From 54d3b73d0ae931cb750c78d8e3390827be3a9eef Mon Sep 17 00:00:00 2001 From: DavidOry Date: Mon, 7 Jul 2025 14:35:19 -0400 Subject: [PATCH 1/2] Initial commit of sameness assessment, with UV config --- .gitignore | 12 +- .python-version | 1 + notebooks/sameness-investigations.twb | 3400 +++++++++++++++++ ...tour-mode-choice-sameness-assessment.ipynb | 1150 ++++++ pyproject.toml | 13 + uv.lock | 359 ++ 6 files changed, 4934 insertions(+), 1 deletion(-) create mode 100644 .python-version create mode 100644 notebooks/sameness-investigations.twb create mode 100644 notebooks/tour-mode-choice-sameness-assessment.ipynb create mode 100644 pyproject.toml create mode 100644 uv.lock diff --git a/.gitignore b/.gitignore index a469d54..9a2bcb7 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,14 @@ input/build/ output/ *.zip **/.ipynb_checkpoints/ -output_*/ \ No newline at end of file +output_*/ + +# tour mode choice sameness investigation +.DS_Store +input/tour-mc-data/* + +notebooks/*.twbx +notebooks/tour-mc-investigation-for-tableau.csv + +scripts/.Rhistory +scripts/.Rproj.user/* diff --git a/.python-version b/.python-version new file mode 100644 index 0000000..24ee5b1 --- /dev/null +++ b/.python-version @@ -0,0 +1 @@ +3.13 diff --git a/notebooks/sameness-investigations.twb b/notebooks/sameness-investigations.twb new file mode 100644 index 0000000..6852fd4 --- /dev/null +++ b/notebooks/sameness-investigations.twb @@ -0,0 +1,3400 @@ + + + + + + <_.fcp.AnimationOnByDefault.true...AnimationOnByDefault /> + + + <_.fcp.MarkAnimation.true...MarkAnimation /> + <_.fcp.ObjectModelEncapsulateLegacy.true...ObjectModelEncapsulateLegacy /> + <_.fcp.ObjectModelTableType.true...ObjectModelTableType /> + <_.fcp.SchemaViewerObjectModel.true...SchemaViewerObjectModel /> + + + + + + + + + <_.fcp.AnimationOnByDefault.false...style> + <_.fcp.AnimationOnByDefault.false..._.fcp.MarkAnimation.true...style-rule element='animation'> + <_.fcp.AnimationOnByDefault.false...format attr='animation-on' value='ao-on' /> + + + + + + + + + + + <_.fcp.ObjectModelEncapsulateLegacy.false...relation connection='textscan.0fb8pml1k8fz0i19f8m2r1iv76gd' name='tour-mc-investigation-for-tableau.csv' table='[tour-mc-investigation-for-tableau#csv]' type='table'> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + <_.fcp.ObjectModelEncapsulateLegacy.true...relation connection='textscan.0fb8pml1k8fz0i19f8m2r1iv76gd' name='tour-mc-investigation-for-tableau.csv' table='[tour-mc-investigation-for-tableau#csv]' type='table'> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 0 + [tour-mc-investigation-for-tableau.csv] + + Count + true + + "UTF-8" + "en_US" + "," + "true" + "en_US" + "" + + + + base_unique_id + 20 + [base_unique_id] + [tour-mc-investigation-for-tableau.csv] + base_unique_id + 0 + integer + Sum + true + 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+ + + + + + + + + + + + + + + + + + + + + + + + + "Success: Correct match to build" + "Success: Nothing comparable in build" + "Failure: Incorrect match to build" + "Success: Correct match to build." + "Success: Nothing comparable in build." + "Failure: Incorrect match to build." + "Failure: Error term not generated in build." + "Failure: Error term not generated in build" + + + + + "Basics" + "Basics + tour_type_num" + "Basics + destination" + "Basics + start_time" + "Basics + start_time + duration + origin + destination" + + + + <_.fcp.ObjectModelEncapsulateLegacy.true...object-graph> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + <formatted-text> + <run>Instances of Multiple Matches in Build Scenario for each entry in Base Scenario</run> + </formatted-text> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + "[federated.1536qtb065a9em1bqm00h1rvkbm3].