Installation Instructions

Installing CalibrateEmulateSample.jl

Currently CalibrateEmulateSample (CES) depends on some external python dependencies including scipy (version 1.8.1 works) and scikit-learn (version 1.1.1 works) that are wrapped by ScikitLearn.jl.

If you have dependencies installed already, then the code can be used by simply entering

julia --project
> ]
> add CalibrateEmulateSample

One may instead clone the project into a new local repository (using SSH or https link from github), to easily access the CES codebase (e.g. to run our example suite) .

If you do not have the dependencies installed, we have found it is easiest to install them via Julia's "Conda.jl",

julia --project
> ]
> add Conda
> add CalibrateEmulateSample

Then install the dependencies by having the project use its own Conda environment variable (set by exporting the ENV variable PYTHON="").

> PYTHON="" julia --project -e 'using Pkg; Pkg.instantiate()'

This call should build Conda and Pycall. The scikit-learn package (along with scipy) then has to be installed if using a Julia project-specific Conda environment:

> PYTHON="" julia --project -e 'using Conda; Conda.add("scipy=1.8.1", channel="conda-forge")'
> PYTHON="" julia --project -e 'using Conda; Conda.add("scikit-learn=1.1.1")'

See the PyCall.jl documentation for more information about how to configure the local Julia / Conda / Python environment.

To test that the package is working:

> julia --project -e 'using Pkg; Pkg.test()'

Building the documentation locally

You need to first build the top-level project before building the documentation:

cd CalibrateEmulateSample.jl
julia --project -e 'using Pkg; Pkg.instantiate()'

Then you can build the project documentation under the docs/ sub-project:

julia --project=docs/ -e 'using Pkg; Pkg.instantiate()'
julia --project=docs/ docs/make.jl

The locally rendered HTML documentation can be viewed at docs/build/index.html. Occasional figures may only be viewable in the online documentation due to the fancy-url package.