header: title: Trips description: General information about modal share and trip distributions. subtabs: - title: Trips rows: - first - second - third - dist-dist - departures - arrivals - title: By Groups rows: - category_header_age - category_1_age - category_2_age - category_header_income - category_1_income - category_2_income - category_header_employment - category_1_employment - category_2_employment - category_header_economic_status - category_1_economic_status - category_2_economic_status - title: Mode Choice rows: - choice-intro - choice - choice-plots layout: first: - type: plotly title: Modal split datasets: dataset: file: analysis/population/mode_share.csv constant: source: Simulated aggregate: func: SUM target: share groupBy: - main_mode modeshareref: file: analysis/resources/mode_share_ref.csv constant: source: Reference aggregate: func: SUM target: share groupBy: - main_mode traces: - x: $dataset.share "y": $dataset.source orientation: h type: bar name: $dataset.main_mode layout: barmode: stack mergeDatasets: true - type: plotly title: Trip distance distribution datasets: dataset: file: analysis/population/mode_share.csv aggregate: func: SUM target: share groupBy: - dist_group modeshareref: file: analysis/resources/mode_share_ref.csv aggregate: func: SUM target: share groupBy: - dist_group traces: - x: $dataset.dist_group "y": $dataset.share orientation: v type: bar name: Simulated original_name: Simulated - x: $modeshareref.dist_group "y": $modeshareref.share orientation: v type: bar name: Reference original_name: Reference colorRamp: Viridis second: - type: csv title: Mode Statistics description: "by main mode, over whole trip (including access & egress)" dataset: analysis/population/trip_stats.csv showAllRows: true - type: plotly title: Modal distance distribution datasets: dataset: file: analysis/population/mode_share_per_dist.csv constant: source: Sim modeshareperdistref: file: analysis/resources/mode_share_per_dist_ref.csv constant: source: Ref traces: - x: $dataset.dist_group "y": $dataset.share orientation: v type: bar name: $dataset.main_mode layout: xaxis: title: Distance group color: "#444" type: '-' barmode: stack yaxis: title: Share color: "#444" type: '-' mergeDatasets: true multiIndex: dist_group: source third: - type: csv title: Population statistics description: over simulated persons (not scaled by sample size) dataset: analysis/population/population_trip_stats.csv showAllRows: true - type: plotly title: Mode usage description: Share of persons using a main mode at least once per day. datasets: dataset: file: analysis/population/mode_users.csv constant: source: sim modeusersref: file: analysis/resources/mode_users_ref.csv constant: source: ref traces: - x: $dataset.main_mode "y": $dataset.user orientation: v type: bar name: $dataset.main_mode width: 2.0 mergeDatasets: true multiIndex: main_mode: source dist-dist: - type: plotly title: Detailed distance distribution description: by mode. Dashed line represents the reference data. datasets: dataset: file: analysis/population/mode_share_distance_distribution.csv pivot: exclude: - dist namesTo: main_mode valuesTo: share constant: source: Sim modesharedistancedistribution: file: analysis/resources/mode_share_distance_distribution.csv pivot: exclude: - dist namesTo: main_mode valuesTo: share constant: source: Ref traces: - fill: none "y": $dataset.share x: $dataset.dist mode: lines whiskerwidth: 0.0 type: scatter name: $dataset.main_mode - fill: none "y": $modesharedistancedistribution.share x: $modesharedistancedistribution.dist mode: lines line: color: black width: 2.0 smoothing: 1.0 shape: linear dash: dash simplify: true context: color: black shape: linear width: 2.0 smoothing: 1.0 simplify: true dash: dash whiskerwidth: 0.0 type: scatter name: $modesharedistancedistribution.main_mode text: $modesharedistancedistribution.source layout: xaxis: title: "Distance [m]" color: "#444" type: '-' showlegend: false yaxis: title: Share color: "#444" type: '-' colorRamp: Viridis interactive: dropdown departures: - type: plotly title: Departures description: by hour and purpose datasets: dataset: analysis/population/trip_purposes_by_hour.csv traces: - x: $dataset.h "y": $dataset.departure orientation: v type: bar name: $dataset.purpose colorRamp: Spectral layout: xaxis: title: Hour color: "#444" type: '-' barmode: stack yaxis: title: Share color: "#444" type: '-' arrivals: - type: plotly title: Arrivals description: by hour and purpose datasets: dataset: analysis/population/trip_purposes_by_hour.csv traces: - x: $dataset.h "y": $dataset.arrival orientation: v type: bar name: $dataset.purpose colorRamp: Spectral layout: xaxis: title: Hour color: "#444" type: '-' barmode: stack yaxis: title: Share color: "#444" type: '-' category_header_age: - type: text backgroundColor: transparent content: "## **Age**" category_1_age: - type: plotly title: Mode share description: by age datasets: dataset: file: analysis/population/mode_share_per_age.csv pivot: exclude: - main_mode - dist_group - age namesTo: source valuesTo: share aggregate: func: SUM target: share groupBy: - main_mode - source - age rename: sim_share: Sim ref_share: Ref traces: - x: $dataset.source "y": $dataset.share orientation: v type: bar name: $dataset.main_mode facet_col: $dataset.age layout: barmode: stack height: 6.0 category_2_age: - type: plotly title: Modal distance distribution description: by age datasets: dataset: file: analysis/population/mode_share_per_age.csv pivot: exclude: - main_mode - dist_group - age namesTo: source valuesTo: share normalize: groupBy: - dist_group - source - age target: share rename: sim_share: Sim ref_share: Ref traces: - x: $dataset.dist_group "y": $dataset.share orientation: v type: bar name: $dataset.main_mode facet_col: $dataset.age layout: xaxis: title: Distance group color: "#444" type: '-' barmode: stack yaxis: title: Share color: "#444" type: '-' interactive: dropdown multiIndex: dist_group: source category_header_income: - type: text backgroundColor: transparent content: "## **Income**" category_1_income: - type: plotly title: Mode share description: by income datasets: dataset: file: analysis/population/mode_share_per_income.csv pivot: exclude: - main_mode - dist_group - income namesTo: source valuesTo: share aggregate: func: SUM target: share groupBy: - main_mode - source - income rename: sim_share: Sim ref_share: Ref traces: - x: $dataset.source "y": $dataset.share orientation: v type: bar name: $dataset.main_mode facet_col: $dataset.income layout: barmode: stack height: 6.0 category_2_income: - type: plotly title: Modal distance distribution description: by income datasets: dataset: file: analysis/population/mode_share_per_income.csv pivot: exclude: - main_mode - dist_group - income namesTo: source valuesTo: share normalize: groupBy: - dist_group - source - income target: share rename: sim_share: Sim ref_share: Ref traces: - x: $dataset.dist_group "y": $dataset.share orientation: v type: bar name: $dataset.main_mode facet_col: $dataset.income layout: xaxis: title: Distance group color: "#444" type: '-' barmode: stack yaxis: title: Share color: "#444" type: '-' interactive: dropdown multiIndex: dist_group: source category_header_employment: - type: text backgroundColor: transparent content: "## **Employment**" category_1_employment: - type: plotly title: Mode share description: by employment datasets: dataset: file: analysis/population/mode_share_per_employment.csv pivot: exclude: - main_mode - dist_group - employment namesTo: source valuesTo: share aggregate: func: SUM target: share groupBy: - main_mode - source - employment rename: sim_share: Sim ref_share: Ref traces: - x: $dataset.source "y": $dataset.share orientation: v type: bar name: $dataset.main_mode facet_col: $dataset.employment layout: barmode: stack height: 6.0 category_2_employment: - type: plotly title: Modal distance distribution description: by employment datasets: dataset: file: analysis/population/mode_share_per_employment.csv pivot: exclude: - main_mode - dist_group - employment namesTo: source valuesTo: share normalize: groupBy: - dist_group - source - employment target: share rename: sim_share: Sim ref_share: Ref traces: - x: $dataset.dist_group "y": $dataset.share orientation: v type: bar name: $dataset.main_mode facet_col: $dataset.employment layout: xaxis: title: Distance group color: "#444" type: '-' barmode: stack yaxis: title: Share color: "#444" type: '-' interactive: dropdown multiIndex: dist_group: source category_header_economic_status: - type: text backgroundColor: transparent content: "## **Economic_status**" category_1_economic_status: - type: plotly title: Mode share description: by economic_status datasets: dataset: file: analysis/population/mode_share_per_economic_status.csv pivot: exclude: - main_mode - dist_group - economic_status namesTo: source valuesTo: share aggregate: func: SUM target: share groupBy: - main_mode - source - economic_status rename: sim_share: Sim ref_share: Ref traces: - x: $dataset.source "y": $dataset.share orientation: v type: bar name: $dataset.main_mode facet_col: $dataset.economic_status layout: barmode: stack height: 6.0 category_2_economic_status: - type: plotly title: Modal distance distribution description: by economic_status datasets: dataset: file: analysis/population/mode_share_per_economic_status.csv pivot: exclude: - main_mode - dist_group - economic_status namesTo: source valuesTo: share normalize: groupBy: - dist_group - source - economic_status target: share rename: sim_share: Sim ref_share: Ref traces: - x: $dataset.dist_group "y": $dataset.share orientation: v type: bar name: $dataset.main_mode facet_col: $dataset.economic_status layout: xaxis: title: Distance group color: "#444" type: '-' barmode: stack yaxis: title: Share color: "#444" type: '-' interactive: dropdown multiIndex: dist_group: source choice-intro: - type: text backgroundColor: transparent content: | ### **Information** Note that these metrics are based on a single run and may have limited interpretability. For a more robust evaluation, consider running multiple simulations with different seeds and use metrics that consider probabilities as well. (log-likelihood, Brier score, etc.) For policy cases, these metrics do not have any meaning. They are solely for the base-case. - Precision is the fraction of instances correctly classified as belonging to a specific class out of all instances the model predicted to belong to that class. - Recall is the fraction of instances in a class that the model correctly classified out of all instances in that class. - The macro-average computes the metric independently for each class and then take the average (hence treating all classes equally). - The micro-averages of Precision, Recall and F1 score are identical to the accuracy. - Cohen's Kappa is a measure of agreement between two raters that corrects for chance agreement. 1.0 indicates perfect agreement, 0.0 or less indicates agreement by chance. choice: - type: csv title: Choice Evaluation description: Metrics for mode choice. dataset: analysis/population/mode_choice_evaluation.csv showAllRows: true - type: csv title: Choice Evaluation per Mode description: Metrics for choices per mode. dataset: analysis/population/mode_choice_evaluation_per_mode.csv showAllRows: true choice-plots: - type: heatmap title: Confusion Matrix description: Share of (mis)classified modes. dataset: analysis/population/mode_confusion_matrix.csv "y": True/Pred xAxisTitle: Predicted yAxisTitle: "True" flipAxes: false showLabels: true - type: plotly title: Mode Prediction Error description: Plot showing the number of (mis)classified modes. datasets: dataset: analysis/population/mode_prediction_error.csv traces: - x: $dataset.true_mode "y": $dataset.count orientation: v type: bar name: $dataset.predicted_mode layout: xaxis: title: True mode color: "#444" type: '-' barmode: stack yaxis: title: Predicted mode count color: "#444" type: '-'