2)
# 3D with 3D
assert_raises(ValueError, nditer,
[arange(36).reshape(3,3,4), arange(24).reshape(2,3,4)],
[], [['readonly']]*2)
assert_raises(ValueError, nditer,
[arange(8).reshape(2,4,1), arange(24).reshape(2,3,4)],
[], [['readonly']]*2)
# Verify that the error message mentions the right shapes
try:
i = nditer([arange(2).reshape(1,2,1),
arange(3).reshape(1,3),
arange(6).reshape(2,3)],
[],
[['readonly'], ['readonly'], ['writeonly','no_broadcast']])
assert_(False, 'Should have raised a broadcast error')
except ValueError, e:
msg = str(e)
# The message should contain the shape of the 3rd operand
assert_(msg.find('(2,3)') >= 0,
'Message "%s" doesn\'t contain operand shape (2,3)' % msg)
# The message should contain the broadcast shape
assert_(msg.find('(1,2,3)') >= 0,
'Message "%s" doesn\'t contain broadcast shape (1,2,3)' % msg)
try:
i = nditer([arange(6).reshape(2,3), arange(2)], [],
[['readonly'],['readonly']],
op_axes=[[0,1], [0,np.newaxis]],
itershape=(4,3))
assert_(False, 'Should have raised a broadcast error')
except ValueError, e:
msg = str(e)
# The message should contain "shape->remappedshape" for each operand
assert_(msg.find('(2,3)->(2,3)') >= 0,
'Message "%s" doesn\'t contain operand shape (2,3)->(2,3)' % msg)
assert_(msg.find('(2)->(2,newaxis)') >= 0,
('Message "%s" doesn\'t contain remapped operand shape' +
'(2)->(2,newaxis)') % msg)
# The message should contain the itershape parameter
assert_(msg.find('(4,3)') >= 0,
'Message "%s" doesn\'t contain itershape parameter (4,3)' % msg)
try:
i = nditer([np.zeros((2,1,1)), np.zeros((2,))],
[],
[['writeonly','no_broadcast'], ['readonly']])
assert_(False, 'Should have raised a broadcast error')
except ValueError, e:
msg = str(e)
# The message should contain the shape of the bad operand
assert_(msg.find('(2,1,1)') >= 0,
'Message "%s" doesn\'t contain operand shape (2,1,1)' % msg)
# The message should contain the broadcast shape
assert_(msg.find('(2,1,2)') >= 0,
'Message "%s" doesn\'t contain the broadcast shape (2,1,2)' % msg)
def test_iter_flags_errors():
# Check that bad combinations of flags produce errors
a = arange(6)
# Not enough operands
assert_raises(ValueError, nditer, [], [], [])
# Too many operands
assert_raises(ValueError, nditer, [a]*100, [], [['readonly']]*100)
# Bad global flag
assert_raises(ValueError, nditer, [a], ['bad flag'], [['readonly']])
# Bad op flag
assert_raises(ValueError, nditer, [a], [], [['readonly','bad flag']])
# Bad order parameter
assert_raises(ValueError, nditer, [a], [], [['readonly']], order='G')
# Bad casting parameter
assert_raises(ValueError, nditer, [a], [], [['readonly']], casting='noon')
# op_flags must match ops
assert_raises(ValueError, nditer, [a]*3, [], [['readonly']]*2)
# Cannot track both a C and an F index
assert_raises(ValueError, nditer, a,
['c_index','f_index'], [['readonly']])
# Inner iteration and multi-indices/indices are incompatible
assert_raises(ValueError, nditer, a,
['external_loop','multi_index'], [['readonly']])
assert_raises(ValueError, nditer, a,
['external_loop','c_index'], [['readonly']])
assert_raises(ValueError, nditer, a,
['external_loop','f_index'], [['readonly']])
# Must specify exactly one of readwrite/readonly/writeonly per operand
assert_raises(ValueError, nditer, a, [], [[]])
assert_raises(ValueError, nditer, a, [], [['readonly','writeonly']])
assert_raises(ValueError, nditer, a, [], [['readonly','readwrite']])
assert_raises(ValueError, nditer, a, [], [['writeonly','readwrite']])
assert_raises(ValueError, nditer, a,
[], [['readonly','writeonly','readwrite']])
# Python scalars are always readonly
assert_raises(TypeError, nditer, 1.5, [], [['writeonly']])
assert_raises(TypeError, nditer, 1.5, [], [['readwrite']])
# Array scalars are always readonly
assert_raises(TypeError, nditer, np.int32(1), [], [['writeonly']])
assert_raises(TypeError, nditer, np.int32(1), [], [['readwrite']])
# Check readonly array
a.flags.writeable = False
assert_raises(ValueError, nditer, a, [], [['writeonly']])
assert_raises(ValueError, nditer, a, [], [['readwrite']])
a.flags.writeable = True
# Multi-indices available only with the multi_index flag
i = nditer(arange(6), [], [['readonly']])
assert_raises(ValueError, lambda i:i.multi_index, i)
# Index available only with an index flag
assert_raises(ValueError, lambda i:i.index, i)
# GotoCoords and GotoIndex incompatible with buffering or no_inner
def assign_multi_index(i):
i.multi_index = (0,)
def assign_index(i):
i.index = 0
def assign_iterindex(i):
i.iterindex = 0;
def assign_iterrange(i):
i.iterrange = (0,1);
i = nditer(arange(6), ['external_loop'])
assert_raises(ValueError, assign_multi_index, i)
assert_raises(ValueError, assign_index, i)
assert_raises(ValueError, assign_iterindex, i)
assert_raises(ValueError, assign_iterrange, i)
i = nditer(arange(6), ['buffered'])
assert_raises(ValueError, assign_multi_index, i)
assert_raises(ValueError, assign_index, i)
assert_raises(ValueError, assign_iterrange, i)
# Can't iterate if size is zero
assert_raises(ValueError, nditer, np.array([]))
def test_iter_slice():
a, b, c = np.arange(3), np.arange(3), np.arange(3.)
i = nditer([a,b,c], [], ['readwrite'])
i[0:2] = (3,3)
assert_equal(a, [3,1,2])
assert_equal(b, [3,1,2])
assert_equal(c, [0,1,2])
i[1] = 12
assert_equal(i[0:2], [3,12])
def test_iter_nbo_align_contig():
# Check that byte order, alignment, and contig changes work
# Byte order change by requesting a specific dtype
a = np.arange(6, dtype='f4')
au = a.byteswap().newbyteorder()
assert_(a.dtype.byteorder != au.dtype.byteorder)
i = nditer(au, [], [['readwrite','updateifcopy']],
casting='equiv',
op_dtypes=[np.dtype('f4')])
assert_equal(i.dtypes[0].byteorder, a.dtype.byteorder)
assert_equal(i.operands[0].dtype.byteorder, a.dtype.byteorder)
assert_equal(i.operands[0], a)
i.operands[0][:] = 2
i = None
assert_equal(au, [2]*6)
# Byte order change by requesting NBO
a = np.arange(6, dtype='f4')
au = a.byteswap().newbyteorder()
assert_(a.dtype.byteorder != au.dtype.byteorder)
i = nditer(au, [], [['readwrite','updateifcopy','nbo']], casting='equiv')
assert_equal(i.dtypes[0].byteorder, a.dtype.byteorder)
assert_equal(i.operands[0].dtype.byteorder, a.dtype.byteorder)
assert_equal(i.operands[0], a)
i.operands[0][:] = 2
i = None
assert_equal(au, [2]*6)
# Unaligned input
a = np.zeros((6*4+1,), dtype='i1')[1:]
a.dtype = 'f4'
a[:] = np.arange(6, dtype='f4')
assert_(not a.flags.aligned)
# Without 'aligned', shouldn't copy
i = nditer(a, [], [['readonly']])
assert_(not i.operands[0].flags.aligned)
assert_equal(i.operands[0], a);
# With 'aligned', should make a copy
i = nditer(a, [], [['readwrite','updateifcopy','aligned']])
assert_(i.operands[0].flags.aligned)
assert_equal(i.operands[0], a);
i.operands[0][:] = 3
i = None
assert_equal(a, [3]*6)
# Discontiguous input
a = arange(12)
# If it is contiguous, shouldn't copy
i = nditer(a[:6], [], [['readonly']])
assert_(i.operands[0].flags.contiguous)
assert_equal(i.operands[0], a[:6]);
# If it isn't contiguous, should buffer
i = nditer(a[::2], ['buffered','external_loop'],
[['readonly','contig']],
buffersize=10)
assert_(i[0].flags.contiguous)
assert_equal(i[0], a[::2])
def test_iter_array_cast():
# Check that arrays are cast as requested
# No cast 'f4' -> 'f4'
a = np.arange(6, dtype='f4').reshape(2,3)
i = nditer(a, [], [['readwrite']], op_dtypes=[np.dtype('f4')])
assert_equal(i.operands[0], a)
assert_equal(i.operands[0].dtype, np.dtype('f4'))
# Byte-order cast '<f4' -> '>f4'
a = np.arange(6, dtype='<f4').reshape(2,3)
i = nditer(a, [], [['readwrite','updateifcopy']],
casting='equiv',
op_dtypes=[np.dtype('>f4')])
assert_equal(i.operands[0], a)
assert_equal(i.operands[0].dtype, np.dtype('>f4'))
# Safe case 'f4' -> 'f8'
a = np.arange(24, dtype='f4').reshape(2,3,4).swapaxes(1,2)
i = nditer(a, [], [['readonly','copy']],
casting='safe',
op_dtypes=[np.dtype('f8')])
assert_equal(i.operands[0], a)
assert_equal(i.operands[0].dtype, np.dtype('f8'))
