From 5d0fdb101f3c23b3df1b5ab9cb2c85dd41edb25f Mon Sep 17 00:00:00 2001 From: Daniel Friesel Date: Mon, 7 Oct 2019 16:38:46 +0200 Subject: Move codependent parameter logic to ParamStats / parameters.py --- bin/analyze-archive.py | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) (limited to 'bin/analyze-archive.py') diff --git a/bin/analyze-archive.py b/bin/analyze-archive.py index a4af02a..69eab6e 100755 --- a/bin/analyze-archive.py +++ b/bin/analyze-archive.py @@ -79,9 +79,10 @@ import json import plotter import re import sys -from dfatool import PTAModel, RawData, pta_trace_to_aggregate, filter_aggregate_by_param +from dfatool import PTAModel, RawData, pta_trace_to_aggregate from dfatool import soft_cast_int, is_numeric, gplearn_to_function from dfatool import CrossValidator +from utils import filter_aggregate_by_param opts = {} @@ -301,6 +302,11 @@ if __name__ == '__main__': '', param, model.stats.param_dependence_ratio(state, 'power', param))) + if model.depends_on_param(state, 'power', param) and len(model.stats.stats[state]['power']['param_data'][param]['codependent_parameters']): + print('{:24s} co-dependencies: {:s}'.format('', ', '.join(model.stats.stats[state]['power']['param_data'][param]['codependent_parameters']))) + for combi, depends in model.stats.stats[state]['power']['param_data'][param]['depends_for_codependent_value'].items(): + print('{} -> {}'.format(combi, depends)) + for trans in model.transitions(): # Mean power is not a typical transition attribute, but may be present for debugging or analysis purposes try: -- cgit v1.2.3