| 475 | } |
| 476 | |
| 477 | static int |
| 478 | _fix_unknown_dimension(PyArray_Dims *newshape, PyArrayObject *arr) |
| 479 | { |
| 480 | npy_intp *dimensions; |
| 481 | npy_intp s_original = PyArray_SIZE(arr); |
| 482 | npy_intp i_unknown, s_known; |
| 483 | int i, n; |
| 484 | |
| 485 | dimensions = newshape->ptr; |
| 486 | n = newshape->len; |
| 487 | s_known = 1; |
| 488 | i_unknown = -1; |
| 489 | |
| 490 | for (i = 0; i < n; i++) { |
| 491 | if (dimensions[i] < 0) { |
| 492 | if (i_unknown == -1) { |
| 493 | i_unknown = i; |
| 494 | } |
| 495 | else { |
| 496 | PyErr_SetString(PyExc_ValueError, |
| 497 | "can only specify one unknown dimension"); |
| 498 | return -1; |
| 499 | } |
| 500 | } |
| 501 | else if (npy_mul_sizes_with_overflow(&s_known, s_known, |
| 502 | dimensions[i])) { |
| 503 | raise_reshape_size_mismatch(newshape, arr); |
| 504 | return -1; |
| 505 | } |
| 506 | } |
| 507 | |
| 508 | if (i_unknown >= 0) { |
| 509 | if (s_known == 0 || s_original % s_known != 0) { |
| 510 | raise_reshape_size_mismatch(newshape, arr); |
| 511 | return -1; |
| 512 | } |
| 513 | dimensions[i_unknown] = s_original / s_known; |
| 514 | } |
| 515 | else { |
| 516 | if (s_original != s_known) { |
| 517 | raise_reshape_size_mismatch(newshape, arr); |
| 518 | return -1; |
| 519 | } |
| 520 | } |
| 521 | return 0; |
| 522 | } |
| 523 | |
| 524 | /*NUMPY_API |
| 525 | * |
no test coverage detected