hdf5-reader 0.2.0

//! Integration tests for hdf5-reader against generated fixtures.
//!
//! These tests require the fixture files to be generated by running:
//!   cd testdata && python3 generate_fixtures.py
//!
//! Tests are skipped at runtime if fixture files are missing.

use std::path::Path;

fn fixture_path(name: &str) -> Option<std::path::PathBuf> {
    let base = Path::new(env!("CARGO_MANIFEST_DIR"))
        .parent()
        .unwrap()
        .join("testdata/hdf5");
    let path = base.join(name);
    if path.exists() {
        Some(path)
    } else {
        None
    }
}

macro_rules! skip_if_missing {
    ($name:expr) => {
        match fixture_path($name) {
            Some(p) => p,
            None => {
                eprintln!("SKIPPED: fixture {} not found", $name);
                return;
            }
        }
    };
}

#[test]
fn test_simple_contiguous() {
    let path = skip_if_missing!("simple_contiguous.h5");
    let file = hdf5_reader::Hdf5File::open(&path).unwrap();

    let root = file.root_group().unwrap();
    let ds = root.dataset("data").unwrap();
    assert_eq!(ds.shape(), &[4, 5]);

    let data: ndarray::ArrayD<f64> = ds.read_array().unwrap();
    assert_eq!(data.shape(), &[4, 5]);
    // First row should be 0..5
    for i in 0..5 {
        assert!((data[[0, i]] - i as f64).abs() < 1e-10);
    }
}

#[test]
fn test_simple_chunked_deflate() {
    let path = skip_if_missing!("simple_chunked_deflate.h5");
    let file = hdf5_reader::Hdf5File::open(&path).unwrap();

    let ds = file.dataset("/temperature").unwrap();
    assert_eq!(ds.shape(), &[10, 20]);
    assert_eq!(ds.chunks().unwrap(), vec![5, 10]);

    let data: ndarray::ArrayD<f32> = ds.read_array().unwrap();
    assert_eq!(data.shape(), &[10, 20]);
    assert!((data[[0, 0]] - 0.0).abs() < 1e-6);
    assert!((data[[1, 0]] - 20.0).abs() < 1e-6);
}

#[cfg(feature = "rayon")]
#[test]
fn test_simple_chunked_deflate_parallel_matches_serial() {
    let path = skip_if_missing!("simple_chunked_deflate.h5");
    let file = hdf5_reader::Hdf5File::open(&path).unwrap();
    let ds = file.dataset("/temperature").unwrap();
    let pool = rayon::ThreadPoolBuilder::new()
        .num_threads(4)
        .build()
        .unwrap();

    let serial: ndarray::ArrayD<f32> = ds.read_array().unwrap();
    let parallel: ndarray::ArrayD<f32> = ds.read_array_in_pool(&pool).unwrap();

    assert_eq!(serial, parallel);
}

#[test]
fn test_nested_groups() {
    let path = skip_if_missing!("nested_groups.h5");
    let file = hdf5_reader::Hdf5File::open(&path).unwrap();

    let g1 = file.group("/group1").unwrap();
    let ds1: ndarray::ArrayD<i32> = g1.dataset("data").unwrap().read_array().unwrap();
    assert_eq!(ds1.as_slice().unwrap(), &[1, 2, 3]);

    let sg = file.group("/group1/subgroup").unwrap();
    let ds2: ndarray::ArrayD<i32> = sg.dataset("data").unwrap().read_array().unwrap();
    assert_eq!(ds2.as_slice().unwrap(), &[4, 5, 6]);

    let g2 = file.group("/group2").unwrap();
    let ds3: ndarray::ArrayD<i32> = g2.dataset("data").unwrap().read_array().unwrap();
    assert_eq!(ds3.as_slice().unwrap(), &[7, 8, 9]);
}

#[test]
fn test_string_attributes() {
    let path = skip_if_missing!("string_attrs.h5");
    let file = hdf5_reader::Hdf5File::open(&path).unwrap();

    let ds = file.dataset("/data").unwrap();
    let name = ds.attribute("name").unwrap();
    assert_eq!(name.read_string().unwrap(), "test_dataset");

    let scale = ds.attribute("scale_factor").unwrap();
    assert!((scale.read_scalar::<f64>().unwrap() - 1.5).abs() < 1e-10);

    let range = ds.attribute("valid_range").unwrap();
    assert_eq!(range.read_1d::<i32>().unwrap(), vec![0, 100]);
}

