Stefan Krah | 9a2d99e | 2012-02-25 12:24:21 +0100 | [diff] [blame] | 1 | # |
| 2 | # The ndarray object from _testbuffer.c is a complete implementation of |
| 3 | # a PEP-3118 buffer provider. It is independent from NumPy's ndarray |
| 4 | # and the tests don't require NumPy. |
| 5 | # |
| 6 | # If NumPy is present, some tests check both ndarray implementations |
| 7 | # against each other. |
| 8 | # |
| 9 | # Most ndarray tests also check that memoryview(ndarray) behaves in |
| 10 | # the same way as the original. Thus, a substantial part of the |
| 11 | # memoryview tests is now in this module. |
| 12 | # |
| 13 | |
| 14 | import unittest |
| 15 | from test import support |
| 16 | from itertools import permutations, product |
| 17 | from random import randrange, sample, choice |
| 18 | from sysconfig import get_config_var |
| 19 | from platform import architecture |
| 20 | import warnings |
| 21 | import sys, array, io |
| 22 | from decimal import Decimal |
| 23 | from fractions import Fraction |
| 24 | |
| 25 | try: |
| 26 | from _testbuffer import * |
| 27 | except ImportError: |
| 28 | ndarray = None |
| 29 | |
| 30 | try: |
| 31 | import struct |
| 32 | except ImportError: |
| 33 | struct = None |
| 34 | |
| 35 | try: |
| 36 | with warnings.catch_warnings(): |
| 37 | from numpy import ndarray as numpy_array |
| 38 | except ImportError: |
| 39 | numpy_array = None |
| 40 | |
| 41 | |
| 42 | SHORT_TEST = True |
| 43 | |
| 44 | |
| 45 | # ====================================================================== |
| 46 | # Random lists by format specifier |
| 47 | # ====================================================================== |
| 48 | |
| 49 | # Native format chars and their ranges. |
| 50 | NATIVE = { |
| 51 | '?':0, 'c':0, 'b':0, 'B':0, |
| 52 | 'h':0, 'H':0, 'i':0, 'I':0, |
| 53 | 'l':0, 'L':0, 'n':0, 'N':0, |
| 54 | 'f':0, 'd':0, 'P':0 |
| 55 | } |
| 56 | |
| 57 | if struct: |
| 58 | try: |
| 59 | # Add "qQ" if present in native mode. |
| 60 | struct.pack('Q', 2**64-1) |
| 61 | NATIVE['q'] = 0 |
| 62 | NATIVE['Q'] = 0 |
| 63 | except struct.error: |
| 64 | pass |
| 65 | |
| 66 | # Standard format chars and their ranges. |
| 67 | STANDARD = { |
| 68 | '?':(0, 2), 'c':(0, 1<<8), |
| 69 | 'b':(-(1<<7), 1<<7), 'B':(0, 1<<8), |
| 70 | 'h':(-(1<<15), 1<<15), 'H':(0, 1<<16), |
| 71 | 'i':(-(1<<31), 1<<31), 'I':(0, 1<<32), |
| 72 | 'l':(-(1<<31), 1<<31), 'L':(0, 1<<32), |
| 73 | 'q':(-(1<<63), 1<<63), 'Q':(0, 1<<64), |
| 74 | 'f':(-(1<<63), 1<<63), 'd':(-(1<<1023), 1<<1023) |
| 75 | } |
| 76 | |
| 77 | def native_type_range(fmt): |
| 78 | """Return range of a native type.""" |
| 79 | if fmt == 'c': |
| 80 | lh = (0, 256) |
| 81 | elif fmt == '?': |
| 82 | lh = (0, 2) |
| 83 | elif fmt == 'f': |
| 84 | lh = (-(1<<63), 1<<63) |
| 85 | elif fmt == 'd': |
| 86 | lh = (-(1<<1023), 1<<1023) |
| 87 | else: |
| 88 | for exp in (128, 127, 64, 63, 32, 31, 16, 15, 8, 7): |
| 89 | try: |
| 90 | struct.pack(fmt, (1<<exp)-1) |
| 91 | break |
| 92 | except struct.error: |
| 93 | pass |
| 94 | lh = (-(1<<exp), 1<<exp) if exp & 1 else (0, 1<<exp) |
| 95 | return lh |
| 96 | |
| 97 | fmtdict = { |
| 98 | '':NATIVE, |
| 99 | '@':NATIVE, |
| 100 | '<':STANDARD, |
| 101 | '>':STANDARD, |
| 102 | '=':STANDARD, |
| 103 | '!':STANDARD |
| 104 | } |
| 105 | |
| 106 | if struct: |
| 107 | for fmt in fmtdict['@']: |
| 108 | fmtdict['@'][fmt] = native_type_range(fmt) |
| 109 | |
| 110 | MEMORYVIEW = NATIVE.copy() |
| 111 | ARRAY = NATIVE.copy() |
| 112 | for k in NATIVE: |
| 113 | if not k in "bBhHiIlLfd": |
| 114 | del ARRAY[k] |
| 115 | |
| 116 | BYTEFMT = NATIVE.copy() |
| 117 | for k in NATIVE: |
| 118 | if not k in "Bbc": |
| 119 | del BYTEFMT[k] |
| 120 | |
| 121 | fmtdict['m'] = MEMORYVIEW |
| 122 | fmtdict['@m'] = MEMORYVIEW |
| 123 | fmtdict['a'] = ARRAY |
| 124 | fmtdict['b'] = BYTEFMT |
| 125 | fmtdict['@b'] = BYTEFMT |
| 126 | |
| 127 | # Capabilities of the test objects: |
| 128 | MODE = 0 |
| 129 | MULT = 1 |
| 130 | cap = { # format chars # multiplier |
| 131 | 'ndarray': (['', '@', '<', '>', '=', '!'], ['', '1', '2', '3']), |
| 132 | 'array': (['a'], ['']), |
| 133 | 'numpy': ([''], ['']), |
| 134 | 'memoryview': (['@m', 'm'], ['']), |
| 135 | 'bytefmt': (['@b', 'b'], ['']), |
| 136 | } |
| 137 | |
| 138 | def randrange_fmt(mode, char, obj): |
| 139 | """Return random item for a type specified by a mode and a single |
| 140 | format character.""" |
| 141 | x = randrange(*fmtdict[mode][char]) |
| 142 | if char == 'c': |
| 143 | x = bytes(chr(x), 'latin1') |
| 144 | if char == '?': |
| 145 | x = bool(x) |
| 146 | if char == 'f' or char == 'd': |
| 147 | x = struct.pack(char, x) |
| 148 | x = struct.unpack(char, x)[0] |
| 149 | if obj == 'numpy' and x == b'\x00': |
| 150 | # http://projects.scipy.org/numpy/ticket/1925 |
| 151 | x = b'\x01' |
| 152 | return x |
| 153 | |
| 154 | def gen_item(fmt, obj): |
| 155 | """Return single random item.""" |
| 156 | mode, chars = fmt.split('#') |
| 157 | x = [] |
| 158 | for c in chars: |
| 159 | x.append(randrange_fmt(mode, c, obj)) |
| 160 | return x[0] if len(x) == 1 else tuple(x) |
| 161 | |
| 162 | def gen_items(n, fmt, obj): |
| 163 | """Return a list of random items (or a scalar).""" |
| 164 | if n == 0: |
| 165 | return gen_item(fmt, obj) |
| 166 | lst = [0] * n |
| 167 | for i in range(n): |
| 168 | lst[i] = gen_item(fmt, obj) |
| 169 | return lst |
| 170 | |
| 171 | def struct_items(n, obj): |
| 172 | mode = choice(cap[obj][MODE]) |
| 173 | xfmt = mode + '#' |
| 174 | fmt = mode.strip('amb') |
| 175 | nmemb = randrange(2, 10) # number of struct members |
| 176 | for _ in range(nmemb): |
| 177 | char = choice(tuple(fmtdict[mode])) |
| 178 | multiplier = choice(cap[obj][MULT]) |
| 179 | xfmt += (char * int(multiplier if multiplier else 1)) |
| 180 | fmt += (multiplier + char) |
| 181 | items = gen_items(n, xfmt, obj) |
| 182 | item = gen_item(xfmt, obj) |
| 183 | return fmt, items, item |
| 184 | |
| 185 | def randitems(n, obj='ndarray', mode=None, char=None): |
| 186 | """Return random format, items, item.""" |
| 187 | if mode is None: |
| 188 | mode = choice(cap[obj][MODE]) |
| 189 | if char is None: |
| 190 | char = choice(tuple(fmtdict[mode])) |
| 191 | multiplier = choice(cap[obj][MULT]) |
| 192 | fmt = mode + '#' + char * int(multiplier if multiplier else 1) |
| 193 | items = gen_items(n, fmt, obj) |
| 194 | item = gen_item(fmt, obj) |
| 195 | fmt = mode.strip('amb') + multiplier + char |
| 196 | return fmt, items, item |
| 197 | |
| 198 | def iter_mode(n, obj='ndarray'): |
| 199 | """Iterate through supported mode/char combinations.""" |
| 200 | for mode in cap[obj][MODE]: |
| 201 | for char in fmtdict[mode]: |
| 202 | yield randitems(n, obj, mode, char) |
| 203 | |
| 204 | def iter_format(nitems, testobj='ndarray'): |
| 205 | """Yield (format, items, item) for all possible modes and format |
| 206 | characters plus one random compound format string.""" |
| 207 | for t in iter_mode(nitems, testobj): |
| 208 | yield t |
| 209 | if testobj != 'ndarray': |
| 210 | raise StopIteration |
| 211 | yield struct_items(nitems, testobj) |
| 212 | |
| 213 | |
| 214 | def is_byte_format(fmt): |
| 215 | return 'c' in fmt or 'b' in fmt or 'B' in fmt |
| 216 | |
| 217 | def is_memoryview_format(fmt): |
| 218 | """format suitable for memoryview""" |
| 219 | x = len(fmt) |
| 220 | return ((x == 1 or (x == 2 and fmt[0] == '@')) and |
| 221 | fmt[x-1] in MEMORYVIEW) |
| 222 | |
| 223 | NON_BYTE_FORMAT = [c for c in fmtdict['@'] if not is_byte_format(c)] |
| 224 | |
| 225 | |
| 226 | # ====================================================================== |
| 227 | # Multi-dimensional tolist(), slicing and slice assignments |
| 228 | # ====================================================================== |
| 229 | |
| 230 | def atomp(lst): |
| 231 | """Tuple items (representing structs) are regarded as atoms.""" |
| 232 | return not isinstance(lst, list) |
| 233 | |
| 234 | def listp(lst): |
| 235 | return isinstance(lst, list) |
| 236 | |
| 237 | def prod(lst): |
| 238 | """Product of list elements.""" |
| 239 | if len(lst) == 0: |
| 240 | return 0 |
| 241 | x = lst[0] |
| 242 | for v in lst[1:]: |
| 243 | x *= v |
| 244 | return x |
| 245 | |
| 246 | def strides_from_shape(ndim, shape, itemsize, layout): |
| 247 | """Calculate strides of a contiguous array. Layout is 'C' or |
| 248 | 'F' (Fortran).""" |
| 249 | if ndim == 0: |
| 250 | return () |
| 251 | if layout == 'C': |
| 252 | strides = list(shape[1:]) + [itemsize] |
| 253 | for i in range(ndim-2, -1, -1): |
| 254 | strides[i] *= strides[i+1] |
| 255 | else: |
| 256 | strides = [itemsize] + list(shape[:-1]) |
| 257 | for i in range(1, ndim): |
| 258 | strides[i] *= strides[i-1] |
| 259 | return strides |
| 260 | |
| 261 | def _ca(items, s): |
| 262 | """Convert flat item list to the nested list representation of a |
| 263 | multidimensional C array with shape 's'.""" |
| 264 | if atomp(items): |
| 265 | return items |
| 266 | if len(s) == 0: |
| 267 | return items[0] |
| 268 | lst = [0] * s[0] |
| 269 | stride = len(items) // s[0] if s[0] else 0 |
| 270 | for i in range(s[0]): |
| 271 | start = i*stride |
| 272 | lst[i] = _ca(items[start:start+stride], s[1:]) |
| 273 | return lst |
| 274 | |
| 275 | def _fa(items, s): |
| 276 | """Convert flat item list to the nested list representation of a |
| 277 | multidimensional Fortran array with shape 's'.""" |
| 278 | if atomp(items): |
| 279 | return items |
| 280 | if len(s) == 0: |
| 281 | return items[0] |
| 282 | lst = [0] * s[0] |
| 283 | stride = s[0] |
| 284 | for i in range(s[0]): |
| 285 | lst[i] = _fa(items[i::stride], s[1:]) |
| 286 | return lst |
| 287 | |
| 288 | def carray(items, shape): |
| 289 | if listp(items) and not 0 in shape and prod(shape) != len(items): |
| 290 | raise ValueError("prod(shape) != len(items)") |
| 291 | return _ca(items, shape) |
| 292 | |
| 293 | def farray(items, shape): |
| 294 | if listp(items) and not 0 in shape and prod(shape) != len(items): |
| 295 | raise ValueError("prod(shape) != len(items)") |
| 296 | return _fa(items, shape) |
| 297 | |
| 298 | def indices(shape): |
| 299 | """Generate all possible tuples of indices.""" |
| 300 | iterables = [range(v) for v in shape] |
| 301 | return product(*iterables) |
| 302 | |
| 303 | def getindex(ndim, ind, strides): |
| 304 | """Convert multi-dimensional index to the position in the flat list.""" |
| 305 | ret = 0 |
| 306 | for i in range(ndim): |
| 307 | ret += strides[i] * ind[i] |
| 308 | return ret |
| 309 | |
| 310 | def transpose(src, shape): |
| 311 | """Transpose flat item list that is regarded as a multi-dimensional |
| 312 | matrix defined by shape: dest...[k][j][i] = src[i][j][k]... """ |
| 313 | if not shape: |
| 314 | return src |
| 315 | ndim = len(shape) |
| 316 | sstrides = strides_from_shape(ndim, shape, 1, 'C') |
| 317 | dstrides = strides_from_shape(ndim, shape[::-1], 1, 'C') |
| 318 | dest = [0] * len(src) |
| 319 | for ind in indices(shape): |
| 320 | fr = getindex(ndim, ind, sstrides) |
| 321 | to = getindex(ndim, ind[::-1], dstrides) |
| 322 | dest[to] = src[fr] |
| 323 | return dest |
| 324 | |
| 325 | def _flatten(lst): |
| 326 | """flatten list""" |
| 327 | if lst == []: |
| 328 | return lst |
| 329 | if atomp(lst): |
| 330 | return [lst] |
| 331 | return _flatten(lst[0]) + _flatten(lst[1:]) |
| 332 | |
| 333 | def flatten(lst): |
| 334 | """flatten list or return scalar""" |
| 335 | if atomp(lst): # scalar |
| 336 | return lst |
| 337 | return _flatten(lst) |
| 338 | |
| 339 | def slice_shape(lst, slices): |
| 340 | """Get the shape of lst after slicing: slices is a list of slice |
| 341 | objects.""" |
| 342 | if atomp(lst): |
| 343 | return [] |
| 344 | return [len(lst[slices[0]])] + slice_shape(lst[0], slices[1:]) |
| 345 | |
| 346 | def multislice(lst, slices): |
| 347 | """Multi-dimensional slicing: slices is a list of slice objects.""" |
| 348 | if atomp(lst): |
| 349 | return lst |
| 350 | return [multislice(sublst, slices[1:]) for sublst in lst[slices[0]]] |
| 351 | |
| 352 | def m_assign(llst, rlst, lslices, rslices): |
| 353 | """Multi-dimensional slice assignment: llst and rlst are the operands, |
| 354 | lslices and rslices are lists of slice objects. llst and rlst must |
| 355 | have the same structure. |
| 356 | |
| 357 | For a two-dimensional example, this is not implemented in Python: |
| 358 | |
| 359 | llst[0:3:2, 0:3:2] = rlst[1:3:1, 1:3:1] |
| 360 | |
| 361 | Instead we write: |
| 362 | |
| 363 | lslices = [slice(0,3,2), slice(0,3,2)] |
| 364 | rslices = [slice(1,3,1), slice(1,3,1)] |
| 365 | multislice_assign(llst, rlst, lslices, rslices) |
| 366 | """ |
| 367 | if atomp(rlst): |
| 368 | return rlst |
| 369 | rlst = [m_assign(l, r, lslices[1:], rslices[1:]) |
| 370 | for l, r in zip(llst[lslices[0]], rlst[rslices[0]])] |
| 371 | llst[lslices[0]] = rlst |
| 372 | return llst |
| 373 | |
| 374 | def cmp_structure(llst, rlst, lslices, rslices): |
| 375 | """Compare the structure of llst[lslices] and rlst[rslices].""" |
| 376 | lshape = slice_shape(llst, lslices) |
| 377 | rshape = slice_shape(rlst, rslices) |
| 378 | if (len(lshape) != len(rshape)): |
| 379 | return -1 |
| 380 | for i in range(len(lshape)): |
| 381 | if lshape[i] != rshape[i]: |
| 382 | return -1 |
| 383 | if lshape[i] == 0: |
| 384 | return 0 |
| 385 | return 0 |
| 386 | |
| 387 | def multislice_assign(llst, rlst, lslices, rslices): |
| 388 | """Return llst after assigning: llst[lslices] = rlst[rslices]""" |
| 389 | if cmp_structure(llst, rlst, lslices, rslices) < 0: |
| 390 | raise ValueError("lvalue and rvalue have different structures") |
| 391 | return m_assign(llst, rlst, lslices, rslices) |
| 392 | |
| 393 | |
| 394 | # ====================================================================== |
| 395 | # Random structures |
| 396 | # ====================================================================== |
| 397 | |
| 398 | # |
| 399 | # PEP-3118 is very permissive with respect to the contents of a |
| 400 | # Py_buffer. In particular: |
| 401 | # |
| 402 | # - shape can be zero |
| 403 | # - strides can be any integer, including zero |
| 404 | # - offset can point to any location in the underlying |
| 405 | # memory block, provided that it is a multiple of |
| 406 | # itemsize. |
| 407 | # |
| 408 | # The functions in this section test and verify random structures |
| 409 | # in full generality. A structure is valid iff it fits in the |
| 410 | # underlying memory block. |
| 411 | # |
| 412 | # The structure 't' (short for 'tuple') is fully defined by: |
| 413 | # |
| 414 | # t = (memlen, itemsize, ndim, shape, strides, offset) |
| 415 | # |
| 416 | |
| 417 | def verify_structure(memlen, itemsize, ndim, shape, strides, offset): |
| 418 | """Verify that the parameters represent a valid array within |
| 419 | the bounds of the allocated memory: |
| 420 | char *mem: start of the physical memory block |
| 421 | memlen: length of the physical memory block |
| 422 | offset: (char *)buf - mem |
| 423 | """ |
| 424 | if offset % itemsize: |
| 425 | return False |
| 426 | if offset < 0 or offset+itemsize > memlen: |
| 427 | return False |
| 428 | if any(v % itemsize for v in strides): |
| 429 | return False |
| 430 | |
| 431 | if ndim <= 0: |
| 432 | return ndim == 0 and not shape and not strides |
| 433 | if 0 in shape: |
| 434 | return True |
| 435 | |
| 436 | imin = sum(strides[j]*(shape[j]-1) for j in range(ndim) |
| 437 | if strides[j] <= 0) |
| 438 | imax = sum(strides[j]*(shape[j]-1) for j in range(ndim) |
| 439 | if strides[j] > 0) |
| 440 | |
| 441 | return 0 <= offset+imin and offset+imax+itemsize <= memlen |
| 442 | |
| 443 | def get_item(lst, indices): |
| 444 | for i in indices: |
| 445 | lst = lst[i] |
| 446 | return lst |
| 447 | |
| 448 | def memory_index(indices, t): |
| 449 | """Location of an item in the underlying memory.""" |
| 450 | memlen, itemsize, ndim, shape, strides, offset = t |
| 451 | p = offset |
| 452 | for i in range(ndim): |
| 453 | p += strides[i]*indices[i] |
| 454 | return p |
| 455 | |
| 456 | def is_overlapping(t): |
| 457 | """The structure 't' is overlapping if at least one memory location |
| 458 | is visited twice while iterating through all possible tuples of |
| 459 | indices.""" |
| 460 | memlen, itemsize, ndim, shape, strides, offset = t |
| 461 | visited = 1<<memlen |
| 462 | for ind in indices(shape): |
| 463 | i = memory_index(ind, t) |
| 464 | bit = 1<<i |
| 465 | if visited & bit: |
| 466 | return True |
| 467 | visited |= bit |
| 468 | return False |
| 469 | |
| 470 | def rand_structure(itemsize, valid, maxdim=5, maxshape=16, shape=()): |
| 471 | """Return random structure: |
| 472 | (memlen, itemsize, ndim, shape, strides, offset) |
| 473 | If 'valid' is true, the returned structure is valid, otherwise invalid. |
| 474 | If 'shape' is given, use that instead of creating a random shape. |
| 475 | """ |
| 476 | if not shape: |
| 477 | ndim = randrange(maxdim+1) |
| 478 | if (ndim == 0): |
| 479 | if valid: |
| 480 | return itemsize, itemsize, ndim, (), (), 0 |
