pub fn approx_threshold(mut self, threshold: F) -> Self {
        self.approx_threshold = threshold;

        self
    }
/// Set the approximation threshold of the Barnes Hut algorithm
///
/// The threshold decides whether a cluster centroid can be used as a summary for the whole
/// area. This was proposed by Barnes and Hut and compares the ratio of cell radius and
/// distance to a factor theta. This threshold lies in range (0, inf) where a value of 0
/// disables approximation and a positive value approximates the gradient with the cell center.
Set the approximation threshold of the Barnes Hut algorithm
The threshold decides whether a cluster centroid can be used as a summary for the whole
area. This was proposed by Barnes and Hut and compares the ratio of cell radius and
distance to a factor theta. This threshold lies in range (0, inf) where a value of 0
disables approximation and a positive value approximates the gradient with the cell center.
Set the approximation threshold of the Barnes Hut algorithm The threshold decides whether a cluster centroid can be used as a summary for the whole area . This was proposed by Barnes and Hut and compares the ratio of cell radius and distance to a factor theta . This threshold lies in range ( 0 inf ) where a value of 0 disables approximation and a positive value approximates the gradient with the cell center .
pub fn approx_threshold(mut self, threshold: F) -> Self {
        self.approx_threshold = threshold;
        self
    }
pub fn approx_threshold ( mut self , threshold : F ) -> Self { self . approx_threshold = threshold ; self }
Set the approximation threshold of the Barnes Hut algorithm
The threshold decides whether a cluster centroid can be used as a summary for the whole
area.
Set the approximation threshold of the Barnes Hut algorithm The threshold decides whether a cluster centroid can be used as a summary for the whole area .
mut self
threshold
F
mut self
threshold
F