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Showing content from http://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.log1p.html below:

numpy.log1p — NumPy v1.11 Manual

numpy.log1p¶
numpy.log1p(x[, out]) = <ufunc 'log1p'>¶

Return the natural logarithm of one plus the input array, element-wise.

Calculates log(1 + x).

Parameters:

x : array_like

Input values.

Returns:

y : ndarray

Natural logarithm of 1 + x, element-wise.

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

Examples

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

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