Analysis of Network-constrained Spatial Data
Project description
pysal/spaghetti
SPAtial GrapHs: nETworks, Topology, & Inference
Spaghetti is an open-source Python library for the analysis of network-based spatial data. Originating from the network
module in PySAL (Python Spatial Analysis Library), it is under active development for the inclusion of newly proposed methods for building graph-theoretic networks and the analysis of network events.
An example of a network's minimum spanning tree:
:spaghetti: |
Examples
The following are a selection of some examples that can be launched individually as interactive binders from the links on their respective pages. Additional examples can be found in the Tutorials section of the documentation. See the pysal/notebooks
project for a jupyter-book
version of this repository.
Installation
As of version 1.4.2, spaghetti
officially supports Python 3.6, 3.7, and 3.8. Please make sure that you are operating in a Python >= 3.6 environment.
Installing with conda
via conda-forge
(highly recommended)
To install spaghetti
and all its dependencies, we recommend using the conda
manager, specifically with the conda-forge
channel. This can be obtained by installing the Anaconda Distribution
(a free Python distribution for data science), or through miniconda
(minimal distribution only containing Python and the conda package manager).
Using conda
, spaghetti
can be installed as follows:
$ conda config --set channel_priority strict
$ conda install --channel conda-forge spaghetti
Also, geopandas
provides a nice example to create a fresh environment for working with spatial data.
Installing with PyPI
$ pip install spaghetti
or download the source distribution (.tar.gz
) and decompress it to your selected destination. Open a command shell and navigate to the decompressed folder.
$ pip install .
Warning
When installing via pip
, you have to ensure that the required dependencies for spaghetti
are installed on your operating system. Details on how to install these packages are linked below. Using conda
(above) avoids having to install the dependencies separately.
Install the most current development version of spaghetti
by running:
$ pip install git+https://github.com/pysal/spaghetti
Requirements
Soft Dependencies
Contribute
PySAL-spaghetti is under active development and contributors are welcome.
If you have any suggestions, feature requests, or bug reports, please open new issues on GitHub. To submit patches, please review PySAL: Getting Started, the PySAL development guidelines, the spaghetti
contributing guidelines before opening a pull request. Once your changes get merged, you’ll automatically be added to the Contributors List.
Support
If you are having issues, please create an issue or talk to us in the gitter room.
Code of Conduct
As a PySAL-federated project, spaghetti
follows the Code of Conduct under the PySAL governance model.
License
The project is licensed under the BSD 3-Clause license.
BibTeX Citation
If you use PySAL-spaghetti in a scientific publication, we would appreciate using the following citation:
@misc{Gaboardi2018,
author = {Gaboardi, James D. and Laura, Jay and Rey, Sergio and
Wolf, Levi John and Folch, David C. and Kang, Wei and
Stephens, Philip and Schmidt, Charles},
month = {oct},
year = {2018},
title = {pysal/spaghetti},
url = {https://github.com/pysal/spaghetti},
doi = {10.5281/zenodo.1343650},
keywords = {graph-theory,network-analysis,python,spatial-networks,topology}
}
Funding
This project is/was partially funded through:
Atlanta Research Data Center: A Polygon-Based Approach to Spatial Network Allocation
National Science Foundation Award #1825768: National Historical Geographic Information System
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