#[test]
fn test_scalar_dataset() {
    let path = skip_if_missing!("scalar_dataset.h5");
    let file = hdf5_reader::Hdf5File::open(&path).unwrap();

    let ds = file.dataset("/value").unwrap();
    assert_eq!(ds.shape(), &[]);

    let data: ndarray::ArrayD<f64> = ds.read_array().unwrap();
    assert_eq!(data.ndim(), 0);
    assert!((data[[]] - 42.0).abs() < 1e-10);
}

#[test]
fn test_old_format_v1() {
    let path = skip_if_missing!("old_format_v1.h5");
    let file = hdf5_reader::Hdf5File::open(&path).unwrap();

    let ds = file.dataset("/data").unwrap();
    assert_eq!(ds.shape(), &[4, 5]);

    let data: ndarray::ArrayD<f64> = ds.read_array().unwrap();
    assert_eq!(data.shape(), &[4, 5]);
}

#[test]
fn test_fill_value() {
    let path = skip_if_missing!("fill_value.h5");
    let file = hdf5_reader::Hdf5File::open(&path).unwrap();

    let ds = file.dataset("/sparse").unwrap();
    let data: ndarray::ArrayD<i32> = ds.read_array().unwrap();

    // Elements 0, 3, 7 were written; rest should be fill value 999
    assert_eq!(data[[0]], 0);
    assert_eq!(data[[1]], 999);
    assert_eq!(data[[2]], 999);
    assert_eq!(data[[3]], 3);
    assert_eq!(data[[4]], 999);
    assert_eq!(data[[7]], 7);
    assert_eq!(data[[9]], 999);
}

#[test]
fn test_fletcher32() {
    let path = skip_if_missing!("fletcher32.h5");
    let file = hdf5_reader::Hdf5File::open(&path).unwrap();

    let ds = file.dataset("/checked").unwrap();
    let data: ndarray::ArrayD<f32> = ds.read_array().unwrap();
    assert_eq!(data.shape(), &[4, 4]);
    // Identity matrix
    assert!((data[[0, 0]] - 1.0).abs() < 1e-6);
    assert!((data[[0, 1]] - 0.0).abs() < 1e-6);
    assert!((data[[1, 1]] - 1.0).abs() < 1e-6);
}

#[test]
fn test_dense_groups() {
    let path = skip_if_missing!("dense_groups.h5");
    let file = hdf5_reader::Hdf5File::open(&path).unwrap();

    let root = file.root_group().unwrap();
    let datasets = root.datasets().unwrap();
    assert!(
        datasets.len() >= 20,
        "expected at least 20 datasets, got {}",
        datasets.len()
    );

    // Read one of them
    let ds = root.dataset("ds_000").unwrap();
    let data: ndarray::ArrayD<i32> = ds.read_array().unwrap();
    assert_eq!(data.as_slice().unwrap(), &[0]);
}

#[test]
fn test_from_vec() {
    let path = skip_if_missing!("scalar_dataset.h5");
    let bytes = std::fs::read(&path).unwrap();
    let file = hdf5_reader::Hdf5File::from_vec(bytes).unwrap();
    let ds = file.dataset("/value").unwrap();
    let data: ndarray::ArrayD<f64> = ds.read_array().unwrap();
    assert!((data[[]] - 42.0).abs() < 1e-10);
}

#[test]
fn test_from_bytes_with_options() {
    let path = skip_if_missing!("scalar_dataset.h5");
    let bytes = std::fs::read(&path).unwrap();
    let file = hdf5_reader::Hdf5File::from_bytes_with_options(
        &bytes,
        hdf5_reader::OpenOptions {
            chunk_cache_bytes: 1024,
            chunk_cache_slots: 17,
            filter_registry: None,
        },
    )
    .unwrap();
    let ds = file.dataset("/value").unwrap();
    let data: ndarray::ArrayD<f64> = ds.read_array().unwrap();
    assert!((data[[]] - 42.0).abs() < 1e-10);
}

