fix tests by removing redundant statement and add print statements

pysteps/blending/steps.py

@@ -523,26 +523,8 @@ def forecast(
         precip, velocity, ar_order, xy_coords, extrapolator, extrap_kwargs, num_workers
     )
 
-    # 2. Initialize the noise method
-    np.random.seed(seed)
-    pp, generate_noise, noise_std_coeffs = _init_noise(
-        precip,
-        precip_thr,
-        n_cascade_levels,
-        bp_filter,
-        decompositor,
-        fft,
-        noise_method,
-        noise_kwargs,
-        noise_stddev_adj,
-        measure_time,
-        num_workers,
-        seed,
-    )
-
-    # 3. Perform the cascade decomposition for the input precip fields and
+    # 2. Perform the cascade decomposition for the input precip fields and
     # and, if necessary, for the (NWP) model fields
-
     # 2.1 Compute the cascade decompositions of the input precipitation fields
     (
         precip_cascade,
@@ -574,7 +556,9 @@ def forecast(
     zero_precip_radar = blending.utils.check_norain(precip, precip_thr, norain_thr)
     # The norain fraction threshold used for nwp is the default value of 0.0,
     # since nwp does not suffer from clutter.
-    zero_model_fields = blending.utils.check_norain(precip_models_pm, precip_thr)
+    zero_model_fields = blending.utils.check_norain(
+        precip_models_pm, precip_thr, norain_thr
+    )
 
     # 2.3.1 If precip is below the norain threshold and precip_models_pm is zero,
     # we consider it as no rain in the domain.

pysteps/blending/utils.py

@@ -525,6 +525,7 @@ def load_NWP(input_nc_path_decomp, input_path_velocities, start_time, n_timestep
         # Append the output list
         R_d.append(decomp_dict_)
 
+    ncf_decomp.close()
     return R_d, uv
 
 
@@ -552,4 +553,6 @@ def check_norain(precip_arr, precip_thr=None, norain_thr=0.0):
         precip_thr = np.nanmin(precip_arr)
     rain_pixels = precip_arr[precip_arr > precip_thr]
     norain = rain_pixels.size / precip_arr.size <= norain_thr
+    print("Field is below no rain fraction :", norain)
+    print("rain fraction is :", rain_pixels.size / precip_arr.size)
     return norain