numpy.diff¶

numpy.
diff
(a, n=1, axis=1)[source]¶ Calculate the nth discrete difference along given axis.
The first difference is given by
out[n] = a[n+1]  a[n]
along the given axis, higher differences are calculated by usingdiff
recursively.Parameters: a : array_like
Input array
n : int, optional
The number of times values are differenced.
axis : int, optional
The axis along which the difference is taken, default is the last axis.
Returns: diff : ndarray
The nth differences. The shape of the output is the same as a except along axis where the dimension is smaller by n. The type of the output is the same as that of the input.
Notes
For boolean arrays, the preservation of type means that the result will contain False when consecutive elements are the same and True when they differ.
For unsigned integer arrays, the results will also be unsigned. This should not be surprising, as the result is consistent with calculating the difference directly:
>>> u8_arr = np.array([1, 0], dtype=np.uint8) >>> np.diff(u8_arr) array([255], dtype=uint8) >>> u8_arr[1,...]  u8_arr[0,...] array(255, np.uint8)
If this is not desirable, then the array should be cast to a larger integer type first:
>>> i16_arr = u8_arr.astype(np.int16) >>> np.diff(i16_arr) array([1], dtype=int16)
Examples
>>> x = np.array([1, 2, 4, 7, 0]) >>> np.diff(x) array([ 1, 2, 3, 7]) >>> np.diff(x, n=2) array([ 1, 1, 10])
>>> x = np.array([[1, 3, 6, 10], [0, 5, 6, 8]]) >>> np.diff(x) array([[2, 3, 4], [5, 1, 2]]) >>> np.diff(x, axis=0) array([[1, 2, 0, 2]])