test: We should observe a tendency on predicted output

Validate two aspects:
- We should be able to run a forward pass in a unbiased data.
- The bias trend should be observed in the predicted output.

tests/bias/test_qdm_bias_correction.py

@@ -364,8 +364,12 @@ def test_bc_trend_same_hist(tmp_path, fp_fut_cc, dist_params):
 
 
 def test_fwp_integration(tmp_path, fp_fut_cc):
- """Test the integration of the bias correction method into the forward pass
- framework"""
+ """Integration of the bias correction method into the forward pass
+
+ Validate two aspects:
+ - We should be able to run a forward pass with unbiased data.
+ - The bias trend should be observed in the predicted output.
+ """
  fp_gen = os.path.join(CONFIG_DIR, 'spatiotemporal/gen_3x_4x_2f.json')
  fp_disc = os.path.join(CONFIG_DIR, 'spatiotemporal/disc.json')
  features = ['U_100m', 'V_100m']
@@ -383,11 +387,11 @@ def test_fwp_integration(tmp_path, fp_fut_cc):
  params = {}
  with xr.open_dataset(os.path.join(TEST_DATA_DIR, 'ua_test.nc')) as ds:
  params['bias_U_100m_params'] = ds['ua'].quantile(quantiles).to_numpy()
- params['base_Uref_100m_params'] = params['bias_U_100m_params'] - 1
+ params['base_Uref_100m_params'] = params['bias_U_100m_params'] - 2.72
  params['bias_fut_U_100m_params'] = params['bias_U_100m_params']
  with xr.open_dataset(os.path.join(TEST_DATA_DIR, 'va_test.nc')) as ds:
  params['bias_V_100m_params'] = ds['va'].quantile(quantiles).to_numpy()
- params['base_Vref_100m_params'] = params['bias_V_100m_params'] + 1
+ params['base_Vref_100m_params'] = params['bias_V_100m_params'] + 2.72
  params['bias_fut_V_100m_params'] = params['bias_V_100m_params']
 
  lat_lon = DataHandlerNCforCC(input_files, features=[], target=target,
@@ -458,10 +462,13 @@ def test_fwp_integration(tmp_path, fp_fut_cc):
  bias_correct_kwargs=bias_correct_kwargs)
 
  for ichunk in range(strat.chunks):
-
  fwp = ForwardPass(strat, chunk_index=ichunk)
  bc_fwp = ForwardPass(bc_strat, chunk_index=ichunk)
 
  delta = bc_fwp.input_data - fwp.input_data
- assert np.allclose(delta[..., 0], -1, atol=1e-03), "U reference offset is -1"
- assert np.allclose(delta[..., 1], 1, atol=1e-03), "V reference offset is 1"
+ assert np.allclose(delta[..., 0], -2.72, atol=1e-03), "U reference offset is -1"
+ assert np.allclose(delta[..., 1], 2.72, atol=1e-03), "V reference offset is 1"
+
+ delta = bc_fwp.run_chunk() - fwp.run_chunk()
+ assert delta[..., 0].mean() < 0, "Predicted U should trend <0"
+ assert delta[..., 1].mean() > 0, "Predicted V should trend >0"