Index: trunk/psLib/src/math/psStats.c =================================================================== --- trunk/psLib/src/math/psStats.c (revision 2227) +++ trunk/psLib/src/math/psStats.c (revision 2228) @@ -9,7 +9,7 @@ * @author GLG, MHPCC * - * @version $Revision: 1.79 $ $Name: not supported by cvs2svn $ - * @date $Date: 2004-10-28 00:46:04 $ -n * + * @version $Revision: 1.80 $ $Name: not supported by cvs2svn $ + * @date $Date: 2004-10-28 22:46:57 $ + * * Copyright 2004 Maui High Performance Computing Center, University of Hawaii */ @@ -123,22 +123,4 @@ default: return false; - } -} - -/***************************************************************************** -p_psVectorPrint(myVector, maskVector, maskVal, stats): a private internal -function that simply prints a vector to STDOUT. Used primarily for -debugging. - *****************************************************************************/ - -void p_psVectorPrint(psVector* myVector, psVector* maskVector, psU32 maskVal, psStats* stats) -{ - psS32 i = 0; // Loop index variable. - - for (i = 0; i < myVector->n; i++) { - if (maskVector != NULL) - printf("Element %d is %f (mask is %d)\n", i, myVector->data.F32[i], maskVector->data.U8[i]); - else - printf("Element %d is %f\n", i, myVector->data.F32[i]); } } @@ -428,8 +410,5 @@ // Allocate temporary vectors for the data. unsortedVector = psVectorAlloc(nValues, PS_TYPE_F32); - unsortedVector->n = unsortedVector->nalloc; - sortedVector = psVectorAlloc(nValues, PS_TYPE_F32); - sortedVector->n = sortedVector->nalloc; // Determine if we must only use data points within a min/max range. @@ -579,7 +558,5 @@ // Allocate temporary vectors for the data. unsortedVector = psVectorAlloc(nValues, PS_TYPE_F32); - unsortedVector->n = unsortedVector->nalloc; sortedVector = psVectorAlloc(nValues, PS_TYPE_F32); - sortedVector->n = sortedVector->nalloc; // Determine if we must only use data points within a min/max range. @@ -817,4 +794,6 @@ p_psNormalizeVectorF32(myData): this is a private function which normalizes the elements of a vector to a range between 0.0 and 1.0. + +XXX: how about an arbitrary p_psNormalizeVectorF32(myData, min, max)? *****************************************************************************/ void p_psNormalizeVectorF32(psVector* myData) @@ -847,4 +826,6 @@ elements of a vector to a range between -1.0 and 1.0. XXX: 0-1 or -1:1? + +XXX: how about an arbitrary p_psNormalizeVectorF64(myData, min, max)? *****************************************************************************/ void p_psNormalizeVectorF64(psVector* myData) @@ -876,4 +857,5 @@ } +// XXX: how about an arbitrary p_psNormalizeVector(myData, min, max)? void p_psNormalizeVector(psVector* myData) { @@ -885,87 +867,4 @@ psError(__func__, "Unalowable data type.\n"); } -} - -/***************************************************************************** -p_psGaussian(myData, myParams): an internal function, used by robust stats, -intended to compute the Gaussian with a specified sigma/mean, at the -specified data point. - *****************************************************************************/ -float p_psGaussian(const psVector* restrict myData, - const psVector* restrict myParams) -{ - float x = myData->data.F32[0]; - float mean = myParams->data.F32[0]; - float stdev = myParams->data.F32[1]; - float tmp = exp(-((x - mean) * (x - mean)) / (2.0 * stdev * stdev)); - - tmp /= ((float)sqrt(2.0 * M_PI * (stdev * stdev))); - - // printf("p_psGaussian((%.2f), %.2f, %.2f) is %.2f\n", x, mean, stdev, tmp); - return (tmp); -} - -/***************************************************************************** -p_psGaussianDeriv(myData, myParams, whichParam): an internal function, which -calculates the specified partial derivative of the above Gaussian