clawhdf5/crates/clawhdf5-netcdf4/src/model.rs

//! A file's groups, dimensions and variables, as netCDF-C reads them.
//!
//! netCDF-C (`libhdf5/hdf5open.c`, 4.9.3) reads a file in two passes, and
//! the names, order and sharing of the dimensions depend on both, so this
//! module replays them for the whole file at once:
//!
//! 1. `rec_read_metadata`: each group's links in creation order when the
//!    group tracks it, else in name order; a group's datasets and named
//!    datatypes before its subgroups, which follow in the same order. A
//!    dimension scale (`CLASS` `DIMENSION_SCALE`) defines a dimension with
//!    the id in its `_Netcdf4Dimid`, else the next free id (ids are
//!    file-wide), its first extent as length, unlimited when that axis is
//!    (or the length is 0); it is a variable too unless its `NAME` says it
//!    is only a dimension. Every other dataset is a variable, unless its
//!    type is one netCDF-C cannot represent ([`VarTypes::nc_type`]); a
//!    dataset `_nc4_non_coord_<name>` is the variable `<name>`.
//! 2. `rec_match_dimscales`, subgroups first, then the group's variables in
//!    order: a variable gets the dimensions whose ids its
//!    `_Netcdf4Coordinates` lists (looked up file-wide), else — when its
//!    `DIMENSION_LIST` attaches a scale to its first axis — the scales that
//!    list attaches, looked up in its group and then each parent, else
//!    "phony" dimensions (`create_phony_dims`): per axis, the first
//!    dimension of the variable's group of that length and unlimitedness
//!    not already used by an earlier axis of the variable, else a new one
//!    called `phony_dim_<id>`.
//!
//! An unlimited dimension's length is the largest extent, along it, of the
//! variables that use it in its group and the groups below
//! (`nc4_find_dim_len`).
//!
//! Where netCDF-C 4.9.3 leaves an axis without a dimension (an id or a scale
//! it cannot find, or an axis without a scale of a variable whose first
//! axis has one — there it reads uninitialised memory), netCDF4-python
//! cannot open the file; this crate gives such an axis a dimension by the
//! phony rule instead.

use std::collections::HashMap;

use clawhdf5::AttrValue;
use clawhdf5_format::datatype::{Datatype, DatatypeByteOrder};
use clawhdf5_format::object_header::{ObjectClass, ObjectHeader};

use crate::dimension::{self, Dimension};
use crate::error::Error;
use crate::types::NcType;
use crate::variable::Variable;

/// The prefix netCDF-C gives the dataset of a variable that has a
/// dimension's name but is not that dimension's coordinate variable (the
/// dimension's scale holds the name).
const NON_COORD_PREFIX: &str = "_nc4_non_coord_";

/// Groups read at most, a guard against files whose groups are hard-linked
/// into each other many times over (netCDF-C reads each link as its own
/// group).
const MAX_GROUPS: usize = 100_000;

/// A file as netCDF-C sees it.
#[derive(Debug)]
pub(crate) struct Model {
    /// Every group; the root is the first.
    groups: Vec<Group>,
    /// Every dimension, in the order they were created.
    dims: Vec<Dim>,
}

#[derive(Debug)]
struct Group {
    /// Object header address of the HDF5 group.
    address: u64,
    /// Its subgroups, `(name, index in Model::groups)`, in netCDF-C's order.
    children: Vec<(String, usize)>,
    parent: Option<usize>,
    /// The dimensions it defines (indexes in `Model::dims`), in creation
    /// order.
    dims: Vec<usize>,
    /// Its variables, in netCDF-C's order.
    vars: Vec<Var>,
}

#[derive(Debug)]
struct Dim {
    id: i64,
    name: String,
    /// The length it was created with (for an unlimited dimension, replaced
    /// by its current length once every variable has its dimensions).
    len: u64,
    unlimited: bool,
    /// Object header address of its dimension scale; `None` for a phony
    /// dimension.
    scale: Option<u64>,
}

