numpy.diff

numpy.diff(a, n=1, axis=-1)

Calculate the n-th order discrete difference along given axis.

The first order difference is given by out[n] = a[n+1] - a[n] along the given axis, higher order differences are calculated by using diff 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 n order differences. The shape of the output is the same as a except along axis where the dimension is smaller by n.

See also

gradient, ediff1d, cumsum

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]])