nlcpy.log = <ufunc 'nlcpy_log'>

Computes the element-wise natural logarithm of x.


Input an array or a scalar.

outndarray or 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 freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.

wherearray_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.


For other keyword-only arguments, see the section Optional Keyword Arguments.


A ndarray, containing the natural logarithm of x. If x is a scalar, this function returns the result as a 0-dimension ndarray.



Computes the element-wise base-10 logarithm of x.


Computes the element-wise base-2 logarithm of x.


Computes the element-wise natural logarithm of 1 + x.


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

  • For real-valued input data types, log() 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, log() is a complex analytical function that has a branch cut [-inf, 0] and is continuous from above on it. log() handles the floating-point negative zero as an infinitesimal negative number, conforming to the C99 standard.


>>> import nlcpy as vp
>>> vp.log([1, vp.e, vp.e**2, vp.e**3]) 
array([0., 1., 2., 3.])