Separate the construction of `traj_vert_ind`

Separate the construction of `traj_vert_ind` and the definition of
`traj_prop`. The motivation is to be able to create the files
`*traj*.json` for only a component of the graph, so that
`plot_traj.py` can plot the trajectories in a single component, with
different colors for different trajectories. A side benefit is that
the script `trajectories.py` becomes clearer. I have measured on the
global graph for 1993-2023 that this modification does not make a
significant change on the running time of the script.

Trajectories/trajectories.py

@@ -28,12 +28,11 @@ import numpy as np
 import util_eddies
 
 
-def new_traj(ind_traj, traj_prop, n, traj_vert_ind):
+def new_traj(ind_traj, traj_prop, n):
     """Assign new trajectory to vertex index n."""
 
     ind_traj += 1
     traj_prop[n] = ind_traj
-    traj_vert_ind.append([n])
     return ind_traj
 
 
@@ -84,16 +83,12 @@ g.vp["traj"] = traj_prop
 # the index in lists traj_vert_ind, traj_segm and expanded_traj.
 
 ind_traj = -1  # initialize index of trajectory
-
-traj_vert_ind = []
-# An element of traj_vert_ind is a trajectory, represented by a list
-# of vertex indices.
-
 in_deg_prop = g.degree_property_map("in")
 out_deg_prop = g.degree_property_map("out")
+my_sort = topology.topological_sort(g)
 
 # Loop to define traj_prop:
-for n in topology.topological_sort(g):
+for n in my_sort:
     # First, we check whether we have a phantom pattern. Phantom
     # eddies may appear in altimetric data because of
     # interpolation. In a phantom pattern, we have splitting
@@ -149,16 +144,8 @@ for n in topology.topological_sort(g):
                             traj_prop[pred[1]],
                             traj_prop[pred[0]],
                         )
-                        (
-                            traj_vert_ind[traj_prop[pred[0]]][-1],
-                            traj_vert_ind[traj_prop[pred[1]]][-1],
-                        ) = (
-                            traj_vert_ind[traj_prop[pred[1]]][-1],
-                            traj_vert_ind[traj_prop[pred[0]]][-1],
-                        )
 
                     traj_prop[n] = traj_prop[n1]
-                    traj_vert_ind[traj_prop[n1]].append(n)
 
     if traj_prop[n] == -1:
         if in_deg_prop[n] >= 1:
@@ -173,22 +160,35 @@ for n in topology.topological_sort(g):
 
             if closest_succ[closest_pred] == n:
                 # Assign to n the trajectory of closest_pred. This
-                # means updating traj_prop and
-                # traj_vert_ind. closest_pred is already in a
-                # trajectory, traj_prop[closest_pred]] != - 1. We
+                # means updating traj_prop. closest_pred is already in
+                # a trajectory, traj_prop[closest_pred]] != - 1. We
                 # extend the trajectory of closest_pred forward.
                 traj_prop[n] = traj_prop[closest_pred]
-                traj_vert_ind[traj_prop[n]].append(n)
             else:
-                ind_traj = new_traj(ind_traj, traj_prop, n, traj_vert_ind)
+                ind_traj = new_traj(ind_traj, traj_prop, n)
         else:
-            ind_traj = new_traj(ind_traj, traj_prop, n, traj_vert_ind)
+            ind_traj = new_traj(ind_traj, traj_prop, n)
 
     # assert traj_prop[n] != - 1
 
 t1 = time.perf_counter()
 timings_file.write(f"traj_prop defined in {t1 - t0:.0f} s\n")
 t0 = t1
+
+# Construct traj_vert_ind from traj_prop:
+
+traj_vert_ind = {}
+
+for n in my_sort:
+    if traj_prop[n] in traj_vert_ind:
+        traj_vert_ind[traj_prop[n]].append(n)
+    else:
+        traj_vert_ind[traj_prop[n]] = [n]
+
+traj_vert_ind = [traj_vert_ind[t] for t in range(len(traj_vert_ind))]
+# An element of traj_vert_ind is a trajectory, represented by a list
+# of vertex indices.
+
 print("Number of trajectories: ", len(traj_vert_ind))
 
 # We have trajectories as lists of vertex indices. Now construct