[][src]Struct goko::plugins::discrete::baseline::KLDivergenceBaseline

pub struct KLDivergenceBaseline {
    pub num_sequences: usize,
    pub sequence_len: Vec<usize>,
    pub stats: Vec<KLDivergenceBaselineStats>,
}

Computing the KL div of each node's prior and posterior is expensive.

Fields

num_sequences: usize

The number of sequences we're have the stats from

sequence_len: Vec<usize>

The lenght of the sequences we have stats for. All other values are linearly interpolated between these.

stats: Vec<KLDivergenceBaselineStats>

The actual stats objects. These are stored by the moments, but are returned by (mean,var)

Implementations

impl KLDivergenceBaseline[src]

pub fn stats(&self, i: usize) -> KLDivergenceBaselineStats[src]

Gets the stats object that stores an approximate mean and variance of the samples.

Auto Trait Implementations

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