Struct SliceBuilder 

pub struct SliceBuilder<'a> { /* private fields */ }

Builder for tensor slicing (RFC-008 §10). This is the canonical API.

Create via Tensor::slice; finish with .build().

Examples

use matten::Tensor;

let t = Tensor::new(vec![1.0,2.0,3.0,4.0,5.0,6.0], &[2, 3]);

// First row: index axis 0, keep all of axis 1
let row = t.slice().index(0).all().build().unwrap();
assert_eq!(row.shape(), &[3]);
assert_eq!(row.as_slice(), &[1.0, 2.0, 3.0]);

// First two rows, all columns
let top = t.slice().range(0..2).all().build().unwrap();
assert_eq!(top.shape(), &[2, 3]);

Implementations

impl<'a> SliceBuilder<'a>

pub fn all(self) -> Self

Selects all elements along the next axis.

Examples found in repository

examples/54_pairwise_distance.rs (line 40)

fn main() {
    let points = Tensor::new(vec![0.0, 0.0, 3.0, 4.0, 6.0, 0.0], &[3, 2]);

    let dists = pairwise_euclidean(&points);
    println!("pairwise distances:");
    for i in 0..3 {
        let row = dists.slice().index(i).all().build().unwrap();
        println!("  row {i}: {:?}", row.as_slice());
    }

    // (0,0)→(3,4) = 5, (3,4)→(6,0) = 5, (0,0)→(6,0) = 6
    assert!((dists.get(&[0, 1]).unwrap() - 5.0).abs() < 1e-9);
    assert!((dists.get(&[1, 2]).unwrap() - 5.0).abs() < 1e-9);
    assert!((dists.get(&[0, 2]).unwrap() - 6.0).abs() < 1e-9);
    println!("Pairwise distances: OK");
}

examples/08_slicing_builder.rs (line 14)

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let t = Tensor::new((1..=12).map(|x| x as f64).collect(), &[3, 4]);
    println!("tensor   {t:?}");

    // First row (index 0, axis removed from output shape)
    let row0 = t.slice().index(0).all().build()?;
    println!("row 0    {row0:?}"); // shape [4]

    // First two rows, all columns
    let top2 = t.slice().range(0..2).all().build()?;
    println!("top 2    {top2:?}"); // shape [2,4]

    // All rows, columns 1..3
    let cols = t.slice().all().range(1..3).build()?;
    println!("cols 1:3 {cols:?}"); // shape [3,2]

    // Single element -> scalar
    let elem = t.slice().index(1).index(2).build()?;
    assert!(elem.is_scalar());
    println!("t[1,2]   {elem:?}");

    Ok(())
}

examples/09_slice_str.rs (line 25)

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let t = Tensor::new((1..=12).map(|x| x as f64).collect(), &[3, 4]);

    println!("\"0, :\"    = {:?}", t.slice_str("0, :")?);
    println!("\"0:2, :\" = {:?}", t.slice_str("0:2, :")?);
    println!("\":, 1:3\" = {:?}", t.slice_str(":, 1:3")?);

    // Whitespace is ignored
    let a = t.slice_str("0:2, :")?;
    let b = t.slice_str(" 0:2 , : ")?;
    assert_eq!(a, b);
    println!("whitespace-insensitive: OK");

    // builder and slice_str agree
    let from_str = t.slice_str("0:2, :")?;
    let from_builder = t.slice().range(0..2).all().build()?;
    assert_eq!(from_str, from_builder);
    println!("builder == slice_str: OK");

    // Malformed specs never panic
    println!("bad spec: {:?}", t.slice_str("0::")); // Err

    Ok(())
}

examples/52_minmax_scaling.rs (line 26)

fn main() {
    let data = Tensor::new(
        vec![1.0, 10.0, 100.0, 2.0, 20.0, 200.0, 3.0, 30.0, 300.0],
        &[3, 3],
    );

    // Column min and max using axis reductions
    let col_min = data.min_axis(0);
    let col_max = data.max_axis(0);
    let range = &col_max - &col_min;

