customized distribution of prior when using DREAM

[cymkG]

Hello,
I’m currently working on uncertainty analysis using the DREAM algorithm, and I noticed that the library (https://github.com/thouska/spotpy/blob/master/src/spotpy/parameter.py ) does not seem to include a zero-mean Gaussian distribution truncated at 0 for the prior of one of the parameters, as this type of distribution is recommended to avoid negative values for my analysis.
Could you please help to provide a sample code to implement such a distribution, so it can be run when using the DREAM algorithm?
Thank you so much.