| 481 | else: |
| 482 | nitems = randrange(1, 16+1) |
| 483 | memlen = nitems * itemsize |
| 484 | offset = -itemsize if randrange(2) == 0 else memlen |
| 485 | return memlen, itemsize, ndim, (), (), offset |
| 486 | |
| 487 | minshape = 2 |
| 488 | n = randrange(100) |
| 489 | if n >= 95 and valid: |
| 490 | minshape = 0 |
| 491 | elif n >= 90: |
| 492 | minshape = 1 |
| 493 | shape = [0] * ndim |
| 494 | |
| 495 | for i in range(ndim): |
| 496 | shape[i] = randrange(minshape, maxshape+1) |
| 497 | else: |
| 498 | ndim = len(shape) |
| 499 | |
| 500 | maxstride = 5 |
| 501 | n = randrange(100) |
| 502 | zero_stride = True if n >= 95 and n & 1 else False |
| 503 | |
| 504 | strides = [0] * ndim |
| 505 | strides[ndim-1] = itemsize * randrange(-maxstride, maxstride+1) |
| 506 | if not zero_stride and strides[ndim-1] == 0: |
| 507 | strides[ndim-1] = itemsize |
| 508 | |
| 509 | for i in range(ndim-2, -1, -1): |
| 510 | maxstride *= shape[i+1] if shape[i+1] else 1 |
| 511 | if zero_stride: |
| 512 | strides[i] = itemsize * randrange(-maxstride, maxstride+1) |
| 513 | else: |
| 514 | strides[i] = ((1,-1)[randrange(2)] * |
| 515 | itemsize * randrange(1, maxstride+1)) |
| 516 | |
| 517 | imin = imax = 0 |
| 518 | if not 0 in shape: |
| 519 | imin = sum(strides[j]*(shape[j]-1) for j in range(ndim) |
| 520 | if strides[j] <= 0) |
| 521 | imax = sum(strides[j]*(shape[j]-1) for j in range(ndim) |
| 522 | if strides[j] > 0) |
| 523 | |
| 524 | nitems = imax - imin |
| 525 | if valid: |
| 526 | offset = -imin * itemsize |
| 527 | memlen = offset + (imax+1) * itemsize |
| 528 | else: |
| 529 | memlen = (-imin + imax) * itemsize |
| 530 | offset = -imin-itemsize if randrange(2) == 0 else memlen |
| 531 | return memlen, itemsize, ndim, shape, strides, offset |
| 532 | |
| 533 | def randslice_from_slicelen(slicelen, listlen): |
| 534 | """Create a random slice of len slicelen that fits into listlen.""" |
| 535 | maxstart = listlen - slicelen |
| 536 | start = randrange(maxstart+1) |
| 537 | maxstep = (listlen - start) // slicelen if slicelen else 1 |
| 538 | step = randrange(1, maxstep+1) |
| 539 | stop = start + slicelen * step |
| 540 | s = slice(start, stop, step) |
| 541 | _, _, _, control = slice_indices(s, listlen) |
| 542 | if control != slicelen: |
| 543 | raise RuntimeError |
| 544 | return s |
| 545 | |
| 546 | def randslice_from_shape(ndim, shape): |
| 547 | """Create two sets of slices for an array x with shape 'shape' |
| 548 | such that shapeof(x[lslices]) == shapeof(x[rslices]).""" |
| 549 | lslices = [0] * ndim |
| 550 | rslices = [0] * ndim |
| 551 | for n in range(ndim): |
| 552 | l = shape[n] |
| 553 | slicelen = randrange(1, l+1) if l > 0 else 0 |
| 554 | lslices[n] = randslice_from_slicelen(slicelen, l) |
| 555 | rslices[n] = randslice_from_slicelen(slicelen, l) |
| 556 | return tuple(lslices), tuple(rslices) |
| 557 | |
| 558 | def rand_aligned_slices(maxdim=5, maxshape=16): |
| 559 | """Create (lshape, rshape, tuple(lslices), tuple(rslices)) such that |
| 560 | shapeof(x[lslices]) == shapeof(y[rslices]), where x is an array |
| 561 | with shape 'lshape' and y is an array with shape 'rshape'.""" |
| 562 | ndim = randrange(1, maxdim+1) |
| 563 | minshape = 2 |
| 564 | n = randrange(100) |
| 565 | if n >= 95: |
| 566 | minshape = 0 |
| 567 | elif n >= 90: |
| 568 | minshape = 1 |
| 569 | all_random = True if randrange(100) >= 80 else False |
| 570 | lshape = [0]*ndim; rshape = [0]*ndim |
| 571 | lslices = [0]*ndim; rslices = [0]*ndim |
| 572 | |
| 573 | for n in range(ndim): |
| 574 | small = randrange(minshape, maxshape+1) |
| 575 | big = randrange(minshape, maxshape+1) |
| 576 | if big < small: |
| 577 | big, small = small, big |
| 578 | |
| 579 | # Create a slice that fits the smaller value. |
| 580 | if all_random: |
| 581 | start = randrange(-small, small+1) |
| 582 | stop = randrange(-small, small+1) |
| 583 | step = (1,-1)[randrange(2)] * randrange(1, small+2) |
| 584 | s_small = slice(start, stop, step) |
| 585 | _, _, _, slicelen = slice_indices(s_small, small) |
| 586 | else: |
| 587 | slicelen = randrange(1, small+1) if small > 0 else 0 |
| 588 | s_small = randslice_from_slicelen(slicelen, small) |
| 589 | |
| 590 | # Create a slice of the same length for the bigger value. |
| 591 | s_big = randslice_from_slicelen(slicelen, big) |
| 592 | if randrange(2) == 0: |
| 593 | rshape[n], lshape[n] = big, small |
| 594 | rslices[n], lslices[n] = s_big, s_small |
| 595 | else: |
| 596 | rshape[n], lshape[n] = small, big |
| 597 | rslices[n], lslices[n] = s_small, s_big |
| 598 | |
| 599 | return lshape, rshape, tuple(lslices), tuple(rslices) |
| 600 | |
| 601 | def randitems_from_structure(fmt, t): |
| 602 | """Return a list of random items for structure 't' with format |
| 603 | 'fmtchar'.""" |
| 604 | memlen, itemsize, _, _, _, _ = t |
| 605 | return gen_items(memlen//itemsize, '#'+fmt, 'numpy') |
| 606 | |
| 607 | def ndarray_from_structure(items, fmt, t, flags=0): |
| 608 | """Return ndarray from the tuple returned by rand_structure()""" |
| 609 | memlen, itemsize, ndim, shape, strides, offset = t |
| 610 | return ndarray(items, shape=shape, strides=strides, format=fmt, |
| 611 | offset=offset, flags=ND_WRITABLE|flags) |
| 612 | |
| 613 | def numpy_array_from_structure(items, fmt, t): |
| 614 | """Return numpy_array from the tuple returned by rand_structure()""" |
| 615 | memlen, itemsize, ndim, shape, strides, offset = t |
| 616 | buf = bytearray(memlen) |
| 617 | for j, v in enumerate(items): |
| 618 | struct.pack_into(fmt, buf, j*itemsize, v) |
| 619 | return numpy_array(buffer=buf, shape=shape, strides=strides, |
| 620 | dtype=fmt, offset=offset) |
| 621 | |
| 622 | |
| 623 | # ====================================================================== |
| 624 | # memoryview casts |
| 625 | # ====================================================================== |
| 626 | |
| 627 | def cast_items(exporter, fmt, itemsize, shape=None): |
| 628 | """Interpret the raw memory of 'exporter' as a list of items with |
| 629 | size 'itemsize'. If shape=None, the new structure is assumed to |
| 630 | be 1-D with n * itemsize = bytelen. If shape is given, the usual |
| 631 | constraint for contiguous arrays prod(shape) * itemsize = bytelen |
| 632 | applies. On success, return (items, shape). If the constraints |
| 633 | cannot be met, return (None, None). If a chunk of bytes is interpreted |
| 634 | as NaN as a result of float conversion, return ('nan', None).""" |
| 635 | bytelen = exporter.nbytes |
| 636 | if shape: |
| 637 | if prod(shape) * itemsize != bytelen: |
| 638 | return None, shape |
| 639 | elif shape == []: |
| 640 | if exporter.ndim == 0 or itemsize != bytelen: |
| 641 | return None, shape |
| 642 | else: |
| 643 | n, r = divmod(bytelen, itemsize) |
| 644 | shape = [n] |
| 645 | if r != 0: |
| 646 | return None, shape |
| 647 | |
| 648 | mem = exporter.tobytes() |
| 649 | byteitems = [mem[i:i+itemsize] for i in range(0, len(mem), itemsize)] |
| 650 | |
| 651 | items = [] |
| 652 | for v in byteitems: |
| 653 | item = struct.unpack(fmt, v)[0] |
| 654 | if item != item: |
| 655 | return 'nan', shape |
| 656 | items.append(item) |
| 657 | |
| 658 | return (items, shape) if shape != [] else (items[0], shape) |
| 659 | |
| 660 | def gencastshapes(): |
| 661 | """Generate shapes to test casting.""" |
| 662 | for n in range(32): |
| 663 | yield [n] |
| 664 | ndim = randrange(4, 6) |
| 665 | minshape = 1 if randrange(100) > 80 else 2 |
| 666 | yield [randrange(minshape, 5) for _ in range(ndim)] |
| 667 | ndim = randrange(2, 4) |
| 668 | minshape = 1 if randrange(100) > 80 else 2 |
| 669 | yield [randrange(minshape, 5) for _ in range(ndim)] |
| 670 | |
| 671 | |
| 672 | # ====================================================================== |
| 673 | # Actual tests |
| 674 | # ====================================================================== |
| 675 | |
| 676 | def genslices(n): |
| 677 | """Generate all possible slices for a single dimension.""" |
| 678 | return product(range(-n, n+1), range(-n, n+1), range(-n, n+1)) |
| 679 | |
| 680 | def genslices_ndim(ndim, shape): |
| 681 | """Generate all possible slice tuples for 'shape'.""" |
| 682 | iterables = [genslices(shape[n]) for n in range(ndim)] |
| 683 | return product(*iterables) |
| 684 | |
| 685 | def rslice(n, allow_empty=False): |
| 686 | """Generate random slice for a single dimension of length n. |
| 687 | If zero=True, the slices may be empty, otherwise they will |
| 688 | be non-empty.""" |
| 689 | minlen = 0 if allow_empty or n == 0 else 1 |
| 690 | slicelen = randrange(minlen, n+1) |
| 691 | return randslice_from_slicelen(slicelen, n) |
| 692 | |
| 693 | def rslices(n, allow_empty=False): |
| 694 | """Generate random slices for a single dimension.""" |
| 695 | for _ in range(5): |
| 696 | yield rslice(n, allow_empty) |
| 697 | |
| 698 | def rslices_ndim(ndim, shape, iterations=5): |
| 699 | """Generate random slice tuples for 'shape'.""" |
| 700 | # non-empty slices |
| 701 | for _ in range(iterations): |
| 702 | yield tuple(rslice(shape[n]) for n in range(ndim)) |
| 703 | # possibly empty slices |
| 704 | for _ in range(iterations): |
| 705 | yield tuple(rslice(shape[n], allow_empty=True) for n in range(ndim)) |
| 706 | # invalid slices |
| 707 | yield tuple(slice(0,1,0) for _ in range(ndim)) |
| 708 | |
| 709 | def rpermutation(iterable, r=None): |
| 710 | pool = tuple(iterable) |
| 711 | r = len(pool) if r is None else r |
| 712 | yield tuple(sample(pool, r)) |
| 713 | |
| 714 | def ndarray_print(nd): |
| 715 | """Print ndarray for debugging.""" |
| 716 | try: |
| 717 | x = nd.tolist() |
| 718 | except (TypeError, NotImplementedError): |
| 719 | x = nd.tobytes() |
| 720 | if isinstance(nd, ndarray): |
| 721 | offset = nd.offset |
| 722 | flags = nd.flags |
| 723 | else: |
| 724 | offset = 'unknown' |
| 725 | flags = 'unknown' |
| 726 | print("ndarray(%s, shape=%s, strides=%s, suboffsets=%s, offset=%s, " |
| 727 | "format='%s', itemsize=%s, flags=%s)" % |
| 728 | (x, nd.shape, nd.strides, nd.suboffsets, offset, |
| 729 | nd.format, nd.itemsize, flags)) |
| 730 | sys.stdout.flush() |
| 731 | |
| 732 | |
| 733 | ITERATIONS = 100 |
| 734 | MAXDIM = 5 |
| 735 | MAXSHAPE = 10 |
| 736 | |
| 737 | if SHORT_TEST: |
| 738 | ITERATIONS = 10 |
| 739 | MAXDIM = 3 |
| 740 | MAXSHAPE = 4 |
| 741 | genslices = rslices |
| 742 | genslices_ndim = rslices_ndim |
| 743 | permutations = rpermutation |
| 744 | |
| 745 | |
| 746 | @unittest.skipUnless(struct, 'struct module required for this test.') |
| 747 | @unittest.skipUnless(ndarray, 'ndarray object required for this test') |
| 748 | class TestBufferProtocol(unittest.TestCase): |
| 749 | |
| 750 | def setUp(self): |
| 751 | self.sizeof_void_p = get_config_var('SIZEOF_VOID_P') |
| 752 | if not self.sizeof_void_p: |
| 753 | self.sizeof_void_p = 8 if architecture()[0] == '64bit' else 4 |
| 754 | |
| 755 | def verify(self, result, obj=-1, |
| 756 | itemsize={1}, fmt=-1, readonly={1}, |
| 757 | ndim={1}, shape=-1, strides=-1, |
| 758 | lst=-1, sliced=False, cast=False): |
| 759 | # Verify buffer contents against expected values. Default values |
| 760 | # are deliberately initialized to invalid types. |
| 761 | if shape: |
| 762 | expected_len = prod(shape)*itemsize |
| 763 | else: |
| 764 | if not fmt: # array has been implicitly cast to unsigned bytes |
| 765 | expected_len = len(lst) |
| 766 | else: # ndim = 0 |
| 767 | expected_len = itemsize |
| 768 | |
| 769 | # Reconstruct suboffsets from strides. Support for slicing |
| 770 | # could be added, but is currently only needed for test_getbuf(). |
| 771 | suboffsets = () |
| 772 | if result.suboffsets: |
| 773 | self.assertGreater(ndim, 0) |
| 774 | |
| 775 | suboffset0 = 0 |
| 776 | for n in range(1, ndim): |
| 777 | if shape[n] == 0: |
| 778 | break |
| 779 | if strides[n] <= 0: |
| 780 | suboffset0 += -strides[n] * (shape[n]-1) |
| 781 | |
| 782 | suboffsets = [suboffset0] + [-1 for v in range(ndim-1)] |
| 783 | |
| 784 | # Not correct if slicing has occurred in the first dimension. |
| 785 | stride0 = self.sizeof_void_p |
| 786 | if strides[0] < 0: |
| 787 | stride0 = -stride0 |
| 788 | strides = [stride0] + list(strides[1:]) |
| 789 | |
| 790 | self.assertIs(result.obj, obj) |
| 791 | self.assertEqual(result.nbytes, expected_len) |
| 792 | self.assertEqual(result.itemsize, itemsize) |
| 793 | self.assertEqual(result.format, fmt) |
| 794 | self.assertEqual(result.readonly, readonly) |
| 795 | self.assertEqual(result.ndim, ndim) |
| 796 | self.assertEqual(result.shape, tuple(shape)) |
| 797 | if not (sliced and suboffsets): |
| 798 | self.assertEqual(result.strides, tuple(strides)) |
| 799 | self.assertEqual(result.suboffsets, tuple(suboffsets)) |
| 800 | |
| 801 | if isinstance(result, ndarray) or is_memoryview_format(fmt): |
| 802 | rep = result.tolist() if fmt else result.tobytes() |
| 803 | self.assertEqual(rep, lst) |
| 804 | |
| 805 | if not fmt: # array has been cast to unsigned bytes, |
| 806 | return # the remaining tests won't work. |
| 807 | |
| 808 | # PyBuffer_GetPointer() is the definition how to access an item. |
| 809 | # If PyBuffer_GetPointer(indices) is correct for all possible |
| 810 | # combinations of indices, the buffer is correct. |
| 811 | # |
| 812 | # Also test tobytes() against the flattened 'lst', with all items |
| 813 | # packed to bytes. |
| 814 | if not cast: # casts chop up 'lst' in different ways |
| 815 | b = bytearray() |
| 816 | buf_err = None |
| 817 | for ind in indices(shape): |
| 818 | try: |
| 819 | item1 = get_pointer(result, ind) |
| 820 | item2 = get_item(lst, ind) |
| 821 | if isinstance(item2, tuple): |
| 822 | x = struct.pack(fmt, *item2) |
| 823 | else: |
| 824 | x = struct.pack(fmt, item2) |
| 825 | b.extend(x) |
| 826 | except BufferError: |
| 827 | buf_err = True # re-exporter does not provide full buffer |
| 828 | break |
| 829 | self.assertEqual(item1, item2) |
| 830 | |
| 831 | if not buf_err: |
| 832 | # test tobytes() |
| 833 | self.assertEqual(result.tobytes(), b) |
| 834 | |
| 835 | if not buf_err and is_memoryview_format(fmt): |
| 836 | |
| 837 | # lst := expected multi-dimensional logical representation |
| 838 | # flatten(lst) := elements in C-order |
| 839 | ff = fmt if fmt else 'B' |
| 840 | flattened = flatten(lst) |
| 841 | |
| 842 | # Rules for 'A': if the array is already contiguous, return |
| 843 | # the array unaltered. Otherwise, return a contiguous 'C' |
| 844 | # representation. |
| 845 | for order in ['C', 'F', 'A']: |
| 846 | expected = result |
| 847 | if order == 'F': |
| 848 | if not is_contiguous(result, 'A') or \ |
| 849 | is_contiguous(result, 'C'): |
| 850 | # For constructing the ndarray, convert the |
| 851 | # flattened logical representation to Fortran order. |
| 852 | trans = transpose(flattened, shape) |
| 853 | expected = ndarray(trans, shape=shape, format=ff, |
| 854 | flags=ND_FORTRAN) |
| 855 | else: # 'C', 'A' |
| 856 | if not is_contiguous(result, 'A') or \ |
| 857 | is_contiguous(result, 'F') and order == 'C': |
| 858 | # The flattened list is already in C-order. |
| 859 | expected = ndarray(flattened, shape=shape, format=ff) |
| 860 | contig = get_contiguous(result, PyBUF_READ, order) |
| 861 | contig = get_contiguous(result, PyBUF_READ, order) |
| 862 | self.assertEqual(contig.tobytes(), b) |
| 863 | self.assertTrue(cmp_contig(contig, expected)) |
| 864 | |
| 865 | if is_memoryview_format(fmt): |
| 866 | try: |
| 867 | m = memoryview(result) |
| 868 | except BufferError: # re-exporter does not provide full information |
| 869 | return |
| 870 | ex = result.obj if isinstance(result, memoryview) else result |
| 871 | self.assertIs(m.obj, ex) |
| 872 | self.assertEqual(m.nbytes, expected_len) |
| 873 | self.assertEqual(m.itemsize, itemsize) |
| 874 | self.assertEqual(m.format, fmt) |
| 875 | self.assertEqual(m.readonly, readonly) |
| 876 | self.assertEqual(m.ndim, ndim) |
| 877 | self.assertEqual(m.shape, tuple(shape)) |
| 878 | if not (sliced and suboffsets): |
| 879 | self.assertEqual(m.strides, tuple(strides)) |
| 880 | self.assertEqual(m.suboffsets, tuple(suboffsets)) |
| 881 | |
| 882 | n = 1 if ndim == 0 else len(lst) |
| 883 | self.assertEqual(len(m), n) |
| 884 | |
| 885 | rep = result.tolist() if fmt else result.tobytes() |
| 886 | self.assertEqual(rep, lst) |
| 887 | self.assertEqual(m, result) |
| 888 | |
| 889 | def verify_getbuf(self, orig_ex, ex, req, sliced=False): |
| 890 | def simple_fmt(ex): |
| 891 | return ex.format == '' or ex.format == 'B' |
| 892 | def match(req, flag): |
| 893 | return ((req&flag) == flag) |
| 894 | |
| 895 | if (# writable request to read-only exporter |
| 896 | (ex.readonly and match(req, PyBUF_WRITABLE)) or |
| 897 | # cannot match explicit contiguity request |
| 898 | (match(req, PyBUF_C_CONTIGUOUS) and not ex.c_contiguous) or |
| 899 | (match(req, PyBUF_F_CONTIGUOUS) and not ex.f_contiguous) or |
| 900 | (match(req, PyBUF_ANY_CONTIGUOUS) and not ex.contiguous) or |
| 901 | # buffer needs suboffsets |
| 902 | (not match(req, PyBUF_INDIRECT) and ex.suboffsets) or |