    // Broadcast: (data - min) / (max - min)
    let scaled = &(&data - &col_min) / ⦥

    println!("col_min  = {:?}", col_min.as_slice());
    println!("col_max  = {:?}", col_max.as_slice());
    println!("scaled shape = {:?}", scaled.shape());

    // First row should be all 0.0, last row all 1.0
    let row0 = scaled.slice().index(0).all().build().unwrap();
    let row2 = scaled.slice().index(2).all().build().unwrap();
    assert!(row0.as_slice().iter().all(|&v| (v - 0.0).abs() < 1e-10));
    assert!(row2.as_slice().iter().all(|&v| (v - 1.0).abs() < 1e-10));
    println!("Min-max scaling: OK");
}

examples/12_boundary_error_handling.rs (line 45)

fn main() {
    // ── shape/data mismatch ──────────────────────────────────────────────
    match Tensor::try_new(vec![1.0, 2.0], &[3]) {
        Err(MattenError::Shape { operation, message }) => {
            println!("[Shape]  {operation}: {message}")
        }
        other => println!("{other:?}"),
    }

    // ── malformed JSON ───────────────────────────────────────────────────
    match Tensor::from_json(r#"[[1.0,"text"]]"#) {
        Err(MattenError::Parse { format, message }) => println!("[Parse/{format}]  {message}"),
        other => println!("{other:?}"),
    }

    // ── ragged JSON array ────────────────────────────────────────────────
    match Tensor::from_json("[[1.0,2.0],[3.0]]") {
        Err(MattenError::Parse { format, message }) => println!("[Parse/{format}]  {message}"),
        other => println!("{other:?}"),
    }

    // ── non-numeric CSV field ────────────────────────────────────────────
    match Tensor::load_csv("examples/data/malformed_numeric.csv") {
        Err(MattenError::Parse { format, message }) => println!("[Parse/{format}]  {message}"),
        other => println!("{other:?}"),
    }

    // ── missing file ─────────────────────────────────────────────────────
    match Tensor::load_json("/no/such/file.json") {
        Err(MattenError::Io { path, source }) => println!("[Io]  {}: {source}", path.display()),
        other => println!("{other:?}"),
    }

    // ── slice out of range ───────────────────────────────────────────────
    let t = Tensor::new(vec![1.0, 2.0, 3.0, 4.0], &[2, 2]);
    match t.slice().index(5).all().build() {
        Err(MattenError::Slice { message, .. }) => println!("[Slice]  {message}"),
        other => println!("{other:?}"),
    }

    println!("All boundary errors handled gracefully — no panics.");
}

pub fn index(self, index: usize) -> Self

Selects a single element along the next axis. That axis is removed from the output shape.

Examples found in repository

examples/54_pairwise_distance.rs (line 40)

fn main() {
    let points = Tensor::new(vec![0.0, 0.0, 3.0, 4.0, 6.0, 0.0], &[3, 2]);

    let dists = pairwise_euclidean(&points);
    println!("pairwise distances:");
    for i in 0..3 {
        let row = dists.slice().index(i).all().build().unwrap();
        println!("  row {i}: {:?}", row.as_slice());
    }

    // (0,0)→(3,4) = 5, (3,4)→(6,0) = 5, (0,0)→(6,0) = 6
    assert!((dists.get(&[0, 1]).unwrap() - 5.0).abs() < 1e-9);
    assert!((dists.get(&[1, 2]).unwrap() - 5.0).abs() < 1e-9);
    assert!((dists.get(&[0, 2]).unwrap() - 6.0).abs() < 1e-9);
    println!("Pairwise distances: OK");
}

examples/08_slicing_builder.rs (line 14)

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let t = Tensor::new((1..=12).map(|x| x as f64).collect(), &[3, 4]);
    println!("tensor   {t:?}");

    // First row (index 0, axis removed from output shape)
    let row0 = t.slice().index(0).all().build()?;
    println!("row 0    {row0:?}"); // shape [4]

    // First two rows, all columns
    let top2 = t.slice().range(0..2).all().build()?;
    println!("top 2    {top2:?}"); // shape [2,4]

