Algorithms for trajectory similarity measures

This repo contains some algorithms retrieved from literature and implemented in C++ and Python, with the idea of performing analysis and benchmarking in order to help us gain insights to build a Python library that will work with trajectories (in GeoJSON format) to mainly find similarity measures between them.

Usage

For building the C++ libraries that the src directory will contain the Makefile needs to be modified and executed:

make

Notice that this should create the dynamic library that will be used by the Python library cppyy.

g++ -fPIC -Wall -o <Dynamic library with .so extension> <C++ file>

make clean will clean compiled files.

For future development we should consider using cmake.

Python integration

To integrate with python, requirements.txt should be installed via pip:

pip install -r requirements.txt

Having done this now you can import cppyy into your code:

import cppyy
cppyy.include('src/your_header_file.h') # Enables calls
cppyy.load_library('your_dynamic_lib.so') # Executes calls
lib = cppyy.gbl # To shorten library calls, i.e.: lib.your_function()

cppyy will meant to be used only for testing!

Jupyter notebooks

Install requirements-jupyter.txt dependencies:

pip install -r requirements-jupyter.txt

This will contain requirements.txt dependencies. Make sure to match same dependencies versions! In order not to get versions conflicts.

Hosting jupyter lab

In order to view, modify or work with the notebooks you only need to run:

jupyter lab

This will open the jupyter host in your default browser.

Directory structure

Below find the proposed structure for this repository:

.
├── .github/workflows       # Github Actions
├── docs                    # Sphinx documentation generator directory
├── examples                # Some useful examples
├── notebooks               # Jupyter notebooks
├── similarity_measures_b106# The python test module (library)
├── src                     # C++ source code
└── tests                   # Tests (C++/Python) to ensure expected outcomes