Merge branch 'master' into feat/180-update-geo-dependencies

docs/user_guide/user_guide.rst

@@ -123,7 +123,7 @@ Initialization file templates
     polygon = map.geojson			# <name + file extension of the geojson polygon file in the static/network folder> / None
     network_type = drive			# drive / walk / bike / drive_service / all
     road_types = motorway,motorway_link,trunk,trunk_link,primary, primary_link,secondary,secondary_link,tertiary,tertiary_link
-    save_shp = True				# True / False
+    save_gpkg = True				# True / False
 
     [origins_destinations]
     origins = origins.shp 			# <file name> / None
@@ -159,7 +159,7 @@ Initialization file templates
   name = single link redundancy test
   analysis = single_link_redundancy
   weighing = distance
-  save_shp = True
+  save_gpkg = True
   save_csv = True
 
   [analysis2]
@@ -168,14 +168,14 @@ Initialization file templates
   aggregate_wl = max
   threshold = 0.5
   weighing = distance
-  save_shp = True
+  save_gpkg = True
   save_csv = True
 
   [analysis3]
   name = optimal origin dest test
   analysis = optimal_route_origin_destination
   weighing = distance
-  save_shp = True
+  save_gpkg = True
   save_csv = True
 
   [analysis4]
@@ -184,7 +184,7 @@ Initialization file templates
   aggregate_wl = max
   threshold = 0.5
   weighing = distance
-  save_shp = True
+  save_gpkg = True
   save_csv = False
 
   [analysis5]
@@ -193,7 +193,7 @@ Initialization file templates
   aggregate_wl = max
   threshold = 0.5
   weighing = distance
-  save_shp = True
+  save_gpkg = True
   save_csv = True
 
   [analysis6]
@@ -204,6 +204,6 @@ Initialization file templates
   weighing = length
   buffer_meters = 40
   category_field_name = category
-  save_shp = True
+  save_gpkg = True
   save_csv = True
 

examples/example_origin_destination_analysis.ipynb

@@ -4133,7 +4133,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.11"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,

examples/example_ra2ce_basics.ipynb

@@ -864,7 +864,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.11"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,

examples/example_single_link_redundancy.ipynb

@@ -2067,7 +2067,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.11"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,

examples/pizza_course_material_DIY.ipynb

@@ -147,7 +147,7 @@
     "**polygon = ...<br>**\n",
     "network_type = drive<br>\n",
     "**road_types = ...<br>**\n",
-    "save_shp = True<br>\n",
+    "save_gpkg = True<br>\n",
     "<br>"
    ]
   },
@@ -301,7 +301,7 @@
     "name = beira_redundancy <br>\n",
     "analysis = single_link_redundancy <br>\n",
     "weighing = distance <br>\n",
-    "save_shp = True <br>\n",
+    "save_gpkg = True <br>\n",
     "save_csv = True <br>"
    ]
   },

ra2ce/analyses/direct/analyses_direct.py

@@ -75,8 +75,8 @@ def execute(self):
                 gdf = []
 
             output_path = self.config["output"] / analysis["analysis"]
-            if analysis["save_shp"]:
-                shp_path = output_path / (analysis["name"].replace(" ", "_") + ".shp")
+            if analysis["save_gpkg"]:
+                shp_path = output_path / (analysis["name"].replace(" ", "_") + ".gpkg")
                 save_gdf(gdf, shp_path)
             if analysis["save_csv"]:
                 csv_path = output_path / (analysis["name"].replace(" ", "_") + ".csv")
@@ -187,7 +187,7 @@ def effectiveness_measures(self, analysis):
         else:
             df = em.load_table(
                 self.config["input"] / "direct",
-                analysis["file_name"].replace(".shp", ".csv"),
+                analysis["file_name"].replace(".gpkg", ".csv"),
             )
 
         df = em.calculate_strategy_effectiveness(df, effectiveness_dict)

ra2ce/analyses/direct/cost_benefit_analysis.py

@@ -115,7 +115,7 @@ def create_feature_table(file_path: Path):
 
