estimator.nd.Uniform

estimator.nd.Uniform#

class estimator.nd.Uniform(a, b, n=None)[source]#

Uniform distribution ∈ ZZ [a, b], endpoints inclusive.

EXAMPLE:

>>> from estimator import *
>>> ND.Uniform(-3, 3)
D(σ=2.00)
>>> ND.Uniform(-4, 3)
D(σ=2.29, μ=-0.50)
__call__(**kwargs)#

Call self as a function.

Methods

__init__(a, b[, n])

resize(new_n)

Return an altered distribution having a dimension new_n.

support_size([fraction])

Compute the size of the support covering the probability given as fraction.

Attributes

bounds

hamming_weight

The number of non-zero coefficients in this distribution

is_Gaussian_like

is_bounded

Whether the value of coefficients are bounded

is_sparse

Whether the density of the distribution is < 1/2.

mean

n

stddev