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MinDalle_StableDiff/Python310/Lib/test/test_buffer.py

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#
# The ndarray object from _testbuffer.c is a complete implementation of
# a PEP-3118 buffer provider. It is independent from NumPy's ndarray
# and the tests don't require NumPy.
#
# If NumPy is present, some tests check both ndarray implementations
# against each other.
#
# Most ndarray tests also check that memoryview(ndarray) behaves in
# the same way as the original. Thus, a substantial part of the
# memoryview tests is now in this module.
#
# Written and designed by Stefan Krah for Python 3.3.
#
import contextlib
import unittest
from test import support
from test.support import os_helper
from itertools import permutations, product
from random import randrange, sample, choice
import warnings
import sys, array, io, os
from decimal import Decimal
from fractions import Fraction
try:
from _testbuffer import *
except ImportError:
ndarray = None
try:
import struct
except ImportError:
struct = None
try:
import ctypes
except ImportError:
ctypes = None
try:
with os_helper.EnvironmentVarGuard() as os.environ, \
warnings.catch_warnings():
from numpy import ndarray as numpy_array
except ImportError:
numpy_array = None
try:
import _testcapi
except ImportError:
_testcapi = None
SHORT_TEST = True
# ======================================================================
# Random lists by format specifier
# ======================================================================
# Native format chars and their ranges.
NATIVE = {
'?':0, 'c':0, 'b':0, 'B':0,
'h':0, 'H':0, 'i':0, 'I':0,
'l':0, 'L':0, 'n':0, 'N':0,
'f':0, 'd':0, 'P':0
}
# NumPy does not have 'n' or 'N':
if numpy_array:
del NATIVE['n']
del NATIVE['N']
if struct:
try:
# Add "qQ" if present in native mode.
struct.pack('Q', 2**64-1)
NATIVE['q'] = 0
NATIVE['Q'] = 0
except struct.error:
pass
# Standard format chars and their ranges.
STANDARD = {
'?':(0, 2), 'c':(0, 1<<8),
'b':(-(1<<7), 1<<7), 'B':(0, 1<<8),
'h':(-(1<<15), 1<<15), 'H':(0, 1<<16),
'i':(-(1<<31), 1<<31), 'I':(0, 1<<32),
'l':(-(1<<31), 1<<31), 'L':(0, 1<<32),
'q':(-(1<<63), 1<<63), 'Q':(0, 1<<64),
'f':(-(1<<63), 1<<63), 'd':(-(1<<1023), 1<<1023)
}
def native_type_range(fmt):
"""Return range of a native type."""
if fmt == 'c':
lh = (0, 256)
elif fmt == '?':
lh = (0, 2)
elif fmt == 'f':
lh = (-(1<<63), 1<<63)
elif fmt == 'd':
lh = (-(1<<1023), 1<<1023)
else:
for exp in (128, 127, 64, 63, 32, 31, 16, 15, 8, 7):
try:
struct.pack(fmt, (1<<exp)-1)
break
except struct.error:
pass
lh = (-(1<<exp), 1<<exp) if exp & 1 else (0, 1<<exp)
return lh
fmtdict = {
'':NATIVE,
'@':NATIVE,
'<':STANDARD,
'>':STANDARD,
'=':STANDARD,
'!':STANDARD
}
if struct:
for fmt in fmtdict['@']:
fmtdict['@'][fmt] = native_type_range(fmt)
MEMORYVIEW = NATIVE.copy()
ARRAY = NATIVE.copy()
for k in NATIVE:
if not k in "bBhHiIlLfd":
del ARRAY[k]
BYTEFMT = NATIVE.copy()
for k in NATIVE:
if not k in "Bbc":
del BYTEFMT[k]
fmtdict['m'] = MEMORYVIEW
fmtdict['@m'] = MEMORYVIEW
fmtdict['a'] = ARRAY
fmtdict['b'] = BYTEFMT
fmtdict['@b'] = BYTEFMT
# Capabilities of the test objects:
MODE = 0
MULT = 1
cap = { # format chars # multiplier
'ndarray': (['', '@', '<', '>', '=', '!'], ['', '1', '2', '3']),
'array': (['a'], ['']),
'numpy': ([''], ['']),
'memoryview': (['@m', 'm'], ['']),
'bytefmt': (['@b', 'b'], ['']),
}
def randrange_fmt(mode, char, obj):
"""Return random item for a type specified by a mode and a single
format character."""
x = randrange(*fmtdict[mode][char])
if char == 'c':
x = bytes([x])
if obj == 'numpy' and x == b'\x00':
# http://projects.scipy.org/numpy/ticket/1925
x = b'\x01'
if char == '?':
x = bool(x)
if char == 'f' or char == 'd':
x = struct.pack(char, x)
x = struct.unpack(char, x)[0]
return x
def gen_item(fmt, obj):
"""Return single random item."""
mode, chars = fmt.split('#')
x = []
for c in chars:
x.append(randrange_fmt(mode, c, obj))
return x[0] if len(x) == 1 else tuple(x)
def gen_items(n, fmt, obj):
"""Return a list of random items (or a scalar)."""
if n == 0:
return gen_item(fmt, obj)
lst = [0] * n
for i in range(n):
lst[i] = gen_item(fmt, obj)
return lst
def struct_items(n, obj):
mode = choice(cap[obj][MODE])
xfmt = mode + '#'
fmt = mode.strip('amb')
nmemb = randrange(2, 10) # number of struct members
for _ in range(nmemb):
char = choice(tuple(fmtdict[mode]))
multiplier = choice(cap[obj][MULT])
xfmt += (char * int(multiplier if multiplier else 1))
fmt += (multiplier + char)
items = gen_items(n, xfmt, obj)
item = gen_item(xfmt, obj)
return fmt, items, item
def randitems(n, obj='ndarray', mode=None, char=None):
"""Return random format, items, item."""
if mode is None:
mode = choice(cap[obj][MODE])
if char is None:
char = choice(tuple(fmtdict[mode]))
multiplier = choice(cap[obj][MULT])
fmt = mode + '#' + char * int(multiplier if multiplier else 1)
items = gen_items(n, fmt, obj)
item = gen_item(fmt, obj)
fmt = mode.strip('amb') + multiplier + char
return fmt, items, item
def iter_mode(n, obj='ndarray'):
"""Iterate through supported mode/char combinations."""
for mode in cap[obj][MODE]:
for char in fmtdict[mode]:
yield randitems(n, obj, mode, char)
def iter_format(nitems, testobj='ndarray'):
"""Yield (format, items, item) for all possible modes and format
characters plus one random compound format string."""
for t in iter_mode(nitems, testobj):
yield t
if testobj != 'ndarray':
return
yield struct_items(nitems, testobj)
def is_byte_format(fmt):
return 'c' in fmt or 'b' in fmt or 'B' in fmt
def is_memoryview_format(fmt):
"""format suitable for memoryview"""
x = len(fmt)
return ((x == 1 or (x == 2 and fmt[0] == '@')) and
fmt[x-1] in MEMORYVIEW)
NON_BYTE_FORMAT = [c for c in fmtdict['@'] if not is_byte_format(c)]
# ======================================================================
# Multi-dimensional tolist(), slicing and slice assignments
# ======================================================================
def atomp(lst):
"""Tuple items (representing structs) are regarded as atoms."""
return not isinstance(lst, list)
def listp(lst):
return isinstance(lst, list)
def prod(lst):
"""Product of list elements."""
if len(lst) == 0:
return 0
x = lst[0]
for v in lst[1:]:
x *= v
return x
def strides_from_shape(ndim, shape, itemsize, layout):
"""Calculate strides of a contiguous array. Layout is 'C' or
'F' (Fortran)."""
if ndim == 0:
return ()
if layout == 'C':
strides = list(shape[1:]) + [itemsize]
for i in range(ndim-2, -1, -1):
strides[i] *= strides[i+1]
else:
strides = [itemsize] + list(shape[:-1])
for i in range(1, ndim):
strides[i] *= strides[i-1]
return strides
def _ca(items, s):
"""Convert flat item list to the nested list representation of a
multidimensional C array with shape 's'."""
if atomp(items):
return items
if len(s) == 0:
return items[0]
lst = [0] * s[0]
stride = len(items) // s[0] if s[0] else 0
for i in range(s[0]):
start = i*stride
lst[i] = _ca(items[start:start+stride], s[1:])
return lst
def _fa(items, s):
"""Convert flat item list to the nested list representation of a
multidimensional Fortran array with shape 's'."""
if atomp(items):
return items
if len(s) == 0:
return items[0]
lst = [0] * s[0]
stride = s[0]
for i in range(s[0]):
lst[i] = _fa(items[i::stride], s[1:])
return lst
def carray(items, shape):
if listp(items) and not 0 in shape and prod(shape) != len(items):
raise ValueError("prod(shape) != len(items)")
return _ca(items, shape)
def farray(items, shape):
if listp(items) and not 0 in shape and prod(shape) != len(items):
raise ValueError("prod(shape) != len(items)")
return _fa(items, shape)
def indices(shape):
"""Generate all possible tuples of indices."""
iterables = [range(v) for v in shape]
return product(*iterables)
def getindex(ndim, ind, strides):
"""Convert multi-dimensional index to the position in the flat list."""
ret = 0
for i in range(ndim):
ret += strides[i] * ind[i]
return ret
def transpose(src, shape):
"""Transpose flat item list that is regarded as a multi-dimensional
matrix defined by shape: dest...[k][j][i] = src[i][j][k]... """
if not shape:
return src
ndim = len(shape)
sstrides = strides_from_shape(ndim, shape, 1, 'C')
dstrides = strides_from_shape(ndim, shape[::-1], 1, 'C')
dest = [0] * len(src)
for ind in indices(shape):
fr = getindex(ndim, ind, sstrides)
to = getindex(ndim, ind[::-1], dstrides)
dest[to] = src[fr]
return dest
def _flatten(lst):
"""flatten list"""
if lst == []:
return lst
if atomp(lst):
return [lst]
return _flatten(lst[0]) + _flatten(lst[1:])
def flatten(lst):
"""flatten list or return scalar"""
if atomp(lst): # scalar
return lst
return _flatten(lst)
def slice_shape(lst, slices):
"""Get the shape of lst after slicing: slices is a list of slice
objects."""
if atomp(lst):
return []
return [len(lst[slices[0]])] + slice_shape(lst[0], slices[1:])
def multislice(lst, slices):
"""Multi-dimensional slicing: slices is a list of slice objects."""
if atomp(lst):
return lst
return [multislice(sublst, slices[1:]) for sublst in lst[slices[0]]]
def m_assign(llst, rlst, lslices, rslices):
"""Multi-dimensional slice assignment: llst and rlst are the operands,
lslices and rslices are lists of slice objects. llst and rlst must
have the same structure.
For a two-dimensional example, this is not implemented in Python:
llst[0:3:2, 0:3:2] = rlst[1:3:1, 1:3:1]
Instead we write:
lslices = [slice(0,3,2), slice(0,3,2)]
rslices = [slice(1,3,1), slice(1,3,1)]
multislice_assign(llst, rlst, lslices, rslices)
"""
if atomp(rlst):
return rlst
rlst = [m_assign(l, r, lslices[1:], rslices[1:])
for l, r in zip(llst[lslices[0]], rlst[rslices[0]])]
llst[lslices[0]] = rlst
return llst
def cmp_structure(llst, rlst, lslices, rslices):
"""Compare the structure of llst[lslices] and rlst[rslices]."""
lshape = slice_shape(llst, lslices)
rshape = slice_shape(rlst, rslices)
if (len(lshape) != len(rshape)):
return -1
for i in range(len(lshape)):
if lshape[i] != rshape[i]:
return -1
if lshape[i] == 0:
return 0
return 0
def multislice_assign(llst, rlst, lslices, rslices):
"""Return llst after assigning: llst[lslices] = rlst[rslices]"""
if cmp_structure(llst, rlst, lslices, rslices) < 0:
raise ValueError("lvalue and rvalue have different structures")
return m_assign(llst, rlst, lslices, rslices)
# ======================================================================
# Random structures
# ======================================================================
#
# PEP-3118 is very permissive with respect to the contents of a
# Py_buffer. In particular:
#
# - shape can be zero
# - strides can be any integer, including zero
# - offset can point to any location in the underlying
# memory block, provided that it is a multiple of
# itemsize.
#
# The functions in this section test and verify random structures
# in full generality. A structure is valid iff it fits in the
# underlying memory block.
#
# The structure 't' (short for 'tuple') is fully defined by:
#
# t = (memlen, itemsize, ndim, shape, strides, offset)
#
def verify_structure(memlen, itemsize, ndim, shape, strides, offset):
"""Verify that the parameters represent a valid array within
the bounds of the allocated memory:
char *mem: start of the physical memory block
memlen: length of the physical memory block
offset: (char *)buf - mem
"""
if offset % itemsize:
return False
if offset < 0 or offset+itemsize > memlen:
return False
if any(v % itemsize for v in strides):
return False
if ndim <= 0:
return ndim == 0 and not shape and not strides
if 0 in shape:
return True
imin = sum(strides[j]*(shape[j]-1) for j in range(ndim)
if strides[j] <= 0)
imax = sum(strides[j]*(shape[j]-1) for j in range(ndim)
if strides[j] > 0)
return 0 <= offset+imin and offset+imax+itemsize <= memlen
def get_item(lst, indices):
for i in indices:
lst = lst[i]
return lst
def memory_index(indices, t):
"""Location of an item in the underlying memory."""
memlen, itemsize, ndim, shape, strides, offset = t
p = offset
for i in range(ndim):
p += strides[i]*indices[i]
return p
def is_overlapping(t):
"""The structure 't' is overlapping if at least one memory location
is visited twice while iterating through all possible tuples of
indices."""
memlen, itemsize, ndim, shape, strides, offset = t
visited = 1<<memlen
for ind in indices(shape):
i = memory_index(ind, t)
bit = 1<<i
if visited & bit:
return True
visited |= bit
return False
def rand_structure(itemsize, valid, maxdim=5, maxshape=16, shape=()):
"""Return random structure:
(memlen, itemsize, ndim, shape, strides, offset)
If 'valid' is true, the returned structure is valid, otherwise invalid.
If 'shape' is given, use that instead of creating a random shape.
"""
if not shape:
ndim = randrange(maxdim+1)
if (ndim == 0):
if valid:
return itemsize, itemsize, ndim, (), (), 0
else:
nitems = randrange(1, 16+1)
memlen = nitems * itemsize
offset = -itemsize if randrange(2) == 0 else memlen
return memlen, itemsize, ndim, (), (), offset
minshape = 2
n = randrange(100)
if n >= 95 and valid:
minshape = 0
elif n >= 90:
minshape = 1
shape = [0] * ndim
for i in range(ndim):
shape[i] = randrange(minshape, maxshape+1)
else:
ndim = len(shape)
maxstride = 5
n = randrange(100)
zero_stride = True if n >= 95 and n & 1 else False
strides = [0] * ndim
strides[ndim-1] = itemsize * randrange(-maxstride, maxstride+1)
if not zero_stride and strides[ndim-1] == 0:
strides[ndim-1] = itemsize
for i in range(ndim-2, -1, -1):
maxstride *= shape[i+1] if shape[i+1] else 1
if zero_stride:
strides[i] = itemsize * randrange(-maxstride, maxstride+1)
else:
strides[i] = ((1,-1)[randrange(2)] *
itemsize * randrange(1, maxstride+1))
imin = imax = 0
if not 0 in shape:
imin = sum(strides[j]*(shape[j]-1) for j in range(ndim)
if strides[j] <= 0)
imax = sum(strides[j]*(shape[j]-1) for j in range(ndim)
if strides[j] > 0)
nitems = imax - imin
if valid:
offset = -imin * itemsize
memlen = offset + (imax+1) * itemsize
else:
memlen = (-imin + imax) * itemsize
offset = -imin-itemsize if randrange(2) == 0 else memlen
return memlen, itemsize, ndim, shape, strides, offset
def randslice_from_slicelen(slicelen, listlen):
"""Create a random slice of len slicelen that fits into listlen."""
maxstart = listlen - slicelen
start = randrange(maxstart+1)
maxstep = (listlen - start) // slicelen if slicelen else 1
step = randrange(1, maxstep+1)
stop = start + slicelen * step
s = slice(start, stop, step)
_, _, _, control = slice_indices(s, listlen)
if control != slicelen:
raise RuntimeError
return s
def randslice_from_shape(ndim, shape):
"""Create two sets of slices for an array x with shape 'shape'
such that shapeof(x[lslices]) == shapeof(x[rslices])."""
lslices = [0] * ndim
rslices = [0] * ndim
for n in range(ndim):
l = shape[n]
slicelen = randrange(1, l+1) if l > 0 else 0
lslices[n] = randslice_from_slicelen(slicelen, l)
rslices[n] = randslice_from_slicelen(slicelen, l)
return tuple(lslices), tuple(rslices)
def rand_aligned_slices(maxdim=5, maxshape=16):
"""Create (lshape, rshape, tuple(lslices), tuple(rslices)) such that
shapeof(x[lslices]) == shapeof(y[rslices]), where x is an array
with shape 'lshape' and y is an array with shape 'rshape'."""
ndim = randrange(1, maxdim+1)
minshape = 2
n = randrange(100)
if n >= 95:
minshape = 0
elif n >= 90:
minshape = 1
all_random = True if randrange(100) >= 80 else False
lshape = [0]*ndim; rshape = [0]*ndim
lslices = [0]*ndim; rslices = [0]*ndim
for n in range(ndim):
small = randrange(minshape, maxshape+1)
big = randrange(minshape, maxshape+1)
if big < small:
big, small = small, big
# Create a slice that fits the smaller value.
if all_random:
start = randrange(-small, small+1)
stop = randrange(-small, small+1)
step = (1,-1)[randrange(2)] * randrange(1, small+2)
s_small = slice(start, stop, step)
_, _, _, slicelen = slice_indices(s_small, small)
else:
slicelen = randrange(1, small+1) if small > 0 else 0
s_small = randslice_from_slicelen(slicelen, small)
# Create a slice of the same length for the bigger value.
s_big = randslice_from_slicelen(slicelen, big)
if randrange(2) == 0:
rshape[n], lshape[n] = big, small
rslices[n], lslices[n] = s_big, s_small
else:
rshape[n], lshape[n] = small, big
rslices[n], lslices[n] = s_small, s_big
return lshape, rshape, tuple(lslices), tuple(rslices)
def randitems_from_structure(fmt, t):
"""Return a list of random items for structure 't' with format
'fmtchar'."""
memlen, itemsize, _, _, _, _ = t
return gen_items(memlen//itemsize, '#'+fmt, 'numpy')
def ndarray_from_structure(items, fmt, t, flags=0):
"""Return ndarray from the tuple returned by rand_structure()"""
memlen, itemsize, ndim, shape, strides, offset = t
return ndarray(items, shape=shape, strides=strides, format=fmt,
offset=offset, flags=ND_WRITABLE|flags)
def numpy_array_from_structure(items, fmt, t):
"""Return numpy_array from the tuple returned by rand_structure()"""
memlen, itemsize, ndim, shape, strides, offset = t
buf = bytearray(memlen)
for j, v in enumerate(items):
struct.pack_into(fmt, buf, j*itemsize, v)
return numpy_array(buffer=buf, shape=shape, strides=strides,
dtype=fmt, offset=offset)
# ======================================================================
# memoryview casts
# ======================================================================
def cast_items(exporter, fmt, itemsize, shape=None):
"""Interpret the raw memory of 'exporter' as a list of items with
size 'itemsize'. If shape=None, the new structure is assumed to
be 1-D with n * itemsize = bytelen. If shape is given, the usual
constraint for contiguous arrays prod(shape) * itemsize = bytelen
applies. On success, return (items, shape). If the constraints
cannot be met, return (None, None). If a chunk of bytes is interpreted
as NaN as a result of float conversion, return ('nan', None)."""
bytelen = exporter.nbytes
if shape:
if prod(shape) * itemsize != bytelen:
return None, shape
elif shape == []:
if exporter.ndim == 0 or itemsize != bytelen:
return None, shape
else:
n, r = divmod(bytelen, itemsize)
shape = [n]
if r != 0:
return None, shape
mem = exporter.tobytes()
byteitems = [mem[i:i+itemsize] for i in range(0, len(mem), itemsize)]
items = []
for v in byteitems:
item = struct.unpack(fmt, v)[0]
if item != item:
return 'nan', shape
items.append(item)
return (items, shape) if shape != [] else (items[0], shape)
def gencastshapes():
"""Generate shapes to test casting."""
for n in range(32):
yield [n]
ndim = randrange(4, 6)
minshape = 1 if randrange(100) > 80 else 2
yield [randrange(minshape, 5) for _ in range(ndim)]
ndim = randrange(2, 4)
minshape = 1 if randrange(100) > 80 else 2
yield [randrange(minshape, 5) for _ in range(ndim)]
# ======================================================================
# Actual tests
# ======================================================================
def genslices(n):
"""Generate all possible slices for a single dimension."""
return product(range(-n, n+1), range(-n, n+1), range(-n, n+1))
def genslices_ndim(ndim, shape):
"""Generate all possible slice tuples for 'shape'."""
iterables = [genslices(shape[n]) for n in range(ndim)]
return product(*iterables)
def rslice(n, allow_empty=False):
"""Generate random slice for a single dimension of length n.
