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+# Turing Change Point Detection Benchmark
+
+Welcome to the host repository of the Turing Change Point Detection Benchmark, 
+a set of benchmark experiments for the evaluation of change point detection 
+algorithms. This benchmark uses the time series and annotations from the 
+[Turing Change Point Dataset](https://github.com/alan-turing-institute/TCPD) 
+(TCPD).
+
+This directory contains the code necessary to run and analyse a significant 
+number of change point detection algorithms on the TCPD, and serves to 
+reproduce the work in [Van den Burg and Williams (2020)](/url/to/paper).
+
+Note that work based on either TCPD or this repository should cite that paper:
+
+```bib
+```
+
+## Getting Started
+
+This repository contains all the code to generate the results (tables/figures) 
+from the paper, as well as to reproduce the experiments entirely.
+
+### Generating Tables/Figures
+
+Generating the tables and figures from the paper is done through the scripts 
+in ``analysis/scripts`` and can be run through the provided ``Makefile``. 
+
+First make sure you have all requirements:
+
+```
+$ pip install -r ./analysis/requirements.txt
+```
+
+and then use make:
+
+```
+$ make results
+```
+
+The results will be placed in ``./analysis/output``. Note that to generate the 
+figures a working LaTeX and ``latexmk`` installation is needed (see the 
+[labella.py](https://github.com/GjjvdBurg/labella.py) repository for more 
+info).
+
+### Running the experiments
+
+To fully reproduce the experiments, some more steps are needed.
+
+First, obtain the TCPD from [this 
+URL](https://github.com/alan-turing-institute/TCPD) and follow the 
+instructions provided there. Copy the dataset files to a ``datasets`` 
+directory in this repository.
+
+To run all the tasks we use the [abed](https://github.com/GjjvdBurg/abed) 
+command line tool. This allows us to define the experiments in a single 
+configuration file (``abed_conf.py``) and makes it easy to keep track of which 
+tasks still need to be run.
+
+Note that this repository contains all the result files, so it is not 
+necessary to redo all the experiments. If you still wish to do so, the 
+instructions are as follows:
+
+1. Move the current result directory out of the way:
+
+   ```
+   $ mv abed_results old_abed_results
+   ```
+
+2. Install [abed](https://github.com/GjjvdBurg/abed). This requires an 
+   existing installation of openmpi, but otherwise should be a matter of 
+   running:
+
+   ```
+   $ pip install abed
+   ```
+
+3. Tell abed to rediscover all the tasks that need to be done:
+   ```
+   $ abed reload_tasks
+   ```
+
+   This will populate the ``abed_tasks.txt`` file and will automatically 
+   commit the updated file to the Git repository. You can show the number of 
+   tasks that need to be completed through:
+
+   ```
+   $ abed status
+   ```
+
+4. Initialize the virtual environments for Python and R, which installs all 
+   required dependencies:
+
+   ```
+   $ make venvs
+   ```
+
+   Note that this will also create an R virtual environment (using 
+   [RSimpleVenv](https://github.com/GjjvdBurg/RSimpleVenv), which ensures that 
+   the exact versions of the packages used in the experiments will be 
+   installed.
+
+5. Run abed through ``mpiexec``, as follows:
+
+   ```
+   $ mpiexec -np 4 abed local
+   ```
+
+   This will run abed using 4 cores, which can of course be increased if 
+   desired. Note that a minimum of two cores is needed for abed to operate. 
+   Furthermore, you may want to run these experiments in parallel on a large 
+   number of cores, as the expected runtime is on the order of 21 days on a 
+   single core.
+
+
+## License
+
+The code in this repository is licensed under the MIT license, unless 
+otherwise specified. See the [LICENSE file](LICENSE) for further details. 
+Reuse of the code in this repository is allowed, but should cite [our 
+paper](/url/to/paper).
+
+## Notes
+
+If you find any problems or have a suggestion for improvement of this 
+repository, please let us know as it will help us make this resource better 
+for everyone. You can open an issue on 
+[GitHub](https://github.com/alan-turing-institute/TCPDBench) or send an email 
+to ``gvandenburg at turing dot ac dot uk``.