vtk-pure-rs 0.2.0

Pure Rust visualization toolkit — data structures, filters, I/O, rendering
Documentation 
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use crate::data::{AnyDataArray, DataArray, ImageData};

/// Downsample an ImageData by averaging blocks of voxels.
///
/// Reduces resolution by `factor` in each dimension by averaging
/// non-overlapping blocks. More robust than nearest-neighbor downsampling.
pub fn image_downsample(input: &ImageData, scalars: &str, factor: usize) -> ImageData {
    let arr = match input.point_data().get_array(scalars) {
        Some(a) => a,
        None => return input.clone(),
    };

    let f = factor.max(1);
    let dims = input.dimensions();
    let nx = dims[0] as usize;
    let ny = dims[1] as usize;
    let nz = dims[2] as usize;
    let spacing = input.spacing();
    let origin = input.origin();

    let nnx = (nx + f - 1) / f;
    let nny = (ny + f - 1) / f;
    let nnz = (nz + f - 1) / f;

    let mut values = vec![0.0f64; nnx * nny * nnz];
    let mut buf = [0.0f64];

    for dk in 0..nnz {
        for dj in 0..nny {
            for di in 0..nnx {
                let mut sum = 0.0;
                let mut count = 0;
                for k in dk*f..(dk*f+f).min(nz) {
                    for j in dj*f..(dj*f+f).min(ny) {
                        for i in di*f..(di*f+f).min(nx) {
                            arr.tuple_as_f64(k * ny * nx + j * nx + i, &mut buf);
                            sum += buf[0];
                            count += 1;
                        }
                    }
                }
                values[dk * nny * nnx + dj * nnx + di] = sum / count as f64;
            }
        }
    }

    let new_spacing = [spacing[0] * f as f64, spacing[1] * f as f64, spacing[2] * f as f64];
    let mut img = ImageData::with_dimensions(nnx, nny, nnz);
    img.set_origin(origin);
    img.set_spacing(new_spacing);
    img.point_data_mut().add_array(AnyDataArray::F64(DataArray::from_vec(scalars, values, 1)));
    img
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn downsample_2x() {
        let mut img = ImageData::with_dimensions(4, 4, 1);
        let values: Vec<f64> = (0..16).map(|i| i as f64).collect();
        img.point_data_mut().add_array(AnyDataArray::F64(
            DataArray::from_vec("v", values, 1),
        ));

        let result = image_downsample(&img, "v", 2);
        assert_eq!(result.dimensions(), [2, 2, 1]);
    }

    #[test]
    fn averaging() {
        let mut img = ImageData::with_dimensions(2, 2, 1);
        img.point_data_mut().add_array(AnyDataArray::F64(
            DataArray::from_vec("v", vec![0.0, 10.0, 20.0, 30.0], 1),
        ));

        let result = image_downsample(&img, "v", 2);
        assert_eq!(result.dimensions(), [1, 1, 1]);
        let arr = result.point_data().get_array("v").unwrap();
        let mut buf = [0.0f64];
        arr.tuple_as_f64(0, &mut buf);
        assert!((buf[0] - 15.0).abs() < 1e-10); // (0+10+20+30)/4
    }

    #[test]
    fn factor_1_noop() {
        let mut img = ImageData::with_dimensions(3, 3, 1);
        img.point_data_mut().add_array(AnyDataArray::F64(
            DataArray::from_vec("v", vec![1.0; 9], 1),
        ));

        let result = image_downsample(&img, "v", 1);
        assert_eq!(result.dimensions(), [3, 3, 1]);
    }
}