Merge pull request #1164 from cal-itp/speedmap-deep-dive

Big Blue Bus speedmap segments deep dive

rt_segment_speeds/35_bbb_segment_backtrack.ipynb

@@ -0,0 +1,359 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "f9f1baa5-2de0-4152-89ec-e43880ea043d",
+   "metadata": {},
+   "source": [
+    "# Speedmap segments \n",
+    "* The 20th, 50th, 80th percentiles look extremely tight, why?\n",
+    "* Is this happening in the trip files?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b18ab7df-9592-4897-8193-ca0ccc015930",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import geopandas as gpd\n",
+    "import pandas as pd\n",
+    "\n",
+    "from segment_speed_utils import helpers\n",
+    "from segment_speed_utils.project_vars import SEGMENT_GCS, GTFS_DATA_DICT\n",
+    "from shared_utils import rt_dates\n",
+    "\n",
+    "analysis_date = rt_dates.DATES[\"apr2024\"]\n",
+    "nov_date = rt_dates.DATES[\"nov2023\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "48f4c06f-be94-440f-90ee-df365b4f06b4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "TRIP_FILE = GTFS_DATA_DICT.speedmap_segments.stage4\n",
+    "SHAPE_FILE = GTFS_DATA_DICT.speedmap_segments.shape_stop_single_segment"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ab776438-86bc-4b86-a276-9b52aad3f454",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "operator_name = \"Big Blue Bus Schedule\"\n",
+    "\n",
+    "operator_route_df = helpers.import_scheduled_trips(\n",
+    "    analysis_date,\n",
+    "    columns = [\"gtfs_dataset_key\", \"name\", \n",
+    "               \"route_short_name\", \"route_long_name\", \"route_id\"],\n",
+    "    filters = [[(\"name\", \"==\", operator_name)]],\n",
+    "    get_pandas = True,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "61f76f27-8c20-45dd-8910-ed60fafbf2d1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "nov_trips = helpers.import_scheduled_trips(\n",
+    "    nov_date,\n",
+    "    columns = [\"gtfs_dataset_key\", \"name\", \"shape_id\", \"route_id\", \n",
+    "               \"route_long_name\", \"route_short_name\"],\n",
+    "    filters = [[(\"name\", \"==\", operator_name)]],\n",
+    "    get_pandas = True\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a5a6a7ff-8466-403a-abf5-3db4a69f42b6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if nov_trips.schedule_gtfs_dataset_key.iloc[0] == operator_route_df.schedule_gtfs_dataset_key.iloc[0]:\n",
+    "    bbb_key = nov_trips.schedule_gtfs_dataset_key.iloc[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d448d865-2546-487b-83e8-eabeaceccdcd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def nov_shape_to_apr_route(\n",
+    "    nov_trips: pd.DataFrame,\n",
+    "    apr_route_df: pd.DataFrame,\n",
+    "    operator_key: str = bbb_key,\n",
+    "    one_shape: str = \"\"\n",
+    "):\n",
+    "\n",
+    "    nov_route_name = nov_trips[\n",
+    "        #(nov_trips.schedule.str.contains(operator_substring)) & \n",
+    "        (nov_trips.shape_id==one_shape)\n",
+    "    ].route_short_name.iloc[0]\n",
+    "    \n",
+    "    return apr_route_df[\n",
+    "        #(apr_route_df.name.str.contains(operator_substring)) & \n",
+    "        (apr_route_df.route_short_name==nov_route_name)\n",
+    "    ].route_id.iloc[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ccee2dd5-e335-4bd3-9d83-7ebeec4bc422",
+   "metadata": {},
+   "source": [
+    "## Trip"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1e04594e-18ff-4283-aa9f-bd811d577882",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "trip_df = pd.read_parquet(\n",
+    "    f\"{SEGMENT_GCS}{TRIP_FILE}_{analysis_date}.parquet\",\n",
+    "    filters = [[(\"schedule_gtfs_dataset_key\", \"==\", bbb_key)]]\n",
+    ")\n",
+    "\n",
+    "trip_df = trip_df.assign(\n",
+    "    speed_mph = trip_df.speed_mph.round(2)\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c2216fd7-92cf-4dce-82bb-125e2ecce384",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "olympic_shape1 = \"26450\"\n",
+    "olympic_route1 = nov_shape_to_apr_route(\n",
+    "    nov_trips,\n",
+    "    operator_route_df,\n",
+    "    bbb_key,\n",
+    "    olympic_shape1\n",
+    ")\n",
+    "\n",
+    "santa_monica_shape1 = \"26437\"\n",
+    "santa_monica_route1 = nov_shape_to_apr_route(\n",
+    "    nov_trips,\n",
+    "    operator_route_df,\n",
+    "    bbb_key,\n",
+    "    santa_monica_shape1\n",
+    ")\n",
+    "\n",
+    "santa_monica_shape2 = \"26509\"\n",
+    "santa_monica_route2 = nov_shape_to_apr_route(\n",
+    "    nov_trips,\n",
+    "    operator_route_df,\n",
+    "    bbb_key,\n",
+    "    santa_monica_shape2\n",
+    ")\n",
+    "\n",
+    "fourth_shape1 = \"26464\"\n",
+    "fourth_route1 = nov_shape_to_apr_route(\n",
