test: test_presrat_transform_nochanges() working

tests/bias/test_presrat_bias_correction.py

@@ -116,6 +116,27 @@ def fp_fut_cc_notrend(tmpdir_factory):
  return fn
 
 
+@pytest.fixture(scope='module')
+def fut_cc_notrend(fp_fut_cc_notrend):
+ ds = xr.open_dataset(fp_fut_cc_notrend)
+ da = ds['rsds'].compute().transpose('lat', 'lon', 'time')
+ # Unfortunatelly, _get_factors() assume latitude as descending
+ da = da.sortby('lat', ascending=False)
+ latlon = np.stack(xr.broadcast(da["lat"], da["lon"] - 360),
+ axis=-1).astype('float32')
+ for ii in range(4):
+ for jj in range(4):
+ np.allclose(
+ da.sel(lat=latlon[ii, jj, 0], method='nearest').sel(
+ lon=latlon[ii, jj, 1] + 360, method='nearest'
+ )[0],
+ da.data[ii, jj, 0],
+ )
+ assert np.allclose(latlon, FP_CC_LAT_LON)
+
+ return da.compute()
+
+
 @pytest.fixture(scope='module')
 def presrat_params(tmpdir_factory, fp_fut_cc):
  """PresRat parameters for standard datasets
@@ -444,47 +465,20 @@ def test_presrat_transform(presrat_params, fut_cc):
  assert not np.allclose(data, corrected, equal_nan=False)
 
 
-def test_presrat_transform_nochanges(presrat_nochanges_params, fp_fut_cc_notrend):
+def test_presrat_transform_nochanges(
+ presrat_nochanges_params, fut_cc_notrend
+):
  """No changes if the three datasets are the same and no zeros"""
- # data = np.ones((*FP_CC_LAT_LON.shape[:-1], 3))
- # time = pd.to_datetime( ['2015-01-01 12:00:00', '2015-01-02 12:00:00', '2015-01-01 12:00:00'])
- breakpoint()
- ds = xr.open_dataset(fp_fut_cc_notrend)
- da = ds['rsds'].compute().transpose('lat', 'lon', 'time')
- # Unfortunatelly, _get_factors() assume latitude as descending
- da = da.sortby('lat', ascending=False)
- data = da.data
- time = pd.to_datetime(da.time)
- # latlon = np.stack(xr.broadcast(da["lat"], da["lon"] - 360), axis=-1).astype('float32')
- latlon = np.stack(np.meshgrid(da['lon'] - 360, da['lat']), axis=-1)[
- :, :, ::-1
- ].astype('float32')
- # da.sel(lat=latlon[ii,jj,0], method="nearest").sel(lon=latlon[ii,jj,1], method="nearest")[0] - data[ii,jj,0]
- for ii in range(4):
- for jj in range(4):
- np.allclose(
- da.sel(lat=latlon[ii, jj, 0], method='nearest').sel(
- lon=latlon[ii, jj, 1] + 360, method='nearest'
- )[0],
- data[ii, jj, 0],
- )
- np.allclose(latlon, FP_CC_LAT_LON)
+ data = fut_cc_notrend.values
+ time = pd.to_datetime(fut_cc_notrend.time)
+ latlon = np.stack(xr.broadcast(fut_cc_notrend["lat"], fut_cc_notrend["lon"] - 360), axis=-1).astype('float32')
 
- # data = np.ones((*FP_CC_LAT_LON.shape[:-1], 3))
- # time = pd.to_datetime(
- # ['2015-01-01 12:00:00', '2015-01-02 12:00:00', '2015-01-01 12:00:00']
- # )
  corrected = local_presrat_bc(
- data,
- time,
- latlon,
- 'ghi',
- 'rsds',
- presrat_nochanges_params,
+ data, time, latlon, 'ghi', 'rsds', presrat_nochanges_params
  )
 
- assert not np.isnan(corrected).all(), "Can't compare if only NaN"
- assert np.allclose(data, corrected, equal_nan=False)
+ assert np.isfinite(corrected).any(), "Can't compare if only NaN"
+ assert np.allclose(data, corrected, equal_nan=False), "This case shouldn't modify the data"
 
 
 def test_presrat_transform_nozerochanges(