# numpy.log1p¶

numpy.log1p(x[, out])

log(1 + x) in base e, elementwise.

Parameters: x : array_like Input values. y : ndarray Natural logarithm of 1 + x, elementwise.

Notes

For real-valued input, log1p is accurate also for x so small that 1 + x == 1 in floating-point accuracy.

Logarithm is a multivalued function: for each x there is an infinite number of z such that exp(z) = 1 + x. The convention is to return the z whose imaginary part lies in [-pi, pi].

For real-valued input data types, log1p 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, log1p is a complex analytical function that has a branch cut [-inf, -1] and is continuous from above on it. log1p handles the floating-point negative zero as an infinitesimal negative number, conforming to the C99 standard.

References

 [48] M. Abramowitz and I.A. Stegun, “Handbook of Mathematical Functions”, 10th printing, 1964, pp. 67. http://www.math.sfu.ca/~cbm/aands/
 [49] Wikipedia, “Logarithm”. http://en.wikipedia.org/wiki/Logarithm

Examples

```>>> np.log1p(1e-99)
1e-99
>>> np.log(1 + 1e-99)
0.0
```

numpy.log2

numpy.i0