If zero=True, the slices may be empty, otherwise they will
be non-empty."""
minlen = 0 if allow_empty or n == 0 else 1
slicelen = randrange(minlen, n+1)
return randslice_from_slicelen(slicelen, n)
def rslices(n, allow_empty=False):
"""Generate random slices for a single dimension."""
for _ in range(5):
yield rslice(n, allow_empty)
def rslices_ndim(ndim, shape, iterations=5):
"""Generate random slice tuples for 'shape'."""
# non-empty slices
for _ in range(iterations):
yield tuple(rslice(shape[n]) for n in range(ndim))
# possibly empty slices
for _ in range(iterations):
yield tuple(rslice(shape[n], allow_empty=True) for n in range(ndim))
# invalid slices
yield tuple(slice(0,1,0) for _ in range(ndim))
def rpermutation(iterable, r=None):
pool = tuple(iterable)
r = len(pool) if r is None else r
yield tuple(sample(pool, r))
def ndarray_print(nd):
"""Print ndarray for debugging."""
try:
x = nd.tolist()
except (TypeError, NotImplementedError):
x = nd.tobytes()
if isinstance(nd, ndarray):
offset = nd.offset
flags = nd.flags
else:
offset = 'unknown'
flags = 'unknown'
print("ndarray(%s, shape=%s, strides=%s, suboffsets=%s, offset=%s, "
"format='%s', itemsize=%s, flags=%s)" %
(x, nd.shape, nd.strides, nd.suboffsets, offset,
nd.format, nd.itemsize, flags))
sys.stdout.flush()
ITERATIONS = 100
MAXDIM = 5
MAXSHAPE = 10
if SHORT_TEST:
ITERATIONS = 10
MAXDIM = 3
MAXSHAPE = 4
genslices = rslices
genslices_ndim = rslices_ndim
permutations = rpermutation
@unittest.skipUnless(struct, 'struct module required for this test.')
@unittest.skipUnless(ndarray, 'ndarray object required for this test')
class TestBufferProtocol(unittest.TestCase):
def setUp(self):
# The suboffsets tests need sizeof(void *).
self.sizeof_void_p = get_sizeof_void_p()
def verify(self, result, *, obj,
itemsize, fmt, readonly,
ndim, shape, strides,
lst, sliced=False, cast=False):
# Verify buffer contents against expected values.
if shape:
expected_len = prod(shape)*itemsize
else:
if not fmt: # array has been implicitly cast to unsigned bytes
expected_len = len(lst)
else: # ndim = 0
expected_len = itemsize
# Reconstruct suboffsets from strides. Support for slicing
# could be added, but is currently only needed for test_getbuf().
suboffsets = ()
if result.suboffsets:
self.assertGreater(ndim, 0)
suboffset0 = 0
for n in range(1, ndim):
if shape[n] == 0:
break
if strides[n] <= 0:
suboffset0 += -strides[n] * (shape[n]-1)
suboffsets = [suboffset0] + [-1 for v in range(ndim-1)]
# Not correct if slicing has occurred in the first dimension.
stride0 = self.sizeof_void_p
if strides[0] < 0:
stride0 = -stride0
strides = [stride0] + list(strides[1:])
self.assertIs(result.obj, obj)
self.assertEqual(result.nbytes, expected_len)
self.assertEqual(result.itemsize, itemsize)
self.assertEqual(result.format, fmt)
self.assertIs(result.readonly, readonly)
self.assertEqual(result.ndim, ndim)
self.assertEqual(result.shape, tuple(shape))
if not (sliced and suboffsets):
self.assertEqual(result.strides, tuple(strides))
self.assertEqual(result.suboffsets, tuple(suboffsets))
if isinstance(result, ndarray) or is_memoryview_format(fmt):
rep = result.tolist() if fmt else result.tobytes()
self.assertEqual(rep, lst)
if not fmt: # array has been cast to unsigned bytes,
return # the remaining tests won't work.
# PyBuffer_GetPointer() is the definition how to access an item.
# If PyBuffer_GetPointer(indices) is correct for all possible
# combinations of indices, the buffer is correct.
#
# Also test tobytes() against the flattened 'lst', with all items
# packed to bytes.
if not cast: # casts chop up 'lst' in different ways
b = bytearray()
buf_err = None
for ind in indices(shape):
try:
item1 = get_pointer(result, ind)
item2 = get_item(lst, ind)
if isinstance(item2, tuple):
x = struct.pack(fmt, *item2)
else:
x = struct.pack(fmt, item2)
b.extend(x)
except BufferError:
buf_err = True # re-exporter does not provide full buffer
break
self.assertEqual(item1, item2)
if not buf_err:
# test tobytes()
self.assertEqual(result.tobytes(), b)
# test hex()
m = memoryview(result)
h = "".join("%02x" % c for c in b)
self.assertEqual(m.hex(), h)
# lst := expected multi-dimensional logical representation
# flatten(lst) := elements in C-order
ff = fmt if fmt else 'B'
flattened = flatten(lst)
# Rules for 'A': if the array is already contiguous, return
# the array unaltered. Otherwise, return a contiguous 'C'
# representation.
for order in ['C', 'F', 'A']:
expected = result
if order == 'F':
if not is_contiguous(result, 'A') or \
is_contiguous(result, 'C'):
# For constructing the ndarray, convert the
# flattened logical representation to Fortran order.
trans = transpose(flattened, shape)
expected = ndarray(trans, shape=shape, format=ff,
flags=ND_FORTRAN)
else: # 'C', 'A'
if not is_contiguous(result, 'A') or \
is_contiguous(result, 'F') and order == 'C':
# The flattened list is already in C-order.
expected = ndarray(flattened, shape=shape, format=ff)
contig = get_contiguous(result, PyBUF_READ, order)
self.assertEqual(contig.tobytes(), b)
self.assertTrue(cmp_contig(contig, expected))
if ndim == 0:
continue
nmemb = len(flattened)
ro = 0 if readonly else ND_WRITABLE
### See comment in test_py_buffer_to_contiguous for an
### explanation why these tests are valid.
# To 'C'
contig = py_buffer_to_contiguous(result, 'C', PyBUF_FULL_RO)
self.assertEqual(len(contig), nmemb * itemsize)
initlst = [struct.unpack_from(fmt, contig, n*itemsize)
for n in range(nmemb)]
if len(initlst[0]) == 1:
initlst = [v[0] for v in initlst]
y = ndarray(initlst, shape=shape, flags=ro, format=fmt)
self.assertEqual(memoryview(y), memoryview(result))
contig_bytes = memoryview(result).tobytes()
self.assertEqual(contig_bytes, contig)
contig_bytes = memoryview(result).tobytes(order=None)
self.assertEqual(contig_bytes, contig)
contig_bytes = memoryview(result).tobytes(order='C')
self.assertEqual(contig_bytes, contig)
# To 'F'
contig = py_buffer_to_contiguous(result, 'F', PyBUF_FULL_RO)
self.assertEqual(len(contig), nmemb * itemsize)
initlst = [struct.unpack_from(fmt, contig, n*itemsize)
for n in range(nmemb)]
if len(initlst[0]) == 1:
initlst = [v[0] for v in initlst]
y = ndarray(initlst, shape=shape, flags=ro|ND_FORTRAN,
format=fmt)
self.assertEqual(memoryview(y), memoryview(result))
contig_bytes = memoryview(result).tobytes(order='F')
self.assertEqual(contig_bytes, contig)
# To 'A'
contig = py_buffer_to_contiguous(result, 'A', PyBUF_FULL_RO)
self.assertEqual(len(contig), nmemb * itemsize)
initlst = [struct.unpack_from(fmt, contig, n*itemsize)
for n in range(nmemb)]
if len(initlst[0]) == 1:
initlst = [v[0] for v in initlst]
f = ND_FORTRAN if is_contiguous(result, 'F') else 0
y = ndarray(initlst, shape=shape, flags=f|ro, format=fmt)
self.assertEqual(memoryview(y), memoryview(result))
contig_bytes = memoryview(result).tobytes(order='A')
self.assertEqual(contig_bytes, contig)
if is_memoryview_format(fmt):
try:
m = memoryview(result)
except BufferError: # re-exporter does not provide full information
return
ex = result.obj if isinstance(result, memoryview) else result
def check_memoryview(m, expected_readonly=readonly):
self.assertIs(m.obj, ex)
self.assertEqual(m.nbytes, expected_len)
self.assertEqual(m.itemsize, itemsize)
self.assertEqual(m.format, fmt)
self.assertEqual(m.readonly, expected_readonly)
self.assertEqual(m.ndim, ndim)
self.assertEqual(m.shape, tuple(shape))
if not (sliced and suboffsets):
self.assertEqual(m.strides, tuple(strides))
self.assertEqual(m.suboffsets, tuple(suboffsets))
n = 1 if ndim == 0 else len(lst)
self.assertEqual(len(m), n)
rep = result.tolist() if fmt else result.tobytes()
self.assertEqual(rep, lst)
self.assertEqual(m, result)
check_memoryview(m)
with m.toreadonly() as mm:
check_memoryview(mm, expected_readonly=True)
m.tobytes() # Releasing mm didn't release m
def verify_getbuf(self, orig_ex, ex, req, sliced=False):
def match(req, flag):
return ((req&flag) == flag)
if (# writable request to read-only exporter
(ex.readonly and match(req, PyBUF_WRITABLE)) or
# cannot match explicit contiguity request
(match(req, PyBUF_C_CONTIGUOUS) and not ex.c_contiguous) or
(match(req, PyBUF_F_CONTIGUOUS) and not ex.f_contiguous) or
(match(req, PyBUF_ANY_CONTIGUOUS) and not ex.contiguous) or
# buffer needs suboffsets
(not match(req, PyBUF_INDIRECT) and ex.suboffsets) or
# buffer without strides must be C-contiguous
(not match(req, PyBUF_STRIDES) and not ex.c_contiguous) or
# PyBUF_SIMPLE|PyBUF_FORMAT and PyBUF_WRITABLE|PyBUF_FORMAT
(not match(req, PyBUF_ND) and match(req, PyBUF_FORMAT))):
self.assertRaises(BufferError, ndarray, ex, getbuf=req)
return
if isinstance(ex, ndarray) or is_memoryview_format(ex.format):
lst = ex.tolist()
else:
nd = ndarray(ex, getbuf=PyBUF_FULL_RO)
lst = nd.tolist()
# The consumer may have requested default values or a NULL format.
ro = False if match(req, PyBUF_WRITABLE) else ex.readonly
fmt = ex.format
itemsize = ex.itemsize
ndim = ex.ndim
if not match(req, PyBUF_FORMAT):
# itemsize refers to the original itemsize before the cast.
# The equality product(shape) * itemsize = len still holds.
# The equality calcsize(format) = itemsize does _not_ hold.
fmt = ''
lst = orig_ex.tobytes() # Issue 12834
if not match(req, PyBUF_ND):
ndim = 1
shape = orig_ex.shape if match(req, PyBUF_ND) else ()
strides = orig_ex.strides if match(req, PyBUF_STRIDES) else ()
nd = ndarray(ex, getbuf=req)
self.verify(nd, obj=ex,
itemsize=itemsize, fmt=fmt, readonly=ro,
ndim=ndim, shape=shape, strides=strides,
lst=lst, sliced=sliced)
def test_ndarray_getbuf(self):
requests = (
# distinct flags
PyBUF_INDIRECT, PyBUF_STRIDES, PyBUF_ND, PyBUF_SIMPLE,
PyBUF_C_CONTIGUOUS, PyBUF_F_CONTIGUOUS, PyBUF_ANY_CONTIGUOUS,
# compound requests
PyBUF_FULL, PyBUF_FULL_RO,
PyBUF_RECORDS, PyBUF_RECORDS_RO,
PyBUF_STRIDED, PyBUF_STRIDED_RO,
PyBUF_CONTIG, PyBUF_CONTIG_RO,
)
# items and format
items_fmt = (
([True if x % 2 else False for x in range(12)], '?'),
([1,2,3,4,5,6,7,8,9,10,11,12], 'b'),
([1,2,3,4,5,6,7,8,9,10,11,12], 'B'),
([(2**31-x) if x % 2 else (-2**31+x) for x in range(12)], 'l')
)
# shape, strides, offset
structure = (
([], [], 0),
([1,3,1], [], 0),
([12], [], 0),
([12], [-1], 11),
([6], [2], 0),
([6], [-2], 11),
([3, 4], [], 0),
([3, 4], [-4, -1], 11),
([2, 2], [4, 1], 4),
([2, 2], [-4, -1], 8)
)
# ndarray creation flags
ndflags = (
0, ND_WRITABLE, ND_FORTRAN, ND_FORTRAN|ND_WRITABLE,
ND_PIL, ND_PIL|ND_WRITABLE
)
# flags that can actually be used as flags
real_flags = (0, PyBUF_WRITABLE, PyBUF_FORMAT,
PyBUF_WRITABLE|PyBUF_FORMAT)
for items, fmt in items_fmt:
itemsize = struct.calcsize(fmt)
for shape, strides, offset in structure:
strides = [v * itemsize for v in strides]
offset *= itemsize
for flags in ndflags:
if strides and (flags&ND_FORTRAN):
continue
if not shape and (flags&ND_PIL):
continue
_items = items if shape else items[0]
ex1 = ndarray(_items, format=fmt, flags=flags,
shape=shape, strides=strides, offset=offset)
ex2 = ex1[::-2] if shape else None
m1 = memoryview(ex1)
if ex2:
m2 = memoryview(ex2)
if ex1.ndim == 0 or (ex1.ndim == 1 and shape and strides):
self.assertEqual(m1, ex1)
if ex2 and ex2.ndim == 1 and shape and strides:
self.assertEqual(m2, ex2)
for req in requests:
for bits in real_flags:
self.verify_getbuf(ex1, ex1, req|bits)
self.verify_getbuf(ex1, m1, req|bits)
if ex2:
self.verify_getbuf(ex2, ex2, req|bits,
sliced=True)
self.verify_getbuf(ex2, m2, req|bits,
sliced=True)
items = [1,2,3,4,5,6,7,8,9,10,11,12]
# ND_GETBUF_FAIL
ex = ndarray(items, shape=[12], flags=ND_GETBUF_FAIL)
self.assertRaises(BufferError, ndarray, ex)
# Request complex structure from a simple exporter. In this
# particular case the test object is not PEP-3118 compliant.
base = ndarray([9], [1])
ex = ndarray(base, getbuf=PyBUF_SIMPLE)
self.assertRaises(BufferError, ndarray, ex, getbuf=PyBUF_WRITABLE)
self.assertRaises(BufferError, ndarray, ex, getbuf=PyBUF_ND)
self.assertRaises(BufferError, ndarray, ex, getbuf=PyBUF_STRIDES)
self.assertRaises(BufferError, ndarray, ex, getbuf=PyBUF_C_CONTIGUOUS)
self.assertRaises(BufferError, ndarray, ex, getbuf=PyBUF_F_CONTIGUOUS)
self.assertRaises(BufferError, ndarray, ex, getbuf=PyBUF_ANY_CONTIGUOUS)
nd = ndarray(ex, getbuf=PyBUF_SIMPLE)
# Issue #22445: New precise contiguity definition.
for shape in [1,12,1], [7,0,7]:
for order in 0, ND_FORTRAN:
ex = ndarray(items, shape=shape, flags=order|ND_WRITABLE)
self.assertTrue(is_contiguous(ex, 'F'))
self.assertTrue(is_contiguous(ex, 'C'))
for flags in requests:
nd = ndarray(ex, getbuf=flags)
self.assertTrue(is_contiguous(nd, 'F'))
self.assertTrue(is_contiguous(nd, 'C'))
def test_ndarray_exceptions(self):
nd = ndarray([9], [1])
ndm = ndarray([9], [1], flags=ND_VAREXPORT)
# Initialization of a new ndarray or mutation of an existing array.
for c in (ndarray, nd.push, ndm.push):
# Invalid types.
self.assertRaises(TypeError, c, {1,2,3})
self.assertRaises(TypeError, c, [1,2,'3'])
self.assertRaises(TypeError, c, [1,2,(3,4)])
self.assertRaises(TypeError, c, [1,2,3], shape={3})
self.assertRaises(TypeError, c, [1,2,3], shape=[3], strides={1})
self.assertRaises(TypeError, c, [1,2,3], shape=[3], offset=[])
self.assertRaises(TypeError, c, [1], shape=[1], format={})
self.assertRaises(TypeError, c, [1], shape=[1], flags={})
self.assertRaises(TypeError, c, [1], shape=[1], getbuf={})
# ND_FORTRAN flag is only valid without strides.
self.assertRaises(TypeError, c, [1], shape=[1], strides=[1],
flags=ND_FORTRAN)
# ND_PIL flag is only valid with ndim > 0.
self.assertRaises(TypeError, c, [1], shape=[], flags=ND_PIL)
# Invalid items.
self.assertRaises(ValueError, c, [], shape=[1])
self.assertRaises(ValueError, c, ['XXX'], shape=[1], format="L")