# The memory layout of the temporary should match a (a is (48,4,16))
# except negative strides get flipped to positive strides.
assert_equal(i.operands[0].strides, (96,8,32))
a = a[::-1,:,::-1]
i = nditer(a, [], [['readonly','copy']],
casting='safe',
op_dtypes=[np.dtype('f8')])
assert_equal(i.operands[0], a)
assert_equal(i.operands[0].dtype, np.dtype('f8'))
assert_equal(i.operands[0].strides, (96,8,32))
# Same-kind cast 'f8' -> 'f4' -> 'f8'
a = np.arange(24, dtype='f8').reshape(2,3,4).T
i = nditer(a, [],
[['readwrite','updateifcopy']],
casting='same_kind',
op_dtypes=[np.dtype('f4')])
assert_equal(i.operands[0], a)
assert_equal(i.operands[0].dtype, np.dtype('f4'))
assert_equal(i.operands[0].strides, (4, 16, 48))
# Check that UPDATEIFCOPY is activated
i.operands[0][2,1,1] = -12.5
assert_(a[2,1,1] != -12.5)
i = None
assert_equal(a[2,1,1], -12.5)
a = np.arange(6, dtype='i4')[::-2]
i = nditer(a, [],
[['writeonly','updateifcopy']],
casting='unsafe',
op_dtypes=[np.dtype('f4')])
assert_equal(i.operands[0].dtype, np.dtype('f4'))
# Even though the stride was negative in 'a', it
# becomes positive in the temporary
assert_equal(i.operands[0].strides, (4,))
i.operands[0][:] = [1,2,3]
i = None
assert_equal(a, [1,2,3])
def test_iter_array_cast_errors():
# Check that invalid casts are caught
# Need to enable copying for casts to occur
assert_raises(TypeError, nditer, arange(2,dtype='f4'), [],
[['readonly']], op_dtypes=[np.dtype('f8')])
# Also need to allow casting for casts to occur
assert_raises(TypeError, nditer, arange(2,dtype='f4'), [],
[['readonly','copy']], casting='no',
op_dtypes=[np.dtype('f8')])
assert_raises(TypeError, nditer, arange(2,dtype='f4'), [],
[['readonly','copy']], casting='equiv',
op_dtypes=[np.dtype('f8')])
assert_raises(TypeError, nditer, arange(2,dtype='f8'), [],
[['writeonly','updateifcopy']],
casting='no',
op_dtypes=[np.dtype('f4')])
assert_raises(TypeError, nditer, arange(2,dtype='f8'), [],
[['writeonly','updateifcopy']],
casting='equiv',
op_dtypes=[np.dtype('f4')])
# '<f4' -> '>f4' should not work with casting='no'
assert_raises(TypeError, nditer, arange(2,dtype='<f4'), [],
[['readonly','copy']], casting='no',
op_dtypes=[np.dtype('>f4')])
# 'f4' -> 'f8' is a safe cast, but 'f8' -> 'f4' isn't
assert_raises(TypeError, nditer, arange(2,dtype='f4'), [],
[['readwrite','updateifcopy']],
casting='safe',
op_dtypes=[np.dtype('f8')])
assert_raises(TypeError, nditer, arange(2,dtype='f8'), [],
[['readwrite','updateifcopy']],
casting='safe',
op_dtypes=[np.dtype('f4')])
# 'f4' -> 'i4' is neither a safe nor a same-kind cast
assert_raises(TypeError, nditer, arange(2,dtype='f4'), [],
[['readonly','copy']],
casting='same_kind',
op_dtypes=[np.dtype('i4')])
assert_raises(TypeError, nditer, arange(2,dtype='i4'), [],
[['writeonly','updateifcopy']],
casting='same_kind',
op_dtypes=[np.dtype('f4')])
def test_iter_scalar_cast():
# Check that scalars are cast as requested
# No cast 'f4' -> 'f4'
i = nditer(np.float32(2.5), [], [['readonly']],
op_dtypes=[np.dtype('f4')])
assert_equal(i.dtypes[0], np.dtype('f4'))
assert_equal(i.value.dtype, np.dtype('f4'))
assert_equal(i.value, 2.5)
# Safe cast 'f4' -> 'f8'
i = nditer(np.float32(2.5), [],
[['readonly','copy']],
casting='safe',
op_dtypes=[np.dtype('f8')])
assert_equal(i.dtypes[0], np.dtype('f8'))
assert_equal(i.value.dtype, np.dtype('f8'))
assert_equal(i.value, 2.5)
# Same-kind cast 'f8' -> 'f4'
i = nditer(np.float64(2.5), [],
[['readonly','copy']],
casting='same_kind',
op_dtypes=[np.dtype('f4')])
assert_equal(i.dtypes[0], np.dtype('f4'))
assert_equal(i.value.dtype, np.dtype('f4'))
assert_equal(i.value, 2.5)
# Unsafe cast 'f8' -> 'i4'
i = nditer(np.float64(3.0), [],
[['readonly','copy']],
casting='unsafe',
op_dtypes=[np.dtype('i4')])
assert_equal(i.dtypes[0], np.dtype('i4'))
assert_equal(i.value.dtype, np.dtype('i4'))
assert_equal(i.value, 3)
# Readonly scalars may be cast even without setting COPY or BUFFERED
i = nditer(3, [], [['readonly']], op_dtypes=[np.dtype('f8')])
assert_equal(i[0].dtype, np.dtype('f8'))
assert_equal(i[0], 3.)
def test_iter_scalar_cast_errors():
# Check that invalid casts are caught
# Need to allow copying/buffering for write casts of scalars to occur
assert_raises(TypeError, nditer, np.float32(2), [],
[['readwrite']], op_dtypes=[np.dtype('f8')])
assert_raises(TypeError, nditer, 2.5, [],
[['readwrite']], op_dtypes=[np.dtype('f4')])
# 'f8' -> 'f4' isn't a safe cast if the value would overflow
assert_raises(TypeError, nditer, np.float64(1e60), [],
[['readonly']],
casting='safe',
op_dtypes=[np.dtype('f4')])
# 'f4' -> 'i4' is neither a safe nor a same-kind cast
assert_raises(TypeError, nditer, np.float32(2), [],
[['readonly']],
casting='same_kind',
op_dtypes=[np.dtype('i4')])
def test_iter_object_arrays_basic():
# Check that object arrays work
obj = {'a':3,'b':'d'}
a = np.array([[1,2,3], None, obj, None], dtype='O')
rc = sys.getrefcount(obj)
# Need to allow references for object arrays
assert_raises(TypeError, nditer, a)
assert_equal(sys.getrefcount(obj), rc)
i = nditer(a, ['refs_ok'], ['readonly'])
vals = [x[()] for x in i]
assert_equal(np.array(vals, dtype='O'), a)
vals, i, x = [None]*3
assert_equal(sys.getrefcount(obj), rc)
i = nditer(a.reshape(2,2).T, ['refs_ok','buffered'],
['readonly'], order='C')
assert_(i.iterationneedsapi)
vals = [x[()] for x in i]
assert_equal(np.array(vals, dtype='O'), a.reshape(2,2).ravel(order='F'))
vals, i, x = [None]*3
assert_equal(sys.getrefcount(obj), rc)
i = nditer(a.reshape(2,2).T, ['refs_ok','buffered'],
['readwrite'], order='C')
for x in i:
x[...] = None
vals, i, x = [None]*3
assert_equal(sys.getrefcount(obj), rc-1)
assert_equal(a, np.array([None]*4, dtype='O'))
def test_iter_object_arrays_conversions():
# Conversions to/from objects
a = np.arange(6, dtype='O')
i = nditer(a, ['refs_ok','buffered'], ['readwrite'],
casting='unsafe', op_dtypes='i4')
for x in i:
x[...] += 1
assert_equal(a, np.arange(6)+1)
a = np.arange(6, dtype='i4')
i = nditer(a, ['refs_ok','buffered'], ['readwrite'],
casting='unsafe', op_dtypes='O')
for x in i:
x[...] += 1
assert_equal(a, np.arange(6)+1)
# Non-contiguous object array
a = np.zeros((6,), dtype=[('p','i1'),('a','O')])
a = a['a']
a[:] = np.arange(6)
i = nditer(a, ['refs_ok','buffered'], ['readwrite'],
casting='unsafe', op_dtypes='i4')
for x in i:
x[...] += 1
assert_equal(a, np.arange(6)+1)
#Non-contiguous value array
