Point multibuffer function

geest/core/multibuffer_point.py

@@ -0,0 +1,212 @@
+from qgis.core import (
+    QgsVectorLayer,
+    QgsField,
+    QgsFeatureRequest,
+    QgsProcessingFeedback,
+    QgsCoordinateReferenceSystem,
+    QgsProcessingException,
+    edit,
+)
+from PyQt5.QtCore import QVariant
+import processing
+
+
+class MultiBufferCreator:
+    def __init__(self, distance_list, subset_size=5):
+        """
+        Initialize the MultiBufferCreator class.
+
+        :param distance_list: List of buffer distances (in meters or seconds if using time-based buffers)
+        :param subset_size: Number of features to process in each subset
+        """
+        self.distance_list = distance_list
+        self.subset_size = subset_size
+
+    # TODO: refactor function
+    def create_multibuffers(
+        self,
+        point_layer,
+        output_path,
+        mode="driving-car",
+        measurement="distance",
+        crs="EPSG:4326",
+    ):
+        """
+        Creates multibuffers for each point in the input point layer.
+
+        :param point_layer: QgsVectorLayer containing point features
+        :param output_path: Path to save the merged output layer
+        :param mode: Mode of travel for ORS API (e.g., 'driving-car')
+        :param measurement: 'distance' or 'time'
+        :param crs: Coordinate reference system (default is WGS84)
+        :return: QgsVectorLayer containing the buffers as polygons
+        """
+        # Prepare to collect intermediate layers
+        temp_layers = []
+        features = list(point_layer.getFeatures())
+        total_features = len(features)
+
+        # Process features in subsets to handle large datasets
+        for i in range(0, total_features, self.subset_size):
+            subset_features = features[i : i + self.subset_size]
+            # Create a temporary layer for the subset
+            subset_layer = QgsVectorLayer(f"Point?crs={crs}", f"subset_{i}", "memory")
+            subset_layer_data = subset_layer.dataProvider()
+            subset_layer_data.addAttributes(point_layer.fields())
+            subset_layer.updateFields()
+            subset_layer_data.addFeatures(subset_features)
+
+            # Prepare parameters for ORS isochrones tool
+
+            params = {
+                "INPUT_PROVIDER": 0,  # 0 for OpenRouteService
+                "INPUT_PROFILE": mode,
+                "INPUT_POINT_LAYER": subset_layer,
+                "INPUT_FIELD": "",  # No specific field for ranges
+                "INPUT_METRIC": 0 if measurement == "distance" else 1,
+                "INPUT_UNITS": 0,  # 0 for meters/seconds
+                "INPUT_RANGES": ",".join(map(str, self.distance_list)),
+                "INPUT_DATE_TIME": None,
+                "INPUT_INTERVAL": None,
+                "INPUT_SMOOTHING": None,
+                "INPUT_SRID": "",
+                "LOCATION_TYPE": 0,
+                "INPUT_AVOID_FEATURES": "",
+                "INPUT_AVOID_BORDERS": "",
+                "INPUT_AVOID_COUNTRIES": "",
+                "INPUT_AVOID_POLYGONS": "",
+                "OUTPUT": "memory:",
+            }
+
+            try:
+                # Run the ORS isochrones tool
+                result = processing.run(
+                    "ORS Tools:isochrones_from_layer",
+                    params,
+                    feedback=QgsProcessingFeedback(),
+                )
+                isochrone_layer = result["OUTPUT"]
+                temp_layers.append(isochrone_layer)
+
+                # Provide progress feedback
+                print(
+                    f"Processed subset {i + 1} to {min(i + self.subset_size, total_features)} of {total_features}"
+                )
+
+            except QgsProcessingException as e:
+                print(
+                    f"Error processing subset {i + 1} to {min(i + self.subset_size, total_features)}: {e}"
+                )
+                continue
+
+        # Merge all isochrone layers into one
+        if temp_layers:
+            merge_params = {
+                "LAYERS": temp_layers,
+                "CRS": QgsCoordinateReferenceSystem(crs),
+                "OUTPUT": "memory:",
+            }
+            merged_result = processing.run("native:mergevectorlayers", merge_params)
+            merged_layer = merged_result["OUTPUT"]
+
+            # Proceed to create bands by differencing the ranges
