Trait sampling::histogram::HistogramPartition

source · 
pub trait HistogramPartition: Sized {
    // Required method
    fn overlapping_partition(
        &self,
        n: usize,
        overlap: usize
    ) -> Result<Vec<Self>, HistErrors>;
}
Expand description

Your Interval is to large to sample in a reasonable amount of time? No problem

In WangLandau or EntropicSampling, you can split your interval in smaller, overlapping intervals and “glue” them together later on

Required Methods§

source

fn overlapping_partition( &self, n: usize, overlap: usize ) -> Result<Vec<Self>, HistErrors>

partition the interval
  • returns Vector of n histograms, that together
parameter
  • n number of resulting intervals
  • overlap How much overlap should there be?
To understand overlap, we have to look at the formula for the i_th interval in the result vector:

let left be the left border of self and right be the right border of self

  • left border of interval i = left + i * (right - left) / (n + overlap)
  • right border of interval i = left + (i + overlap) * (right - left) / (n + overlap)

Object Safety§

This trait is not object safe.

Implementors§