From 95d635df4b3daa1df1b66c360f38e4d52ee721eb Mon Sep 17 00:00:00 2001 From: Daniel Friesel Date: Mon, 6 Jul 2020 14:01:08 +0200 Subject: Remove co-dependent parameter detection code It doesn't work and is not methodically sound. Decision/Regression Trees seem to be the way to go --- bin/analyze-archive.py | 15 --------------- 1 file changed, 15 deletions(-) (limited to 'bin/analyze-archive.py') diff --git a/bin/analyze-archive.py b/bin/analyze-archive.py index e9d70f6..80ebd78 100755 --- a/bin/analyze-archive.py +++ b/bin/analyze-archive.py @@ -513,21 +513,6 @@ if __name__ == "__main__": model.stats.param_dependence_ratio(state, "power", param), ) ) - if model.stats.has_codependent_parameters(state, "power", param): - print( - "{:24s} co-dependencies: {:s}".format( - "", - ", ".join( - model.stats.codependent_parameters( - state, "power", param - ) - ), - ) - ) - for param_dict in model.stats.codependent_parameter_value_dicts( - state, "power", param - ): - print("{:24s} parameter-aware for {}".format("", param_dict)) for trans in model.transitions(): # Mean power is not a typical transition attribute, but may be present for debugging or analysis purposes -- cgit v1.2.3