e70152e44cc66cc599ff6b699eb8adc07f3e656a kent Sat May 24 21:09:34 2014 -0700 Adding Copyright NNNN Regents of the University of California to all files I believe with reasonable certainty were developed under UCSC employ or as part of Genome Browser copyright assignment. diff --git src/utils/textHistogram/textHistogram.c src/utils/textHistogram/textHistogram.c index 9560a40..a1af305 100644 --- src/utils/textHistogram/textHistogram.c +++ src/utils/textHistogram/textHistogram.c @@ -1,470 +1,473 @@ /* textHistogram - Make a histogram in ascii. */ + +/* Copyright (C) 2011 The Regents of the University of California + * See README in this or parent directory for licensing information. */ #include "common.h" #include "linefile.h" #include "hash.h" #include "options.h" /* command line option specifications */ static struct optionSpec optionSpecs[] = { {"binSize", OPTION_STRING}, {"maxBinCount", OPTION_INT}, {"minVal", OPTION_STRING}, {"log", OPTION_BOOLEAN}, {"noStar", OPTION_BOOLEAN}, {"col", OPTION_INT}, {"aveCol", OPTION_INT}, {"real", OPTION_BOOLEAN}, {"autoscale", OPTION_INT}, {"autoScale", OPTION_INT}, {"skip", OPTION_INT}, {"probValues", OPTION_BOOLEAN}, {"freq", OPTION_BOOLEAN}, {NULL, 0} }; int binSize = 1; double binSizeR = 1.0; int maxBinCount = 25; int skip = 0; char * minValStr = (char *) NULL; int minVal = 0; double minValR = 0.0; boolean doLog = FALSE; boolean noStar = FALSE; boolean probValues = FALSE; int col = 0; int aveCol = -1; boolean real = FALSE; int autoscale = 0; boolean freq = FALSE; void usage() /* Explain usage and exit. */ { errAbort( "textHistogram - Make a histogram in ascii\n" "usage:\n" " textHistogram [options] inFile\n" "Where inFile contains one number per line.\n" " options:\n" " -binSize=N - Size of bins, default 1\n" " -maxBinCount=N - Maximum # of bins, default 25\n" " -minVal=N - Minimum value to put in histogram, default 0\n" " -log - Do log transformation before plotting\n" " -noStar - Don't draw asterisks\n" " -col=N - Which column to use. Default 1\n" " -aveCol=N - A second column to average over. The averages\n" " will be output in place of counts of primary column.\n" " -real - Data input are real values (default is integer)\n" " -autoScale=N - autoscale to N # of bins\n" " -probValues - show prob-Values (density and cum.distr.) (sets -noStar too)\n" " -freq - show frequences instead of counts\n" " -skip=N - skip N lines before starting, default 0\n" ); } /* Read through the file and determine min,max and thus range * set bin size and minimum value */ static void autoScale(char *inFile) { int wordCount; char *row[256]; unsigned long dataCount = 0; double min = HUGE; double max = - HUGE; double range = 0.0; struct lineFile *lf = lineFileOpen(inFile, TRUE); while ((wordCount = lineFileChop(lf, row))) { double d; if ((wordCount <= col) || (wordCount <= aveCol)) errAbort("Not enough words line %d of %s", lf->lineIx, lf->fileName); d = lineFileNeedDouble(lf, row, col); if ( d < min ) min = d; if ( d > max ) max = d; ++dataCount; } lineFileClose(&lf); range = max - min; if (range < 0.0) errAbort("range of data invalid: %g = [%g:%g]", range, min, max); maxBinCount = autoscale; if (real) { minValR = min; /* need to make binSizeR slightly larger to get the last data point * in the last bin. This is a floating point round off situation. */ binSizeR = (range + (range/1000000.0)) / maxBinCount; } else { minVal = (int) floor(min); binSize = (int)ceil(range / maxBinCount); if (binSize < 1) binSize = 1; verbose(1, "#\tautoscale data range: (%d - %d)/%d = %d\n", (int) ceil(max), minVal, maxBinCount, binSize); } verbose(2, "#\tautoscale number of data values: %lu\n", dataCount); verbose(2, "#\tautoscale maxBinCount: %d\n", maxBinCount); if (real) { verbose(2, "#\tautoscale data range: %g = [%g:%g]\n", range, minValR, max); verbose(2, "#\tautoscale minVal: %g\n", minValR); verbose(2, "#\tautoscale binSize: %g\n", binSizeR); } else { verbose(2, "#\tautoscale data range: %g = [%d:%d]\n", range, minVal, (int) ceil(max)); verbose(2, "#\tautoscale minVal: %d\n", minVal); verbose(2, "#\tautoscale binSize: %d\n", binSize); } } /* autoScale() */ static void textHistogram(char *inFile) /* textHistogram - Make a histogram in ascii. */ { double *hist = NULL; double *total = NULL; char *row[256]; int wordCount; struct lineFile *lf = lineFileOpen(inFile, TRUE); int i,j; int minData = maxBinCount, maxData = 0; int totalTooBig = 0; double maxCount = 0; double maxCt; double maxVal = 0; int truncation = 0; int begin, end; unsigned long long totalCounts = 0; double cpd; /* Allocate histogram and optionally space for * second column totals. */ AllocArray(hist, maxBinCount); if (aveCol >= 0) AllocArray(total, maxBinCount); while (skip-- > 0) wordCount = lineFileChop(lf, row); /* Go through each line of input file accumulating * data. */ while ((wordCount = lineFileChop(lf, row))) { int x; /* will become the index into hist[] */ if (wordCount <= col || wordCount <= aveCol) errAbort("Not enough words line %d of %s", lf->lineIx, lf->fileName); x = -1; if (real) /* for real data, work in real space to find index */ { double d; d = lineFileNeedDouble(lf, row, col); if (d > maxVal) maxVal = d; if (d >= minValR) { d -= minValR; x = (int) floor(d / binSizeR); } } else { x = lineFileNeedNum(lf, row, col); if (x > maxVal) maxVal = x; if (x >= minVal) { x -= minVal; x /= binSize; } } /* index x is calculated, accumulate it when in range */ if (x >= 0 && x < maxBinCount) { hist[x] += 1; if (aveCol >= 0) { double a; a = lineFileNeedDouble(lf, row, aveCol); total[x] += a; } } else { verbose(2, "truncating index %d\n", x); truncation = (x > truncation) ? x : truncation; totalTooBig += 1; } } lineFileClose(&lf); if (truncation > 0) { if (real) fprintf(stderr,"large values truncated: need %d bins or larger binSize than %g\n",truncation, binSizeR); else fprintf(stderr,"large values truncated: need %d bins or larger binSize than %d\n",truncation, binSize); printf("Maximum value %f\n", maxVal); } /* Figure out range that has data, maximum data * value and optionally compute averages. */ if (aveCol >= 0) { double ave, maxAve = -BIGNUM; for (i=0; i<maxBinCount; ++i) { int count = hist[i]; if (count != 0) { ave = total[i]/count; if (maxAve < ave) maxAve = ave; if (minData > i) minData = i; if (maxData < i) maxData = i; } } maxCt = maxAve; } else { for (i=0; i<maxBinCount; ++i) { int count = hist[i]; if (count != 0) { if (maxCount < count) maxCount = count; if (minData > i) minData = i; if (maxData < i) maxData = i; } } maxCt = maxCount; } begin = minData; end = maxData + 1; if (verboseLevel()>1) { begin = 0; end = maxBinCount; } if (probValues || freq) { totalCounts = 0; for (i=begin; i<end; ++i) totalCounts += hist[i]; verbose(2,"#\ttotal data values: %llu\n", totalCounts); if (totalCounts < 1) errAbort("ERROR: No bins with any data ?\n"); } if (freq) maxCt = maxCt/(double)totalCounts; if (doLog) maxCt = log(maxCt); if (verboseLevel()>1) { if (noStar) { if (probValues) printf("# bin\tValue\t\tprob-Value\t\tlog2(prob-Value)\tCPD\t1-CPD\n"); else printf("# bin Value ascii graph\n"); } else printf("# bin Value ascii graph\n"); } cpd = 0.0; /* cumulative probability distribution */ /* Output results. */ for (i=begin; i<=end; ++i) { double ct; double binStartR = 0.0; int binStart = 0; long count; if (i != end) count = hist[i]; else { if (totalTooBig == 0) break; count = totalTooBig; } if (real) binStartR = i*binSizeR + minValR; else binStart = i*binSize + minVal; if (aveCol >= 0) { if (count > 0) ct = total[i]/count; else ct = 0; } else if (freq) { ct = count/(double)totalCounts; } else { ct = count; } if (doLog) ct = log(ct); if (noStar) { if (i == end) printf("<minVal or >="); if (verboseLevel()>1) printf("%02d\t", i); if (real) { if (probValues) { if (verboseLevel()>1) printf("%g:%g", binStartR, binStartR+binSizeR); else printf("%3d %g:%g", i, binStartR, binStartR+binSizeR); } else printf("%3d %g:%g\t%f", i, binStartR, binStartR+binSizeR, ct); } else { printf("%d\t%f", binStart, ct); } if (probValues) { if (ct > 0) { cpd += (double)ct/(double)totalCounts; printf("\t%f\t%f\t%f\t%f\n", (double)ct/(double)totalCounts, log((double)ct/(double)totalCounts)/log(2.0), cpd, 1.0-cpd); } else printf("\t0.0 \tN/A \t%f\t%f\n", cpd, 1.0-cpd); } else printf("\n"); } else { int astCount = round(ct * 60.0 / maxCt); if (i == end) printf("<minVal or >="); if (verboseLevel()>1) printf("%2d ", i); if (real) printf("%f ", binStartR); else printf("%3d ", binStart); for (j=0; j<astCount; ++j) putchar('*'); if ((aveCol >= 0) || freq) printf(" %f\n", ct); else printf(" %ld\n", count); } } } /* textHistogram() */ int main(int argc, char *argv[]) /* Process command line. */ { char * binSizeStr = (char *) NULL; optionInit(&argc, argv, optionSpecs); if (argc < 2) usage(); binSizeStr = optionVal("binSize", "1"); maxBinCount = optionInt("maxBinCount", 25); minValStr = optionVal("minVal", "0"); doLog = optionExists("log"); noStar = optionExists("noStar"); probValues = optionExists("probValues"); col = optionInt("col", 1) - 1; aveCol = optionInt("aveCol", 0) - 1; real = optionExists("real"); autoscale = optionInt("autoscale", 0); if (autoscale == 0) autoscale = optionInt("autoScale", 0); freq = optionExists("freq") && !probValues; /* freq and probValues don't currently work right together */ skip = optionInt("skip", 0); /* probValues turns on noStar too */ if (probValues) noStar = TRUE; if (real) { char *valEnd; char *val = binSizeStr; binSizeR = strtod(val, &valEnd); if ((*val == '\0') || (*valEnd != '\0')) errAbort("Not a valid float for -binSize=%s\n", binSizeStr); if (binSizeR <= 0.0) errAbort("invalid binSize, must be greater than zero: %g\n", binSizeR); val = minValStr; minValR = strtod(val, &valEnd); if ((*val == '\0') || (*valEnd != '\0')) errAbort("Not a valid float for -minVal=%s\n", binSizeStr); } else { binSize = atoi(binSizeStr); if (binSize < 1) errAbort("invalid binSize, must be >= one: %d\n", binSize); minVal = atoi(minValStr); } verbose(2,"#\tbinSize: "); if (real) verbose(2, "%f\n", binSizeR); else verbose(2, "%d\n", binSize); verbose(2,"#\tmaxBinCount: %d\n", maxBinCount); verbose(2,"#\tminVal: "); if (real) verbose(2, "%f\n", minValR); else verbose(2, "%d\n", minVal); verbose(2,"#\tlog function: %s\n", doLog ? "ON" : "OFF" ); verbose(2,"#\tdraw asterisks: %s\n", noStar ? "NO" : "YES" ); verbose(2,"#\thistogram on data input column: %d\n", col+1); if (aveCol >= 0) verbose(2, "#\taveCol: %d\n", aveCol); else verbose(2, "#\taveCol: not selected\n"); verbose(2,"#\treal valued data: %s\n", real ? "YES" : "NO" ); if (autoscale > 0) verbose(2, "#\tautoscaling to %d bins\n", autoscale); else verbose(2, "#\tautoscale: not selected\n"); verbose(2, "#\tshow prob-Values: %s\n", probValues ? "YES" : "NO" ); /* to autoscale stdin we would need to keep all the data read in * during the min,max scan and reuse that data for the histogram * calculation. Not implemented yet. */ if (autoscale > 0) { if (startsWith("stdin", argv[1])) { errAbort("Sorry, can not autoscale stdin at this time. Outstanding feature request."); } autoScale(argv[1]); } textHistogram(argv[1]); return 0; }