code: def local_minima(vector,min_distance = 4, brd_mode = "wrap"):
      fits = gaussian_filter(numpy.asarray(vector,dtype=numpy.float32),1., mode=brd_mode)
      for ii in range(len(fits)):
          if fits[ii] == fits[ii-1]:
              fits[ii-1] = numpy.pi/2.0
      minfits = minimum_filter(fits, size=min_distance, mode=brd_mode)
      minima_mask = fits == minfits
      minima = numpy.transpose(minima_mask.nonzero())
      return numpy.asarray(minima)