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.