bundles / scipy latest / scipy / ndimage / _measurements / extrema
function
scipy.ndimage._measurements:extrema
Signature
def extrema ( input , labels = None , index = None ) Summary
Calculate the minimums and maximums of the values of an array at labels, along with their positions.
Parameters
input: ndarrayN-D image data to process.
labels: ndarray, optionalLabels of features in input. If not None, must be same shape as
input.index: int or sequence of ints, optionalLabels to include in output. If None (default), all values where non-zero
labelsare used.
Returns
minimums, maximums: int or ndarrayValues of minimums and maximums in each feature.
min_positions, max_positions: tuple or list of tuplesEach tuple gives the N-D coordinates of the corresponding minimum or maximum.
Notes
Array API Standard Support
extrema 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
dev-arrayapifor more information.
Examples
import numpy as np a = np.array([[1, 2, 0, 0], [5, 3, 0, 4], [0, 0, 0, 7], [9, 3, 0, 0]]) from scipy import ndimage✓
ndimage.extrema(a)
✗lbl, nlbl = ndimage.label(a)
✓ndimage.extrema(a, lbl, index=np.arange(1, nlbl+1))
✗ndimage.extrema(a, lbl)
✗See also
Aliases
-
scipy.ndimage.extrema