#[test]
fn test_header_cache_reuse() {
    let path = skip_if_missing!("nested_groups.h5");
    let file = hdf5_reader::Hdf5File::open(&path).unwrap();

    // Access the same group twice — should use the header cache
    let g1a = file.group("/group1").unwrap();
    let g1b = file.group("/group1").unwrap();
    assert_eq!(g1a.name(), g1b.name());
}

#[test]
fn test_fixed_array_chunked() {
    let path = skip_if_missing!("fixed_array_chunked.h5");
    let file = hdf5_reader::Hdf5File::open(&path).unwrap();

    let ds = file.dataset("/data").unwrap();
    assert_eq!(ds.shape(), &[6, 10]);

    let data: ndarray::ArrayD<f64> = ds.read_array().unwrap();
    assert_eq!(data.shape(), &[6, 10]);
    // Verify data: arange(60).reshape(6,10)
    for r in 0..6 {
        for c in 0..10 {
            let expected = (r * 10 + c) as f64;
            assert!(
                (data[[r, c]] - expected).abs() < 1e-10,
                "mismatch at [{},{}]: got {}, expected {}",
                r,
                c,
                data[[r, c]],
                expected
            );
        }
    }
}

#[test]
fn test_extensible_array_chunked() {
    let path = skip_if_missing!("extensible_array_chunked.h5");
    let file = hdf5_reader::Hdf5File::open(&path).unwrap();

    let ds = file.dataset("/data").unwrap();
    assert_eq!(ds.shape(), &[5, 8]);

    let data: ndarray::ArrayD<f64> = ds.read_array().unwrap();
    assert_eq!(data.shape(), &[5, 8]);
    // Verify data: arange(40).reshape(5,8)
    for r in 0..5 {
        for c in 0..8 {
            let expected = (r * 8 + c) as f64;
            assert!(
                (data[[r, c]] - expected).abs() < 1e-10,
                "mismatch at [{},{}]: got {}, expected {}",
                r,
                c,
                data[[r, c]],
                expected
            );
        }
    }
}

#[test]
fn test_vlen_string_dataset() {
    let path = skip_if_missing!("vlen_strings.h5");
    let file = hdf5_reader::Hdf5File::open(&path).unwrap();
    let ds = file.dataset("/labels").unwrap();

    let strings = ds.read_strings().unwrap();
    assert_eq!(strings, vec!["alpha", "beta", "gamma"]);

    let err = ds.read_string().unwrap_err();
    assert!(matches!(err, hdf5_reader::error::Error::InvalidData(_)));
}

#[test]
fn test_chunked_slice_single_index() {
    let path = skip_if_missing!("fixed_array_chunked.h5");
    let file = hdf5_reader::Hdf5File::open(&path).unwrap();

    let ds = file.dataset("/data").unwrap();

    // Select row 2 (should give [20, 21, 22, ..., 29])
    let selection = hdf5_reader::SliceInfo {
        selections: vec![
            hdf5_reader::SliceInfoElem::Index(2),
            hdf5_reader::SliceInfoElem::Slice {
                start: 0,
                end: u64::MAX,
                step: 1,
            },
        ],
    };
    let sliced: ndarray::ArrayD<f64> = ds.read_slice(&selection).unwrap();
    assert_eq!(sliced.shape(), &[10]);
    for c in 0..10 {
        let expected = (2 * 10 + c) as f64;
        assert!(
            (sliced[[c]] - expected).abs() < 1e-10,
            "mismatch at [{}]: got {}, expected {}",
            c,
            sliced[[c]],
            expected
        );
    }
}

#[test]
fn test_chunked_slice_range_with_step() {
    let path = skip_if_missing!("simple_chunked_deflate.h5");
    let file = hdf5_reader::Hdf5File::open(&path).unwrap();

    let ds = file.dataset("/temperature").unwrap();
    // Shape: [10, 20], select rows 0,2,4,6,8 and cols 0..10
    let selection = hdf5_reader::SliceInfo {
        selections: vec![
            hdf5_reader::SliceInfoElem::Slice {
                start: 0,
                end: 10,
                step: 2,
            },
            hdf5_reader::SliceInfoElem::Slice {
                start: 0,
                end: 10,
                step: 1,
            },
        ],
    };
    let sliced: ndarray::ArrayD<f32> = ds.read_slice(&selection).unwrap();
    assert_eq!(sliced.shape(), &[5, 10]);
    // Row 0 of result = dataset row 0: [0, 1, 2, ..., 9]
    for c in 0..10 {
        assert!((sliced[[0, c]] - c as f32).abs() < 1e-6);
    }
    // Row 1 of result = dataset row 2: [40, 41, 42, ..., 49]
    for c in 0..10 {
        assert!((sliced[[1, c]] - (40 + c) as f32).abs() < 1e-6);
    }
}

