ostat.c

图像处理的压缩算法

	
	// Rows and columns are indexed from 0
	
	// Output Test name in Means Comparison header in
	iRow = 0; // row 1 and column 2 of worksheet
	iCol = 1;
	strOut.Format( AN1_MEANS_COMP_HDR1, strTestName );
	wksMeansTable.SetCell( iRow, iCol, strOut );
	
	// Localize significance level and the test value
	strSigLevel = LocalizeDouble( dSigLevel, OSTAT_SIG_CON_LEVEL_FORMAT );

	// Output Significance Level in Means Comparison header in
	iRow = 3; // row 4 and column 7 of worksheet
	iCol = 6;
	strOut.Format( AN_MEANS_COMP_AT_LEVEL, strSigLevel );
	wksMeansTable.SetCell( iRow, iCol, strOut );	

	// Loop on all selected datasets
	for( jj = 1; jj < inData; jj++ )
	{
		// Compute row of current dataset
		iRow++;
		if( jj != 1 ) //  For all but first dataset...
		{
			Type_Blank_Lines_To_Wks( wksMeansTable, iRow, 2 ); // Blank out 2 rows and skip one blank row
			iRow++;
		}
		
		// Output current dataset name in column 2 in row of current dataset 
		iCol = 1;
		strDB.Format( "%%A=ANOVA1Way!SelectedDataLBX.v%d$", jj );
		LT_execute( strDB );
		LT_get_str( "%A", szTemp, 40 );
		strDatasetName = szTemp;
		wksMeansTable.SetCell( iRow, iCol, strDatasetName );
		
		// Output mean of current dataset in column 3 in row of current dataset 
		iCol++;
		wksMeansTable.SetCell( iRow, iCol, vMEAN[jj - 1] );
		
		// Output separator line
		iRow++;
		Type_Separator_Line_To_Wks( wksMeansTable, iRow );
		
		for( ii = jj + 1; ii <= inData; ii++ )
		{
			// Compute row of comparison dataset and initially blank row out
			iRow++;
			Type_Blank_Lines_To_Wks( wksMeansTable, iRow, 1 );
			
			// Output comparison dataset name in column 2 in row of comparison dataset
			iCol = 1;
			strDB.Format( "%%A=ANOVA1Way!SelectedDataLBX.v%d$", ii );
			LT_execute( strDB );
			LT_get_str( "%A", szTemp, 40 );
			strDatasetName = szTemp;
			wksMeansTable.SetCell( iRow, iCol, strDatasetName );
			
			// Output mean of comparison dataset in column 3 in row of comparison dataset 
			iCol++;
			wksMeansTable.SetCell( iRow, iCol, vMEAN[ii - 1] );

			// Output the difference of the mean of the current dataset minus the mean of the comparison
			//  dataset in column 4
			iCol++;
			dMeanDif = vMEAN[jj - 1] - vMEAN[ii - 1];
			wksMeansTable.SetCell( iRow, iCol, dMeanDif );

			// Compute index into confidence limit and significance vectors			
			iv = ( ( ii - 1 ) * ( ii - 2 ) ) / 2 + ( jj - 1 );
			
			// Output lower confidence limit for difference of means in column 5
			iCol++;
			wksMeansTable.SetCell( iRow, iCol, vCILT[iv] );

			// Output upper confidence limit for difference of means in column 6
			iCol++;
			wksMeansTable.SetCell( iRow, iCol, vCIUT[iv] );

			// Output significance decision YES or NO in column 7
			iCol++;
			if( vISIG[iv] == 1 )
				strOut = AN_SIGNIFICANT_YES;
			else
				strOut = AN_SIGNIFICANT_NO;
			wksMeansTable.SetCell( iRow, iCol, strOut );
		}

		// Output separator line
		iRow++;
		Type_Separator_Line_To_Wks( wksMeansTable, iRow );
	}
		
