File size: 20,754 Bytes
7885a28 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 |
import contextlib
import pytest
import numpy as np
from numpy.testing import assert_allclose, assert_equal
from scipy.sparse import csr_array, dok_array, SparseEfficiencyWarning
from .test_arithmetic1d import toarray
formats_for_index1d = [csr_array, dok_array]
@contextlib.contextmanager
def check_remains_sorted(X):
"""Checks that sorted indices property is retained through an operation"""
yield
if not hasattr(X, 'has_sorted_indices') or not X.has_sorted_indices:
return
indices = X.indices.copy()
X.has_sorted_indices = False
X.sort_indices()
assert_equal(indices, X.indices, 'Expected sorted indices, found unsorted')
@pytest.mark.parametrize("spcreator", formats_for_index1d)
class TestGetSet1D:
def test_None_index(self, spcreator):
D = np.array([4, 3, 0])
A = spcreator(D)
N = D.shape[0]
for j in range(-N, N):
assert_equal(A[j, None].toarray(), D[j, None])
assert_equal(A[None, j].toarray(), D[None, j])
assert_equal(A[None, None, j].toarray(), D[None, None, j])
def test_getitem_shape(self, spcreator):
A = spcreator(np.arange(3 * 4).reshape(3, 4))
assert A[1, 2].ndim == 0
assert A[1, 2:3].shape == (1,)
assert A[None, 1, 2:3].shape == (1, 1)
assert A[None, 1, 2].shape == (1,)
assert A[None, 1, 2, None].shape == (1, 1)
# see gh-22458
assert A[None, 1].shape == (1, 4)
assert A[1, None].shape == (1, 4)
assert A[None, 1, :].shape == (1, 4)
assert A[1, None, :].shape == (1, 4)
assert A[1, :, None].shape == (4, 1)
with pytest.raises(IndexError, match='Only 1D or 2D arrays'):
A[None, 2, 1, None, None]
with pytest.raises(IndexError, match='Only 1D or 2D arrays'):
A[None, 0:2, None, 1]
with pytest.raises(IndexError, match='Only 1D or 2D arrays'):
A[0:1, 1:, None]
with pytest.raises(IndexError, match='Only 1D or 2D arrays'):
A[1:, 1, None, None]
def test_getelement(self, spcreator):
D = np.array([4, 3, 0])
A = spcreator(D)
N = D.shape[0]
for j in range(-N, N):
assert_equal(A[j], D[j])
for ij in [3, -4]:
with pytest.raises(IndexError, match='index (.*) out of (range|bounds)'):
A.__getitem__(ij)
# single element tuples unwrapped
assert A[(0,)] == 4
with pytest.raises(IndexError, match='index (.*) out of (range|bounds)'):
A.__getitem__((4,))
def test_setelement(self, spcreator):
dtype = np.float64
A = spcreator((12,), dtype=dtype)
with np.testing.suppress_warnings() as sup:
sup.filter(
SparseEfficiencyWarning,
"Changing the sparsity structure of .* is expensive",
)
A[0] = dtype(0)
A[1] = dtype(3)
A[8] = dtype(9.0)
A[-2] = dtype(7)
A[5] = 9
A[-9,] = dtype(8)
A[1,] = dtype(5) # overwrite using 1-tuple index
for ij in [13, -14, (13,), (14,)]:
with pytest.raises(IndexError, match='out of (range|bounds)'):
A.__setitem__(ij, 123.0)
@pytest.mark.parametrize("spcreator", formats_for_index1d)
class TestSlicingAndFancy1D:
#######################
# Int-like Array Index
#######################
def test_get_array_index(self, spcreator):
D = np.array([4, 3, 0])
A = spcreator(D)
assert_equal(A[()].toarray(), D[()])
for ij in [(0, 3), (3,)]:
with pytest.raises(IndexError, match='out of (range|bounds)|many indices'):
A.__getitem__(ij)
def test_set_array_index(self, spcreator):
dtype = np.float64
A = spcreator((12,), dtype=dtype)
with np.testing.suppress_warnings() as sup:
sup.filter(
SparseEfficiencyWarning,
"Changing the sparsity structure of .* is expensive",
)
A[np.array(6)] = dtype(4.0) # scalar index
A[np.array(6)] = dtype(2.0) # overwrite with scalar index
assert_equal(A.toarray(), [0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0])
for ij in [(13,), (-14,)]:
with pytest.raises(IndexError, match='index .* out of (range|bounds)'):
A.__setitem__(ij, 123.0)
for v in [(), (0, 3), [1, 2, 3], np.array([1, 2, 3])]:
msg = 'Trying to assign a sequence to an item'
with pytest.raises(ValueError, match=msg):
A.__setitem__(0, v)
####################
# 1d Slice as index
####################
def test_dtype_preservation(self, spcreator):
assert_equal(spcreator((10,), dtype=np.int16)[1:5].dtype, np.int16)
assert_equal(spcreator((6,), dtype=np.int32)[0:0:2].dtype, np.int32)
assert_equal(spcreator((6,), dtype=np.int64)[:].dtype, np.int64)
def test_get_1d_slice(self, spcreator):
B = np.arange(50.)