         # save as csv
         path, file = os.path.split(file_path)
-        df.to_csv(os.path.join(path, file.replace(".shp", ".csv")), index=False)
+        df.to_csv(os.path.join(path, file.replace(".gpkg", ".csv")), index=False)
         return df
 
     @staticmethod

ra2ce/analyses/indirect/analyses_indirect.py

@@ -510,7 +510,31 @@ def multi_link_losses(self, gdf, analysis):
         aggregated_results = pd.concat(results, ignore_index=True)
         return aggregated_results
 
-    def _get_origin_destination_pairs(self, graph):
+    @staticmethod
+    def extract_od_nodes_from_graph(
+        graph: nx.classes.MultiGraph,
+    ) -> list[tuple[str, str]]:
+        """
+        Extracts all Origin - Destination nodes from the graph, prevents from entries
+        with list of nodes for a node.
+
+        Args:
+            graph (nx.classes.MultiGraph): Graph containing origin-destination nodes.
+
+        Returns:
+            list[tuple[str, str]]]: List containing tuples of origin - destination node combinations.
+        """
+        _od_nodes = []
+        for n, v in graph.nodes(data=True):
+            if "od_id" not in v:
+                continue
+            _o_node_list = list(map(lambda x: (n, x), v["od_id"].split(",")))
+            _od_nodes.extend(_o_node_list)
+        return _od_nodes
+
+    def _get_origin_destination_pairs(
+        self, graph: nx.classes.MultiGraph
+    ) -> list[tuple[int, str], tuple[int, str]]:
         od_path = self.config["static"].joinpath(
             "output_graph", "origin_destination_table.feather"
         )
@@ -520,7 +544,7 @@ def _get_origin_destination_pairs(self, graph):
             for a in od.loc[od["o_id"].notnull(), "o_id"]
             for b in od.loc[od["d_id"].notnull(), "d_id"]
         ]
-        all_nodes = [(n, v["od_id"]) for n, v in graph.nodes(data=True) if "od_id" in v]
+        all_nodes = self.extract_od_nodes_from_graph(graph)
         od_nodes = []
         for aa, bb in od_pairs:
             # it is possible that there are multiple origins/destinations at the same 'entry-point' in the road
@@ -542,7 +566,7 @@ def _get_origin_destination_pairs(self, graph):
 
     def optimal_route_origin_destination(
         self, graph: nx.classes.MultiGraph, analysis: dict
-    ):
+    ) -> gpd.GeoDataFrame:
         # create list of origin-destination pairs
         od_nodes = self._get_origin_destination_pairs(graph)
         pref_routes = find_route_ods(graph, od_nodes, analysis["weighing"])
@@ -754,10 +778,8 @@ def multi_link_origin_destination_regional_impact(self, gdf_ori):
         gdf_ori_ = gdf_ori.copy()
 
         # read origin points
-        origin_fn = (
-            Path(self.config["static"])
-            / "output_graph"
-            / "origin_destination_table.gpkg"
+        origin_fn = Path(self.config["static"]).joinpath(
+            "output_graph", "origin_destination_table.gpkg"
         )
         origin = gpd.read_file(origin_fn, engine="pyogrio")
         index = [type(x) == str for x in origin["o_id"]]
@@ -892,7 +914,7 @@ def multi_link_isolated_locations(
             results_hz_roads.to_file(
                 self.config["output"]
                 / analysis["analysis"]
-                / f"flooded_and_isolated_roads_{hazard_name}.shp"
+                / f"flooded_and_isolated_roads_{hazard_name}.gpkg"
             )
 
             # relate the locations to network disruption due to hazard by spatial overlay
@@ -1008,7 +1030,7 @@ def execute(self):
             opt_routes = None
             output_path = self.config["output"].joinpath(analysis["analysis"])
 