	// GJL 11/14/02 v7.0434 USE_OC_WKS_TYPE_NOT_LT
	// Send output Means Comparison worksheet to Results Log
	wksMeansTable.Type( TYPETARGET_OUTPUTLOG, NULL, 8 );

	return OSTAT_NO_ERROR;
}

////////////////////////////////////////////////////////////////////////////////////
/**
		Main Two-Way ANOVA function used to compute and output the Two-Way ANOVA
		table, Means Comparison, and Power analysis.
	Example:
		See the [ANOVA2Way] section in the ANOVA2Way.OGS file.
	Parameter:
		dSigLevel=Significance Level
		iInteractions=Enable (1) or disable (0) computation of Two-Way ANOVA interactions
		iSpecifyLevelsBy=Method of specifying levels. By Dataset=1, by Classification
			Variable=2
		iN=Number of selected datasets
		iPower=Bitwise integer specifying whether or not to compute actual and hypothetical
			Power: Actual=1, Hypothetical=2
		dPowerAlpha=Alpha used to compute Power
		strSampleSize=Name of dataset holding comma separated list of hypothetical sample sizes
		iTest=Bitwise integer specifying which Means Comparison test(s) if any to run:
			Bonferroni=1, Scheffe=2, Tukey=4
	Return:
		Outputs the Two-Way ANOVA table, Means Comparison table, and Power Analysis table
		to the Results Log. Returns OSTAT_NO_ERROR on successful exit or an OSTAT error
		code on failure.
*/
int osANOVA2Way( double dSigLevel, int iInteractions, int iSpecifyLevelsBy, int nData, int iPower, double dPowerAlpha,
	 string strSampleSizes, int iTest )
{
	int iErr, iANOVAErr;
	int nLevelsA, nLevelsB, nPts;
	char cFactor;
	string strErrMsg;
	
	// Vector to hold names of selected datasets
	vector<string> vDataNames;
	vDataNames.SetSize( nData );

	// Vectors to hold integral indexes to levels of Factors A and B
	vector<int> vFACTOR_A;
	vector<int> vFACTOR_B;
	
	// Vector to hold the values of the dependent variable
	vector<double> vDEP_VAR;
	
	// Vectors to hold the text values of the levels of Factors A and B 
	vector<string> vLEVELSA;
	vector<string> vLEVELSB;

	// A four element array of an ANOVA2_Row structure to hold ANOVA2 Table
	ANOVA2_Row arANOVA2_Table[4];

	// Get all datasets needed from the Origin project file, combine individual datasets into factor A and factor B
	// vectors (if needed), and return the number of levels and the number of data points in each factor
	iErr = osANOVA2Way_Get_Data( iSpecifyLevelsBy, nData, vDataNames, vFACTOR_A, vLEVELSA, nLevelsA, vFACTOR_B, vLEVELSB,
		 nLevelsB, vDEP_VAR, nPts );
	if( iErr != OSTAT_NO_ERROR )	// If error getting data return without performing ANOVA
		return iErr;

	// Factor A must have at least 2 levels, if not display error message and return
	if( nLevelsA < 2 )
	{																		
		Type_ErrorMsg( AN2_TOO_FEW_LEVELSA );
		return OSTAT_ABORT_NO_ERROR_MSG;
	}

	// Factor B must have at least 2 levels, if not display error message and return	
	if( nLevelsB < 2 )
	{
		Type_ErrorMsg( AN2_TOO_FEW_LEVELSB );
		return OSTAT_ABORT_NO_ERROR_MSG;
	}
	
	// Compute all values displayed in Two-Way ANOVA table 
	iANOVAErr = osANOVA2Way_Compute_ANOVA_Table( iInteractions, vFACTOR_A, nLevelsA, vFACTOR_B, nLevelsB, vDEP_VAR, nPts, &arANOVA2_Table[0] );

	// Output Two-Way ANOVA table to Results Log even if there were errors (still may be useful information)
	iErr = osANOVA2Way_ANOVA_Table_Output_to_ResultsLog( iSpecifyLevelsBy, nData, vDataNames, iInteractions, &arANOVA2_Table[0] );
	
	// If errors found when computing ANOVA table then exit after outputing ANOVA table and error message
	if( iANOVAErr != OSTAT_NO_ERROR )
	{
		strErrMsg.Format( AN2_COMPUTATIONAL_ERROR_MSG, iANOVAErr ); 
		Type_ErrorMsg( strErrMsg );
		return OSTAT_ABORT_NO_ERROR_MSG;
	}
	
