(self, q, skipna, compute_backend)
| 6418 | @pytest.mark.parametrize("skipna", [True, False, None]) |
| 6419 | @pytest.mark.parametrize("q", [0.25, [0.50], [0.25, 0.75]]) |
| 6420 | def test_quantile(self, q, skipna, compute_backend) -> None: |
| 6421 | ds = create_test_data(seed=123) |
| 6422 | ds.var1.data[0, 0] = np.nan |
| 6423 | |
| 6424 | for dim in [None, "dim1", ["dim1"]]: |
| 6425 | ds_quantile = ds.quantile(q, dim=dim, skipna=skipna) |
| 6426 | if is_scalar(q): |
| 6427 | assert "quantile" not in ds_quantile.dims |
| 6428 | else: |
| 6429 | assert "quantile" in ds_quantile.dims |
| 6430 | |
| 6431 | for var, dar in ds.data_vars.items(): |
| 6432 | assert var in ds_quantile |
| 6433 | assert_identical( |
| 6434 | ds_quantile[var], dar.quantile(q, dim=dim, skipna=skipna) |
| 6435 | ) |
| 6436 | dim = ["dim1", "dim2"] |
| 6437 | ds_quantile = ds.quantile(q, dim=dim, skipna=skipna) |
| 6438 | assert "dim3" in ds_quantile.dims |
| 6439 | assert all(d not in ds_quantile.dims for d in dim) |
| 6440 | |
| 6441 | @pytest.mark.parametrize("compute_backend", ["numbagg", None], indirect=True) |
| 6442 | @pytest.mark.parametrize("skipna", [True, False]) |
nothing calls this directly
no test coverage detected