-            def _save_shp_analysis(
+            def _save_gpkg_analysis(
                 base_graph,
                 to_save_gdf: List[gpd.GeoDataFrame],
                 to_save_gdf_names: List[str],
@@ -1137,11 +1159,11 @@ def _save_shp_analysis(
                     opt_routes,
                     destinations,
                 ) = analyzer.optimal_route_origin_closest_destination()
-                if analysis["save_shp"]:
+                if analysis["save_gpkg"]:
                     # Save the GeoDataFrames
                     to_save_gdf = [destinations, opt_routes]
                     to_save_gdf_names = ["destinations", "optimal_routes"]
-                    _save_shp_analysis(base_graph, to_save_gdf, to_save_gdf_names)
+                    _save_gpkg_analysis(base_graph, to_save_gdf, to_save_gdf_names)
 
                 if analysis["save_csv"]:
                     csv_path = output_path / (
@@ -1191,7 +1213,7 @@ def _save_shp_analysis(
                     ) = analyzer.multi_link_origin_closest_destination()
                     opt_routes_without_hazard = gpd.GeoDataFrame()
 
-                if analysis["save_shp"]:
+                if analysis["save_gpkg"]:
                     # Save the GeoDataFrames
                     to_save_gdf = [
                         origins,
@@ -1205,7 +1227,7 @@ def _save_shp_analysis(
                         "optimal_routes_without_hazard",
                         "optimal_routes_with_hazard",
                     ]
-                    _save_shp_analysis(base_graph, to_save_gdf, to_save_gdf_names)
+                    _save_gpkg_analysis(base_graph, to_save_gdf, to_save_gdf_names)
                 if analysis["save_csv"]:
                     csv_path = output_path / (
                         analysis["name"].replace(" ", "_") + "_destinations.csv"
@@ -1253,7 +1275,7 @@ def _save_shp_analysis(
 
             if not gdf.empty:
                 # Not for all analyses a gdf is created as output.
-                if analysis["save_shp"]:
+                if analysis["save_gpkg"]:
                     gpkg_path = output_path.joinpath(
                         analysis["name"].replace(" ", "_") + ".gpkg"
                     )
@@ -1285,8 +1307,7 @@ def save_gdf(gdf: gpd.GeoDataFrame, save_path: Path):
 
     Arguments:
         gdf [geodataframe]: geodataframe object to be converted
-        edge_shp [str]: output path including extension for edges shapefile
-        node_shp [str]: output path including extension for nodes shapefile
+        save_path [str]: output path including extension for edges shapefile
     Returns:
         None
     """
@@ -1302,7 +1323,9 @@ def save_gdf(gdf: gpd.GeoDataFrame, save_path: Path):
 
 
 def find_route_ods(
-    graph: nx.classes.MultiGraph, od_nodes: list[tuple[tuple[int, str]]], weighing: str
+    graph: nx.classes.MultiGraph,
+    od_nodes: list[tuple[tuple[int, str], tuple[int, str]]],
+    weighing: str,
 ) -> gpd.GeoDataFrame:
     # create the routes between all OD pairs
     (
@@ -1374,6 +1397,11 @@ def find_route_ods(
         geometry="geometry",
         crs="epsg:4326",
     )
+    # Remove potential duplicates (o, d node) with a different Origin name.
+    _duplicate_columns = ["o_node", "d_node", "destination", "length", "geometry"]
+    pref_routes = pref_routes.drop_duplicates(
+        subset=_duplicate_columns, keep="first"
+    ).reset_index(drop=True)
     return pref_routes
 
 

ra2ce/analyses/indirect/traffic_analysis/traffic_analysis_base.py

@@ -21,6 +21,7 @@
 
 import ast
 import itertools
+import logging
 import operator
 from abc import ABC, abstractmethod
 from typing import Any
@@ -60,9 +61,15 @@ def optimal_route_od_link(
                 opt_path = self._get_opt_path_values(o_node, d_node)
                 for u_node, v_node in itertools.pairwise(opt_path):
                     _nodes_key_name = self._get_node_key(u_node, v_node)
-                    _calculated_traffic = self._calculate_origin_node_traffic(
+                    if "," in o_node:
+                        logging.error(
+                            "List of nodes as 'origin node' is not accepted and will be skipped."
+                        )
+                        continue
+                    _calculated_traffic = self._get_accumulated_traffic_from_node(
                         o_node, count_destination_nodes
                     )
+
                     if "," in d_node:
                         _calculated_traffic *= len(d_node.split(","))
 