| 903 | # buffer without strides must be C-contiguous |
| 904 | (not match(req, PyBUF_STRIDES) and not ex.c_contiguous) or |
| 905 | # PyBUF_SIMPLE|PyBUF_FORMAT and PyBUF_WRITABLE|PyBUF_FORMAT |
| 906 | (not match(req, PyBUF_ND) and match(req, PyBUF_FORMAT))): |
| 907 | |
| 908 | self.assertRaises(BufferError, ndarray, ex, getbuf=req) |
| 909 | return |
| 910 | |
| 911 | if isinstance(ex, ndarray) or is_memoryview_format(ex.format): |
| 912 | lst = ex.tolist() |
| 913 | else: |
| 914 | nd = ndarray(ex, getbuf=PyBUF_FULL_RO) |
| 915 | lst = nd.tolist() |
| 916 | |
| 917 | # The consumer may have requested default values or a NULL format. |
| 918 | ro = 0 if match(req, PyBUF_WRITABLE) else ex.readonly |
| 919 | fmt = ex.format |
| 920 | itemsize = ex.itemsize |
| 921 | ndim = ex.ndim |
| 922 | if not match(req, PyBUF_FORMAT): |
| 923 | # itemsize refers to the original itemsize before the cast. |
| 924 | # The equality product(shape) * itemsize = len still holds. |
| 925 | # The equality calcsize(format) = itemsize does _not_ hold. |
| 926 | fmt = '' |
| 927 | lst = orig_ex.tobytes() # Issue 12834 |
| 928 | if not match(req, PyBUF_ND): |
| 929 | ndim = 1 |
| 930 | shape = orig_ex.shape if match(req, PyBUF_ND) else () |
| 931 | strides = orig_ex.strides if match(req, PyBUF_STRIDES) else () |
| 932 | |
| 933 | nd = ndarray(ex, getbuf=req) |
| 934 | self.verify(nd, obj=ex, |
| 935 | itemsize=itemsize, fmt=fmt, readonly=ro, |
| 936 | ndim=ndim, shape=shape, strides=strides, |
| 937 | lst=lst, sliced=sliced) |
| 938 | |
| 939 | def test_ndarray_getbuf(self): |
| 940 | requests = ( |
| 941 | # distinct flags |
| 942 | PyBUF_INDIRECT, PyBUF_STRIDES, PyBUF_ND, PyBUF_SIMPLE, |
| 943 | PyBUF_C_CONTIGUOUS, PyBUF_F_CONTIGUOUS, PyBUF_ANY_CONTIGUOUS, |
| 944 | # compound requests |
| 945 | PyBUF_FULL, PyBUF_FULL_RO, |
| 946 | PyBUF_RECORDS, PyBUF_RECORDS_RO, |
| 947 | PyBUF_STRIDED, PyBUF_STRIDED_RO, |
| 948 | PyBUF_CONTIG, PyBUF_CONTIG_RO, |
| 949 | ) |
| 950 | # items and format |
| 951 | items_fmt = ( |
| 952 | ([True if x % 2 else False for x in range(12)], '?'), |
| 953 | ([1,2,3,4,5,6,7,8,9,10,11,12], 'b'), |
| 954 | ([1,2,3,4,5,6,7,8,9,10,11,12], 'B'), |
| 955 | ([(2**31-x) if x % 2 else (-2**31+x) for x in range(12)], 'l') |
| 956 | ) |
| 957 | # shape, strides, offset |
| 958 | structure = ( |
| 959 | ([], [], 0), |
| 960 | ([12], [], 0), |
| 961 | ([12], [-1], 11), |
| 962 | ([6], [2], 0), |
| 963 | ([6], [-2], 11), |
| 964 | ([3, 4], [], 0), |
| 965 | ([3, 4], [-4, -1], 11), |
| 966 | ([2, 2], [4, 1], 4), |
| 967 | ([2, 2], [-4, -1], 8) |
| 968 | ) |
| 969 | # ndarray creation flags |
| 970 | ndflags = ( |
| 971 | 0, ND_WRITABLE, ND_FORTRAN, ND_FORTRAN|ND_WRITABLE, |
| 972 | ND_PIL, ND_PIL|ND_WRITABLE |
| 973 | ) |
| 974 | # flags that can actually be used as flags |
| 975 | real_flags = (0, PyBUF_WRITABLE, PyBUF_FORMAT, |
| 976 | PyBUF_WRITABLE|PyBUF_FORMAT) |
| 977 | |
| 978 | for items, fmt in items_fmt: |
| 979 | itemsize = struct.calcsize(fmt) |
| 980 | for shape, strides, offset in structure: |
| 981 | strides = [v * itemsize for v in strides] |
| 982 | offset *= itemsize |
| 983 | for flags in ndflags: |
| 984 | |
| 985 | if strides and (flags&ND_FORTRAN): |
| 986 | continue |
| 987 | if not shape and (flags&ND_PIL): |
| 988 | continue |
| 989 | |
| 990 | _items = items if shape else items[0] |
| 991 | ex1 = ndarray(_items, format=fmt, flags=flags, |
| 992 | shape=shape, strides=strides, offset=offset) |
| 993 | ex2 = ex1[::-2] if shape else None |
| 994 | |
| 995 | m1 = memoryview(ex1) |
| 996 | if ex2: |
| 997 | m2 = memoryview(ex2) |
| 998 | if ex1.ndim == 0 or (ex1.ndim == 1 and shape and strides): |
| 999 | self.assertEqual(m1, ex1) |
| 1000 | if ex2 and ex2.ndim == 1 and shape and strides: |
| 1001 | self.assertEqual(m2, ex2) |
| 1002 | |
| 1003 | for req in requests: |
| 1004 | for bits in real_flags: |
| 1005 | self.verify_getbuf(ex1, ex1, req|bits) |
| 1006 | self.verify_getbuf(ex1, m1, req|bits) |
| 1007 | if ex2: |
| 1008 | self.verify_getbuf(ex2, ex2, req|bits, |
| 1009 | sliced=True) |
| 1010 | self.verify_getbuf(ex2, m2, req|bits, |
| 1011 | sliced=True) |
| 1012 | |
| 1013 | items = [1,2,3,4,5,6,7,8,9,10,11,12] |
| 1014 | |
| 1015 | # ND_GETBUF_FAIL |
| 1016 | ex = ndarray(items, shape=[12], flags=ND_GETBUF_FAIL) |
| 1017 | self.assertRaises(BufferError, ndarray, ex) |
| 1018 | |
| 1019 | # Request complex structure from a simple exporter. In this |
| 1020 | # particular case the test object is not PEP-3118 compliant. |
| 1021 | base = ndarray([9], [1]) |
| 1022 | ex = ndarray(base, getbuf=PyBUF_SIMPLE) |
| 1023 | self.assertRaises(BufferError, ndarray, ex, getbuf=PyBUF_WRITABLE) |
| 1024 | self.assertRaises(BufferError, ndarray, ex, getbuf=PyBUF_ND) |
| 1025 | self.assertRaises(BufferError, ndarray, ex, getbuf=PyBUF_STRIDES) |
| 1026 | self.assertRaises(BufferError, ndarray, ex, getbuf=PyBUF_C_CONTIGUOUS) |
| 1027 | self.assertRaises(BufferError, ndarray, ex, getbuf=PyBUF_F_CONTIGUOUS) |
| 1028 | self.assertRaises(BufferError, ndarray, ex, getbuf=PyBUF_ANY_CONTIGUOUS) |
| 1029 | nd = ndarray(ex, getbuf=PyBUF_SIMPLE) |
| 1030 | |
| 1031 | def test_ndarray_exceptions(self): |
| 1032 | nd = ndarray([9], [1]) |
| 1033 | ndm = ndarray([9], [1], flags=ND_VAREXPORT) |
| 1034 | |
| 1035 | # Initialization of a new ndarray or mutation of an existing array. |
| 1036 | for c in (ndarray, nd.push, ndm.push): |
| 1037 | # Invalid types. |
| 1038 | self.assertRaises(TypeError, c, {1,2,3}) |
| 1039 | self.assertRaises(TypeError, c, [1,2,'3']) |
| 1040 | self.assertRaises(TypeError, c, [1,2,(3,4)]) |
| 1041 | self.assertRaises(TypeError, c, [1,2,3], shape={3}) |
| 1042 | self.assertRaises(TypeError, c, [1,2,3], shape=[3], strides={1}) |
| 1043 | self.assertRaises(TypeError, c, [1,2,3], shape=[3], offset=[]) |
| 1044 | self.assertRaises(TypeError, c, [1], shape=[1], format={}) |
| 1045 | self.assertRaises(TypeError, c, [1], shape=[1], flags={}) |
| 1046 | self.assertRaises(TypeError, c, [1], shape=[1], getbuf={}) |
| 1047 | |
| 1048 | # ND_FORTRAN flag is only valid without strides. |
| 1049 | self.assertRaises(TypeError, c, [1], shape=[1], strides=[1], |
| 1050 | flags=ND_FORTRAN) |
| 1051 | |
| 1052 | # ND_PIL flag is only valid with ndim > 0. |
| 1053 | self.assertRaises(TypeError, c, [1], shape=[], flags=ND_PIL) |
| 1054 | |
| 1055 | # Invalid items. |
| 1056 | self.assertRaises(ValueError, c, [], shape=[1]) |
| 1057 | self.assertRaises(ValueError, c, ['XXX'], shape=[1], format="L") |
| 1058 | # Invalid combination of items and format. |
| 1059 | self.assertRaises(struct.error, c, [1000], shape=[1], format="B") |
| 1060 | self.assertRaises(ValueError, c, [1,(2,3)], shape=[2], format="B") |
| 1061 | self.assertRaises(ValueError, c, [1,2,3], shape=[3], format="QL") |
| 1062 | |
| 1063 | # Invalid ndim. |
| 1064 | n = ND_MAX_NDIM+1 |
| 1065 | self.assertRaises(ValueError, c, [1]*n, shape=[1]*n) |
| 1066 | |
| 1067 | # Invalid shape. |
| 1068 | self.assertRaises(ValueError, c, [1], shape=[-1]) |
| 1069 | self.assertRaises(ValueError, c, [1,2,3], shape=['3']) |
| 1070 | self.assertRaises(OverflowError, c, [1], shape=[2**128]) |
| 1071 | # prod(shape) * itemsize != len(items) |
| 1072 | self.assertRaises(ValueError, c, [1,2,3,4,5], shape=[2,2], offset=3) |
| 1073 | |
| 1074 | # Invalid strides. |
| 1075 | self.assertRaises(ValueError, c, [1,2,3], shape=[3], strides=['1']) |
| 1076 | self.assertRaises(OverflowError, c, [1], shape=[1], |
| 1077 | strides=[2**128]) |
| 1078 | |
| 1079 | # Invalid combination of strides and shape. |
| 1080 | self.assertRaises(ValueError, c, [1,2], shape=[2,1], strides=[1]) |
| 1081 | # Invalid combination of strides and format. |
| 1082 | self.assertRaises(ValueError, c, [1,2,3,4], shape=[2], strides=[3], |
| 1083 | format="L") |
| 1084 | |
| 1085 | # Invalid offset. |
| 1086 | self.assertRaises(ValueError, c, [1,2,3], shape=[3], offset=4) |
| 1087 | self.assertRaises(ValueError, c, [1,2,3], shape=[1], offset=3, |
| 1088 | format="L") |
| 1089 | |
| 1090 | # Invalid format. |
| 1091 | self.assertRaises(ValueError, c, [1,2,3], shape=[3], format="") |
| 1092 | self.assertRaises(struct.error, c, [(1,2,3)], shape=[1], |
| 1093 | format="@#$") |
| 1094 | |
| 1095 | # Striding out of the memory bounds. |
| 1096 | items = [1,2,3,4,5,6,7,8,9,10] |
| 1097 | self.assertRaises(ValueError, c, items, shape=[2,3], |
| 1098 | strides=[-3, -2], offset=5) |
| 1099 | |
| 1100 | # Constructing consumer: format argument invalid. |
| 1101 | self.assertRaises(TypeError, c, bytearray(), format="Q") |
| 1102 | |
| 1103 | # Constructing original base object: getbuf argument invalid. |
| 1104 | self.assertRaises(TypeError, c, [1], shape=[1], getbuf=PyBUF_FULL) |
| 1105 | |
| 1106 | # Shape argument is mandatory for original base objects. |
| 1107 | self.assertRaises(TypeError, c, [1]) |
| 1108 | |
| 1109 | |
| 1110 | # PyBUF_WRITABLE request to read-only provider. |
| 1111 | self.assertRaises(BufferError, ndarray, b'123', getbuf=PyBUF_WRITABLE) |
| 1112 | |
| 1113 | # ND_VAREXPORT can only be specified during construction. |
| 1114 | nd = ndarray([9], [1], flags=ND_VAREXPORT) |
| 1115 | self.assertRaises(ValueError, nd.push, [1], [1], flags=ND_VAREXPORT) |
| 1116 | |
| 1117 | # Invalid operation for consumers: push/pop |
| 1118 | nd = ndarray(b'123') |
| 1119 | self.assertRaises(BufferError, nd.push, [1], [1]) |
| 1120 | self.assertRaises(BufferError, nd.pop) |
| 1121 | |
| 1122 | # ND_VAREXPORT not set: push/pop fail with exported buffers |
| 1123 | nd = ndarray([9], [1]) |
| 1124 | nd.push([1], [1]) |
| 1125 | m = memoryview(nd) |
| 1126 | self.assertRaises(BufferError, nd.push, [1], [1]) |
| 1127 | self.assertRaises(BufferError, nd.pop) |
| 1128 | m.release() |
| 1129 | nd.pop() |
| 1130 | |
| 1131 | # Single remaining buffer: pop fails |
| 1132 | self.assertRaises(BufferError, nd.pop) |
| 1133 | del nd |
| 1134 | |
| 1135 | # get_pointer() |
| 1136 | self.assertRaises(TypeError, get_pointer, {}, [1,2,3]) |
| 1137 | self.assertRaises(TypeError, get_pointer, b'123', {}) |
| 1138 | |
| 1139 | nd = ndarray(list(range(100)), shape=[1]*100) |
| 1140 | self.assertRaises(ValueError, get_pointer, nd, [5]) |
| 1141 | |
| 1142 | nd = ndarray(list(range(12)), shape=[3,4]) |
| 1143 | self.assertRaises(ValueError, get_pointer, nd, [2,3,4]) |
| 1144 | self.assertRaises(ValueError, get_pointer, nd, [3,3]) |
| 1145 | self.assertRaises(ValueError, get_pointer, nd, [-3,3]) |
| 1146 | self.assertRaises(OverflowError, get_pointer, nd, [1<<64,3]) |
| 1147 | |
| 1148 | # tolist() needs format |
| 1149 | ex = ndarray([1,2,3], shape=[3], format='L') |
| 1150 | nd = ndarray(ex, getbuf=PyBUF_SIMPLE) |
| 1151 | self.assertRaises(ValueError, nd.tolist) |
| 1152 | |
| 1153 | # memoryview_from_buffer() |
| 1154 | ex1 = ndarray([1,2,3], shape=[3], format='L') |
| 1155 | ex2 = ndarray(ex1) |
| 1156 | nd = ndarray(ex2) |
| 1157 | self.assertRaises(TypeError, nd.memoryview_from_buffer) |
| 1158 | |
| 1159 | nd = ndarray([(1,)*200], shape=[1], format='L'*200) |
| 1160 | self.assertRaises(TypeError, nd.memoryview_from_buffer) |
| 1161 | |
| 1162 | n = ND_MAX_NDIM |
| 1163 | nd = ndarray(list(range(n)), shape=[1]*n) |
| 1164 | self.assertRaises(ValueError, nd.memoryview_from_buffer) |
| 1165 | |
| 1166 | # get_contiguous() |
| 1167 | nd = ndarray([1], shape=[1]) |
| 1168 | self.assertRaises(TypeError, get_contiguous, 1, 2, 3, 4, 5) |
| 1169 | self.assertRaises(TypeError, get_contiguous, nd, "xyz", 'C') |
| 1170 | self.assertRaises(OverflowError, get_contiguous, nd, 2**64, 'C') |
| 1171 | self.assertRaises(TypeError, get_contiguous, nd, PyBUF_READ, 961) |
| 1172 | self.assertRaises(UnicodeEncodeError, get_contiguous, nd, PyBUF_READ, |
| 1173 | '\u2007') |
| 1174 | |
| 1175 | # cmp_contig() |
| 1176 | nd = ndarray([1], shape=[1]) |
| 1177 | self.assertRaises(TypeError, cmp_contig, 1, 2, 3, 4, 5) |
| 1178 | self.assertRaises(TypeError, cmp_contig, {}, nd) |
| 1179 | self.assertRaises(TypeError, cmp_contig, nd, {}) |
| 1180 | |
| 1181 | # is_contiguous() |
| 1182 | nd = ndarray([1], shape=[1]) |
| 1183 | self.assertRaises(TypeError, is_contiguous, 1, 2, 3, 4, 5) |
| 1184 | self.assertRaises(TypeError, is_contiguous, {}, 'A') |
| 1185 | self.assertRaises(TypeError, is_contiguous, nd, 201) |
| 1186 | |
| 1187 | def test_ndarray_linked_list(self): |
| 1188 | for perm in permutations(range(5)): |
| 1189 | m = [0]*5 |
| 1190 | nd = ndarray([1,2,3], shape=[3], flags=ND_VAREXPORT) |
| 1191 | m[0] = memoryview(nd) |
| 1192 | |
| 1193 | for i in range(1, 5): |
| 1194 | nd.push([1,2,3], shape=[3]) |
| 1195 | m[i] = memoryview(nd) |
| 1196 | |
| 1197 | for i in range(5): |
| 1198 | m[perm[i]].release() |
| 1199 | |
| 1200 | self.assertRaises(BufferError, nd.pop) |
| 1201 | del nd |
| 1202 | |
| 1203 | def test_ndarray_format_scalar(self): |
| 1204 | # ndim = 0: scalar |
| 1205 | for fmt, scalar, _ in iter_format(0): |
| 1206 | itemsize = struct.calcsize(fmt) |
| 1207 | nd = ndarray(scalar, shape=(), format=fmt) |
| 1208 | self.verify(nd, obj=None, |
| 1209 | itemsize=itemsize, fmt=fmt, readonly=1, |
| 1210 | ndim=0, shape=(), strides=(), |
| 1211 | lst=scalar) |
| 1212 | |
| 1213 | def test_ndarray_format_shape(self): |
| 1214 | # ndim = 1, shape = [n] |
| 1215 | nitems = randrange(1, 10) |
| 1216 | for fmt, items, _ in iter_format(nitems): |
| 1217 | itemsize = struct.calcsize(fmt) |
| 1218 | for flags in (0, ND_PIL): |
| 1219 | nd = ndarray(items, shape=[nitems], format=fmt, flags=flags) |
| 1220 | self.verify(nd, obj=None, |
| 1221 | itemsize=itemsize, fmt=fmt, readonly=1, |
| 1222 | ndim=1, shape=(nitems,), strides=(itemsize,), |
| 1223 | lst=items) |
| 1224 | |
| 1225 | def test_ndarray_format_strides(self): |
| 1226 | # ndim = 1, strides |
| 1227 | nitems = randrange(1, 30) |
| 1228 | for fmt, items, _ in iter_format(nitems): |
| 1229 | itemsize = struct.calcsize(fmt) |
| 1230 | for step in range(-5, 5): |
| 1231 | if step == 0: |
| 1232 | continue |
| 1233 | |
| 1234 | shape = [len(items[::step])] |
| 1235 | strides = [step*itemsize] |
| 1236 | offset = itemsize*(nitems-1) if step < 0 else 0 |
| 1237 | |
| 1238 | for flags in (0, ND_PIL): |
| 1239 | nd = ndarray(items, shape=shape, strides=strides, |
| 1240 | format=fmt, offset=offset, flags=flags) |
| 1241 | self.verify(nd, obj=None, |
| 1242 | itemsize=itemsize, fmt=fmt, readonly=1, |
| 1243 | ndim=1, shape=shape, strides=strides, |
| 1244 | lst=items[::step]) |
| 1245 | |
| 1246 | def test_ndarray_fortran(self): |
| 1247 | items = [1,2,3,4,5,6,7,8,9,10,11,12] |
| 1248 | ex = ndarray(items, shape=(3, 4), strides=(1, 3)) |
| 1249 | nd = ndarray(ex, getbuf=PyBUF_F_CONTIGUOUS|PyBUF_FORMAT) |
| 1250 | self.assertEqual(nd.tolist(), farray(items, (3, 4))) |
| 1251 | |
| 1252 | def test_ndarray_multidim(self): |
| 1253 | for ndim in range(5): |
| 1254 | shape_t = [randrange(2, 10) for _ in range(ndim)] |
| 1255 | nitems = prod(shape_t) |
| 1256 | for shape in permutations(shape_t): |
| 1257 | |
| 1258 | fmt, items, _ = randitems(nitems) |
| 1259 | itemsize = struct.calcsize(fmt) |
| 1260 | |
| 1261 | for flags in (0, ND_PIL): |
| 1262 | if ndim == 0 and flags == ND_PIL: |
| 1263 | continue |
| 1264 | |
| 1265 | # C array |
| 1266 | nd = ndarray(items, shape=shape, format=fmt, flags=flags) |
| 1267 | |
| 1268 | strides = strides_from_shape(ndim, shape, itemsize, 'C') |
| 1269 | lst = carray(items, shape) |
| 1270 | self.verify(nd, obj=None, |
| 1271 | itemsize=itemsize, fmt=fmt, readonly=1, |
| 1272 | ndim=ndim, shape=shape, strides=strides, |
| 1273 | lst=lst) |
| 1274 | |
| 1275 | if is_memoryview_format(fmt): |
| 1276 | # memoryview: reconstruct strides |
| 1277 | ex = ndarray(items, shape=shape, format=fmt) |
| 1278 | nd = ndarray(ex, getbuf=PyBUF_CONTIG_RO|PyBUF_FORMAT) |
| 1279 | self.assertTrue(nd.strides == ()) |
| 1280 | mv = nd.memoryview_from_buffer() |
| 1281 | self.verify(mv, obj=None, |
| 1282 | itemsize=itemsize, fmt=fmt, readonly=1, |
| 1283 | ndim=ndim, shape=shape, strides=strides, |
| 1284 | lst=lst) |
| 1285 | |
| 1286 | # Fortran array |
| 1287 | nd = ndarray(items, shape=shape, format=fmt, |
| 1288 | flags=flags|ND_FORTRAN) |
| 1289 | |
| 1290 | strides = strides_from_shape(ndim, shape, itemsize, 'F') |
| 1291 | lst = farray(items, shape) |
| 1292 | self.verify(nd, obj=None, |
| 1293 | itemsize=itemsize, fmt=fmt, readonly=1, |
| 1294 | ndim=ndim, shape=shape, strides=strides, |
| 1295 | lst=lst) |
| 1296 | |
| 1297 | def test_ndarray_index_invalid(self): |
| 1298 | # not writable |
| 1299 | nd = ndarray([1], shape=[1]) |
| 1300 | self.assertRaises(TypeError, nd.__setitem__, 1, 8) |
| 1301 | mv = memoryview(nd) |
| 1302 | self.assertEqual(mv, nd) |
| 1303 | self.assertRaises(TypeError, mv.__setitem__, 1, 8) |
| 1304 | |
| 1305 | # cannot be deleted |
| 1306 | nd = ndarray([1], shape=[1], flags=ND_WRITABLE) |
| 1307 | self.assertRaises(TypeError, nd.__delitem__, 1) |
| 1308 | mv = memoryview(nd) |
| 1309 | self.assertEqual(mv, nd) |
| 1310 | self.assertRaises(TypeError, mv.__delitem__, 1) |