[ctd:base_unique_id:qk]" + 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+ + + + + + <formatted-text> + <run>Matching Performance for </run> + <run bold='true'>Tour Mode Choice</run> + <run> of Explicit Error Term using Monte Carlo Approach to Generating Seeds for Random Error Draws</run> + </formatted-text> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + [federated.1536qtb065a9em1bqm00h1rvkbm3].[none:sameness_definition:nk] + + + + + + + + + + + + + + + + + + + + + Sameness: + ]]> + Æ + ]]> + Æ + Base Scenario Tours: + ]]> + Æ + Share of Tours: + ]]> + + + + + < + [federated.1536qtb065a9em1bqm00h1rvkbm3].[none:sameness_definition:nk] + > < + [federated.1536qtb065a9em1bqm00h1rvkbm3].[none:eet_performance:nk] + > < + [federated.1536qtb065a9em1bqm00h1rvkbm3].[ctd:base_unique_id:qk] + > < + [federated.1536qtb065a9em1bqm00h1rvkbm3].[pcto:ctd:base_unique_id:qk] + > + + + + + + + +
+ + + + + + <formatted-text> + <run>Matching Performance for </run> + <run bold='true'>Tour Mode Choice</run> + <run> of Explicit Error Term using Monte Carlo Approach to Generating Seeds for Random Error Draws</run> + </formatted-text> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + "[federated.1536qtb065a9em1bqm00h1rvkbm3].[ctd:base_unique_id:qk]" + "[federated.1536qtb065a9em1bqm00h1rvkbm3].[pcto:ctd:base_unique_id:qk]" + + + + + "Basics" + "Basics + tour_type_num" + "Basics + destination" + "Basics + start_time" + "Basics + start_time + duration + origin + destination" + + + + [federated.1536qtb065a9em1bqm00h1rvkbm3].[:Measure Names] + + + + + + + + + + + + + + + + + ([federated.1536qtb065a9em1bqm00h1rvkbm3].[:Measure Names] / [federated.1536qtb065a9em1bqm00h1rvkbm3].[none:sameness_definition:nk]) + [federated.1536qtb065a9em1bqm00h1rvkbm3].[none:eet_performance:nk] + +
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b/notebooks/tour-mode-choice-sameness-assessment.ipynb @@ -0,0 +1,1150 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "bc52a044", + "metadata": {}, + "outputs": [], + "source": [ + "import polars as pl\n", + "from IPython.display import display\n", + "import os" + ] + }, + { + "cell_type": "markdown", + "id": "fde9214a", + "metadata": {}, + "source": [ + "### Parameters" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "f2cfccbc", + "metadata": {}, + "outputs": [], + "source": [ + "SAMENESS_MONTE_CARLO_WORD = \"Basics + tour_type_num\"\n", + "SAMENESS_BASICS_WORD = \"Basics\"\n", + "SAMENESS_START_TIME_WORD = \"Basics + start_time\"\n", + "SAMENESS_SCHEDULE_LOCATION_WORD = \"Basics + start_time + duration + origin + destination\"\n", + "SAMENESS_DESTINATION_WORD = \"Basics + destination\"" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "b0c72f19", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'/Users/wsp/Documents/GitHub/asim_eet_viz'" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "os.getcwd()" + ] + }, + { + "cell_type": "markdown", + "id": "6fc60c73", + "metadata": {}, + "source": [ + "### Remote I/O" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "ee9b8290", + "metadata": {}, + "outputs": [], + "source": [ + "input_dir = \"./input/tour-mc-data/\"\n", + "output_dir = \"./notebooks/\"\n", + "\n", + "base_dir_name = \"base\"\n", + "build_dir_name = \"build-transit\"\n", + "\n", + "eet_dir_name = \"eet\"\n", + "mc_same_dir_name = \"mc_same_seed\"\n", + "\n", + "tour_file_name = \"final_tours.csv\"\n", + "\n", + "output_file = os.path.join(output_dir, \"tour-mc-investigation-for-tableau.csv\")" + ] + }, + { + "cell_type": "markdown", + "id": "15968903", + "metadata": {}, + "source": [ + "### Data Reads" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "e596feda", + "metadata": {}, + "outputs": [], + "source": [ + "df_list = {}\n", + "\n", + "column_types = {\n", + " \"person_id\": pl.Float64,\n", + " \"tour_type\": pl.Utf8,\n", + " \"tour_type_count\": pl.Float64,\n", + " \"tour_type_num\": pl.Float64,\n", + " \"tour_num\": pl.Float64,\n", + " \"tour_count\": pl.Float64,\n", + " \"tour_category\": pl.Utf8,\n", + " \"number_of_participants\": pl.Float64,\n", + " \"destination\": pl.Float64,\n", + " \"origin\": pl.Float64,\n", + " \"household_id\": pl.Float64,\n", + " \"start\": pl.Float64,\n", + " \"end\": pl.Float64,\n", + " \"duration\": pl.Float64,\n", + " \"school_esc_outbound\": pl.Utf8,\n", + " \"school_esc_inbound\": pl.Utf8,\n", + " \"num_escortees\": pl.Float64,\n", + " \"tdd\": pl.Float64,\n", + " \"tour_id_temp\": pl.Float64,\n", + " \"composition\": pl.Utf8,\n", + " \"is_external_tour\": pl.Boolean,\n", + " \"is_internal_tour\": pl.Boolean,\n", + " \"destination_logsum\": pl.Float64,\n", + " \"vehicle_occup_1\": pl.Utf8,\n", + " \"vehicle_occup_2\": pl.Utf8,\n", + " \"vehicle_occup_3.5\": pl.Utf8,\n", + " \"tour_mode\": pl.Utf8,\n", + " \"mode_choice_logsum\": pl.Float64,\n", + " \"selected_vehicle\": pl.Utf8,\n", + " \"atwork_subtour_frequency\": pl.Utf8,\n", + " \"parent_tour_id\": pl.Float64,\n", + " \"stop_frequency\": pl.Utf8,\n", + " \"primary_purpose\": pl.Utf8,\n", + " \"tour_id\": pl.Int64,\n", + "}\n", + "\n", + "\n", + "for scen_name in [base_dir_name, build_dir_name]:\n", + " for sim_type_name in [eet_dir_name, mc_same_dir_name]:\n", + " in_file = os.path.join(input_dir, scen_name, sim_type_name, tour_file_name)\n", + " \n", + " df = pl.read_csv(in_file, schema_overrides=column_types)\n", + " \n", + " df = df.with_columns(\n", + " pl.lit(scen_name).alias(\"scenario\"),\n", + " pl.lit(sim_type_name).alias(\"simulation_type\")\n", + " )\n", + " \n", + " df_list[f\"{scen_name}--{sim_type_name}\"] = df" + ] + }, + { + "cell_type": "markdown", + "id": "e42ea0f3", + "metadata": {}, + "source": [ + "### Reductions" + ] + }, + { + "cell_type": "markdown", + "id": "494e9ac2", + "metadata": {}, + "source": [ + "#### EET Reductions" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "adbe0a47", + "metadata": {}, + "outputs": [], + "source": [ + "eet_base_df = df_list[f\"{base_dir_name}--{eet_dir_name}\"].select(\n", + " pl.col(\"household_id\").alias(\"base_household_id\"),\n", + " pl.col(\"person_id\").alias(\"base_person_id\"),\n", + " pl.col(\"tour_type\").alias(\"base_tour_type\"),\n", + " pl.col(\"primary_purpose\").alias(\"base_primary_purpose\"),\n", + " pl.col(\"tour_type_num\").alias(\"base_tour_type_num\"),\n", + " pl.col(\"tour_type_count\").alias(\"base_tour_type_count\"),\n", + " pl.col(\"tour_id\").alias(\"base_tour_id\"),\n", + " pl.col(\"tour_mode\").alias(\"base_tour_mode\"),\n", + " pl.col(\"duration\").alias(\"base_duration\"),\n", + " pl.col(\"start\").alias(\"base_start_time_index\"),\n", + " pl.col(\"end\").alias(\"base_end_time_index\"),\n", + " pl.col(\"origin\").alias(\"base_origin\"),\n", + " pl.col(\"destination\").alias(\"base_destination\"),\n", + ").with_row_index(name=\"base_unique_id\", offset = 1).sort(\"base_unique_id\")\n", + "\n", + "\n", + "eet_build_df = df_list[f\"{build_dir_name}--{eet_dir_name}\"].select(\n", + " pl.col(\"household_id\").alias(\"build_household_id\"),\n", + " pl.col(\"person_id\").alias(\"build_person_id\"),\n", + " pl.col(\"tour_type\").alias(\"build_tour_type\"),\n", + " pl.col(\"primary_purpose\").alias(\"build_primary_purpose\"),\n", + " pl.col(\"tour_type_num\").alias(\"build_tour_type_num\"),\n", + " pl.col(\"tour_type_count\").alias(\"build_tour_type_count\"),\n", + " pl.col(\"tour_id\").alias(\"build_tour_id\"),\n", + " pl.col(\"tour_mode\").alias(\"build_tour_mode\"),\n", + " pl.col(\"duration\").alias(\"build_duration\"),\n", + " pl.col(\"start\").alias(\"build_start_time_index\"),\n", + " pl.col(\"end\").alias(\"build_end_time_index\"),\n", + " pl.col(\"origin\").alias(\"build_origin\"),\n", + " pl.col(\"destination\").alias(\"build_destination\"),\n", + ").with_row_index(name=\"build_unique_id\", offset = 1).sort(\"build_unique_id\") # `with_row_count` generates 0-indexed row