# Invalid combination of items and format.
self.assertRaises(struct.error, c, [1000], shape=[1], format="B")
self.assertRaises(ValueError, c, [1,(2,3)], shape=[2], format="B")
self.assertRaises(ValueError, c, [1,2,3], shape=[3], format="QL")
# Invalid ndim.
n = ND_MAX_NDIM+1
self.assertRaises(ValueError, c, [1]*n, shape=[1]*n)
# Invalid shape.
self.assertRaises(ValueError, c, [1], shape=[-1])
self.assertRaises(ValueError, c, [1,2,3], shape=['3'])
self.assertRaises(OverflowError, c, [1], shape=[2**128])
# prod(shape) * itemsize != len(items)
self.assertRaises(ValueError, c, [1,2,3,4,5], shape=[2,2], offset=3)
# Invalid strides.
self.assertRaises(ValueError, c, [1,2,3], shape=[3], strides=['1'])
self.assertRaises(OverflowError, c, [1], shape=[1],
strides=[2**128])
# Invalid combination of strides and shape.
self.assertRaises(ValueError, c, [1,2], shape=[2,1], strides=[1])
# Invalid combination of strides and format.
self.assertRaises(ValueError, c, [1,2,3,4], shape=[2], strides=[3],
format="L")
# Invalid offset.
self.assertRaises(ValueError, c, [1,2,3], shape=[3], offset=4)
self.assertRaises(ValueError, c, [1,2,3], shape=[1], offset=3,
format="L")
# Invalid format.
self.assertRaises(ValueError, c, [1,2,3], shape=[3], format="")
self.assertRaises(struct.error, c, [(1,2,3)], shape=[1],
format="@#$")
# Striding out of the memory bounds.
items = [1,2,3,4,5,6,7,8,9,10]
self.assertRaises(ValueError, c, items, shape=[2,3],
strides=[-3, -2], offset=5)
# Constructing consumer: format argument invalid.
self.assertRaises(TypeError, c, bytearray(), format="Q")
# Constructing original base object: getbuf argument invalid.
self.assertRaises(TypeError, c, [1], shape=[1], getbuf=PyBUF_FULL)
# Shape argument is mandatory for original base objects.
self.assertRaises(TypeError, c, [1])
# PyBUF_WRITABLE request to read-only provider.
self.assertRaises(BufferError, ndarray, b'123', getbuf=PyBUF_WRITABLE)
# ND_VAREXPORT can only be specified during construction.
nd = ndarray([9], [1], flags=ND_VAREXPORT)
self.assertRaises(ValueError, nd.push, [1], [1], flags=ND_VAREXPORT)
# Invalid operation for consumers: push/pop
nd = ndarray(b'123')
self.assertRaises(BufferError, nd.push, [1], [1])
self.assertRaises(BufferError, nd.pop)
# ND_VAREXPORT not set: push/pop fail with exported buffers
nd = ndarray([9], [1])
nd.push([1], [1])
m = memoryview(nd)
self.assertRaises(BufferError, nd.push, [1], [1])
self.assertRaises(BufferError, nd.pop)
m.release()
nd.pop()
# Single remaining buffer: pop fails
self.assertRaises(BufferError, nd.pop)
del nd
# get_pointer()
self.assertRaises(TypeError, get_pointer, {}, [1,2,3])
self.assertRaises(TypeError, get_pointer, b'123', {})
nd = ndarray(list(range(100)), shape=[1]*100)
self.assertRaises(ValueError, get_pointer, nd, [5])
nd = ndarray(list(range(12)), shape=[3,4])
self.assertRaises(ValueError, get_pointer, nd, [2,3,4])
self.assertRaises(ValueError, get_pointer, nd, [3,3])
self.assertRaises(ValueError, get_pointer, nd, [-3,3])
self.assertRaises(OverflowError, get_pointer, nd, [1<<64,3])
# tolist() needs format
ex = ndarray([1,2,3], shape=[3], format='L')
nd = ndarray(ex, getbuf=PyBUF_SIMPLE)
self.assertRaises(ValueError, nd.tolist)
# memoryview_from_buffer()
ex1 = ndarray([1,2,3], shape=[3], format='L')
ex2 = ndarray(ex1)
nd = ndarray(ex2)
self.assertRaises(TypeError, nd.memoryview_from_buffer)
nd = ndarray([(1,)*200], shape=[1], format='L'*200)
self.assertRaises(TypeError, nd.memoryview_from_buffer)
n = ND_MAX_NDIM
nd = ndarray(list(range(n)), shape=[1]*n)
self.assertRaises(ValueError, nd.memoryview_from_buffer)
# get_contiguous()
nd = ndarray([1], shape=[1])
self.assertRaises(TypeError, get_contiguous, 1, 2, 3, 4, 5)
self.assertRaises(TypeError, get_contiguous, nd, "xyz", 'C')
self.assertRaises(OverflowError, get_contiguous, nd, 2**64, 'C')
self.assertRaises(TypeError, get_contiguous, nd, PyBUF_READ, 961)
self.assertRaises(UnicodeEncodeError, get_contiguous, nd, PyBUF_READ,
'\u2007')
self.assertRaises(ValueError, get_contiguous, nd, PyBUF_READ, 'Z')
self.assertRaises(ValueError, get_contiguous, nd, 255, 'A')
# cmp_contig()
nd = ndarray([1], shape=[1])
self.assertRaises(TypeError, cmp_contig, 1, 2, 3, 4, 5)
self.assertRaises(TypeError, cmp_contig, {}, nd)
self.assertRaises(TypeError, cmp_contig, nd, {})
# is_contiguous()
nd = ndarray([1], shape=[1])
self.assertRaises(TypeError, is_contiguous, 1, 2, 3, 4, 5)
self.assertRaises(TypeError, is_contiguous, {}, 'A')
self.assertRaises(TypeError, is_contiguous, nd, 201)
def test_ndarray_linked_list(self):
for perm in permutations(range(5)):
m = [0]*5
nd = ndarray([1,2,3], shape=[3], flags=ND_VAREXPORT)
m[0] = memoryview(nd)
for i in range(1, 5):
nd.push([1,2,3], shape=[3])
m[i] = memoryview(nd)
for i in range(5):
m[perm[i]].release()
self.assertRaises(BufferError, nd.pop)
del nd
def test_ndarray_format_scalar(self):
# ndim = 0: scalar
for fmt, scalar, _ in iter_format(0):
itemsize = struct.calcsize(fmt)
nd = ndarray(scalar, shape=(), format=fmt)
self.verify(nd, obj=None,
itemsize=itemsize, fmt=fmt, readonly=True,
ndim=0, shape=(), strides=(),
lst=scalar)
def test_ndarray_format_shape(self):
# ndim = 1, shape = [n]
nitems = randrange(1, 10)
for fmt, items, _ in iter_format(nitems):
itemsize = struct.calcsize(fmt)
for flags in (0, ND_PIL):
nd = ndarray(items, shape=[nitems], format=fmt, flags=flags)
self.verify(nd, obj=None,
itemsize=itemsize, fmt=fmt, readonly=True,
ndim=1, shape=(nitems,), strides=(itemsize,),
lst=items)
def test_ndarray_format_strides(self):
# ndim = 1, strides
nitems = randrange(1, 30)
for fmt, items, _ in iter_format(nitems):
itemsize = struct.calcsize(fmt)
for step in range(-5, 5):
if step == 0:
continue
shape = [len(items[::step])]
strides = [step*itemsize]
offset = itemsize*(nitems-1) if step < 0 else 0
for flags in (0, ND_PIL):
nd = ndarray(items, shape=shape, strides=strides,
format=fmt, offset=offset, flags=flags)
self.verify(nd, obj=None,
itemsize=itemsize, fmt=fmt, readonly=True,
ndim=1, shape=shape, strides=strides,
lst=items[::step])
def test_ndarray_fortran(self):
items = [1,2,3,4,5,6,7,8,9,10,11,12]
ex = ndarray(items, shape=(3, 4), strides=(1, 3))
nd = ndarray(ex, getbuf=PyBUF_F_CONTIGUOUS|PyBUF_FORMAT)
self.assertEqual(nd.tolist(), farray(items, (3, 4)))
def test_ndarray_multidim(self):
for ndim in range(5):
shape_t = [randrange(2, 10) for _ in range(ndim)]
nitems = prod(shape_t)
for shape in permutations(shape_t):
fmt, items, _ = randitems(nitems)
itemsize = struct.calcsize(fmt)
for flags in (0, ND_PIL):
if ndim == 0 and flags == ND_PIL:
continue
# C array
nd = ndarray(items, shape=shape, format=fmt, flags=flags)
strides = strides_from_shape(ndim, shape, itemsize, 'C')
lst = carray(items, shape)
self.verify(nd, obj=None,
itemsize=itemsize, fmt=fmt, readonly=True,
ndim=ndim, shape=shape, strides=strides,
lst=lst)
if is_memoryview_format(fmt):
# memoryview: reconstruct strides
ex = ndarray(items, shape=shape, format=fmt)
nd = ndarray(ex, getbuf=PyBUF_CONTIG_RO|PyBUF_FORMAT)
self.assertTrue(nd.strides == ())
mv = nd.memoryview_from_buffer()
self.verify(mv, obj=None,
itemsize=itemsize, fmt=fmt, readonly=True,
ndim=ndim, shape=shape, strides=strides,
lst=lst)
# Fortran array
nd = ndarray(items, shape=shape, format=fmt,
flags=flags|ND_FORTRAN)
strides = strides_from_shape(ndim, shape, itemsize, 'F')
lst = farray(items, shape)
self.verify(nd, obj=None,
itemsize=itemsize, fmt=fmt, readonly=True,
ndim=ndim, shape=shape, strides=strides,
lst=lst)
def test_ndarray_index_invalid(self):
# not writable
nd = ndarray([1], shape=[1])
self.assertRaises(TypeError, nd.__setitem__, 1, 8)
mv = memoryview(nd)
self.assertEqual(mv, nd)
self.assertRaises(TypeError, mv.__setitem__, 1, 8)
# cannot be deleted
nd = ndarray([1], shape=[1], flags=ND_WRITABLE)
self.assertRaises(TypeError, nd.__delitem__, 1)
mv = memoryview(nd)
self.assertEqual(mv, nd)
self.assertRaises(TypeError, mv.__delitem__, 1)
# overflow
nd = ndarray([1], shape=[1], flags=ND_WRITABLE)
self.assertRaises(OverflowError, nd.__getitem__, 1<<64)
self.assertRaises(OverflowError, nd.__setitem__, 1<<64, 8)
mv = memoryview(nd)
self.assertEqual(mv, nd)
self.assertRaises(IndexError, mv.__getitem__, 1<<64)
self.assertRaises(IndexError, mv.__setitem__, 1<<64, 8)
# format
items = [1,2,3,4,5,6,7,8]
nd = ndarray(items, shape=[len(items)], format="B", flags=ND_WRITABLE)
self.assertRaises(struct.error, nd.__setitem__, 2, 300)
self.assertRaises(ValueError, nd.__setitem__, 1, (100, 200))
mv = memoryview(nd)
self.assertEqual(mv, nd)
self.assertRaises(ValueError, mv.__setitem__, 2, 300)
self.assertRaises(TypeError, mv.__setitem__, 1, (100, 200))
items = [(1,2), (3,4), (5,6)]
nd = ndarray(items, shape=[len(items)], format="LQ", flags=ND_WRITABLE)
self.assertRaises(ValueError, nd.__setitem__, 2, 300)
self.assertRaises(struct.error, nd.__setitem__, 1, (b'\x001', 200))
def test_ndarray_index_scalar(self):
# scalar
nd = ndarray(1, shape=(), flags=ND_WRITABLE)
mv = memoryview(nd)
self.assertEqual(mv, nd)
x = nd[()]; self.assertEqual(x, 1)
x = nd[...]; self.assertEqual(x.tolist(), nd.tolist())
x = mv[()]; self.assertEqual(x, 1)
x = mv[...]; self.assertEqual(x.tolist(), nd.tolist())
self.assertRaises(TypeError, nd.__getitem__, 0)
self.assertRaises(TypeError, mv.__getitem__, 0)
self.assertRaises(TypeError, nd.__setitem__, 0, 8)
self.assertRaises(TypeError, mv.__setitem__, 0, 8)
self.assertEqual(nd.tolist(), 1)
self.assertEqual(mv.tolist(), 1)
nd[()] = 9; self.assertEqual(nd.tolist(), 9)
mv[()] = 9; self.assertEqual(mv.tolist(), 9)
nd[...] = 5; self.assertEqual(nd.tolist(), 5)
mv[...] = 5; self.assertEqual(mv.tolist(), 5)
def test_ndarray_index_null_strides(self):
ex = ndarray(list(range(2*4)), shape=[2, 4], flags=ND_WRITABLE)
nd = ndarray(ex, getbuf=PyBUF_CONTIG)
# Sub-views are only possible for full exporters.
self.assertRaises(BufferError, nd.__getitem__, 1)
# Same for slices.
self.assertRaises(BufferError, nd.__getitem__, slice(3,5,1))
def test_ndarray_index_getitem_single(self):
# getitem
for fmt, items, _ in iter_format(5):
nd = ndarray(items, shape=[5], format=fmt)
for i in range(-5, 5):
self.assertEqual(nd[i], items[i])
self.assertRaises(IndexError, nd.__getitem__, -6)
self.assertRaises(IndexError, nd.__getitem__, 5)
if is_memoryview_format(fmt):
mv = memoryview(nd)
self.assertEqual(mv, nd)
for i in range(-5, 5):
self.assertEqual(mv[i], items[i])
self.assertRaises(IndexError, mv.__getitem__, -6)
self.assertRaises(IndexError, mv.__getitem__, 5)
# getitem with null strides
for fmt, items, _ in iter_format(5):
ex = ndarray(items, shape=[5], flags=ND_WRITABLE, format=fmt)
nd = ndarray(ex, getbuf=PyBUF_CONTIG|PyBUF_FORMAT)
for i in range(-5, 5):
self.assertEqual(nd[i], items[i])
if is_memoryview_format(fmt):
mv = nd.memoryview_from_buffer()
self.assertIs(mv.__eq__(nd), NotImplemented)
for i in range(-5, 5):
self.assertEqual(mv[i], items[i])
# getitem with null format
items = [1,2,3,4,5]
ex = ndarray(items, shape=[5])
nd = ndarray(ex, getbuf=PyBUF_CONTIG_RO)
for i in range(-5, 5):
self.assertEqual(nd[i], items[i])
# getitem with null shape/strides/format
items = [1,2,3,4,5]
ex = ndarray(items, shape=[5])
nd = ndarray(ex, getbuf=PyBUF_SIMPLE)
for i in range(-5, 5):
self.assertEqual(nd[i], items[i])
def test_ndarray_index_setitem_single(self):
# assign single value
for fmt, items, single_item in iter_format(5):
nd = ndarray(items, shape=[5], format=fmt, flags=ND_WRITABLE)
for i in range(5):
items[i] = single_item
nd[i] = single_item
self.assertEqual(nd.tolist(), items)
self.assertRaises(IndexError, nd.__setitem__, -6, single_item)
self.assertRaises(IndexError, nd.__setitem__, 5, single_item)
if not is_memoryview_format(fmt):
continue
nd = ndarray(items, shape=[5], format=fmt, flags=ND_WRITABLE)
mv = memoryview(nd)
self.assertEqual(mv, nd)
for i in range(5):
items[i] = single_item
mv[i] = single_item
self.assertEqual(mv.tolist(), items)
self.assertRaises(IndexError, mv.__setitem__, -6, single_item)
self.assertRaises(IndexError, mv.__setitem__, 5, single_item)
# assign single value: lobject = robject
for fmt, items, single_item in iter_format(5):
nd = ndarray(items, shape=[5], format=fmt, flags=ND_WRITABLE)
for i in range(-5, 4):
items[i] = items[i+1]
nd[i] = nd[i+1]
self.assertEqual(nd.tolist(), items)
if not is_memoryview_format(fmt):
continue
nd = ndarray(items, shape=[5], format=fmt, flags=ND_WRITABLE)
mv = memoryview(nd)
self.assertEqual(mv, nd)
for i in range(-5, 4):
items[i] = items[i+1]
mv[i] = mv[i+1]
self.assertEqual(mv.tolist(), items)
def test_ndarray_index_getitem_multidim(self):
shape_t = (2, 3, 5)
nitems = prod(shape_t)
for shape in permutations(shape_t):
fmt, items, _ = randitems(nitems)
for flags in (0, ND_PIL):
# C array
nd = ndarray(items, shape=shape, format=fmt, flags=flags)
lst = carray(items, shape)
for i in range(-shape[0], shape[0]):
self.assertEqual(lst[i], nd[i].tolist())
for j in range(-shape[1], shape[1]):
self.assertEqual(lst[i][j], nd[i][j].tolist())
for k in range(-shape[2], shape[2]):
self.assertEqual(lst[i][j][k], nd[i][j][k])
# Fortran array
nd = ndarray(items, shape=shape, format=fmt,
flags=flags|ND_FORTRAN)
lst = farray(items, shape)
for i in range(-shape[0], shape[0]):
self.assertEqual(lst[i], nd[i].tolist())
for j in range(-shape[1], shape[1]):
self.assertEqual(lst[i][j], nd[i][j].tolist())
for k in range(shape[2], shape[2]):
self.assertEqual(lst[i][j][k], nd[i][j][k])
def test_ndarray_sequence(self):
nd = ndarray(1, shape=())
self.assertRaises(TypeError, eval, "1 in nd", locals())
mv = memoryview(nd)
self.assertEqual(mv, nd)
self.assertRaises(TypeError, eval, "1 in mv", locals())
for fmt, items, _ in iter_format(5):
nd = ndarray(items, shape=[5], format=fmt)
for i, v in enumerate(nd):
self.assertEqual(v, items[i])
self.assertTrue(v in nd)
if is_memoryview_format(fmt):
mv = memoryview(nd)
for i, v in enumerate(mv):
self.assertEqual(v, items[i])
self.assertTrue(v in mv)
def test_ndarray_slice_invalid(self):
items = [1,2,3,4,5,6,7,8]
# rvalue is not an exporter
xl = ndarray(items, shape=[8], flags=ND_WRITABLE)
ml = memoryview(xl)
self.assertRaises(TypeError, xl.__setitem__, slice(0,8,1), items)
self.assertRaises(TypeError, ml.__setitem__, slice(0,8,1), items)
# rvalue is not a full exporter
xl = ndarray(items, shape=[8], flags=ND_WRITABLE)
ex = ndarray(items, shape=[8], flags=ND_WRITABLE)
xr = ndarray(ex, getbuf=PyBUF_ND)
self.assertRaises(BufferError, xl.__setitem__, slice(0,8,1), xr)
