nltk.probability.UniformProbDist

class nltk.probability.UniformProbDist[source]

Bases: ProbDistI

A probability distribution that assigns equal probability to each sample in a given set; and a zero probability to all other samples.

__init__(samples)[source]

Construct a new uniform probability distribution, that assigns equal probability to each sample in samples.

Parameters

samples (list) – The samples that should be given uniform probability.

Raises

ValueError – If samples is empty.

prob(sample)[source]

Return the probability for a given sample. Probabilities are always real numbers in the range [0, 1].

Parameters

sample (any) – The sample whose probability should be returned.

Return type

float

max()[source]

Return the sample with the greatest probability. If two or more samples have the same probability, return one of them; which sample is returned is undefined.

Return type

any

samples()[source]

Return a list of all samples that have nonzero probabilities. Use prob to find the probability of each sample.

Return type

list

SUM_TO_ONE = True

True if the probabilities of the samples in this probability distribution will always sum to one.

discount()[source]

Return the ratio by which counts are discounted on average: c*/c

Return type

float

generate()[source]

Return a randomly selected sample from this probability distribution. The probability of returning each sample samp is equal to self.prob(samp).

logprob(sample)[source]

Return the base 2 logarithm of the probability for a given sample.

Parameters

sample (any) – The sample whose probability should be returned.

Return type

float