| 1311 | |
| 1312 | # overflow |
| 1313 | nd = ndarray([1], shape=[1], flags=ND_WRITABLE) |
| 1314 | self.assertRaises(OverflowError, nd.__getitem__, 1<<64) |
| 1315 | self.assertRaises(OverflowError, nd.__setitem__, 1<<64, 8) |
| 1316 | mv = memoryview(nd) |
| 1317 | self.assertEqual(mv, nd) |
| 1318 | self.assertRaises(IndexError, mv.__getitem__, 1<<64) |
| 1319 | self.assertRaises(IndexError, mv.__setitem__, 1<<64, 8) |
| 1320 | |
| 1321 | # format |
| 1322 | items = [1,2,3,4,5,6,7,8] |
| 1323 | nd = ndarray(items, shape=[len(items)], format="B", flags=ND_WRITABLE) |
| 1324 | self.assertRaises(struct.error, nd.__setitem__, 2, 300) |
| 1325 | self.assertRaises(ValueError, nd.__setitem__, 1, (100, 200)) |
| 1326 | mv = memoryview(nd) |
| 1327 | self.assertEqual(mv, nd) |
| 1328 | self.assertRaises(ValueError, mv.__setitem__, 2, 300) |
| 1329 | self.assertRaises(TypeError, mv.__setitem__, 1, (100, 200)) |
| 1330 | |
| 1331 | items = [(1,2), (3,4), (5,6)] |
| 1332 | nd = ndarray(items, shape=[len(items)], format="LQ", flags=ND_WRITABLE) |
| 1333 | self.assertRaises(ValueError, nd.__setitem__, 2, 300) |
| 1334 | self.assertRaises(struct.error, nd.__setitem__, 1, (b'\x001', 200)) |
| 1335 | |
| 1336 | def test_ndarray_index_scalar(self): |
| 1337 | # scalar |
| 1338 | nd = ndarray(1, shape=(), flags=ND_WRITABLE) |
| 1339 | mv = memoryview(nd) |
| 1340 | self.assertEqual(mv, nd) |
| 1341 | |
| 1342 | x = nd[()]; self.assertEqual(x, 1) |
| 1343 | x = nd[...]; self.assertEqual(x.tolist(), nd.tolist()) |
| 1344 | |
| 1345 | x = mv[()]; self.assertEqual(x, 1) |
| 1346 | x = mv[...]; self.assertEqual(x.tolist(), nd.tolist()) |
| 1347 | |
| 1348 | self.assertRaises(TypeError, nd.__getitem__, 0) |
| 1349 | self.assertRaises(TypeError, mv.__getitem__, 0) |
| 1350 | self.assertRaises(TypeError, nd.__setitem__, 0, 8) |
| 1351 | self.assertRaises(TypeError, mv.__setitem__, 0, 8) |
| 1352 | |
| 1353 | self.assertEqual(nd.tolist(), 1) |
| 1354 | self.assertEqual(mv.tolist(), 1) |
| 1355 | |
| 1356 | nd[()] = 9; self.assertEqual(nd.tolist(), 9) |
| 1357 | mv[()] = 9; self.assertEqual(mv.tolist(), 9) |
| 1358 | |
| 1359 | nd[...] = 5; self.assertEqual(nd.tolist(), 5) |
| 1360 | mv[...] = 5; self.assertEqual(mv.tolist(), 5) |
| 1361 | |
| 1362 | def test_ndarray_index_null_strides(self): |
| 1363 | ex = ndarray(list(range(2*4)), shape=[2, 4], flags=ND_WRITABLE) |
| 1364 | nd = ndarray(ex, getbuf=PyBUF_CONTIG) |
| 1365 | |
| 1366 | # Sub-views are only possible for full exporters. |
| 1367 | self.assertRaises(BufferError, nd.__getitem__, 1) |
| 1368 | # Same for slices. |
| 1369 | self.assertRaises(BufferError, nd.__getitem__, slice(3,5,1)) |
| 1370 | |
| 1371 | def test_ndarray_index_getitem_single(self): |
| 1372 | # getitem |
| 1373 | for fmt, items, _ in iter_format(5): |
| 1374 | nd = ndarray(items, shape=[5], format=fmt) |
| 1375 | for i in range(-5, 5): |
| 1376 | self.assertEqual(nd[i], items[i]) |
| 1377 | |
| 1378 | self.assertRaises(IndexError, nd.__getitem__, -6) |
| 1379 | self.assertRaises(IndexError, nd.__getitem__, 5) |
| 1380 | |
| 1381 | if is_memoryview_format(fmt): |
| 1382 | mv = memoryview(nd) |
| 1383 | self.assertEqual(mv, nd) |
| 1384 | for i in range(-5, 5): |
| 1385 | self.assertEqual(mv[i], items[i]) |
| 1386 | |
| 1387 | self.assertRaises(IndexError, mv.__getitem__, -6) |
| 1388 | self.assertRaises(IndexError, mv.__getitem__, 5) |
| 1389 | |
| 1390 | # getitem with null strides |
| 1391 | for fmt, items, _ in iter_format(5): |
| 1392 | ex = ndarray(items, shape=[5], flags=ND_WRITABLE, format=fmt) |
| 1393 | nd = ndarray(ex, getbuf=PyBUF_CONTIG|PyBUF_FORMAT) |
| 1394 | |
| 1395 | for i in range(-5, 5): |
| 1396 | self.assertEqual(nd[i], items[i]) |
| 1397 | |
| 1398 | if is_memoryview_format(fmt): |
| 1399 | mv = nd.memoryview_from_buffer() |
| 1400 | self.assertIs(mv.__eq__(nd), NotImplemented) |
| 1401 | for i in range(-5, 5): |
| 1402 | self.assertEqual(mv[i], items[i]) |
| 1403 | |
| 1404 | # getitem with null format |
| 1405 | items = [1,2,3,4,5] |
| 1406 | ex = ndarray(items, shape=[5]) |
| 1407 | nd = ndarray(ex, getbuf=PyBUF_CONTIG_RO) |
| 1408 | for i in range(-5, 5): |
| 1409 | self.assertEqual(nd[i], items[i]) |
| 1410 | |
| 1411 | # getitem with null shape/strides/format |
| 1412 | items = [1,2,3,4,5] |
| 1413 | ex = ndarray(items, shape=[5]) |
| 1414 | nd = ndarray(ex, getbuf=PyBUF_SIMPLE) |
| 1415 | |
| 1416 | for i in range(-5, 5): |
| 1417 | self.assertEqual(nd[i], items[i]) |
| 1418 | |
| 1419 | def test_ndarray_index_setitem_single(self): |
| 1420 | # assign single value |
| 1421 | for fmt, items, single_item in iter_format(5): |
| 1422 | nd = ndarray(items, shape=[5], format=fmt, flags=ND_WRITABLE) |
| 1423 | for i in range(5): |
| 1424 | items[i] = single_item |
| 1425 | nd[i] = single_item |
| 1426 | self.assertEqual(nd.tolist(), items) |
| 1427 | |
| 1428 | self.assertRaises(IndexError, nd.__setitem__, -6, single_item) |
| 1429 | self.assertRaises(IndexError, nd.__setitem__, 5, single_item) |
| 1430 | |
| 1431 | if not is_memoryview_format(fmt): |
| 1432 | continue |
| 1433 | |
| 1434 | nd = ndarray(items, shape=[5], format=fmt, flags=ND_WRITABLE) |
| 1435 | mv = memoryview(nd) |
| 1436 | self.assertEqual(mv, nd) |
| 1437 | for i in range(5): |
| 1438 | items[i] = single_item |
| 1439 | mv[i] = single_item |
| 1440 | self.assertEqual(mv.tolist(), items) |
| 1441 | |
| 1442 | self.assertRaises(IndexError, mv.__setitem__, -6, single_item) |
| 1443 | self.assertRaises(IndexError, mv.__setitem__, 5, single_item) |
| 1444 | |
| 1445 | |
| 1446 | # assign single value: lobject = robject |
| 1447 | for fmt, items, single_item in iter_format(5): |
| 1448 | nd = ndarray(items, shape=[5], format=fmt, flags=ND_WRITABLE) |
| 1449 | for i in range(-5, 4): |
| 1450 | items[i] = items[i+1] |
| 1451 | nd[i] = nd[i+1] |
| 1452 | self.assertEqual(nd.tolist(), items) |
| 1453 | |
| 1454 | if not is_memoryview_format(fmt): |
| 1455 | continue |
| 1456 | |
| 1457 | nd = ndarray(items, shape=[5], format=fmt, flags=ND_WRITABLE) |
| 1458 | mv = memoryview(nd) |
| 1459 | self.assertEqual(mv, nd) |
| 1460 | for i in range(-5, 4): |
| 1461 | items[i] = items[i+1] |
| 1462 | mv[i] = mv[i+1] |
| 1463 | self.assertEqual(mv.tolist(), items) |
| 1464 | |
| 1465 | def test_ndarray_index_getitem_multidim(self): |
| 1466 | shape_t = (2, 3, 5) |
| 1467 | nitems = prod(shape_t) |
| 1468 | for shape in permutations(shape_t): |
| 1469 | |
| 1470 | fmt, items, _ = randitems(nitems) |
| 1471 | |
| 1472 | for flags in (0, ND_PIL): |
| 1473 | # C array |
| 1474 | nd = ndarray(items, shape=shape, format=fmt, flags=flags) |
| 1475 | lst = carray(items, shape) |
| 1476 | |
| 1477 | for i in range(-shape[0], shape[0]): |
| 1478 | self.assertEqual(lst[i], nd[i].tolist()) |
| 1479 | for j in range(-shape[1], shape[1]): |
| 1480 | self.assertEqual(lst[i][j], nd[i][j].tolist()) |
| 1481 | for k in range(-shape[2], shape[2]): |
| 1482 | self.assertEqual(lst[i][j][k], nd[i][j][k]) |
| 1483 | |
| 1484 | # Fortran array |
| 1485 | nd = ndarray(items, shape=shape, format=fmt, |
| 1486 | flags=flags|ND_FORTRAN) |
| 1487 | lst = farray(items, shape) |
| 1488 | |
| 1489 | for i in range(-shape[0], shape[0]): |
| 1490 | self.assertEqual(lst[i], nd[i].tolist()) |
| 1491 | for j in range(-shape[1], shape[1]): |
| 1492 | self.assertEqual(lst[i][j], nd[i][j].tolist()) |
| 1493 | for k in range(shape[2], shape[2]): |
| 1494 | self.assertEqual(lst[i][j][k], nd[i][j][k]) |
| 1495 | |
| 1496 | def test_ndarray_sequence(self): |
| 1497 | nd = ndarray(1, shape=()) |
| 1498 | self.assertRaises(TypeError, eval, "1 in nd", locals()) |
| 1499 | mv = memoryview(nd) |
| 1500 | self.assertEqual(mv, nd) |
| 1501 | self.assertRaises(TypeError, eval, "1 in mv", locals()) |
| 1502 | |
| 1503 | for fmt, items, _ in iter_format(5): |
| 1504 | nd = ndarray(items, shape=[5], format=fmt) |
| 1505 | for i, v in enumerate(nd): |
| 1506 | self.assertEqual(v, items[i]) |
| 1507 | self.assertTrue(v in nd) |
| 1508 | |
| 1509 | if is_memoryview_format(fmt): |
| 1510 | mv = memoryview(nd) |
| 1511 | for i, v in enumerate(mv): |
| 1512 | self.assertEqual(v, items[i]) |
| 1513 | self.assertTrue(v in mv) |
| 1514 | |
| 1515 | def test_ndarray_slice_invalid(self): |
| 1516 | items = [1,2,3,4,5,6,7,8] |
| 1517 | |
| 1518 | # rvalue is not an exporter |
| 1519 | xl = ndarray(items, shape=[8], flags=ND_WRITABLE) |
| 1520 | ml = memoryview(xl) |
| 1521 | self.assertRaises(TypeError, xl.__setitem__, slice(0,8,1), items) |
| 1522 | self.assertRaises(TypeError, ml.__setitem__, slice(0,8,1), items) |
| 1523 | |
| 1524 | # rvalue is not a full exporter |
| 1525 | xl = ndarray(items, shape=[8], flags=ND_WRITABLE) |
| 1526 | ex = ndarray(items, shape=[8], flags=ND_WRITABLE) |
| 1527 | xr = ndarray(ex, getbuf=PyBUF_ND) |
| 1528 | self.assertRaises(BufferError, xl.__setitem__, slice(0,8,1), xr) |
| 1529 | |
| 1530 | # zero step |
| 1531 | nd = ndarray(items, shape=[8], format="L", flags=ND_WRITABLE) |
| 1532 | mv = memoryview(nd) |
| 1533 | self.assertRaises(ValueError, nd.__getitem__, slice(0,1,0)) |
| 1534 | self.assertRaises(ValueError, mv.__getitem__, slice(0,1,0)) |
| 1535 | |
| 1536 | nd = ndarray(items, shape=[2,4], format="L", flags=ND_WRITABLE) |
| 1537 | mv = memoryview(nd) |
| 1538 | |
| 1539 | self.assertRaises(ValueError, nd.__getitem__, |
| 1540 | (slice(0,1,1), slice(0,1,0))) |
| 1541 | self.assertRaises(ValueError, nd.__getitem__, |
| 1542 | (slice(0,1,0), slice(0,1,1))) |
| 1543 | self.assertRaises(TypeError, nd.__getitem__, "@%$") |
| 1544 | self.assertRaises(TypeError, nd.__getitem__, ("@%$", slice(0,1,1))) |
| 1545 | self.assertRaises(TypeError, nd.__getitem__, (slice(0,1,1), {})) |
| 1546 | |
| 1547 | # memoryview: not implemented |
| 1548 | self.assertRaises(NotImplementedError, mv.__getitem__, |
| 1549 | (slice(0,1,1), slice(0,1,0))) |
| 1550 | self.assertRaises(TypeError, mv.__getitem__, "@%$") |
| 1551 | |
| 1552 | # differing format |
| 1553 | xl = ndarray(items, shape=[8], format="B", flags=ND_WRITABLE) |
| 1554 | xr = ndarray(items, shape=[8], format="b") |
| 1555 | ml = memoryview(xl) |
| 1556 | mr = memoryview(xr) |
| 1557 | self.assertRaises(ValueError, xl.__setitem__, slice(0,1,1), xr[7:8]) |
| 1558 | self.assertEqual(xl.tolist(), items) |
| 1559 | self.assertRaises(ValueError, ml.__setitem__, slice(0,1,1), mr[7:8]) |
| 1560 | self.assertEqual(ml.tolist(), items) |
| 1561 | |
| 1562 | # differing itemsize |
| 1563 | xl = ndarray(items, shape=[8], format="B", flags=ND_WRITABLE) |
| 1564 | yr = ndarray(items, shape=[8], format="L") |
| 1565 | ml = memoryview(xl) |
| 1566 | mr = memoryview(xr) |
| 1567 | self.assertRaises(ValueError, xl.__setitem__, slice(0,1,1), xr[7:8]) |
| 1568 | self.assertEqual(xl.tolist(), items) |
| 1569 | self.assertRaises(ValueError, ml.__setitem__, slice(0,1,1), mr[7:8]) |
| 1570 | self.assertEqual(ml.tolist(), items) |
| 1571 | |
| 1572 | # differing ndim |
| 1573 | xl = ndarray(items, shape=[2, 4], format="b", flags=ND_WRITABLE) |
| 1574 | xr = ndarray(items, shape=[8], format="b") |
| 1575 | ml = memoryview(xl) |
| 1576 | mr = memoryview(xr) |
| 1577 | self.assertRaises(ValueError, xl.__setitem__, slice(0,1,1), xr[7:8]) |
| 1578 | self.assertEqual(xl.tolist(), [[1,2,3,4], [5,6,7,8]]) |
| 1579 | self.assertRaises(NotImplementedError, ml.__setitem__, slice(0,1,1), |
| 1580 | mr[7:8]) |
| 1581 | |
| 1582 | # differing shape |
| 1583 | xl = ndarray(items, shape=[8], format="b", flags=ND_WRITABLE) |
| 1584 | xr = ndarray(items, shape=[8], format="b") |
| 1585 | ml = memoryview(xl) |
| 1586 | mr = memoryview(xr) |
| 1587 | self.assertRaises(ValueError, xl.__setitem__, slice(0,2,1), xr[7:8]) |
| 1588 | self.assertEqual(xl.tolist(), items) |
| 1589 | self.assertRaises(ValueError, ml.__setitem__, slice(0,2,1), mr[7:8]) |
| 1590 | self.assertEqual(ml.tolist(), items) |
| 1591 | |
| 1592 | # _testbuffer.c module functions |
| 1593 | self.assertRaises(TypeError, slice_indices, slice(0,1,2), {}) |
| 1594 | self.assertRaises(TypeError, slice_indices, "###########", 1) |
| 1595 | self.assertRaises(ValueError, slice_indices, slice(0,1,0), 4) |
| 1596 | |
| 1597 | x = ndarray(items, shape=[8], format="b", flags=ND_PIL) |
| 1598 | self.assertRaises(TypeError, x.add_suboffsets) |
| 1599 | |
| 1600 | ex = ndarray(items, shape=[8], format="B") |
| 1601 | x = ndarray(ex, getbuf=PyBUF_SIMPLE) |
| 1602 | self.assertRaises(TypeError, x.add_suboffsets) |
| 1603 | |
| 1604 | def test_ndarray_slice_zero_shape(self): |
| 1605 | items = [1,2,3,4,5,6,7,8,9,10,11,12] |
| 1606 | |
| 1607 | x = ndarray(items, shape=[12], format="L", flags=ND_WRITABLE) |
| 1608 | y = ndarray(items, shape=[12], format="L") |
| 1609 | x[4:4] = y[9:9] |
| 1610 | self.assertEqual(x.tolist(), items) |
| 1611 | |
| 1612 | ml = memoryview(x) |
| 1613 | mr = memoryview(y) |
| 1614 | self.assertEqual(ml, x) |
| 1615 | self.assertEqual(ml, y) |
| 1616 | ml[4:4] = mr[9:9] |
| 1617 | self.assertEqual(ml.tolist(), items) |
| 1618 | |
| 1619 | x = ndarray(items, shape=[3, 4], format="L", flags=ND_WRITABLE) |
| 1620 | y = ndarray(items, shape=[4, 3], format="L") |
| 1621 | x[1:2, 2:2] = y[1:2, 3:3] |
| 1622 | self.assertEqual(x.tolist(), carray(items, [3, 4])) |
| 1623 | |
| 1624 | def test_ndarray_slice_multidim(self): |
| 1625 | shape_t = (2, 3, 5) |
| 1626 | ndim = len(shape_t) |
| 1627 | nitems = prod(shape_t) |
| 1628 | for shape in permutations(shape_t): |
| 1629 | |
| 1630 | fmt, items, _ = randitems(nitems) |
| 1631 | itemsize = struct.calcsize(fmt) |
| 1632 | |
| 1633 | for flags in (0, ND_PIL): |
| 1634 | nd = ndarray(items, shape=shape, format=fmt, flags=flags) |
| 1635 | lst = carray(items, shape) |
| 1636 | |
| 1637 | for slices in rslices_ndim(ndim, shape): |
| 1638 | |
| 1639 | listerr = None |
| 1640 | try: |
| 1641 | sliced = multislice(lst, slices) |
| 1642 | except Exception as e: |
| 1643 | listerr = e.__class__ |
| 1644 | |
| 1645 | nderr = None |
| 1646 | try: |
| 1647 | ndsliced = nd[slices] |
| 1648 | except Exception as e: |
| 1649 | nderr = e.__class__ |
| 1650 | |
| 1651 | if nderr or listerr: |
| 1652 | self.assertIs(nderr, listerr) |
| 1653 | else: |
| 1654 | self.assertEqual(ndsliced.tolist(), sliced) |
| 1655 | |
| 1656 | def test_ndarray_slice_redundant_suboffsets(self): |
| 1657 | shape_t = (2, 3, 5, 2) |
| 1658 | ndim = len(shape_t) |
| 1659 | nitems = prod(shape_t) |
| 1660 | for shape in permutations(shape_t): |
| 1661 | |
| 1662 | fmt, items, _ = randitems(nitems) |
| 1663 | itemsize = struct.calcsize(fmt) |
| 1664 | |
| 1665 | nd = ndarray(items, shape=shape, format=fmt) |
| 1666 | nd.add_suboffsets() |
| 1667 | ex = ndarray(items, shape=shape, format=fmt) |
| 1668 | ex.add_suboffsets() |
| 1669 | mv = memoryview(ex) |
| 1670 | lst = carray(items, shape) |
| 1671 | |
| 1672 | for slices in rslices_ndim(ndim, shape): |
| 1673 | |
| 1674 | listerr = None |
| 1675 | try: |
| 1676 | sliced = multislice(lst, slices) |
| 1677 | except Exception as e: |
| 1678 | listerr = e.__class__ |
| 1679 | |
| 1680 | nderr = None |
| 1681 | try: |
| 1682 | ndsliced = nd[slices] |
| 1683 | except Exception as e: |
| 1684 | nderr = e.__class__ |
| 1685 | |
| 1686 | if nderr or listerr: |
| 1687 | self.assertIs(nderr, listerr) |
| 1688 | else: |
| 1689 | self.assertEqual(ndsliced.tolist(), sliced) |
| 1690 | |
| 1691 | def test_ndarray_slice_assign_single(self): |
| 1692 | for fmt, items, _ in iter_format(5): |
| 1693 | for lslice in genslices(5): |
| 1694 | for rslice in genslices(5): |
| 1695 | for flags in (0, ND_PIL): |
| 1696 | |
| 1697 | f = flags|ND_WRITABLE |
| 1698 | nd = ndarray(items, shape=[5], format=fmt, flags=f) |
| 1699 | ex = ndarray(items, shape=[5], format=fmt, flags=f) |
| 1700 | mv = memoryview(ex) |
| 1701 | |
| 1702 | lsterr = None |
| 1703 | diff_structure = None |
| 1704 | lst = items[:] |
| 1705 | try: |
| 1706 | lval = lst[lslice] |
| 1707 | rval = lst[rslice] |
| 1708 | lst[lslice] = lst[rslice] |
| 1709 | diff_structure = len(lval) != len(rval) |
| 1710 | except Exception as e: |
| 1711 | lsterr = e.__class__ |
| 1712 | |
| 1713 | nderr = None |
| 1714 | try: |
| 1715 | nd[lslice] = nd[rslice] |
| 1716 | except Exception as e: |
| 1717 | nderr = e.__class__ |
| 1718 | |
| 1719 | if diff_structure: # ndarray cannot change shape |
| 1720 | self.assertIs(nderr, ValueError) |
| 1721 | else: |
| 1722 | self.assertEqual(nd.tolist(), lst) |
| 1723 | self.assertIs(nderr, lsterr) |
| 1724 | |
| 1725 | if not is_memoryview_format(fmt): |
| 1726 | continue |
| 1727 | |
| 1728 | mverr = None |
| 1729 | try: |
| 1730 | mv[lslice] = mv[rslice] |
| 1731 | except Exception as e: |
| 1732 | mverr = e.__class__ |
| 1733 | |
| 1734 | if diff_structure: # memoryview cannot change shape |
| 1735 | self.assertIs(mverr, ValueError) |
| 1736 | else: |
| 1737 | self.assertEqual(mv.tolist(), lst) |
| 1738 | self.assertEqual(mv, nd) |
| 1739 | self.assertIs(mverr, lsterr) |
| 1740 | self.verify(mv, obj=ex, |
| 1741 | itemsize=nd.itemsize, fmt=fmt, readonly=0, |
| 1742 | ndim=nd.ndim, shape=nd.shape, strides=nd.strides, |