a = np.zeros((6,), dtype=[('p','i1'),('a','i4')])
a = a['a']
a[:] = np.arange(6) + 98172488
i = nditer(a, ['refs_ok','buffered'], ['readwrite'],
casting='unsafe', op_dtypes='O')
ob = i[0][()]
rc = sys.getrefcount(ob)
for x in i:
x[...] += 1
assert_equal(sys.getrefcount(ob), rc-1)
assert_equal(a, np.arange(6)+98172489)
def test_iter_common_dtype():
# Check that the iterator finds a common data type correctly
i = nditer([array([3],dtype='f4'),array([0],dtype='f8')],
['common_dtype'],
[['readonly','copy']]*2,
casting='safe')
assert_equal(i.dtypes[0], np.dtype('f8'));
assert_equal(i.dtypes[1], np.dtype('f8'));
i = nditer([array([3],dtype='i4'),array([0],dtype='f4')],
['common_dtype'],
[['readonly','copy']]*2,
casting='safe')
assert_equal(i.dtypes[0], np.dtype('f8'));
assert_equal(i.dtypes[1], np.dtype('f8'));
i = nditer([array([3],dtype='f4'),array(0,dtype='f8')],
['common_dtype'],
[['readonly','copy']]*2,
casting='same_kind')
assert_equal(i.dtypes[0], np.dtype('f4'));
assert_equal(i.dtypes[1], np.dtype('f4'));
i = nditer([array([3],dtype='u4'),array(0,dtype='i4')],
['common_dtype'],
[['readonly','copy']]*2,
casting='safe')
assert_equal(i.dtypes[0], np.dtype('u4'));
assert_equal(i.dtypes[1], np.dtype('u4'));
i = nditer([array([3],dtype='u4'),array(-12,dtype='i4')],
['common_dtype'],
[['readonly','copy']]*2,
casting='safe')
assert_equal(i.dtypes[0], np.dtype('i8'));
assert_equal(i.dtypes[1], np.dtype('i8'));
i = nditer([array([3],dtype='u4'),array(-12,dtype='i4'),
array([2j],dtype='c8'),array([9],dtype='f8')],
['common_dtype'],
[['readonly','copy']]*4,
casting='safe')
assert_equal(i.dtypes[0], np.dtype('c16'));
assert_equal(i.dtypes[1], np.dtype('c16'));
assert_equal(i.dtypes[2], np.dtype('c16'));
assert_equal(i.dtypes[3], np.dtype('c16'));
assert_equal(i.value, (3,-12,2j,9))
# When allocating outputs, other outputs aren't factored in
i = nditer([array([3],dtype='i4'),None,array([2j],dtype='c16')], [],
[['readonly','copy'],
['writeonly','allocate'],
['writeonly']],
casting='safe')
assert_equal(i.dtypes[0], np.dtype('i4'));
assert_equal(i.dtypes[1], np.dtype('i4'));
assert_equal(i.dtypes[2], np.dtype('c16'));
# But, if common data types are requested, they are
i = nditer([array([3],dtype='i4'),None,array([2j],dtype='c16')],
['common_dtype'],
[['readonly','copy'],
['writeonly','allocate'],
['writeonly']],
casting='safe')
assert_equal(i.dtypes[0], np.dtype('c16'));
assert_equal(i.dtypes[1], np.dtype('c16'));
assert_equal(i.dtypes[2], np.dtype('c16'));
def test_iter_op_axes():
# Check that custom axes work
# Reverse the axes
a = arange(6).reshape(2,3)
i = nditer([a,a.T], [], [['readonly']]*2, op_axes=[[0,1],[1,0]])
assert_(all([x==y for (x,y) in i]))
a = arange(24).reshape(2,3,4)
i = nditer([a.T,a], [], [['readonly']]*2, op_axes=[[2,1,0],None])
assert_(all([x==y for (x,y) in i]))
# Broadcast 1D to any dimension
a = arange(1,31).reshape(2,3,5)
b = arange(1,3)
i = nditer([a,b], [], [['readonly']]*2, op_axes=[None,[0,-1,-1]])
assert_equal([x*y for (x,y) in i], (a*b.reshape(2,1,1)).ravel())
b = arange(1,4)
i = nditer([a,b], [], [['readonly']]*2, op_axes=[None,[-1,0,-1]])
assert_equal([x*y for (x,y) in i], (a*b.reshape(1,3,1)).ravel())
b = arange(1,6)
i = nditer([a,b], [], [['readonly']]*2,
op_axes=[None,[np.newaxis,np.newaxis,0]])
assert_equal([x*y for (x,y) in i], (a*b.reshape(1,1,5)).ravel())
# Inner product-style broadcasting
a = arange(24).reshape(2,3,4)
b = arange(40).reshape(5,2,4)
i = nditer([a,b], ['multi_index'], [['readonly']]*2,
op_axes=[[0,1,-1,-1],[-1,-1,0,1]])
assert_equal(i.shape, (2,3,5,2))
# Matrix product-style broadcasting
a = arange(12).reshape(3,4)
b = arange(20).reshape(4,5)
i = nditer([a,b], ['multi_index'], [['readonly']]*2,
op_axes=[[0,-1],[-1,1]])
assert_equal(i.shape, (3,5))
def test_iter_op_axes_errors():
# Check that custom axes throws errors for bad inputs
# Wrong number of items in op_axes
a = arange(6).reshape(2,3)
assert_raises(ValueError, nditer, [a,a], [], [['readonly']]*2,
op_axes=[[0],[1],[0]])
# Out of bounds items in op_axes
assert_raises(ValueError, nditer, [a,a], [], [['readonly']]*2,
op_axes=[[2,1],[0,1]])
assert_raises(ValueError, nditer, [a,a], [], [['readonly']]*2,
op_axes=[[0,1],[2,-1]])
# Duplicate items in op_axes
assert_raises(ValueError, nditer, [a,a], [], [['readonly']]*2,
op_axes=[[0,0],[0,1]])
assert_raises(ValueError, nditer, [a,a], [], [['readonly']]*2,
op_axes=[[0,1],[1,1]])
# Different sized arrays in op_axes
assert_raises(ValueError, nditer, [a,a], [], [['readonly']]*2,
op_axes=[[0,1],[0,1,0]])
# Non-broadcastable dimensions in the result
assert_raises(ValueError, nditer, [a,a], [], [['readonly']]*2,
op_axes=[[0,1],[1,0]])
def test_iter_copy():
# Check that copying the iterator works correctly
a = arange(24).reshape(2,3,4)
# Simple iterator
i = nditer(a)
j = i.copy()
assert_equal([x[()] for x in i], [x[()] for x in j])
i.iterindex = 3
j = i.copy()
assert_equal([x[()] for x in i], [x[()] for x in j])
# Buffered iterator
i = nditer(a, ['buffered','ranged'], order='F', buffersize=3)
j = i.copy()
assert_equal([x[()] for x in i], [x[()] for x in j])
i.iterindex = 3
j = i.copy()
assert_equal([x[()] for x in i], [x[()] for x in j])
i.iterrange = (3,9)
j = i.copy()
assert_equal([x[()] for x in i], [x[()] for x in j])
i.iterrange = (2,18)
i.next(); i.next()
j = i.copy()
assert_equal([x[()] for x in i], [x[()] for x in j])
# Casting iterator
i = nditer(a, ['buffered'], order='F', casting='unsafe',
op_dtypes='f8', buffersize=5)
j = i.copy()
i = None
assert_equal([x[()] for x in j], a.ravel(order='F'))
a = arange(24, dtype='<i4').reshape(2,3,4)
i = nditer(a, ['buffered'], order='F', casting='unsafe',
op_dtypes='>f8', buffersize=5)
j = i.copy()
i = None
assert_equal([x[()] for x in j], a.ravel(order='F'))
def test_iter_allocate_output_simple():
# Check that the iterator will properly allocate outputs
# Simple case
a = arange(6)
i = nditer([a,None], [], [['readonly'],['writeonly','allocate']],
op_dtypes=[None,np.dtype('f4')])
assert_equal(i.operands[1].shape, a.shape)
assert_equal(i.operands[1].dtype, np.dtype('f4'))
def test_iter_allocate_output_buffered_readwrite():
# Allocated output with buffering + delay_bufalloc
a = arange(6)
i = nditer([a,None], ['buffered','delay_bufalloc'],
[['readonly'],['allocate','readwrite']])
i.operands[1][:] = 1
i.reset()
for x in i:
x[1][...] += x[0][...]
