Minor work regularizing fit statististics for Simple examples

zunzun · Dec 17, 2016 · c9e5a50 · c9e5a50
1 parent 2f69874
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Showing 3 changed files with 300 additions and 5 deletions.
diff --git a/Examples/Simple/FitOneNamedEquation_3D.py b/Examples/Simple/FitOneNamedEquation_3D.py
@@ -30,3 +30,104 @@
 print("Fitted Parameters:")
 for i in range(len(equation.solvedCoefficients)):
     print("    %s = %-.16E" % (equation.GetCoefficientDesignators()[i], equation.solvedCoefficients[i]))
+
+
+equation.CalculateModelErrors(equation.solvedCoefficients, equation.dataCache.allDataCacheDictionary)
+print()
+for i in range(len(equation.dataCache.allDataCacheDictionary['DependentData'])):
+    print('X:', equation.dataCache.allDataCacheDictionary['IndependentData'][0][i],)
+    print('Y:', equation.dataCache.allDataCacheDictionary['IndependentData'][1][i],)
+    print('Z:', equation.dataCache.allDataCacheDictionary['DependentData'][i],)
+    print('Model:', equation.modelPredictions[i],)
+    print('Abs. Error:', equation.modelAbsoluteError[i],)
+    if not equation.dataCache.DependentDataContainsZeroFlag:
+        print('Rel. Error:', equation.modelRelativeError[i],)
+        print('Percent Error:', equation.modelPercentError[i])
+    else:
+        print()
+print()
+
+
+##########################################################
+
+
+equation.CalculateCoefficientAndFitStatistics()
+
+if equation.upperCoefficientBounds or equation.lowerCoefficientBounds:
+    print('You entered coefficient bounds. Parameter statistics may')
+    print('not be valid for parameter values at or near the bounds.')
+    print()
+
+print('Degress of freedom error',  equation.df_e)
+print('Degress of freedom regression',  equation.df_r)
+
+if equation.rmse == None:
+    print('Root Mean Squared Error (RMSE): n/a')
+else:
+    print('Root Mean Squared Error (RMSE):',  equation.rmse)
+
+if equation.r2 == None:
+    print('R-squared: n/a')
+else:
+    print('R-squared:',  equation.r2)
+
+if equation.r2adj == None:
+    print('R-squared adjusted: n/a')
+else:
+    print('R-squared adjusted:',  equation.r2adj)
+
+if equation.Fstat == None:
+    print('Model F-statistic: n/a')
+else:
+    print('Model F-statistic:',  equation.Fstat)
+
+if equation.Fpv == None:
+    print('Model F-statistic p-value: n/a')
+else:
+    print('Model F-statistic p-value:',  equation.Fpv)
+
+if equation.ll == None:
+    print('Model log-likelihood: n/a')
+else:
+    print('Model log-likelihood:',  equation.ll)
+
+if equation.aic == None:
+    print('Model AIC: n/a')
+else:
+    print('Model AIC:',  equation.aic)
+
+if equation.bic == None:
+    print('Model BIC: n/a')
+else:
+    print('Model BIC:',  equation.bic)
+
+
+print()
+print("Individual Parameter Statistics:")
+for i in range(len(equation.solvedCoefficients)):
+    if type(equation.tstat_beta) == type(None):
+        tstat = 'n/a'
+    else:
+        tstat = '%-.5E' %  ( equation.tstat_beta[i])
+
+    if type(equation.pstat_beta) == type(None):
+        pstat = 'n/a'
+    else:
+        pstat = '%-.5E' %  ( equation.pstat_beta[i])
+
+    if type(equation.sd_beta) != type(None):
+        print("Coefficient %s = %-.16E, std error: %-.5E" % (equation.GetCoefficientDesignators()[i], equation.solvedCoefficients[i], equation.sd_beta[i]))
+    else:
+        print("Coefficient %s = %-.16E, std error: n/a" % (equation.GetCoefficientDesignators()[i], equation.solvedCoefficients[i]))
+    print("          t-stat: %s, p-stat: %s, 95 percent confidence intervals: [%-.5E, %-.5E]" % (tstat,  pstat, equation.ci[i][0], equation.ci[i][1]))
+
+
+print()
+print("Coefficient Covariance Matrix:")
+for i in  equation.cov_beta:
+    print(i)
+
+
+print()
+print('Java Source Code:')
+print(pyeq3.outputSourceCodeService().GetOutputSourceCodeJAVA(equation))
diff --git a/Examples/Simple/FitUserData_2D.py b/Examples/Simple/FitUserData_2D.py
@@ -38,8 +38,108 @@