# zero step
nd = ndarray(items, shape=[8], format="L", flags=ND_WRITABLE)
mv = memoryview(nd)
self.assertRaises(ValueError, nd.__getitem__, slice(0,1,0))
self.assertRaises(ValueError, mv.__getitem__, slice(0,1,0))
nd = ndarray(items, shape=[2,4], format="L", flags=ND_WRITABLE)
mv = memoryview(nd)
self.assertRaises(ValueError, nd.__getitem__,
(slice(0,1,1), slice(0,1,0)))
self.assertRaises(ValueError, nd.__getitem__,
(slice(0,1,0), slice(0,1,1)))
self.assertRaises(TypeError, nd.__getitem__, "@%$")
self.assertRaises(TypeError, nd.__getitem__, ("@%$", slice(0,1,1)))
self.assertRaises(TypeError, nd.__getitem__, (slice(0,1,1), {}))
# memoryview: not implemented
self.assertRaises(NotImplementedError, mv.__getitem__,
(slice(0,1,1), slice(0,1,0)))
self.assertRaises(TypeError, mv.__getitem__, "@%$")
# differing format
xl = ndarray(items, shape=[8], format="B", flags=ND_WRITABLE)
xr = ndarray(items, shape=[8], format="b")
ml = memoryview(xl)
mr = memoryview(xr)
self.assertRaises(ValueError, xl.__setitem__, slice(0,1,1), xr[7:8])
self.assertEqual(xl.tolist(), items)
self.assertRaises(ValueError, ml.__setitem__, slice(0,1,1), mr[7:8])
self.assertEqual(ml.tolist(), items)
# differing itemsize
xl = ndarray(items, shape=[8], format="B", flags=ND_WRITABLE)
yr = ndarray(items, shape=[8], format="L")
ml = memoryview(xl)
mr = memoryview(xr)
self.assertRaises(ValueError, xl.__setitem__, slice(0,1,1), xr[7:8])
self.assertEqual(xl.tolist(), items)
self.assertRaises(ValueError, ml.__setitem__, slice(0,1,1), mr[7:8])
self.assertEqual(ml.tolist(), items)
# differing ndim
xl = ndarray(items, shape=[2, 4], format="b", flags=ND_WRITABLE)
xr = ndarray(items, shape=[8], format="b")
ml = memoryview(xl)
mr = memoryview(xr)
self.assertRaises(ValueError, xl.__setitem__, slice(0,1,1), xr[7:8])
self.assertEqual(xl.tolist(), [[1,2,3,4], [5,6,7,8]])
self.assertRaises(NotImplementedError, ml.__setitem__, slice(0,1,1),
mr[7:8])
# differing shape
xl = ndarray(items, shape=[8], format="b", flags=ND_WRITABLE)
xr = ndarray(items, shape=[8], format="b")
ml = memoryview(xl)
mr = memoryview(xr)
self.assertRaises(ValueError, xl.__setitem__, slice(0,2,1), xr[7:8])
self.assertEqual(xl.tolist(), items)
self.assertRaises(ValueError, ml.__setitem__, slice(0,2,1), mr[7:8])
self.assertEqual(ml.tolist(), items)
# _testbuffer.c module functions
self.assertRaises(TypeError, slice_indices, slice(0,1,2), {})
self.assertRaises(TypeError, slice_indices, "###########", 1)
self.assertRaises(ValueError, slice_indices, slice(0,1,0), 4)
x = ndarray(items, shape=[8], format="b", flags=ND_PIL)
self.assertRaises(TypeError, x.add_suboffsets)
ex = ndarray(items, shape=[8], format="B")
x = ndarray(ex, getbuf=PyBUF_SIMPLE)
self.assertRaises(TypeError, x.add_suboffsets)
def test_ndarray_slice_zero_shape(self):
items = [1,2,3,4,5,6,7,8,9,10,11,12]
x = ndarray(items, shape=[12], format="L", flags=ND_WRITABLE)
y = ndarray(items, shape=[12], format="L")
x[4:4] = y[9:9]
self.assertEqual(x.tolist(), items)
ml = memoryview(x)
mr = memoryview(y)
self.assertEqual(ml, x)
self.assertEqual(ml, y)
ml[4:4] = mr[9:9]
self.assertEqual(ml.tolist(), items)
x = ndarray(items, shape=[3, 4], format="L", flags=ND_WRITABLE)
y = ndarray(items, shape=[4, 3], format="L")
x[1:2, 2:2] = y[1:2, 3:3]
self.assertEqual(x.tolist(), carray(items, [3, 4]))
def test_ndarray_slice_multidim(self):
shape_t = (2, 3, 5)
ndim = len(shape_t)
nitems = prod(shape_t)
for shape in permutations(shape_t):
fmt, items, _ = randitems(nitems)
itemsize = struct.calcsize(fmt)
for flags in (0, ND_PIL):
nd = ndarray(items, shape=shape, format=fmt, flags=flags)
lst = carray(items, shape)
for slices in rslices_ndim(ndim, shape):
listerr = None
try:
sliced = multislice(lst, slices)
except Exception as e:
listerr = e.__class__
nderr = None
try:
ndsliced = nd[slices]
except Exception as e:
nderr = e.__class__
if nderr or listerr:
self.assertIs(nderr, listerr)
else:
self.assertEqual(ndsliced.tolist(), sliced)
def test_ndarray_slice_redundant_suboffsets(self):
shape_t = (2, 3, 5, 2)
ndim = len(shape_t)
nitems = prod(shape_t)
for shape in permutations(shape_t):
fmt, items, _ = randitems(nitems)
itemsize = struct.calcsize(fmt)
nd = ndarray(items, shape=shape, format=fmt)
nd.add_suboffsets()
ex = ndarray(items, shape=shape, format=fmt)
ex.add_suboffsets()
mv = memoryview(ex)
lst = carray(items, shape)
for slices in rslices_ndim(ndim, shape):
listerr = None
try:
sliced = multislice(lst, slices)
except Exception as e:
listerr = e.__class__
nderr = None
try:
ndsliced = nd[slices]
except Exception as e:
nderr = e.__class__
if nderr or listerr:
self.assertIs(nderr, listerr)
else:
self.assertEqual(ndsliced.tolist(), sliced)
def test_ndarray_slice_assign_single(self):
for fmt, items, _ in iter_format(5):
for lslice in genslices(5):
for rslice in genslices(5):
for flags in (0, ND_PIL):
f = flags|ND_WRITABLE
nd = ndarray(items, shape=[5], format=fmt, flags=f)
ex = ndarray(items, shape=[5], format=fmt, flags=f)
mv = memoryview(ex)
lsterr = None
diff_structure = None
lst = items[:]
try:
lval = lst[lslice]
rval = lst[rslice]
lst[lslice] = lst[rslice]
diff_structure = len(lval) != len(rval)
except Exception as e:
lsterr = e.__class__
nderr = None
try:
nd[lslice] = nd[rslice]
except Exception as e:
nderr = e.__class__
if diff_structure: # ndarray cannot change shape
self.assertIs(nderr, ValueError)
else:
self.assertEqual(nd.tolist(), lst)
self.assertIs(nderr, lsterr)
if not is_memoryview_format(fmt):
continue
mverr = None
try:
mv[lslice] = mv[rslice]
except Exception as e:
mverr = e.__class__
if diff_structure: # memoryview cannot change shape
self.assertIs(mverr, ValueError)
else:
self.assertEqual(mv.tolist(), lst)
self.assertEqual(mv, nd)
self.assertIs(mverr, lsterr)
self.verify(mv, obj=ex,
itemsize=nd.itemsize, fmt=fmt, readonly=False,
ndim=nd.ndim, shape=nd.shape, strides=nd.strides,
lst=nd.tolist())
def test_ndarray_slice_assign_multidim(self):
shape_t = (2, 3, 5)
ndim = len(shape_t)
nitems = prod(shape_t)
for shape in permutations(shape_t):
fmt, items, _ = randitems(nitems)
for flags in (0, ND_PIL):
for _ in range(ITERATIONS):
lslices, rslices = randslice_from_shape(ndim, shape)
nd = ndarray(items, shape=shape, format=fmt,
flags=flags|ND_WRITABLE)
lst = carray(items, shape)
listerr = None
try:
result = multislice_assign(lst, lst, lslices, rslices)
except Exception as e:
listerr = e.__class__
nderr = None
try:
nd[lslices] = nd[rslices]
except Exception as e:
nderr = e.__class__
if nderr or listerr:
self.assertIs(nderr, listerr)
else:
self.assertEqual(nd.tolist(), result)
def test_ndarray_random(self):
# construction of valid arrays
for _ in range(ITERATIONS):
for fmt in fmtdict['@']:
itemsize = struct.calcsize(fmt)
t = rand_structure(itemsize, True, maxdim=MAXDIM,
maxshape=MAXSHAPE)
self.assertTrue(verify_structure(*t))
items = randitems_from_structure(fmt, t)
x = ndarray_from_structure(items, fmt, t)
xlist = x.tolist()
mv = memoryview(x)
if is_memoryview_format(fmt):
mvlist = mv.tolist()
self.assertEqual(mvlist, xlist)
if t[2] > 0:
# ndim > 0: test against suboffsets representation.
y = ndarray_from_structure(items, fmt, t, flags=ND_PIL)
ylist = y.tolist()
self.assertEqual(xlist, ylist)
mv = memoryview(y)
if is_memoryview_format(fmt):
self.assertEqual(mv, y)
mvlist = mv.tolist()
self.assertEqual(mvlist, ylist)
if numpy_array:
shape = t[3]
if 0 in shape:
continue # http://projects.scipy.org/numpy/ticket/1910
z = numpy_array_from_structure(items, fmt, t)
self.verify(x, obj=None,
itemsize=z.itemsize, fmt=fmt, readonly=False,
ndim=z.ndim, shape=z.shape, strides=z.strides,
lst=z.tolist())
def test_ndarray_random_invalid(self):
# exceptions during construction of invalid arrays
for _ in range(ITERATIONS):
for fmt in fmtdict['@']:
itemsize = struct.calcsize(fmt)
t = rand_structure(itemsize, False, maxdim=MAXDIM,
maxshape=MAXSHAPE)
self.assertFalse(verify_structure(*t))
items = randitems_from_structure(fmt, t)
nderr = False
try:
x = ndarray_from_structure(items, fmt, t)
except Exception as e:
nderr = e.__class__
self.assertTrue(nderr)
if numpy_array:
numpy_err = False
try:
y = numpy_array_from_structure(items, fmt, t)
except Exception as e:
numpy_err = e.__class__
if 0: # http://projects.scipy.org/numpy/ticket/1910
self.assertTrue(numpy_err)
def test_ndarray_random_slice_assign(self):
# valid slice assignments
for _ in range(ITERATIONS):
for fmt in fmtdict['@']:
itemsize = struct.calcsize(fmt)
lshape, rshape, lslices, rslices = \
rand_aligned_slices(maxdim=MAXDIM, maxshape=MAXSHAPE)
tl = rand_structure(itemsize, True, shape=lshape)
tr = rand_structure(itemsize, True, shape=rshape)
self.assertTrue(verify_structure(*tl))
self.assertTrue(verify_structure(*tr))
litems = randitems_from_structure(fmt, tl)
ritems = randitems_from_structure(fmt, tr)
xl = ndarray_from_structure(litems, fmt, tl)
xr = ndarray_from_structure(ritems, fmt, tr)
xl[lslices] = xr[rslices]
xllist = xl.tolist()
xrlist = xr.tolist()
ml = memoryview(xl)
mr = memoryview(xr)
self.assertEqual(ml.tolist(), xllist)
self.assertEqual(mr.tolist(), xrlist)
if tl[2] > 0 and tr[2] > 0:
# ndim > 0: test against suboffsets representation.
yl = ndarray_from_structure(litems, fmt, tl, flags=ND_PIL)
yr = ndarray_from_structure(ritems, fmt, tr, flags=ND_PIL)
yl[lslices] = yr[rslices]
yllist = yl.tolist()
yrlist = yr.tolist()
self.assertEqual(xllist, yllist)
self.assertEqual(xrlist, yrlist)
ml = memoryview(yl)
mr = memoryview(yr)
self.assertEqual(ml.tolist(), yllist)
self.assertEqual(mr.tolist(), yrlist)
if numpy_array:
if 0 in lshape or 0 in rshape:
continue # http://projects.scipy.org/numpy/ticket/1910
zl = numpy_array_from_structure(litems, fmt, tl)
zr = numpy_array_from_structure(ritems, fmt, tr)
zl[lslices] = zr[rslices]
if not is_overlapping(tl) and not is_overlapping(tr):
# Slice assignment of overlapping structures
# is undefined in NumPy.
self.verify(xl, obj=None,
itemsize=zl.itemsize, fmt=fmt, readonly=False,
ndim=zl.ndim, shape=zl.shape,
strides=zl.strides, lst=zl.tolist())
self.verify(xr, obj=None,
itemsize=zr.itemsize, fmt=fmt, readonly=False,
ndim=zr.ndim, shape=zr.shape,
strides=zr.strides, lst=zr.tolist())
def test_ndarray_re_export(self):
items = [1,2,3,4,5,6,7,8,9,10,11,12]
nd = ndarray(items, shape=[3,4], flags=ND_PIL)
ex = ndarray(nd)
self.assertTrue(ex.flags & ND_PIL)
self.assertIs(ex.obj, nd)
self.assertEqual(ex.suboffsets, (0, -1))
self.assertFalse(ex.c_contiguous)
self.assertFalse(ex.f_contiguous)
self.assertFalse(ex.contiguous)
def test_ndarray_zero_shape(self):
# zeros in shape
for flags in (0, ND_PIL):
nd = ndarray([1,2,3], shape=[0], flags=flags)
mv = memoryview(nd)
self.assertEqual(mv, nd)
self.assertEqual(nd.tolist(), [])
self.assertEqual(mv.tolist(), [])
nd = ndarray([1,2,3], shape=[0,3,3], flags=flags)
self.assertEqual(nd.tolist(), [])
nd = ndarray([1,2,3], shape=[3,0,3], flags=flags)
self.assertEqual(nd.tolist(), [[], [], []])
nd = ndarray([1,2,3], shape=[3,3,0], flags=flags)
self.assertEqual(nd.tolist(),
[[[], [], []], [[], [], []], [[], [], []]])
def test_ndarray_zero_strides(self):
# zero strides
for flags in (0, ND_PIL):
nd = ndarray([1], shape=[5], strides=[0], flags=flags)
mv = memoryview(nd)
self.assertEqual(mv, nd)
self.assertEqual(nd.tolist(), [1, 1, 1, 1, 1])
self.assertEqual(mv.tolist(), [1, 1, 1, 1, 1])
def test_ndarray_offset(self):
nd = ndarray(list(range(20)), shape=[3], offset=7)
self.assertEqual(nd.offset, 7)
self.assertEqual(nd.tolist(), [7,8,9])
def test_ndarray_memoryview_from_buffer(self):
for flags in (0, ND_PIL):
nd = ndarray(list(range(3)), shape=[3], flags=flags)
m = nd.memoryview_from_buffer()
self.assertEqual(m, nd)
def test_ndarray_get_pointer(self):
for flags in (0, ND_PIL):
nd = ndarray(list(range(3)), shape=[3], flags=flags)
for i in range(3):
self.assertEqual(nd[i], get_pointer(nd, [i]))
def test_ndarray_tolist_null_strides(self):
ex = ndarray(list(range(20)), shape=[2,2,5])
nd = ndarray(ex, getbuf=PyBUF_ND|PyBUF_FORMAT)
self.assertEqual(nd.tolist(), ex.tolist())
m = memoryview(ex)
self.assertEqual(m.tolist(), ex.tolist())
def test_ndarray_cmp_contig(self):
self.assertFalse(cmp_contig(b"123", b"456"))
x = ndarray(list(range(12)), shape=[3,4])
y = ndarray(list(range(12)), shape=[4,3])
self.assertFalse(cmp_contig(x, y))
x = ndarray([1], shape=[1], format="B")
self.assertTrue(cmp_contig(x, b'\x01'))
self.assertTrue(cmp_contig(b'\x01', x))
def test_ndarray_hash(self):
a = array.array('L', [1,2,3])
nd = ndarray(a)
self.assertRaises(ValueError, hash, nd)
# one-dimensional
b = bytes(list(range(12)))
nd = ndarray(list(range(12)), shape=[12])
self.assertEqual(hash(nd), hash(b))
# C-contiguous
nd = ndarray(list(range(12)), shape=[3,4])
self.assertEqual(hash(nd), hash(b))
nd = ndarray(list(range(12)), shape=[3,2,2])
self.assertEqual(hash(nd), hash(b))
# Fortran contiguous
b = bytes(transpose(list(range(12)), shape=[4,3]))
nd = ndarray(list(range(12)), shape=[3,4], flags=ND_FORTRAN)
self.assertEqual(hash(nd), hash(b))
b = bytes(transpose(list(range(12)), shape=[2,3,2]))
nd = ndarray(list(range(12)), shape=[2,3,2], flags=ND_FORTRAN)
self.assertEqual(hash(nd), hash(b))
# suboffsets
b = bytes(list(range(12)))
nd = ndarray(list(range(12)), shape=[2,2,3], flags=ND_PIL)
self.assertEqual(hash(nd), hash(b))
# non-byte formats
nd = ndarray(list(range(12)), shape=[2,2,3], format='L')
self.assertEqual(hash(nd), hash(nd.tobytes()))
def test_py_buffer_to_contiguous(self):
# The requests are used in _testbuffer.c:py_buffer_to_contiguous
# to generate buffers without full information for testing.
requests = (
# distinct flags
PyBUF_INDIRECT, PyBUF_STRIDES, PyBUF_ND, PyBUF_SIMPLE,
# compound requests
PyBUF_FULL, PyBUF_FULL_RO,
PyBUF_RECORDS, PyBUF_RECORDS_RO,
PyBUF_STRIDED, PyBUF_STRIDED_RO,
PyBUF_CONTIG, PyBUF_CONTIG_RO,
)
# no buffer interface
self.assertRaises(TypeError, py_buffer_to_contiguous, {}, 'F',
PyBUF_FULL_RO)
# scalar, read-only request
nd = ndarray(9, shape=(), format="L", flags=ND_WRITABLE)
for order in ['C', 'F', 'A']:
for request in requests:
b = py_buffer_to_contiguous(nd, order, request)
self.assertEqual(b, nd.tobytes())
# zeros in shape
nd = ndarray([1], shape=[0], format="L", flags=ND_WRITABLE)
for order in ['C', 'F', 'A']:
for request in requests:
b = py_buffer_to_contiguous(nd, order, request)
self.assertEqual(b, b'')
nd = ndarray(list(range(8)), shape=[2, 0, 7], format="L",
flags=ND_WRITABLE)
for order in ['C', 'F', 'A']:
for request in requests:
b = py_buffer_to_contiguous(nd, order, request)
self.assertEqual(b, b'')
