numpy.log
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numpy.log(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'log'>
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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: -
x : array_like
-
Input value.
-
out : ndarray, 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. -
where : array_like, optional
-
Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone.
- **kwargs
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For other keyword-only arguments, see the ufunc docs.
Returns: -
y : ndarray
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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://docs.scipy.org/doc/numpy-1.16.1/reference/generated/numpy.log.html