@@ -5,88 +5,6 @@ use noisy_float::prelude::*;
55
66use super :: brain_volume;
77
8- /*
9-
10- /// Scale x and y relative so that the bigger one will be max_val.
11- fn _scale_relative(x: u32, y: u32, max_val: u32) -> (u32, u32) {
12- let (fx, fy, fmax_val) = (x as f32, y as f32, max_val as f32);
13-
14- let fxy_max = std::cmp::max(x, y) as f32;
15-
16- let out_x = std::cmp::min(((fx / fxy_max) * fmax_val) as u32, max_val);
17- let out_y = std::cmp::min(((fy / fxy_max) * fmax_val) as u32, max_val);
18-
19- return (out_x, out_y);
20- }
21-
22- fn fit_relative(src_x: u32, src_y: u32, dest_x: u32, dest_y: u32) -> (u32, u32) {
23- let src_aspect = src_x as f32 / src_y as f32;
24- let dest_aspect = dest_x as f32 / dest_y as f32;
25-
26- let resize_factor = if src_aspect >= dest_aspect {
27- dest_x as f32 / src_x as f32
28- } else {
29- dest_y as f32 / src_y as f32
30- };
31-
32- return (
33- (src_x as f32 * resize_factor) as u32,
34- (src_y as f32 * resize_factor) as u32,
35- );
36- }
37-
38- fn _normalize_u8<D>(
39- data: &ndarray::Array<f32, D>,
40- intensity_range: (f32, f32),
41- ) -> ndarray::Array<u8, D>
42- where
43- D: ndarray::Dimension,
44- {
45- let (imin, imax) = intensity_range;
46- return (((data - imin) / (imax - imin)) * (u8::MAX as f32))
47- .mapv(|v| num::clamp(v, u8::MIN as f32, u8::MAX as f32) as u8);
48- }
49-
50- fn normalize_u16<D>(
51- data: &ndarray::Array<f32, D>,
52- intensity_range: (f32, f32),
53- ) -> ndarray::Array<u16, D>
54- where
55- D: ndarray::Dimension,
56- {
57- let (imin, imax) = intensity_range;
58- return (((data - imin) / (imax - imin)) * (u16::MAX as f32))
59- .mapv(|v| num::clamp(v, u16::MIN as f32, u16::MAX as f32) as u16);
60- }
61-
62- fn normalize_u16_f64<D>(
63- data: &ndarray::Array<f64, D>,
64- intensity_range: (f64, f64),
65- ) -> ndarray::Array<u16, D>
66- where
67- D: ndarray::Dimension,
68- {
69- let (imin, imax) = intensity_range;
70- return (((data - imin) / (imax - imin)) * (u16::MAX as f64))
71- .mapv(|v| num::clamp(v, u16::MIN as f64, u16::MAX as f64) as u16);
72- }
73-
74- fn make_image_gray<D>(data: ndarray::Array2<D>) -> image::ImageBuffer<Luma<D>, Vec<D>>
75- where
76- D: image::Primitive,
77- {
78- let width = data.shape()[0] as u32;
79- let height = data.shape()[1] as u32;
80- return image::ImageBuffer::<Luma<D>, Vec<D>>::from_raw(
81- height,
82- width,
83- data.reversed_axes().into_raw_vec(),
84- )
85- .unwrap();
86- }
87-
88- */
89-
908#[ derive( Debug , Clone , Copy , PartialEq , Eq , Hash ) ]
919pub struct CachableSlicerParams {
9210 pub axis : sampling:: SliceAxis ,
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