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 nonnegative. If x1.shape != x2.shape , they must be broadcastable to a common shape (which becomes the shape of the output). 
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 freshlyallocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs. 
where : array_like, optional 
This condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized out array is created via the default out=None , locations within it where the condition is False will remain uninitialized.  **kwargs

For other keywordonly 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])