compass.landice.tests.ismip7_calibration.objective.run_optimisation

compass.landice.tests.ismip7_calibration.objective.run_optimisation(terms, param_values, resolution=8000.0, sample_size=100000, seed=None)[source]

Sample the objective function and return the parameter distribution.

Parameters:

  • terms (dict) – From build_toolbox_terms()

  • param_values (numpy.ndarray) – The parameter grid the terms were built on

  • resolution (float, optional) – Passed through to the toolbox; it does not use it for these terms, which arrive already aggregated

  • sample_size (int, optional) – Number of random draws of the term weights and the targets

  • seed (int, optional) – Seed for the random draws. Set it so that the reported percentiles are reproducible; the toolbox draws from the global numpy random state.

Returns:

result (dict) – p5, median, p95, mode, the raw min_p1, and at_upper_bound, the fraction of draws that chose the largest parameter on the grid