# jax.numpy.trace#

jax.numpy.trace(a, offset=0, axis1=0, axis2=1, dtype=None, out=None)[source]#

Return the sum along diagonals of the array.

LAX-backend implementation of `numpy.trace()`.

Original docstring below.

If a is 2-D, the sum along its diagonal with the given offset is returned, i.e., the sum of elements `a[i,i+offset]` for all i.

If a has more than two dimensions, then the axes specified by axis1 and axis2 are used to determine the 2-D sub-arrays whose traces are returned. The shape of the resulting array is the same as that of a with axis1 and axis2 removed.

Parameters:
• a (array_like) â€“ Input array, from which the diagonals are taken.

• offset (int, optional) â€“ Offset of the diagonal from the main diagonal. Can be both positive and negative. Defaults to 0.

• axis1 (int, optional) â€“ 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.

• axis2 (int, optional) â€“ 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.

• dtype (dtype, optional) â€“ 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.

• out (None)

Returns:

sum_along_diagonals â€“ 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.

Return type:

ndarray