make final fit parameter values
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067857eda2
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6ecc4a4126
@ -186,7 +186,6 @@ class Parameter:
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@property
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@property
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def value(self) -> float | None:
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def value(self) -> float | None:
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# TODO first _value, then _expr
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if self._value is not None:
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if self._value is not None:
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return self._value
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return self._value
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@ -239,3 +238,7 @@ class Parameter:
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return para_copy
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return para_copy
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def fix(self):
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self._value = self.value
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self.namespace = {}
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@ -187,7 +187,7 @@ class FitResult(Points):
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nice_name = m.group(1)
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nice_name = m.group(1)
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if func_number in split_funcs:
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if func_number in split_funcs:
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nice_func = split_funcs[func_number]
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nice_func = split_funcs[func_number]
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pvalue.fix()
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pvalue.name = nice_name
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pvalue.name = nice_name
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pvalue.function = nice_func
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pvalue.function = nice_func
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parameter_dic[pname] = pvalue
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parameter_dic[pname] = pvalue
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@ -196,6 +196,8 @@ class FitResult(Points):
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if modelname[0] == '(' and modelname[-1] == ')':
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if modelname[0] == '(' and modelname[-1] == ')':
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modelname = modelname[1:-1]
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modelname = modelname[1:-1]
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print(parameter_dic)
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return parameter_dic, modelname
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return parameter_dic, modelname
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@property
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@property
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@ -233,9 +235,9 @@ class FitResult(Points):
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s.write(self.parameter_string())
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s.write(self.parameter_string())
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if statistics:
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if statistics:
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s.write('Statistics\n')
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s.write('\nStatistics\n')
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for k, v in self.statistics.items():
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for k, v in self.statistics.items():
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s.write(f' {k} : {v:.4f}')
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s.write(f' {k} : {v:.4f}\n')
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if correlations and self.correlation is not None:
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if correlations and self.correlation is not None:
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s.write('\nCorrelation (partial corr.)\n')
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s.write('\nCorrelation (partial corr.)\n')
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