+    "    nov_trips,\n",
+    "    operator_route_df,\n",
+    "    bbb_key,\n",
+    "    fourth_shape1\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a45b3e7d-ad9e-4f3c-8d43-2821ca2e9aed",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def filter_to_route(trip_df, operator_key, one_route, one_stop):\n",
+    "    return trip_df[\n",
+    "        (trip_df.schedule_gtfs_dataset_key==operator_key) & \n",
+    "        (trip_df.route_id==one_route) & \n",
+    "        (trip_df.stop_id==one_stop)\n",
+    "        ][[\"stop_pair_name\", \"time_of_day\", \"arrival_time\", \"speed_mph\", \n",
+    "           \"meters_elapsed\", \"sec_elapsed\"]].sort_values(\"arrival_time\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "85641403-384d-409c-8de4-ea3d525b5c1c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "green_olympic_speeds = {\n",
+    "    \"721\": \"Olympic & Prosser\",\n",
+    "    \"688\": \"Olympic & Veteran\",\n",
+    "    \"716\": \"Olympic & Colby\",\n",
+    "    \"800\": \"Olympic & Purdue\",\n",
+    "    \"801\": \"Olympic & Colby\",\n",
+    "    \"700\": \"Olympic & 3030\"\n",
+    "}\n",
+    "\n",
+    "green_santa_monica_blvd_speeds = {\n",
+    "    \"370\": \"Santa Monica & 14th\",\n",
+    "    \"117\": \"Santa Monica & 14th, under\",\n",
+    "    \"1234\": \"Santa Monica & 17th\"\n",
+    "}\n",
+    "\n",
+    "green_fourth_speeds = {\n",
+    "    \"668\": \"4th & San Vincente\",\n",
+    "    \"666\": \"4th & Marguerita\",\n",
+    "    \"665\": \"4th & Alta\",\n",
+    "    \"664\": \"4th & Montana\",\n",
+    "    \"505\": \"4th & Washington\",\n",
+    "    \"504\": \"4th & California\",\n",
+    "    \"502\": \"4th & Washington\",\n",
+    "    \"503\":\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3c8ba1d6-388b-498c-bfa5-49ea1b8cb0cb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# There are several exact speeds across trips, take a look at\n",
+    "# interpolated stop arrivals, what are the chances this happens?\n",
+    "# is it actually interpolating between different vp_idx values?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "22d67801-c7c4-4726-be0c-9702a20c9c1c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "filter_to_route(trip_df, bbb_key, fourth_route1, \"502\").query('time_of_day==\"AM Peak\"')\n",
+    "#.groupby(\"time_of_day\").agg(\n",
+    "#{\"speed_mph\": lambda x: sorted(list(x))})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5f6e6bff-bdfc-42b7-a549-6d3c62c3af20",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Why are there the same speeds there?\n",
+    "trip_df[\n",
+    "    (trip_df.schedule_gtfs_dataset_key==bbb_key) & \n",
+    "    (trip_df.route_id==fourth_route1) & \n",
+    "    (trip_df.stop_id==\"502\") & \n",
+    "    (trip_df.time_of_day==\"AM Peak\") & \n",
+    "    (trip_df.speed_mph > 15) & (trip_df.speed_mph < 16)\n",
+    "].trip_instance_key.unique()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "93087f88-18f1-4517-a9f3-0f35a695ef6f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "INTERP_FILE = GTFS_DATA_DICT.speedmap_segments.stage3b\n",
+    "NEAREST_VP_FILE = GTFS_DATA_DICT.rt_stop_times.stage2\n",
+    "subset_trips = [\n",
+    "        '0d448c743a91bc96271d36ba4450ebc9',\n",
+    "       '1fbea8d720efd0dd513e98eef5383dbf',\n",
+    "       '3a2e5c9e7304d091406cb5bbdfcc27e4',\n",
+    "       'a0f65344cb59c750934aff210b325f7e',\n",
+    "       'b6fc33a3b002b0bc63b07b6f39d80cb0'\n",
+    "]\n",
+    "\n",
+    "stop_arrivals = pd.read_parquet(\n",
+    "    f\"{SEGMENT_GCS}{INTERP_FILE}_{analysis_date}.parquet\",\n",
+    "    filters = [[(\"trip_instance_key\", \"in\", subset_trips), \n",
+    "               (\"stop_id\", \"==\", \"502\")]]\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7f85adf9-bc36-411f-a890-1aa42b655d5d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "nearest = gpd.read_parquet(\n",
+    "    f\"{SEGMENT_GCS}{NEAREST_VP_FILE}_{analysis_date}.parquet\",\n",
+    "    filters = [[(\"trip_instance_key\", \"in\", subset_trips), \n",
+    "               (\"stop_id\", \"==\", \"502\")]]\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a231783c-0eb6-47d6-879a-6840ecfaaaff",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for i in nearest.index:\n",
+    "    print(i)\n",
+    "    print(nearest.loc[i][\"location_timestamp_local_trio\"])\n",
+    "    #print(nearest.loc[i][\"vp_coords_trio\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a5a3c27f-cff5-4368-99d3-00c556239b8d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "nearest.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "36341936-6747-4ce6-aee2-aa47b6d3c283",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}