numbers" + ] + }, + { + "cell_type": "markdown", + "id": "bd77b083", + "metadata": {}, + "source": [ + "#### Free up some memory -- No Monte Carlo for now" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "a260f6cf", + "metadata": {}, + "outputs": [], + "source": [ + "del df_list" + ] + }, + { + "cell_type": "markdown", + "id": "f2190709", + "metadata": {}, + "source": [ + "#### Identify tours with the same error terms" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "80a80f78", + "metadata": {}, + "outputs": [], + "source": [ + "same_error_df = eet_base_df.join(\n", + " eet_build_df,\n", + " left_on=\"base_tour_id\",\n", + " right_on=\"build_tour_id\",\n", + " how=\"left\", \n", + ").select(\n", + " pl.col(\"base_unique_id\"),\n", + " pl.col(\"build_unique_id\"),\n", + " pl.col(\"base_tour_id\").alias(\"error_term_id\")\n", + ")\n", + "\n", + "base_error_term_in_build_df = eet_base_df.select(\n", + " pl.col(\"base_unique_id\"),\n", + " pl.col(\"base_tour_id\").alias(\"error_term_id\")\n", + ").with_columns(\n", + " pl.col(\"error_term_id\").is_in(pl.Series(eet_build_df[\"build_tour_id\"]).implode()).alias(\"error_term_present_in_build\")\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "c838ac82", + "metadata": {}, + "source": [ + "#### Method to Assess Sameness across Different Definitions" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "be564af6", + "metadata": {}, + "outputs": [], + "source": [ + "def process_sameness(base_df, build_df, join_cols, sameness_word, same_error_df, base_error_term_in_build_df):\n", + "\n", + " temp_df = base_df.join(\n", + " build_df,\n", + " left_on=[col[0] for col in join_cols],\n", + " right_on=[col[1] for col in join_cols],\n", + " how=\"left\", \n", + " suffix=\"_build_join\",\n", + " coalesce=False\n", + " ).with_columns(\n", + " pl.col(\"build_unique_id\").is_null().alias(\"nothing_comparable_in_build\")\n", + " ).with_columns(\n", + " pl.col(\"build_unique_id\").fill_null(0)\n", + " ).join(\n", + " same_error_df,\n", + " on=[\"base_unique_id\", \"build_unique_id\"],\n", + " how=\"left\"\n", + " ).with_columns(\n", + " pl.col(\"error_term_id\").is_not_null().alias(\"same_error_term\")\n", + " ).join(\n", + " base_error_term_in_build_df,\n", + " on=\"base_unique_id\",\n", + " how=\"left\"\n", + " ).with_columns(\n", + " pl.lit(sameness_word).alias(\"sameness_definition\")\n", + " )\n", + "\n", + " # Estimate likely iia violations\n", + " iia_violations_df = temp_df.sort(\n", + " pl.col(\"base_unique_id\"),\n", + " pl.col(\"same_error_term\").cast(pl.Int32).neg(), \n", + " pl.col(\"build_unique_id\")\n", + " ).group_by(\n", + " pl.col(\"base_unique_id\")\n", + " ).agg(\n", + " pl.len().alias(\"iia_violations\"),\n", + " pl.col(\"build_unique_id\").first().alias(\"build_unique_id\"),\n", + " ).with_columns(\n", + " pl.col(\"iia_violations\").fill_null(0) \n", + " ).with_columns(\n", + " pl.col(\"build_unique_id\").fill_null(0)\n", + " )\n", + "\n", + " # Count the number uf unique error terms likely to have\n", + " unique_error_terms_count = base_df.select(\n", + " *[pl.col(col[0]) for col in join_cols]\n", + " ).unique().shape[0]\n", + " \n", + " total_base_rows = base_df.shape[0]\n", + " unique_error_terms_percentage = unique_error_terms_count / total_base_rows if total_base_rows > 0 else 0\n", + "\n", + " result_df = temp_df.join(\n", + " iia_violations_df,\n", + " on=[\"base_unique_id\", \"build_unique_id\"],\n", + " how=\"left\"\n", + " ).filter(\n", + " pl.col(\"iia_violations\").is_not_null()\n", + " ).with_columns(\n", + " (pl.col(\"iia_violations\") - 1).alias(\"iia_violations\"),\n", + " pl.lit(unique_error_terms_percentage).alias(\"unique_error_terms\")\n", + " )\n", + " \n", + " return result_df" + ] + }, + { + "cell_type": "markdown", + "id": "f08d56dd", + "metadata": {}, + "source": [ + "#### Sameness Definition 1: By household_id, person_id, tour_type, primary_purpose, and