A = spcreator(B)
assert_equal(B[:], A[:].toarray())
assert_equal(B[2:5], A[2:5].toarray())
C = np.array([4, 0, 6, 0, 0, 0, 0, 0, 1])
D = spcreator(C)
assert_equal(C[1:3], D[1:3].toarray())
# Now test slicing when a row contains only zeros
E = np.array([0, 0, 0, 0, 0])
F = spcreator(E)
assert_equal(E[1:3], F[1:3].toarray())
assert_equal(E[-2:], F[-2:].toarray())
assert_equal(E[:], F[:].toarray())
assert_equal(E[slice(None)], F[slice(None)].toarray())
def test_slicing_idx_slice(self, spcreator):
B = np.arange(50)
A = spcreator(B)
# [i]
assert_equal(A[2], B[2])
assert_equal(A[-1], B[-1])
assert_equal(A[np.array(-2)], B[-2])
# [1:2]
assert_equal(A[:].toarray(), B[:])
assert_equal(A[5:-2].toarray(), B[5:-2])
assert_equal(A[5:12:3].toarray(), B[5:12:3])
# int8 slice
s = slice(np.int8(2), np.int8(4), None)
assert_equal(A[s].toarray(), B[2:4])
# np.s_
s_ = np.s_
slices = [s_[:2], s_[1:2], s_[3:], s_[3::2],
s_[15:20], s_[3:2],
s_[8:3:-1], s_[4::-2], s_[:5:-1],
0, 1, s_[:], s_[1:5], -1, -2, -5,
np.array(-1), np.int8(-3)]
for j, a in enumerate(slices):
x = A[a]
y = B[a]
if y.shape == ():
assert_equal(x, y, repr(a))
else:
if x.size == 0 and y.size == 0:
pass
else:
assert_equal(x.toarray(), y, repr(a))
def test_ellipsis_1d_slicing(self, spcreator):
B = np.arange(50)
A = spcreator(B)
assert_equal(A[...].toarray(), B[...])
assert_equal(A[...,].toarray(), B[...,])
##########################
# Assignment with Slicing
##########################
def test_slice_scalar_assign(self, spcreator):
A = spcreator((5,))
B = np.zeros((5,))
with np.testing.suppress_warnings() as sup:
sup.filter(
SparseEfficiencyWarning,
"Changing the sparsity structure of .* is expensive",
)
for C in [A, B]:
C[0:1] = 1
C[2:0] = 4
C[2:3] = 9
C[3:] = 1
C[3::-1] = 9
assert_equal(A.toarray(), B)
def test_slice_assign_2(self, spcreator):
shape = (10,)
for idx in [slice(3), slice(None, 10, 4), slice(5, -2)]:
A = spcreator(shape)
with np.testing.suppress_warnings() as sup:
sup.filter(
SparseEfficiencyWarning,
"Changing the sparsity structure of .* is expensive",
)
A[idx] = 1
B = np.zeros(shape)
B[idx] = 1
msg = f"idx={idx!r}"
assert_allclose(A.toarray(), B, err_msg=msg)
def test_self_self_assignment(self, spcreator):
