Skip to content

Feedback on GrainLearning from Balazs #52

@chyalexcheng

Description

@chyalexcheng
  • The need for deterministic parameter sampling
    • after each iteration
    • independent GL run
  • Need for constrains during parameter sampling
    • Situations when parameters have constraints v0 < v1 < v2
    • Possibility for users to define their own resample function
  • Common interface as other codes
    • Example scipy or matlab
      def run_sim(batch_parameters,...):
          # loop within the code
          return batch of samples
      
    • Or at least have it well documented and explained
  • Overall improve documentation. More documentation etc.
  • A way to access the current iteration (system linked with calibration module?)
  • On loading previous proposal - an example how it can be done in run_sim
  • Add link to new GL repository on old one

Metadata

Metadata

Assignees

Labels

No labels
No labels

Type

No type
No fields configured for issues without a type.

Projects

No projects

Milestone

No milestone

Relationships

None yet

Development

No branches or pull requests

Issue actions