#[derive(Debug)]
struct Var {
    /// The netCDF name.
    name: String,
    /// Whether its dataset is `_nc4_non_coord_<name>`.
    non_coord: bool,
    address: u64,
    nc_type: NcType,
    extent: Vec<u64>,
    /// Whether each axis is unlimited in the dataspace.
    unlimited: Vec<bool>,
    /// How netCDF-C finds its dimensions.
    source: DimSource,
    /// Its dimensions (indexes in `Model::dims`), one per axis, once found.
    dims: Vec<usize>,
}

#[derive(Debug)]
enum DimSource {
    /// A one-dimensional coordinate variable: its own scale's dimension.
    OwnScale(usize),
    /// The ids in `_Netcdf4Coordinates`; for a multi-dimensional coordinate
    /// variable, also its own dimension (for the first axis, should an id
    /// not be found).
    Coordinates(Vec<i64>, Option<usize>),
    /// The scale `DIMENSION_LIST` attaches to each axis (the first has one).
    Scales(Vec<Option<u64>>, Option<usize>),
    /// None: phony dimensions.
    Phony(Option<usize>),
}

impl Model {
    /// Read the metadata of `file` as netCDF-C does.
    pub fn build(file: &clawhdf5::File) -> Result<Self, Error> {
        let mut builder = Builder {
            file,
            model: Model {
                groups: Vec::new(),
                dims: Vec::new(),
            },
            next_id: 0,
            types: VarTypes::default(),
        };
        let root = file.superblock().root_group_address;
        builder.model.groups.push(Group {
            address: root,
            children: Vec::new(),
            parent: None,
            dims: Vec::new(),
            vars: Vec::new(),
        });
        builder.read_group(0, &mut vec![root])?;
        builder.match_dims(0);
        builder.unlimited_lengths();
        Ok(builder.model)
    }

    /// The group at `path` (`/`-separated names), from the group `from`.
    pub fn find_group(&self, from: usize, path: &str) -> Option<usize> {
        path.split('/')
            .filter(|p| !p.is_empty())
            .try_fold(from, |g, name| {
                self.groups[g]
                    .children
                    .iter()
                    .find(|(n, _)| n == name)
                    .map(|&(_, i)| i)
            })
    }

    /// The object header address of group `g`.
    pub fn group_address(&self, g: usize) -> u64 {
        self.groups[g].address
    }

    /// The names of group `g`'s subgroups, in netCDF-C's order.
    pub fn group_names(&self, g: usize) -> Vec<String> {
        self.groups[g]
            .children
            .iter()
            .map(|(n, _)| n.clone())
            .collect()
    }

    /// The dimensions group `g` defines, in id order (as `nc_inq_dimids`).
    pub fn dimensions(&self, g: usize) -> Vec<Dimension> {
        let mut dims: Vec<&Dim> = self.groups[g].dims.iter().map(|&d| &self.dims[d]).collect();
        dims.sort_by_key(|d| d.id);
        dims.into_iter().map(Dim::dimension).collect()
    }

    /// The names of group `g`'s variables, in netCDF-C's order.
    pub fn variable_names(&self, g: usize) -> Vec<String> {
        self.groups[g].vars.iter().map(|v| v.name.clone()).collect()
    }

    /// Group `g`'s variables, in netCDF-C's order.
    pub fn variables<'f>(
        &self,
        file: &'f clawhdf5::File,
        g: usize,
    ) -> Result<Vec<Variable<'f>>, Error> {
        self.groups[g]
            .vars
            .iter()
            .map(|v| self.open(file, v))
            .collect()
    }

    /// The variable `name` of group `g`; `name` may be a path (`"sub/var"`)
    /// relative to it. Of two variables of one name (datasets `<name>` and
    /// `_nc4_non_coord_<name>`), the second.
    pub fn variable<'f>(
        &self,
        file: &'f clawhdf5::File,
        g: usize,
        name: &str,
    ) -> Result<Variable<'f>, Error> {
        let not_found = || Error::VariableNotFound(name.to_string());
        let trimmed = name.trim_start_matches('/');
        let (g, leaf) = match trimmed.rsplit_once('/') {
            Some((dir, leaf)) => (self.find_group(g, dir).ok_or_else(not_found)?, leaf),
            None => (g, trimmed),
        };
        let vars = &self.groups[g].vars;
        let var = vars
            .iter()
            .find(|v| v.name == leaf && v.non_coord)
            .or_else(|| vars.iter().find(|v| v.name == leaf))
            .ok_or_else(not_found)?;
        self.open(file, var)
    }

