scipy.special.spence(z, out=None) = <ufunc 'spence'>#

Spence’s function, also known as the dilogarithm.

It is defined to be

\[\int_1^z \frac{\log(t)}{1 - t}dt\]

for complex \(z\), where the contour of integration is taken to avoid the branch cut of the logarithm. Spence’s function is analytic everywhere except the negative real axis where it has a branch cut.


Points at which to evaluate Spence’s function

outndarray, optional

Optional output array for the function results

sscalar or ndarray

Computed values of Spence’s function


There is a different convention which defines Spence’s function by the integral

\[-\int_0^z \frac{\log(1 - t)}{t}dt;\]

this is our spence(1 - z).


>>> import numpy as np
>>> from scipy.special import spence
>>> import matplotlib.pyplot as plt

The function is defined for complex inputs:

>>> spence([1-1j, 1.5+2j, 3j, -10-5j])
array([-0.20561676+0.91596559j, -0.86766909-1.39560134j,
       -0.59422064-2.49129918j, -1.14044398+6.80075924j])

For complex inputs on the branch cut, which is the negative real axis, the function returns the limit for z with positive imaginary part. For example, in the following, note the sign change of the imaginary part of the output for z = -2 and z = -2 - 1e-8j:

>>> spence([-2 + 1e-8j, -2, -2 - 1e-8j])
array([2.32018041-3.45139229j, 2.32018042-3.4513923j ,

The function returns nan for real inputs on the branch cut:

>>> spence(-1.5)

Verify some particular values: spence(0) = pi**2/6, spence(1) = 0 and spence(2) = -pi**2/12.

>>> spence([0, 1, 2])
array([ 1.64493407,  0.        , -0.82246703])
>>> np.pi**2/6, -np.pi**2/12
(1.6449340668482264, -0.8224670334241132)

Verify the identity:

spence(z) + spence(1 - z) = pi**2/6 - log(z)*log(1 - z)
>>> z = 3 + 4j
>>> spence(z) + spence(1 - z)
>>> np.pi**2/6 - np.log(z)*np.log(1 - z)

Plot the function for positive real input.

>>> fig, ax = plt.subplots()
>>> x = np.linspace(0, 6, 400)
>>> ax.plot(x, spence(x))
>>> ax.grid()
>>> ax.set_xlabel('x')
>>> ax.set_title('spence(x)')