pcompress

Currently it is hard to store the state of every single step of a normal Markov Chain Monte Carlo from GerryChain Python or GerryChain Julia. This repo aims to produce an efficient intermediate binary representation of partitions/districting assignments that will enable for generated plans to be saved on-the-fly. Each step is represented as the diff from the previous step, enabling a significant reduction in disk usage per step.

Note that if a step repeats, it will be omitted.

Installation

bash cargo install pcompress pip install pcompress

Python Usage

Note that chain is a normal MarkovChain object and graph is a normal GerryChain graph.

Recording

```python from pcompress import Record

for partition in Record(chain, "pa-run.chain"): # normal chain stuff here ```

Replaying

```python from pcompress import Record

for partition in Replay(graph, "pa-run.chain", updaters=my_updaters): # normal chain stuff here ```