some minor changes

config.py

@@ -36,7 +36,7 @@
 save_int_forcing = True
 # If restart_forcing, the forcing will be read from the intermediate files of
 # a previous run
-restart_forcing = False
+restart_forcing = True
 # if real_time, it will be possible to run MuSA from initial condition files,
 # These files are ensemble objects, generated by a previous run, or by a
 # very advanced user. Init files are saved in real_time_restart_path,
@@ -123,9 +123,9 @@
 nprocess = 8
 
 # number of cells to be solved per processor at each iteration
-cells_per_process = None
+cells_per_process = None # None is 1
 # maximun number of seconds each pool is killed before try again
-timeout = None
+timeout = None # None is inf
 
 aws_lat = 4735225.54  # Latitude in case of point_scale
 aws_lon = 710701.28   # Longitude in case of point_scale
@@ -149,7 +149,7 @@
 dist_algo = 'euclidean'
 # distance_mat_calc Enables calculating the distance matrix, iterativelly
 # as an sparse distance matrix, using KDtree or in the regular way
-# (memory consuming). It is slow but can save a lot of memory
+# (memory consuming).
 distance_mat_calc = 'Regular'  # Regular, Sparse, KDtree
 # Optionally perform dimension reduction to try to avoid nonPD
 dimension_reduction = 'None'  # LMDS, PCA or None

main.py

@@ -164,8 +164,8 @@ def MuSA():
                     continue
 
                 # create prior Ensembles
-                inputs = [grid[ids, 0], grid[ids, 1],
-                          [ini_DA_window] * grid.shape[0],
+                inputs = [list(grid[ids, 0]), list(grid[ids, 1]),
+                          [ini_DA_window] * sum(ids),
                           [step] * sum(ids),
                           [gsc_count] * sum(ids)]
 
@@ -181,7 +181,7 @@ def MuSA():
                     # add info to log
                     logging.info(f'step: {step} - j: {j}')
 
-                    inputs = [grid[ids, 0], grid[ids, 1],
+                    inputs = [list(grid[ids, 0]), list(grid[ids, 1]),
                               [step] * sum(ids), [j]*sum(ids)]
 
                     ifn.safe_pool(spM.spatial_assim, inputs, nprocess)
@@ -230,10 +230,10 @@ def MuSA():
                     continue
 
                 # create prior Ensembles
-                inputs = [grid[:, 0], grid[:, 1],
-                          [ini_DA_window] * grid.shape[0],
-                          [step] * grid.shape[0],
-                          [gsc_count] * grid.shape[0]]
+                inputs = [list(grid[ids, 0]), list(grid[ids, 1]),
+                          [ini_DA_window] * sum(ids),
+                          [step] * sum(ids),
+                          [gsc_count] * sum(ids)]
 
                 ifn.safe_pool(spM.create_ensemble_cell, inputs, nprocess)
 
@@ -247,7 +247,7 @@ def MuSA():
                     # add info to log
                     logging.info(f'step: {step} - j: {j}')
 
-                    inputs = [grid[:, 0], grid[:, 1],
+                    inputs = [list(grid[:, 0]), list(grid[:, 1]),
                               [step] * grid.shape[0],
                               [j] * grid.shape[0]]
 

modules/fsm_tools.py

@@ -212,6 +212,11 @@ def model_compile_HPC(HPC_task_id):
     fsm_path = cfg.fsm_src_path
     file_name = os.path.join(fsm_path, "FSM2")
 
+    # if binary exist, pass to avoid breaking HPC job arrays
+    fsm_filename = os.path.join(cfg.fsm_src_path, "FSM2")
+    if os.path.isfile(fsm_filename):
+        return None
+
     if HPC_task_id == 0:
         model_compile()
     else:

modules/internal_fns.py

@@ -47,7 +47,12 @@ def pre_cheks():
                         'supports simulations generated from '
                         'Spatial_propagation simulation.')
     if cfg.timeout and cfg.MPI:
-        warnings.warn("timeout is ignored  MPI")
+        warnings.warn("timeout is ignored with MPI")
+
+    if cfg.parallelization == "HPC.array" and cfg.numerical_model == "FSM2":
+        fsm_filename = os.path.join(cfg.fsm_src_path, "FSM2")
+        if os.path.isfile(fsm_filename):
+            warnings.warn("FSM binary exists, reusing compile options")
 
 
 def last_line(filename):

modules/spatialMuSA.py

@@ -152,6 +152,7 @@ def get_topo_arr():
     dem = nc.Dataset(dem)
 
     dem_arr = dem.variables[nc_dem_varname][:]
+    dem_arr = dem_arr.filled(np.nan)  # from numpy.ma to numpy
     dem_arr = fill_nan_arr(dem_arr)
 
     # Grid spacing
@@ -559,6 +560,7 @@ def get_rho(prior_id):
             # NOTE: this masks the current cell, but the current cell
             # is added anyway when the neig is created
             tmp_dis[tmp_dis == 0.] = np.nan
+            tmp_dis[n] = 0. # put 0 in diagonal
 
             distnc[:, n] = tmp_dis
         f.close()