scipy.special.

spence#

scipy.special.spence(z, out=None)#

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.

Parameters:

zarray_like: Points at which to evaluate Spence’s function
outndarray, optional: Optional output array for the function results

Returns:

sscalar or ndarray: Computed values of Spence’s function

Notes

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).

Array API Standard Support

spence has experimental support for Python Array API Standard compatible backends in addition to NumPy. Please consider testing these features by setting an environment variable SCIPY_ARRAY_API=1 and providing CuPy, PyTorch, JAX, or Dask arrays as array arguments. The following combinations of backend and device (or other capability) are supported.

Library	CPU	GPU
NumPy	✅	n/a
CuPy	n/a	⛔
PyTorch	✅	⛔
JAX	✅	✅
Dask	✅	n/a

See Support for the array API standard for more information.

Examples

>>> importnumpyasnp
>>> fromscipy.specialimport spence
>>> importmatplotlib.pyplotasplt

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 ,
 2.32018041+3.45139229j])

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

>>> spence(-1.5)
nan

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)
(-2.6523186143876067+1.8853470951513935j)
>>> np.pi**2/6 - np.log(z)*np.log(1 - z)
(-2.652318614387606+1.885347095151394j)

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)')
>>> plt.show()

../../_images/scipy-special-spence-1.png