 ##########################################################
 
 
-print(equation.GetDisplayName(), str(equation.GetDimensionality()) + "D")
-print(equation.fittingTargetDictionary[equation.fittingTarget], '=', equation.CalculateAllDataFittingTarget(equation.solvedCoefficients))
+print("Equation:", equation.GetDisplayName(), str(equation.GetDimensionality()) + "D")
+print("Fitting target of", equation.fittingTargetDictionary[equation.fittingTarget], '=', equation.CalculateAllDataFittingTarget(equation.solvedCoefficients))
 print("Fitted Parameters:")
 for i in range(len(equation.solvedCoefficients)):
     print("    %s = %-.16E" % (equation.GetCoefficientDesignators()[i], equation.solvedCoefficients[i]))
+
+
+equation.CalculateModelErrors(equation.solvedCoefficients, equation.dataCache.allDataCacheDictionary)
+print()
+for i in range(len(equation.dataCache.allDataCacheDictionary['DependentData'])):
+    print('X:', equation.dataCache.allDataCacheDictionary['IndependentData'][0][i],)
+    print('Y:', equation.dataCache.allDataCacheDictionary['DependentData'][i],)
+    print('Model:', equation.modelPredictions[i],)
+    print('Abs. Error:', equation.modelAbsoluteError[i],)
+    if not equation.dataCache.DependentDataContainsZeroFlag:
+        print('Rel. Error:', equation.modelRelativeError[i],)
+        print('Percent Error:', equation.modelPercentError[i])
+    else:
+        print()
+print()
+
+
+##########################################################
+
+
+equation.CalculateCoefficientAndFitStatistics()
+
+if equation.upperCoefficientBounds or equation.lowerCoefficientBounds:
+    print('You entered coefficient bounds. Parameter statistics may')
+    print('not be valid for parameter values at or near the bounds.')
+    print()
+
+print('Degress of freedom error',  equation.df_e)
+print('Degress of freedom regression',  equation.df_r)
+
+if equation.rmse == None:
+    print('Root Mean Squared Error (RMSE): n/a')
+else:
+    print('Root Mean Squared Error (RMSE):',  equation.rmse)
+
+if equation.r2 == None:
+    print('R-squared: n/a')
+else:
+    print('R-squared:',  equation.r2)
+
+if equation.r2adj == None:
+    print('R-squared adjusted: n/a')
+else:
+    print('R-squared adjusted:',  equation.r2adj)
+
+if equation.Fstat == None:
+    print('Model F-statistic: n/a')
+else:
+    print('Model F-statistic:',  equation.Fstat)
+
+if equation.Fpv == None:
+    print('Model F-statistic p-value: n/a')
+else:
+    print('Model F-statistic p-value:',  equation.Fpv)
+
+if equation.ll == None:
+    print('Model log-likelihood: n/a')
+else:
+    print('Model log-likelihood:',  equation.ll)
+
+if equation.aic == None:
+    print('Model AIC: n/a')
+else:
+    print('Model AIC:',  equation.aic)
+
+if equation.bic == None:
+    print('Model BIC: n/a')
+else:
+    print('Model BIC:',  equation.bic)
+
+
+print()
+print("Individual Parameter Statistics:")
+for i in range(len(equation.solvedCoefficients)):
+    if type(equation.tstat_beta) == type(None):
+        tstat = 'n/a'
+    else:
+        tstat = '%-.5E' %  ( equation.tstat_beta[i])
+
+    if type(equation.pstat_beta) == type(None):
+        pstat = 'n/a'
+    else:
+        pstat = '%-.5E' %  ( equation.pstat_beta[i])
+
+    if type(equation.sd_beta) != type(None):
+        print("Coefficient %s = %-.16E, std error: %-.5E" % (equation.GetCoefficientDesignators()[i], equation.solvedCoefficients[i], equation.sd_beta[i]))
+    else:
+        print("Coefficient %s = %-.16E, std error: n/a" % (equation.GetCoefficientDesignators()[i], equation.solvedCoefficients[i]))
+    print("          t-stat: %s, p-stat: %s, 95 percent confidence intervals: [%-.5E, %-.5E]" % (tstat,  pstat, equation.ci[i][0], equation.ci[i][1]))
+
+
+print()
+print("Coefficient Covariance Matrix:")
+for i in  equation.cov_beta:
+    print(i)
+
+
+print()
+print('Java Source Code:')
+print(pyeq3.outputSourceCodeService().GetOutputSourceCodeJAVA(equation))
