| 547 | |
| 548 | @pytest.mark.filterwarnings("ignore:The dask.delayed:UserWarning") |
| 549 | def test_array_delayed(): |
| 550 | np = pytest.importorskip("numpy") |
| 551 | da = pytest.importorskip("dask.array") |
| 552 | |
| 553 | arr = np.arange(100).reshape((10, 10)) |
| 554 | darr = da.from_array(arr, chunks=(5, 5)) |
| 555 | val = delayed(sum)([arr, darr, 1]) |
| 556 | assert isinstance(val, Delayed) |
| 557 | assert np.allclose(val.compute(), arr + arr + 1) |
| 558 | assert val.sum().compute() == (arr + arr + 1).sum() |
| 559 | assert val[0, 0].compute() == (arr + arr + 1)[0, 0] |
| 560 | |
| 561 | task, dsk = to_task_dask(darr) |
| 562 | assert not darr.dask.keys() - dsk.keys() |
| 563 | diff = dsk.keys() - darr.dask.keys() |
| 564 | assert len(diff) == 1 |
| 565 | |
| 566 | delayed_arr = delayed(darr) |
| 567 | assert (delayed_arr.compute() == arr).all() |
| 568 | |
| 569 | |
| 570 | def test_array_delayed_complex_optimization(): |