scipy.ndimage.
extrema#
- scipy.ndimage.extrema(input, labels=None, index=None)[source]#
- Calculate the minimums and maximums of the values of an array at labels, along with their positions. - Parameters:
- inputndarray
- N-D image data to process. 
- labelsndarray, optional
- Labels of features in input. If not None, must be same shape as input. 
- indexint or sequence of ints, optional
- Labels to include in output. If None (default), all values where non-zero labels are used. 
 
- Returns:
- minimums, maximumsint or ndarray
- Values of minimums and maximums in each feature. 
- min_positions, max_positionstuple or list of tuples
- Each tuple gives the N-D coordinates of the corresponding minimum or maximum. 
 
 - See also - 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) (0, 9, (0, 2), (3, 0)) - Features to process can be specified using labels and index: - >>> lbl, nlbl = ndimage.label(a) >>> ndimage.extrema(a, lbl, index=np.arange(1, nlbl+1)) (array([1, 4, 3]), array([5, 7, 9]), [(0, 0), (1, 3), (3, 1)], [(1, 0), (2, 3), (3, 0)]) - If no index is given, non-zero labels are processed: - >>> ndimage.extrema(a, lbl) (1, 9, (0, 0), (3, 0))