MYRIAD-SIM Code and Files

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Python Code

MYRIAD-SIM is implemented in Python. The code folder includes several scripts required to fit and run the model.

Table 1. Code Files and Their Purpose

File Name	Purpose
bestfitdist.py	Fits the distributions for each variable in each grid for each month.
converttouniform.py	Converts the original data to uniform margins using best-fit distributions.
fitmodel.py	Fits the vine copula model to the different variables for each month.
runmodel.py	Runs the model to generate the synthetic data.
converttouniformoutput.py	Converts synthetic data from uniform margins back to the original data space.

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Environment Setup

To run the code, set up a Python environment using the myriadsim_env.yml file. Follow these instructions:

1. Open Anaconda Prompt.

2. Navigate to the MYRIAD-SIM folder:

   cd 'insert path to your folder here'

3. Create the environment using:

   conda env create -f myriadsim_env.yml

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Training Data

The training data used for this model can be found in the data folder. This is also where the outputs of converttouniform.py are stored.

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Model Files

• The outputs of bestfitdist.py (fitted distributions for each variable) are saved in the varpar folder.
• The outputs of fitmodel.py (vine copula structures for each month) are stored in the modelpar folder.

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Output Files

The outputs generated by runmodel.py are stored in the outputall folder. This supplementary material includes an example of three days. The full dataset, as described in the paper, is already publicly available on Zenodo: 🔗 https://doi.org/10.5281/zenodo.14979282

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