public static HistogramHolder createSimpleHistogram(int binWidth, List<Integer> theValues) { if (theValues == null || theValues.isEmpty()) { throw new IllegalArgumentException( "values and valueErrors cannot be null and must be the same length"); } float[] values = new float[theValues.size()]; for (int i = 0; i < theValues.size(); ++i) { int v = theValues.get(i).intValue(); values[i] = v; } float[] valueErrors = Errors.populateYErrorsBySqrt(values); float[] minMax = MiscMath.calculateOuterRoundedMinAndMax(values); int nBins = (int) Math.ceil(((minMax[1] - minMax[0])) / binWidth); if (nBins < 0) { nBins *= -1; } float[] xHist = new float[nBins]; int[] yHist = new int[nBins]; Histogram.createHistogram(values, nBins, minMax[0], minMax[1], xHist, yHist, binWidth); float[] yHistFloat = new float[yHist.length]; for (int i = 0; i < yHist.length; i++) { yHistFloat[i] = (float) yHist[i]; } float[] yErrors = new float[xHist.length]; float[] xErrors = new float[xHist.length]; calulateHistogramBinErrors(xHist, yHist, values, valueErrors, xErrors, yErrors); HistogramHolder histogram = new HistogramHolder(); histogram.setXHist(xHist); histogram.setYHist(yHist); histogram.setYHistFloat(yHistFloat); histogram.setYErrors(yErrors); histogram.setXErrors(xErrors); return histogram; }
public static HistogramHolder createSimpleHistogram(GreyscaleImage img) { float[] values = new float[img.getNPixels()]; int count = 0; for (int i = 0; i < img.getWidth(); ++i) { for (int j = 0; j < img.getHeight(); ++j) { int v = img.getValue(i, j); values[count] = v; count++; } } float[] errors = Errors.populateYErrorsBySqrt(values); HistogramHolder hist = createSimpleHistogram(values, errors); return hist; }
public static HistogramHolder createSimpleHistogram(List<Integer> values) { if (values == null) { throw new IllegalArgumentException( "values and valueErrors cannot be null and must be the same length"); } if (values.isEmpty()) { return null; } float[] v = new float[values.size()]; for (int i = 0; i < values.size(); ++i) { v[i] = values.get(i).intValue(); } float[] ve = Errors.populateYErrorsBySqrt(v); int nBins = (int) (2 * Math.pow(v.length, 0.3333)); if (v.length == 1) { nBins = 1; } return createSimpleHistogram(nBins, v, ve); }
public static HistogramHolder createHistogramAndRemovePreAndProceedingZeros(GreyscaleImage img) { float[] values = new float[img.getNPixels()]; int count = 0; for (int i = 0; i < img.getWidth(); ++i) { for (int j = 0; j < img.getHeight(); ++j) { int v = img.getValue(i, j); values[count] = v; count++; } } float[] errors = Errors.populateYErrorsBySqrt(values); HistogramHolder hist = createSimpleHistogram(values, errors); if (hist.getXHist().length < 2) { return hist; } int n = hist.getXHist().length; // int yMax = MiscMath.findMax(hist.getYHist()); // int yMin = MiscMath.findMin(hist.getYHist()); int fIdx = 0; for (int i = 0; i < n; ++i) { fIdx = i; int y = hist.getYHist()[i]; if (y > 0) { break; } } int lIdx = (n - 1); for (int i = (n - 1); i > -1; --i) { lIdx = i; int y = hist.getYHist()[i]; if (y > 0) { break; } } if ((fIdx <= 1) && (lIdx >= (n - 2))) { return hist; } /* if there are a large number of bins, re-do the x idx limits using a lower limit larger than spurious counts... this may need revision */ // TODO: consider comparing (lIdx - fIdx) > 30 if (hist.getXHist().length > 30) { int tmp0 = fIdx; int tmp1 = lIdx; int xMaxYIdx = MiscMath.findYMaxIndex(hist.getYHist()); float limit = (int) Math.ceil(Math.sqrt(hist.getYHist()[xMaxYIdx])); fIdx = 0; for (int i = 0; i < n; ++i) { fIdx = i; int y = hist.getYHist()[i]; if (y > limit) { break; } } lIdx = (n - 1); for (int i = (n - 1); i > -1; --i) { lIdx = i; int y = hist.getYHist()[i]; if (y > limit) { break; } } int maxDiffIdx = Math.max(xMaxYIdx - fIdx, lIdx - xMaxYIdx); fIdx = xMaxYIdx - 3 * maxDiffIdx; lIdx = xMaxYIdx + 3 * maxDiffIdx; if (fIdx < 0) { fIdx = tmp0; } if (lIdx > (n - 1)) { lIdx = tmp1; } } // re-do for smaller range float xBin = hist.getXHist()[1] - hist.getXHist()[0]; float xf; if (fIdx == 0) { xf = hist.getXHist()[0] - (xBin / 2.f); } else { xf = hist.getXHist()[fIdx - 1] - (xBin / 2.f); } float xl; if (lIdx == (n - 1)) { xl = hist.getXHist()[lIdx] + (xBin / 2.f); } else { xl = hist.getXHist()[lIdx + 1] + (xBin / 2.f); } int n2 = 0; float[] values2 = new float[values.length]; float[] errors2 = new float[values2.length]; for (int i = 0; i < values2.length; ++i) { float v = values[i]; if ((v >= xf) && (v <= xl)) { values2[n2] = v; errors2[n2] = errors[n2]; n2++; } } values2 = Arrays.copyOf(values2, n2); errors2 = Arrays.copyOf(errors2, n2); hist = createSimpleHistogram(values2, errors2); return hist; }