numpy.left_shift

numpy.left_shift(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'left_shift'>

Shift the bits of an integer to the left.

Bits are shifted to the left by appending x2 0s at the right of x1. Since the internal representation of numbers is in binary format, this operation is equivalent to multiplying x1 by 2**x2.

Parameters:

x1 : array_like of integer type Input values. x2 : array_like of integer type Number of zeros to append to x1. Has to be non-negative. out : ndarray, None, or tuple of ndarray and None, optional A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs. where : array_like, optional Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone. **kwargs For other keyword-only arguments, see the ufunc docs.

Returns:

out : array of integer type Return x1 with bits shifted x2 times to the left. This is a scalar if both x1 and x2 are scalars.

See also

right_shift

Shift the bits of an integer to the right.

binary_repr

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

Examples

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

>>> np.left_shift(5, [1,2,3])
array([10, 20, 40])