### One-dimensional arrays are trivial, since Fortran and C order
### are the same.
# one-dimensional
for f in [0, ND_FORTRAN]:
nd = ndarray([1], shape=[1], format="h", flags=f|ND_WRITABLE)
ndbytes = nd.tobytes()
for order in ['C', 'F', 'A']:
for request in requests:
b = py_buffer_to_contiguous(nd, order, request)
self.assertEqual(b, ndbytes)
nd = ndarray([1, 2, 3], shape=[3], format="b", flags=f|ND_WRITABLE)
ndbytes = nd.tobytes()
for order in ['C', 'F', 'A']:
for request in requests:
b = py_buffer_to_contiguous(nd, order, request)
self.assertEqual(b, ndbytes)
# one-dimensional, non-contiguous input
nd = ndarray([1, 2, 3], shape=[2], strides=[2], flags=ND_WRITABLE)
ndbytes = nd.tobytes()
for order in ['C', 'F', 'A']:
for request in [PyBUF_STRIDES, PyBUF_FULL]:
b = py_buffer_to_contiguous(nd, order, request)
self.assertEqual(b, ndbytes)
nd = nd[::-1]
ndbytes = nd.tobytes()
for order in ['C', 'F', 'A']:
for request in requests:
try:
b = py_buffer_to_contiguous(nd, order, request)
except BufferError:
continue
self.assertEqual(b, ndbytes)
###
### Multi-dimensional arrays:
###
### The goal here is to preserve the logical representation of the
### input array but change the physical representation if necessary.
###
### _testbuffer example:
### ====================
###
### C input array:
### --------------
### >>> nd = ndarray(list(range(12)), shape=[3, 4])
### >>> nd.tolist()
### [[0, 1, 2, 3],
### [4, 5, 6, 7],
### [8, 9, 10, 11]]
###
### Fortran output:
### ---------------
### >>> py_buffer_to_contiguous(nd, 'F', PyBUF_FULL_RO)
### >>> b'\x00\x04\x08\x01\x05\t\x02\x06\n\x03\x07\x0b'
###
### The return value corresponds to this input list for
### _testbuffer's ndarray:
### >>> nd = ndarray([0,4,8,1,5,9,2,6,10,3,7,11], shape=[3,4],
### flags=ND_FORTRAN)
### >>> nd.tolist()
### [[0, 1, 2, 3],
### [4, 5, 6, 7],
### [8, 9, 10, 11]]
###
### The logical array is the same, but the values in memory are now
### in Fortran order.
###
### NumPy example:
### ==============
### _testbuffer's ndarray takes lists to initialize the memory.
### Here's the same sequence in NumPy:
###
### C input:
### --------
### >>> nd = ndarray(buffer=bytearray(list(range(12))),
### shape=[3, 4], dtype='B')
### >>> nd
### array([[ 0, 1, 2, 3],
### [ 4, 5, 6, 7],
### [ 8, 9, 10, 11]], dtype=uint8)
###
### Fortran output:
### ---------------
### >>> fortran_buf = nd.tostring(order='F')
### >>> fortran_buf
### b'\x00\x04\x08\x01\x05\t\x02\x06\n\x03\x07\x0b'
###
### >>> nd = ndarray(buffer=fortran_buf, shape=[3, 4],
### dtype='B', order='F')
###
### >>> nd
### array([[ 0, 1, 2, 3],
### [ 4, 5, 6, 7],
### [ 8, 9, 10, 11]], dtype=uint8)
###
# multi-dimensional, contiguous input
lst = list(range(12))
for f in [0, ND_FORTRAN]:
nd = ndarray(lst, shape=[3, 4], flags=f|ND_WRITABLE)
if numpy_array:
na = numpy_array(buffer=bytearray(lst),
shape=[3, 4], dtype='B',
order='C' if f == 0 else 'F')
# 'C' request
if f == ND_FORTRAN: # 'F' to 'C'
x = ndarray(transpose(lst, [4, 3]), shape=[3, 4],
flags=ND_WRITABLE)
expected = x.tobytes()
else:
expected = nd.tobytes()
for request in requests:
try:
b = py_buffer_to_contiguous(nd, 'C', request)
except BufferError:
continue
self.assertEqual(b, expected)
# Check that output can be used as the basis for constructing
# a C array that is logically identical to the input array.
y = ndarray([v for v in b], shape=[3, 4], flags=ND_WRITABLE)
self.assertEqual(memoryview(y), memoryview(nd))
if numpy_array:
self.assertEqual(b, na.tostring(order='C'))
# 'F' request
if f == 0: # 'C' to 'F'
x = ndarray(transpose(lst, [3, 4]), shape=[4, 3],
flags=ND_WRITABLE)
else:
x = ndarray(lst, shape=[3, 4], flags=ND_WRITABLE)
expected = x.tobytes()
for request in [PyBUF_FULL, PyBUF_FULL_RO, PyBUF_INDIRECT,
PyBUF_STRIDES, PyBUF_ND]:
try:
b = py_buffer_to_contiguous(nd, 'F', request)
except BufferError:
continue
self.assertEqual(b, expected)
# Check that output can be used as the basis for constructing
# a Fortran array that is logically identical to the input array.
y = ndarray([v for v in b], shape=[3, 4], flags=ND_FORTRAN|ND_WRITABLE)
self.assertEqual(memoryview(y), memoryview(nd))
if numpy_array:
self.assertEqual(b, na.tostring(order='F'))
# 'A' request
if f == ND_FORTRAN:
x = ndarray(lst, shape=[3, 4], flags=ND_WRITABLE)
expected = x.tobytes()
else:
expected = nd.tobytes()
for request in [PyBUF_FULL, PyBUF_FULL_RO, PyBUF_INDIRECT,
PyBUF_STRIDES, PyBUF_ND]:
try:
b = py_buffer_to_contiguous(nd, 'A', request)
except BufferError:
continue
self.assertEqual(b, expected)
# Check that output can be used as the basis for constructing
# an array with order=f that is logically identical to the input
# array.
y = ndarray([v for v in b], shape=[3, 4], flags=f|ND_WRITABLE)
self.assertEqual(memoryview(y), memoryview(nd))
if numpy_array:
self.assertEqual(b, na.tostring(order='A'))
# multi-dimensional, non-contiguous input
nd = ndarray(list(range(12)), shape=[3, 4], flags=ND_WRITABLE|ND_PIL)
# 'C'
b = py_buffer_to_contiguous(nd, 'C', PyBUF_FULL_RO)
self.assertEqual(b, nd.tobytes())
y = ndarray([v for v in b], shape=[3, 4], flags=ND_WRITABLE)
self.assertEqual(memoryview(y), memoryview(nd))
# 'F'
b = py_buffer_to_contiguous(nd, 'F', PyBUF_FULL_RO)
x = ndarray(transpose(lst, [3, 4]), shape=[4, 3], flags=ND_WRITABLE)
self.assertEqual(b, x.tobytes())
y = ndarray([v for v in b], shape=[3, 4], flags=ND_FORTRAN|ND_WRITABLE)
self.assertEqual(memoryview(y), memoryview(nd))
# 'A'
b = py_buffer_to_contiguous(nd, 'A', PyBUF_FULL_RO)
self.assertEqual(b, nd.tobytes())
y = ndarray([v for v in b], shape=[3, 4], flags=ND_WRITABLE)
self.assertEqual(memoryview(y), memoryview(nd))
def test_memoryview_construction(self):
items_shape = [(9, []), ([1,2,3], [3]), (list(range(2*3*5)), [2,3,5])]
# NumPy style, C-contiguous:
for items, shape in items_shape:
# From PEP-3118 compliant exporter:
ex = ndarray(items, shape=shape)
m = memoryview(ex)
self.assertTrue(m.c_contiguous)
self.assertTrue(m.contiguous)
ndim = len(shape)
strides = strides_from_shape(ndim, shape, 1, 'C')
lst = carray(items, shape)
self.verify(m, obj=ex,
itemsize=1, fmt='B', readonly=True,
ndim=ndim, shape=shape, strides=strides,
lst=lst)
# From memoryview:
m2 = memoryview(m)
self.verify(m2, obj=ex,
itemsize=1, fmt='B', readonly=True,
ndim=ndim, shape=shape, strides=strides,
lst=lst)
# PyMemoryView_FromBuffer(): no strides
nd = ndarray(ex, getbuf=PyBUF_CONTIG_RO|PyBUF_FORMAT)
self.assertEqual(nd.strides, ())
m = nd.memoryview_from_buffer()
self.verify(m, obj=None,
itemsize=1, fmt='B', readonly=True,
ndim=ndim, shape=shape, strides=strides,
lst=lst)
# PyMemoryView_FromBuffer(): no format, shape, strides
nd = ndarray(ex, getbuf=PyBUF_SIMPLE)
self.assertEqual(nd.format, '')
self.assertEqual(nd.shape, ())
self.assertEqual(nd.strides, ())
m = nd.memoryview_from_buffer()
lst = [items] if ndim == 0 else items
self.verify(m, obj=None,
itemsize=1, fmt='B', readonly=True,
ndim=1, shape=[ex.nbytes], strides=(1,),
lst=lst)
# NumPy style, Fortran contiguous:
for items, shape in items_shape:
# From PEP-3118 compliant exporter:
ex = ndarray(items, shape=shape, flags=ND_FORTRAN)
m = memoryview(ex)
self.assertTrue(m.f_contiguous)
self.assertTrue(m.contiguous)
ndim = len(shape)
strides = strides_from_shape(ndim, shape, 1, 'F')
lst = farray(items, shape)
self.verify(m, obj=ex,
itemsize=1, fmt='B', readonly=True,
ndim=ndim, shape=shape, strides=strides,
lst=lst)
# From memoryview:
m2 = memoryview(m)
self.verify(m2, obj=ex,
itemsize=1, fmt='B', readonly=True,
ndim=ndim, shape=shape, strides=strides,
lst=lst)
# PIL style:
for items, shape in items_shape[1:]:
# From PEP-3118 compliant exporter:
ex = ndarray(items, shape=shape, flags=ND_PIL)
m = memoryview(ex)
ndim = len(shape)
lst = carray(items, shape)
self.verify(m, obj=ex,
itemsize=1, fmt='B', readonly=True,
ndim=ndim, shape=shape, strides=ex.strides,
lst=lst)
# From memoryview:
m2 = memoryview(m)
self.verify(m2, obj=ex,
itemsize=1, fmt='B', readonly=True,
ndim=ndim, shape=shape, strides=ex.strides,
lst=lst)
# Invalid number of arguments:
self.assertRaises(TypeError, memoryview, b'9', 'x')
# Not a buffer provider:
self.assertRaises(TypeError, memoryview, {})
# Non-compliant buffer provider:
ex = ndarray([1,2,3], shape=[3])
nd = ndarray(ex, getbuf=PyBUF_SIMPLE)
self.assertRaises(BufferError, memoryview, nd)
nd = ndarray(ex, getbuf=PyBUF_CONTIG_RO|PyBUF_FORMAT)
self.assertRaises(BufferError, memoryview, nd)
# ndim > 64
nd = ndarray([1]*128, shape=[1]*128, format='L')
self.assertRaises(ValueError, memoryview, nd)
self.assertRaises(ValueError, nd.memoryview_from_buffer)
self.assertRaises(ValueError, get_contiguous, nd, PyBUF_READ, 'C')
self.assertRaises(ValueError, get_contiguous, nd, PyBUF_READ, 'F')
self.assertRaises(ValueError, get_contiguous, nd[::-1], PyBUF_READ, 'C')
def test_memoryview_cast_zero_shape(self):
# Casts are undefined if buffer is multidimensional and shape
# contains zeros. These arrays are regarded as C-contiguous by
# Numpy and PyBuffer_GetContiguous(), so they are not caught by
# the test for C-contiguity in memory_cast().
items = [1,2,3]
for shape in ([0,3,3], [3,0,3], [0,3,3]):
ex = ndarray(items, shape=shape)
self.assertTrue(ex.c_contiguous)
msrc = memoryview(ex)
self.assertRaises(TypeError, msrc.cast, 'c')
# Monodimensional empty view can be cast (issue #19014).
for fmt, _, _ in iter_format(1, 'memoryview'):
msrc = memoryview(b'')
m = msrc.cast(fmt)
self.assertEqual(m.tobytes(), b'')
self.assertEqual(m.tolist(), [])
check_sizeof = support.check_sizeof
def test_memoryview_sizeof(self):
check = self.check_sizeof
vsize = support.calcvobjsize
base_struct = 'Pnin 2P2n2i5P P'
per_dim = '3n'
items = list(range(8))
check(memoryview(b''), vsize(base_struct + 1 * per_dim))
a = ndarray(items, shape=[2, 4], format="b")
check(memoryview(a), vsize(base_struct + 2 * per_dim))
a = ndarray(items, shape=[2, 2, 2], format="b")
check(memoryview(a), vsize(base_struct + 3 * per_dim))
def test_memoryview_struct_module(self):
class INT(object):
def __init__(self, val):
self.val = val
def __int__(self):
return self.val
class IDX(object):
def __init__(self, val):
self.val = val
def __index__(self):
return self.val
def f(): return 7
values = [INT(9), IDX(9),
2.2+3j, Decimal("-21.1"), 12.2, Fraction(5, 2),
[1,2,3], {4,5,6}, {7:8}, (), (9,),
True, False, None, Ellipsis,
b'a', b'abc', bytearray(b'a'), bytearray(b'abc'),
'a', 'abc', r'a', r'abc',
f, lambda x: x]
for fmt, items, item in iter_format(10, 'memoryview'):
ex = ndarray(items, shape=[10], format=fmt, flags=ND_WRITABLE)
nd = ndarray(items, shape=[10], format=fmt, flags=ND_WRITABLE)
m = memoryview(ex)
struct.pack_into(fmt, nd, 0, item)
m[0] = item
self.assertEqual(m[0], nd[0])
itemsize = struct.calcsize(fmt)
if 'P' in fmt:
continue
for v in values:
struct_err = None
try:
struct.pack_into(fmt, nd, itemsize, v)
except struct.error:
struct_err = struct.error
mv_err = None
try:
m[1] = v
except (TypeError, ValueError) as e:
mv_err = e.__class__
if struct_err or mv_err:
self.assertIsNot(struct_err, None)
self.assertIsNot(mv_err, None)
else:
self.assertEqual(m[1], nd[1])
def test_memoryview_cast_zero_strides(self):
# Casts are undefined if strides contains zeros. These arrays are
# (sometimes!) regarded as C-contiguous by Numpy, but not by
# PyBuffer_GetContiguous().
ex = ndarray([1,2,3], shape=[3], strides=[0])
self.assertFalse(ex.c_contiguous)
msrc = memoryview(ex)
self.assertRaises(TypeError, msrc.cast, 'c')
def test_memoryview_cast_invalid(self):
# invalid format
for sfmt in NON_BYTE_FORMAT:
sformat = '@' + sfmt if randrange(2) else sfmt
ssize = struct.calcsize(sformat)
for dfmt in NON_BYTE_FORMAT:
dformat = '@' + dfmt if randrange(2) else dfmt
dsize = struct.calcsize(dformat)
ex = ndarray(list(range(32)), shape=[32//ssize], format=sformat)
msrc = memoryview(ex)
self.assertRaises(TypeError, msrc.cast, dfmt, [32//dsize])
for sfmt, sitems, _ in iter_format(1):
ex = ndarray(sitems, shape=[1], format=sfmt)
msrc = memoryview(ex)
for dfmt, _, _ in iter_format(1):
if not is_memoryview_format(dfmt):
self.assertRaises(ValueError, msrc.cast, dfmt,
[32//dsize])
else:
if not is_byte_format(sfmt) and not is_byte_format(dfmt):
self.assertRaises(TypeError, msrc.cast, dfmt,
[32//dsize])
# invalid shape
size_h = struct.calcsize('h')
size_d = struct.calcsize('d')
ex = ndarray(list(range(2*2*size_d)), shape=[2,2,size_d], format='h')
msrc = memoryview(ex)
self.assertRaises(TypeError, msrc.cast, shape=[2,2,size_h], format='d')
ex = ndarray(list(range(120)), shape=[1,2,3,4,5])
m = memoryview(ex)
# incorrect number of args
self.assertRaises(TypeError, m.cast)
self.assertRaises(TypeError, m.cast, 1, 2, 3)
# incorrect dest format type
self.assertRaises(TypeError, m.cast, {})
# incorrect dest format
self.assertRaises(ValueError, m.cast, "X")
self.assertRaises(ValueError, m.cast, "@X")
self.assertRaises(ValueError, m.cast, "@XY")
# dest format not implemented
self.assertRaises(ValueError, m.cast, "=B")
self.assertRaises(ValueError, m.cast, "!L")
self.assertRaises(ValueError, m.cast, "<P")
self.assertRaises(ValueError, m.cast, ">l")
self.assertRaises(ValueError, m.cast, "BI")
self.assertRaises(ValueError, m.cast, "xBI")
# src format not implemented
ex = ndarray([(1,2), (3,4)], shape=[2], format="II")
m = memoryview(ex)
self.assertRaises(NotImplementedError, m.__getitem__, 0)
self.assertRaises(NotImplementedError, m.__setitem__, 0, 8)
self.assertRaises(NotImplementedError, m.tolist)
# incorrect shape type
ex = ndarray(list(range(120)), shape=[1,2,3,4,5])
m = memoryview(ex)
self.assertRaises(TypeError, m.cast, "B", shape={})
# incorrect shape elements
ex = ndarray(list(range(120)), shape=[2*3*4*5])
m = memoryview(ex)
self.assertRaises(OverflowError, m.cast, "B", shape=[2**64])
self.assertRaises(ValueError, m.cast, "B", shape=[-1])
self.assertRaises(ValueError, m.cast, "B", shape=[2,3,4,5,6,7,-1])
self.assertRaises(ValueError, m.cast, "B", shape=[2,3,4,5,6,7,0])
self.assertRaises(TypeError, m.cast, "B", shape=[2,3,4,5,6,7,'x'])
# N-D -> N-D cast
ex = ndarray(list([9 for _ in range(3*5*7*11)]), shape=[3,5,7,11])
m = memoryview(ex)
self.assertRaises(TypeError, m.cast, "I", shape=[2,3,4,5])
# cast with ndim > 64
nd = ndarray(list(range(128)), shape=[128], format='I')
m = memoryview(nd)
self.assertRaises(ValueError, m.cast, 'I', [1]*128)
# view->len not a multiple of itemsize
ex = ndarray(list([9 for _ in range(3*5*7*11)]), shape=[3*5*7*11])
m = memoryview(ex)
self.assertRaises(TypeError, m.cast, "I", shape=[2,3,4,5])
# product(shape) * itemsize != buffer size
ex = ndarray(list([9 for _ in range(3*5*7*11)]), shape=[3*5*7*11])
m = memoryview(ex)
self.assertRaises(TypeError, m.cast, "B", shape=[2,3,4,5])
# product(shape) * itemsize overflow
nd = ndarray(list(range(128)), shape=[128], format='I')
m1 = memoryview(nd)
nd = ndarray(list(range(128)), shape=[128], format='B')
m2 = memoryview(nd)
if sys.maxsize == 2**63-1:
self.assertRaises(TypeError, m1.cast, 'B',
[7, 7, 73, 127, 337, 92737, 649657])
self.assertRaises(ValueError, m1.cast, 'B',
[2**20, 2**20, 2**10, 2**10, 2**3])
self.assertRaises(ValueError, m2.cast, 'I',
[2**20, 2**20, 2**10, 2**10, 2**1])
else:
self.assertRaises(TypeError, m1.cast, 'B',
[1, 2147483647])
self.assertRaises(ValueError, m1.cast, 'B',
[2**10, 2**10, 2**5, 2**5, 2**1])
self.assertRaises(ValueError, m2.cast, 'I',
[2**10, 2**10, 2**5, 2**3, 2**1])
def test_memoryview_cast(self):
bytespec = (
('B', lambda ex: list(ex.tobytes())),
('b', lambda ex: [x-256 if x > 127 else x for x in list(ex.tobytes())]),
('c', lambda ex: [bytes(chr(x), 'latin-1') for x in list(ex.tobytes())]),
)
def iter_roundtrip(ex, m, items, fmt):
srcsize = struct.calcsize(fmt)
for bytefmt, to_bytelist in bytespec:
m2 = m.cast(bytefmt)
lst = to_bytelist(ex)
self.verify(m2, obj=ex,
itemsize=1, fmt=bytefmt, readonly=False,
ndim=1, shape=[31*srcsize], strides=(1,),
lst=lst, cast=True)
m3 = m2.cast(fmt)
self.assertEqual(m3, ex)
lst = ex.tolist()
self.verify(m3, obj=ex,
itemsize=srcsize, fmt=fmt, readonly=False,
ndim=1, shape=[31], strides=(srcsize,),
lst=lst, cast=True)
# cast from ndim = 0 to ndim = 1
srcsize = struct.calcsize('I')
ex = ndarray(9, shape=[], format='I')
destitems, destshape = cast_items(ex, 'B', 1)
m = memoryview(ex)
m2 = m.cast('B')
self.verify(m2, obj=ex,
itemsize=1, fmt='B', readonly=True,
ndim=1, shape=destshape, strides=(1,),
lst=destitems, cast=True)
# cast from ndim = 1 to ndim = 0
destsize = struct.calcsize('I')
ex = ndarray([9]*destsize, shape=[destsize], format='B')
destitems, destshape = cast_items(ex, 'I', destsize, shape=[])
m = memoryview(ex)
m2 = m.cast('I', shape=[])
self.verify(m2, obj=ex,
itemsize=destsize, fmt='I', readonly=True,
ndim=0, shape=(), strides=(),
lst=destitems, cast=True)
# array.array: roundtrip to/from bytes
for fmt, items, _ in iter_format(31, 'array'):
ex = array.array(fmt, items)
m = memoryview(ex)
iter_roundtrip(ex, m, items, fmt)
# ndarray: roundtrip to/from bytes
for fmt, items, _ in iter_format(31, 'memoryview'):
ex = ndarray(items, shape=[31], format=fmt, flags=ND_WRITABLE)
m = memoryview(ex)
iter_roundtrip(ex, m, items, fmt)
def test_memoryview_cast_1D_ND(self):