diff --git a/Examples/Simple/FitUserDefinedFunction_2D.py b/Examples/Simple/FitUserDefinedFunction_2D.py
@@ -27,9 +27,103 @@
 ##########################################################
 
 
-print(equation.GetDisplayName(), str(equation.GetDimensionality()) + "D")
-print('User Defined Function:', functionString)
-print(equation.fittingTargetDictionary[equation.fittingTarget], '=', equation.CalculateAllDataFittingTarget(equation.solvedCoefficients))
+print("Equation:", equation.GetDisplayName(), str(equation.GetDimensionality()) + "D")
+print("Fitting target of", equation.fittingTargetDictionary[equation.fittingTarget], '=', equation.CalculateAllDataFittingTarget(equation.solvedCoefficients))
 print("Fitted Parameters:")
 for i in range(len(equation.solvedCoefficients)):
     print("    %s = %-.16E" % (equation.GetCoefficientDesignators()[i], equation.solvedCoefficients[i]))
+
+
+equation.CalculateModelErrors(equation.solvedCoefficients, equation.dataCache.allDataCacheDictionary)
+print()
+for i in range(len(equation.dataCache.allDataCacheDictionary['DependentData'])):
+    print('X:', equation.dataCache.allDataCacheDictionary['IndependentData'][0][i],)
+    print('Y:', equation.dataCache.allDataCacheDictionary['DependentData'][i],)
+    print('Model:', equation.modelPredictions[i],)
+    print('Abs. Error:', equation.modelAbsoluteError[i],)
+    if not equation.dataCache.DependentDataContainsZeroFlag:
+        print('Rel. Error:', equation.modelRelativeError[i],)
+        print('Percent Error:', equation.modelPercentError[i])
+    else:
+        print()
+print()
+
+
+##########################################################
+
+
+equation.CalculateCoefficientAndFitStatistics()
+
+if equation.upperCoefficientBounds or equation.lowerCoefficientBounds:
+    print('You entered coefficient bounds. Parameter statistics may')
+    print('not be valid for parameter values at or near the bounds.')
+    print()
+
+print('Degress of freedom error',  equation.df_e)
+print('Degress of freedom regression',  equation.df_r)
+
+if equation.rmse == None:
+    print('Root Mean Squared Error (RMSE): n/a')
+else:
+    print('Root Mean Squared Error (RMSE):',  equation.rmse)
+
+if equation.r2 == None:
+    print('R-squared: n/a')
+else:
+    print('R-squared:',  equation.r2)
+
+if equation.r2adj == None:
+    print('R-squared adjusted: n/a')
+else:
+    print('R-squared adjusted:',  equation.r2adj)
+
+if equation.Fstat == None:
+    print('Model F-statistic: n/a')
+else:
+    print('Model F-statistic:',  equation.Fstat)
+
+if equation.Fpv == None:
+    print('Model F-statistic p-value: n/a')
+else:
+    print('Model F-statistic p-value:',  equation.Fpv)
+
+if equation.ll == None:
+    print('Model log-likelihood: n/a')
+else:
+    print('Model log-likelihood:',  equation.ll)
+
+if equation.aic == None:
+    print('Model AIC: n/a')
+else:
+    print('Model AIC:',  equation.aic)
+
+if equation.bic == None:
+    print('Model BIC: n/a')
+else:
+    print('Model BIC:',  equation.bic)
+
+
+print()
+print("Individual Parameter Statistics:")
+for i in range(len(equation.solvedCoefficients)):
+    if type(equation.tstat_beta) == type(None):
+        tstat = 'n/a'
+    else:
+        tstat = '%-.5E' %  ( equation.tstat_beta[i])
+
+    if type(equation.pstat_beta) == type(None):
+        pstat = 'n/a'
+    else:
+        pstat = '%-.5E' %  ( equation.pstat_beta[i])
+
+    if type(equation.sd_beta) != type(None):
+        print("Coefficient %s = %-.16E, std error: %-.5E" % (equation.GetCoefficientDesignators()[i], equation.solvedCoefficients[i], equation.sd_beta[i]))
+    else:
+        print("Coefficient %s = %-.16E, std error: n/a" % (equation.GetCoefficientDesignators()[i], equation.solvedCoefficients[i]))
+    print("          t-stat: %s, p-stat: %s, 95 percent confidence intervals: [%-.5E, %-.5E]" % (tstat,  pstat, equation.ci[i][0], equation.ci[i][1]))
+
+
+print()
+print("Coefficient Covariance Matrix:")
+for i in  equation.cov_beta:
+    print(i)