Analysis of taxicab trajectories in NY region.

Run the modules in order as listed below :

1.> Run the exe

Cleans the data. Put the Jan data in Data\1
The cleand up data will be generated in Output\

**2.> Run the python scripts present in Output **

Converts Lat, Lon to projected co-ordinates

1.> Put the cleanup data into TrajectoryFormation\Data

1.> Run the exe

Generates 5000 unique sampled cab IDs Output file : "sampled.txt" in Data\1\

1.> Run the exe

Creates 5000 trajectory files Output : "{cabID}_trajectory.traj" in Output\

1.> Run the exe

Creates 5000 sampled trajectory files of 720 length each Output : "{cabID}_sampled.traj" in Output\

1.> Run NodePointGenerator.py

Generates 263 node points corresponding to each taxi zone Output file : "NodePoints.data"

1.> Run TrajToNodeConverter.py

Converts the sampled trajectories generated to node point representation Output : "AllTrajecsNopePoints.data"

1.> Run the exe

Trajectory splitting is performed Output file : "{cabID}_{Split_number}.traj" in Output\Split

**1.> Copy "Split" folder to "Clustering\Parallel" ** **2.> Copy "Sampled.txt" folder to "Clustering\Parallel" ****

1.> Run ClusterGenerator.py Output file : "FinalClusters_before_Optimization.csv"

**1.> Copy "FinalClusters_before_Optimization.csv" folder to "Output" ** **2.> Copy "TestTask.data" folder to "Output" ****

**1.> Put "TestTask.data" in Output ** 2.> Run the exe

The optimizing algorithm Output : "FinalClusters.data" in Output
Contains the clustered cab IDs along with their cluster prototype

**1.> Copy "SpecifiedTasks.data" folder to "Output" **

**1.> Put "SpecifiedTasks.data" in Output ** 2.> Run the exe

Assigns Tasks specified in "SpecifiedTasks.data" to suitable cluster Output: "ClusterID_TaskAssignation.data" in Output
contains Cluster ID of each corresponding task