numpy - Python - Apply a function over a labeled multidimensional array -

i have numpy array labelled using scipy connected component labelling.

import numpy scipy import ndimage  = numpy.zeros((8,8), dtype=numpy.int) a[1,1] = a[1,2] = a[2,1] = a[2,2] = a[3,1] = a[3,2] = 1 a[5,5] = a[5,6] = a[6,5] = a[6,6] = a[7,5] = a[7,6] = 1  lbl, numpatches = ndimage.label(a) 

i want apply custom function (calculation of specific value) on labels within labelled array. similar instance ndimage algebra functions:

ndimage.sum(a,lbl,range(1,numpatches+1)) 

( in case returns me number of values each label [6,6]. )

is there way this?

you can pass arbitrary function ndimage.labeled_comprehension, equivalent

[func(a[lbl == i]) in index] 

here labeled_comprehension-equivalent of ndimage.sum(a,lbl,range(1,numpatches+1)):

import numpy np scipy import ndimage  = np.zeros((8,8), dtype=np.int) a[1,1] = a[1,2] = a[2,1] = a[2,2] = a[3,1] = a[3,2] = 1 a[5,5] = a[5,6] = a[6,5] = a[6,6] = a[7,5] = a[7,6] = 1  lbl, numpatches = ndimage.label(a)  def func(x):     return x.sum()  print(ndimage.labeled_comprehension(a, lbl, index=range(1, numpatches+1),                                      func=func, out_dtype='float', default=none)) # [6 6]