Matrix manipulation toolkit (high level functions) for transport planners written in python.
Matrices:
- Input / Output in different formats (e.g.: EMME, TBA3).
- Submatrices
- Calculating trip-ends.
- Conversion from one zoning system to another. (Generalization for both cost and demand -trip- matrices)
- Proportions for origins, destinations, columns. (e.g.: segmentation by time periods, demand segments, etc)
- Produce trip-end comparisons between matrices: scatterplots and regression statistics.
Trip-Length Distributions:
- Calculating Trip-Length Distributions from matrices.
- Input / Output in different formats (e.g.: EMME, TBA3).
- Adjust starting point.
- Truncate maximum distance.
- Calculate TLD proportions and average distance.
- Aggregate TLD to different bands.
- Produce TLD graphs.
Gravity models:
- Estimate Gravity Parameters based on different functions.
- Apply gravity models.
Assumes matrices are pandas dataframes, with "Origin" and "Destination" as multiindex, and one column per matrix. Matrices could be trips or cost.