numpy.log
-
numpy.log(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'log'>
-
Natural logarithm, element-wise.
The natural logarithm
log
is the inverse of the exponential function, so thatlog(exp(x)) = x
. The natural logarithm is logarithm in basee
.- Parameters
-
-
xarray_like
-
Input value.
-
outndarray, 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 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, theout
array will retain its original value. Note that if an uninitializedout
array is created via the defaultout=None
, locations within it where the condition is False will remain uninitialized. - **kwargs
-
For other keyword-only arguments, see the ufunc docs.
-
- Returns
-
-
yndarray
-
The natural logarithm of
x
, element-wise. This is a scalar ifx
is a scalar.
-
Notes
Logarithm is a multivalued function: for each
x
there is an infinite number ofz
such thatexp(z) = x
. The convention is to return thez
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 yieldsnan
and sets theinvalid
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.References
-
1
-
M. Abramowitz and I.A. Stegun, “Handbook of Mathematical Functions”, 10th printing, 1964, pp. 67. http://www.math.sfu.ca/~cbm/aands/
-
2
-
Wikipedia, “Logarithm”. https://en.wikipedia.org/wiki/Logarithm
Examples
>>> np.log([1, np.e, np.e**2, 0]) array([ 0., 1., 2., -Inf])
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Licensed under the 3-clause BSD License.
https://numpy.org/doc/1.19/reference/generated/numpy.log.html