    // All rows, columns 1..3
    let cols = t.slice().all().range(1..3).build()?;
    println!("cols 1:3 {cols:?}"); // shape [3,2]

    // Single element -> scalar
    let elem = t.slice().index(1).index(2).build()?;
    assert!(elem.is_scalar());
    println!("t[1,2]   {elem:?}");

    Ok(())
}

examples/52_minmax_scaling.rs (line 26)

fn main() {
    let data = Tensor::new(
        vec![1.0, 10.0, 100.0, 2.0, 20.0, 200.0, 3.0, 30.0, 300.0],
        &[3, 3],
    );

    // Column min and max using axis reductions
    let col_min = data.min_axis(0);
    let col_max = data.max_axis(0);
    let range = &col_max - &col_min;

    // Broadcast: (data - min) / (max - min)
    let scaled = &(&data - &col_min) / ⦥

    println!("col_min  = {:?}", col_min.as_slice());
    println!("col_max  = {:?}", col_max.as_slice());
    println!("scaled shape = {:?}", scaled.shape());

    // First row should be all 0.0, last row all 1.0
    let row0 = scaled.slice().index(0).all().build().unwrap();
    let row2 = scaled.slice().index(2).all().build().unwrap();
    assert!(row0.as_slice().iter().all(|&v| (v - 0.0).abs() < 1e-10));
    assert!(row2.as_slice().iter().all(|&v| (v - 1.0).abs() < 1e-10));
    println!("Min-max scaling: OK");
}

examples/12_boundary_error_handling.rs (line 45)

fn main() {
    // ── shape/data mismatch ──────────────────────────────────────────────
    match Tensor::try_new(vec![1.0, 2.0], &[3]) {
        Err(MattenError::Shape { operation, message }) => {
            println!("[Shape]  {operation}: {message}")
        }
        other => println!("{other:?}"),
    }

    // ── malformed JSON ───────────────────────────────────────────────────
    match Tensor::from_json(r#"[[1.0,"text"]]"#) {
        Err(MattenError::Parse { format, message }) => println!("[Parse/{format}]  {message}"),
        other => println!("{other:?}"),
    }

    // ── ragged JSON array ────────────────────────────────────────────────
    match Tensor::from_json("[[1.0,2.0],[3.0]]") {
        Err(MattenError::Parse { format, message }) => println!("[Parse/{format}]  {message}"),
        other => println!("{other:?}"),
    }

    // ── non-numeric CSV field ────────────────────────────────────────────
    match Tensor::load_csv("examples/data/malformed_numeric.csv") {
        Err(MattenError::Parse { format, message }) => println!("[Parse/{format}]  {message}"),
        other => println!("{other:?}"),
    }

    // ── missing file ─────────────────────────────────────────────────────
    match Tensor::load_json("/no/such/file.json") {
        Err(MattenError::Io { path, source }) => println!("[Io]  {}: {source}", path.display()),
        other => println!("{other:?}"),
    }

    // ── slice out of range ───────────────────────────────────────────────
    let t = Tensor::new(vec![1.0, 2.0, 3.0, 4.0], &[2, 2]);
    match t.slice().index(5).all().build() {
        Err(MattenError::Slice { message, .. }) => println!("[Slice]  {message}"),
        other => println!("{other:?}"),
    }

    println!("All boundary errors handled gracefully — no panics.");
}

pub fn range<R: IntoSliceRange>(self, range: R) -> Self

Selects a range of elements along the next axis.

Accepts Range, RangeFrom, RangeTo, RangeFull, or RangeInclusive.

