Index: trunk/psLib/src/math/psStats.c =================================================================== --- trunk/psLib/src/math/psStats.c (revision 8245) +++ trunk/psLib/src/math/psStats.c (revision 8627) @@ -16,6 +16,6 @@ * use ->min and ->max (PS_STAT_USE_RANGE) * - * @version $Revision: 1.184 $ $Name: not supported by cvs2svn $ - * @date $Date: 2006-08-09 02:26:44 $ + * @version $Revision: 1.185 $ $Name: not supported by cvs2svn $ + * @date $Date: 2006-08-26 04:34:28 $ * * Copyright 2004 Maui High Performance Computing Center, University of Hawaii @@ -665,10 +665,10 @@ if (count == 0) { stats->sampleStdev = NAN; - psLogMsg(__func__, PS_LOG_WARN, "WARNING: vectorSampleStdev(): no valid psVector elements (%d). Setting stats->sampleStdev = NAN.\n", count); + psLogMsg(__func__, PS_LOG_WARN, "WARNING: vectorSampleStdev(): no valid psVector elements (%ld). Setting stats->sampleStdev = NAN.\n", count); return false; } if (count == 1) { stats->sampleStdev = 0.0; - psLogMsg(__func__, PS_LOG_WARN, "WARNING: vectorSampleStdev(): only one valid psVector elements (%d). Setting stats->sampleStdev = 0.0.\n", count); + psLogMsg(__func__, PS_LOG_WARN, "WARNING: vectorSampleStdev(): only one valid psVector elements (%ld). Setting stats->sampleStdev = 0.0.\n", count); return false; } @@ -713,7 +713,7 @@ // Ensure that stats->clipSigma is within the proper range. - PS_ASSERT_INT_WITHIN_RANGE(stats->clipSigma, - PS_CLIPPED_SIGMA_LB, - PS_CLIPPED_SIGMA_UB, -1); + PS_ASSERT_FLOAT_WITHIN_RANGE(stats->clipSigma, + PS_CLIPPED_SIGMA_LB, + PS_CLIPPED_SIGMA_UB, -1); // Allocate a psStats structure for calculating the mean, median, and @@ -777,5 +777,5 @@ fabsf(myVector->data.F32[j] - clippedMean) > stats->clipSigma * errors->data.F32[j]) { tmpMask->data.U8[j] = 0xff; - psTrace("psLib.math", 10, "Clipped %d: %f +/- %f\n", j, + psTrace("psLib.math", 10, "Clipped %ld: %f +/- %f\n", j, myVector->data.F32[j], errors->data.F32[j]); numClipped++; @@ -788,5 +788,5 @@ fabsf(myVector->data.F32[j] - clippedMean) > (stats->clipSigma * clippedStdev)) { tmpMask->data.U8[j] = 0xff; - psTrace("psLib.math", 10, "Clipped %d: %f\n", j, myVector->data.F32[j]); + psTrace("psLib.math", 10, "Clipped %ld: %f\n", j, myVector->data.F32[j]); numClipped++; clipped = true; @@ -896,6 +896,6 @@ PS_ASSERT_VECTOR_TYPE(yVec, PS_TYPE_F32, NAN); // PS_ASSERT_VECTORS_SIZE_EQUAL(xVec, yVec, NAN); - PS_ASSERT_INT_WITHIN_RANGE(binNum, 0, (xVec->n - 1), NAN); - PS_ASSERT_INT_WITHIN_RANGE(binNum, 0, (yVec->n - 1), NAN); + PS_ASSERT_INT_WITHIN_RANGE(binNum, 0, (int)(xVec->n - 1), NAN); + PS_ASSERT_INT_WITHIN_RANGE(binNum, 0, (int)(yVec->n - 1), NAN); psVector *x = psVectorAlloc(3, PS_TYPE_F64); @@ -1008,8 +1008,8 @@ psTrace("psLib.math", 4, "---- %s() begin ----\n", __func__); PS_ASSERT_VECTOR_NON_NULL(params, NAN); - PS_ASSERT_VECTOR_SIZE(params, 2, NAN); + PS_ASSERT_VECTOR_SIZE(params, (long)2, NAN); PS_ASSERT_VECTOR_TYPE(params, PS_TYPE_F32, NAN); PS_ASSERT_VECTOR_NON_NULL(coords, NAN); - PS_ASSERT_VECTOR_SIZE(coords, 1, NAN); + PS_ASSERT_VECTOR_SIZE(coords, (long)1, NAN); PS_ASSERT_VECTOR_TYPE(coords, PS_TYPE_F32, NAN); @@ -1020,5 +1020,5 @@ psF32 gauss = psGaussian(x, mean, stdev, false); if (deriv) { - PS_ASSERT_VECTOR_SIZE(deriv, 2, NAN); + PS_ASSERT_VECTOR_SIZE(deriv, (long)2, NAN); PS_ASSERT_VECTOR_TYPE(deriv, PS_TYPE_F32, NAN); psF32 tmp = (x - mean) * gauss; @@ -1136,5 +1136,5 @@ // we get here, we know that binSize != 0.0. long numBins = (max - min) / binSize; // Number of bins - psTrace("psLib.math", 6, "Numbins is %d\n", numBins); + psTrace("psLib.math", 6, "Numbins is %ld\n", numBins); psTrace("psLib.math", 6, "Creating a robust histogram from data range (%.2f - %.2f)\n", min, max); // Generate the histogram @@ -1159,5 +1159,5 @@ // ADD step 2: Find the bin which contains the 50% data point. totalDataPoints = cumulative->nums->data.F32[numBins - 1]; - psTrace("psLib.math", 6, "Total data points is %d\n", totalDataPoints); + psTrace("psLib.math", 6, "Total data points is %ld\n", totalDataPoints); long binMedian; if (totalDataPoints/2.0 < cumulative->nums->data.F32[0]) { @@ -1170,5 +1170,5 @@ if (binMedian < 0) { psError(PS_ERR_UNKNOWN, false, - "Failed to calculate the 50 precent data point (%d).