| 1743 | lst=nd.tolist()) |
| 1744 | |
| 1745 | def test_ndarray_slice_assign_multidim(self): |
| 1746 | shape_t = (2, 3, 5) |
| 1747 | ndim = len(shape_t) |
| 1748 | nitems = prod(shape_t) |
| 1749 | for shape in permutations(shape_t): |
| 1750 | |
| 1751 | fmt, items, _ = randitems(nitems) |
| 1752 | |
| 1753 | for flags in (0, ND_PIL): |
| 1754 | for _ in range(ITERATIONS): |
| 1755 | lslices, rslices = randslice_from_shape(ndim, shape) |
| 1756 | |
| 1757 | nd = ndarray(items, shape=shape, format=fmt, |
| 1758 | flags=flags|ND_WRITABLE) |
| 1759 | lst = carray(items, shape) |
| 1760 | |
| 1761 | listerr = None |
| 1762 | try: |
| 1763 | result = multislice_assign(lst, lst, lslices, rslices) |
| 1764 | except Exception as e: |
| 1765 | listerr = e.__class__ |
| 1766 | |
| 1767 | nderr = None |
| 1768 | try: |
| 1769 | nd[lslices] = nd[rslices] |
| 1770 | except Exception as e: |
| 1771 | nderr = e.__class__ |
| 1772 | |
| 1773 | if nderr or listerr: |
| 1774 | self.assertIs(nderr, listerr) |
| 1775 | else: |
| 1776 | self.assertEqual(nd.tolist(), result) |
| 1777 | |
| 1778 | def test_ndarray_random(self): |
| 1779 | # construction of valid arrays |
| 1780 | for _ in range(ITERATIONS): |
| 1781 | for fmt in fmtdict['@']: |
| 1782 | itemsize = struct.calcsize(fmt) |
| 1783 | |
| 1784 | t = rand_structure(itemsize, True, maxdim=MAXDIM, |
| 1785 | maxshape=MAXSHAPE) |
| 1786 | self.assertTrue(verify_structure(*t)) |
| 1787 | items = randitems_from_structure(fmt, t) |
| 1788 | |
| 1789 | x = ndarray_from_structure(items, fmt, t) |
| 1790 | xlist = x.tolist() |
| 1791 | |
| 1792 | mv = memoryview(x) |
| 1793 | if is_memoryview_format(fmt): |
| 1794 | mvlist = mv.tolist() |
| 1795 | self.assertEqual(mvlist, xlist) |
| 1796 | |
| 1797 | if t[2] > 0: |
| 1798 | # ndim > 0: test against suboffsets representation. |
| 1799 | y = ndarray_from_structure(items, fmt, t, flags=ND_PIL) |
| 1800 | ylist = y.tolist() |
| 1801 | self.assertEqual(xlist, ylist) |
| 1802 | |
| 1803 | mv = memoryview(y) |
| 1804 | if is_memoryview_format(fmt): |
| 1805 | self.assertEqual(mv, y) |
| 1806 | mvlist = mv.tolist() |
| 1807 | self.assertEqual(mvlist, ylist) |
| 1808 | |
| 1809 | if numpy_array: |
| 1810 | shape = t[3] |
| 1811 | if 0 in shape: |
| 1812 | continue # http://projects.scipy.org/numpy/ticket/1910 |
| 1813 | z = numpy_array_from_structure(items, fmt, t) |
| 1814 | self.verify(x, obj=None, |
| 1815 | itemsize=z.itemsize, fmt=fmt, readonly=0, |
| 1816 | ndim=z.ndim, shape=z.shape, strides=z.strides, |
| 1817 | lst=z.tolist()) |
| 1818 | |
| 1819 | def test_ndarray_random_invalid(self): |
| 1820 | # exceptions during construction of invalid arrays |
| 1821 | for _ in range(ITERATIONS): |
| 1822 | for fmt in fmtdict['@']: |
| 1823 | itemsize = struct.calcsize(fmt) |
| 1824 | |
| 1825 | t = rand_structure(itemsize, False, maxdim=MAXDIM, |
| 1826 | maxshape=MAXSHAPE) |
| 1827 | self.assertFalse(verify_structure(*t)) |
| 1828 | items = randitems_from_structure(fmt, t) |
| 1829 | |
| 1830 | nderr = False |
| 1831 | try: |
| 1832 | x = ndarray_from_structure(items, fmt, t) |
| 1833 | except Exception as e: |
| 1834 | nderr = e.__class__ |
| 1835 | self.assertTrue(nderr) |
| 1836 | |
| 1837 | if numpy_array: |
| 1838 | numpy_err = False |
| 1839 | try: |
| 1840 | y = numpy_array_from_structure(items, fmt, t) |
| 1841 | except Exception as e: |
| 1842 | numpy_err = e.__class__ |
| 1843 | |
| 1844 | if 0: # http://projects.scipy.org/numpy/ticket/1910 |
| 1845 | self.assertTrue(numpy_err) |
| 1846 | |
| 1847 | def test_ndarray_random_slice_assign(self): |
| 1848 | # valid slice assignments |
| 1849 | for _ in range(ITERATIONS): |
| 1850 | for fmt in fmtdict['@']: |
| 1851 | itemsize = struct.calcsize(fmt) |
| 1852 | |
| 1853 | lshape, rshape, lslices, rslices = \ |
| 1854 | rand_aligned_slices(maxdim=MAXDIM, maxshape=MAXSHAPE) |
| 1855 | tl = rand_structure(itemsize, True, shape=lshape) |
| 1856 | tr = rand_structure(itemsize, True, shape=rshape) |
| 1857 | self.assertTrue(verify_structure(*tl)) |
| 1858 | self.assertTrue(verify_structure(*tr)) |
| 1859 | litems = randitems_from_structure(fmt, tl) |
| 1860 | ritems = randitems_from_structure(fmt, tr) |
| 1861 | |
| 1862 | xl = ndarray_from_structure(litems, fmt, tl) |
| 1863 | xr = ndarray_from_structure(ritems, fmt, tr) |
| 1864 | xl[lslices] = xr[rslices] |
| 1865 | xllist = xl.tolist() |
| 1866 | xrlist = xr.tolist() |
| 1867 | |
| 1868 | ml = memoryview(xl) |
| 1869 | mr = memoryview(xr) |
| 1870 | self.assertEqual(ml.tolist(), xllist) |
| 1871 | self.assertEqual(mr.tolist(), xrlist) |
| 1872 | |
| 1873 | if tl[2] > 0 and tr[2] > 0: |
| 1874 | # ndim > 0: test against suboffsets representation. |
| 1875 | yl = ndarray_from_structure(litems, fmt, tl, flags=ND_PIL) |
| 1876 | yr = ndarray_from_structure(ritems, fmt, tr, flags=ND_PIL) |
| 1877 | yl[lslices] = yr[rslices] |
| 1878 | yllist = yl.tolist() |
| 1879 | yrlist = yr.tolist() |
| 1880 | self.assertEqual(xllist, yllist) |
| 1881 | self.assertEqual(xrlist, yrlist) |
| 1882 | |
| 1883 | ml = memoryview(yl) |
| 1884 | mr = memoryview(yr) |
| 1885 | self.assertEqual(ml.tolist(), yllist) |
| 1886 | self.assertEqual(mr.tolist(), yrlist) |
| 1887 | |
| 1888 | if numpy_array: |
| 1889 | if 0 in lshape or 0 in rshape: |
| 1890 | continue # http://projects.scipy.org/numpy/ticket/1910 |
| 1891 | |
| 1892 | zl = numpy_array_from_structure(litems, fmt, tl) |
| 1893 | zr = numpy_array_from_structure(ritems, fmt, tr) |
| 1894 | zl[lslices] = zr[rslices] |
| 1895 | |
| 1896 | if not is_overlapping(tl) and not is_overlapping(tr): |
| 1897 | # Slice assignment of overlapping structures |
| 1898 | # is undefined in NumPy. |
| 1899 | self.verify(xl, obj=None, |
| 1900 | itemsize=zl.itemsize, fmt=fmt, readonly=0, |
| 1901 | ndim=zl.ndim, shape=zl.shape, |
| 1902 | strides=zl.strides, lst=zl.tolist()) |
| 1903 | |
| 1904 | self.verify(xr, obj=None, |
| 1905 | itemsize=zr.itemsize, fmt=fmt, readonly=0, |
| 1906 | ndim=zr.ndim, shape=zr.shape, |
| 1907 | strides=zr.strides, lst=zr.tolist()) |
| 1908 | |
| 1909 | def test_ndarray_re_export(self): |
| 1910 | items = [1,2,3,4,5,6,7,8,9,10,11,12] |
| 1911 | |
| 1912 | nd = ndarray(items, shape=[3,4], flags=ND_PIL) |
| 1913 | ex = ndarray(nd) |
| 1914 | |
| 1915 | self.assertTrue(ex.flags & ND_PIL) |
| 1916 | self.assertIs(ex.obj, nd) |
| 1917 | self.assertEqual(ex.suboffsets, (0, -1)) |
| 1918 | self.assertFalse(ex.c_contiguous) |
| 1919 | self.assertFalse(ex.f_contiguous) |
| 1920 | self.assertFalse(ex.contiguous) |
| 1921 | |
| 1922 | def test_ndarray_zero_shape(self): |
| 1923 | # zeros in shape |
| 1924 | for flags in (0, ND_PIL): |
| 1925 | nd = ndarray([1,2,3], shape=[0], flags=flags) |
| 1926 | mv = memoryview(nd) |
| 1927 | self.assertEqual(mv, nd) |
| 1928 | self.assertEqual(nd.tolist(), []) |
| 1929 | self.assertEqual(mv.tolist(), []) |
| 1930 | |
| 1931 | nd = ndarray([1,2,3], shape=[0,3,3], flags=flags) |
| 1932 | self.assertEqual(nd.tolist(), []) |
| 1933 | |
| 1934 | nd = ndarray([1,2,3], shape=[3,0,3], flags=flags) |
| 1935 | self.assertEqual(nd.tolist(), [[], [], []]) |
| 1936 | |
| 1937 | nd = ndarray([1,2,3], shape=[3,3,0], flags=flags) |
| 1938 | self.assertEqual(nd.tolist(), |
| 1939 | [[[], [], []], [[], [], []], [[], [], []]]) |
| 1940 | |
| 1941 | def test_ndarray_zero_strides(self): |
| 1942 | # zero strides |
| 1943 | for flags in (0, ND_PIL): |
| 1944 | nd = ndarray([1], shape=[5], strides=[0], flags=flags) |
| 1945 | mv = memoryview(nd) |
| 1946 | self.assertEqual(mv, nd) |
| 1947 | self.assertEqual(nd.tolist(), [1, 1, 1, 1, 1]) |
| 1948 | self.assertEqual(mv.tolist(), [1, 1, 1, 1, 1]) |
| 1949 | |
| 1950 | def test_ndarray_offset(self): |
| 1951 | nd = ndarray(list(range(20)), shape=[3], offset=7) |
| 1952 | self.assertEqual(nd.offset, 7) |
| 1953 | self.assertEqual(nd.tolist(), [7,8,9]) |
| 1954 | |
| 1955 | def test_ndarray_memoryview_from_buffer(self): |
| 1956 | for flags in (0, ND_PIL): |
| 1957 | nd = ndarray(list(range(3)), shape=[3], flags=flags) |
| 1958 | m = nd.memoryview_from_buffer() |
| 1959 | self.assertEqual(m, nd) |
| 1960 | |
| 1961 | def test_ndarray_get_pointer(self): |
| 1962 | for flags in (0, ND_PIL): |
| 1963 | nd = ndarray(list(range(3)), shape=[3], flags=flags) |
| 1964 | for i in range(3): |
| 1965 | self.assertEqual(nd[i], get_pointer(nd, [i])) |
| 1966 | |
| 1967 | def test_ndarray_tolist_null_strides(self): |
| 1968 | ex = ndarray(list(range(20)), shape=[2,2,5]) |
| 1969 | |
| 1970 | nd = ndarray(ex, getbuf=PyBUF_ND|PyBUF_FORMAT) |
| 1971 | self.assertEqual(nd.tolist(), ex.tolist()) |
| 1972 | |
| 1973 | m = memoryview(ex) |
| 1974 | self.assertEqual(m.tolist(), ex.tolist()) |
| 1975 | |
| 1976 | def test_ndarray_cmp_contig(self): |
| 1977 | |
| 1978 | self.assertFalse(cmp_contig(b"123", b"456")) |
| 1979 | |
| 1980 | x = ndarray(list(range(12)), shape=[3,4]) |
| 1981 | y = ndarray(list(range(12)), shape=[4,3]) |
| 1982 | self.assertFalse(cmp_contig(x, y)) |
| 1983 | |
| 1984 | x = ndarray([1], shape=[1], format="B") |
| 1985 | self.assertTrue(cmp_contig(x, b'\x01')) |
| 1986 | self.assertTrue(cmp_contig(b'\x01', x)) |
| 1987 | |
| 1988 | def test_ndarray_hash(self): |
| 1989 | |
| 1990 | a = array.array('L', [1,2,3]) |
| 1991 | nd = ndarray(a) |
| 1992 | self.assertRaises(ValueError, hash, nd) |
| 1993 | |
| 1994 | # one-dimensional |
| 1995 | b = bytes(list(range(12))) |
| 1996 | |
| 1997 | nd = ndarray(list(range(12)), shape=[12]) |
| 1998 | self.assertEqual(hash(nd), hash(b)) |
| 1999 | |
| 2000 | # C-contiguous |
| 2001 | nd = ndarray(list(range(12)), shape=[3,4]) |
| 2002 | self.assertEqual(hash(nd), hash(b)) |
| 2003 | |
| 2004 | nd = ndarray(list(range(12)), shape=[3,2,2]) |
| 2005 | self.assertEqual(hash(nd), hash(b)) |
| 2006 | |
| 2007 | # Fortran contiguous |
| 2008 | b = bytes(transpose(list(range(12)), shape=[4,3])) |
| 2009 | nd = ndarray(list(range(12)), shape=[3,4], flags=ND_FORTRAN) |
| 2010 | self.assertEqual(hash(nd), hash(b)) |
| 2011 | |
| 2012 | b = bytes(transpose(list(range(12)), shape=[2,3,2])) |
| 2013 | nd = ndarray(list(range(12)), shape=[2,3,2], flags=ND_FORTRAN) |
| 2014 | self.assertEqual(hash(nd), hash(b)) |
| 2015 | |
| 2016 | # suboffsets |
| 2017 | b = bytes(list(range(12))) |
| 2018 | nd = ndarray(list(range(12)), shape=[2,2,3], flags=ND_PIL) |
| 2019 | self.assertEqual(hash(nd), hash(b)) |
| 2020 | |
| 2021 | # non-byte formats |
| 2022 | nd = ndarray(list(range(12)), shape=[2,2,3], format='L') |
| 2023 | self.assertEqual(hash(nd), hash(nd.tobytes())) |
| 2024 | |
| 2025 | def test_memoryview_construction(self): |
| 2026 | |
| 2027 | items_shape = [(9, []), ([1,2,3], [3]), (list(range(2*3*5)), [2,3,5])] |
| 2028 | |
| 2029 | # NumPy style, C-contiguous: |
| 2030 | for items, shape in items_shape: |
| 2031 | |
| 2032 | # From PEP-3118 compliant exporter: |
| 2033 | ex = ndarray(items, shape=shape) |
| 2034 | m = memoryview(ex) |
| 2035 | self.assertTrue(m.c_contiguous) |
| 2036 | self.assertTrue(m.contiguous) |
| 2037 | |
| 2038 | ndim = len(shape) |
| 2039 | strides = strides_from_shape(ndim, shape, 1, 'C') |
| 2040 | lst = carray(items, shape) |
| 2041 | |
| 2042 | self.verify(m, obj=ex, |
| 2043 | itemsize=1, fmt='B', readonly=1, |
| 2044 | ndim=ndim, shape=shape, strides=strides, |
| 2045 | lst=lst) |
| 2046 | |
| 2047 | # From memoryview: |
| 2048 | m2 = memoryview(m) |
| 2049 | self.verify(m2, obj=ex, |
| 2050 | itemsize=1, fmt='B', readonly=1, |
| 2051 | ndim=ndim, shape=shape, strides=strides, |
| 2052 | lst=lst) |
| 2053 | |
| 2054 | # PyMemoryView_FromBuffer(): no strides |
| 2055 | nd = ndarray(ex, getbuf=PyBUF_CONTIG_RO|PyBUF_FORMAT) |
| 2056 | self.assertEqual(nd.strides, ()) |
| 2057 | m = nd.memoryview_from_buffer() |
| 2058 | self.verify(m, obj=None, |
| 2059 | itemsize=1, fmt='B', readonly=1, |
| 2060 | ndim=ndim, shape=shape, strides=strides, |
| 2061 | lst=lst) |
| 2062 | |
| 2063 | # PyMemoryView_FromBuffer(): no format, shape, strides |
| 2064 | nd = ndarray(ex, getbuf=PyBUF_SIMPLE) |
| 2065 | self.assertEqual(nd.format, '') |
| 2066 | self.assertEqual(nd.shape, ()) |
| 2067 | self.assertEqual(nd.strides, ()) |
| 2068 | m = nd.memoryview_from_buffer() |
| 2069 | |
| 2070 | lst = [items] if ndim == 0 else items |
| 2071 | self.verify(m, obj=None, |
| 2072 | itemsize=1, fmt='B', readonly=1, |
| 2073 | ndim=1, shape=[ex.nbytes], strides=(1,), |
| 2074 | lst=lst) |
| 2075 | |
| 2076 | # NumPy style, Fortran contiguous: |
| 2077 | for items, shape in items_shape: |
| 2078 | |
| 2079 | # From PEP-3118 compliant exporter: |
| 2080 | ex = ndarray(items, shape=shape, flags=ND_FORTRAN) |
| 2081 | m = memoryview(ex) |
| 2082 | self.assertTrue(m.f_contiguous) |
| 2083 | self.assertTrue(m.contiguous) |
| 2084 | |
| 2085 | ndim = len(shape) |
| 2086 | strides = strides_from_shape(ndim, shape, 1, 'F') |
| 2087 | lst = farray(items, shape) |
| 2088 | |
| 2089 | self.verify(m, obj=ex, |
| 2090 | itemsize=1, fmt='B', readonly=1, |
| 2091 | ndim=ndim, shape=shape, strides=strides, |
| 2092 | lst=lst) |
| 2093 | |
| 2094 | # From memoryview: |
| 2095 | m2 = memoryview(m) |
| 2096 | self.verify(m2, obj=ex, |
| 2097 | itemsize=1, fmt='B', readonly=1, |
| 2098 | ndim=ndim, shape=shape, strides=strides, |
| 2099 | lst=lst) |
| 2100 | |
| 2101 | # PIL style: |
| 2102 | for items, shape in items_shape[1:]: |
| 2103 | |
| 2104 | # From PEP-3118 compliant exporter: |
| 2105 | ex = ndarray(items, shape=shape, flags=ND_PIL) |
| 2106 | m = memoryview(ex) |
| 2107 | |
| 2108 | ndim = len(shape) |
| 2109 | lst = carray(items, shape) |
| 2110 | |
| 2111 | self.verify(m, obj=ex, |
| 2112 | itemsize=1, fmt='B', readonly=1, |
| 2113 | ndim=ndim, shape=shape, strides=ex.strides, |
| 2114 | lst=lst) |
| 2115 | |
| 2116 | # From memoryview: |
| 2117 | m2 = memoryview(m) |
| 2118 | self.verify(m2, obj=ex, |
| 2119 | itemsize=1, fmt='B', readonly=1, |
| 2120 | ndim=ndim, shape=shape, strides=ex.strides, |
| 2121 | lst=lst) |
| 2122 | |
| 2123 | # Invalid number of arguments: |
| 2124 | self.assertRaises(TypeError, memoryview, b'9', 'x') |
| 2125 | # Not a buffer provider: |
| 2126 | self.assertRaises(TypeError, memoryview, {}) |
| 2127 | # Non-compliant buffer provider: |
| 2128 | ex = ndarray([1,2,3], shape=[3]) |
| 2129 | nd = ndarray(ex, getbuf=PyBUF_SIMPLE) |
| 2130 | self.assertRaises(BufferError, memoryview, nd) |
| 2131 | nd = ndarray(ex, getbuf=PyBUF_CONTIG_RO|PyBUF_FORMAT) |
| 2132 | self.assertRaises(BufferError, memoryview, nd) |
| 2133 | |
| 2134 | # ndim > 64 |
| 2135 | nd = ndarray([1]*128, shape=[1]*128, format='L') |
| 2136 | self.assertRaises(ValueError, memoryview, nd) |
| 2137 | self.assertRaises(ValueError, nd.memoryview_from_buffer) |
| 2138 | self.assertRaises(ValueError, get_contiguous, nd, PyBUF_READ, 'C') |
| 2139 | self.assertRaises(ValueError, get_contiguous, nd, PyBUF_READ, 'F') |
| 2140 | self.assertRaises(ValueError, get_contiguous, nd[::-1], PyBUF_READ, 'C') |
| 2141 | |
| 2142 | def test_memoryview_cast_zero_shape(self): |
| 2143 | # Casts are undefined if shape contains zeros. These arrays are |
| 2144 | # regarded as C-contiguous by Numpy and PyBuffer_GetContiguous(), |
| 2145 | # so they are not caught by the test for C-contiguity in memory_cast(). |
| 2146 | items = [1,2,3] |
| 2147 | for shape in ([0,3,3], [3,0,3], [0,3,3]): |
| 2148 | ex = ndarray(items, shape=shape) |
| 2149 | self.assertTrue(ex.c_contiguous) |
| 2150 | msrc = memoryview(ex) |
| 2151 | self.assertRaises(TypeError, msrc.cast, 'c') |
| 2152 | |
| 2153 | def test_memoryview_struct_module(self): |
| 2154 | |
| 2155 | class INT(object): |
| 2156 | def __init__(self, val): |
| 2157 | self.val = val |
| 2158 | def __int__(self): |
| 2159 | return self.val |
| 2160 | |
| 2161 | class IDX(object): |
| 2162 | def __init__(self, val): |
| 2163 | self.val = val |
| 2164 | def __index__(self): |
| 2165 | return self.val |
| 2166 | |
| 2167 | def f(): return 7 |
| 2168 | |
| 2169 | values = [INT(9), IDX(9), |
| 2170 | 2.2+3j, Decimal("-21.1"), 12.2, Fraction(5, 2), |
| 2171 | [1,2,3], {4,5,6}, {7:8}, (), (9,), |
| 2172 | True, False, None, NotImplemented, |
| 2173 | b'a', b'abc', bytearray(b'a'), bytearray(b'abc'), |
| 2174 | 'a', 'abc', r'a', r'abc', |
| 2175 | f, lambda x: x] |
| 2176 | |
| 2177 | for fmt, items, item in iter_format(10, 'memoryview'): |
| 2178 | ex = ndarray(items, shape=[10], format=fmt, flags=ND_WRITABLE) |
| 2179 | nd = ndarray(items, shape=[10], format=fmt, flags=ND_WRITABLE) |
| 2180 | m = memoryview(ex) |
| 2181 | |
| 2182 | struct.pack_into(fmt, nd, 0, item) |
| 2183 | m[0] = item |
| 2184 | self.assertEqual(m[0], nd[0]) |
| 2185 | |
| 2186 | itemsize = struct.calcsize(fmt) |
| 2187 | if 'P' in fmt: |
| 2188 | continue |
| 2189 | |
| 2190 | for v in values: |
| 2191 | struct_err = None |
| 2192 | try: |
| 2193 | struct.pack_into(fmt, nd, itemsize, v) |
| 2194 | except struct.error: |
| 2195 | struct_err = struct.error |
| 2196 | |
| 2197 | mv_err = None |
| 2198 | try: |
| 2199 | m[1] = v |
| 2200 | except (TypeError, ValueError) as e: |