# Cast between C-contiguous buffers. At least one buffer must
# be 1D, at least one format must be 'c', 'b' or 'B'.
for _tshape in gencastshapes():
for char in fmtdict['@']:
# Casts to _Bool are undefined if the source contains values
# other than 0 or 1.
if char == "?":
continue
tfmt = ('', '@')[randrange(2)] + char
tsize = struct.calcsize(tfmt)
n = prod(_tshape) * tsize
obj = 'memoryview' if is_byte_format(tfmt) else 'bytefmt'
for fmt, items, _ in iter_format(n, obj):
size = struct.calcsize(fmt)
shape = [n] if n > 0 else []
tshape = _tshape + [size]
ex = ndarray(items, shape=shape, format=fmt)
m = memoryview(ex)
titems, tshape = cast_items(ex, tfmt, tsize, shape=tshape)
if titems is None:
self.assertRaises(TypeError, m.cast, tfmt, tshape)
continue
if titems == 'nan':
continue # NaNs in lists are a recipe for trouble.
# 1D -> ND
nd = ndarray(titems, shape=tshape, format=tfmt)
m2 = m.cast(tfmt, shape=tshape)
ndim = len(tshape)
strides = nd.strides
lst = nd.tolist()
self.verify(m2, obj=ex,
itemsize=tsize, fmt=tfmt, readonly=True,
ndim=ndim, shape=tshape, strides=strides,
lst=lst, cast=True)
# ND -> 1D
m3 = m2.cast(fmt)
m4 = m2.cast(fmt, shape=shape)
ndim = len(shape)
strides = ex.strides
lst = ex.tolist()
self.verify(m3, obj=ex,
itemsize=size, fmt=fmt, readonly=True,
ndim=ndim, shape=shape, strides=strides,
lst=lst, cast=True)
self.verify(m4, obj=ex,
itemsize=size, fmt=fmt, readonly=True,
ndim=ndim, shape=shape, strides=strides,
lst=lst, cast=True)
if ctypes:
# format: "T{>l:x:>d:y:}"
class BEPoint(ctypes.BigEndianStructure):
_fields_ = [("x", ctypes.c_long), ("y", ctypes.c_double)]
point = BEPoint(100, 200.1)
m1 = memoryview(point)
m2 = m1.cast('B')
self.assertEqual(m2.obj, point)
self.assertEqual(m2.itemsize, 1)
self.assertIs(m2.readonly, False)
self.assertEqual(m2.ndim, 1)
self.assertEqual(m2.shape, (m2.nbytes,))
self.assertEqual(m2.strides, (1,))
self.assertEqual(m2.suboffsets, ())
x = ctypes.c_double(1.2)
m1 = memoryview(x)
m2 = m1.cast('c')
self.assertEqual(m2.obj, x)
self.assertEqual(m2.itemsize, 1)
self.assertIs(m2.readonly, False)
self.assertEqual(m2.ndim, 1)
self.assertEqual(m2.shape, (m2.nbytes,))
self.assertEqual(m2.strides, (1,))
self.assertEqual(m2.suboffsets, ())
def test_memoryview_tolist(self):
# Most tolist() tests are in self.verify() etc.
a = array.array('h', list(range(-6, 6)))
m = memoryview(a)
self.assertEqual(m, a)
self.assertEqual(m.tolist(), a.tolist())
a = a[2::3]
m = m[2::3]
self.assertEqual(m, a)
self.assertEqual(m.tolist(), a.tolist())
ex = ndarray(list(range(2*3*5*7*11)), shape=[11,2,7,3,5], format='L')
m = memoryview(ex)
self.assertEqual(m.tolist(), ex.tolist())
ex = ndarray([(2, 5), (7, 11)], shape=[2], format='lh')
m = memoryview(ex)
self.assertRaises(NotImplementedError, m.tolist)
ex = ndarray([b'12345'], shape=[1], format="s")
m = memoryview(ex)
self.assertRaises(NotImplementedError, m.tolist)
ex = ndarray([b"a",b"b",b"c",b"d",b"e",b"f"], shape=[2,3], format='s')
m = memoryview(ex)
self.assertRaises(NotImplementedError, m.tolist)
def test_memoryview_repr(self):
m = memoryview(bytearray(9))
r = m.__repr__()
self.assertTrue(r.startswith("<memory"))
m.release()
r = m.__repr__()
self.assertTrue(r.startswith("<released"))
def test_memoryview_sequence(self):
for fmt in ('d', 'f'):
inf = float(3e400)
ex = array.array(fmt, [1.0, inf, 3.0])
m = memoryview(ex)
self.assertIn(1.0, m)
self.assertIn(5e700, m)
self.assertIn(3.0, m)
ex = ndarray(9.0, [], format='f')
m = memoryview(ex)
self.assertRaises(TypeError, eval, "9.0 in m", locals())
@contextlib.contextmanager
def assert_out_of_bounds_error(self, dim):
with self.assertRaises(IndexError) as cm:
yield
self.assertEqual(str(cm.exception),
"index out of bounds on dimension %d" % (dim,))
def test_memoryview_index(self):
# ndim = 0
ex = ndarray(12.5, shape=[], format='d')
m = memoryview(ex)
self.assertEqual(m[()], 12.5)
self.assertEqual(m[...], m)
self.assertEqual(m[...], ex)
self.assertRaises(TypeError, m.__getitem__, 0)
ex = ndarray((1,2,3), shape=[], format='iii')
m = memoryview(ex)
self.assertRaises(NotImplementedError, m.__getitem__, ())
# range
ex = ndarray(list(range(7)), shape=[7], flags=ND_WRITABLE)
m = memoryview(ex)
self.assertRaises(IndexError, m.__getitem__, 2**64)
self.assertRaises(TypeError, m.__getitem__, 2.0)
self.assertRaises(TypeError, m.__getitem__, 0.0)
# out of bounds
self.assertRaises(IndexError, m.__getitem__, -8)
self.assertRaises(IndexError, m.__getitem__, 8)
# multi-dimensional
ex = ndarray(list(range(12)), shape=[3,4], flags=ND_WRITABLE)
m = memoryview(ex)
self.assertEqual(m[0, 0], 0)
self.assertEqual(m[2, 0], 8)
self.assertEqual(m[2, 3], 11)
self.assertEqual(m[-1, -1], 11)
self.assertEqual(m[-3, -4], 0)
# out of bounds
for index in (3, -4):
with self.assert_out_of_bounds_error(dim=1):
m[index, 0]
for index in (4, -5):
with self.assert_out_of_bounds_error(dim=2):
m[0, index]
self.assertRaises(IndexError, m.__getitem__, (2**64, 0))
self.assertRaises(IndexError, m.__getitem__, (0, 2**64))
self.assertRaises(TypeError, m.__getitem__, (0, 0, 0))
self.assertRaises(TypeError, m.__getitem__, (0.0, 0.0))
# Not implemented: multidimensional sub-views
self.assertRaises(NotImplementedError, m.__getitem__, ())
self.assertRaises(NotImplementedError, m.__getitem__, 0)
def test_memoryview_assign(self):
# ndim = 0
ex = ndarray(12.5, shape=[], format='f', flags=ND_WRITABLE)
m = memoryview(ex)
m[()] = 22.5
self.assertEqual(m[()], 22.5)
m[...] = 23.5
self.assertEqual(m[()], 23.5)
self.assertRaises(TypeError, m.__setitem__, 0, 24.7)
# read-only
ex = ndarray(list(range(7)), shape=[7])
m = memoryview(ex)
self.assertRaises(TypeError, m.__setitem__, 2, 10)
# range
ex = ndarray(list(range(7)), shape=[7], flags=ND_WRITABLE)
m = memoryview(ex)
self.assertRaises(IndexError, m.__setitem__, 2**64, 9)
self.assertRaises(TypeError, m.__setitem__, 2.0, 10)
self.assertRaises(TypeError, m.__setitem__, 0.0, 11)
# out of bounds
self.assertRaises(IndexError, m.__setitem__, -8, 20)
self.assertRaises(IndexError, m.__setitem__, 8, 25)
# pack_single() success:
for fmt in fmtdict['@']:
if fmt == 'c' or fmt == '?':
continue
ex = ndarray([1,2,3], shape=[3], format=fmt, flags=ND_WRITABLE)
m = memoryview(ex)
i = randrange(-3, 3)
m[i] = 8
self.assertEqual(m[i], 8)
self.assertEqual(m[i], ex[i])
ex = ndarray([b'1', b'2', b'3'], shape=[3], format='c',
flags=ND_WRITABLE)
m = memoryview(ex)
m[2] = b'9'
self.assertEqual(m[2], b'9')
ex = ndarray([True, False, True], shape=[3], format='?',
flags=ND_WRITABLE)
m = memoryview(ex)
m[1] = True
self.assertIs(m[1], True)
# pack_single() exceptions:
nd = ndarray([b'x'], shape=[1], format='c', flags=ND_WRITABLE)
m = memoryview(nd)
self.assertRaises(TypeError, m.__setitem__, 0, 100)
ex = ndarray(list(range(120)), shape=[1,2,3,4,5], flags=ND_WRITABLE)
m1 = memoryview(ex)
for fmt, _range in fmtdict['@'].items():
if (fmt == '?'): # PyObject_IsTrue() accepts anything
continue
if fmt == 'c': # special case tested above
continue
m2 = m1.cast(fmt)
lo, hi = _range
if fmt == 'd' or fmt == 'f':
lo, hi = -2**1024, 2**1024
if fmt != 'P': # PyLong_AsVoidPtr() accepts negative numbers
self.assertRaises(ValueError, m2.__setitem__, 0, lo-1)
self.assertRaises(TypeError, m2.__setitem__, 0, "xyz")
self.assertRaises(ValueError, m2.__setitem__, 0, hi)
# invalid item
m2 = m1.cast('c')
self.assertRaises(ValueError, m2.__setitem__, 0, b'\xff\xff')
# format not implemented
ex = ndarray(list(range(1)), shape=[1], format="xL", flags=ND_WRITABLE)
m = memoryview(ex)
self.assertRaises(NotImplementedError, m.__setitem__, 0, 1)
ex = ndarray([b'12345'], shape=[1], format="s", flags=ND_WRITABLE)
m = memoryview(ex)
self.assertRaises(NotImplementedError, m.__setitem__, 0, 1)
# multi-dimensional
ex = ndarray(list(range(12)), shape=[3,4], flags=ND_WRITABLE)
m = memoryview(ex)
m[0,1] = 42
self.assertEqual(ex[0][1], 42)
m[-1,-1] = 43
self.assertEqual(ex[2][3], 43)
# errors
for index in (3, -4):
with self.assert_out_of_bounds_error(dim=1):
m[index, 0] = 0
for index in (4, -5):
with self.assert_out_of_bounds_error(dim=2):
m[0, index] = 0
self.assertRaises(IndexError, m.__setitem__, (2**64, 0), 0)
self.assertRaises(IndexError, m.__setitem__, (0, 2**64), 0)
self.assertRaises(TypeError, m.__setitem__, (0, 0, 0), 0)
self.assertRaises(TypeError, m.__setitem__, (0.0, 0.0), 0)
# Not implemented: multidimensional sub-views
self.assertRaises(NotImplementedError, m.__setitem__, 0, [2, 3])
def test_memoryview_slice(self):
ex = ndarray(list(range(12)), shape=[12], flags=ND_WRITABLE)
m = memoryview(ex)
# zero step
self.assertRaises(ValueError, m.__getitem__, slice(0,2,0))
self.assertRaises(ValueError, m.__setitem__, slice(0,2,0),
bytearray([1,2]))
# 0-dim slicing (identity function)
self.assertRaises(NotImplementedError, m.__getitem__, ())
# multidimensional slices
ex = ndarray(list(range(12)), shape=[12], flags=ND_WRITABLE)
m = memoryview(ex)
self.assertRaises(NotImplementedError, m.__getitem__,
(slice(0,2,1), slice(0,2,1)))
self.assertRaises(NotImplementedError, m.__setitem__,
(slice(0,2,1), slice(0,2,1)), bytearray([1,2]))
# invalid slice tuple
self.assertRaises(TypeError, m.__getitem__, (slice(0,2,1), {}))
self.assertRaises(TypeError, m.__setitem__, (slice(0,2,1), {}),
bytearray([1,2]))
# rvalue is not an exporter
self.assertRaises(TypeError, m.__setitem__, slice(0,1,1), [1])
# non-contiguous slice assignment
for flags in (0, ND_PIL):
ex1 = ndarray(list(range(12)), shape=[12], strides=[-1], offset=11,
flags=ND_WRITABLE|flags)
ex2 = ndarray(list(range(24)), shape=[12], strides=[2], flags=flags)
m1 = memoryview(ex1)
m2 = memoryview(ex2)
ex1[2:5] = ex1[2:5]
m1[2:5] = m2[2:5]
self.assertEqual(m1, ex1)
self.assertEqual(m2, ex2)
ex1[1:3][::-1] = ex2[0:2][::1]
m1[1:3][::-1] = m2[0:2][::1]
self.assertEqual(m1, ex1)
self.assertEqual(m2, ex2)
ex1[4:1:-2][::-1] = ex1[1:4:2][::1]
m1[4:1:-2][::-1] = m1[1:4:2][::1]
self.assertEqual(m1, ex1)
self.assertEqual(m2, ex2)
def test_memoryview_array(self):
def cmptest(testcase, a, b, m, singleitem):
for i, _ in enumerate(a):
ai = a[i]
mi = m[i]
testcase.assertEqual(ai, mi)
a[i] = singleitem
if singleitem != ai:
testcase.assertNotEqual(a, m)
testcase.assertNotEqual(a, b)
else:
testcase.assertEqual(a, m)
testcase.assertEqual(a, b)
m[i] = singleitem
testcase.assertEqual(a, m)
testcase.assertEqual(b, m)
a[i] = ai
m[i] = mi
for n in range(1, 5):
for fmt, items, singleitem in iter_format(n, 'array'):
for lslice in genslices(n):
for rslice in genslices(n):
a = array.array(fmt, items)
b = array.array(fmt, items)
m = memoryview(b)
self.assertEqual(m, a)
self.assertEqual(m.tolist(), a.tolist())
self.assertEqual(m.tobytes(), a.tobytes())
self.assertEqual(len(m), len(a))
cmptest(self, a, b, m, singleitem)
array_err = None
have_resize = None
try:
al = a[lslice]
ar = a[rslice]
a[lslice] = a[rslice]
have_resize = len(al) != len(ar)
except Exception as e:
array_err = e.__class__
m_err = None
try:
m[lslice] = m[rslice]
except Exception as e:
m_err = e.__class__
if have_resize: # memoryview cannot change shape
self.assertIs(m_err, ValueError)
elif m_err or array_err:
self.assertIs(m_err, array_err)
else:
self.assertEqual(m, a)
self.assertEqual(m.tolist(), a.tolist())
self.assertEqual(m.tobytes(), a.tobytes())
cmptest(self, a, b, m, singleitem)
def test_memoryview_compare_special_cases(self):
a = array.array('L', [1, 2, 3])
b = array.array('L', [1, 2, 7])
# Ordering comparisons raise:
v = memoryview(a)
w = memoryview(b)
for attr in ('__lt__', '__le__', '__gt__', '__ge__'):
self.assertIs(getattr(v, attr)(w), NotImplemented)
self.assertIs(getattr(a, attr)(v), NotImplemented)
# Released views compare equal to themselves:
v = memoryview(a)
v.release()
self.assertEqual(v, v)
self.assertNotEqual(v, a)
self.assertNotEqual(a, v)
v = memoryview(a)
w = memoryview(a)
w.release()
self.assertNotEqual(v, w)
self.assertNotEqual(w, v)
# Operand does not implement the buffer protocol:
v = memoryview(a)
self.assertNotEqual(v, [1, 2, 3])
# NaNs
nd = ndarray([(0, 0)], shape=[1], format='l x d x', flags=ND_WRITABLE)
nd[0] = (-1, float('nan'))
self.assertNotEqual(memoryview(nd), nd)
# Depends on issue #15625: the struct module does not understand 'u'.
a = array.array('u', 'xyz')
v = memoryview(a)
self.assertNotEqual(a, v)
self.assertNotEqual(v, a)