Examples found in repository

examples/56_rolling_windows_basic.rs (line 9)

fn rolling_sum(t: &Tensor, window: usize) -> Vec<f64> {
    (0..=(t.len() - window))
        .map(|i| t.slice().range(i..i + window).build().unwrap().sum())
        .collect()
}

fn rolling_max(t: &Tensor, window: usize) -> Vec<f64> {
    (0..=(t.len() - window))
        .map(|i| t.slice().range(i..i + window).build().unwrap().max())
        .collect()
}

examples/55_moving_average.rs (line 15)

fn main() {
    let series = Tensor::from_vec(vec![1.0, 3.0, 5.0, 7.0, 9.0, 11.0, 13.0]);
    let window = 3usize;
    let n = series.len();

    // Compute moving averages for windows [0..3], [1..4], ...
    let mut avgs = Vec::new();
    for start in 0..=(n - window) {
        let w = series.slice().range(start..start + window).build().unwrap();
        avgs.push(w.mean());
    }

    println!("series = {:?}", series.as_slice());
    println!("3-pt moving avg = {:?}", avgs);
    assert_eq!(avgs.len(), n - window + 1);
    assert!((avgs[0] - 3.0).abs() < 1e-10); // mean(1,3,5) = 3
    assert!((avgs[1] - 5.0).abs() < 1e-10); // mean(3,5,7) = 5
    println!("Moving average: OK");
}

examples/08_slicing_builder.rs (line 18)

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let t = Tensor::new((1..=12).map(|x| x as f64).collect(), &[3, 4]);
    println!("tensor   {t:?}");

    // First row (index 0, axis removed from output shape)
    let row0 = t.slice().index(0).all().build()?;
    println!("row 0    {row0:?}"); // shape [4]

    // First two rows, all columns
    let top2 = t.slice().range(0..2).all().build()?;
    println!("top 2    {top2:?}"); // shape [2,4]

    // All rows, columns 1..3
    let cols = t.slice().all().range(1..3).build()?;
    println!("cols 1:3 {cols:?}"); // shape [3,2]

    // Single element -> scalar
    let elem = t.slice().index(1).index(2).build()?;
    assert!(elem.is_scalar());
    println!("t[1,2]   {elem:?}");

    Ok(())
}

examples/09_slice_str.rs (line 25)

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let t = Tensor::new((1..=12).map(|x| x as f64).collect(), &[3, 4]);

    println!("\"0, :\"    = {:?}", t.slice_str("0, :")?);
    println!("\"0:2, :\" = {:?}", t.slice_str("0:2, :")?);
    println!("\":, 1:3\" = {:?}", t.slice_str(":, 1:3")?);

    // Whitespace is ignored
    let a = t.slice_str("0:2, :")?;
    let b = t.slice_str(" 0:2 , : ")?;
    assert_eq!(a, b);
    println!("whitespace-insensitive: OK");

    // builder and slice_str agree
    let from_str = t.slice_str("0:2, :")?;
    let from_builder = t.slice().range(0..2).all().build()?;
    assert_eq!(from_str, from_builder);
    println!("builder == slice_str: OK");

    // Malformed specs never panic
    println!("bad spec: {:?}", t.slice_str("0::")); // Err

    Ok(())
}

pub fn build(self) -> Result<Tensor, MattenError>

Materialises the slice as an owned Tensor.

Errors

Returns MattenError::Slice on rank mismatch or out-of-bounds specs.

Examples found in repository

examples/56_rolling_windows_basic.rs (line 9)

fn rolling_sum(t: &Tensor, window: usize) -> Vec<f64> {
    (0..=(t.len() - window))
        .map(|i| t.slice().range(i..i + window).build().unwrap().sum())
        .collect()
}

fn rolling_max(t: &Tensor, window: usize) -> Vec<f64> {
    (0..=(t.len() - window))
        .map(|i| t.slice().range(i..i + window).build().unwrap().max())
        .collect()
}

examples/54_pairwise_distance.rs (line 40)

fn main() {
    let points = Tensor::new(vec![0.0, 0.0, 3.0, 4.0, 6.0, 0.0], &[3, 2]);

    let dists = pairwise_euclidean(&points);
    println!("pairwise distances:");
    for i in 0..3 {
        let row = dists.slice().index(i).all().build().unwrap();
        println!("  row {i}: {:?}", row.as_slice());
    }

