def validate_agg_perf(perf_da, min_trial=1): """Validate the aggregated eval data set.""" assert isinstance(perf_da, xr.DataArray) assert perf_da.dims == (ITER, SUGGEST, TEST_CASE, METHOD, TRIAL) assert xru.is_simple_coords(perf_da.coords, dims=(ITER, SUGGEST, TRIAL)) assert not np.any(np.isnan(perf_da.values)) assert perf_da.sizes[TRIAL] >= min_trial
def validate_time(all_time): """Validate the aggregated time data set.""" assert isinstance(all_time, xr.Dataset) assert all_time[cc.SUGGEST_PHASE].dims == (ITER,) assert all_time[cc.EVAL_PHASE].dims == (ITER, SUGGEST) assert all_time[cc.OBS_PHASE].dims == (ITER,) assert xru.is_simple_coords(all_time.coords, min_side=1)
def test_is_simple_coords_pass(da): simple = xru.is_simple_coords(da.coords) assert simple
def test_is_simple_coords(da, min_side): xru.is_simple_coords(da.coords, min_side=min_side)
def validate_perf(perf_da): """Validate the input eval data arrays.""" assert isinstance(perf_da, xr.Dataset) assert perf_da.dims == (ITER, SUGGEST) assert xru.is_simple_coords(perf_da.coords) assert not np.any(np.isnan(perf_da.values))
def validate_perf(perf_da): assert isinstance(perf_da, xr.DataArray) assert perf_da.dims == (ITER, SUGGEST) assert xru.is_simple_coords(perf_da.coords) assert not np.any(np.isnan(perf_da.values))