[COORDINATES] add spatial_index attributes. add test accordingly.

spatio_temporal_dataset/coordinates/abstract_coordinates.py

@@ -168,6 +168,9 @@ class AbstractCoordinates(object):
         else:
             return self.df_coordinates(split).loc[:, self.coordinates_spatial_names].drop_duplicates()
 
+    def spatial_index(self, split: Split = Split.all) -> pd.Index:
+        return self.df_spatial_coordinates(split).index
+
     # Temporal attributes
 
     @property

spatio_temporal_dataset/coordinates/spatio_temporal_coordinates/abstract_spatio_temporal_coordinates.py

@@ -17,12 +17,15 @@ class AbstractSpatioTemporalCoordinates(AbstractCoordinates):
         return super().from_df_and_slicer(df, SpatioTemporalSlicer, train_split_ratio)
 
     @classmethod
-    def generate_df_spatio_temporal(cls, df_spatial, nb_steps):
-        # df_temporal = ConsecutiveTemporalCoordinates.df_temporal(nb_temporal_steps=nb_temporal_steps)
+    def from_df_spatial_and_nb_steps(cls, df_spatial, nb_steps, train_split_ratio: float = None, start=0):
         df_time_steps = []
+        index_type = type(df_spatial.index[0])
         for t in range(nb_steps):
             df_time_step = df_spatial.copy()
-            df_time_step[cls.COORDINATE_T] = t
+            df_time_step[cls.COORDINATE_T] = start + t
+            index_suffix = index_type(t + len(df_spatial))
+            time_step_index = [i + index_suffix for i in df_spatial.index] if t > 0 else df_spatial.index
+            df_time_step.index = time_step_index
             df_time_steps.append(df_time_step)
-        df_time_steps = pd.concat(df_time_steps, ignore_index=True)
-        return df_time_steps
+        df_time_steps = pd.concat(df_time_steps)
+        return cls.from_df(df=df_time_steps, train_split_ratio=train_split_ratio)
\ No newline at end of file

spatio_temporal_dataset/coordinates/spatio_temporal_coordinates/generated_spatio_temporal_coordinates.py

@@ -15,8 +15,7 @@ class GeneratedSpatioTemporalCoordinates(AbstractSpatioTemporalCoordinates):
         assert cls.SPATIAL_COORDINATES_CLASS is not None
         assert hasattr(cls.SPATIAL_COORDINATES_CLASS, 'df_spatial')
         df_spatial = cls.SPATIAL_COORDINATES_CLASS.df_spatial(nb_points=nb_points)
-        df_time_steps = cls.generate_df_spatio_temporal(df_spatial, nb_steps)
-        return cls.from_df(df=df_time_steps, train_split_ratio=train_split_ratio)
+        return cls.from_df_spatial_and_nb_steps(df_spatial, nb_steps, train_split_ratio)
 
 
 class UniformSpatioTemporalCoordinates(GeneratedSpatioTemporalCoordinates):

test/test_spatio_temporal_dataset/test_coordinates.py

@@ -4,8 +4,9 @@ from collections import Counter, OrderedDict
 
 from spatio_temporal_dataset.coordinates.abstract_coordinates import AbstractCoordinates
 from spatio_temporal_dataset.coordinates.spatio_temporal_coordinates.generated_spatio_temporal_coordinates import \
-    UniformSpatioTemporalCoordinates
-from spatio_temporal_dataset.coordinates.spatial_coordinates.coordinates_1D import UniformSpatialCoordinates
+    UniformSpatioTemporalCoordinates, GeneratedSpatioTemporalCoordinates
+from spatio_temporal_dataset.coordinates.spatial_coordinates.coordinates_1D import UniformSpatialCoordinates, \
+    LinSpaceSpatialCoordinates
 from spatio_temporal_dataset.coordinates.spatial_coordinates.alps_station_2D_coordinates import \
     AlpsStation2DCoordinatesBetweenZeroAndOne
 from spatio_temporal_dataset.coordinates.spatial_coordinates.alps_station_3D_coordinates import \
@@ -52,6 +53,23 @@ class SpatioTemporalCoordinates(unittest.TestCase):
         good_count = c == Counter([2, 2, 2, 2]) or c == Counter([0, 0, 4, 4])
         self.assertTrue(good_count)
 
+    def test_unique_spatio_temporal_index_and_matching_spatial_index(self):
+        spatial_coordinates = LinSpaceSpatialCoordinates.from_nb_points(self.nb_points)
+        spatial_indexes = [[10, 11, 12, 13], ['a', 'b', 'c', 'd']]
+        for spatial_index in spatial_indexes:
+            spatial_coordinates.df_all_coordinates.index = spatial_index
+            df_spatial = spatial_coordinates.df_spatial_coordinates()
+            coordinates = GeneratedSpatioTemporalCoordinates.from_df_spatial_and_nb_steps(df_spatial=df_spatial,
+                                                                                          nb_steps=self.nb_steps)
+
+            # the uniqueness of each spatio temporal index is not garanteed by the current algo
+            # it will work in classical cases, and raise an assert when uniqueness is needed (when using a slicer)
+            index1 = pd.Series(spatial_coordinates.spatial_index())
+            index2 = pd.Series(coordinates.spatial_index())
+            ind = index1 != index2  # type: pd.Series
+            self.assertEqual(sum(ind), 0, msg="spatial_coordinates:\n{} \n!= spatio_temporal_coordinates \n{}".
+                             format(index1.loc[ind], index2.loc[ind]))
+
     def test_ordered_coordinates(self):
         # Order coordinates, to ensure that the first dimension/the second dimension and so on..
         # Always are in the same order to a given type (e.g. spatio_temporal= of coordinates