    // (0,0)→(3,4) = 5, (3,4)→(6,0) = 5, (0,0)→(6,0) = 6
    assert!((dists.get(&[0, 1]).unwrap() - 5.0).abs() < 1e-9);
    assert!((dists.get(&[1, 2]).unwrap() - 5.0).abs() < 1e-9);
    assert!((dists.get(&[0, 2]).unwrap() - 6.0).abs() < 1e-9);
    println!("Pairwise distances: OK");
}

examples/55_moving_average.rs (line 15)

fn main() {
    let series = Tensor::from_vec(vec![1.0, 3.0, 5.0, 7.0, 9.0, 11.0, 13.0]);
    let window = 3usize;
    let n = series.len();

    // Compute moving averages for windows [0..3], [1..4], ...
    let mut avgs = Vec::new();
    for start in 0..=(n - window) {
        let w = series.slice().range(start..start + window).build().unwrap();
        avgs.push(w.mean());
    }

    println!("series = {:?}", series.as_slice());
    println!("3-pt moving avg = {:?}", avgs);
    assert_eq!(avgs.len(), n - window + 1);
    assert!((avgs[0] - 3.0).abs() < 1e-10); // mean(1,3,5) = 3
    assert!((avgs[1] - 5.0).abs() < 1e-10); // mean(3,5,7) = 5
    println!("Moving average: OK");
}

examples/08_slicing_builder.rs (line 14)

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let t = Tensor::new((1..=12).map(|x| x as f64).collect(), &[3, 4]);
    println!("tensor   {t:?}");

    // First row (index 0, axis removed from output shape)
    let row0 = t.slice().index(0).all().build()?;
    println!("row 0    {row0:?}"); // shape [4]

    // First two rows, all columns
    let top2 = t.slice().range(0..2).all().build()?;
    println!("top 2    {top2:?}"); // shape [2,4]

    // All rows, columns 1..3
    let cols = t.slice().all().range(1..3).build()?;
    println!("cols 1:3 {cols:?}"); // shape [3,2]

    // Single element -> scalar
    let elem = t.slice().index(1).index(2).build()?;
    assert!(elem.is_scalar());
    println!("t[1,2]   {elem:?}");

    Ok(())
}

examples/09_slice_str.rs (line 25)

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let t = Tensor::new((1..=12).map(|x| x as f64).collect(), &[3, 4]);

    println!("\"0, :\"    = {:?}", t.slice_str("0, :")?);
    println!("\"0:2, :\" = {:?}", t.slice_str("0:2, :")?);
    println!("\":, 1:3\" = {:?}", t.slice_str(":, 1:3")?);

    // Whitespace is ignored
    let a = t.slice_str("0:2, :")?;
    let b = t.slice_str(" 0:2 , : ")?;
    assert_eq!(a, b);
    println!("whitespace-insensitive: OK");

    // builder and slice_str agree
    let from_str = t.slice_str("0:2, :")?;
    let from_builder = t.slice().range(0..2).all().build()?;
    assert_eq!(from_str, from_builder);
    println!("builder == slice_str: OK");

    // Malformed specs never panic
    println!("bad spec: {:?}", t.slice_str("0::")); // Err

    Ok(())
}

examples/52_minmax_scaling.rs (line 26)

fn main() {
    let data = Tensor::new(
        vec![1.0, 10.0, 100.0, 2.0, 20.0, 200.0, 3.0, 30.0, 300.0],
        &[3, 3],
    );

    // Column min and max using axis reductions
    let col_min = data.min_axis(0);
    let col_max = data.max_axis(0);
    let range = &col_max - &col_min;

    // Broadcast: (data - min) / (max - min)
    let scaled = &(&data - &col_min) / ⦥

    println!("col_min  = {:?}", col_min.as_slice());
    println!("col_max  = {:?}", col_max.as_slice());
    println!("scaled shape = {:?}", scaled.shape());

    // First row should be all 0.0, last row all 1.0
    let row0 = scaled.slice().index(0).all().build().unwrap();
    let row2 = scaled.slice().index(2).all().build().unwrap();
    assert!(row0.as_slice().iter().all(|&v| (v - 0.0).abs() < 1e-10));
    assert!(row2.as_slice().iter().all(|&v| (v - 1.0).abs() < 1e-10));
    println!("Min-max scaling: OK");
}

Additional examples can be found in:

• examples/12_boundary_error_handling.rs