# Tests whether a row of one lil_matrix can be assigned to another.
B = spcreator((5,))
with np.testing.suppress_warnings() as sup:
sup.filter(
SparseEfficiencyWarning,
"Changing the sparsity structure of .* is expensive",
)
B[0] = 2
B[1] = 0
B[2] = 3
B[3] = 10
A = B / 10
B[:] = A[:]
assert_equal(A[:].toarray(), B[:].toarray())
A = B / 10
B[:] = A[:1]
assert_equal(np.zeros((5,)) + A[0], B.toarray())
A = B / 10
B[:-1] = A[1:]
assert_equal(A[1:].toarray(), B[:-1].toarray())
def test_slice_assignment(self, spcreator):
B = spcreator((4,))
expected = np.array([10, 0, 14, 0])
block = [2, 1]
with np.testing.suppress_warnings() as sup:
sup.filter(
SparseEfficiencyWarning,
"Changing the sparsity structure of .* is expensive",
)
B[0] = 5
B[2] = 7
B[:] = B + B
assert_equal(B.toarray(), expected)
B[:2] = csr_array(block)
assert_equal(B.toarray()[:2], block)
def test_set_slice(self, spcreator):
A = spcreator((5,))
B = np.zeros(5, float)
s_ = np.s_
slices = [s_[:2], s_[1:2], s_[3:], s_[3::2],
s_[8:3:-1], s_[4::-2], s_[:5:-1],
0, 1, s_[:], s_[1:5], -1, -2, -5,
np.array(-1), np.int8(-3)]
with np.testing.suppress_warnings() as sup:
sup.filter(
SparseEfficiencyWarning,
"Changing the sparsity structure of .* is expensive",
)
for j, a in enumerate(slices):
A[a] = j
B[a] = j
assert_equal(A.toarray(), B, repr(a))
A[1:10:2] = range(1, 5, 2)
B[1:10:2] = range(1, 5, 2)
assert_equal(A.toarray(), B)
# The next commands should raise exceptions
toobig = list(range(100))
with pytest.raises(ValueError, match='Trying to assign a sequence to an item'):
A.__setitem__(0, toobig)
with pytest.raises(ValueError, match='could not be broadcast together'):
A.__setitem__(slice(None), toobig)
def test_assign_empty(self, spcreator):
A = spcreator(np.ones(3))
B = spcreator((2,))
A[:2] = B
assert_equal(A.toarray(), [0, 0, 1])
####################
# 1d Fancy Indexing
####################
def test_dtype_preservation_empty_index(self, spcreator):
A = spcreator((2,), dtype=np.int16)
assert_equal(A[[False, False]].dtype, np.int16)
assert_equal(A[[]].dtype, np.int16)
def test_bad_index(self, spcreator):
A = spcreator(np.zeros(5))
with pytest.raises(
(IndexError, ValueError, TypeError),
match='Index dimension must be 1 or 2|only integers',
):
A.__getitem__("foo")
with pytest.raises(
(IndexError, ValueError, TypeError),
match='tuple index out of range|only integers',
):
A.__getitem__((2, "foo"))
def test_fancy_indexing_2darray(self, spcreator):
B = np.arange(50).reshape((5, 10))
A = spcreator(B)
# [i]
assert_equal(A[[1, 3]].toarray(), B[[1, 3]])
# [i,[1,2]]
assert_equal(A[3, [1, 3]].toarray(), B[3, [1, 3]])
assert_equal(A[-1, [2, -5]].toarray(), B[-1, [2, -5]])
assert_equal(A[np.array(-1), [2, -5]].toarray(), B[-1, [2, -5]])
assert_equal(A[-1, np.array([2, -5])].toarray(), B[-1, [2, -5]])
assert_equal(A[np.array(-1), np.array([2, -5])].toarray(), B[-1, [2, -5]])
# [1:2,[1,2]]
assert_equal(A[:, [2, 8, 3, -1]].toarray(), B[:, [2, 8, 3, -1]])
assert_equal(A[3:4, [9]].toarray(), B[3:4, [9]])
assert_equal(A[1:4, [-1, -5]].toarray(), B[1:4, [-1, -5]])
assert_equal(A[1:4, np.array([-1, -5])].toarray(), B[1:4, [-1, -5]])
# [[1,2],j]
assert_equal(A[[1, 3], 3].toarray(), B[[1, 3], 3])
