Crime data simulating toolkit
The crime_sim_toolkit is a python package that originated from a joint Alan Turing Institute and Leeds Institute of Data Analytics project formulated by Dr. Dan Birks at the University of Leeds. It focuses on generating simulations of crime demand, using alternate methodologies, that can then be used as an input into an agent based model of police supply.
The toolkit was envisioned to have three main strategies for data simulation:
- a simple poisson sampler based on past data
- a decision tree using a wide range of predictor variables (TODO)
- a microsimulation using transition probabilities
The data_manipulation folder contains notebooks highlighting how some data sources have been constructed.
Installation
Install via Python package index
This package is now available via PyPi.
pip install --user crime_sim_toolkit
Install from sources
You can also install this package from source by cloning this repository, navigating into the crime_sim_toolkit
directory and running the following.
python setup.py install --user
Wiki
Find out how to get started using the crime_sim_toolkit via our Wiki
License
Notes on datafiles
The census_2011_population_hh.csv file is derived from ONS data. Taking data from sheet LSOA and using row 12 as the header row and keeping only rows below with data.
TODO
- Build method for using Police data API
- Decision tree implementation
1 maintainer
Metadata
1 maintainer
Release files for crime-sim-toolkit 1.5.0
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Built distribution (wheel)
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| crime_sim_toolkit-1.5.0-py3-none-any.whl | Python 3 | none | any | Details for crime_sim_toolkit-1.5.0-py3-none-any.whl |
Total release size: 13.6 MB
Release files / crime_sim_toolkit-1.5.0.tar.gz
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Release files / crime_sim_toolkit-1.5.0-py3-none-any.whl
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