rerun hqta pipeline and check that coronado included

Author: edasmalchi

high_quality_transit_areas/11_check_coronado_ferry.ipynb

@@ -42,7 +42,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 108,
+   "execution_count": 4,
    "id": "7014fbd3-dcf0-49bb-a96b-0b9eefe4f8cd",
    "metadata": {
     "tags": []
@@ -150,6 +150,10 @@
    "execution_count": 125,
    "id": "1fa74fa7-8c60-4f22-9668-2504391d9af2",
    "metadata": {
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    },
     "tags": []
    },
    "outputs": [
@@ -929,7 +933,6 @@
    "cell_type": "markdown",
    "id": "35b296be-d7ca-4b88-90e2-97eadf96cd4b",
    "metadata": {
-    "jp-MarkdownHeadingCollapsed": true,
     "tags": []
    },
    "source": [
@@ -1779,6 +1782,40 @@
    "source": [
     "trips.query('route_id == \"COR\"').merge(st_prepped, on=['trip_instance_key']).head(3) #  OK here"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dfe84f3a-ae12-4e9a-8518-b0c057116943",
+   "metadata": {},
+   "source": [
+    "## final output check\n",
+    "\n",
+    "* looks good!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "f5082974-29bc-429a-9288-d2251e8b07c4",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "path = f'{GCS_FILE_PATH}hqta_areas.parquet'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "931c36f1-cd63-4335-822f-ee3b3c0ea399",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# gpd.read_parquet(path).query('hqta_type == \"major_stop_ferry\"').explore()"
+   ]
   }
  ],
  "metadata": {

high_quality_transit_areas/logs/hqta_processing.log

@@ -201,3 +201,12 @@
 2025-04-22 08:40:53.296 | INFO     | __main__:<module>:175 - C3_create_bus_hqta_types 2025-04-16 execution time: 0:00:13.423910
 2025-04-22 08:41:32.679 | INFO     | __main__:<module>:219 - D1_assemble_hqta_points 2025-04-16 execution time: 0:00:17.606480
 2025-04-22 08:42:09.189 | INFO     | __main__:<module>:168 - D2_assemble_hqta_polygons 2025-04-16 execution time: 0:00:14.338260
+2025-04-24 17:16:24.854 | INFO     | __main__:<module>:280 - A1_rail_ferry_brt_stops 2025-04-16 execution time: 0:00:21.065356
+2025-04-24 17:22:39.637 | INFO     | __main__:<module>:248 - B1_create_hqta_segments execution time: 0:05:41.149052
+2025-04-24 17:25:44.559 | INFO     | __main__:<module>:334 - B2_create_aggregate_stop_frequencies 2025-04-16 execution time: 0:02:42.829724
+2025-04-24 17:26:20.730 | INFO     | __main__:<module>:326 - B3_sjoin_stops_to_segments 2025-04-16 execution time: 0:00:13.305625
+2025-04-24 17:26:45.715 | INFO     | __main__:<module>:152 - C1_prep_pairwise_intersections 2025-04-16 execution time: 0:00:04.071368
+2025-04-24 17:27:28.540 | INFO     | __main__:<module>:124 - C2_find_intersections 2025-04-16 execution time: 0:00:08.957911
+2025-04-24 17:28:01.613 | INFO     | __main__:<module>:175 - C3_create_bus_hqta_types 2025-04-16 execution time: 0:00:11.675193
+2025-04-24 17:28:39.115 | INFO     | __main__:<module>:219 - D1_assemble_hqta_points 2025-04-16 execution time: 0:00:17.169588
+2025-04-24 17:29:14.216 | INFO     | __main__:<module>:168 - D2_assemble_hqta_polygons 2025-04-16 execution time: 0:00:13.831337

high_quality_transit_areas/rail_ferry_brt_stops.py

@@ -100,9 +100,10 @@ def assemble_stops(analysis_date: str) -> gpd.GeoDataFrame:
         columns = [
             "name", "feed_key", "trip_id",
             "route_id", "route_type", "route_desc",
+            "gtfs_dataset_key"
         ],
         get_pandas = True
-    )
+    ).rename(columns={"gtfs_dataset_key":"schedule_gtfs_dataset_key"})
 
     stops_with_route = pd.merge(
         stop_times,