assert_equal(i.operands[1], a+1)
def test_iter_allocate_output_itorder():
# The allocated output should match the iteration order
# C-order input, best iteration order
a = arange(6, dtype='i4').reshape(2,3)
i = nditer([a,None], [], [['readonly'],['writeonly','allocate']],
op_dtypes=[None,np.dtype('f4')])
assert_equal(i.operands[1].shape, a.shape)
assert_equal(i.operands[1].strides, a.strides)
assert_equal(i.operands[1].dtype, np.dtype('f4'))
# F-order input, best iteration order
a = arange(24, dtype='i4').reshape(2,3,4).T
i = nditer([a,None], [], [['readonly'],['writeonly','allocate']],
op_dtypes=[None,np.dtype('f4')])
assert_equal(i.operands[1].shape, a.shape)
assert_equal(i.operands[1].strides, a.strides)
assert_equal(i.operands[1].dtype, np.dtype('f4'))
# Non-contiguous input, C iteration order
a = arange(24, dtype='i4').reshape(2,3,4).swapaxes(0,1)
i = nditer([a,None], [],
[['readonly'],['writeonly','allocate']],
order='C',
op_dtypes=[None,np.dtype('f4')])
assert_equal(i.operands[1].shape, a.shape)
assert_equal(i.operands[1].strides, (32,16,4))
assert_equal(i.operands[1].dtype, np.dtype('f4'))
def test_iter_allocate_output_opaxes():
# Specifing op_axes should work
a = arange(24, dtype='i4').reshape(2,3,4)
i = nditer([None,a], [], [['writeonly','allocate'],['readonly']],
op_dtypes=[np.dtype('u4'),None],
op_axes=[[1,2,0],None]);
assert_equal(i.operands[0].shape, (4,2,3))
assert_equal(i.operands[0].strides, (4,48,16))
assert_equal(i.operands[0].dtype, np.dtype('u4'))
def test_iter_allocate_output_types_promotion():
# Check type promotion of automatic outputs
i = nditer([array([3],dtype='f4'),array([0],dtype='f8'),None], [],
[['readonly']]*2+[['writeonly','allocate']])
assert_equal(i.dtypes[2], np.dtype('f8'));
i = nditer([array([3],dtype='i4'),array([0],dtype='f4'),None], [],
[['readonly']]*2+[['writeonly','allocate']])
assert_equal(i.dtypes[2], np.dtype('f8'));
i = nditer([array([3],dtype='f4'),array(0,dtype='f8'),None], [],
[['readonly']]*2+[['writeonly','allocate']])
assert_equal(i.dtypes[2], np.dtype('f4'));
i = nditer([array([3],dtype='u4'),array(0,dtype='i4'),None], [],
[['readonly']]*2+[['writeonly','allocate']])
assert_equal(i.dtypes[2], np.dtype('u4'));
i = nditer([array([3],dtype='u4'),array(-12,dtype='i4'),None], [],
[['readonly']]*2+[['writeonly','allocate']])
assert_equal(i.dtypes[2], np.dtype('i8'));
def test_iter_allocate_output_types_byte_order():
# Verify the rules for byte order changes
# When there's just one input, the output type exactly matches
a = array([3],dtype='u4').newbyteorder()
i = nditer([a,None], [],
[['readonly'],['writeonly','allocate']])
assert_equal(i.dtypes[0], i.dtypes[1]);
# With two or more inputs, the output type is in native byte order
i = nditer([a,a,None], [],
[['readonly'],['readonly'],['writeonly','allocate']])
assert_(i.dtypes[0] != i.dtypes[2]);
assert_equal(i.dtypes[0].newbyteorder('='), i.dtypes[2])
def test_iter_allocate_output_types_scalar():
# If the inputs are all scalars, the output should be a scalar
i = nditer([None,1,2.3,np.float32(12),np.complex128(3)],[],
[['writeonly','allocate']] + [['readonly']]*4)
assert_equal(i.operands[0].dtype, np.dtype('complex128'))
assert_equal(i.operands[0].ndim, 0)
def test_iter_allocate_output_subtype():
# Make sure that the subtype with priority wins
# matrix vs ndarray
a = np.matrix([[1,2], [3,4]])
b = np.arange(4).reshape(2,2).T
i = nditer([a,b,None], [],
[['readonly'],['readonly'],['writeonly','allocate']])
assert_equal(type(a), type(i.operands[2]))
assert_(type(b) != type(i.operands[2]))
assert_equal(i.operands[2].shape, (2,2))
# matrix always wants things to be 2D
b = np.arange(4).reshape(1,2,2)
assert_raises(RuntimeError, nditer, [a,b,None], [],
[['readonly'],['readonly'],['writeonly','allocate']])
# but if subtypes are disabled, the result can still work
i = nditer([a,b,None], [],
[['readonly'],['readonly'],['writeonly','allocate','no_subtype']])
assert_equal(type(b), type(i.operands[2]))
assert_(type(a) != type(i.operands[2]))
assert_equal(i.operands[2].shape, (1,2,2))
def test_iter_allocate_output_errors():
# Check that the iterator will throw errors for bad output allocations
# Need an input if no output data type is specified
a = arange(6)
assert_raises(TypeError, nditer, [a,None], [],
[['writeonly'],['writeonly','allocate']])
# Allocated output should be flagged for writing
assert_raises(ValueError, nditer, [a,None], [],
[['readonly'],['allocate','readonly']])
# Allocated output can't have buffering without delayed bufalloc
assert_raises(ValueError, nditer, [a,None], ['buffered'],
['allocate','readwrite'])
# Must specify at least one input
assert_raises(ValueError, nditer, [None,None], [],
[['writeonly','allocate'],
['writeonly','allocate']],
op_dtypes=[np.dtype('f4'),np.dtype('f4')])
# If using op_axes, must specify all the axes
a = arange(24, dtype='i4').reshape(2,3,4)
assert_raises(ValueError, nditer, [a,None], [],
[['readonly'],['writeonly','allocate']],
op_dtypes=[None,np.dtype('f4')],
op_axes=[None,[0,np.newaxis,1]])
# If using op_axes, the axes must be within bounds
assert_raises(ValueError, nditer, [a,None], [],
[['readonly'],['writeonly','allocate']],
op_dtypes=[None,np.dtype('f4')],
op_axes=[None,[0,3,1]])
# If using op_axes, there can't be duplicates
assert_raises(ValueError, nditer, [a,None], [],
[['readonly'],['writeonly','allocate']],
op_dtypes=[None,np.dtype('f4')],
op_axes=[None,[0,2,1,0]])
def test_iter_remove_axis():
a = arange(24).reshape(2,3,4)
i = nditer(a,['multi_index'])
i.remove_axis(1)
assert_equal([x for x in i], a[:,0,:].ravel())
a = a[::-1,:,:]
i = nditer(a,['multi_index'])
i.remove_axis(0)
assert_equal([x for x in i], a[0,:,:].ravel())
def test_iter_remove_multi_index_inner_loop():
# Check that removing multi-index support works
a = arange(24).reshape(2,3,4)
i = nditer(a,['multi_index'])
assert_equal(i.ndim, 3)
assert_equal(i.shape, (2,3,4))
assert_equal(i.itviews[0].shape, (2,3,4))
# Removing the multi-index tracking causes all dimensions to coalesce
before = [x for x in i]
i.remove_multi_index()
after = [x for x in i]
assert_equal(before, after)
assert_equal(i.ndim, 1)
assert_raises(ValueError, lambda i:i.shape, i)
assert_equal(i.itviews[0].shape, (24,))
# Removing the inner loop means there's just one iteration
i.reset()
assert_equal(i.itersize, 24)
assert_equal(i[0].shape, tuple())
i.enable_external_loop()
assert_equal(i.itersize, 24)
assert_equal(i[0].shape, (24,))
assert_equal(i.value, arange(24))
def test_iter_iterindex():
# Make sure iterindex works
buffersize = 5
a = arange(24).reshape(4,3,2)
for flags in ([], ['buffered']):
i = nditer(a, flags, buffersize=buffersize)
assert_equal(iter_iterindices(i), range(24))
i.iterindex = 2
assert_equal(iter_iterindices(i), range(2,24))
i = nditer(a, flags, order='F', buffersize=buffersize)
assert_equal(iter_iterindices(i), range(24))
i.iterindex = 5
assert_equal(iter_iterindices(i), range(5,24))
i = nditer(a[::-1], flags, order='F', buffersize=buffersize)
assert_equal(iter_iterindices(i), range(24))
i.iterindex = 9
assert_equal(iter_iterindices(i), range(9,24))
i = nditer(a[::-1,::-1], flags, order='C', buffersize=buffersize)
assert_equal(iter_iterindices(i), range(24))
i.iterindex = 13
assert_equal(iter_iterindices(i), range(13,24))
i = nditer(a[::1,::-1], flags, buffersize=buffersize)
