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-rwxr-xr-xlib/dfatool.py11
1 files changed, 6 insertions, 5 deletions
diff --git a/lib/dfatool.py b/lib/dfatool.py
index 3d8c321..a66e673 100755
--- a/lib/dfatool.py
+++ b/lib/dfatool.py
@@ -1062,7 +1062,7 @@ def _num_args_from_by_name(by_name):
num_args[key] = len(value['args'][0])
return num_args
-def get_fit_result(results, name, attribute):
+def get_fit_result(results, name, attribute, verbose = False):
"""
Parse and sanitize fit results for state/transition/... 'name' and model attribute 'attribute'.
@@ -1071,18 +1071,19 @@ def get_fit_result(results, name, attribute):
:param results: fit results as returned by `paramfit.results`
:param name: state/transition/... name, e.g. 'TX'
:param attribute: model attribute, e.g. 'duration'
+ :param verbose: print debug message to stdout when deliberately not using a determined fit function
"""
fit_result = dict()
for result in results:
if result['key'][0] == name and result['key'][1] == attribute and result['result']['best'] != None:
this_result = result['result']
if this_result['best_rmsd'] >= min(this_result['mean_rmsd'], this_result['median_rmsd']):
- vprint(self.verbose, '[I] Not modeling {} {} as function of {}: best ({:.0f}) is worse than ref ({:.0f}, {:.0f})'.format(
+ vprint(verbose, '[I] Not modeling {} {} as function of {}: best ({:.0f}) is worse than ref ({:.0f}, {:.0f})'.format(
name, attribute, result['key'][2], this_result['best_rmsd'],
this_result['mean_rmsd'], this_result['median_rmsd']))
# See notes on depends_on_param
elif this_result['best_rmsd'] >= 0.8 * min(this_result['mean_rmsd'], this_result['median_rmsd']):
- vprint(self.verbose, '[I] Not modeling {} {} as function of {}: best ({:.0f}) is not much better than ({:.0f}, {:.0f})'.format(
+ vprint(verbose, '[I] Not modeling {} {} as function of {}: best ({:.0f}) is not much better than ({:.0f}, {:.0f})'.format(
name, attribute, result['key'][2], this_result['best_rmsd'],
this_result['mean_rmsd'], this_result['median_rmsd']))
else:
@@ -1282,7 +1283,7 @@ class AnalyticModel:
if name in self._num_args:
num_args = self._num_args[name]
for attribute in self.by_name[name]['attributes']:
- fit_result = get_fit_result(paramfit.results, name, attribute)
+ fit_result = get_fit_result(paramfit.results, name, attribute, self.verbose)
if len(fit_result.keys()):
x = analytic.function_powerset(fit_result, self.parameters, num_args)
@@ -1639,7 +1640,7 @@ class PTAModel:
if arg_support_enabled and self.by_name[state_or_tran]['isa'] == 'transition':
num_args = self._num_args[state_or_tran]
for model_attribute in self.by_name[state_or_tran]['attributes']:
- fit_results = get_fit_result(paramfit.results, state_or_tran, model_attribute)
+ fit_results = get_fit_result(paramfit.results, state_or_tran, model_attribute, self.verbose)
if (state_or_tran, model_attribute) in self.function_override:
function_str = self.function_override[(state_or_tran, model_attribute)]