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Nn precision fix (#124) #126

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Feb 20, 2025
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8 changes: 8 additions & 0 deletions CHANGELOG.md
Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,12 @@ All notable changes to this project will be documented in this file.
The format is based on [Keep a Changelog](http://keepachangelog.com/)
and this project adheres to [Semantic Versioning](http://semver.org/).

## [2.13.0] - 2025-02-20

### Fix
- Fixes #124
- Increases MSRV to 1.56.1

## [2.12.1] - 2024-09-09

### Fix
Expand Down Expand Up @@ -475,6 +481,8 @@ A lot has changed for the 1.0. release, only larger changes are shown.

Initial commit

[2.13.0]: https://github.com/Stoeoef/spade/compare/v2.12.1...v2.13.0

[2.12.1]: https://github.com/Stoeoef/spade/compare/v2.12.0...v2.12.1

[2.12.0]: https://github.com/Stoeoef/spade/compare/v2.11.0...v2.12.0
Expand Down
6 changes: 4 additions & 2 deletions examples/interpolation/main.rs
Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
use anyhow::*;
use image::{ImageBuffer, Rgba};
use image::{buffer::ConvertBuffer, ImageBuffer, Rgb, Rgba};
use std::io::{Cursor, Write};

use base64::Engine;
Expand Down Expand Up @@ -152,8 +152,10 @@ pub fn main() -> Result<()> {
// the jpeg encoding.
let (width, height) = (pixmap.width(), pixmap.height());
let data = pixmap.take();
let buffer = ImageBuffer::<Rgba<u8>, _>::from_vec(width, height, data)
let buffer_with_alpha = ImageBuffer::<Rgba<u8>, _>::from_vec(width, height, data)
.context("Failed to convert to ImageBuffer")?;
// Get rid of the alpha component which isn't supported by jpeg
let buffer: ImageBuffer<Rgb<u8>, _> = buffer_with_alpha.convert();

let mut data_jpeg: Cursor<Vec<u8>> = Cursor::new(Vec::new());
buffer.write_to(&mut data_jpeg, image::ImageFormat::Jpeg)?;
Expand Down
2 changes: 1 addition & 1 deletion images/interpolation_nearest_neighbor.img

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2 changes: 2 additions & 0 deletions src/cdt.rs
Original file line number Diff line number Diff line change
Expand Up @@ -717,11 +717,13 @@ where
}

#[cfg(any(test, fuzzing))]
#[allow(missing_docs)]
pub fn cdt_sanity_check(&self) {
self.cdt_sanity_check_with_params(true);
}

#[cfg(any(test, fuzzing))]
#[allow(missing_docs)]
pub fn cdt_sanity_check_with_params(&self, check_convexity: bool) {
let num_undirected_edges = self
.dcel
Expand Down
78 changes: 76 additions & 2 deletions src/delaunay_core/interpolation.rs
Original file line number Diff line number Diff line change
Expand Up @@ -486,7 +486,14 @@
let cur_nn = self.triangulation.directed_edge(*cur_nn);

let [from, to] = cur_nn.positions();
insertion_cell.push(math::circumcenter([to, from, position]).0);
insertion_cell.push(
math::circumcenter([
to.sub(position),
from.sub(position),
Point2::new(zero(), zero()),
])
.0,
);
}

let mut total_area = zero(); // Used to normalize weights at the end
Expand Down Expand Up @@ -524,7 +531,15 @@
// out edge of the current natural neighbor.
//
// The natural_neighbor_polygon.svg refers to this variable as `c0`, `c1`, and `c2`.
let current = last_edge.face().as_inner().unwrap().circumcenter();
let vertices = last_edge
.face()
.as_inner()
.unwrap()
.positions()
.map(|p| p.sub(position));

let current = math::circumcenter(vertices).0;

positive_area = positive_area + last.x * current.y;
negative_area = negative_area + last.y * current.x;

Expand Down Expand Up @@ -668,6 +683,9 @@

#[cfg(test)]
mod test {
use std::io;

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unused import: `std::io`

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unused import: `std::io`

use anyhow::Context;

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unused import: `anyhow::Context`
use approx::assert_ulps_eq;

use crate::test_utilities::{random_points_in_range, random_points_with_seed, SEED, SEED2};
Expand Down Expand Up @@ -892,4 +910,60 @@

Ok(())
}

#[test]
fn test_nan_issue() -> Result<(), InsertionError> {
let vertices = vec![
Point2 {
x: 2273118.4147972693,
y: 6205168.575915335,
},
Point2 {
x: 2273118.2119929367,
y: 6205168.6854697745,
},
Point2 {
x: 2273118.1835989403,
y: 6205168.653506873,
},
Point2 {
x: 2273118.2647345643,
y: 6205169.082690307,
},
Point2 {
x: 2273118.105938253,
y: 6205168.163882839,
},
Point2 {
x: 2273117.7264146665,
y: 6205168.718028998,
},
Point2 {
x: 2273118.0946678743,
y: 6205169.148656867,
},
Point2 {
x: 2273118.3779900977,
y: 6205168.1644559605,
},
Point2 {
x: 2273117.71105166,
y: 6205168.459413756,
},
Point2 {
x: 2273118.30732556,
y: 6205169.130634655,
},
];

let delaunay = DelaunayTriangulation::<_>::bulk_load(vertices)?;

let nns = delaunay.natural_neighbor();
let result: f64 = nns
.interpolate(|_| 1.0, Point2::new(2273118.2, 6205168.666666667))
.unwrap();

assert!(!result.is_nan());
Ok(())
}
}
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