Add hybrid method in appli

Author: AntSimi

src/py_eddy_tracker/appli/network.py

@@ -36,6 +36,11 @@ def build_network():
         action="store_true",
         help="If True, use intersection/little polygon, else intersection/union",
     )
+    parser.add_argument(
+        "--hybrid-area",
+        action="store_true",
+        help="If True, use minimal-area method if overlap is under min overlap, else intersection/union",
+    )
 
     parser.contour_intern_arg()
 
@@ -49,7 +54,7 @@ def build_network():
         memory=args.memory,
     )
     group = n.group_observations(
-        min_overlap=args.min_overlap, minimal_area=args.minimal_area
+        min_overlap=args.min_overlap, minimal_area=args.minimal_area, hybrid_area=args.hybrid_area
     )
     n.build_dataset(group).write_file(filename=args.out)
 
@@ -74,6 +79,11 @@ def divide_network():
         action="store_true",
         help="If True, use intersection/little polygon, else intersection/union",
     )
+    parser.add_argument(
+        "--hybrid-area",
+        action="store_true",
+        help="If True, use minimal-area method if overlap is under min overlap, else intersection/union",
+    )
     args = parser.parse_args()
     contour_name = TrackEddiesObservations.intern(args.intern, public_label=True)
     e = TrackEddiesObservations.load_file(
@@ -87,6 +97,7 @@ def divide_network():
             window=args.window,
             min_overlap=args.min_overlap,
             minimal_area=args.minimal_area,
+            hybrid_area=args.hybrid_area
         ),
     )
     n.write_file(filename=args.out)

src/py_eddy_tracker/observations/network.py

@@ -1913,21 +1913,14 @@ def group_translator(nb, duos):
                 apply_replace(translate, gr_i, gr_j)
         return translate
 
-    def group_observations(self, min_overlap=0.2, minimal_area=False):
+    def group_observations(self, min_overlap=0.2, minimal_area=False, **kwargs):
         """Store every interaction between identifications
 
-        Parameters
-        ----------
-        minimal_area : bool, optional
-            If True, function will compute intersection/little polygon, else intersection/union, by default False
+        :param bool minimal_area: If True, function will compute intersection/little polygon, else intersection/union, by default False
+        :param float min_overlap: minimum overlap area to associate observations, by default 0.2
 
-        min_overlap : float, optional
-            minimum overlap area to associate observations, by default 0.2
-
-        Returns
-        -------
-        TrackEddiesObservations
-            netcdf with interactions
+        :return: 
+        :rtype: TrackEddiesObservations
         """
 
         results, nb_obs = list(), list()
@@ -1945,9 +1938,9 @@ def group_observations(self, min_overlap=0.2, minimal_area=False):
                 ii, ij = bbox_intersection(xi, yi, xj, yj)
                 m = (
                     vertice_overlap(
-                        xi[ii], yi[ii], xj[ij], yj[ij], minimal_area=minimal_area
+                        xi[ii], yi[ii], xj[ij], yj[ij], minimal_area=minimal_area, min_overlap=min_overlap, **kwargs
                     )
-                    > min_overlap
+                    != 0
                 )
                 results.append((i, j, ii[m], ij[m]))
         if display_iteration:

src/py_eddy_tracker/observations/tracking.py

@@ -720,7 +720,7 @@ def get_previous_obs(
         time_ref,
         window,
         min_overlap=0.2,
-        minimal_area=False,
+        **kwargs,
     ):
         """Backward association of observations to the segments"""
         time_cur = int_(ids["time"][i_current])
@@ -737,10 +737,8 @@ def get_previous_obs(
                 continue
             c = zeros(len(xj))
             c[ij] = vertice_overlap(
-                xi[ii], yi[ii], xj[ij], yj[ij], minimal_area=minimal_area
+                xi[ii], yi[ii], xj[ij], yj[ij], min_overlap=min_overlap, **kwargs
             )
-            # We remove low overlap
-            c[c < min_overlap] = 0
             # We get index of maximal overlap
             i = c.argmax()
             c_i = c[i]
@@ -762,7 +760,7 @@ def get_next_obs(
         time_ref,
         window,
         min_overlap=0.2,
-        minimal_area=False,
+        **kwargs
     ):
         """Forward association of observations to the segments"""
         time_max = time_e.shape[0] - 1
@@ -782,10 +780,8 @@ def get_next_obs(
                 continue
             c = zeros(len(xj))
             c[ij] = vertice_overlap(
-                xi[ii], yi[ii], xj[ij], yj[ij], minimal_area=minimal_area
+                xi[ii], yi[ii], xj[ij], yj[ij], min_overlap=min_overlap, **kwargs
             )
-            # We remove low overlap
-            c[c < min_overlap] = 0
             # We get index of maximal overlap
             i = c.argmax()
             c_i = c[i]