Download the code and data: https://github.com/MIT-SPARK/TEASER-plusplus  Follow the instructions: https://github.com/MIT-SPARK/TEASER-plusplus/blob/master/README.md 

Setup This project requires the emp-toolkit. Please install the Semihonest two party computation tool. https://github.com/emp-toolkit/emp-sh2pc   Generating results To generate the time results run the following on a terminal from the root directory: $ python compute_times.py   The output should be 3 csv files called y10_u2_results.csv, y50_u10_results.csv, y250_u50_results.csv.

A temp file for testing.

A temp file for testing.

AHG LIDAR Data Visualization for IRL   Dependencies: - numpy - matplotlib   Recreating information: - ut-walrus-output.pickle contains the rosbag information in pickle format and includes obstacle and trajectory data. - The pickle data can be parsed using pickle_parse.py - The point cloud data in binary is present in full_map_binary.npy and can be visualized using plot_grid.py  

Solves the network-wide contraflow lane reversal problem using three different methodologies . The problem is analougus to many Network Design Problems (NDP). The network and demand data is provided as in TNTP data format. To run use: python3 -m experiments.{name of the file without extension} Requirements: gurobipy, networkx, scipy, numpy, pwlf