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-rwxr-xr-x[-rw-r--r--]bin/analyze-archive.py10
1 files changed, 6 insertions, 4 deletions
diff --git a/bin/analyze-archive.py b/bin/analyze-archive.py
index 47fabd4..685ce92 100644..100755
--- a/bin/analyze-archive.py
+++ b/bin/analyze-archive.py
@@ -311,10 +311,10 @@ 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))
+ 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
@@ -377,6 +377,8 @@ if __name__ == '__main__':
))
if 'param' in show_models or 'all' in show_models:
+ if not model.stats.can_be_fitted():
+ print('[!] measurements have insufficient distinct numeric parameters for fitting. A parameter-aware model is not available.')
for state in model.states():
for attribute in model.attributes(state):
if param_info(state, attribute):