assert_equal(A[[2, -5], -4].toarray(), B[[2, -5], -4])
assert_equal(A[np.array([2, -5]), -4].toarray(), B[[2, -5], -4])
assert_equal(A[[2, -5], np.array(-4)].toarray(), B[[2, -5], -4])
assert_equal(A[np.array([2, -5]), np.array(-4)].toarray(), B[[2, -5], -4])
# [[1,2],1:2]
assert_equal(A[[1, 3], :].toarray(), B[[1, 3], :])
assert_equal(A[[2, -5], 8:-1].toarray(), B[[2, -5], 8:-1])
assert_equal(A[np.array([2, -5]), 8:-1].toarray(), B[[2, -5], 8:-1])
# [[1,2],[1,2]]
assert_equal(toarray(A[[1, 3], [2, 4]]), B[[1, 3], [2, 4]])
assert_equal(toarray(A[[-1, -3], [2, -4]]), B[[-1, -3], [2, -4]])
assert_equal(
toarray(A[np.array([-1, -3]), [2, -4]]), B[[-1, -3], [2, -4]]
)
assert_equal(
toarray(A[[-1, -3], np.array([2, -4])]), B[[-1, -3], [2, -4]]
)
assert_equal(
toarray(A[np.array([-1, -3]), np.array([2, -4])]), B[[-1, -3], [2, -4]]
)
# [[[1],[2]],[1,2]]
assert_equal(A[[[1], [3]], [2, 4]].toarray(), B[[[1], [3]], [2, 4]])
assert_equal(
A[[[-1], [-3], [-2]], [2, -4]].toarray(),
B[[[-1], [-3], [-2]], [2, -4]]
)
assert_equal(
A[np.array([[-1], [-3], [-2]]), [2, -4]].toarray(),
B[[[-1], [-3], [-2]], [2, -4]]
)
assert_equal(
A[[[-1], [-3], [-2]], np.array([2, -4])].toarray(),
B[[[-1], [-3], [-2]], [2, -4]]
)
assert_equal(
A[np.array([[-1], [-3], [-2]]), np.array([2, -4])].toarray(),
B[[[-1], [-3], [-2]], [2, -4]]
)
# [[1,2]]
assert_equal(A[[1, 3]].toarray(), B[[1, 3]])
assert_equal(A[[-1, -3]].toarray(), B[[-1, -3]])
assert_equal(A[np.array([-1, -3])].toarray(), B[[-1, -3]])
# [[1,2],:][:,[1,2]]
assert_equal(
A[[1, 3], :][:, [2, 4]].toarray(), B[[1, 3], :][:, [2, 4]]
)
assert_equal(
A[[-1, -3], :][:, [2, -4]].toarray(), B[[-1, -3], :][:, [2, -4]]
)
assert_equal(
A[np.array([-1, -3]), :][:, np.array([2, -4])].toarray(),
B[[-1, -3], :][:, [2, -4]]
)
# [:,[1,2]][[1,2],:]
assert_equal(
A[:, [1, 3]][[2, 4], :].toarray(), B[:, [1, 3]][[2, 4], :]
)
assert_equal(
A[:, [-1, -3]][[2, -4], :].toarray(), B[:, [-1, -3]][[2, -4], :]
)
assert_equal(
A[:, np.array([-1, -3])][np.array([2, -4]), :].toarray(),
B[:, [-1, -3]][[2, -4], :]
)
def test_fancy_indexing(self, spcreator):
B = np.arange(50)
A = spcreator(B)
# [i]
assert_equal(A[[3]].toarray(), B[[3]])
# [np.array]
assert_equal(A[[1, 3]].toarray(), B[[1, 3]])
assert_equal(A[[2, -5]].toarray(), B[[2, -5]])
assert_equal(A[np.array(-1)], B[-1])
assert_equal(A[np.array([-1, 2])].toarray(), B[[-1, 2]])
assert_equal(A[np.array(5)], B[np.array(5)])
# [[[1],[2]]]
ind = np.array([[1], [3]])
assert_equal(A[ind].toarray(), B[ind])
ind = np.array([[-1], [-3], [-2]])
assert_equal(A[ind].toarray(), B[ind])
# [[1, 2]]
assert_equal(A[[1, 3]].toarray(), B[[1, 3]])
assert_equal(A[[-1, -3]].toarray(), B[[-1, -3]])
assert_equal(A[np.array([-1, -3])].toarray(), B[[-1, -3]])
# [[1, 2]][[1, 2]]
assert_equal(A[[1, 5, 2, 8]][[1, 3]].toarray(),
B[[1, 5, 2, 8]][[1, 3]])
assert_equal(A[[-1, -5, 2, 8]][[1, -4]].toarray(),
B[[-1, -5, 2, 8]][[1, -4]])
def test_fancy_indexing_boolean(self, spcreator):
np.random.seed(1234) # make runs repeatable
B = np.arange(50)
A = spcreator(B)
I = np.array(np.random.randint(0, 2, size=50), dtype=bool)
assert_equal(toarray(A[I]), B[I])
assert_equal(toarray(A[B > 9]), B[B > 9])