assert_equal(iter_iterindices(i), range(24))
i.iterindex = 23
assert_equal(iter_iterindices(i), range(23,24))
i.reset()
i.iterindex = 2
assert_equal(iter_iterindices(i), range(2,24))
def test_iter_iterrange():
# Make sure getting and resetting the iterrange works
buffersize = 5
a = arange(24, dtype='i4').reshape(4,3,2)
a_fort = a.ravel(order='F')
i = nditer(a, ['ranged'], ['readonly'], order='F',
buffersize=buffersize)
assert_equal(i.iterrange, (0,24))
assert_equal([x[()] for x in i], a_fort)
for r in [(0,24), (1,2), (3,24), (5,5), (0,20), (23,24)]:
i.iterrange = r
assert_equal(i.iterrange, r)
assert_equal([x[()] for x in i], a_fort[r[0]:r[1]])
i = nditer(a, ['ranged','buffered'], ['readonly'], order='F',
op_dtypes='f8', buffersize=buffersize)
assert_equal(i.iterrange, (0,24))
assert_equal([x[()] for x in i], a_fort)
for r in [(0,24), (1,2), (3,24), (5,5), (0,20), (23,24)]:
i.iterrange = r
assert_equal(i.iterrange, r)
assert_equal([x[()] for x in i], a_fort[r[0]:r[1]])
def get_array(i):
val = np.array([], dtype='f8')
for x in i:
val = np.concatenate((val, x))
return val
i = nditer(a, ['ranged','buffered','external_loop'],
['readonly'], order='F',
op_dtypes='f8', buffersize=buffersize)
assert_equal(i.iterrange, (0,24))
assert_equal(get_array(i), a_fort)
for r in [(0,24), (1,2), (3,24), (5,5), (0,20), (23,24)]:
i.iterrange = r
assert_equal(i.iterrange, r)
assert_equal(get_array(i), a_fort[r[0]:r[1]])
def test_iter_buffering():
# Test buffering with several buffer sizes and types
arrays = []
# F-order swapped array
arrays.append(np.arange(24,
dtype='c16').reshape(2,3,4).T.newbyteorder().byteswap())
# Contiguous 1-dimensional array
arrays.append(np.arange(10, dtype='f4'))
# Unaligned array
a = np.zeros((4*16+1,), dtype='i1')[1:]
a.dtype = 'i4'
a[:] = np.arange(16,dtype='i4')
arrays.append(a)
# 4-D F-order array
arrays.append(np.arange(120,dtype='i4').reshape(5,3,2,4).T)
for a in arrays:
for buffersize in (1,2,3,5,8,11,16,1024):
vals = []
i = nditer(a, ['buffered','external_loop'],
[['readonly','nbo','aligned']],
order='C',
casting='equiv',
buffersize=buffersize)
while not i.finished:
assert_(i[0].size <= buffersize)
vals.append(i[0].copy())
i.iternext()
assert_equal(np.concatenate(vals), a.ravel(order='C'))
def test_iter_write_buffering():
# Test that buffering of writes is working
# F-order swapped array
a = np.arange(24).reshape(2,3,4).T.newbyteorder().byteswap()
i = nditer(a, ['buffered'],
[['readwrite','nbo','aligned']],
casting='equiv',
order='C',
buffersize=16)
x = 0
while not i.finished:
i[0] = x
x += 1
i.iternext()
assert_equal(a.ravel(order='C'), np.arange(24))
def test_iter_buffering_delayed_alloc():
# Test that delaying buffer allocation works
a = np.arange(6)
b = np.arange(1, dtype='f4')
i = nditer([a,b], ['buffered','delay_bufalloc','multi_index','reduce_ok'],
['readwrite'],
casting='unsafe',
op_dtypes='f4')
assert_(i.has_delayed_bufalloc)
assert_raises(ValueError, lambda i:i.multi_index, i)
assert_raises(ValueError, lambda i:i[0], i)
assert_raises(ValueError, lambda i:i[0:2], i)
def assign_iter(i):
i[0] = 0
assert_raises(ValueError, assign_iter, i)
i.reset()
assert_(not i.has_delayed_bufalloc)
assert_equal(i.multi_index, (0,))
assert_equal(i[0], 0)
i[1] = 1
assert_equal(i[0:2], [0,1])
assert_equal([[x[0][()],x[1][()]] for x in i], zip(range(6), [1]*6))
def test_iter_buffered_cast_simple():
# Test that buffering can handle a simple cast
a = np.arange(10, dtype='f4')
i = nditer(a, ['buffered','external_loop'],
[['readwrite','nbo','aligned']],
casting='same_kind',
op_dtypes=[np.dtype('f8')],
buffersize=3)
for v in i:
v[...] *= 2
assert_equal(a, 2*np.arange(10, dtype='f4'))
def test_iter_buffered_cast_byteswapped():
# Test that buffering can handle a cast which requires swap->cast->swap
a = np.arange(10, dtype='f4').newbyteorder().byteswap()
i = nditer(a, ['buffered','external_loop'],
[['readwrite','nbo','aligned']],
casting='same_kind',
op_dtypes=[np.dtype('f8').newbyteorder()],
buffersize=3)
for v in i:
v[...] *= 2
assert_equal(a, 2*np.arange(10, dtype='f4'))
try:
warnings.simplefilter("ignore", np.ComplexWarning)
a = np.arange(10, dtype='f8').newbyteorder().byteswap()
i = nditer(a, ['buffered','external_loop'],
[['readwrite','nbo','aligned']],
casting='unsafe',
op_dtypes=[np.dtype('c8').newbyteorder()],
buffersize=3)
for v in i:
v[...] *= 2
assert_equal(a, 2*np.arange(10, dtype='f8'))
finally:
warnings.simplefilter("default", np.ComplexWarning)
def test_iter_buffered_cast_byteswapped_complex():
# Test that buffering can handle a cast which requires swap->cast->copy
a = np.arange(10, dtype='c8').newbyteorder().byteswap()
a += 2j
i = nditer(a, ['buffered','external_loop'],
[['readwrite','nbo','aligned']],
casting='same_kind',
op_dtypes=[np.dtype('c16')],
buffersize=3)
for v in i:
v[...] *= 2
assert_equal(a, 2*np.arange(10, dtype='c8') + 4j)
a = np.arange(10, dtype='c8')
a += 2j
i = nditer(a, ['buffered','external_loop'],
[['readwrite','nbo','aligned']],
casting='same_kind',
op_dtypes=[np.dtype('c16').newbyteorder()],
buffersize=3)
for v in i:
v[...] *= 2
assert_equal(a, 2*np.arange(10, dtype='c8') + 4j)
a = np.arange(10, dtype=np.clongdouble).newbyteorder().byteswap()
a += 2j
i = nditer(a, ['buffered','external_loop'],
[['readwrite','nbo','aligned']],
casting='same_kind',
op_dtypes=[np.dtype('c16')],
buffersize=3)
for v in i:
v[...] *= 2
assert_equal(a, 2*np.arange(10, dtype=np.clongdouble) + 4j)
a = np.arange(10, dtype=np.longdouble).newbyteorder().byteswap()
i = nditer(a, ['buffered','external_loop'],
[['readwrite','nbo','aligned']],
casting='same_kind',
op_dtypes=[np.dtype('f4')],
buffersize=7)
for v in i:
v[...] *= 2
assert_equal(a, 2*np.arange(10, dtype=np.longdouble))
def test_iter_buffered_cast_structured_type():
# Tests buffering of structured types
# simple -> struct type (duplicates the value)
sdt = [('a', 'f4'), ('b', 'i8'), ('c', 'c8', (2,3)), ('d', 'O')]
a = np.arange(3, dtype='f4') + 0.5
i = nditer(a, ['buffered','refs_ok'], ['readonly'],
casting='unsafe',
op_dtypes=sdt)
vals = [np.array(x) for x in i]
assert_equal(vals[0]['a'], 0.5)
assert_equal(vals[0]['b'], 0)
assert_equal(vals[0]['c'], [[(0.5)]*3]*2)
assert_equal(vals[0]['d'], 0.5)
assert_equal(vals[1]['a'], 1.5)
assert_equal(vals[1]['b'], 1)
assert_equal(vals[1]['c'], [[(1.5)]*3]*2)
assert_equal(vals[1]['d'], 1.5)
assert_equal(vals[0].dtype, np.dtype(sdt))
# object -> struct type
sdt = [('a', 'f4'), ('b', 'i8'), ('c', 'c8', (2,3)), ('d', 'O')]
a = np.zeros((3,), dtype='O')
a[0] = (0.5,0.5,[[0.5,0.5,0.5],[0.5,0.5,0.5]],0.5)
a[1] = (1.5,1.5,[[1.5,1.5,1.5],[1.5,1.5,1.5]],1.5)
a[2] = (2.5,2.5,[[2.5,2.5,2.5],[2.5,2.5,2.5]],2.5)
rc = sys.getrefcount(a[0])
i = nditer(a, ['buffered','refs_ok'], ['readonly'],
casting='unsafe',
op_dtypes=sdt)
vals = [x.copy() for x in i]
assert_equal(vals[0]['a'], 0.5)
assert_equal(vals[0]['b'], 0)
assert_equal(vals[0]['c'], [[(0.5)]*3]*2)
assert_equal(vals[0]['d'], 0.5)
assert_equal(vals[1]['a'], 1.5)
assert_equal(vals[1]['b'], 1)
assert_equal(vals[1]['c'], [[(1.5)]*3]*2)
assert_equal(vals[1]['d'], 1.5)
assert_equal(vals[0].dtype, np.dtype(sdt))
vals, i, x = [None]*3
assert_equal(sys.getrefcount(a[0]), rc)
# struct type -> simple (takes the first value)
sdt = [('a', 'f4'), ('b', 'i8'), ('d', 'O')]