	// If errors found when outputing ANOVA table then exit 
	if( iErr != OSTAT_NO_ERROR )
		return iErr;

	// If Two-Way ANOVA Means Comparison is requested...
	if( iTest )
	{
		// Perform Means Comparison of Factor A Levels, output to Results Log, and return if error
		cFactor = 'A';
		iErr = osANOVA2Way_Means_Comparison( cFactor, iTest, vFACTOR_A, vLEVELSA, nLevelsA, vDEP_VAR, nPts,
			arANOVA2_Table[3].dDF, arANOVA2_Table[3].dMS, dSigLevel );
		if( iErr != OSTAT_NO_ERROR )
			return iErr;	

		// Perform Means Comparison of Factor B Levels, output to Results Log, and return if error
		cFactor = 'B';
		iErr = osANOVA2Way_Means_Comparison( cFactor, iTest, vFACTOR_B, vLEVELSB, nLevelsB, vDEP_VAR, nPts,
			arANOVA2_Table[3].dDF, arANOVA2_Table[3].dMS, dSigLevel );
		if( iErr != OSTAT_NO_ERROR )
			return iErr;
	}

	// If Actual Power computation is requested...
	if( iPower & 1 )
	{
		// Perform Power computations, output to Results Log, and return if error 
		iErr = osANOVA2Way_Power( iPower, iInteractions, dPowerAlpha, nPts, strSampleSizes,
			 &arANOVA2_Table[0] );
		if( iErr != OSTAT_NO_ERROR )
			return iErr;
	}

	return OSTAT_NO_ERROR;
}

/**
		Two-Way ANOVA function to read in and pre-process all required input datasets.
	Example:
		See the function osANOVA2Way above for a sample call.
	Parameter:
		iSpecifyLevelsBy=Radio button setting that determines how levels are specified: either by datasets (1)
			or by classification variables (2)
		nData=Number of input datasets
		vDataNames=Output vector containing names of all input datasets and their levels or variable types
		vFACTOR_A=Output vector containing integerized Factor A level indices into vLEVELSA for each data point
		vLEVELSA=Output vector containing Factor A level names indexed by vFACTOR_A
		nLevelsA=The output number of Factor A levels
		vFACTOR_B=Output vector containing integerized Factor B level indices into vLEVELSB for each data point
		vLEVELSB=Output vector containing Factor B level names indexed by vFACTOR_B
		nLevelsB=The output number of Factor B levels
		vDEP_VAR=Vector containing the dependent variable data whose levels are indicated by the paired vectors
			vFACTOR_A and vFACTOR_B
		iSize=The number of data values in the dependent variable vector
	Return:
		Returns required datasets and OSTAT_NO_ERROR on successful exit or an OSTAT error code on failure.
*/
int osANOVA2Way_Get_Data( int iSpecifyLevelsBy, int nData, vector<string> &vDataNames, vector<int> &vFACTOR_A,
	 vector<string> &vLEVELSA, int &nLevelsA, vector<int> &vFACTOR_B, vector<string> &vLEVELSB, int &nLevelsB,
	 vector<double> &vDEP_VAR, int &iSize )
{
	BOOL bErr;
	int ii, jj, iErr;
	string str, strDB, strErrMsg;
	char szTemp[40];

	// Matrix to hold the number of data values in each treatment level combination 
	matrix<int> mValuesPerCell;

	// Input dataset
	Dataset dsDATA_IN();
	
	if( iSpecifyLevelsBy == 1 ) // If levels are specified by Dataset...
	{
		int iiA, iiB;
		int iNewSize, iIncrSizeBy;
		string strDataName, strLevelA, strLevelB;
				
		// Set vector of strings to size 0 and then start adding levels datasets
		vLEVELSA.SetSize(0);
		vLEVELSB.SetSize(0);
		
		// Get all dataset and level names from list control in Two-Way ANOVA DB
		for( ii = 0; ii < nData; ii++ )
		{
			// Get name of dataset in row ii and column 1 of list control
			strDB.Format( "%%A=ANOVA2Way!SelectedDataLCNTRL.V%d_1$", ii + 1 );
			LT_execute( strDB );
			LT_get_str( "%A", szTemp, 40 );
			strDataName = szTemp;
			
