code: def signalMinimum2(img, bins=None):
      '''
      minimum position between signal and background peak
      '''
      f = FitHistogramPeaks(img, bins=bins)
      i = signalPeakIndex(f.fitParams)
      spos = f.fitParams[i][1]
  #     spos = getSignalPeak(f.fitParams)[1]
  #     bpos = getBackgroundPeak(f.fitParams)[1]
      bpos = f.fitParams[i - 1][1]
      ind = np.logical_and(f.xvals > bpos, f.xvals < spos)
      try:
          i = np.argmin(f.yvals[ind])
          return f.xvals[ind][i]
      except ValueError as e:
          if bins is None:
              return signalMinimum2(img, bins=400)
          else:
              raise f signalMinimum2(img, bins=None):
      '''
      minimum position between signal and background peak
      '''
      f = FitHistogramPeaks(img, bins=bins)
      i = signalPeakIndex(f.fitParams)
      spos = f.fitParams[i][1]
  #     spos = getSignalPeak(f.fitParams)[1]
  #     bpos = getBackgroundPeak(f.fitParams)[1]
      bpos = f.fitParams[i - 1][1]
      ind = np.logical_and(f.xvals > bpos, f.xvals < spos)
      try:
          i = np.argmin(f.yvals[ind])
          return f.xvals[ind][i]
      except ValueError as e:
          if bins is None:
              return signalMinimum2(img, bins=400)
          else:
              raise e
docs: minimum position between signal and background peak