function. - *****************************************************************************/ -float p_psGaussianDeriv(const psVector* restrict myData, - const psVector* restrict myParams, psS32 whichParam) -{ - float x = myData->data.F32[0]; - float mean = myParams->data.F32[0]; - float stdev = myParams->data.F32[1]; - float tmp = 0.0; - - if (whichParam == 0) { - // Return the derivative w.r.t. the mean. - tmp = (x - mean) * p_psGaussian(myData, myParams); - tmp /= (stdev * stdev); - } else if (whichParam == 1) { - // Return the derivative w.r.t. the stdev. - tmp = (x - mean) * (x - mean) * p_psGaussian(myData, myParams); - tmp /= (stdev * stdev * stdev); - } - printf("p_psGaussianDeriv((%.2f), %.2f, %.2f, (%d)) is %.2f\n", x, mean, stdev, whichParam, tmp); - - return (tmp); -} - -/***************************************************************************** -p_psQuadratic(myData, myParams): an internal function, used by robust stats, -intended to compute a quadratic, with the specified parameters, at the -specified data point. - *****************************************************************************/ -float p_psQuadratic(const psVector* restrict myParams, const psVector* restrict myCoords) -{ - float x = myCoords->data.F32[0]; - float A = myParams->data.F32[0]; - float B = myParams->data.F32[1]; - float C = myParams->data.F32[2]; - float tmp = 0.0; - - tmp = (A * x * x) + (B * x) + C; - return (tmp); -} - -/***************************************************************************** -p_psQuadraticDeriv(myData, myParams, whichParam): an internal function, which -calculates the specified partial derivative of the above quadratic function. - *****************************************************************************/ -float p_psQuadraticDeriv(const psVector* restrict myParams, - const psVector* restrict myCoords, psS32 whichParamDeriv) -{ - float x = myCoords->data.F32[0]; - float tmp = 0.0; - - if (whichParamDeriv == 0) { - tmp = x * x; - } else if (whichParamDeriv == 1) { - tmp = x; - } else if (whichParamDeriv == 2) { - tmp = 1.0; - } - - return (tmp); } @@ -1022,6 +921,4 @@ and i+1 is used for x[i]). It then determines for what value x does that quadratic f(x) = yVal (the input parameter). - -// XXX: Use static variables. *****************************************************************************/ float fitQuadraticSearchForYThenReturnX(psVector *xVec, @@ -1030,26 +927,13 @@ float yVal) { - // static psVector* x = NULL; - // static psVector* y = NULL; - // static psVector* yErr = NULL; - psVector* x = psVectorAlloc(3, PS_TYPE_F64); - psVector* y = psVectorAlloc(3, PS_TYPE_F64); - psVector* yErr = psVectorAlloc(3, PS_TYPE_F64); - - /* - if (x == NULL) { - x = psVectorAlloc(3, PS_TYPE_F64); - p_psMemSetPersistent(x, true); - } - if (y == NULL) { - y = psVectorAlloc(3, PS_TYPE_F64); - p_psMemSetPersistent(y, true); - } - if (yErr == NULL) { - yErr = psVectorAlloc(3, PS_TYPE_F64); - p_psMemSetPersistent(yErr, true); - } - */ - psPolynomial1D* myPoly = psPolynomial1DAlloc(2, PS_POLYNOMIAL_ORD); + PS_VECTOR_DECLARE_ALLOC_STATIC(x, 3, PS_TYPE_F64); + PS_VECTOR_DECLARE_ALLOC_STATIC(y, 3, PS_TYPE_F64); + PS_VECTOR_DECLARE_ALLOC_STATIC(yErr, 3, PS_TYPE_F64); + static psPolynomial1D* myPoly = NULL; + + if (myPoly == NULL) { + myPoly = psPolynomial1DAlloc(2, PS_POLYNOMIAL_ORD); + p_psMemSetPersistent(myPoly, true); + } float tmpFloat; @@ -1090,8 +974,4 @@ } - psFree(x); - psFree(y); - psFree(yErr); - psFree(myPoly); return(tmpFloat); } @@ -1475,5 +1355,5 @@ /****************************************************************************** -psHistogramAllocGenric(bounds): allocate a non-uniform histogram structure +psHistogramAllocGeneric(bounds): allocate a non-uniform histogram structure with the specifed bounds.