			// Get name of Level A in row ii and column 2 of list control
			strDB.Format( "%%A=ANOVA2Way!SelectedDataLCNTRL.V%d_2$", ii + 1 );
			LT_execute( strDB );
			LT_get_str( "%A", szTemp, 40 );
			strLevelA = szTemp;
			
			// Get name of Level B in row ii and column 3 of list control
			strDB.Format( "%%A=ANOVA2Way!SelectedDataLCNTRL.V%d_3$", ii + 1 );
			LT_execute( strDB );
			LT_get_str( "%A", szTemp, 40 );
			strLevelB = szTemp;
			
			// Save dataset and level names for later output
			str.Format( OSTAT_STR_TOKEN, OSTAT_SEPARATOR_CHAR, strLevelA );
			vDataNames[ii] = strDataName + str;
			str.Format( OSTAT_STR_TOKEN, OSTAT_SEPARATOR_CHAR, strLevelB );
			vDataNames[ii] += str;
			
			// Add new level names to vector of strings for sorting
			osANOVA2Way_Add_String_to_Vector( strLevelA, vLEVELSA );
			osANOVA2Way_Add_String_to_Vector( strLevelB, vLEVELSB );
		}

		vLEVELSA.Sort(); // Sort level names in Factor A Levels vector (in ascending order) 
		vLEVELSB.Sort(); // Sort level names in Factor B Levels vector (in ascending order)
		
		// Read in dependent variable dataset and assign indices for level names in sorted vectors
		iSize = 0;  
		for( ii = 0; ii < nData; ii++ )
		{
			// Get dataset and level names 
			str = vDataNames[ii]; // Get current element of vDataNames string array
			strDataName = str.GetToken( 0, OSTAT_SEPARATOR_CHAR );
			strLevelA = str.GetToken( 1, OSTAT_SEPARATOR_CHAR );
			strLevelB = str.GetToken( 2, OSTAT_SEPARATOR_CHAR );

			// Read in dependent variable dataset values
			dsDATA_IN.Attach( strDataName );
			vector<double> vDATA_IN( dsDATA_IN, TRUE ); // Copy dataset to vector removing missing and masked values

			// Get index of level name from sorted vector of strings holding all level names
			iiA = osANOVA2Way_Add_String_to_Vector( strLevelA, vLEVELSA ) + 1; // Add 1 because NAG indexs from 1
			iiB = osANOVA2Way_Add_String_to_Vector( strLevelB, vLEVELSB ) + 1;
			
			iIncrSizeBy = vDATA_IN.GetSize(); // Get number of elements to be added
			iNewSize = iSize + iIncrSizeBy;   // Compute new size of variables
			vDEP_VAR.SetSize( iNewSize );     // Set new size of vectors
			vFACTOR_A.SetSize( iNewSize );
			vFACTOR_B.SetSize( iNewSize );

			for( jj = 0; jj < iIncrSizeBy; jj++ )       // Loop for each element in input dataset
			{
				vDEP_VAR[ iSize + jj ] = vDATA_IN[jj];  // Copy dependent variable value to vector
				vFACTOR_A[ iSize + jj ] = iiA;          // Assign index to level name in vLEVELSA
				vFACTOR_B[ iSize + jj ] = iiB;          // Assign index to level name in vLEVELSB
			}
			
			iSize = iNewSize; // Update new current size of vectors 	
			
			dsDATA_IN.Detach(); // No longer need input dataset
		}
	}
	else // Else levels specified by Classification Variables...
	{
		string strVarName, strVarType, strValue;
		string strDepVar, strFactAVar, strFactBVar;
		CategoricalData cdDATA_IN; // Categorical Dataset
		
		for( ii = 1; ii <= nData; ii++ )
		{
			// Get name of dataset in row ii and column 1 of list control
			strDB.Format( "%%A=ANOVA2Way!SelectedDataLCNTRL.V%d_1$", ii );
			LT_execute( strDB );