Z1 = np.zeros(51, dtype=bool)
Z2 = np.zeros(51, dtype=bool)
Z2[-1] = True
Z3 = np.zeros(51, dtype=bool)
Z3[0] = True
msg = 'bool index .* has shape|boolean index did not match'
with pytest.raises(IndexError, match=msg):
A.__getitem__(Z1)
with pytest.raises(IndexError, match=msg):
A.__getitem__(Z2)
with pytest.raises(IndexError, match=msg):
A.__getitem__(Z3)
def test_fancy_indexing_sparse_boolean(self, spcreator):
np.random.seed(1234) # make runs repeatable
B = np.arange(20)
A = spcreator(B)
X = np.array(np.random.randint(0, 2, size=20), dtype=bool)
Xsp = csr_array(X)
assert_equal(toarray(A[Xsp]), B[X])
assert_equal(toarray(A[A > 9]), B[B > 9])
Y = np.array(np.random.randint(0, 2, size=60), dtype=bool)
Ysp = csr_array(Y)
with pytest.raises(IndexError, match='bool index .* has shape|only integers'):
A.__getitem__(Ysp)
with pytest.raises(IndexError, match='tuple index out of range|only integers'):
A.__getitem__((Xsp, 1))
def test_fancy_indexing_seq_assign(self, spcreator):
mat = spcreator(np.array([1, 0]))
with pytest.raises(ValueError, match='Trying to assign a sequence to an item'):
mat.__setitem__(0, np.array([1, 2]))
def test_fancy_indexing_empty(self, spcreator):
B = np.arange(50)
B[3:9] = 0
B[30] = 0
A = spcreator(B)
K = np.array([False] * 50)
assert_equal(toarray(A[K]), B[K])
K = np.array([], dtype=int)
assert_equal(toarray(A[K]), B[K])
J = np.array([0, 1, 2, 3, 4], dtype=int)
assert_equal(toarray(A[J]), B[J])
############################
# 1d Fancy Index Assignment
############################
def test_bad_index_assign(self, spcreator):
A = spcreator(np.zeros(5))
msg = 'Index dimension must be 1 or 2|only integers'
with pytest.raises((IndexError, ValueError, TypeError), match=msg):
A.__setitem__("foo", 2)
def test_fancy_indexing_set(self, spcreator):
M = (5,)
# [1:2]
for j in [[2, 3, 4], slice(None, 10, 4), np.arange(3),
slice(5, -2), slice(2, 5)]:
A = spcreator(M)
B = np.zeros(M)
with np.testing.suppress_warnings() as sup:
sup.filter(
SparseEfficiencyWarning,
"Changing the sparsity structure of .* is expensive",
)
B[j] = 1
with check_remains_sorted(A):
A[j] = 1
assert_allclose(A.toarray(), B)
def test_sequence_assignment(self, spcreator):
A = spcreator((4,))
B = spcreator((3,))
i0 = [0, 1, 2]
i1 = (0, 1, 2)
i2 = np.array(i0)
with np.testing.suppress_warnings() as sup:
sup.filter(
SparseEfficiencyWarning,
"Changing the sparsity structure of .* is expensive",
)
with check_remains_sorted(A):
A[i0] = B[i0]
msg = "too many indices for array|tuple index out of range"
with pytest.raises(IndexError, match=msg):
B.__getitem__(i1)
A[i2] = B[i2]
assert_equal(A[:3].toarray(), B.toarray())
assert A.shape == (4,)
# slice
A = spcreator((4,))
with check_remains_sorted(A):
A[1:3] = [10, 20]
assert_equal(A.toarray(), [0, 10, 20, 0])
# array
A = spcreator((4,))
B = np.zeros(4)
with check_remains_sorted(A):
for C in [A, B]:
C[[0, 1, 2]] = [4, 5, 6]
assert_equal(A.toarray(), B)
def test_fancy_assign_empty(self, spcreator):
B = np.arange(50)
B[2] = 0
B[[3, 6]] = 0
A = spcreator(B)
K = np.array([False] * 50)
A[K] = 42
assert_equal(A.toarray(), B)
K = np.array([], dtype=int)
A[K] = 42
assert_equal(A.toarray(), B)
|