scipy.ndimage.

sum_labels#

scipy.ndimage.sum_labels(input, labels=None, index=None)[source]#

Calculate the sum of the values of the array.

Parameters:

inputarray_like: Values of input inside the regions defined by labels are summed together.
labelsarray_like of ints, optional: Assign labels to the values of the array. Has to have the same shape as input.
indexarray_like, optional: A single label number or a sequence of label numbers of the objects to be measured.

Returns:

sumndarray or scalar: An array of the sums of values of input inside the regions defined by labels with the same shape as index. If ‘index’ is None or scalar, a scalar is returned.

See also

mean, median

Notes

Array API Standard Support

sum_labels has experimental support for Python Array API Standard compatible backends in addition to NumPy. Please consider testing these features by setting an environment variable SCIPY_ARRAY_API=1 and providing CuPy, PyTorch, JAX, or Dask arrays as array arguments. The following combinations of backend and device (or other capability) are supported.

Library	CPU	GPU
NumPy	✅	n/a
CuPy	n/a	✅
PyTorch	✅	⛔
JAX	⚠️ no JIT	⛔
Dask	⚠️ computes graph	n/a

See Support for the array API standard for more information.

Examples

>>> from scipy import ndimage
>>> input =  [0,1,2,3]
>>> labels = [1,1,2,2]
>>> ndimage.sum_labels(input, labels, index=[1,2])
[1.0, 5.0]
>>> ndimage.sum_labels(input, labels, index=1)
1
>>> ndimage.sum_labels(input, labels)
6