| 2201 | mv_err = e.__class__ |
| 2202 | |
| 2203 | if struct_err or mv_err: |
| 2204 | self.assertIsNot(struct_err, None) |
| 2205 | self.assertIsNot(mv_err, None) |
| 2206 | else: |
| 2207 | self.assertEqual(m[1], nd[1]) |
| 2208 | |
| 2209 | def test_memoryview_cast_zero_strides(self): |
| 2210 | # Casts are undefined if strides contains zeros. These arrays are |
| 2211 | # (sometimes!) regarded as C-contiguous by Numpy, but not by |
| 2212 | # PyBuffer_GetContiguous(). |
| 2213 | ex = ndarray([1,2,3], shape=[3], strides=[0]) |
| 2214 | self.assertFalse(ex.c_contiguous) |
| 2215 | msrc = memoryview(ex) |
| 2216 | self.assertRaises(TypeError, msrc.cast, 'c') |
| 2217 | |
| 2218 | def test_memoryview_cast_invalid(self): |
| 2219 | # invalid format |
| 2220 | for sfmt in NON_BYTE_FORMAT: |
| 2221 | sformat = '@' + sfmt if randrange(2) else sfmt |
| 2222 | ssize = struct.calcsize(sformat) |
| 2223 | for dfmt in NON_BYTE_FORMAT: |
| 2224 | dformat = '@' + dfmt if randrange(2) else dfmt |
| 2225 | dsize = struct.calcsize(dformat) |
| 2226 | ex = ndarray(list(range(32)), shape=[32//ssize], format=sformat) |
| 2227 | msrc = memoryview(ex) |
| 2228 | self.assertRaises(TypeError, msrc.cast, dfmt, [32//dsize]) |
| 2229 | |
| 2230 | for sfmt, sitems, _ in iter_format(1): |
| 2231 | ex = ndarray(sitems, shape=[1], format=sfmt) |
| 2232 | msrc = memoryview(ex) |
| 2233 | for dfmt, _, _ in iter_format(1): |
| 2234 | if (not is_memoryview_format(sfmt) or |
| 2235 | not is_memoryview_format(dfmt)): |
| 2236 | self.assertRaises(ValueError, msrc.cast, dfmt, |
| 2237 | [32//dsize]) |
| 2238 | else: |
| 2239 | if not is_byte_format(sfmt) and not is_byte_format(dfmt): |
| 2240 | self.assertRaises(TypeError, msrc.cast, dfmt, |
| 2241 | [32//dsize]) |
| 2242 | |
| 2243 | # invalid shape |
| 2244 | size_h = struct.calcsize('h') |
| 2245 | size_d = struct.calcsize('d') |
| 2246 | ex = ndarray(list(range(2*2*size_d)), shape=[2,2,size_d], format='h') |
| 2247 | msrc = memoryview(ex) |
| 2248 | self.assertRaises(TypeError, msrc.cast, shape=[2,2,size_h], format='d') |
| 2249 | |
| 2250 | ex = ndarray(list(range(120)), shape=[1,2,3,4,5]) |
| 2251 | m = memoryview(ex) |
| 2252 | |
| 2253 | # incorrect number of args |
| 2254 | self.assertRaises(TypeError, m.cast) |
| 2255 | self.assertRaises(TypeError, m.cast, 1, 2, 3) |
| 2256 | |
| 2257 | # incorrect dest format type |
| 2258 | self.assertRaises(TypeError, m.cast, {}) |
| 2259 | |
| 2260 | # incorrect dest format |
| 2261 | self.assertRaises(ValueError, m.cast, "X") |
| 2262 | self.assertRaises(ValueError, m.cast, "@X") |
| 2263 | self.assertRaises(ValueError, m.cast, "@XY") |
| 2264 | |
| 2265 | # dest format not implemented |
| 2266 | self.assertRaises(ValueError, m.cast, "=B") |
| 2267 | self.assertRaises(ValueError, m.cast, "!L") |
| 2268 | self.assertRaises(ValueError, m.cast, "<P") |
| 2269 | self.assertRaises(ValueError, m.cast, ">l") |
| 2270 | self.assertRaises(ValueError, m.cast, "BI") |
| 2271 | self.assertRaises(ValueError, m.cast, "xBI") |
| 2272 | |
| 2273 | # src format not implemented |
| 2274 | ex = ndarray([(1,2), (3,4)], shape=[2], format="II") |
| 2275 | m = memoryview(ex) |
| 2276 | self.assertRaises(NotImplementedError, m.__getitem__, 0) |
| 2277 | self.assertRaises(NotImplementedError, m.__setitem__, 0, 8) |
| 2278 | self.assertRaises(NotImplementedError, m.tolist) |
| 2279 | |
| 2280 | # incorrect shape type |
| 2281 | ex = ndarray(list(range(120)), shape=[1,2,3,4,5]) |
| 2282 | m = memoryview(ex) |
| 2283 | self.assertRaises(TypeError, m.cast, "B", shape={}) |
| 2284 | |
| 2285 | # incorrect shape elements |
| 2286 | ex = ndarray(list(range(120)), shape=[2*3*4*5]) |
| 2287 | m = memoryview(ex) |
| 2288 | self.assertRaises(OverflowError, m.cast, "B", shape=[2**64]) |
| 2289 | self.assertRaises(ValueError, m.cast, "B", shape=[-1]) |
| 2290 | self.assertRaises(ValueError, m.cast, "B", shape=[2,3,4,5,6,7,-1]) |
| 2291 | self.assertRaises(ValueError, m.cast, "B", shape=[2,3,4,5,6,7,0]) |
| 2292 | self.assertRaises(TypeError, m.cast, "B", shape=[2,3,4,5,6,7,'x']) |
| 2293 | |
| 2294 | # N-D -> N-D cast |
| 2295 | ex = ndarray(list([9 for _ in range(3*5*7*11)]), shape=[3,5,7,11]) |
| 2296 | m = memoryview(ex) |
| 2297 | self.assertRaises(TypeError, m.cast, "I", shape=[2,3,4,5]) |
| 2298 | |
| 2299 | # cast with ndim > 64 |
| 2300 | nd = ndarray(list(range(128)), shape=[128], format='I') |
| 2301 | m = memoryview(nd) |
| 2302 | self.assertRaises(ValueError, m.cast, 'I', [1]*128) |
| 2303 | |
| 2304 | # view->len not a multiple of itemsize |
| 2305 | ex = ndarray(list([9 for _ in range(3*5*7*11)]), shape=[3*5*7*11]) |
| 2306 | m = memoryview(ex) |
| 2307 | self.assertRaises(TypeError, m.cast, "I", shape=[2,3,4,5]) |
| 2308 | |
| 2309 | # product(shape) * itemsize != buffer size |
| 2310 | ex = ndarray(list([9 for _ in range(3*5*7*11)]), shape=[3*5*7*11]) |
| 2311 | m = memoryview(ex) |
| 2312 | self.assertRaises(TypeError, m.cast, "B", shape=[2,3,4,5]) |
| 2313 | |
| 2314 | # product(shape) * itemsize overflow |
| 2315 | nd = ndarray(list(range(128)), shape=[128], format='I') |
| 2316 | m1 = memoryview(nd) |
| 2317 | nd = ndarray(list(range(128)), shape=[128], format='B') |
| 2318 | m2 = memoryview(nd) |
| 2319 | if sys.maxsize == 2**63-1: |
| 2320 | self.assertRaises(TypeError, m1.cast, 'B', |
| 2321 | [7, 7, 73, 127, 337, 92737, 649657]) |
| 2322 | self.assertRaises(ValueError, m1.cast, 'B', |
| 2323 | [2**20, 2**20, 2**10, 2**10, 2**3]) |
| 2324 | self.assertRaises(ValueError, m2.cast, 'I', |
| 2325 | [2**20, 2**20, 2**10, 2**10, 2**1]) |
| 2326 | else: |
| 2327 | self.assertRaises(TypeError, m1.cast, 'B', |
| 2328 | [1, 2147483647]) |
| 2329 | self.assertRaises(ValueError, m1.cast, 'B', |
| 2330 | [2**10, 2**10, 2**5, 2**5, 2**1]) |
| 2331 | self.assertRaises(ValueError, m2.cast, 'I', |
| 2332 | [2**10, 2**10, 2**5, 2**3, 2**1]) |
| 2333 | |
| 2334 | def test_memoryview_cast(self): |
| 2335 | bytespec = ( |
| 2336 | ('B', lambda ex: list(ex.tobytes())), |
| 2337 | ('b', lambda ex: [x-256 if x > 127 else x for x in list(ex.tobytes())]), |
| 2338 | ('c', lambda ex: [bytes(chr(x), 'latin-1') for x in list(ex.tobytes())]), |
| 2339 | ) |
| 2340 | |
| 2341 | def iter_roundtrip(ex, m, items, fmt): |
| 2342 | srcsize = struct.calcsize(fmt) |
| 2343 | for bytefmt, to_bytelist in bytespec: |
| 2344 | |
| 2345 | m2 = m.cast(bytefmt) |
| 2346 | lst = to_bytelist(ex) |
| 2347 | self.verify(m2, obj=ex, |
| 2348 | itemsize=1, fmt=bytefmt, readonly=0, |
| 2349 | ndim=1, shape=[31*srcsize], strides=(1,), |
| 2350 | lst=lst, cast=True) |
| 2351 | |
| 2352 | m3 = m2.cast(fmt) |
| 2353 | self.assertEqual(m3, ex) |
| 2354 | lst = ex.tolist() |
| 2355 | self.verify(m3, obj=ex, |
| 2356 | itemsize=srcsize, fmt=fmt, readonly=0, |
| 2357 | ndim=1, shape=[31], strides=(srcsize,), |
| 2358 | lst=lst, cast=True) |
| 2359 | |
| 2360 | # cast from ndim = 0 to ndim = 1 |
| 2361 | srcsize = struct.calcsize('I') |
| 2362 | ex = ndarray(9, shape=[], format='I') |
| 2363 | destitems, destshape = cast_items(ex, 'B', 1) |
| 2364 | m = memoryview(ex) |
| 2365 | m2 = m.cast('B') |
| 2366 | self.verify(m2, obj=ex, |
| 2367 | itemsize=1, fmt='B', readonly=1, |
| 2368 | ndim=1, shape=destshape, strides=(1,), |
| 2369 | lst=destitems, cast=True) |
| 2370 | |
| 2371 | # cast from ndim = 1 to ndim = 0 |
| 2372 | destsize = struct.calcsize('I') |
| 2373 | ex = ndarray([9]*destsize, shape=[destsize], format='B') |
| 2374 | destitems, destshape = cast_items(ex, 'I', destsize, shape=[]) |
| 2375 | m = memoryview(ex) |
| 2376 | m2 = m.cast('I', shape=[]) |
| 2377 | self.verify(m2, obj=ex, |
| 2378 | itemsize=destsize, fmt='I', readonly=1, |
| 2379 | ndim=0, shape=(), strides=(), |
| 2380 | lst=destitems, cast=True) |
| 2381 | |
| 2382 | # array.array: roundtrip to/from bytes |
| 2383 | for fmt, items, _ in iter_format(31, 'array'): |
| 2384 | ex = array.array(fmt, items) |
| 2385 | m = memoryview(ex) |
| 2386 | iter_roundtrip(ex, m, items, fmt) |
| 2387 | |
| 2388 | # ndarray: roundtrip to/from bytes |
| 2389 | for fmt, items, _ in iter_format(31, 'memoryview'): |
| 2390 | ex = ndarray(items, shape=[31], format=fmt, flags=ND_WRITABLE) |
| 2391 | m = memoryview(ex) |
| 2392 | iter_roundtrip(ex, m, items, fmt) |
| 2393 | |
| 2394 | def test_memoryview_cast_1D_ND(self): |
| 2395 | # Cast between C-contiguous buffers. At least one buffer must |
| 2396 | # be 1D, at least one format must be 'c', 'b' or 'B'. |
| 2397 | for _tshape in gencastshapes(): |
| 2398 | for char in fmtdict['@']: |
| 2399 | tfmt = ('', '@')[randrange(2)] + char |
| 2400 | tsize = struct.calcsize(tfmt) |
| 2401 | n = prod(_tshape) * tsize |
| 2402 | obj = 'memoryview' if is_byte_format(tfmt) else 'bytefmt' |
| 2403 | for fmt, items, _ in iter_format(n, obj): |
| 2404 | size = struct.calcsize(fmt) |
| 2405 | shape = [n] if n > 0 else [] |
| 2406 | tshape = _tshape + [size] |
| 2407 | |
| 2408 | ex = ndarray(items, shape=shape, format=fmt) |
| 2409 | m = memoryview(ex) |
| 2410 | |
| 2411 | titems, tshape = cast_items(ex, tfmt, tsize, shape=tshape) |
| 2412 | |
| 2413 | if titems is None: |
| 2414 | self.assertRaises(TypeError, m.cast, tfmt, tshape) |
| 2415 | continue |
| 2416 | if titems == 'nan': |
| 2417 | continue # NaNs in lists are a recipe for trouble. |
| 2418 | |
| 2419 | # 1D -> ND |
| 2420 | nd = ndarray(titems, shape=tshape, format=tfmt) |
| 2421 | |
| 2422 | m2 = m.cast(tfmt, shape=tshape) |
| 2423 | ndim = len(tshape) |
| 2424 | strides = nd.strides |
| 2425 | lst = nd.tolist() |
| 2426 | self.verify(m2, obj=ex, |
| 2427 | itemsize=tsize, fmt=tfmt, readonly=1, |
| 2428 | ndim=ndim, shape=tshape, strides=strides, |
| 2429 | lst=lst, cast=True) |
| 2430 | |
| 2431 | # ND -> 1D |
| 2432 | m3 = m2.cast(fmt) |
| 2433 | m4 = m2.cast(fmt, shape=shape) |
| 2434 | ndim = len(shape) |
| 2435 | strides = ex.strides |
| 2436 | lst = ex.tolist() |
| 2437 | |
| 2438 | self.verify(m3, obj=ex, |
| 2439 | itemsize=size, fmt=fmt, readonly=1, |
| 2440 | ndim=ndim, shape=shape, strides=strides, |
| 2441 | lst=lst, cast=True) |
| 2442 | |
| 2443 | self.verify(m4, obj=ex, |
| 2444 | itemsize=size, fmt=fmt, readonly=1, |
| 2445 | ndim=ndim, shape=shape, strides=strides, |
| 2446 | lst=lst, cast=True) |
| 2447 | |
| 2448 | def test_memoryview_tolist(self): |
| 2449 | |
| 2450 | # Most tolist() tests are in self.verify() etc. |
| 2451 | |
| 2452 | a = array.array('h', list(range(-6, 6))) |
| 2453 | m = memoryview(a) |
| 2454 | self.assertEqual(m, a) |
| 2455 | self.assertEqual(m.tolist(), a.tolist()) |
| 2456 | |
| 2457 | a = a[2::3] |
| 2458 | m = m[2::3] |
| 2459 | self.assertEqual(m, a) |
| 2460 | self.assertEqual(m.tolist(), a.tolist()) |
| 2461 | |
| 2462 | ex = ndarray(list(range(2*3*5*7*11)), shape=[11,2,7,3,5], format='L') |
| 2463 | m = memoryview(ex) |
| 2464 | self.assertEqual(m.tolist(), ex.tolist()) |
| 2465 | |
| 2466 | ex = ndarray([(2, 5), (7, 11)], shape=[2], format='lh') |
| 2467 | m = memoryview(ex) |
| 2468 | self.assertRaises(NotImplementedError, m.tolist) |
| 2469 | |
| 2470 | ex = ndarray([b'12345'], shape=[1], format="s") |
| 2471 | m = memoryview(ex) |
| 2472 | self.assertRaises(NotImplementedError, m.tolist) |
| 2473 | |
| 2474 | ex = ndarray([b"a",b"b",b"c",b"d",b"e",b"f"], shape=[2,3], format='s') |
| 2475 | m = memoryview(ex) |
| 2476 | self.assertRaises(NotImplementedError, m.tolist) |
| 2477 | |
| 2478 | def test_memoryview_repr(self): |
| 2479 | m = memoryview(bytearray(9)) |
| 2480 | r = m.__repr__() |
| 2481 | self.assertTrue(r.startswith("<memory")) |
| 2482 | |
| 2483 | m.release() |
| 2484 | r = m.__repr__() |
| 2485 | self.assertTrue(r.startswith("<released")) |
| 2486 | |
| 2487 | def test_memoryview_sequence(self): |
| 2488 | |
| 2489 | for fmt in ('d', 'f'): |
| 2490 | inf = float(3e400) |
| 2491 | ex = array.array(fmt, [1.0, inf, 3.0]) |
| 2492 | m = memoryview(ex) |
| 2493 | self.assertIn(1.0, m) |
| 2494 | self.assertIn(5e700, m) |
| 2495 | self.assertIn(3.0, m) |
| 2496 | |
| 2497 | ex = ndarray(9.0, [], format='f') |
| 2498 | m = memoryview(ex) |
| 2499 | self.assertRaises(TypeError, eval, "9.0 in m", locals()) |
| 2500 | |
| 2501 | def test_memoryview_index(self): |
| 2502 | |
| 2503 | # ndim = 0 |
| 2504 | ex = ndarray(12.5, shape=[], format='d') |
| 2505 | m = memoryview(ex) |
| 2506 | self.assertEqual(m[()], 12.5) |
| 2507 | self.assertEqual(m[...], m) |
| 2508 | self.assertEqual(m[...], ex) |
| 2509 | self.assertRaises(TypeError, m.__getitem__, 0) |
| 2510 | |
| 2511 | ex = ndarray((1,2,3), shape=[], format='iii') |
| 2512 | m = memoryview(ex) |
| 2513 | self.assertRaises(NotImplementedError, m.__getitem__, ()) |
| 2514 | |
| 2515 | # range |
| 2516 | ex = ndarray(list(range(7)), shape=[7], flags=ND_WRITABLE) |
| 2517 | m = memoryview(ex) |
| 2518 | |
| 2519 | self.assertRaises(IndexError, m.__getitem__, 2**64) |
| 2520 | self.assertRaises(TypeError, m.__getitem__, 2.0) |
| 2521 | self.assertRaises(TypeError, m.__getitem__, 0.0) |
| 2522 | |
| 2523 | # out of bounds |
| 2524 | self.assertRaises(IndexError, m.__getitem__, -8) |
| 2525 | self.assertRaises(IndexError, m.__getitem__, 8) |
| 2526 | |
| 2527 | # Not implemented: multidimensional sub-views |
| 2528 | ex = ndarray(list(range(12)), shape=[3,4], flags=ND_WRITABLE) |
| 2529 | m = memoryview(ex) |
| 2530 | |
| 2531 | self.assertRaises(NotImplementedError, m.__getitem__, 0) |
| 2532 | self.assertRaises(NotImplementedError, m.__setitem__, 0, 9) |
| 2533 | self.assertRaises(NotImplementedError, m.__getitem__, 0) |
| 2534 | |
| 2535 | def test_memoryview_assign(self): |
| 2536 | |
| 2537 | # ndim = 0 |
| 2538 | ex = ndarray(12.5, shape=[], format='f', flags=ND_WRITABLE) |
| 2539 | m = memoryview(ex) |
| 2540 | m[()] = 22.5 |
| 2541 | self.assertEqual(m[()], 22.5) |
| 2542 | m[...] = 23.5 |
| 2543 | self.assertEqual(m[()], 23.5) |
| 2544 | self.assertRaises(TypeError, m.__setitem__, 0, 24.7) |
| 2545 | |
| 2546 | # read-only |
| 2547 | ex = ndarray(list(range(7)), shape=[7]) |
| 2548 | m = memoryview(ex) |
| 2549 | self.assertRaises(TypeError, m.__setitem__, 2, 10) |
| 2550 | |
| 2551 | # range |
| 2552 | ex = ndarray(list(range(7)), shape=[7], flags=ND_WRITABLE) |
| 2553 | m = memoryview(ex) |
| 2554 | |
| 2555 | self.assertRaises(IndexError, m.__setitem__, 2**64, 9) |
| 2556 | self.assertRaises(TypeError, m.__setitem__, 2.0, 10) |
| 2557 | self.assertRaises(TypeError, m.__setitem__, 0.0, 11) |
| 2558 | |
| 2559 | # out of bounds |
| 2560 | self.assertRaises(IndexError, m.__setitem__, -8, 20) |
| 2561 | self.assertRaises(IndexError, m.__setitem__, 8, 25) |
| 2562 | |
| 2563 | # pack_single() success: |
| 2564 | for fmt in fmtdict['@']: |
| 2565 | if fmt == 'c' or fmt == '?': |
| 2566 | continue |
| 2567 | ex = ndarray([1,2,3], shape=[3], format=fmt, flags=ND_WRITABLE) |
| 2568 | m = memoryview(ex) |
| 2569 | i = randrange(-3, 3) |
| 2570 | m[i] = 8 |
| 2571 | self.assertEqual(m[i], 8) |
| 2572 | self.assertEqual(m[i], ex[i]) |
| 2573 | |
| 2574 | ex = ndarray([b'1', b'2', b'3'], shape=[3], format='c', |
| 2575 | flags=ND_WRITABLE) |
| 2576 | m = memoryview(ex) |
| 2577 | m[2] = b'9' |
| 2578 | self.assertEqual(m[2], b'9') |
| 2579 | |
| 2580 | ex = ndarray([True, False, True], shape=[3], format='?', |
| 2581 | flags=ND_WRITABLE) |
| 2582 | m = memoryview(ex) |
| 2583 | m[1] = True |
| 2584 | self.assertEqual(m[1], True) |
| 2585 | |
| 2586 | # pack_single() exceptions: |
| 2587 | nd = ndarray([b'x'], shape=[1], format='c', flags=ND_WRITABLE) |
| 2588 | m = memoryview(nd) |
| 2589 | self.assertRaises(TypeError, m.__setitem__, 0, 100) |
| 2590 | |
| 2591 | ex = ndarray(list(range(120)), shape=[1,2,3,4,5], flags=ND_WRITABLE) |
| 2592 | m1 = memoryview(ex) |
| 2593 | |
| 2594 | for fmt, _range in fmtdict['@'].items(): |
| 2595 | if (fmt == '?'): # PyObject_IsTrue() accepts anything |
| 2596 | continue |
| 2597 | if fmt == 'c': # special case tested above |
| 2598 | continue |
| 2599 | m2 = m1.cast(fmt) |
| 2600 | lo, hi = _range |
| 2601 | if fmt == 'd' or fmt == 'f': |
| 2602 | lo, hi = -2**1024, 2**1024 |
| 2603 | if fmt != 'P': # PyLong_AsVoidPtr() accepts negative numbers |
| 2604 | self.assertRaises(ValueError, m2.__setitem__, 0, lo-1) |
| 2605 | self.assertRaises(TypeError, m2.__setitem__, 0, "xyz") |
| 2606 | self.assertRaises(ValueError, m2.__setitem__, 0, hi) |
| 2607 | |
| 2608 | # invalid item |
| 2609 | m2 = m1.cast('c') |
| 2610 | self.assertRaises(ValueError, m2.__setitem__, 0, b'\xff\xff') |
| 2611 | |
| 2612 | # format not implemented |
| 2613 | ex = ndarray(list(range(1)), shape=[1], format="xL", flags=ND_WRITABLE) |
| 2614 | m = memoryview(ex) |
| 2615 | self.assertRaises(NotImplementedError, m.__setitem__, 0, 1) |
| 2616 | |
| 2617 | ex = ndarray([b'12345'], shape=[1], format="s", flags=ND_WRITABLE) |
| 2618 | m = memoryview(ex) |
| 2619 | self.assertRaises(NotImplementedError, m.__setitem__, 0, 1) |
| 2620 | |
| 2621 | # Not implemented: multidimensional sub-views |
| 2622 | ex = ndarray(list(range(12)), shape=[3,4], flags=ND_WRITABLE) |
| 2623 | m = memoryview(ex) |