#[test]
fn test_chunked_slice_empty_range_is_empty() {
    let path = skip_if_missing!("simple_chunked_deflate.h5");
    let file = hdf5_reader::Hdf5File::open(&path).unwrap();

    let ds = file.dataset("/temperature").unwrap();
    let selection = hdf5_reader::SliceInfo {
        selections: vec![
            hdf5_reader::SliceInfoElem::Slice {
                start: 8,
                end: 4,
                step: 1,
            },
            hdf5_reader::SliceInfoElem::Slice {
                start: 0,
                end: 10,
                step: 1,
            },
        ],
    };

    let sliced: ndarray::ArrayD<f32> = ds.read_slice(&selection).unwrap();
    assert_eq!(sliced.shape(), &[0, 10]);
    assert_eq!(sliced.len(), 0);
}

#[test]
fn test_chunked_slice_start_out_of_bounds_errors() {
    let path = skip_if_missing!("simple_chunked_deflate.h5");
    let file = hdf5_reader::Hdf5File::open(&path).unwrap();

    let ds = file.dataset("/temperature").unwrap();
    let selection = hdf5_reader::SliceInfo {
        selections: vec![
            hdf5_reader::SliceInfoElem::Slice {
                start: 11,
                end: 12,
                step: 1,
            },
            hdf5_reader::SliceInfoElem::Slice {
                start: 0,
                end: 10,
                step: 1,
            },
        ],
    };

    let err = ds.read_slice::<f32>(&selection).unwrap_err();
    assert!(matches!(
        err,
        hdf5_reader::error::Error::SliceOutOfBounds {
            dim: 0,
            index: 11,
            size: 10
        }
    ));
}

#[test]
fn test_chunked_shuffle_deflate() {
    let path = skip_if_missing!("chunked_shuffle_deflate.h5");
    let file = hdf5_reader::Hdf5File::open(&path).unwrap();

    let ds = file.dataset("/values").unwrap();
    assert_eq!(ds.shape(), &[100, 100]);
    assert_eq!(ds.chunks().unwrap(), vec![10, 10]);

    let data: ndarray::ArrayD<f64> = ds.read_array().unwrap();
    assert_eq!(data.shape(), &[100, 100]);
    // Verify the data is finite (generated from np.random.randn with seed 42)
    assert!(data.iter().all(|v| v.is_finite()));
}

#[cfg(feature = "lz4")]
#[test]
fn test_chunked_lz4() {
    let path = skip_if_missing!("chunked_lz4.h5");
    let file = hdf5_reader::Hdf5File::open(&path).unwrap();

    let ds = file.dataset("/data").unwrap();
    assert_eq!(ds.shape(), &[10, 20]);

    let data: ndarray::ArrayD<f32> = ds.read_array().unwrap();
    assert_eq!(data.shape(), &[10, 20]);
    // Data is np.arange(200).reshape(10,20)
    assert!((data[[0, 0]] - 0.0).abs() < 1e-6);
    assert!((data[[0, 1]] - 1.0).abs() < 1e-6);
    assert!((data[[1, 0]] - 20.0).abs() < 1e-6);
    assert!((data[[9, 19]] - 199.0).abs() < 1e-6);
}

#[cfg(feature = "lz4")]
#[test]
fn test_chunked_lz4_compressed() {
    // This fixture has all-zero data that actually compresses with LZ4
    let path = skip_if_missing!("chunked_lz4_zeros.h5");
    let file = hdf5_reader::Hdf5File::open(&path).unwrap();

    let ds = file.dataset("/data").unwrap();
    let data: ndarray::ArrayD<f32> = ds.read_array().unwrap();
    assert_eq!(data.shape(), &[10, 20]);
    assert!(data.iter().all(|&v| v == 0.0));
}