dpnp.bitwise_left_shift

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

Shifts the bits of each element x1_i of the input array x1 to the left by appending x2_i (i.e., the respective element in the input array x2) zeros to the right of x1_i.

Note that dpnp.bitwise_left_shift is an alias of dpnp.left_shift.

For full documentation refer to numpy.left_shift.

Parameters:

  • x1 ({dpnp.ndarray, usm_ndarray, scalar}) -- First input array, expected to have integer data type. Both inputs x1 and x2 can not be scalars at the same time.

  • x2 ({dpnp.ndarray, usm_ndarray, scalar}) -- Second input array, also expected to have integer data type. Each element must be greater than or equal to 0. Both inputs x1 and x2 can not be scalars at the same time. If x1.shape != x2.shape, they must be broadcastable to a common shape (which becomes the shape of the output).

  • 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 element-wise results. The data type of the returned array is determined by the Type Promotion Rules.

Return type:

dpnp.ndarray

Limitations

Parameters where and subok are supported with their default values. Keyword argument kwargs is currently unsupported. Otherwise NotImplementedError exception will be raised.

See also

dpnp.right_shift

Shift the bits of an integer to the right.

dpnp.binary_repr

Return the binary representation of the input number as a string.

Examples

>>> import dpnp as np
>>> x1 = np.array([5])
>>> x2 = np.array([1, 2, 3])
>>> np.left_shift(x1, x2)
array([10, 20, 40])

The << operator can be used as a shorthand for left_shift on dpnp.ndarray.

>>> x1 << x2
array([10, 20, 40])

>>> np.binary_repr(5)
'101'
>>> np.left_shift(np.array(5), 2)
array(20)
>>> np.binary_repr(20)
'10100'