a = np.array([(5.5,7,'test'),(8,10,11)], dtype=sdt)
i = nditer(a, ['buffered','refs_ok'], ['readonly'],
casting='unsafe',
op_dtypes='i4')
assert_equal([x[()] for x in i], [5, 8])
# struct type -> struct type (field-wise copy)
sdt1 = [('a', 'f4'), ('b', 'i8'), ('d', 'O')]
sdt2 = [('d', 'u2'), ('a', 'O'), ('b', 'f8')]
a = np.array([(1,2,3),(4,5,6)], dtype=sdt1)
i = nditer(a, ['buffered','refs_ok'], ['readonly'],
casting='unsafe',
op_dtypes=sdt2)
assert_equal(i[0].dtype, np.dtype(sdt2))
assert_equal([np.array(x) for x in i],
[np.array((3,1,2), dtype=sdt2),
np.array((6,4,5), dtype=sdt2)])
# struct type -> struct type (field gets discarded)
sdt1 = [('a', 'f4'), ('b', 'i8'), ('d', 'O')]
sdt2 = [('b', 'O'), ('a', 'f8')]
a = np.array([(1,2,3),(4,5,6)], dtype=sdt1)
i = nditer(a, ['buffered','refs_ok'], ['readwrite'],
casting='unsafe',
op_dtypes=sdt2)
assert_equal(i[0].dtype, np.dtype(sdt2))
vals = []
for x in i:
vals.append(np.array(x))
x['a'] = x['b']+3
assert_equal(vals, [np.array((2,1), dtype=sdt2),
np.array((5,4), dtype=sdt2)])
assert_equal(a, np.array([(5,2,None),(8,5,None)], dtype=sdt1))
# struct type -> struct type (structured field gets discarded)
sdt1 = [('a', 'f4'), ('b', 'i8'), ('d', [('a', 'i2'),('b','i4')])]
sdt2 = [('b', 'O'), ('a', 'f8')]
a = np.array([(1,2,(0,9)),(4,5,(20,21))], dtype=sdt1)
i = nditer(a, ['buffered','refs_ok'], ['readwrite'],
casting='unsafe',
op_dtypes=sdt2)
assert_equal(i[0].dtype, np.dtype(sdt2))
vals = []
for x in i:
vals.append(np.array(x))
x['a'] = x['b']+3
assert_equal(vals, [np.array((2,1), dtype=sdt2),
np.array((5,4), dtype=sdt2)])
assert_equal(a, np.array([(5,2,(0,0)),(8,5,(0,0))], dtype=sdt1))
# struct type -> struct type (structured field w/ ref gets discarded)
sdt1 = [('a', 'f4'), ('b', 'i8'), ('d', [('a', 'i2'),('b','O')])]
sdt2 = [('b', 'O'), ('a', 'f8')]
a = np.array([(1,2,(0,9)),(4,5,(20,21))], dtype=sdt1)
i = nditer(a, ['buffered','refs_ok'], ['readwrite'],
casting='unsafe',
op_dtypes=sdt2)
assert_equal(i[0].dtype, np.dtype(sdt2))
vals = []
for x in i:
vals.append(np.array(x))
x['a'] = x['b']+3
assert_equal(vals, [np.array((2,1), dtype=sdt2),
np.array((5,4), dtype=sdt2)])
assert_equal(a, np.array([(5,2,(0,None)),(8,5,(0,None))], dtype=sdt1))
# struct type -> struct type back (structured field w/ ref gets discarded)
sdt1 = [('b', 'O'), ('a', 'f8')]
sdt2 = [('a', 'f4'), ('b', 'i8'), ('d', [('a', 'i2'),('b','O')])]
a = np.array([(1,2),(4,5)], dtype=sdt1)
i = nditer(a, ['buffered','refs_ok'], ['readwrite'],
casting='unsafe',
op_dtypes=sdt2)
assert_equal(i[0].dtype, np.dtype(sdt2))
vals = []
for x in i:
vals.append(np.array(x))
assert_equal(x['d'], np.array((0, None), dtype=[('a','i2'),('b','O')]))
x['a'] = x['b']+3
assert_equal(vals, [np.array((2,1,(0,None)), dtype=sdt2),
np.array((5,4,(0,None)), dtype=sdt2)])
assert_equal(a, np.array([(1,4),(4,7)], dtype=sdt1))
def test_iter_buffered_cast_subarray():
# Tests buffering of subarrays
# one element -> many (copies it to all)
sdt1 = [('a', 'f4')]
sdt2 = [('a', 'f8', (3,2,2))]
a = np.zeros((6,), dtype=sdt1)
a['a'] = np.arange(6)
i = nditer(a, ['buffered','refs_ok'], ['readonly'],
casting='unsafe',
op_dtypes=sdt2)
assert_equal(i[0].dtype, np.dtype(sdt2))
for x, count in zip(i, range(6)):
assert_(np.all(x['a'] == count))
# one element -> many -> back (copies it to all)
sdt1 = [('a', 'O', (1,1))]
sdt2 = [('a', 'O', (3,2,2))]
a = np.zeros((6,), dtype=sdt1)
a['a'][:,0,0] = np.arange(6)
i = nditer(a, ['buffered','refs_ok'], ['readwrite'],
casting='unsafe',
op_dtypes=sdt2)
assert_equal(i[0].dtype, np.dtype(sdt2))
count = 0
for x in i:
assert_(np.all(x['a'] == count))
x['a'][0] += 2
count += 1
assert_equal(a['a'], np.arange(6).reshape(6,1,1)+2)
# many -> one element -> back (copies just element 0)
sdt1 = [('a', 'O', (3,2,2))]
sdt2 = [('a', 'O', (1,))]
a = np.zeros((6,), dtype=sdt1)
a['a'][:,0,0,0] = np.arange(6)
i = nditer(a, ['buffered','refs_ok'], ['readwrite'],
casting='unsafe',
op_dtypes=sdt2)
assert_equal(i[0].dtype, np.dtype(sdt2))
count = 0
for x in i:
assert_equal(x['a'], count)
x['a'] += 2
count += 1
assert_equal(a['a'], np.arange(6).reshape(6,1,1,1)*np.ones((1,3,2,2))+2)
# many -> one element -> back (copies just element 0)
sdt1 = [('a', 'f8', (3,2,2))]
sdt2 = [('a', 'O', (1,))]
a = np.zeros((6,), dtype=sdt1)
a['a'][:,0,0,0] = np.arange(6)
i = nditer(a, ['buffered','refs_ok'], ['readonly'],
casting='unsafe',
op_dtypes=sdt2)
assert_equal(i[0].dtype, np.dtype(sdt2))
count = 0
for x in i:
assert_equal(x['a'], count)
count += 1
# many -> one element (copies just element 0)
sdt1 = [('a', 'O', (3,2,2))]
sdt2 = [('a', 'f4', (1,))]
a = np.zeros((6,), dtype=sdt1)
a['a'][:,0,0,0] = np.arange(6)
i = nditer(a, ['buffered','refs_ok'], ['readonly'],
casting='unsafe',
op_dtypes=sdt2)
assert_equal(i[0].dtype, np.dtype(sdt2))
count = 0
for x in i:
assert_equal(x['a'], count)
count += 1
# many -> matching shape (straightforward copy)
sdt1 = [('a', 'O', (3,2,2))]
sdt2 = [('a', 'f4', (3,2,2))]
a = np.zeros((6,), dtype=sdt1)
a['a'] = np.arange(6*3*2*2).reshape(6,3,2,2)
i = nditer(a, ['buffered','refs_ok'], ['readonly'],
casting='unsafe',
op_dtypes=sdt2)
assert_equal(i[0].dtype, np.dtype(sdt2))
count = 0
for x in i:
assert_equal(x['a'], a[count]['a'])
count += 1
# vector -> smaller vector (truncates)
sdt1 = [('a', 'f8', (6,))]
sdt2 = [('a', 'f4', (2,))]
a = np.zeros((6,), dtype=sdt1)
a['a'] = np.arange(6*6).reshape(6,6)
i = nditer(a, ['buffered','refs_ok'], ['readonly'],
casting='unsafe',
op_dtypes=sdt2)
assert_equal(i[0].dtype, np.dtype(sdt2))
count = 0
for x in i:
assert_equal(x['a'], a[count]['a'][:2])
count += 1
# vector -> bigger vector (pads with zeros)
sdt1 = [('a', 'f8', (2,))]
sdt2 = [('a', 'f4', (6,))]
a = np.zeros((6,), dtype=sdt1)
a['a'] = np.arange(6*2).reshape(6,2)
i = nditer(a, ['buffered','refs_ok'], ['readonly'],
casting='unsafe',
op_dtypes=sdt2)
assert_equal(i[0].dtype, np.dtype(sdt2))
count = 0
for x in i:
assert_equal(x['a'][:2], a[count]['a'])
assert_equal(x['a'][2:], [0,0,0,0])
count += 1
# vector -> matrix (broadcasts)
sdt1 = [('a', 'f8', (2,))]
sdt2 = [('a', 'f4', (2,2))]
a = np.zeros((6,), dtype=sdt1)
a['a'] = np.arange(6*2).reshape(6,2)
i = nditer(a, ['buffered','refs_ok'], ['readonly'],
casting='unsafe',
op_dtypes=sdt2)
assert_equal(i[0].dtype, np.dtype(sdt2))
count = 0
for x in i:
assert_equal(x['a'][0], a[count]['a'])
assert_equal(x['a'][1], a[count]['a'])
count += 1
# vector -> matrix (broadcasts and zero-pads)
sdt1 = [('a', 'f8', (2,1))]
sdt2 = [('a', 'f4', (3,2))]
a = np.zeros((6,), dtype=sdt1)
a['a'] = np.arange(6*2).reshape(6,2,1)
i = nditer(a, ['buffered','refs_ok'], ['readonly'],
casting='unsafe',
op_dtypes=sdt2)
assert_equal(i[0].dtype, np.dtype(sdt2))
count = 0
for x in i:
assert_equal(x['a'][:2,0], a[count]['a'][:,0])
assert_equal(x['a'][:2,1], a[count]['a'][:,0])
assert_equal(x['a'][2,:], [0,0])
count += 1
# matrix -> matrix (truncates and zero-pads)
sdt1 = [('a', 'f8', (2,3))]
sdt2 = [('a', 'f4', (3,2))]
a = np.zeros((6,), dtype=sdt1)
a['a'] = np.arange(6*2*3).reshape(6,2,3)
i = nditer(a, ['buffered','refs_ok'], ['readonly'],
casting='unsafe',
op_dtypes=sdt2)
assert_equal(i[0].dtype, np.dtype(sdt2))
count = 0
for x in i:
assert_equal(x['a'][:2,0], a[count]['a'][:,0])
assert_equal(x['a'][:2,1], a[count]['a'][:,1])
assert_equal(x['a'][2,:], [0,0])
count += 1
