numpy.log10

numpy.log1p

# numpy.log2¶

`numpy.``log2`(x[, out]) = <ufunc 'log2'>

Base-2 logarithm of x.

Parameters: x : array_like Input values. y : ndarray Base-2 logarithm of x.

`log`, `log10`, `log1p`, `emath.log2`

Notes

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.

Examples

```>>> 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])
```