tour_type_num" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "ceea26a0", + "metadata": {}, + "outputs": [], + "source": [ + "join_cols = [\n", + " (\"base_household_id\", \"build_household_id\"),\n", + " (\"base_person_id\", \"build_person_id\"),\n", + " (\"base_tour_type\", \"build_tour_type\"),\n", + " (\"base_primary_purpose\", \"build_primary_purpose\"),\n", + " (\"base_tour_type_num\", \"build_tour_type_num\")\n", + "]\n", + "same_01_df = process_sameness(eet_base_df, eet_build_df, join_cols, SAMENESS_MONTE_CARLO_WORD, same_error_df, base_error_term_in_build_df)" + ] + }, + { + "cell_type": "markdown", + "id": "35ad6a51", + "metadata": {}, + "source": [ + "#### Sameness Definition 2: By household_id, person_id, tour_type, primary_purpose, and start_time" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "e607b98b", + "metadata": {}, + "outputs": [], + "source": [ + "join_cols = [\n", + " (\"base_household_id\", \"build_household_id\"),\n", + " (\"base_person_id\", \"build_person_id\"),\n", + " (\"base_tour_type\", \"build_tour_type\"),\n", + " (\"base_primary_purpose\", \"build_primary_purpose\"),\n", + " (\"base_start_time_index\", \"build_start_time_index\")\n", + "]\n", + "same_02_df = process_sameness(eet_base_df, eet_build_df, join_cols, SAMENESS_START_TIME_WORD, same_error_df, base_error_term_in_build_df)" + ] + }, + { + "cell_type": "markdown", + "id": "8c156a2e", + "metadata": {}, + "source": [ + "#### Sameness Definition 3: By household_id, person_id, tour_type, primary_purpose, start_time, duration, origin, and destination" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "2f1942c7", + "metadata": {}, + "outputs": [], + "source": [ + "join_cols = [\n", + " (\"base_household_id\", \"build_household_id\"),\n", + " (\"base_person_id\", \"build_person_id\"),\n", + " (\"base_tour_type\", \"build_tour_type\"),\n", + " (\"base_primary_purpose\", \"build_primary_purpose\"),\n", + " (\"base_start_time_index\", \"build_start_time_index\"),\n", + " (\"base_duration\", \"build_duration\"),\n", + " (\"base_origin\", \"build_origin\"),\n", + " (\"base_destination\", \"build_destination\")\n", + "]\n", + "same_03_df = process_sameness(eet_base_df, eet_build_df, join_cols, SAMENESS_SCHEDULE_LOCATION_WORD, same_error_df, base_error_term_in_build_df)" + ] + }, + { + "cell_type": "markdown", + "id": "6ae9975e", + "metadata": {}, + "source": [ + "#### Sameness Definition 4: By household_id, person_id, tour_type, primary_purpose, and destination" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "5fe3cda8", + "metadata": {}, + "outputs": [], + "source": [ + "join_cols = [\n", + " (\"base_household_id\", \"build_household_id\"),\n", + " (\"base_person_id\", \"build_person_id\"),\n", + " (\"base_tour_type\", \"build_tour_type\"),\n", + " (\"base_primary_purpose\", \"build_primary_purpose\"),\n", + " (\"base_destination\", \"build_destination\")\n", + "]\n", + "same_04_df = process_sameness(eet_base_df, eet_build_df, join_cols, SAMENESS_DESTINATION_WORD, same_error_df, base_error_term_in_build_df)" + ] + }, + { + "cell_type": "markdown", + "id": "cb7181d2", + "metadata": {}, + "source": [ + "#### Sameness Definition 5: By household_id, person_id, tour_type, primary_purpose" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "48bbfa10", + "metadata": {}, + "outputs": [], + "source": [ + "join_cols = [\n", + " (\"base_household_id\", \"build_household_id\"),\n", + " (\"base_person_id\", \"build_person_id\"),\n", + " (\"base_tour_type\", \"build_tour_type\"),\n", + " (\"base_primary_purpose\", \"build_primary_purpose\")\n", + "]\n", + "same_05_df = process_sameness(eet_base_df, eet_build_df, join_cols, SAMENESS_BASICS_WORD, same_error_df, base_error_term_in_build_df)" + ] + }, + { + "cell_type": "markdown", + "id": "1c3f878d", + "metadata": {}, + "source": [ + "#### Consolidate Sameness