ggplot_rs/stat/
bin2d.rs

1use crate::aes::Aesthetic;
2use crate::data::{DataFrame, Value};
3use crate::scale::ScaleSet;
4
5use super::Stat;
6
7/// 2D rectangular binning. Divides x/y ranges into a grid, counts per cell.
8pub struct StatBin2d {
9    pub bins_x: usize,
10    pub bins_y: usize,
11}
12
13impl Default for StatBin2d {
14    fn default() -> Self {
15        StatBin2d {
16            bins_x: 30,
17            bins_y: 30,
18        }
19    }
20}
21
22impl Stat for StatBin2d {
23    fn compute_group(&self, data: &DataFrame, _scales: &ScaleSet) -> DataFrame {
24        let x_col = match data.column("x") {
25            Some(c) => c,
26            None => return DataFrame::new(),
27        };
28        let y_col = match data.column("y") {
29            Some(c) => c,
30            None => return DataFrame::new(),
31        };
32
33        let xs: Vec<f64> = x_col.iter().filter_map(|v| v.as_f64()).collect();
34        let ys: Vec<f64> = y_col.iter().filter_map(|v| v.as_f64()).collect();
35        let n = xs.len().min(ys.len());
36        if n == 0 {
37            return DataFrame::new();
38        }
39
40        let x_min = xs.iter().cloned().fold(f64::INFINITY, f64::min);
41        let x_max = xs.iter().cloned().fold(f64::NEG_INFINITY, f64::max);
42        let y_min = ys.iter().cloned().fold(f64::INFINITY, f64::min);
43        let y_max = ys.iter().cloned().fold(f64::NEG_INFINITY, f64::max);
44
45        let (x_min, x_max) = if (x_max - x_min).abs() < f64::EPSILON {
46            (x_min - 0.5, x_max + 0.5)
47        } else {
48            (x_min, x_max)
49        };
50        let (y_min, y_max) = if (y_max - y_min).abs() < f64::EPSILON {
51            (y_min - 0.5, y_max + 0.5)
52        } else {
53            (y_min, y_max)
54        };
55
56        let bw_x = (x_max - x_min) / self.bins_x as f64;
57        let bw_y = (y_max - y_min) / self.bins_y as f64;
58
59        let mut counts = vec![vec![0usize; self.bins_y]; self.bins_x];
60
61        for i in 0..n {
62            let bx = ((xs[i] - x_min) / bw_x).floor() as usize;
63            let by = ((ys[i] - y_min) / bw_y).floor() as usize;
64            let bx = bx.min(self.bins_x - 1);
65            let by = by.min(self.bins_y - 1);
66            counts[bx][by] += 1;
67        }
68
69        let mut xmin_vals = Vec::new();
70        let mut xmax_vals = Vec::new();
71        let mut ymin_vals = Vec::new();
72        let mut ymax_vals = Vec::new();
73        let mut fill_vals = Vec::new();
74
75        for (bx, row) in counts.iter().enumerate() {
76            for (by, &count) in row.iter().enumerate() {
77                if count == 0 {
78                    continue;
79                }
80                let cell_xmin = x_min + bx as f64 * bw_x;
81                let cell_xmax = cell_xmin + bw_x;
82                let cell_ymin = y_min + by as f64 * bw_y;
83                let cell_ymax = cell_ymin + bw_y;
84
85                xmin_vals.push(Value::Float(cell_xmin));
86                xmax_vals.push(Value::Float(cell_xmax));
87                ymin_vals.push(Value::Float(cell_ymin));
88                ymax_vals.push(Value::Float(cell_ymax));
89                fill_vals.push(Value::Float(count as f64));
90            }
91        }
92
93        let mut result = DataFrame::new();
94        result.add_column("xmin".to_string(), xmin_vals);
95        result.add_column("xmax".to_string(), xmax_vals);
96        result.add_column("ymin".to_string(), ymin_vals);
97        result.add_column("ymax".to_string(), ymax_vals);
98        result.add_column("fill".to_string(), fill_vals);
99
100        result
101    }
102
103    fn required_aes(&self) -> Vec<Aesthetic> {
104        vec![Aesthetic::X, Aesthetic::Y]
105    }
106
107    fn name(&self) -> &str {
108        "bin2d"
109    }
110}
111
112#[cfg(test)]
113mod tests {
114    use super::*;
115
116    #[test]
117    fn test_bin2d_basic() {
118        let mut data = DataFrame::new();
119        let x_vals: Vec<Value> = (0..100).map(|i| Value::Float(i as f64 / 10.0)).collect();
120        let y_vals: Vec<Value> = (0..100).map(|i| Value::Float(i as f64 / 5.0)).collect();
121        data.add_column("x".to_string(), x_vals);
122        data.add_column("y".to_string(), y_vals);
123
124        let stat = StatBin2d {
125            bins_x: 5,
126            bins_y: 5,
127        };
128        let scales = ScaleSet::new();
129        let result = stat.compute_group(&data, &scales);
130
131        assert!(result.nrows() > 0);
132        assert!(result.column("xmin").is_some());
133        assert!(result.column("xmax").is_some());
134        assert!(result.column("ymin").is_some());
135        assert!(result.column("ymax").is_some());
136        assert!(result.column("fill").is_some());
137    }
138}
ggplot_rs/stat/bin2d.rs

ggplot_rs/stat/
bin2d.rs
