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pyincore-viz is a Python project that provides visualization and other utilities for use with pyincore The development is part of NIST sponsored IN-CORE (Interdependent Networked Community Resilience Modeling Environment) initiative.

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IN-CORE/pyincore-viz

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pyincore-viz

pyincore-viz is a component of IN-CORE that provides visualization and other utilities for use with pyincore.

Mac specific notes

  • We use matplotlib library to create graphs. There is a Mac specific installation issue addressed at here (1) and here (2). In a nutshell, insert line: backend : Agg into ~/.matplotlib/matplotlibrc file.

Installation with conda

Installing pyincore-viz with Conda is officially supported by IN-CORE development team.

To add conda-forge channel to your environment, run

conda config –-add channels conda-forge

To install pyincore-viz package, run

conda install -c in-core pyincore-viz

To update pyIncore-viz, run

conda update -c in-core pyincore-viz

Installation with pip

Installing pyincore-viz with pip is NOT supported by IN-CORE development team. Please use pip for installing pyincore-viz at your discretion.

Installing pyincore-viz with pip is only tested on linux environment.

Prerequisite

  • GDAL C library must be installed to install pyincore-viz. (for Ubuntu, gdal-bin and libgdal-dev)
  • For developers, pre-install must be installed. If not, run brew install pre-commit or pip install pre-commit.

To install pyincore-viz package, run

pip install pyincore-viz

Documentation Containter

To build the container with the documentation you can use:

docker build -t doc/pyincore-viz -f Dockerfile.docs .
docker run -ti -p 8000:80 doc/pyincore-viz

Then check the documentation at http://localhost:8000/doc/pyincore_viz/.

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pyincore-viz is a Python project that provides visualization and other utilities for use with pyincore The development is part of NIST sponsored IN-CORE (Interdependent Networked Community Resilience Modeling Environment) initiative.

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