issue_comments: 285425155

This data as json

html_url issue_url id node_id user created_at updated_at author_association body reactions performed_via_github_app issue
https://github.com/pydata/xarray/issues/1303#issuecomment-285425155 https://api.github.com/repos/pydata/xarray/issues/1303 285425155 MDEyOklzc3VlQ29tbWVudDI4NTQyNTE1NQ== 4160723 2017-03-09T17:44:09Z 2017-03-09T17:44:09Z MEMBER

Thanks for the link @rabernat!

climlab looks very nice and actually very close to what I'm trying to do with landscape evolution modeling (just prototyping at the moment, no repository on GH yet).

What I want to do is something that is a bit more deeply integrated with xarray than what you suggest for climlab. The basic idea is that a parameter of a model (i.e., a climlab.Process) can be either a scalar, an array-like with space and/or time dimensions and/or even its own dimension (useful for exploring a parameter space), or a function (callable) of other model parameters/inputs/state variables (it this case it is also an output which inherits the dimensions from the other variables used for its computation). I think that a lot of logic implemented in xarray can be reused for handling this.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   213004586