dpnp.greater_equal

dpnp.greater_equal(x1, x2, out=None, where=True, order='K', dtype=None, subok=True, **kwargs)

Computes the greater-than or equal-to test results for each element \(x1_i\) of the input array x1 with the respective element \(x2_i\) of the input array x2.

For full documentation refer to numpy.greater_equal.

Parameters:

  • x1 ({dpnp.ndarray, usm_ndarray, scalar}) -- First input array, may have any data type.

  • x2 ({dpnp.ndarray, usm_ndarray, scalar}) -- Second input array, also may have any data type.

  • out ({None, dpnp.ndarray, usm_ndarray}, optional) --

    Output array to populate. Array must have the correct shape and the expected data type.

    Default: None.

  • order ({None, "C", "F", "A", "K"}, optional) --

    Memory layout of the newly output array, if parameter out is None.

    Default: "K".

Returns:

out -- An array containing the result of element-wise greater-than or equal-to comparison.

Return type:

dpnp.ndarray of bool dtype

Limitations

Parameters where and subok are supported with their default values. Otherwise NotImplementedError exception will be raised.

See also

dpnp.greater

Return the truth value of (x1 > x2) element-wise.

dpnp.less

Return the truth value of (x1 < x2) element-wise.

dpnp.less_equal

Return the truth value of (x1 =< x2) element-wise.

dpnp.equal

Return (x1 == x2) element-wise.

dpnp.not_equal

Return (x1 != x2) element-wise.

Notes

At least one of x1 or x2 must be an array.

If x1.shape != x2.shape, they must be broadcastable to a common shape (which becomes the shape of the output).

Examples

>>> import dpnp as np
>>> x1 = np.array([4, 2, 1])
>>> x2 = np.array([2, 2, 2])
>>> np.greater_equal(x1, x2)
array([ True,  True, False])

The >= operator can be used as a shorthand for greater_equal on dpnp.ndarray.

>>> a = np.array([4, 2, 1])
>>> b = np.array([2, 2, 2])
>>> a >= b
array([ True,  True, False])