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))