# Some ctypes format strings are unknown to the struct module.
if ctypes:
# format: "T{>l:x:>l:y:}"
class BEPoint(ctypes.BigEndianStructure):
_fields_ = [("x", ctypes.c_long), ("y", ctypes.c_long)]
point = BEPoint(100, 200)
a = memoryview(point)
b = memoryview(point)
self.assertNotEqual(a, b)
self.assertNotEqual(a, point)
self.assertNotEqual(point, a)
self.assertRaises(NotImplementedError, a.tolist)
def test_memoryview_compare_ndim_zero(self):
nd1 = ndarray(1729, shape=[], format='@L')
nd2 = ndarray(1729, shape=[], format='L', flags=ND_WRITABLE)
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, w)
self.assertEqual(w, v)
self.assertEqual(v, nd2)
self.assertEqual(nd2, v)
self.assertEqual(w, nd1)
self.assertEqual(nd1, w)
self.assertFalse(v.__ne__(w))
self.assertFalse(w.__ne__(v))
w[()] = 1728
self.assertNotEqual(v, w)
self.assertNotEqual(w, v)
self.assertNotEqual(v, nd2)
self.assertNotEqual(nd2, v)
self.assertNotEqual(w, nd1)
self.assertNotEqual(nd1, w)
self.assertFalse(v.__eq__(w))
self.assertFalse(w.__eq__(v))
nd = ndarray(list(range(12)), shape=[12], flags=ND_WRITABLE|ND_PIL)
ex = ndarray(list(range(12)), shape=[12], flags=ND_WRITABLE|ND_PIL)
m = memoryview(ex)
self.assertEqual(m, nd)
m[9] = 100
self.assertNotEqual(m, nd)
# struct module: equal
nd1 = ndarray((1729, 1.2, b'12345'), shape=[], format='Lf5s')
nd2 = ndarray((1729, 1.2, b'12345'), shape=[], format='hf5s',
flags=ND_WRITABLE)
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, w)
self.assertEqual(w, v)
self.assertEqual(v, nd2)
self.assertEqual(nd2, v)
self.assertEqual(w, nd1)
self.assertEqual(nd1, w)
# struct module: not equal
nd1 = ndarray((1729, 1.2, b'12345'), shape=[], format='Lf5s')
nd2 = ndarray((-1729, 1.2, b'12345'), shape=[], format='hf5s',
flags=ND_WRITABLE)
v = memoryview(nd1)
w = memoryview(nd2)
self.assertNotEqual(v, w)
self.assertNotEqual(w, v)
self.assertNotEqual(v, nd2)
self.assertNotEqual(nd2, v)
self.assertNotEqual(w, nd1)
self.assertNotEqual(nd1, w)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
def test_memoryview_compare_ndim_one(self):
# contiguous
nd1 = ndarray([-529, 576, -625, 676, -729], shape=[5], format='@h')
nd2 = ndarray([-529, 576, -625, 676, 729], shape=[5], format='@h')
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertNotEqual(v, nd2)
self.assertNotEqual(w, nd1)
self.assertNotEqual(v, w)
# contiguous, struct module
nd1 = ndarray([-529, 576, -625, 676, -729], shape=[5], format='<i')
nd2 = ndarray([-529, 576, -625, 676, 729], shape=[5], format='>h')
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertNotEqual(v, nd2)
self.assertNotEqual(w, nd1)
self.assertNotEqual(v, w)
# non-contiguous
nd1 = ndarray([-529, -625, -729], shape=[3], format='@h')
nd2 = ndarray([-529, 576, -625, 676, -729], shape=[5], format='@h')
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd2[::2])
self.assertEqual(w[::2], nd1)
self.assertEqual(v, w[::2])
self.assertEqual(v[::-1], w[::-2])
# non-contiguous, struct module
nd1 = ndarray([-529, -625, -729], shape=[3], format='!h')
nd2 = ndarray([-529, 576, -625, 676, -729], shape=[5], format='<l')
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd2[::2])
self.assertEqual(w[::2], nd1)
self.assertEqual(v, w[::2])
self.assertEqual(v[::-1], w[::-2])
# non-contiguous, suboffsets
nd1 = ndarray([-529, -625, -729], shape=[3], format='@h')
nd2 = ndarray([-529, 576, -625, 676, -729], shape=[5], format='@h',
flags=ND_PIL)
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd2[::2])
self.assertEqual(w[::2], nd1)
self.assertEqual(v, w[::2])
self.assertEqual(v[::-1], w[::-2])
# non-contiguous, suboffsets, struct module
nd1 = ndarray([-529, -625, -729], shape=[3], format='h 0c')
nd2 = ndarray([-529, 576, -625, 676, -729], shape=[5], format='> h',
flags=ND_PIL)
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd2[::2])
self.assertEqual(w[::2], nd1)
self.assertEqual(v, w[::2])
self.assertEqual(v[::-1], w[::-2])
def test_memoryview_compare_zero_shape(self):
# zeros in shape
nd1 = ndarray([900, 961], shape=[0], format='@h')
nd2 = ndarray([-900, -961], shape=[0], format='@h')
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertEqual(v, nd2)
self.assertEqual(w, nd1)
self.assertEqual(v, w)
# zeros in shape, struct module
nd1 = ndarray([900, 961], shape=[0], format='= h0c')
nd2 = ndarray([-900, -961], shape=[0], format='@ i')
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertEqual(v, nd2)
self.assertEqual(w, nd1)
self.assertEqual(v, w)
def test_memoryview_compare_zero_strides(self):
# zero strides
nd1 = ndarray([900, 900, 900, 900], shape=[4], format='@L')
nd2 = ndarray([900], shape=[4], strides=[0], format='L')
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertEqual(v, nd2)
self.assertEqual(w, nd1)
self.assertEqual(v, w)
# zero strides, struct module
nd1 = ndarray([(900, 900)]*4, shape=[4], format='@ Li')
nd2 = ndarray([(900, 900)], shape=[4], strides=[0], format='!L h')
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertEqual(v, nd2)
self.assertEqual(w, nd1)
self.assertEqual(v, w)
def test_memoryview_compare_random_formats(self):
# random single character native formats
n = 10
for char in fmtdict['@m']:
fmt, items, singleitem = randitems(n, 'memoryview', '@', char)
for flags in (0, ND_PIL):
nd = ndarray(items, shape=[n], format=fmt, flags=flags)
m = memoryview(nd)
self.assertEqual(m, nd)
nd = nd[::-3]
m = memoryview(nd)
self.assertEqual(m, nd)
# random formats
n = 10
for _ in range(100):
fmt, items, singleitem = randitems(n)
for flags in (0, ND_PIL):
nd = ndarray(items, shape=[n], format=fmt, flags=flags)
m = memoryview(nd)
self.assertEqual(m, nd)
nd = nd[::-3]
m = memoryview(nd)
self.assertEqual(m, nd)
def test_memoryview_compare_multidim_c(self):
# C-contiguous, different values
nd1 = ndarray(list(range(-15, 15)), shape=[3, 2, 5], format='@h')
nd2 = ndarray(list(range(0, 30)), shape=[3, 2, 5], format='@h')
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertNotEqual(v, nd2)
self.assertNotEqual(w, nd1)
self.assertNotEqual(v, w)
# C-contiguous, different values, struct module
nd1 = ndarray([(0, 1, 2)]*30, shape=[3, 2, 5], format='=f q xxL')
nd2 = ndarray([(-1.2, 1, 2)]*30, shape=[3, 2, 5], format='< f 2Q')
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertNotEqual(v, nd2)
self.assertNotEqual(w, nd1)
self.assertNotEqual(v, w)
# C-contiguous, different shape
nd1 = ndarray(list(range(30)), shape=[2, 3, 5], format='L')
nd2 = ndarray(list(range(30)), shape=[3, 2, 5], format='L')
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertNotEqual(v, nd2)
self.assertNotEqual(w, nd1)
self.assertNotEqual(v, w)
# C-contiguous, different shape, struct module
nd1 = ndarray([(0, 1, 2)]*21, shape=[3, 7], format='! b B xL')
nd2 = ndarray([(0, 1, 2)]*21, shape=[7, 3], format='= Qx l xxL')
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertNotEqual(v, nd2)
self.assertNotEqual(w, nd1)
self.assertNotEqual(v, w)
# C-contiguous, different format, struct module
nd1 = ndarray(list(range(30)), shape=[2, 3, 5], format='L')
nd2 = ndarray(list(range(30)), shape=[2, 3, 5], format='l')
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertEqual(v, nd2)
self.assertEqual(w, nd1)
self.assertEqual(v, w)
def test_memoryview_compare_multidim_fortran(self):
# Fortran-contiguous, different values
nd1 = ndarray(list(range(-15, 15)), shape=[5, 2, 3], format='@h',
flags=ND_FORTRAN)
nd2 = ndarray(list(range(0, 30)), shape=[5, 2, 3], format='@h',
flags=ND_FORTRAN)
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertNotEqual(v, nd2)
self.assertNotEqual(w, nd1)
self.assertNotEqual(v, w)
# Fortran-contiguous, different values, struct module
nd1 = ndarray([(2**64-1, -1)]*6, shape=[2, 3], format='=Qq',
flags=ND_FORTRAN)
nd2 = ndarray([(-1, 2**64-1)]*6, shape=[2, 3], format='=qQ',
flags=ND_FORTRAN)
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertNotEqual(v, nd2)
self.assertNotEqual(w, nd1)
self.assertNotEqual(v, w)
# Fortran-contiguous, different shape
nd1 = ndarray(list(range(-15, 15)), shape=[2, 3, 5], format='l',
flags=ND_FORTRAN)
nd2 = ndarray(list(range(-15, 15)), shape=[3, 2, 5], format='l',
flags=ND_FORTRAN)
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertNotEqual(v, nd2)
self.assertNotEqual(w, nd1)
self.assertNotEqual(v, w)
# Fortran-contiguous, different shape, struct module
nd1 = ndarray(list(range(-15, 15)), shape=[2, 3, 5], format='0ll',
flags=ND_FORTRAN)
nd2 = ndarray(list(range(-15, 15)), shape=[3, 2, 5], format='l',
flags=ND_FORTRAN)
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertNotEqual(v, nd2)
self.assertNotEqual(w, nd1)
self.assertNotEqual(v, w)
# Fortran-contiguous, different format, struct module
nd1 = ndarray(list(range(30)), shape=[5, 2, 3], format='@h',
flags=ND_FORTRAN)
nd2 = ndarray(list(range(30)), shape=[5, 2, 3], format='@b',
flags=ND_FORTRAN)
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertEqual(v, nd2)
self.assertEqual(w, nd1)
self.assertEqual(v, w)
def test_memoryview_compare_multidim_mixed(self):
# mixed C/Fortran contiguous
lst1 = list(range(-15, 15))
lst2 = transpose(lst1, [3, 2, 5])
nd1 = ndarray(lst1, shape=[3, 2, 5], format='@l')
nd2 = ndarray(lst2, shape=[3, 2, 5], format='l', flags=ND_FORTRAN)
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertEqual(v, w)
# mixed C/Fortran contiguous, struct module
lst1 = [(-3.3, -22, b'x')]*30
lst1[5] = (-2.2, -22, b'x')
lst2 = transpose(lst1, [3, 2, 5])
nd1 = ndarray(lst1, shape=[3, 2, 5], format='d b c')
nd2 = ndarray(lst2, shape=[3, 2, 5], format='d h c', flags=ND_FORTRAN)
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertEqual(v, w)
# different values, non-contiguous
ex1 = ndarray(list(range(40)), shape=[5, 8], format='@I')
nd1 = ex1[3:1:-1, ::-2]
ex2 = ndarray(list(range(40)), shape=[5, 8], format='I')
nd2 = ex2[1:3:1, ::-2]
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertNotEqual(v, nd2)
self.assertNotEqual(w, nd1)
self.assertNotEqual(v, w)
# same values, non-contiguous, struct module
ex1 = ndarray([(2**31-1, -2**31)]*22, shape=[11, 2], format='=ii')
nd1 = ex1[3:1:-1, ::-2]
ex2 = ndarray([(2**31-1, -2**31)]*22, shape=[11, 2], format='>ii')
nd2 = ex2[1:3:1, ::-2]
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertEqual(v, nd2)
self.assertEqual(w, nd1)
self.assertEqual(v, w)
# different shape
ex1 = ndarray(list(range(30)), shape=[2, 3, 5], format='b')
nd1 = ex1[1:3:, ::-2]
nd2 = ndarray(list(range(30)), shape=[3, 2, 5], format='b')
nd2 = ex2[1:3:, ::-2]
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertNotEqual(v, nd2)
self.assertNotEqual(w, nd1)
self.assertNotEqual(v, w)
# different shape, struct module
ex1 = ndarray(list(range(30)), shape=[2, 3, 5], format='B')
nd1 = ex1[1:3:, ::-2]
nd2 = ndarray(list(range(30)), shape=[3, 2, 5], format='b')
nd2 = ex2[1:3:, ::-2]
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertNotEqual(v, nd2)
self.assertNotEqual(w, nd1)
self.assertNotEqual(v, w)
# different format, struct module
ex1 = ndarray([(2, b'123')]*30, shape=[5, 3, 2], format='b3s')
nd1 = ex1[1:3:, ::-2]
nd2 = ndarray([(2, b'123')]*30, shape=[5, 3, 2], format='i3s')
nd2 = ex2[1:3:, ::-2]
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertNotEqual(v, nd2)
self.assertNotEqual(w, nd1)
self.assertNotEqual(v, w)
def test_memoryview_compare_multidim_zero_shape(self):
# zeros in shape
nd1 = ndarray(list(range(30)), shape=[0, 3, 2], format='i')
nd2 = ndarray(list(range(30)), shape=[5, 0, 2], format='@i')
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertNotEqual(v, nd2)
self.assertNotEqual(w, nd1)
self.assertNotEqual(v, w)
# zeros in shape, struct module
nd1 = ndarray(list(range(30)), shape=[0, 3, 2], format='i')
nd2 = ndarray(list(range(30)), shape=[5, 0, 2], format='@i')
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertNotEqual(v, nd2)
self.assertNotEqual(w, nd1)
self.assertNotEqual(v, w)
def test_memoryview_compare_multidim_zero_strides(self):
# zero strides
nd1 = ndarray([900]*80, shape=[4, 5, 4], format='@L')
nd2 = ndarray([900], shape=[4, 5, 4], strides=[0, 0, 0], format='L')
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertEqual(v, nd2)
self.assertEqual(w, nd1)
self.assertEqual(v, w)
self.assertEqual(v.tolist(), w.tolist())
# zero strides, struct module
nd1 = ndarray([(1, 2)]*10, shape=[2, 5], format='=lQ')
nd2 = ndarray([(1, 2)], shape=[2, 5], strides=[0, 0], format='<lQ')
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertEqual(v, nd2)
self.assertEqual(w, nd1)
self.assertEqual(v, w)
def test_memoryview_compare_multidim_suboffsets(self):
# suboffsets
ex1 = ndarray(list(range(40)), shape=[5, 8], format='@I')
nd1 = ex1[3:1:-1, ::-2]
ex2 = ndarray(list(range(40)), shape=[5, 8], format='I', flags=ND_PIL)
nd2 = ex2[1:3:1, ::-2]
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertNotEqual(v, nd2)
self.assertNotEqual(w, nd1)
self.assertNotEqual(v, w)
# suboffsets, struct module
ex1 = ndarray([(2**64-1, -1)]*40, shape=[5, 8], format='=Qq',
flags=ND_WRITABLE)
ex1[2][7] = (1, -2)
nd1 = ex1[3:1:-1, ::-2]
ex2 = ndarray([(2**64-1, -1)]*40, shape=[5, 8], format='>Qq',
flags=ND_PIL|ND_WRITABLE)
ex2[2][7] = (1, -2)
nd2 = ex2[1:3:1, ::-2]
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertEqual(v, nd2)
self.assertEqual(w, nd1)
self.assertEqual(v, w)
# suboffsets, different shape
ex1 = ndarray(list(range(30)), shape=[2, 3, 5], format='b',
flags=ND_PIL)
nd1 = ex1[1:3:, ::-2]
nd2 = ndarray(list(range(30)), shape=[3, 2, 5], format='b')
nd2 = ex2[1:3:, ::-2]
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertNotEqual(v, nd2)
self.assertNotEqual(w, nd1)
self.assertNotEqual(v, w)
# suboffsets, different shape, struct module
ex1 = ndarray([(2**8-1, -1)]*40, shape=[2, 3, 5], format='Bb',
flags=ND_PIL|ND_WRITABLE)
nd1 = ex1[1:2:, ::-2]
ex2 = ndarray([(2**8-1, -1)]*40, shape=[3, 2, 5], format='Bb')
nd2 = ex2[1:2:, ::-2]
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertNotEqual(v, nd2)
self.assertNotEqual(w, nd1)
self.assertNotEqual(v, w)
# suboffsets, different format
ex1 = ndarray(list(range(30)), shape=[5, 3, 2], format='i', flags=ND_PIL)
nd1 = ex1[1:3:, ::-2]
ex2 = ndarray(list(range(30)), shape=[5, 3, 2], format='@I', flags=ND_PIL)
nd2 = ex2[1:3:, ::-2]
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertEqual(v, nd2)
self.assertEqual(w, nd1)
self.assertEqual(v, w)
# suboffsets, different format, struct module
ex1 = ndarray([(b'hello', b'', 1)]*27, shape=[3, 3, 3], format='5s0sP',
flags=ND_PIL|ND_WRITABLE)
ex1[1][2][2] = (b'sushi', b'', 1)
nd1 = ex1[1:3:, ::-2]
ex2 = ndarray([(b'hello', b'', 1)]*27, shape=[3, 3, 3], format='5s0sP',
flags=ND_PIL|ND_WRITABLE)
ex1[1][2][2] = (b'sushi', b'', 1)
nd2 = ex2[1:3:, ::-2]
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertNotEqual(v, nd2)
self.assertNotEqual(w, nd1)
self.assertNotEqual(v, w)
# initialize mixed C/Fortran + suboffsets
lst1 = list(range(-15, 15))
lst2 = transpose(lst1, [3, 2, 5])
nd1 = ndarray(lst1, shape=[3, 2, 5], format='@l', flags=ND_PIL)
nd2 = ndarray(lst2, shape=[3, 2, 5], format='l', flags=ND_FORTRAN|ND_PIL)
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertEqual(v, w)
# initialize mixed C/Fortran + suboffsets, struct module
lst1 = [(b'sashimi', b'sliced', 20.05)]*30
lst1[11] = (b'ramen', b'spicy', 9.45)
lst2 = transpose(lst1, [3, 2, 5])
nd1 = ndarray(lst1, shape=[3, 2, 5], format='< 10p 9p d', flags=ND_PIL)
nd2 = ndarray(lst2, shape=[3, 2, 5], format='> 10p 9p d',
flags=ND_FORTRAN|ND_PIL)
v = memoryview(nd1)
w = memoryview(nd2)
self.assertEqual(v, nd1)
self.assertEqual(w, nd2)
self.assertEqual(v, w)
def test_memoryview_compare_not_equal(self):
# items not equal
for byteorder in ['=', '<', '>', '!']:
x = ndarray([2**63]*120, shape=[3,5,2,2,2], format=byteorder+'Q')
y = ndarray([2**63]*120, shape=[3,5,2,2,2], format=byteorder+'Q',
flags=ND_WRITABLE|ND_FORTRAN)
y[2][3][1][1][1] = 1
a = memoryview(x)
b = memoryview(y)
self.assertEqual(a, x)
self.assertEqual(b, y)
self.assertNotEqual(a, b)
self.assertNotEqual(a, y)
self.assertNotEqual(b, x)
x = ndarray([(2**63, 2**31, 2**15)]*120, shape=[3,5,2,2,2],
format=byteorder+'QLH')
y = ndarray([(2**63, 2**31, 2**15)]*120, shape=[3,5,2,2,2],
format=byteorder+'QLH', flags=ND_WRITABLE|ND_FORTRAN)
y[2][3][1][1][1] = (1, 1, 1)
a = memoryview(x)
b = memoryview(y)
self.assertEqual(a, x)
self.assertEqual(b, y)
self.assertNotEqual(a, b)
self.assertNotEqual(a, y)
self.assertNotEqual(b, x)
def test_memoryview_check_released(self):
a = array.array('d', [1.1, 2.2, 3.3])
m = memoryview(a)
m.release()
# PyMemoryView_FromObject()
self.assertRaises(ValueError, memoryview, m)
# memoryview.cast()
self.assertRaises(ValueError, m.cast, 'c')
# getbuffer()
self.assertRaises(ValueError, ndarray, m)
# memoryview.tolist()
self.assertRaises(ValueError, m.tolist)
# memoryview.tobytes()
self.assertRaises(ValueError, m.tobytes)
# sequence
self.assertRaises(ValueError, eval, "1.0 in m", locals())
# subscript
self.assertRaises(ValueError, m.__getitem__, 0)
# assignment
self.assertRaises(ValueError, m.__setitem__, 0, 1)
for attr in ('obj', 'nbytes', 'readonly', 'itemsize', 'format', 'ndim',
'shape', 'strides', 'suboffsets', 'c_contiguous',
'f_contiguous', 'contiguous'):
self.assertRaises(ValueError, m.__getattribute__, attr)
# richcompare
b = array.array('d', [1.1, 2.2, 3.3])
m1 = memoryview(a)
m2 = memoryview(b)
self.assertEqual(m1, m2)
m1.release()
self.assertNotEqual(m1, m2)
self.assertNotEqual(m1, a)
self.assertEqual(m1, m1)
def test_memoryview_tobytes(self):
