numpy.log2(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'log2'>
Base-2 logarithm of x
.
Parameters: |
x : array_like Input values. 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 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: |
y : ndarray Base-2 logarithm of |
New in version 1.3.0.
Logarithm is a multivalued function: for each x
there is an infinite number of z
such that 2**z = x
. The convention is to return the z
whose imaginary part lies in [-pi, pi]
.
For real-valued input data types, log2
always returns real output. For each value that cannot be expressed as a real number or infinity, it yields nan
and sets the invalid
floating point error flag.
For complex-valued input, log2
is a complex analytical function that has a branch cut [-inf, 0]
and is continuous from above on it. log2
handles the floating-point negative zero as an infinitesimal negative number, conforming to the C99 standard.
>>> x = np.array([0, 1, 2, 2**4]) >>> np.log2(x) array([-Inf, 0., 1., 4.])
>>> xi = np.array([0+1.j, 1, 2+0.j, 4.j]) >>> np.log2(xi) array([ 0.+2.26618007j, 0.+0.j , 1.+0.j , 2.+2.26618007j])
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Licensed under the NumPy License.
https://docs.scipy.org/doc/numpy-1.14.2/reference/generated/numpy.log2.html