[Quantproject-developers] QuantProject/b1_ADT/Statistics BasicFunctions.cs, 1.12, 1.13

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Update of /cvsroot/quantproject/QuantProject/b1_ADT/Statistics
In directory sc8-pr-cvs16.sourceforge.net:/tmp/cvs-serv16368/b1_ADT/Statistics

Modified Files:
	BasicFunctions.cs 
Log Message:
The method that computes the PearsonCorrelationCoefficient with multipliers has been commented out

Index: BasicFunctions.cs
===================================================================
RCS file: /cvsroot/quantproject/QuantProject/b1_ADT/Statistics/BasicFunctions.cs,v
retrieving revision 1.12
retrieving revision 1.13
diff -C2 -d -r1.12 -r1.13
*** BasicFunctions.cs	20 Apr 2008 17:09:16 -0000	1.12
--- BasicFunctions.cs	11 May 2008 17:50:22 -0000	1.13
***************
*** 274,341 ****
      }
  
! 		#region PearsonCorrelationCoefficient with multipliers
! 		static private void checkMultiplierIsNonZero( double multiplier )
! 		{
! 			if ( multiplier == 0 )
! 				throw new Exception( "A multiplier cannot be zero!" );
! 		}
! 		static private void pearsonCorrelationCoefficient_checkParameters(
! 			double firstArrayMultiplier , float[] firstDataVariable,
! 			double secondArrayMultiplier , float[] secondDataVariable )
! 		{
! 			BasicFunctions.checkLengthOfDataVariables(firstDataVariable, secondDataVariable);
! 			checkMultiplierIsNonZero( firstArrayMultiplier );
! 			checkMultiplierIsNonZero( secondArrayMultiplier );
! 		}
! 		/// <summary>
! 		/// Computes the Pearson's Correlation Coefficient for two weighted arrays
! 		/// </summary>
! 		/// <param name="firstMultiplier">multiplies each value of the
! 		/// first data set</param>
! 		/// <param name="firstDataVariable">first data set</param>
! 		/// <param name="secondMultiplier">multiplies each value of the second
! 		/// data set</param>
! 		/// <param name="secondDataVariable">second data set</param>
! 		/// <returns></returns>
! 		static public double PearsonCorrelationCoefficient(
! 			double firstMultiplier , float[] firstDataVariable,
! 			double secondMultiplier , float[] secondDataVariable ) 
! 		{
! 			pearsonCorrelationCoefficient_checkParameters(
! 				firstMultiplier , firstDataVariable,
! 				secondMultiplier , secondDataVariable );
! 			int n = firstDataVariable.Length;
! 			double sumOfProduct = 0.0, sumOfFirst = 0.0, sumOfSecond = 0.0,
! 				sumOfSquaredFirst = 0.0, sumOfSquaredSecond = 0.0;
! 			double currentValueFromFirstDataSet , currentValueFromSecondDataSet;
! 			for(int i = 0; i < n; i++)
! 			{
! 				currentValueFromFirstDataSet = firstMultiplier * firstDataVariable[i];
! 				currentValueFromSecondDataSet = secondMultiplier * secondDataVariable[i];
! 				sumOfFirst += currentValueFromFirstDataSet;
! 				sumOfSecond += currentValueFromSecondDataSet;
! 				sumOfProduct += currentValueFromFirstDataSet * currentValueFromSecondDataSet;
! 				sumOfSquaredFirst +=
! 					currentValueFromFirstDataSet * currentValueFromFirstDataSet;
! 				sumOfSquaredSecond +=
! 					currentValueFromSecondDataSet * currentValueFromSecondDataSet;
! 			}
! 			double n1 = n*sumOfProduct;
! 			double n2 = sumOfFirst*sumOfSecond;
! 			double numerator = n*sumOfProduct - sumOfFirst*sumOfSecond;
! 			double d1 = n*sumOfSquaredFirst;
! 			double d2 = sumOfFirst*sumOfFirst;
! 			double d3 = n*sumOfSquaredSecond;
! 			double d4 = sumOfSecond*sumOfSecond;
! 			double d5 = d1 - d2;
! 			double d6 = d3 - d4;
! 			double a1 = (n*sumOfSquaredFirst - sumOfFirst*sumOfFirst);
! 			double a2 = (n*sumOfSquaredSecond - sumOfSecond*sumOfSecond);
! 
! 			return (n*sumOfProduct - sumOfFirst*sumOfSecond)/
! 				Math.Sqrt( (n*sumOfSquaredFirst - sumOfFirst*sumOfFirst)*
! 				(n*sumOfSquaredSecond - sumOfSecond*sumOfSecond) );
! 		}
! 		#endregion PearsonCorrelationCoefficient with multipliers
  