def test_iter_buffering_badwriteback():
# Writing back from a buffer cannot combine elements
# a needs write buffering, but had a broadcast dimension
a = np.arange(6).reshape(2,3,1)
b = np.arange(12).reshape(2,3,2)
assert_raises(ValueError,nditer,[a,b],
['buffered','external_loop'],
[['readwrite'],['writeonly']],
order='C')
# But if a is readonly, it's fine
i = nditer([a,b],['buffered','external_loop'],
[['readonly'],['writeonly']],
order='C')
# If a has just one element, it's fine too (constant 0 stride, a reduction)
a = np.arange(1).reshape(1,1,1)
i = nditer([a,b],['buffered','external_loop','reduce_ok'],
[['readwrite'],['writeonly']],
order='C')
# check that it fails on other dimensions too
a = np.arange(6).reshape(1,3,2)
assert_raises(ValueError,nditer,[a,b],
['buffered','external_loop'],
[['readwrite'],['writeonly']],
order='C')
a = np.arange(4).reshape(2,1,2)
assert_raises(ValueError,nditer,[a,b],
['buffered','external_loop'],
[['readwrite'],['writeonly']],
order='C')
def test_iter_buffering_string():
# Safe casting disallows shrinking strings
a = np.array(['abc', 'a', 'abcd'], dtype=np.bytes_)
assert_equal(a.dtype, np.dtype('S4'));
assert_raises(TypeError,nditer,a,['buffered'],['readonly'],
op_dtypes='S2')
i = nditer(a, ['buffered'], ['readonly'], op_dtypes='S6')
assert_equal(i[0], asbytes('abc'))
assert_equal(i[0].dtype, np.dtype('S6'))
a = np.array(['abc', 'a', 'abcd'], dtype=np.unicode)
assert_equal(a.dtype, np.dtype('U4'));
assert_raises(TypeError,nditer,a,['buffered'],['readonly'],
op_dtypes='U2')
i = nditer(a, ['buffered'], ['readonly'], op_dtypes='U6')
assert_equal(i[0], 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)
def test_iter_no_broadcast():
# Test that the no_broadcast flag works
a = np.arange(24).reshape(2,3,4)
b = np.arange(6).reshape(2,3,1)
c = np.arange(12).reshape(3,4)
i = nditer([a,b,c], [],
[['readonly','no_broadcast'],['readonly'],['readonly']])
assert_raises(ValueError, nditer, [a,b,c], [],
[['readonly'],['readonly','no_broadcast'],['readonly']])
assert_raises(ValueError, nditer, [a,b,c], [],
[['readonly'],['readonly'],['readonly','no_broadcast']])
def test_iter_nested_iters_basic():
# Test nested iteration basic usage
a = arange(12).reshape(2,3,2)
i, j = np.nested_iters(a, [[0],[1,2]])
vals = []
for x in i:
vals.append([y for y in j])
assert_equal(vals, [[0,1,2,3,4,5],[6,7,8,9,10,11]])
i, j = np.nested_iters(a, [[0,1],[2]])
vals = []
for x in i:
vals.append([y for y in j])
assert_equal(vals, [[0,1],[2,3],[4,5],[6,7],[8,9],[10,11]])
i, j = np.nested_iters(a, [[0,2],[1]])
vals = []
for x in i:
vals.append([y for y in j])
assert_equal(vals, [[0,2,4],[1,3,5],[6,8,10],[7,9,11]])
def test_iter_nested_iters_reorder():
# Test nested iteration basic usage
a = arange(12).reshape(2,3,2)
# In 'K' order (default), it gets reordered
i, j = np.nested_iters(a, [[0],[2,1]])
vals = []
for x in i:
vals.append([y for y in j])
assert_equal(vals, [[0,1,2,3,4,5],[6,7,8,9,10,11]])
i, j = np.nested_iters(a, [[1,0],[2]])
vals = []
for x in i:
vals.append([y for y in j])
assert_equal(vals, [[0,1],[2,3],[4,5],[6,7],[8,9],[10,11]])
i, j = np.nested_iters(a, [[2,0],[1]])
vals = []
for x in i:
vals.append([y for y in j])
assert_equal(vals, [[0,2,4],[1,3,5],[6,8,10],[7,9,11]])
# In 'C' order, it doesn't
i, j = np.nested_iters(a, [[0],[2,1]], order='C')
vals = []
for x in i:
vals.append([y for y in j])
assert_equal(vals, [[0,2,4,1,3,5],[6,8,10,7,9,11]])
i, j = np.nested_iters(a, [[1,0],[2]], order='C')
vals = []
for x in i:
vals.append([y for y in j])
assert_equal(vals, [[0,1],[6,7],[2,3],[8,9],[4,5],[10,11]])
i, j = np.nested_iters(a, [[2,0],[1]], order='C')
vals = []
for x in i:
vals.append([y for y in j])
assert_equal(vals, [[0,2,4],[6,8,10],[1,3,5],[7,9,11]])
def test_iter_nested_iters_flip_axes():
# Test nested iteration with negative axes
a = arange(12).reshape(2,3,2)[::-1,::-1,::-1]
# In 'K' order (default), the axes all get flipped
i, j = np.nested_iters(a, [[0],[1,2]])
vals = []
for x in i:
vals.append([y for y in j])
assert_equal(vals, [[0,1,2,3,4,5],[6,7,8,9,10,11]])
i, j = np.nested_iters(a, [[0,1],[2]])
vals = []
for x in i:
vals.append([y for y in j])
assert_equal(vals, [[0,1],[2,3],[4,5],[6,7],[8,9],[10,11]])
i, j = np.nested_iters(a, [[0,2],[1]])
vals = []
for x in i:
vals.append([y for y in j])
assert_equal(vals, [[0,2,4],[1,3,5],[6,8,10],[7,9,11]])
# In 'C' order, flipping axes is disabled
i, j = np.nested_iters(a, [[0],[1,2]], order='C')
vals = []
for x in i:
vals.append([y for y in j])
assert_equal(vals, [[11,10,9,8,7,6],[5,4,3,2,1,0]])
i, j = np.nested_iters(a, [[0,1],[2]], order='C')
vals = []
for x in i:
vals.append([y for y in j])
assert_equal(vals, [[11,10],[9,8],[7,6],[5,4],[3,2],[1,0]])
i, j = np.nested_iters(a, [[0,2],[1]], order='C')
vals = []
for x in i:
vals.append([y for y in j])
assert_equal(vals, [[11,9,7],[10,8,6],[5,3,1],[4,2,0]])
def test_iter_nested_iters_broadcast():
# Test nested iteration with broadcasting
a = arange(2).reshape(2,1)
b = arange(3).reshape(1,3)
i, j = np.nested_iters([a,b], [[0],[1]])
vals = []
for x in i:
vals.append([y for y in j])
assert_equal(vals, [[[0,0],[0,1],[0,2]],[[1,0],[1,1],[1,2]]])
i, j = np.nested_iters([a,b], [[1],[0]])
vals = []
for x in i:
vals.append([y for y in j])
assert_equal(vals, [[[0,0],[1,0]],[[0,1],[1,1]],[[0,2],[1,2]]])
def test_iter_nested_iters_dtype_copy():
# Test nested iteration with a copy to change dtype
# copy
a = arange(6, dtype='i4').reshape(2,3)
i, j = np.nested_iters(a, [[0],[1]],
op_flags=['readonly','copy'],
op_dtypes='f8')
assert_equal(j[0].dtype, np.dtype('f8'))
vals = []
for x in i:
vals.append([y for y in j])
assert_equal(vals, [[0,1,2],[3,4,5]])
vals = None
# updateifcopy
a = arange(6, dtype='f4').reshape(2,3)
i, j = np.nested_iters(a, [[0],[1]],
op_flags=['readwrite','updateifcopy'],
casting='same_kind',
op_dtypes='f8')
assert_equal(j[0].dtype, np.dtype('f8'))
for x in i:
for y in j:
y[...] += 1
assert_equal(a, [[0,1,2],[3,4,5]])
i, j, x, y = (None,)*4 # force the updateifcopy
assert_equal(a, [[1,2,3],[4,5,6]])
def test_iter_nested_iters_dtype_buffered():
# Test nested iteration with buffering to change dtype
a = arange(6, dtype='f4').reshape(2,3)
i, j = np.nested_iters(a, [[0],[1]],
flags=['buffered'],
op_flags=['readwrite'],
casting='same_kind',
op_dtypes='f8')
assert_equal(j[0].dtype, np.dtype('f8'))
for x in i:
for y in j:
y[...] += 1
assert_equal(a, [[1,2,3],[4,5,6]])
def test_iter_reduction_error():
a = np.arange(6)
assert_raises(ValueError, nditer, [a,None], [],
[['readonly'], ['readwrite','allocate']],
op_axes=[[0],[-1]])
a = np.arange(6).reshape(2,3)
assert_raises(ValueError, nditer, [a,None], ['external_loop'],
[['readonly'], ['readwrite','allocate']],
op_axes=[[0,1],[-1,-1]])
def test_iter_reduction():
# Test doing reductions with the iterator
a = np.arange(6)
i = nditer([a,None], ['reduce_ok'],
[['readonly'], ['readwrite','allocate']],
op_axes=[[0],[-1]])
# Need to initialize the output operand to the addition unit
i.operands[1][...] = 0
# Do the reduction
for x, y in i:
y[...] += x
# Since no axes were specified, should have allocated a scalar
assert_equal(i.operands[1].ndim, 0)
assert_equal(i.operands[1], np.sum(a))
a = np.arange(6).reshape(2,3)
i = nditer([a,None], ['reduce_ok','external_loop'],
[['readonly'], ['readwrite','allocate']],