| 2624 | |
| 2625 | self.assertRaises(NotImplementedError, m.__setitem__, 0, [2, 3]) |
| 2626 | |
| 2627 | def test_memoryview_slice(self): |
| 2628 | |
| 2629 | ex = ndarray(list(range(12)), shape=[12], flags=ND_WRITABLE) |
| 2630 | m = memoryview(ex) |
| 2631 | |
| 2632 | # zero step |
| 2633 | self.assertRaises(ValueError, m.__getitem__, slice(0,2,0)) |
| 2634 | self.assertRaises(ValueError, m.__setitem__, slice(0,2,0), |
| 2635 | bytearray([1,2])) |
| 2636 | |
| 2637 | # invalid slice key |
| 2638 | self.assertRaises(TypeError, m.__getitem__, ()) |
| 2639 | |
| 2640 | # multidimensional slices |
| 2641 | ex = ndarray(list(range(12)), shape=[12], flags=ND_WRITABLE) |
| 2642 | m = memoryview(ex) |
| 2643 | |
| 2644 | self.assertRaises(NotImplementedError, m.__getitem__, |
| 2645 | (slice(0,2,1), slice(0,2,1))) |
| 2646 | self.assertRaises(NotImplementedError, m.__setitem__, |
| 2647 | (slice(0,2,1), slice(0,2,1)), bytearray([1,2])) |
| 2648 | |
| 2649 | # invalid slice tuple |
| 2650 | self.assertRaises(TypeError, m.__getitem__, (slice(0,2,1), {})) |
| 2651 | self.assertRaises(TypeError, m.__setitem__, (slice(0,2,1), {}), |
| 2652 | bytearray([1,2])) |
| 2653 | |
| 2654 | # rvalue is not an exporter |
| 2655 | self.assertRaises(TypeError, m.__setitem__, slice(0,1,1), [1]) |
| 2656 | |
| 2657 | # non-contiguous slice assignment |
| 2658 | for flags in (0, ND_PIL): |
| 2659 | ex1 = ndarray(list(range(12)), shape=[12], strides=[-1], offset=11, |
| 2660 | flags=ND_WRITABLE|flags) |
| 2661 | ex2 = ndarray(list(range(24)), shape=[12], strides=[2], flags=flags) |
| 2662 | m1 = memoryview(ex1) |
| 2663 | m2 = memoryview(ex2) |
| 2664 | |
| 2665 | ex1[2:5] = ex1[2:5] |
| 2666 | m1[2:5] = m2[2:5] |
| 2667 | |
| 2668 | self.assertEqual(m1, ex1) |
| 2669 | self.assertEqual(m2, ex2) |
| 2670 | |
| 2671 | ex1[1:3][::-1] = ex2[0:2][::1] |
| 2672 | m1[1:3][::-1] = m2[0:2][::1] |
| 2673 | |
| 2674 | self.assertEqual(m1, ex1) |
| 2675 | self.assertEqual(m2, ex2) |
| 2676 | |
| 2677 | ex1[4:1:-2][::-1] = ex1[1:4:2][::1] |
| 2678 | m1[4:1:-2][::-1] = m1[1:4:2][::1] |
| 2679 | |
| 2680 | self.assertEqual(m1, ex1) |
| 2681 | self.assertEqual(m2, ex2) |
| 2682 | |
| 2683 | def test_memoryview_array(self): |
| 2684 | |
| 2685 | def cmptest(testcase, a, b, m, singleitem): |
| 2686 | for i, _ in enumerate(a): |
| 2687 | ai = a[i] |
| 2688 | mi = m[i] |
| 2689 | testcase.assertEqual(ai, mi) |
| 2690 | a[i] = singleitem |
| 2691 | if singleitem != ai: |
| 2692 | testcase.assertNotEqual(a, m) |
| 2693 | testcase.assertNotEqual(a, b) |
| 2694 | else: |
| 2695 | testcase.assertEqual(a, m) |
| 2696 | testcase.assertEqual(a, b) |
| 2697 | m[i] = singleitem |
| 2698 | testcase.assertEqual(a, m) |
| 2699 | testcase.assertEqual(b, m) |
| 2700 | a[i] = ai |
| 2701 | m[i] = mi |
| 2702 | |
| 2703 | for n in range(1, 5): |
| 2704 | for fmt, items, singleitem in iter_format(n, 'array'): |
| 2705 | for lslice in genslices(n): |
| 2706 | for rslice in genslices(n): |
| 2707 | |
| 2708 | a = array.array(fmt, items) |
| 2709 | b = array.array(fmt, items) |
| 2710 | m = memoryview(b) |
| 2711 | |
| 2712 | self.assertEqual(m, a) |
| 2713 | self.assertEqual(m.tolist(), a.tolist()) |
| 2714 | self.assertEqual(m.tobytes(), a.tobytes()) |
| 2715 | self.assertEqual(len(m), len(a)) |
| 2716 | |
| 2717 | cmptest(self, a, b, m, singleitem) |
| 2718 | |
| 2719 | array_err = None |
| 2720 | have_resize = None |
| 2721 | try: |
| 2722 | al = a[lslice] |
| 2723 | ar = a[rslice] |
| 2724 | a[lslice] = a[rslice] |
| 2725 | have_resize = len(al) != len(ar) |
| 2726 | except Exception as e: |
| 2727 | array_err = e.__class__ |
| 2728 | |
| 2729 | m_err = None |
| 2730 | try: |
| 2731 | m[lslice] = m[rslice] |
| 2732 | except Exception as e: |
| 2733 | m_err = e.__class__ |
| 2734 | |
| 2735 | if have_resize: # memoryview cannot change shape |
| 2736 | self.assertIs(m_err, ValueError) |
| 2737 | elif m_err or array_err: |
| 2738 | self.assertIs(m_err, array_err) |
| 2739 | else: |
| 2740 | self.assertEqual(m, a) |
| 2741 | self.assertEqual(m.tolist(), a.tolist()) |
| 2742 | self.assertEqual(m.tobytes(), a.tobytes()) |
| 2743 | cmptest(self, a, b, m, singleitem) |
| 2744 | |
| 2745 | def test_memoryview_compare(self): |
| 2746 | |
| 2747 | a = array.array('L', [1, 2, 3]) |
| 2748 | b = array.array('L', [1, 2, 7]) |
| 2749 | |
| 2750 | # Ordering comparisons raise: |
| 2751 | v = memoryview(a) |
| 2752 | w = memoryview(b) |
| 2753 | for attr in ('__lt__', '__le__', '__gt__', '__ge__'): |
| 2754 | self.assertIs(getattr(v, attr)(w), NotImplemented) |
| 2755 | self.assertIs(getattr(a, attr)(v), NotImplemented) |
| 2756 | |
| 2757 | # Released views compare equal to themselves: |
| 2758 | v = memoryview(a) |
| 2759 | v.release() |
| 2760 | self.assertEqual(v, v) |
| 2761 | self.assertNotEqual(v, a) |
| 2762 | self.assertNotEqual(a, v) |
| 2763 | |
| 2764 | v = memoryview(a) |
| 2765 | w = memoryview(a) |
| 2766 | w.release() |
| 2767 | self.assertNotEqual(v, w) |
| 2768 | self.assertNotEqual(w, v) |
| 2769 | |
| 2770 | # Operand does not implement the buffer protocol: |
| 2771 | v = memoryview(a) |
| 2772 | self.assertNotEqual(v, [1, 2, 3]) |
| 2773 | |
| 2774 | # Different formats: |
| 2775 | c = array.array('l', [1, 2, 3]) |
| 2776 | v = memoryview(a) |
| 2777 | self.assertNotEqual(v, c) |
| 2778 | self.assertNotEqual(c, v) |
| 2779 | |
| 2780 | # Not implemented formats. Ugly, but inevitable. This is the same as |
| 2781 | # issue #2531: equality is also used for membership testing and must |
| 2782 | # return a result. |
| 2783 | a = ndarray([(1, 1.5), (2, 2.7)], shape=[2], format='ld') |
| 2784 | v = memoryview(a) |
| 2785 | self.assertNotEqual(v, a) |
| 2786 | self.assertNotEqual(a, v) |
| 2787 | |
| 2788 | a = ndarray([b'12345'], shape=[1], format="s") |
| 2789 | v = memoryview(a) |
| 2790 | self.assertNotEqual(v, a) |
| 2791 | self.assertNotEqual(a, v) |
| 2792 | |
| 2793 | nd = ndarray([(1,1,1), (2,2,2), (3,3,3)], shape=[3], format='iii') |
| 2794 | v = memoryview(nd) |
| 2795 | self.assertNotEqual(v, nd) |
| 2796 | self.assertNotEqual(nd, v) |
| 2797 | |
| 2798 | # '@' prefix can be dropped: |
| 2799 | nd1 = ndarray([1,2,3], shape=[3], format='@i') |
| 2800 | nd2 = ndarray([1,2,3], shape=[3], format='i') |
| 2801 | v = memoryview(nd1) |
| 2802 | w = memoryview(nd2) |
| 2803 | self.assertEqual(v, w) |
| 2804 | self.assertEqual(w, v) |
| 2805 | self.assertEqual(v, nd2) |
| 2806 | self.assertEqual(nd2, v) |
| 2807 | self.assertEqual(w, nd1) |
| 2808 | self.assertEqual(nd1, w) |
| 2809 | |
| 2810 | # ndim = 0 |
| 2811 | nd1 = ndarray(1729, shape=[], format='@L') |
| 2812 | nd2 = ndarray(1729, shape=[], format='L', flags=ND_WRITABLE) |
| 2813 | v = memoryview(nd1) |
| 2814 | w = memoryview(nd2) |
| 2815 | self.assertEqual(v, w) |
| 2816 | self.assertEqual(w, v) |
| 2817 | self.assertEqual(v, nd2) |
| 2818 | self.assertEqual(nd2, v) |
| 2819 | self.assertEqual(w, nd1) |
| 2820 | self.assertEqual(nd1, w) |
| 2821 | |
| 2822 | self.assertFalse(v.__ne__(w)) |
| 2823 | self.assertFalse(w.__ne__(v)) |
| 2824 | |
| 2825 | w[()] = 1728 |
| 2826 | self.assertNotEqual(v, w) |
| 2827 | self.assertNotEqual(w, v) |
| 2828 | self.assertNotEqual(v, nd2) |
| 2829 | self.assertNotEqual(nd2, v) |
| 2830 | self.assertNotEqual(w, nd1) |
| 2831 | self.assertNotEqual(nd1, w) |
| 2832 | |
| 2833 | self.assertFalse(v.__eq__(w)) |
| 2834 | self.assertFalse(w.__eq__(v)) |
| 2835 | |
| 2836 | nd = ndarray(list(range(12)), shape=[12], flags=ND_WRITABLE|ND_PIL) |
| 2837 | ex = ndarray(list(range(12)), shape=[12], flags=ND_WRITABLE|ND_PIL) |
| 2838 | m = memoryview(ex) |
| 2839 | |
| 2840 | self.assertEqual(m, nd) |
| 2841 | m[9] = 100 |
| 2842 | self.assertNotEqual(m, nd) |
| 2843 | |
| 2844 | # ndim = 1: contiguous |
| 2845 | nd1 = ndarray([-529, 576, -625, 676, -729], shape=[5], format='@h') |
| 2846 | nd2 = ndarray([-529, 576, -625, 676, 729], shape=[5], format='@h') |
| 2847 | v = memoryview(nd1) |
| 2848 | w = memoryview(nd2) |
| 2849 | |
| 2850 | self.assertEqual(v, nd1) |
| 2851 | self.assertEqual(w, nd2) |
| 2852 | self.assertNotEqual(v, nd2) |
| 2853 | self.assertNotEqual(w, nd1) |
| 2854 | self.assertNotEqual(v, w) |
| 2855 | |
| 2856 | # ndim = 1: non-contiguous |
| 2857 | nd1 = ndarray([-529, -625, -729], shape=[3], format='@h') |
| 2858 | nd2 = ndarray([-529, 576, -625, 676, -729], shape=[5], format='@h') |
| 2859 | v = memoryview(nd1) |
| 2860 | w = memoryview(nd2) |
| 2861 | |
| 2862 | self.assertEqual(v, nd2[::2]) |
| 2863 | self.assertEqual(w[::2], nd1) |
| 2864 | self.assertEqual(v, w[::2]) |
| 2865 | self.assertEqual(v[::-1], w[::-2]) |
| 2866 | |
| 2867 | # ndim = 1: non-contiguous, suboffsets |
| 2868 | nd1 = ndarray([-529, -625, -729], shape=[3], format='@h') |
| 2869 | nd2 = ndarray([-529, 576, -625, 676, -729], shape=[5], format='@h', |
| 2870 | flags=ND_PIL) |
| 2871 | v = memoryview(nd1) |
| 2872 | w = memoryview(nd2) |
| 2873 | |
| 2874 | self.assertEqual(v, nd2[::2]) |
| 2875 | self.assertEqual(w[::2], nd1) |
| 2876 | self.assertEqual(v, w[::2]) |
| 2877 | self.assertEqual(v[::-1], w[::-2]) |
| 2878 | |
| 2879 | # ndim = 1: zeros in shape |
| 2880 | nd1 = ndarray([900, 961], shape=[0], format='@h') |
| 2881 | nd2 = ndarray([-900, -961], shape=[0], format='@h') |
| 2882 | v = memoryview(nd1) |
| 2883 | w = memoryview(nd2) |
| 2884 | |
| 2885 | self.assertEqual(v, nd1) |
| 2886 | self.assertEqual(w, nd2) |
| 2887 | self.assertEqual(v, nd2) |
| 2888 | self.assertEqual(w, nd1) |
| 2889 | self.assertEqual(v, w) |
| 2890 | |
| 2891 | # ndim = 1: zero strides |
| 2892 | nd1 = ndarray([900, 900, 900, 900], shape=[4], format='@L') |
| 2893 | nd2 = ndarray([900], shape=[4], strides=[0], format='L') |
| 2894 | v = memoryview(nd1) |
| 2895 | w = memoryview(nd2) |
| 2896 | |
| 2897 | self.assertEqual(v, nd1) |
| 2898 | self.assertEqual(w, nd2) |
| 2899 | self.assertEqual(v, nd2) |
| 2900 | self.assertEqual(w, nd1) |
| 2901 | self.assertEqual(v, w) |
| 2902 | |
| 2903 | n = 10 |
| 2904 | for char in fmtdict['@m']: |
| 2905 | fmt, items, singleitem = randitems(n, 'memoryview', '@', char) |
| 2906 | for flags in (0, ND_PIL): |
| 2907 | nd = ndarray(items, shape=[n], format=fmt, flags=flags) |
| 2908 | m = memoryview(nd) |
| 2909 | self.assertEqual(m, nd) |
| 2910 | |
| 2911 | nd = nd[::-3] |
| 2912 | m = memoryview(nd) |
| 2913 | self.assertEqual(m, nd) |
| 2914 | |
| 2915 | ##### ndim > 1: C-contiguous |
| 2916 | # different values |
| 2917 | nd1 = ndarray(list(range(-15, 15)), shape=[3, 2, 5], format='@h') |
| 2918 | nd2 = ndarray(list(range(0, 30)), shape=[3, 2, 5], format='@h') |
| 2919 | v = memoryview(nd1) |
| 2920 | w = memoryview(nd2) |
| 2921 | |
| 2922 | self.assertEqual(v, nd1) |
| 2923 | self.assertEqual(w, nd2) |
| 2924 | self.assertNotEqual(v, nd2) |
| 2925 | self.assertNotEqual(w, nd1) |
| 2926 | self.assertNotEqual(v, w) |
| 2927 | |
| 2928 | # different shape |
| 2929 | nd1 = ndarray(list(range(30)), shape=[2, 3, 5], format='L') |
| 2930 | nd2 = ndarray(list(range(30)), shape=[3, 2, 5], format='L') |
| 2931 | v = memoryview(nd1) |
| 2932 | w = memoryview(nd2) |
| 2933 | |
| 2934 | self.assertEqual(v, nd1) |
| 2935 | self.assertEqual(w, nd2) |
| 2936 | self.assertNotEqual(v, nd2) |
| 2937 | self.assertNotEqual(w, nd1) |
| 2938 | self.assertNotEqual(v, w) |
| 2939 | |
| 2940 | # different format |
| 2941 | nd1 = ndarray(list(range(30)), shape=[2, 3, 5], format='L') |
| 2942 | nd2 = ndarray(list(range(30)), shape=[2, 3, 5], format='l') |
| 2943 | v = memoryview(nd1) |
| 2944 | w = memoryview(nd2) |
| 2945 | |
| 2946 | self.assertEqual(v, nd1) |
| 2947 | self.assertEqual(w, nd2) |
| 2948 | self.assertNotEqual(v, nd2) |
| 2949 | self.assertNotEqual(w, nd1) |
| 2950 | self.assertNotEqual(v, w) |
| 2951 | |
| 2952 | ##### ndim > 1: Fortran contiguous |
| 2953 | # different values |
| 2954 | nd1 = ndarray(list(range(-15, 15)), shape=[5, 2, 3], format='@h', |
| 2955 | flags=ND_FORTRAN) |
| 2956 | nd2 = ndarray(list(range(0, 30)), shape=[5, 2, 3], format='@h', |
| 2957 | flags=ND_FORTRAN) |
| 2958 | v = memoryview(nd1) |
| 2959 | w = memoryview(nd2) |
| 2960 | |
| 2961 | self.assertEqual(v, nd1) |
| 2962 | self.assertEqual(w, nd2) |
| 2963 | self.assertNotEqual(v, nd2) |
| 2964 | self.assertNotEqual(w, nd1) |
| 2965 | self.assertNotEqual(v, w) |
| 2966 | |
| 2967 | # different shape |
| 2968 | nd1 = ndarray(list(range(-15, 15)), shape=[2, 3, 5], format='l', |
| 2969 | flags=ND_FORTRAN) |
| 2970 | nd2 = ndarray(list(range(-15, 15)), shape=[3, 2, 5], format='l', |
| 2971 | flags=ND_FORTRAN) |
| 2972 | v = memoryview(nd1) |
| 2973 | w = memoryview(nd2) |
| 2974 | |
| 2975 | self.assertEqual(v, nd1) |
| 2976 | self.assertEqual(w, nd2) |
| 2977 | self.assertNotEqual(v, nd2) |
| 2978 | self.assertNotEqual(w, nd1) |
| 2979 | self.assertNotEqual(v, w) |
| 2980 | |
| 2981 | # different format |
| 2982 | nd1 = ndarray(list(range(30)), shape=[5, 2, 3], format='@h', |
| 2983 | flags=ND_FORTRAN) |
| 2984 | nd2 = ndarray(list(range(30)), shape=[5, 2, 3], format='@b', |
| 2985 | flags=ND_FORTRAN) |
| 2986 | v = memoryview(nd1) |
| 2987 | w = memoryview(nd2) |
| 2988 | |
| 2989 | self.assertEqual(v, nd1) |
| 2990 | self.assertEqual(w, nd2) |
| 2991 | self.assertNotEqual(v, nd2) |
| 2992 | self.assertNotEqual(w, nd1) |
| 2993 | self.assertNotEqual(v, w) |
| 2994 | |
| 2995 | ##### ndim > 1: mixed C/Fortran contiguous |
| 2996 | lst1 = list(range(-15, 15)) |
| 2997 | lst2 = transpose(lst1, [3, 2, 5]) |
| 2998 | nd1 = ndarray(lst1, shape=[3, 2, 5], format='@l') |
| 2999 | nd2 = ndarray(lst2, shape=[3, 2, 5], format='l', flags=ND_FORTRAN) |
| 3000 | v = memoryview(nd1) |
| 3001 | w = memoryview(nd2) |
| 3002 | |
| 3003 | self.assertEqual(v, nd1) |
| 3004 | self.assertEqual(w, nd2) |
| 3005 | self.assertEqual(v, w) |
| 3006 | |
| 3007 | ##### ndim > 1: non-contiguous |
| 3008 | # different values |
| 3009 | ex1 = ndarray(list(range(40)), shape=[5, 8], format='@I') |
| 3010 | nd1 = ex1[3:1:-1, ::-2] |
| 3011 | ex2 = ndarray(list(range(40)), shape=[5, 8], format='I') |
| 3012 | nd2 = ex2[1:3:1, ::-2] |
| 3013 | v = memoryview(nd1) |
| 3014 | w = memoryview(nd2) |
| 3015 | |
| 3016 | self.assertEqual(v, nd1) |
| 3017 | self.assertEqual(w, nd2) |
| 3018 | self.assertNotEqual(v, nd2) |
| 3019 | self.assertNotEqual(w, nd1) |
| 3020 | self.assertNotEqual(v, w) |
| 3021 | |
| 3022 | # different shape |
| 3023 | ex1 = ndarray(list(range(30)), shape=[2, 3, 5], format='b') |
| 3024 | nd1 = ex1[1:3:, ::-2] |
| 3025 | nd2 = ndarray(list(range(30)), shape=[3, 2, 5], format='b') |
| 3026 | nd2 = ex2[1:3:, ::-2] |
| 3027 | v = memoryview(nd1) |
| 3028 | w = memoryview(nd2) |
| 3029 | |
| 3030 | self.assertEqual(v, nd1) |
| 3031 | self.assertEqual(w, nd2) |
| 3032 | self.assertNotEqual(v, nd2) |
| 3033 | self.assertNotEqual(w, nd1) |
| 3034 | self.assertNotEqual(v, w) |
| 3035 | |
| 3036 | # different format |
| 3037 | ex1 = ndarray(list(range(30)), shape=[5, 3, 2], format='i') |
| 3038 | nd1 = ex1[1:3:, ::-2] |
| 3039 | nd2 = ndarray(list(range(30)), shape=[5, 3, 2], format='@I') |
| 3040 | nd2 = ex2[1:3:, ::-2] |
| 3041 | v = memoryview(nd1) |
| 3042 | w = memoryview(nd2) |
| 3043 | |
| 3044 | self.assertEqual(v, nd1) |
| 3045 | self.assertEqual(w, nd2) |
| 3046 | self.assertNotEqual(v, nd2) |
| 3047 | self.assertNotEqual(w, nd1) |
| 3048 | self.assertNotEqual(v, w) |
| 3049 | |
| 3050 | ##### ndim > 1: zeros in shape |
| 3051 | nd1 = ndarray(list(range(30)), shape=[0, 3, 2], format='i') |
| 3052 | nd2 = ndarray(list(range(30)), shape=[5, 0, 2], format='@i') |
| 3053 | v = memoryview(nd1) |
| 3054 | w = memoryview(nd2) |
| 3055 | |
| 3056 | self.assertEqual(v, nd1) |
| 3057 | self.assertEqual(w, nd2) |
| 3058 | self.assertNotEqual(v, nd2) |
| 3059 | self.assertNotEqual(w, nd1) |
| 3060 | self.assertNotEqual(v, w) |
| 3061 | |
| 3062 | # ndim > 1: zero strides |
| 3063 | nd1 = ndarray([900]*80, shape=[4, 5, 4], format='@L') |
| 3064 | nd2 = ndarray([900], shape=[4, 5, 4], strides=[0, 0, 0], format='L') |
| 3065 | v = memoryview(nd1) |
| 3066 | w = memoryview(nd2) |
| 3067 | |
| 3068 | self.assertEqual(v, nd1) |
| 3069 | self.assertEqual(w, nd2) |
| 3070 | self.assertEqual(v, nd2) |
| 3071 | self.assertEqual(w, nd1) |
| 3072 | self.assertEqual(v, w) |
| 3073 | self.assertEqual(v.tolist(), w.tolist()) |
| 3074 | |
| 3075 | ##### ndim > 1: suboffsets |
| 3076 | ex1 = ndarray(list(range(40)), shape=[5, 8], format='@I') |
| 3077 | nd1 = ex1[3:1:-1, ::-2] |
| 3078 | ex2 = ndarray(list(range(40)), shape=[5, 8], format='I', flags=ND_PIL) |
| 3079 | nd2 = ex2[1:3:1, ::-2] |
| 3080 | v = memoryview(nd1) |
| 3081 | w = memoryview(nd2) |
| 3082 | |
| 3083 | self.assertEqual(v, nd1) |
| 3084 | self.assertEqual(w, nd2) |
| 3085 | self.assertNotEqual(v, nd2) |
| 3086 | self.assertNotEqual(w, nd1) |
| 3087 | self.assertNotEqual(v, w) |
| 3088 | |
| 3089 | # different shape |
| 3090 | ex1 = ndarray(list(range(30)), shape=[2, 3, 5], format='b', flags=ND_PIL) |
| 3091 | nd1 = ex1[1:3:, ::-2] |
| 3092 | nd2 = ndarray(list(range(30)), shape=[3, 2, 5], format='b') |
