Installation

From PyPI

Bash

pip install t3co

From Github

First, clone the repository from Github :

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git clone https://github.com/NREL/T3CO.git T3CO

t3co depends on python>=3.8 and <=3.10. One way to satisfy this is to use conda:

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conda create -n t3co python=3.8
conda activate t3co

Navigate to the parent directory containing the T3CO repository e.g. cd github/T3CO/ and run:

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pip install -e .

This installs the local version of T3CO along with all its dependencies.

FASTSim is installed along with other library dependancies. In case of ModuleNotFoundError: No module named 'fastsim':

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pip install fastsim

from within the t3co python 3.8 environment you created.

This will install t3co with minimal dependencies such that t3co files can be editable. Developers will find the -e option handy since t3co will be installed in place from the installation location, and any updates will be propagated each time t3co is freshly imported.

to be compatible with the current code in T3CO.

Demo

get some quick TCO results

Bash

cd run_scripts
python sweep.py -skip_all_opt -selections  [1,2,3,4,5] -dst_dir ./demodata

using T3CO Config file

Bash

cd run_scripts
pytho sweep.py -analysis_id 0

using optimiztion in sweep module see

Generate MD Documentation from Docstrings

On Windows

Bash

pip install --user pipx
pipx ensurepath

On Mac

Bash

brew install pipx
pipx ensurepath

Then from T3CO root directory

Bash

pipx install pydoc-markdown
pydoc-markdown -I . -p . --render-toc > CodeReference.md

for specific modules, specify the module name after -m: pydoc-markdown -I . -m run_scripts.sweep --render-toc > CodeReference.md

This generates CodeReference.md including a Table of Contents from all python docstrings in the T3CO package