op_axes=[[0,1],[-1,-1]])
# Need to initialize the output operand to the addition unit
i.operands[1][...] = 0
# Reduction shape/strides for the output
assert_equal(i[1].shape, (6,))
assert_equal(i[1].strides, (0,))
# Do the reduction
for x, y in i:
y[...] += x
# Since no axes were specified, should have allocated a scalar
assert_equal(i.operands[1].ndim, 0)
assert_equal(i.operands[1], np.sum(a))
# This is a tricky reduction case for the buffering double loop
# to handle
a = np.ones((2,3,5))
it1 = nditer([a,None], ['reduce_ok','external_loop'],
[['readonly'], ['readwrite','allocate']],
op_axes=[None,[0,-1,1]])
it2 = nditer([a,None], ['reduce_ok','external_loop',
'buffered','delay_bufalloc'],
[['readonly'], ['readwrite','allocate']],
op_axes=[None,[0,-1,1]], buffersize=10)
it1.operands[1].fill(0)
it2.operands[1].fill(0)
it2.reset()
for x in it1:
x[1][...] += x[0]
for x in it2:
x[1][...] += x[0]
assert_equal(it1.operands[1], it2.operands[1])
assert_equal(it2.operands[1].sum(), a.size)
def test_iter_buffering_reduction():
# Test doing buffered reductions with the iterator
a = np.arange(6)
b = np.array(0., dtype='f8').byteswap().newbyteorder()
i = nditer([a,b], ['reduce_ok', 'buffered'],
[['readonly'], ['readwrite','nbo']],
op_axes=[[0],[-1]])
assert_equal(i[1].dtype, np.dtype('f8'))
assert_(i[1].dtype != b.dtype)
# Do the reduction
for x, y in i:
y[...] += x
# Since no axes were specified, should have allocated a scalar
assert_equal(b, np.sum(a))
a = np.arange(6).reshape(2,3)
b = np.array([0,0], dtype='f8').byteswap().newbyteorder()
i = nditer([a,b], ['reduce_ok','external_loop', 'buffered'],
[['readonly'], ['readwrite','nbo']],
op_axes=[[0,1],[0,-1]])
# Reduction shape/strides for the output
assert_equal(i[1].shape, (3,))
assert_equal(i[1].strides, (0,))
# Do the reduction
for x, y in i:
y[...] += x
assert_equal(b, np.sum(a, axis=1))
# Iterator inner double loop was wrong on this one
p = np.arange(2) + 1
it = np.nditer([p,None],
['delay_bufalloc','reduce_ok','buffered','external_loop'],
[['readonly'],['readwrite','allocate']],
op_axes=[[-1,0],[-1,-1]],
itershape=(2,2))
it.operands[1].fill(0)
it.reset()
assert_equal(it[0], [1,2,1,2])
def test_iter_buffering_reduction_reuse_reduce_loops():
# There was a bug triggering reuse of the reduce loop inappropriately,
# which caused processing to happen in unnecessarily small chunks
# and overran the buffer.
a = np.zeros((2,7))
b = np.zeros((1,7))
it = np.nditer([a,b], flags=['reduce_ok', 'external_loop', 'buffered'],
op_flags=[['readonly'], ['readwrite']],
buffersize = 5)
bufsizes = []
for x, y in it:
bufsizes.append(x.shape[0])
assert_equal(bufsizes, [5,2,5,2])
assert_equal(sum(bufsizes), a.size)
def test_iter_writemasked_badinput():
a = np.zeros((2,3))
b = np.zeros((3,))
m = np.array([[True,True,False],[False,True,False]])
m2 = np.array([True,True,False])
m3 = np.array([0,1,1], dtype='u1')
mbad1 = np.array([0,1,1], dtype='i1')
mbad2 = np.array([0,1,1], dtype='f4')
# Need an 'arraymask' if any operand is 'writemasked'
assert_raises(ValueError, nditer, [a,m], [],
[['readwrite','writemasked'],['readonly']])
# A 'writemasked' operand must not be readonly
assert_raises(ValueError, nditer, [a,m], [],
[['readonly','writemasked'],['readonly','arraymask']])
# 'writemasked' and 'arraymask' may not be used together
assert_raises(ValueError, nditer, [a,m], [],
[['readonly'],['readwrite','arraymask','writemasked']])
# 'arraymask' may only be specified once
assert_raises(ValueError, nditer, [a,m, m2], [],
[['readwrite','writemasked'],
['readonly','arraymask'],
['readonly','arraymask']])
# An 'arraymask' with nothing 'writemasked' also doesn't make sense
assert_raises(ValueError, nditer, [a,m], [],
[['readwrite'],['readonly','arraymask']])
# A writemasked reduction requires a similarly smaller mask
assert_raises(ValueError, nditer, [a,b,m], ['reduce_ok'],
[['readonly'],
['readwrite','writemasked'],
['readonly','arraymask']])
# But this should work with a smaller/equal mask to the reduction operand
np.nditer([a,b,m2], ['reduce_ok'],
[['readonly'],
['readwrite','writemasked'],
['readonly','arraymask']])
# The arraymask itself cannot be a reduction
assert_raises(ValueError, nditer, [a,b,m2], ['reduce_ok'],
[['readonly'],
['readwrite','writemasked'],
['readwrite','arraymask']])
# A uint8 mask is ok too
np.nditer([a,m3], ['buffered'],
[['readwrite','writemasked'],
['readonly','arraymask']],
op_dtypes=['f4',None],
casting='same_kind')
# An int8 mask isn't ok
assert_raises(TypeError, np.nditer, [a,mbad1], ['buffered'],
[['readwrite','writemasked'],
['readonly','arraymask']],
op_dtypes=['f4',None],
casting='same_kind')
# A float32 mask isn't ok
assert_raises(TypeError, np.nditer, [a,mbad2], ['buffered'],
[['readwrite','writemasked'],
['readonly','arraymask']],
op_dtypes=['f4',None],
casting='same_kind')
def test_iter_writemasked():
a = np.zeros((3,), dtype='f8')
msk = np.array([True,True,False])
# When buffering is unused, 'writemasked' effectively does nothing.
# It's up to the user of the iterator to obey the requested semantics.
it = np.nditer([a,msk], [],
[['readwrite','writemasked'],
['readonly','arraymask']])
for x, m in it:
x[...] = 1
# Because we violated the semantics, all the values became 1
assert_equal(a, [1,1,1])
# Even if buffering is enabled, we still may be accessing the array
# directly.
it = np.nditer([a,msk], ['buffered'],
[['readwrite','writemasked'],
['readonly','arraymask']])
for x, m in it:
x[...] = 2.5
# Because we violated the semantics, all the values became 2.5
assert_equal(a, [2.5,2.5,2.5])
# If buffering will definitely happening, for instance because of
# a cast, only the items selected by the mask will be copied back from
# the buffer.
it = np.nditer([a,msk], ['buffered'],
[['readwrite','writemasked'],
['readonly','arraymask']],
op_dtypes=['i8',None],
casting='unsafe')
for x, m in it:
x[...] = 3
# Even though we violated the semantics, only the selected values
# were copied back
assert_equal(a, [3,3,2.5])
def test_iter_non_writable_attribute_deletion():
it = np.nditer(np.ones(2))
attr = ["value", "shape", "operands", "itviews", "has_delayed_bufalloc",
"iterationneedsapi", "has_multi_index", "has_index", "dtypes",
"ndim", "nop", "itersize", "finished"]
if sys.version[:3] == '2.4':
error = TypeError
else:
error = AttributeError
for s in attr:
assert_raises(error, delattr, it, s)
def test_iter_writable_attribute_deletion():
it = np.nditer(np.ones(2))
attr = [ "multi_index", "index", "iterrange", "iterindex"]
for s in attr:
assert_raises(AttributeError, delattr, it, s)
def test_iter_element_deletion():
it = np.nditer(np.ones(3))
try:
del it[1]
del it[1:2]
except TypeError:
pass
except:
raise AssertionError
def test_iter_allocated_array_dtypes():
# If the dtype of an allocated output has a shape, the shape gets
# tacked onto the end of the result.
it = np.nditer(([1, 3, 20], None), op_dtypes=[None, ('i4', (2,))])
for a, b in it:
b[0] = a - 1
b[1] = a + 1
assert_equal(it.operands[1], [[0,2], [2,4], [19,21]])
# Make sure this works for scalars too
it = np.nditer((10, 2, None), op_dtypes=[None, None, ('i4', (2,2))])
for a, b, c in it:
c[0,0] = a - b
c[0,1] = a + b
c[1,0] = a * b
c[1,1] = a / b
assert_equal(it.operands[2], [[8, 12], [20, 5]])
if __name__ == "__main__":
run_module_suite()