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SCRG

This repository contains materials broadly related to the Statewide Coastal Restoration Guide (SCRG) project.

Set up

Python Development

So far there isn't a specific version of python necessary, but we recommend >= 3.11. It is also recommended that Python development proceed within a virtual environment to ensure that the code be replicable across machines. Here is the code necessary to set up a python virtualenv and -install the python dependencies.

# This creates the virtual environment directory where all the python
# dependencies are saved. The path saved at the end can be saved in
# the SCRG directory as `scrg_pyenv` as this is in the .gitignore file.
python -m venv path/to/scrg_pyenv
## The following lines must be run in the SCRG directory.
# This activates virtual env in LINUX ONLY
source path/to/scrg_pyenv/bin/activate
# This activates virtual env in WINDOWS ONLY
activate
# With the virtual env activated, install the python dependencies
pip install -r requirements.txt

R Development

There is currently no required version of R, but it is recommended that the version be > 4, if not >= 4.3. Make sure that your R environment has the following packages:

install.packages("sf")
install.packages("stringdist")
install.packages("devtools")
# You will need to access an archived version of the `automap` package
devtools::install_version("automap", version = "1.1-12", repos = "http://cran.us.r-project.org")

# Since the package is contained in a subdirectory of this repository,
# you will need to specify that you want to install from the "ecoinfoscrg" subdirectory
devtools::install_github("https://github.com/ecoinformatic/SCRG/", subdir = "ecoinfoscrg")

An example workflow for the package "Meta-Analysis_Model_Full_Workflow" can be found in the "ecoinfoscrg/inst/scripts/" subdirectory.

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Materials broadly related to the SU2024 Statewide Coastal Restoration Guide (SCRG) project

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