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lambertw(z, k=0, tol=1e-8)

The Lambert W function :None:None:`W(z)` is defined as the inverse function of w * exp(w) . In other words, the value of W(z) is such that z = W(z) * exp(W(z)) for any complex number z .

The Lambert W function is a multivalued function with infinitely many branches. Each branch gives a separate solution of the equation z = w exp(w) . Here, the branches are indexed by the integer k.

Notes

All branches are supported by lambertw :

The Lambert W function has two partially real branches: the principal branch (:None:None:`k = 0`) is real for real z > -1/e , and the k = -1 branch is real for -1/e < z < 0 . All branches except k = 0 have a logarithmic singularity at z = 0 .

Possible issues

The evaluation can become inaccurate very close to the branch point at -1/e . In some corner cases, lambertw might currently fail to converge, or can end up on the wrong branch.

Algorithm

Halley's iteration is used to invert w * exp(w) , using a first-order asymptotic approximation (O(log(w)) or :None:None:`O(w)`) as the initial estimate.

The definition, implementation and choice of branches is based on .

Parameters

z : array_like

Input argument.

k : int, optional

Branch index.

tol : float, optional

Evaluation tolerance.

Returns

w : array

w will have the same shape as z.

Lambert W function.

See Also

wrightomega

the Wright Omega function

Examples

The Lambert W function is the inverse of w exp(w) :

>>> from scipy.special import lambertw
... w = lambertw(1)
... w (0.56714329040978384+0j)
>>> w * np.exp(w)
(1.0+0j)

Any branch gives a valid inverse:

>>> w = lambertw(1, k=3)
... w (-2.8535817554090377+17.113535539412148j)
>>> w*np.exp(w)
(1.0000000000000002+1.609823385706477e-15j)

Applications to equation-solving

The Lambert W function may be used to solve various kinds of equations, such as finding the value of the infinite power tower $z^{z^{z^{\ldots}}}$ :

>>> def tower(z, n):
...  if n == 0:
...  return z
...  return z ** tower(z, n-1) ...
>>> tower(0.5, 100)
0.641185744504986
>>> -lambertw(-np.log(0.5)) / np.log(0.5)
(0.64118574450498589+0j)
See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

scipy.special._lambertw.lambertw

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GitHub : /scipy/special/_lambertw.py#4
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