+            self._create_bands(merged_layer, output_path, crs)
+        else:
+            print("No isochrones were created.")
+
+    def _create_bands(self, merged_layer, output_path, crs):
+        """
+        Creates bands by differencing isochrone ranges.
+
+        :param merged_layer: The merged isochrone layer
+        :param output_path: Path to save the final output layer
+        :param crs: Coordinate reference system
+        """
+        # Extract unique ranges from the 'value' field added by ORS
+        ranges_field = "value"
+        unique_ranges = sorted(
+            {feat[ranges_field] for feat in merged_layer.getFeatures()}
+        )
+
+        # Create dissolved layers for each range
+        range_layers = {}
+        for r in unique_ranges:
+            # Select features matching the current range
+            expr = f'"{ranges_field}" = {r}'
+            request = QgsFeatureRequest().setFilterExpression(expr)
+            features = [feat for feat in merged_layer.getFeatures(request)]
+            if features:
+                # Create a memory layer for this range
+                range_layer = QgsVectorLayer(
+                    f"Polygon?crs={crs}", f"range_{r}", "memory"
+                )
+                dp = range_layer.dataProvider()
+                dp.addAttributes(merged_layer.fields())
+                range_layer.updateFields()
+                dp.addFeatures(features)
+
+                # Dissolve the range layer to create a single feature
+                dissolve_params = {
+                    "INPUT": range_layer,
+                    "FIELD": [],
+                    "OUTPUT": "memory:",
+                }
+                dissolve_result = processing.run("native:dissolve", dissolve_params)
+                dissolved_layer = dissolve_result["OUTPUT"]
+                range_layers[r] = dissolved_layer
+
+        # Create bands by computing differences between the ranges
+        band_layers = []
+        sorted_ranges = sorted(range_layers.keys(), reverse=True)
+        for i in range(len(sorted_ranges) - 1):
+            current_range = sorted_ranges[i]
+            next_range = sorted_ranges[i + 1]
+            current_layer = range_layers[current_range]
+            next_layer = range_layers[next_range]
+
+            # Difference between current and next range
+            difference_params = {
+                "INPUT": current_layer,
+                "OVERLAY": next_layer,
+                "OUTPUT": "memory:",
+            }
+            diff_result = processing.run("native:difference", difference_params)
+            diff_layer = diff_result["OUTPUT"]
+
+            # Add 'rasField' attribute to store the range value
+            diff_layer.dataProvider().addAttributes(
+                [QgsField("rasField", QVariant.Int)]
+            )
+            diff_layer.updateFields()
+            with edit(diff_layer):
+                for feat in diff_layer.getFeatures():
+                    feat["rasField"] = current_range
+                    diff_layer.updateFeature(feat)
+
+            band_layers.append(diff_layer)
+
+        # Handle the smallest range separately
+        smallest_range = sorted_ranges[-1]
+        smallest_layer = range_layers[smallest_range]
+        smallest_layer.dataProvider().addAttributes(
+            [QgsField("rasField", QVariant.Int)]
+        )
+        smallest_layer.updateFields()
+        with edit(smallest_layer):
+            for feat in smallest_layer.getFeatures():
+                feat["rasField"] = smallest_range
+                smallest_layer.updateFeature(feat)
+        band_layers.append(smallest_layer)
+
+        # Merge all band layers into the final output
+        merge_bands_params = {
+            "LAYERS": band_layers,
+            "CRS": QgsCoordinateReferenceSystem(crs),
+            "OUTPUT": output_path,
+        }
+        final_merge_result = processing.run(
+            "native:mergevectorlayers", merge_bands_params
+        )
+        final_layer = QgsVectorLayer(output_path, "MultiBuffer", "ogr")
+
+        print(f"Multi-buffer layer created at {output_path}")

geest/gui/tree_panel.py

@@ -28,7 +28,6 @@
 from geest.core.workflow_queue_manager import WorkflowQueueManager
 
 
-
 class TreePanel(QWidget):
     def __init__(self, parent=None, json_file=None):
         super().__init__(parent)