\n", binMedian); + "Failed to calculate the 50 precent data point (%ld).\n", binMedian); psFree(statsMinMax); psFree(histogram); @@ -1179,5 +1179,5 @@ } } - psTrace("psLib.math", 6, "The median bin is %d (%.2f to %.2f)\n", binMedian, + psTrace("psLib.math", 6, "The median bin is %ld (%.2f to %.2f)\n", binMedian, cumulative->bounds->data.F32[binMedian], cumulative->bounds->data.F32[binMedian+1]); @@ -1217,5 +1217,5 @@ } } - psTrace("psLib.math", 6, "The 15.8655%% and 84.1345%% data point bins are (%d, %d).\n", + psTrace("psLib.math", 6, "The 15.8655%% and 84.1345%% data point bins are (%ld, %ld).\n", binLo, binHi); psTrace("psLib.math", 6, "binLo midpoint is %f\n", PS_BIN_MIDPOINT(cumulative, binLo)); @@ -1248,7 +1248,7 @@ #else // This code basically interpolates to find the positions exactly. - psTrace("psLib.math", 6, "binLo is %d. Nums at that bin and the next are (%.2f, %.2f)\n", + psTrace("psLib.math", 6, "binLo is %ld. Nums at that bin and the next are (%.2f, %.2f)\n", binLo, cumulative->nums->data.F32[binLo], cumulative->nums->data.F32[binLo+1]); - psTrace("psLib.math", 6, "binHi is %d. Nums at that bin and the next are (%.2f, %.2f)\n", + psTrace("psLib.math", 6, "binHi is %ld. Nums at that bin and the next are (%.2f, %.2f)\n", binHi, cumulative->nums->data.F32[binHi], cumulative->nums->data.F32[binHi+1]); @@ -1304,5 +1304,5 @@ psTrace("psLib.math", 6, "Masking data more than 25 bins from the median\n"); psTrace("psLib.math", 6, - "The median is at bin number %d. We mask bins outside the bin range (%d:%d)\n", + "The median is at bin number %ld. We mask bins outside the bin range (%ld:%ld)\n", binMedian, maskLo, maskHi); psTrace("psLib.math", 6, "Masking data outside (%f %f)\n", medianLo, medianHi); @@ -1310,5 +1310,5 @@ if ((myVector->data.F32[i] < medianLo) || (myVector->data.F32[i] > medianHi)) { mask->data.U8[i] = 0xff; - psTrace("psLib.math", 6, "Masking element %d is %f\n", i, myVector->data.F32[i]); + psTrace("psLib.math", 6, "Masking element %ld is %f\n", i, myVector->data.F32[i]); } } @@ -1350,5 +1350,5 @@ return false; } - psTrace("psLib.math", 6, "The 25-percent and 75-precent data point bins are (%d, %d).\n", binLo25, binHi25); + psTrace("psLib.math", 6, "The 25-percent and 75-precent data point bins are (%ld, %ld).\n", binLo25, binHi25); // ADD step 8: Interpolate to find these two positions exactly: these are the upper and lower quartile @@ -1381,5 +1381,5 @@ } stats->robustN50 = N50; - psTrace("psLib.math", 6, "The robustN50 is %d.\n", N50); + psTrace("psLib.math", 6, "The robustN50 is %ld.\n", N50); @@ -1413,5 +1413,5 @@ psTrace("psLib.math", 6, "The new min/max values are (%f, %f).\n", min, max); psTrace("psLib.math", 6, "The new bin size is %f.\n", newBinSize); - psTrace("psLib.math", 6, "The numBins is %d\n", numBins); + psTrace("psLib.math", 6, "The numBins is %ld\n", numBins); psHistogram *histogram = psHistogramAlloc(min, max, numBins); // A new histogram (without outliers) @@ -1460,5 +1460,5 @@ } } - psTrace("psLib.math", 6, "The peak bin is %d, with %f data.n", binNum, binMaxNums); + psTrace("psLib.math", 6, "The peak bin is %ld, with %f data.n", binNum, binMaxNums); // Fit a Gaussian to the bins in the range 20 sigma of the robust histogram median. @@ -1696,5 +1696,5 @@ PS_ASSERT_VECTOR_NON_NULL(bounds, NULL); PS_ASSERT_VECTOR_TYPE(bounds, PS_TYPE_F32, NULL); - PS_ASSERT_INT_LARGER_THAN_OR_EQUAL(bounds->n, 2, NULL); + PS_ASSERT_LONG_LARGER_THAN_OR_EQUAL(bounds->n, (long)2, NULL); // Allocate memory for the new histogram structure. @@ -1761,5 +1761,5 @@ PS_ASSERT_PTR_NON_NULL(out->bounds, false); PS_ASSERT_PTR_NON_NULL(out->nums, false); - PS_ASSERT_INT_WITHIN_RANGE(binNum, 0, ((out->nums->n)-1), false); + PS_ASSERT_LONG_WITHIN_RANGE(binNum, (long)0, (long)((out->nums->n)-1), false); PS_ASSERT_FLOAT_LARGER_THAN_OR_EQUAL(error, 0.0, false); PS_ASSERT_FLOAT_WITHIN_RANGE(data, out->bounds->data.F32[0],