Results" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "2d5e07ef", + "metadata": {}, + "outputs": [], + "source": [ + "output_df = pl.concat([same_01_df, same_02_df, same_03_df, same_04_df, same_05_df])\n", + "output_df = output_df.with_columns(\n", + " (pl.col(\"base_tour_id\") == pl.col(\"build_tour_id\")).alias(\"is_tour_id_same\"),\n", + " (pl.col(\"base_duration\") == pl.col(\"build_duration\")).alias(\"is_duration_same\"),\n", + " (pl.col(\"base_tour_type_num\") == pl.col(\"build_tour_type_num\")).alias(\"is_tour_type_num_same\"),\n", + " (pl.col(\"base_start_time_index\") == pl.col(\"build_start_time_index\")).alias(\"is_start_time_same\"),\n", + " (pl.col(\"base_end_time_index\") == pl.col(\"build_end_time_index\")).alias(\"is_end_time_same\"),\n", + " pl.when(pl.col(\"same_error_term\"))\n", + " .then(pl.lit(\"Success: Correct match to build\"))\n", + " .when(~pl.col(\"same_error_term\") & pl.col(\"error_term_present_in_build\"))\n", + " .then(pl.lit(\"Failure: Incorrect match to build\"))\n", + " .when(~pl.col(\"same_error_term\") & ~pl.col(\"error_term_present_in_build\") & pl.col(\"nothing_comparable_in_build\"))\n", + " .then(pl.lit(\"Success: Nothing comparable in build\"))\n", + " .when(~pl.col(\"same_error_term\") & ~pl.col(\"error_term_present_in_build\") & ~pl.col(\"nothing_comparable_in_build\"))\n", + " .then(pl.lit(\"Failure: Error term not generated in build\"))\n", + " .otherwise(pl.lit(\"ERROR\")).alias(\"eet_performance\")\n", + ")\n" + ] + }, + { + "cell_type": "markdown", + "id": "b9960eef", + "metadata": {}, + "source": [ + "#### High-level Outcome" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "38e57ebb", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'Sameness Definition vs EET Performance:'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + "shape: (5, 2)\n", + "┌───────────────────────────────────────────────────────┬────────────────────┐\n", + "│ sameness_definition ┆ unique_error_terms │\n", + "│ --- ┆ --- │\n", + "│ str ┆ f64 │\n", + "╞═══════════════════════════════════════════════════════╪════════════════════╡\n", + "│ Basics ┆ 0.833356 │\n", + "│ Basics + destination ┆ 0.929703 │\n", + "│ Basics + start_time ┆ 0.992803 │\n", + "│ Basics + start_time + duration + origin + destination ┆ 0.999894 │\n", + "│ Basics + tour_type_num ┆ 0.999931 │\n", + "└───────────────────────────────────────────────────────┴────────────────────┘" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "display(\"Sameness Definition vs Unique Error Terms:\")\n", + "display(output_df.group_by(\"sameness_definition\").agg(pl.col(\"unique_error_terms\").first()).sort(\"sameness_definition\"))\n" + ] + }, + { + "cell_type": "markdown", + "id": "bcfaa664", + "metadata": {}, + "source": [ + "#### Write to CSV for Tableau" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "c9df0221", + "metadata": {}, + "outputs": [], + "source": [ + "output_df.write_csv(output_file)" + ] + }, + { + "cell_type": "markdown", + "id": "ba1d5768", + "metadata": {}, + "source": [ + "### Deep Dive/Debug Investigation" + ] + }, + { + "cell_type": "markdown", + "id": "d0ab9439", + "metadata": {}, + "source": [ + "#### Question #1: Why does the Monte Carlo method fail? It should be perfect." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "9ad2f7cc", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'Primary Purpose distribution for Monte Carlo method failures:'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + "shape: (6, 2)\n", + "┌──────────────────────┬──────┐\n", + "│ base_primary_purpose ┆ len │\n", + "│ --- ┆ --- │\n", + "│ str ┆ u32 │\n", + "╞══════════════════════╪══════╡\n", + "│ atwork ┆ 1 │\n", + "│ eatout ┆ 1 │\n", + "│ escort ┆ 5292 │\n", + "│ othdiscr ┆ 3 │\n", + "│ othmaint ┆ 2 │\n", + "│ shopping ┆ 2 │\n", + "└──────────────────────┴──────┘" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "working_df = output_df.filter(\n", + " (pl.col(\"sameness_definition\") == SAMENESS_MONTE_CARLO_WORD) &\n", + " (pl.col(\"eet_performance\").str.contains(\"Failure\"))\n", + ")\n", + "\n", + "display(\"Primary Purpose distribution for Monte Carlo method failures:\")\n", + "display(working_df.group_by(\"base_primary_purpose\").len().sort(\"base_primary_purpose\"))\n" + ] + }, + { + "cell_type": "markdown", + "id": "e0bf0e6d", + "metadata": {}, + "source": [ + "##### Look into Shopping Failures" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "8edecf5f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + "shape: (2, 2)\n", + "┌────────────────┬───────────────────┐\n", + "│ base_unique_id ┆ base_household_id │\n", + "│ --- ┆ --- │\n", + "│ u32 ┆ f64 │\n", + "╞════════════════╪═══════════════════╡\n", + "│ 1189351 ┆ 302481.0 │\n", + "│ 1189352 ┆ 302481.0 │\n", + "└────────────────┴───────────────────┘" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "df_shopping_failures = working_df.filter(pl.col(\"base_primary_purpose\") == \"shopping\")\n", + "display(df_shopping_failures.select([\"base_unique_id\", \"base_household_id\"]))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "0ce87860", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'Debug Base DataFrame (Shopping):'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + "shape: (1, 8)\n", + "┌────────────┬────────────┬────────────┬───────────┬───────────┬───────────┬───────────┬───────────┐\n", + "│ base_house ┆ base_perso ┆ base_tour_ ┆ base_prim ┆ base_tour ┆ base_dura ┆ base_star ┆ base_end_ │\n", + "│ hold_id ┆ n_id ┆ type ┆ ary_purpo ┆ _id ┆ tion ┆ t_time_in ┆ time_inde │\n", + "│ --- ┆ --- ┆ --- ┆ se ┆ --- ┆ --- ┆ dex ┆ x │\n", + "│ f64 ┆ f64 ┆ str ┆ --- ┆ i64 ┆ f64 ┆ --- ┆ --- │\n", + "│ ┆ ┆ ┆ str ┆ ┆ ┆ f64 ┆ f64 │\n", + "╞════════════╪════════════╪════════════╪═══════════╪═══════════╪═══════════╪═══════════╪═══════════╡\n", + "│ 302481.0 ┆ 858708.0 ┆ shopping ┆ shopping ┆ 42935370 ┆ 1.0 ┆ 21.0 ┆ 22.0 │\n", + "└────────────┴────────────┴────────────┴───────────┴───────────┴───────────┴───────────┴───────────┘" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "DEBUG_HH_ID = 302481\n", + "DEBUG_PERSON_ID = 858708\n", + "DEBUG_PURPOSE = \"shopping\"\n", + "\n", + "debug_base_df = eet_base_df.filter(\n", + " (pl.col(\"base_household_id\") == DEBUG_HH_ID) &\n", + " (pl.col(\"base_person_id\") == DEBUG_PERSON_ID) &\n", + " (pl.col(\"base_tour_type\") == DEBUG_PURPOSE)\n", + ").select(\n", + " [\n", + " \"base_household_id\",\n", + " \"base_person_id\",\n", + " \"base_tour_type\",\n", + " \"base_primary_purpose\",\n", + " \"base_tour_id\",\n", + " \"base_duration\",\n", + " \"base_start_time_index\",\n", + " \"base_end_time_index\",\n", + " ]\n", + ")\n", + "display(\"Debug Base DataFrame (Shopping):\")\n", + "display(debug_base_df)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "5ee647ba", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'Debug Build DataFrame (Shopping):'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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50b8fbcda5aa508512918945d4887d351d4eaeac Mon Sep 17 00:00:00 2001 From: DavidOry Date: Wed, 3 Sep 2025 09:38:09 -0400 Subject: [PATCH 2/2] Re-number sameness assessments to align with the document --- ...tour-mode-choice-sameness-assessment.ipynb | 30 +++++++++---------- 1 file changed, 15 insertions(+), 15 deletions(-) diff --git a/notebooks/tour-mode-choice-sameness-assessment.ipynb b/notebooks/tour-mode-choice-sameness-assessment.ipynb index ec06c53..852ce4d 100644 --- a/notebooks/tour-mode-choice-sameness-assessment.ipynb +++ b/notebooks/tour-mode-choice-sameness-assessment.ipynb @@ -347,12 +347,12 @@ "id": "f08d56dd", "metadata": {}, "source": [ - "#### Sameness Definition 1: By household_id, person_id, tour_type, primary_purpose, and tour_type_num" + "#### Sameness