@@ -102,53 +109,6 @@ def _get_recorded_traffic_in_node(
             / count_destination_nodes
         )
 
-    def _get_accumulated_traffic_from_node_list(
-        self,
-        nodes_list: list[str],
-        count_destination_nodes: int,
-    ) -> AccumulatedTraffic:
-        # TODO: This algorithm is not entirely clear (increase decrease of variable _intermediate_nodes)
-        # When do we want to 'multiply' the accumulated values?
-        # When do we want to 'add' the accumulated values?
-        _accumulated_traffic = AccumulatedTraffic(
-            utilitarian=1, egalitarian=1, prioritarian=1
-        )
-        _intermediate_nodes = 0
-        for _node in nodes_list:
-            if self.destinations_names in _node:
-                _intermediate_nodes -= 1
-                continue
-            _node_traffic = self._get_accumulated_traffic_from_node(
-                _node, count_destination_nodes
-            )
-            # Multiplication ( 'operator.mul' or *) or Addition ( 'operator.add' or +) operations to acummulate traffic.
-            # This will trigger the overloaded methods in `AccumulatedTraffic`.
-            _acummulated_operator = (
-                operator.mul if _intermediate_nodes == 0 else operator.add
-            )
-            _accumulated_traffic = _acummulated_operator(
-                _accumulated_traffic, _node_traffic
-            )
-            _intermediate_nodes += 1
-
-        # Set the remainig values
-        _accumulated_traffic.egalitarian = len(
-            list(filter(lambda x: self.destinations_names not in x, nodes_list))
-        )
-        return _accumulated_traffic
-
-    def _calculate_origin_node_traffic(
-        self,
-        origin_node: str,
-        total_d_nodes: int,
-    ) -> AccumulatedTraffic:
-        if "," in origin_node:
-            return self._get_accumulated_traffic_from_node_list(
-                origin_node.split(","), total_d_nodes
-            )
-
-        return self._get_accumulated_traffic_from_node(origin_node, total_d_nodes)
-
     @abstractmethod
     def _get_accumulated_traffic_from_node(
         self, target_node: str, total_d_nodes: int

ra2ce/graph/exporters/geodataframe_network_exporter.py

@@ -29,8 +29,8 @@
 
 
 class GeoDataFrameNetworkExporter(NetworkExporterBase):
-    def export_to_shp(self, output_dir: Path, export_data: gpd.GeoDataFrame) -> None:
-        _output_shp_path = output_dir / (self._basename + ".shp")
+    def export_to_gpkg(self, output_dir: Path, export_data: gpd.GeoDataFrame) -> None:
+        _output_shp_path = output_dir / (self._basename + ".gpkg")
         export_data.to_file(
             _output_shp_path, index=False
         )  # , encoding='utf-8' -Removed the encoding type because this causes some shapefiles not to save.

ra2ce/graph/exporters/multi_graph_network_exporter.py

@@ -35,7 +35,7 @@
 class MultiGraphNetworkExporter(NetworkExporterBase):
     pickle_path: Optional[Path]
 
-    def export_to_shp(self, output_dir: Path, export_data: MULTIGRAPH_TYPE) -> None:
+    def export_to_gpkg(self, output_dir: Path, export_data: MULTIGRAPH_TYPE) -> None:
         if not output_dir.is_dir():
             output_dir.mkdir(parents=True)
 
@@ -46,7 +46,7 @@ def export_to_shp(self, output_dir: Path, export_data: MULTIGRAPH_TYPE) -> None:
             output_dir / (self._basename + "_nodes.gpkg"),
         )
         logging.info(
-            f"Saved {self._basename + '_edges.shp'} and {self._basename + '_nodes.shp'} in {output_dir}."
+            f"Saved {self._basename + '_edges.gpkg'} and {self._basename + '_nodes.gpkg'} in {output_dir}."
         )
 
     def export_to_pickle(self, output_dir: Path, export_data: MULTIGRAPH_TYPE) -> None: