docs: def prcntiles(x,percents):
      '''Equivalent to matlab prctile(x,p), uses linear interpolation.'''
      x=np.array(x).flatten()
      listx = np.sort(x)
      xpcts=[]
      lenlistx=len(listx)
      refs=[]
      for i in range(0,lenlistx):
          r=100*((.5+i)/lenlistx) #refs[i] is percentile of listx[i] in matrix x
          refs.append(r)
  
      rpcts=[]
      for p in percents:
          if p<refs[0]:
              rpcts.append(listx[0])
          elif p>refs[-1]:
              rpcts.append(listx[-1])
          else:
              for j in range(0,lenlistx): #lenlistx=len(refs)
                  if refs[j]<=p and refs[j+1]>=p:
                      my=listx[j+1]-listx[j]
                      mx=refs[j+1]-refs[j]
                      m=my/mx #slope of line between points
                      rpcts.append((m*(p-refs[j]))+listx[j])
                      break
      xpcts.append(rpcts)
      return np.array(xpcts).transpose()