# Many implicit tests are already in self.verify().
t = (-529, 576, -625, 676, -729)
nd = ndarray(t, shape=[5], format='@h')
m = memoryview(nd)
self.assertEqual(m, nd)
self.assertEqual(m.tobytes(), nd.tobytes())
nd = ndarray([t], shape=[1], format='>hQiLl')
m = memoryview(nd)
self.assertEqual(m, nd)
self.assertEqual(m.tobytes(), nd.tobytes())
nd = ndarray([t for _ in range(12)], shape=[2,2,3], format='=hQiLl')
m = memoryview(nd)
self.assertEqual(m, nd)
self.assertEqual(m.tobytes(), nd.tobytes())
nd = ndarray([t for _ in range(120)], shape=[5,2,2,3,2],
format='<hQiLl')
m = memoryview(nd)
self.assertEqual(m, nd)
self.assertEqual(m.tobytes(), nd.tobytes())
# Unknown formats are handled: tobytes() purely depends on itemsize.
if ctypes:
# format: "T{>l:x:>l:y:}"
class BEPoint(ctypes.BigEndianStructure):
_fields_ = [("x", ctypes.c_long), ("y", ctypes.c_long)]
point = BEPoint(100, 200)
a = memoryview(point)
self.assertEqual(a.tobytes(), bytes(point))
def test_memoryview_get_contiguous(self):
# Many implicit tests are already in self.verify().
# no buffer interface
self.assertRaises(TypeError, get_contiguous, {}, PyBUF_READ, 'F')
# writable request to read-only object
self.assertRaises(BufferError, get_contiguous, b'x', PyBUF_WRITE, 'C')
# writable request to non-contiguous object
nd = ndarray([1, 2, 3], shape=[2], strides=[2])
self.assertRaises(BufferError, get_contiguous, nd, PyBUF_WRITE, 'A')
# scalar, read-only request from read-only exporter
nd = ndarray(9, shape=(), format="L")
for order in ['C', 'F', 'A']:
m = get_contiguous(nd, PyBUF_READ, order)
self.assertEqual(m, nd)
self.assertEqual(m[()], 9)
# scalar, read-only request from writable exporter
nd = ndarray(9, shape=(), format="L", flags=ND_WRITABLE)
for order in ['C', 'F', 'A']:
m = get_contiguous(nd, PyBUF_READ, order)
self.assertEqual(m, nd)
self.assertEqual(m[()], 9)
# scalar, writable request
for order in ['C', 'F', 'A']:
nd[()] = 9
m = get_contiguous(nd, PyBUF_WRITE, order)
self.assertEqual(m, nd)
self.assertEqual(m[()], 9)
m[()] = 10
self.assertEqual(m[()], 10)
self.assertEqual(nd[()], 10)
# zeros in shape
nd = ndarray([1], shape=[0], format="L", flags=ND_WRITABLE)
for order in ['C', 'F', 'A']:
m = get_contiguous(nd, PyBUF_READ, order)
self.assertRaises(IndexError, m.__getitem__, 0)
self.assertEqual(m, nd)
self.assertEqual(m.tolist(), [])
nd = ndarray(list(range(8)), shape=[2, 0, 7], format="L",
flags=ND_WRITABLE)
for order in ['C', 'F', 'A']:
m = get_contiguous(nd, PyBUF_READ, order)
self.assertEqual(ndarray(m).tolist(), [[], []])
# one-dimensional
nd = ndarray([1], shape=[1], format="h", flags=ND_WRITABLE)
for order in ['C', 'F', 'A']:
m = get_contiguous(nd, PyBUF_WRITE, order)
self.assertEqual(m, nd)
self.assertEqual(m.tolist(), nd.tolist())
nd = ndarray([1, 2, 3], shape=[3], format="b", flags=ND_WRITABLE)
for order in ['C', 'F', 'A']:
m = get_contiguous(nd, PyBUF_WRITE, order)
self.assertEqual(m, nd)
self.assertEqual(m.tolist(), nd.tolist())
# one-dimensional, non-contiguous
nd = ndarray([1, 2, 3], shape=[2], strides=[2], flags=ND_WRITABLE)
for order in ['C', 'F', 'A']:
m = get_contiguous(nd, PyBUF_READ, order)
self.assertEqual(m, nd)
self.assertEqual(m.tolist(), nd.tolist())
self.assertRaises(TypeError, m.__setitem__, 1, 20)
self.assertEqual(m[1], 3)
self.assertEqual(nd[1], 3)
nd = nd[::-1]
for order in ['C', 'F', 'A']:
m = get_contiguous(nd, PyBUF_READ, order)
self.assertEqual(m, nd)
self.assertEqual(m.tolist(), nd.tolist())
self.assertRaises(TypeError, m.__setitem__, 1, 20)
self.assertEqual(m[1], 1)
self.assertEqual(nd[1], 1)
# multi-dimensional, contiguous input
nd = ndarray(list(range(12)), shape=[3, 4], flags=ND_WRITABLE)
for order in ['C', 'A']:
m = get_contiguous(nd, PyBUF_WRITE, order)
self.assertEqual(ndarray(m).tolist(), nd.tolist())
self.assertRaises(BufferError, get_contiguous, nd, PyBUF_WRITE, 'F')
m = get_contiguous(nd, PyBUF_READ, order)
self.assertEqual(ndarray(m).tolist(), nd.tolist())
nd = ndarray(list(range(12)), shape=[3, 4],
flags=ND_WRITABLE|ND_FORTRAN)
for order in ['F', 'A']:
m = get_contiguous(nd, PyBUF_WRITE, order)
self.assertEqual(ndarray(m).tolist(), nd.tolist())
self.assertRaises(BufferError, get_contiguous, nd, PyBUF_WRITE, 'C')
m = get_contiguous(nd, PyBUF_READ, order)
self.assertEqual(ndarray(m).tolist(), nd.tolist())
# multi-dimensional, non-contiguous input
nd = ndarray(list(range(12)), shape=[3, 4], flags=ND_WRITABLE|ND_PIL)
for order in ['C', 'F', 'A']:
self.assertRaises(BufferError, get_contiguous, nd, PyBUF_WRITE,
order)
m = get_contiguous(nd, PyBUF_READ, order)
self.assertEqual(ndarray(m).tolist(), nd.tolist())
# flags
nd = ndarray([1,2,3,4,5], shape=[3], strides=[2])
m = get_contiguous(nd, PyBUF_READ, 'C')
self.assertTrue(m.c_contiguous)
def test_memoryview_serializing(self):
# C-contiguous
size = struct.calcsize('i')
a = array.array('i', [1,2,3,4,5])
m = memoryview(a)
buf = io.BytesIO(m)
b = bytearray(5*size)
buf.readinto(b)
self.assertEqual(m.tobytes(), b)
# C-contiguous, multi-dimensional
size = struct.calcsize('L')
nd = ndarray(list(range(12)), shape=[2,3,2], format="L")
m = memoryview(nd)
buf = io.BytesIO(m)
b = bytearray(2*3*2*size)
buf.readinto(b)
self.assertEqual(m.tobytes(), b)
# Fortran contiguous, multi-dimensional
#size = struct.calcsize('L')
#nd = ndarray(list(range(12)), shape=[2,3,2], format="L",
# flags=ND_FORTRAN)
#m = memoryview(nd)
#buf = io.BytesIO(m)
#b = bytearray(2*3*2*size)
#buf.readinto(b)
#self.assertEqual(m.tobytes(), b)
def test_memoryview_hash(self):
# bytes exporter
b = bytes(list(range(12)))
m = memoryview(b)
self.assertEqual(hash(b), hash(m))
# C-contiguous
mc = m.cast('c', shape=[3,4])
self.assertEqual(hash(mc), hash(b))
# non-contiguous
mx = m[::-2]
b = bytes(list(range(12))[::-2])
self.assertEqual(hash(mx), hash(b))
# Fortran contiguous
nd = ndarray(list(range(30)), shape=[3,2,5], flags=ND_FORTRAN)
m = memoryview(nd)
self.assertEqual(hash(m), hash(nd))
# multi-dimensional slice
nd = ndarray(list(range(30)), shape=[3,2,5])
x = nd[::2, ::, ::-1]
m = memoryview(x)
self.assertEqual(hash(m), hash(x))
# multi-dimensional slice with suboffsets
nd = ndarray(list(range(30)), shape=[2,5,3], flags=ND_PIL)
x = nd[::2, ::, ::-1]
m = memoryview(x)
self.assertEqual(hash(m), hash(x))
# equality-hash invariant
x = ndarray(list(range(12)), shape=[12], format='B')
a = memoryview(x)
y = ndarray(list(range(12)), shape=[12], format='b')
b = memoryview(y)
self.assertEqual(a, b)
self.assertEqual(hash(a), hash(b))
# non-byte formats
nd = ndarray(list(range(12)), shape=[2,2,3], format='L')
m = memoryview(nd)
self.assertRaises(ValueError, m.__hash__)
nd = ndarray(list(range(-6, 6)), shape=[2,2,3], format='h')
m = memoryview(nd)
self.assertRaises(ValueError, m.__hash__)
nd = ndarray(list(range(12)), shape=[2,2,3], format='= L')
m = memoryview(nd)
self.assertRaises(ValueError, m.__hash__)
nd = ndarray(list(range(-6, 6)), shape=[2,2,3], format='< h')
m = memoryview(nd)
self.assertRaises(ValueError, m.__hash__)
def test_memoryview_release(self):
# Create re-exporter from getbuffer(memoryview), then release the view.
a = bytearray([1,2,3])
m = memoryview(a)
nd = ndarray(m) # re-exporter
self.assertRaises(BufferError, m.release)
del nd
m.release()
a = bytearray([1,2,3])
m = memoryview(a)
nd1 = ndarray(m, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
nd2 = ndarray(nd1, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
self.assertIs(nd2.obj, m)
self.assertRaises(BufferError, m.release)
del nd1, nd2
m.release()
# chained views
a = bytearray([1,2,3])
m1 = memoryview(a)
m2 = memoryview(m1)
nd = ndarray(m2) # re-exporter
m1.release()
self.assertRaises(BufferError, m2.release)
del nd
m2.release()
a = bytearray([1,2,3])
m1 = memoryview(a)
m2 = memoryview(m1)
nd1 = ndarray(m2, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
nd2 = ndarray(nd1, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
self.assertIs(nd2.obj, m2)
m1.release()
self.assertRaises(BufferError, m2.release)
del nd1, nd2
m2.release()
# Allow changing layout while buffers are exported.
nd = ndarray([1,2,3], shape=[3], flags=ND_VAREXPORT)
m1 = memoryview(nd)
nd.push([4,5,6,7,8], shape=[5]) # mutate nd
m2 = memoryview(nd)
x = memoryview(m1)
self.assertEqual(x.tolist(), m1.tolist())
y = memoryview(m2)
self.assertEqual(y.tolist(), m2.tolist())
self.assertEqual(y.tolist(), nd.tolist())
m2.release()
y.release()
nd.pop() # pop the current view
self.assertEqual(x.tolist(), nd.tolist())
del nd
m1.release()
x.release()
# If multiple memoryviews share the same managed buffer, implicit
# release() in the context manager's __exit__() method should still
# work.
def catch22(b):
with memoryview(b) as m2:
pass
x = bytearray(b'123')
with memoryview(x) as m1:
catch22(m1)
self.assertEqual(m1[0], ord(b'1'))
x = ndarray(list(range(12)), shape=[2,2,3], format='l')
y = ndarray(x, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
z = ndarray(y, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
self.assertIs(z.obj, x)
with memoryview(z) as m:
catch22(m)
self.assertEqual(m[0:1].tolist(), [[[0, 1, 2], [3, 4, 5]]])
# Test garbage collection.
for flags in (0, ND_REDIRECT):
x = bytearray(b'123')
with memoryview(x) as m1:
del x
y = ndarray(m1, getbuf=PyBUF_FULL_RO, flags=flags)
with memoryview(y) as m2:
del y
z = ndarray(m2, getbuf=PyBUF_FULL_RO, flags=flags)
with memoryview(z) as m3:
del z
catch22(m3)
catch22(m2)
catch22(m1)
self.assertEqual(m1[0], ord(b'1'))
self.assertEqual(m2[1], ord(b'2'))
self.assertEqual(m3[2], ord(b'3'))
del m3
del m2
del m1
x = bytearray(b'123')
with memoryview(x) as m1:
del x
y = ndarray(m1, getbuf=PyBUF_FULL_RO, flags=flags)
with memoryview(y) as m2:
del y
z = ndarray(m2, getbuf=PyBUF_FULL_RO, flags=flags)
with memoryview(z) as m3:
del z
catch22(m1)
catch22(m2)
catch22(m3)
self.assertEqual(m1[0], ord(b'1'))
self.assertEqual(m2[1], ord(b'2'))
self.assertEqual(m3[2], ord(b'3'))
del m1, m2, m3
# memoryview.release() fails if the view has exported buffers.
x = bytearray(b'123')
with self.assertRaises(BufferError):
with memoryview(x) as m:
ex = ndarray(m)
m[0] == ord(b'1')
def test_memoryview_redirect(self):
nd = ndarray([1.0 * x for x in range(12)], shape=[12], format='d')
a = array.array('d', [1.0 * x for x in range(12)])
for x in (nd, a):
y = ndarray(x, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
z = ndarray(y, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
m = memoryview(z)
self.assertIs(y.obj, x)
self.assertIs(z.obj, x)
self.assertIs(m.obj, x)
self.assertEqual(m, x)
self.assertEqual(m, y)
self.assertEqual(m, z)
self.assertEqual(m[1:3], x[1:3])
self.assertEqual(m[1:3], y[1:3])
self.assertEqual(m[1:3], z[1:3])
del y, z
self.assertEqual(m[1:3], x[1:3])
def test_memoryview_from_static_exporter(self):
fmt = 'B'
lst = [0,1,2,3,4,5,6,7,8,9,10,11]
# exceptions
self.assertRaises(TypeError, staticarray, 1, 2, 3)
# view.obj==x
x = staticarray()
y = memoryview(x)
self.verify(y, obj=x,
itemsize=1, fmt=fmt, readonly=True,
ndim=1, shape=[12], strides=[1],
lst=lst)
for i in range(12):
self.assertEqual(y[i], i)
del x
del y
x = staticarray()
y = memoryview(x)
del y
del x
x = staticarray()
y = ndarray(x, getbuf=PyBUF_FULL_RO)
z = ndarray(y, getbuf=PyBUF_FULL_RO)
m = memoryview(z)
self.assertIs(y.obj, x)
self.assertIs(m.obj, z)
self.verify(m, obj=z,
itemsize=1, fmt=fmt, readonly=True,
ndim=1, shape=[12], strides=[1],
lst=lst)
del x, y, z, m
x = staticarray()
y = ndarray(x, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
z = ndarray(y, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
m = memoryview(z)
self.assertIs(y.obj, x)
self.assertIs(z.obj, x)
self.assertIs(m.obj, x)
self.verify(m, obj=x,
itemsize=1, fmt=fmt, readonly=True,
ndim=1, shape=[12], strides=[1],
lst=lst)
del x, y, z, m
# view.obj==NULL
x = staticarray(legacy_mode=True)
y = memoryview(x)
self.verify(y, obj=None,
itemsize=1, fmt=fmt, readonly=True,
ndim=1, shape=[12], strides=[1],
lst=lst)
for i in range(12):
self.assertEqual(y[i], i)
del x
del y
x = staticarray(legacy_mode=True)
y = memoryview(x)
del y
del x
x = staticarray(legacy_mode=True)
y = ndarray(x, getbuf=PyBUF_FULL_RO)
z = ndarray(y, getbuf=PyBUF_FULL_RO)
m = memoryview(z)
self.assertIs(y.obj, None)
self.assertIs(m.obj, z)
self.verify(m, obj=z,
itemsize=1, fmt=fmt, readonly=True,
ndim=1, shape=[12], strides=[1],
lst=lst)
del x, y, z, m
x = staticarray(legacy_mode=True)
y = ndarray(x, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
z = ndarray(y, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
m = memoryview(z)
# Clearly setting view.obj==NULL is inferior, since it
# messes up the redirection chain:
self.assertIs(y.obj, None)
self.assertIs(z.obj, y)
self.assertIs(m.obj, y)
self.verify(m, obj=y,
itemsize=1, fmt=fmt, readonly=True,
ndim=1, shape=[12], strides=[1],
lst=lst)
del x, y, z, m
def test_memoryview_getbuffer_undefined(self):
# getbufferproc does not adhere to the new documentation
nd = ndarray([1,2,3], [3], flags=ND_GETBUF_FAIL|ND_GETBUF_UNDEFINED)
self.assertRaises(BufferError, memoryview, nd)
def test_issue_7385(self):
x = ndarray([1,2,3], shape=[3], flags=ND_GETBUF_FAIL)
self.assertRaises(BufferError, memoryview, x)
@support.cpython_only
def test_pybuffer_size_from_format(self):
# basic tests
for format in ('', 'ii', '3s'):
self.assertEqual(_testcapi.PyBuffer_SizeFromFormat(format),
struct.calcsize(format))
if __name__ == "__main__":
unittest.main()
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