| 3093 | nd2 = ex2[1:3:, ::-2] |
| 3094 | v = memoryview(nd1) |
| 3095 | w = memoryview(nd2) |
| 3096 | |
| 3097 | self.assertEqual(v, nd1) |
| 3098 | self.assertEqual(w, nd2) |
| 3099 | self.assertNotEqual(v, nd2) |
| 3100 | self.assertNotEqual(w, nd1) |
| 3101 | self.assertNotEqual(v, w) |
| 3102 | |
| 3103 | # different format |
| 3104 | ex1 = ndarray(list(range(30)), shape=[5, 3, 2], format='i', flags=ND_PIL) |
| 3105 | nd1 = ex1[1:3:, ::-2] |
| 3106 | nd2 = ndarray(list(range(30)), shape=[5, 3, 2], format='@I', flags=ND_PIL) |
| 3107 | nd2 = ex2[1:3:, ::-2] |
| 3108 | v = memoryview(nd1) |
| 3109 | w = memoryview(nd2) |
| 3110 | |
| 3111 | self.assertEqual(v, nd1) |
| 3112 | self.assertEqual(w, nd2) |
| 3113 | self.assertNotEqual(v, nd2) |
| 3114 | self.assertNotEqual(w, nd1) |
| 3115 | self.assertNotEqual(v, w) |
| 3116 | |
| 3117 | # initialize mixed C/Fortran + suboffsets |
| 3118 | lst1 = list(range(-15, 15)) |
| 3119 | lst2 = transpose(lst1, [3, 2, 5]) |
| 3120 | nd1 = ndarray(lst1, shape=[3, 2, 5], format='@l', flags=ND_PIL) |
| 3121 | nd2 = ndarray(lst2, shape=[3, 2, 5], format='l', flags=ND_FORTRAN|ND_PIL) |
| 3122 | v = memoryview(nd1) |
| 3123 | w = memoryview(nd2) |
| 3124 | |
| 3125 | self.assertEqual(v, nd1) |
| 3126 | self.assertEqual(w, nd2) |
| 3127 | self.assertEqual(v, w) |
| 3128 | |
| 3129 | def test_memoryview_check_released(self): |
| 3130 | |
| 3131 | a = array.array('d', [1.1, 2.2, 3.3]) |
| 3132 | |
| 3133 | m = memoryview(a) |
| 3134 | m.release() |
| 3135 | |
| 3136 | # PyMemoryView_FromObject() |
| 3137 | self.assertRaises(ValueError, memoryview, m) |
| 3138 | # memoryview.cast() |
| 3139 | self.assertRaises(ValueError, m.cast, 'c') |
| 3140 | # getbuffer() |
| 3141 | self.assertRaises(ValueError, ndarray, m) |
| 3142 | # memoryview.tolist() |
| 3143 | self.assertRaises(ValueError, m.tolist) |
| 3144 | # memoryview.tobytes() |
| 3145 | self.assertRaises(ValueError, m.tobytes) |
| 3146 | # sequence |
| 3147 | self.assertRaises(ValueError, eval, "1.0 in m", locals()) |
| 3148 | # subscript |
| 3149 | self.assertRaises(ValueError, m.__getitem__, 0) |
| 3150 | # assignment |
| 3151 | self.assertRaises(ValueError, m.__setitem__, 0, 1) |
| 3152 | |
| 3153 | for attr in ('obj', 'nbytes', 'readonly', 'itemsize', 'format', 'ndim', |
| 3154 | 'shape', 'strides', 'suboffsets', 'c_contiguous', |
| 3155 | 'f_contiguous', 'contiguous'): |
| 3156 | self.assertRaises(ValueError, m.__getattribute__, attr) |
| 3157 | |
| 3158 | # richcompare |
| 3159 | b = array.array('d', [1.1, 2.2, 3.3]) |
| 3160 | m1 = memoryview(a) |
| 3161 | m2 = memoryview(b) |
| 3162 | |
| 3163 | self.assertEqual(m1, m2) |
| 3164 | m1.release() |
| 3165 | self.assertNotEqual(m1, m2) |
| 3166 | self.assertNotEqual(m1, a) |
| 3167 | self.assertEqual(m1, m1) |
| 3168 | |
| 3169 | def test_memoryview_tobytes(self): |
| 3170 | # Many implicit tests are already in self.verify(). |
| 3171 | |
| 3172 | nd = ndarray([-529, 576, -625, 676, -729], shape=[5], format='@h') |
| 3173 | |
| 3174 | m = memoryview(nd) |
| 3175 | self.assertEqual(m.tobytes(), nd.tobytes()) |
| 3176 | |
| 3177 | def test_memoryview_get_contiguous(self): |
| 3178 | # Many implicit tests are already in self.verify(). |
| 3179 | |
| 3180 | # no buffer interface |
| 3181 | self.assertRaises(TypeError, get_contiguous, {}, PyBUF_READ, 'F') |
| 3182 | |
| 3183 | # writable request to read-only object |
| 3184 | self.assertRaises(BufferError, get_contiguous, b'x', PyBUF_WRITE, 'C') |
| 3185 | |
| 3186 | # writable request to non-contiguous object |
| 3187 | nd = ndarray([1, 2, 3], shape=[2], strides=[2]) |
| 3188 | self.assertRaises(BufferError, get_contiguous, nd, PyBUF_WRITE, 'A') |
| 3189 | |
| 3190 | # scalar, read-only request from read-only exporter |
| 3191 | nd = ndarray(9, shape=(), format="L") |
| 3192 | for order in ['C', 'F', 'A']: |
| 3193 | m = get_contiguous(nd, PyBUF_READ, order) |
| 3194 | self.assertEqual(m, nd) |
| 3195 | self.assertEqual(m[()], 9) |
| 3196 | |
| 3197 | # scalar, read-only request from writable exporter |
| 3198 | nd = ndarray(9, shape=(), format="L", flags=ND_WRITABLE) |
| 3199 | for order in ['C', 'F', 'A']: |
| 3200 | m = get_contiguous(nd, PyBUF_READ, order) |
| 3201 | self.assertEqual(m, nd) |
| 3202 | self.assertEqual(m[()], 9) |
| 3203 | |
| 3204 | # scalar, writable request |
| 3205 | for order in ['C', 'F', 'A']: |
| 3206 | nd[()] = 9 |
| 3207 | m = get_contiguous(nd, PyBUF_WRITE, order) |
| 3208 | self.assertEqual(m, nd) |
| 3209 | self.assertEqual(m[()], 9) |
| 3210 | |
| 3211 | m[()] = 10 |
| 3212 | self.assertEqual(m[()], 10) |
| 3213 | self.assertEqual(nd[()], 10) |
| 3214 | |
| 3215 | # zeros in shape |
| 3216 | nd = ndarray([1], shape=[0], format="L", flags=ND_WRITABLE) |
| 3217 | for order in ['C', 'F', 'A']: |
| 3218 | m = get_contiguous(nd, PyBUF_READ, order) |
| 3219 | self.assertRaises(IndexError, m.__getitem__, 0) |
| 3220 | self.assertEqual(m, nd) |
| 3221 | self.assertEqual(m.tolist(), []) |
| 3222 | |
| 3223 | nd = ndarray(list(range(8)), shape=[2, 0, 7], format="L", |
| 3224 | flags=ND_WRITABLE) |
| 3225 | for order in ['C', 'F', 'A']: |
| 3226 | m = get_contiguous(nd, PyBUF_READ, order) |
| 3227 | self.assertEqual(ndarray(m).tolist(), [[], []]) |
| 3228 | |
| 3229 | # one-dimensional |
| 3230 | nd = ndarray([1], shape=[1], format="h", flags=ND_WRITABLE) |
| 3231 | for order in ['C', 'F', 'A']: |
| 3232 | m = get_contiguous(nd, PyBUF_WRITE, order) |
| 3233 | self.assertEqual(m, nd) |
| 3234 | self.assertEqual(m.tolist(), nd.tolist()) |
| 3235 | |
| 3236 | nd = ndarray([1, 2, 3], shape=[3], format="b", flags=ND_WRITABLE) |
| 3237 | for order in ['C', 'F', 'A']: |
| 3238 | m = get_contiguous(nd, PyBUF_WRITE, order) |
| 3239 | self.assertEqual(m, nd) |
| 3240 | self.assertEqual(m.tolist(), nd.tolist()) |
| 3241 | |
| 3242 | # one-dimensional, non-contiguous |
| 3243 | nd = ndarray([1, 2, 3], shape=[2], strides=[2], flags=ND_WRITABLE) |
| 3244 | for order in ['C', 'F', 'A']: |
| 3245 | m = get_contiguous(nd, PyBUF_READ, order) |
| 3246 | self.assertEqual(m, nd) |
| 3247 | self.assertEqual(m.tolist(), nd.tolist()) |
| 3248 | self.assertRaises(TypeError, m.__setitem__, 1, 20) |
| 3249 | self.assertEqual(m[1], 3) |
| 3250 | self.assertEqual(nd[1], 3) |
| 3251 | |
| 3252 | nd = nd[::-1] |
| 3253 | for order in ['C', 'F', 'A']: |
| 3254 | m = get_contiguous(nd, PyBUF_READ, order) |
| 3255 | self.assertEqual(m, nd) |
| 3256 | self.assertEqual(m.tolist(), nd.tolist()) |
| 3257 | self.assertRaises(TypeError, m.__setitem__, 1, 20) |
| 3258 | self.assertEqual(m[1], 1) |
| 3259 | self.assertEqual(nd[1], 1) |
| 3260 | |
| 3261 | # multi-dimensional, contiguous input |
| 3262 | nd = ndarray(list(range(12)), shape=[3, 4], flags=ND_WRITABLE) |
| 3263 | for order in ['C', 'A']: |
| 3264 | m = get_contiguous(nd, PyBUF_WRITE, order) |
| 3265 | self.assertEqual(ndarray(m).tolist(), nd.tolist()) |
| 3266 | |
| 3267 | self.assertRaises(BufferError, get_contiguous, nd, PyBUF_WRITE, 'F') |
| 3268 | m = get_contiguous(nd, PyBUF_READ, order) |
| 3269 | self.assertEqual(ndarray(m).tolist(), nd.tolist()) |
| 3270 | |
| 3271 | nd = ndarray(list(range(12)), shape=[3, 4], |
| 3272 | flags=ND_WRITABLE|ND_FORTRAN) |
| 3273 | for order in ['F', 'A']: |
| 3274 | m = get_contiguous(nd, PyBUF_WRITE, order) |
| 3275 | self.assertEqual(ndarray(m).tolist(), nd.tolist()) |
| 3276 | |
| 3277 | self.assertRaises(BufferError, get_contiguous, nd, PyBUF_WRITE, 'C') |
| 3278 | m = get_contiguous(nd, PyBUF_READ, order) |
| 3279 | self.assertEqual(ndarray(m).tolist(), nd.tolist()) |
| 3280 | |
| 3281 | # multi-dimensional, non-contiguous input |
| 3282 | nd = ndarray(list(range(12)), shape=[3, 4], flags=ND_WRITABLE|ND_PIL) |
| 3283 | for order in ['C', 'F', 'A']: |
| 3284 | self.assertRaises(BufferError, get_contiguous, nd, PyBUF_WRITE, |
| 3285 | order) |
| 3286 | m = get_contiguous(nd, PyBUF_READ, order) |
| 3287 | self.assertEqual(ndarray(m).tolist(), nd.tolist()) |
| 3288 | |
| 3289 | # flags |
| 3290 | nd = ndarray([1,2,3,4,5], shape=[3], strides=[2]) |
| 3291 | m = get_contiguous(nd, PyBUF_READ, 'C') |
| 3292 | self.assertTrue(m.c_contiguous) |
| 3293 | |
| 3294 | def test_memoryview_serializing(self): |
| 3295 | |
| 3296 | # C-contiguous |
| 3297 | size = struct.calcsize('i') |
| 3298 | a = array.array('i', [1,2,3,4,5]) |
| 3299 | m = memoryview(a) |
| 3300 | buf = io.BytesIO(m) |
| 3301 | b = bytearray(5*size) |
| 3302 | buf.readinto(b) |
| 3303 | self.assertEqual(m.tobytes(), b) |
| 3304 | |
| 3305 | # C-contiguous, multi-dimensional |
| 3306 | size = struct.calcsize('L') |
| 3307 | nd = ndarray(list(range(12)), shape=[2,3,2], format="L") |
| 3308 | m = memoryview(nd) |
| 3309 | buf = io.BytesIO(m) |
| 3310 | b = bytearray(2*3*2*size) |
| 3311 | buf.readinto(b) |
| 3312 | self.assertEqual(m.tobytes(), b) |
| 3313 | |
| 3314 | # Fortran contiguous, multi-dimensional |
| 3315 | #size = struct.calcsize('L') |
| 3316 | #nd = ndarray(list(range(12)), shape=[2,3,2], format="L", |
| 3317 | # flags=ND_FORTRAN) |
| 3318 | #m = memoryview(nd) |
| 3319 | #buf = io.BytesIO(m) |
| 3320 | #b = bytearray(2*3*2*size) |
| 3321 | #buf.readinto(b) |
| 3322 | #self.assertEqual(m.tobytes(), b) |
| 3323 | |
| 3324 | def test_memoryview_hash(self): |
| 3325 | |
| 3326 | # bytes exporter |
| 3327 | b = bytes(list(range(12))) |
| 3328 | m = memoryview(b) |
| 3329 | self.assertEqual(hash(b), hash(m)) |
| 3330 | |
| 3331 | # C-contiguous |
| 3332 | mc = m.cast('c', shape=[3,4]) |
| 3333 | self.assertEqual(hash(mc), hash(b)) |
| 3334 | |
| 3335 | # non-contiguous |
| 3336 | mx = m[::-2] |
| 3337 | b = bytes(list(range(12))[::-2]) |
| 3338 | self.assertEqual(hash(mx), hash(b)) |
| 3339 | |
| 3340 | # Fortran contiguous |
| 3341 | nd = ndarray(list(range(30)), shape=[3,2,5], flags=ND_FORTRAN) |
| 3342 | m = memoryview(nd) |
| 3343 | self.assertEqual(hash(m), hash(nd)) |
| 3344 | |
| 3345 | # multi-dimensional slice |
| 3346 | nd = ndarray(list(range(30)), shape=[3,2,5]) |
| 3347 | x = nd[::2, ::, ::-1] |
| 3348 | m = memoryview(x) |
| 3349 | self.assertEqual(hash(m), hash(x)) |
| 3350 | |
| 3351 | # multi-dimensional slice with suboffsets |
| 3352 | nd = ndarray(list(range(30)), shape=[2,5,3], flags=ND_PIL) |
| 3353 | x = nd[::2, ::, ::-1] |
| 3354 | m = memoryview(x) |
| 3355 | self.assertEqual(hash(m), hash(x)) |
| 3356 | |
| 3357 | # non-byte formats |
| 3358 | nd = ndarray(list(range(12)), shape=[2,2,3], format='L') |
| 3359 | m = memoryview(nd) |
| 3360 | self.assertEqual(hash(m), hash(nd.tobytes())) |
| 3361 | |
| 3362 | nd = ndarray(list(range(-6, 6)), shape=[2,2,3], format='h') |
| 3363 | m = memoryview(nd) |
| 3364 | self.assertEqual(hash(m), hash(nd.tobytes())) |
| 3365 | |
| 3366 | def test_memoryview_release(self): |
| 3367 | |
| 3368 | # Create re-exporter from getbuffer(memoryview), then release the view. |
| 3369 | a = bytearray([1,2,3]) |
| 3370 | m = memoryview(a) |
| 3371 | nd = ndarray(m) # re-exporter |
| 3372 | self.assertRaises(BufferError, m.release) |
| 3373 | del nd |
| 3374 | m.release() |
| 3375 | |
Stefan Krah | 4e99a31 | 2012-03-05 09:30:47 +0100 | [diff] [blame] | 3376 | a = bytearray([1,2,3]) |
| 3377 | m = memoryview(a) |
| 3378 | nd1 = ndarray(m, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT) |
| 3379 | nd2 = ndarray(nd1, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT) |
| 3380 | self.assertIs(nd2.obj, m) |
| 3381 | self.assertRaises(BufferError, m.release) |
| 3382 | del nd1, nd2 |
| 3383 | m.release() |
| 3384 | |
Stefan Krah | 9a2d99e | 2012-02-25 12:24:21 +0100 | [diff] [blame] | 3385 | # chained views |
| 3386 | a = bytearray([1,2,3]) |
| 3387 | m1 = memoryview(a) |
| 3388 | m2 = memoryview(m1) |
| 3389 | nd = ndarray(m2) # re-exporter |
| 3390 | m1.release() |
| 3391 | self.assertRaises(BufferError, m2.release) |
| 3392 | del nd |
| 3393 | m2.release() |
| 3394 | |
Stefan Krah | 4e99a31 | 2012-03-05 09:30:47 +0100 | [diff] [blame] | 3395 | a = bytearray([1,2,3]) |
| 3396 | m1 = memoryview(a) |
| 3397 | m2 = memoryview(m1) |
| 3398 | nd1 = ndarray(m2, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT) |
| 3399 | nd2 = ndarray(nd1, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT) |
| 3400 | self.assertIs(nd2.obj, m2) |
| 3401 | m1.release() |
| 3402 | self.assertRaises(BufferError, m2.release) |
| 3403 | del nd1, nd2 |
| 3404 | m2.release() |
| 3405 | |
Stefan Krah | 9a2d99e | 2012-02-25 12:24:21 +0100 | [diff] [blame] | 3406 | # Allow changing layout while buffers are exported. |
| 3407 | nd = ndarray([1,2,3], shape=[3], flags=ND_VAREXPORT) |
| 3408 | m1 = memoryview(nd) |
| 3409 | |
| 3410 | nd.push([4,5,6,7,8], shape=[5]) # mutate nd |
| 3411 | m2 = memoryview(nd) |
| 3412 | |
| 3413 | x = memoryview(m1) |
| 3414 | self.assertEqual(x.tolist(), m1.tolist()) |
| 3415 | |
| 3416 | y = memoryview(m2) |
| 3417 | self.assertEqual(y.tolist(), m2.tolist()) |
| 3418 | self.assertEqual(y.tolist(), nd.tolist()) |
| 3419 | m2.release() |
| 3420 | y.release() |
| 3421 | |
| 3422 | nd.pop() # pop the current view |
| 3423 | self.assertEqual(x.tolist(), nd.tolist()) |
| 3424 | |
| 3425 | del nd |
| 3426 | m1.release() |
| 3427 | x.release() |
| 3428 | |
| 3429 | # If multiple memoryviews share the same managed buffer, implicit |
| 3430 | # release() in the context manager's __exit__() method should still |
| 3431 | # work. |
| 3432 | def catch22(b): |
| 3433 | with memoryview(b) as m2: |
| 3434 | pass |
| 3435 | |
| 3436 | x = bytearray(b'123') |
| 3437 | with memoryview(x) as m1: |
| 3438 | catch22(m1) |
| 3439 | self.assertEqual(m1[0], ord(b'1')) |
| 3440 | |
Stefan Krah | 4e99a31 | 2012-03-05 09:30:47 +0100 | [diff] [blame] | 3441 | x = ndarray(list(range(12)), shape=[2,2,3], format='l') |
| 3442 | y = ndarray(x, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT) |
| 3443 | z = ndarray(y, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT) |
| 3444 | self.assertIs(z.obj, x) |
| 3445 | with memoryview(z) as m: |
| 3446 | catch22(m) |
| 3447 | self.assertEqual(m[0:1].tolist(), [[[0, 1, 2], [3, 4, 5]]]) |
| 3448 | |
| 3449 | # Test garbage collection. |
| 3450 | for flags in (0, ND_REDIRECT): |
| 3451 | x = bytearray(b'123') |
| 3452 | with memoryview(x) as m1: |
| 3453 | del x |
| 3454 | y = ndarray(m1, getbuf=PyBUF_FULL_RO, flags=flags) |
| 3455 | with memoryview(y) as m2: |
| 3456 | del y |
| 3457 | z = ndarray(m2, getbuf=PyBUF_FULL_RO, flags=flags) |
| 3458 | with memoryview(z) as m3: |
| 3459 | del z |
| 3460 | catch22(m3) |
| 3461 | catch22(m2) |
| 3462 | catch22(m1) |
| 3463 | self.assertEqual(m1[0], ord(b'1')) |
| 3464 | self.assertEqual(m2[1], ord(b'2')) |
| 3465 | self.assertEqual(m3[2], ord(b'3')) |
| 3466 | del m3 |
| 3467 | del m2 |
| 3468 | del m1 |
| 3469 | |
| 3470 | x = bytearray(b'123') |
| 3471 | with memoryview(x) as m1: |
| 3472 | del x |
| 3473 | y = ndarray(m1, getbuf=PyBUF_FULL_RO, flags=flags) |
| 3474 | with memoryview(y) as m2: |
| 3475 | del y |
| 3476 | z = ndarray(m2, getbuf=PyBUF_FULL_RO, flags=flags) |
| 3477 | with memoryview(z) as m3: |
| 3478 | del z |
| 3479 | catch22(m1) |
| 3480 | catch22(m2) |
| 3481 | catch22(m3) |
| 3482 | self.assertEqual(m1[0], ord(b'1')) |
| 3483 | self.assertEqual(m2[1], ord(b'2')) |
| 3484 | self.assertEqual(m3[2], ord(b'3')) |
| 3485 | del m1, m2, m3 |
| 3486 | |
Stefan Krah | fcbb416 | 2012-03-05 10:45:31 +0100 | [diff] [blame^] | 3487 | # memoryview.release() fails if the view has exported buffers. |
| 3488 | x = bytearray(b'123') |
| 3489 | with self.assertRaises(BufferError): |
| 3490 | with memoryview(x) as m: |
| 3491 | ex = ndarray(m) |
| 3492 | m[0] == ord(b'1') |
Stefan Krah | 9a2d99e | 2012-02-25 12:24:21 +0100 | [diff] [blame] | 3493 | |
Stefan Krah | 4e99a31 | 2012-03-05 09:30:47 +0100 | [diff] [blame] | 3494 | def test_memoryview_redirect(self): |
| 3495 | |
| 3496 | nd = ndarray([1.0 * x for x in range(12)], shape=[12], format='d') |
| 3497 | a = array.array('d', [1.0 * x for x in range(12)]) |
| 3498 | |
| 3499 | for x in (nd, a): |
| 3500 | y = ndarray(x, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT) |
| 3501 | z = ndarray(y, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT) |
| 3502 | m = memoryview(z) |
| 3503 | |
| 3504 | self.assertIs(y.obj, x) |
| 3505 | self.assertIs(z.obj, x) |
| 3506 | self.assertIs(m.obj, x) |
| 3507 | |
| 3508 | self.assertEqual(m, x) |
| 3509 | self.assertEqual(m, y) |
| 3510 | self.assertEqual(m, z) |
| 3511 | |
| 3512 | self.assertEqual(m[1:3], x[1:3]) |
| 3513 | self.assertEqual(m[1:3], y[1:3]) |
| 3514 | self.assertEqual(m[1:3], z[1:3]) |
| 3515 | del y, z |
| 3516 | self.assertEqual(m[1:3], x[1:3]) |
| 3517 | |
Stefan Krah | 9a2d99e | 2012-02-25 12:24:21 +0100 | [diff] [blame] | 3518 | def test_issue_7385(self): |
| 3519 | x = ndarray([1,2,3], shape=[3], flags=ND_GETBUF_FAIL) |
| 3520 | self.assertRaises(BufferError, memoryview, x) |
| 3521 | |
| 3522 | |
| 3523 | def test_main(): |
| 3524 | support.run_unittest(TestBufferProtocol) |
| 3525 | |
| 3526 | |
| 3527 | if __name__ == "__main__": |
| 3528 | test_main() |