PT Fares

Import Fares

The key steps involved in the fares importer process in EMME, includes;

  1. Importing Modules - Imports necessary modules for data manipulation, logging, and database interaction.
  2. Function Definition - The main function build_store_translink_fares is defined to handle the fare matrix creation process. This function reads fare periods, fare groups, fare costs, and centroid data from CSV files and a database table.
  3. Data Merging - The script merges fare costs with fare groups and periods to create a comprehensive fare cost dataset.
  4. Grouping and Organising Data - It groups the fare data by fare group, period, and zones traversed, then organises it into a DataFrame.
  5. Creating Fare Matrices - The script generates a list of required fare matrices and matches zones to fare zones.
  6. Matrix Initialisation and Population - For each fare matrix, it calculates group fares, initialises an empty matrix in EMME, and populates it with the calculated fare data.

Calculate Fares

This script contains two functions that work with pandas DataFrames to calculate fare zones and group fares for PTM, including;

  1. get_zones_traversed_matrix
    • Takes a DataFrame of centroids matched to fare zones.
    • Creates a Cartesian join of all possible origin-destination pairs.
    • Merges the fare zones for each origin and destination.
    • Calculates the number of zones traversed for each pair.
    • Returns a DataFrame with origin, destination, and the number of zones traversed.
  2. calculate_group_fares
    • Takes a DataFrame of fare groups and the zones traversed DataFrame.
    • Merges the fare groups with the zones traversed DataFrame.
    • Sorts the merged DataFrame by origin and destination.
    • Creates and returns a pivot table where each cell represents the fare for a specific origin-destination pair.