dpnp.trace¶

dpnp.trace(a, offset=0, axis1=0, axis2=1, dtype=None, out=None)[source]¶

Return the sum along diagonals of the array.

For full documentation refer to numpy.trace.

Parameters:

a{dpnp.ndarray, usm_ndarray}

Input array, from which the diagonals are taken.

offsetint, optional

Offset of the diagonal from the main diagonal. Can be both positive and negative.

Default: 0.

axis1, axis2int, optional

Axes to be used as the first and second axis of the 2-D sub-arrays from which the diagonals should be taken. Defaults are the first two axes of a.

Default: axis1 = 0, axis2 = 1.

dtype{None, str, dtype object}, optional

Determines the data-type of the returned array and of the accumulator where the elements are summed. If dtype has the value None and a is of integer type of precision less than the default integer precision, then the default integer precision is used. Otherwise, the precision is the same as that of a.

Default: None.

out{None, dpnp.ndarray, usm_ndarray}, optional

Array into which the output is placed. Its type is preserved and it must be of the right shape to hold the output.

Default: None.

Returns:

sum_along_diagonalsdpnp.ndarray: If a is 2-D, the sum along the diagonal is returned. If a has larger dimensions, then an array of sums along diagonals is returned.

See also

dpnp.linalg.trace: Array API compatible version.
dpnp.diag: Extract a diagonal or construct a diagonal array.
dpnp.diagonal: Return specified diagonals.
dpnp.diagflat: Create a 2-D array with the flattened input as a diagonal.

Examples

>>> import dpnp as np
>>> np.trace(np.eye(3))
array(3.)
>>> a = np.arange(8).reshape((2, 2, 2))
>>> np.trace(a)
array([6, 8])

>>> a = np.arange(24).reshape((2, 2, 2, 3))
>>> np.trace(a).shape
(2, 3)