Definition 2: By household_id, person_id, tour_type, primary_purpose, and tour_type_num" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "ceea26a0", "metadata": {}, "outputs": [], @@ -364,7 +364,7 @@ " (\"base_primary_purpose\", \"build_primary_purpose\"),\n", " (\"base_tour_type_num\", \"build_tour_type_num\")\n", "]\n", - "same_01_df = process_sameness(eet_base_df, eet_build_df, join_cols, SAMENESS_MONTE_CARLO_WORD, same_error_df, base_error_term_in_build_df)" + "same_02_df = process_sameness(eet_base_df, eet_build_df, join_cols, SAMENESS_MONTE_CARLO_WORD, same_error_df, base_error_term_in_build_df)" ] }, { @@ -372,12 +372,12 @@ "id": "35ad6a51", "metadata": {}, "source": [ - "#### Sameness Definition 2: By household_id, person_id, tour_type, primary_purpose, and start_time" + "#### Sameness Definition 4: By household_id, person_id, tour_type, primary_purpose, and start_time" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "id": "e607b98b", "metadata": {}, "outputs": [], @@ -389,7 +389,7 @@ " (\"base_primary_purpose\", \"build_primary_purpose\"),\n", " (\"base_start_time_index\", \"build_start_time_index\")\n", "]\n", - "same_02_df = process_sameness(eet_base_df, eet_build_df, join_cols, SAMENESS_START_TIME_WORD, same_error_df, base_error_term_in_build_df)" + "same_04_df = process_sameness(eet_base_df, eet_build_df, join_cols, SAMENESS_START_TIME_WORD, same_error_df, base_error_term_in_build_df)" ] }, { @@ -397,12 +397,12 @@ "id": "8c156a2e", "metadata": {}, "source": [ - "#### Sameness Definition 3: By household_id, person_id, tour_type, primary_purpose, start_time, duration, origin, and destination" + "#### Sameness Definition 5: By household_id, person_id, tour_type, primary_purpose, start_time, duration, origin, and destination" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "id": "2f1942c7", "metadata": {}, "outputs": [], @@ -417,7 +417,7 @@ " (\"base_origin\", \"build_origin\"),\n", " (\"base_destination\", \"build_destination\")\n", "]\n", - "same_03_df = process_sameness(eet_base_df, eet_build_df, join_cols, SAMENESS_SCHEDULE_LOCATION_WORD, same_error_df, base_error_term_in_build_df)" + "same_05_df = process_sameness(eet_base_df, eet_build_df, join_cols, SAMENESS_SCHEDULE_LOCATION_WORD, same_error_df, base_error_term_in_build_df)" ] }, { @@ -425,12 +425,12 @@ "id": "6ae9975e", "metadata": {}, "source": [ - "#### Sameness Definition 4: By household_id, person_id, tour_type, primary_purpose, and destination" + "#### Sameness Definition 3: By household_id, person_id, tour_type, primary_purpose, and destination" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "id": "5fe3cda8", "metadata": {}, "outputs": [], @@ -442,7 +442,7 @@ " (\"base_primary_purpose\", \"build_primary_purpose\"),\n", " (\"base_destination\", \"build_destination\")\n", "]\n", - "same_04_df = process_sameness(eet_base_df, eet_build_df, join_cols, SAMENESS_DESTINATION_WORD, same_error_df, base_error_term_in_build_df)" + "same_03_df = process_sameness(eet_base_df, eet_build_df, join_cols, SAMENESS_DESTINATION_WORD, same_error_df, base_error_term_in_build_df)" ] }, { @@ -450,12 +450,12 @@ "id": "cb7181d2", "metadata": {}, "source": [ - "#### Sameness Definition 5: By household_id, person_id, tour_type, primary_purpose" + "#### Sameness Definition 1: By household_id, person_id, tour_type, primary_purpose" ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "id": "48bbfa10", "metadata": {}, "outputs": [], @@ -466,7 +466,7 @@ " (\"base_tour_type\", \"build_tour_type\"),\n", " (\"base_primary_purpose\", \"build_primary_purpose\")\n", "]\n", - "same_05_df = process_sameness(eet_base_df, eet_build_df, join_cols, SAMENESS_BASICS_WORD, same_error_df, base_error_term_in_build_df)" + "same_01_df = process_sameness(eet_base_df, eet_build_df, join_cols, SAMENESS_BASICS_WORD, same_error_df, base_error_term_in_build_df)" ] }, {