  
--- 274,341 ----
      }
  
! //		#region PearsonCorrelationCoefficient with multipliers
! //		static private void checkMultiplierIsNonZero( double multiplier )
! //		{
! //			if ( multiplier == 0 )
! //				throw new Exception( "A multiplier cannot be zero!" );
! //		}
! //		static private void pearsonCorrelationCoefficient_checkParameters(
! //			double firstArrayMultiplier , float[] firstDataVariable,
! //			double secondArrayMultiplier , float[] secondDataVariable )
! //		{
! //			BasicFunctions.checkLengthOfDataVariables(firstDataVariable, secondDataVariable);
! //			checkMultiplierIsNonZero( firstArrayMultiplier );
! //			checkMultiplierIsNonZero( secondArrayMultiplier );
! //		}
! //		/// <summary>
! //		/// Computes the Pearson's Correlation Coefficient for two weighted arrays
! //		/// </summary>
! //		/// <param name="firstMultiplier">multiplies each value of the
! //		/// first data set</param>
! //		/// <param name="firstDataVariable">first data set</param>
! //		/// <param name="secondMultiplier">multiplies each value of the second
! //		/// data set</param>
! //		/// <param name="secondDataVariable">second data set</param>
! //		/// <returns></returns>
! //		static public double PearsonCorrelationCoefficient(
! //			double firstMultiplier , float[] firstDataVariable,
! //			double secondMultiplier , float[] secondDataVariable ) 
! //		{
! //			pearsonCorrelationCoefficient_checkParameters(
! //				firstMultiplier , firstDataVariable,
! //				secondMultiplier , secondDataVariable );
! //			int n = firstDataVariable.Length;
! //			double sumOfProduct = 0.0, sumOfFirst = 0.0, sumOfSecond = 0.0,
! //				sumOfSquaredFirst = 0.0, sumOfSquaredSecond = 0.0;
! //			double currentValueFromFirstDataSet , currentValueFromSecondDataSet;
! //			for(int i = 0; i < n; i++)
! //			{
! //				currentValueFromFirstDataSet = firstMultiplier * firstDataVariable[i];
! //				currentValueFromSecondDataSet = secondMultiplier * secondDataVariable[i];
! //				sumOfFirst += currentValueFromFirstDataSet;
! //				sumOfSecond += currentValueFromSecondDataSet;
! //				sumOfProduct += currentValueFromFirstDataSet * currentValueFromSecondDataSet;
! //				sumOfSquaredFirst +=
! //					currentValueFromFirstDataSet * currentValueFromFirstDataSet;
! //				sumOfSquaredSecond +=
! //					currentValueFromSecondDataSet * currentValueFromSecondDataSet;
! //			}
! //			double n1 = n*sumOfProduct;
! //			double n2 = sumOfFirst*sumOfSecond;
! //			double numerator = n*sumOfProduct - sumOfFirst*sumOfSecond;
! //			double d1 = n*sumOfSquaredFirst;
! //			double d2 = sumOfFirst*sumOfFirst;
! //			double d3 = n*sumOfSquaredSecond;
! //			double d4 = sumOfSecond*sumOfSecond;
! //			double d5 = d1 - d2;
! //			double d6 = d3 - d4;
! //			double a1 = (n*sumOfSquaredFirst - sumOfFirst*sumOfFirst);
! //			double a2 = (n*sumOfSquaredSecond - sumOfSecond*sumOfSecond);
! //
! //			return (n*sumOfProduct - sumOfFirst*sumOfSecond)/
! //				Math.Sqrt( (n*sumOfSquaredFirst - sumOfFirst*sumOfFirst)*
! //				(n*sumOfSquaredSecond - sumOfSecond*sumOfSecond) );
! //		}
! //		#endregion PearsonCorrelationCoefficient with multipliers