    fn open<'f>(&self, file: &'f clawhdf5::File, var: &Var) -> Result<Variable<'f>, Error> {
        let ds = file.dataset_at(var.address)?;
        let attrs = ds.attrs().unwrap_or_default();
        let dims = var.dims.iter().map(|&d| self.dims[d].dimension()).collect();
        Ok(Variable::new(
            var.name.clone(),
            ds,
            dims,
            attrs,
            var.nc_type,
        ))
    }
}

impl Dim {
    fn dimension(&self) -> Dimension {
        Dimension {
            name: self.name.clone(),
            size: self.len,
            is_unlimited: self.unlimited,
        }
    }
}

struct Builder<'f> {
    file: &'f clawhdf5::File,
    model: Model,
    /// netCDF-C's `next_dimid`.
    next_id: i64,
    types: VarTypes,
}

impl Builder<'_> {
    /// Pass 1 for group `g` and, after its own links, its subgroups.
    /// `ancestors` holds the addresses of the groups from the root to `g`,
    /// so that a group linked into itself is not read forever.
    fn read_group(&mut self, g: usize, ancestors: &mut Vec<u64>) -> Result<(), Error> {
        let address = self.model.groups[g].address;
        let sb = self.file.superblock();
        let mut subgroups = Vec::new();
        for (name, child) in ordered_entries(self.file, address)? {
            let Ok(header) =
                ObjectHeader::parse_in(self.file.storage(), child, sb.offset_size, sb.length_size)
            else {
                continue;
            };
            match header.object_class() {
                Some(ObjectClass::Dataset) => self.read_dataset(g, name, child),
                Some(ObjectClass::NamedDatatype) => {
                    if let Some(dt) = header_datatype(&header) {
                        self.types.named(&dt);
                    }
                }
                _ if is_group(&header) => subgroups.push((name, child)),
                _ => {}
            }
        }
        for (name, child) in subgroups {
            if ancestors.contains(&child) || self.model.groups.len() >= MAX_GROUPS {
                continue;
            }
            let index = self.model.groups.len();
            self.model.groups.push(Group {
                address: child,
                children: Vec::new(),
                parent: Some(g),
                dims: Vec::new(),
                vars: Vec::new(),
            });
            self.model.groups[g].children.push((name, index));
            ancestors.push(child);
            let read = self.read_group(index, ancestors);
            ancestors.pop();
            read?;
        }
        Ok(())
    }

    /// `read_dataset`: a dimension for a dimension scale, a variable for
    /// the rest. A dataset that cannot be opened is skipped.
    fn read_dataset(&mut self, g: usize, name: String, address: u64) {
        let Ok(ds) = self.file.dataset_at(address) else {
            return;
        };
        let attrs = ds.attrs().unwrap_or_default();
        let Ok(extent) = ds.shape() else {
            return;
        };
        let max = ds.max_dimensions().ok().flatten();
        let unlimited: Vec<bool> = (0..extent.len())
            .map(|i| matches!(&max, Some(m) if m.get(i) == Some(&u64::MAX)))
            .collect();

        let mut own = None;
        if dimension::is_dimension_scale(&attrs) && !extent.is_empty() {
            // read_scale
            let id = match dimension::get_dimid(&attrs) {
                Some(id) => {
                    if id >= self.next_id {
                        self.next_id = id.saturating_add(1);
                    }
                    id
                }
                None => self.take_id(),
            };
            let len = extent[0];
            own = Some(self.add_dim(
                g,
                Dim {
                    id,
                    name: name.clone(),
                    len,
                    unlimited: unlimited[0] || len == 0,
                    scale: Some(address),
                },
            ));
            if dimension::is_pure_dimension(&attrs) {
                return;
            }
        }

        // read_var: a type netCDF-C cannot represent drops the variable
        // (the dimension of a scale stays).
        let Some(nc_type) = ds
            .raw_datatype()
            .ok()
            .and_then(|dt| self.types.nc_type(&dt))
        else {
            return;
        };
        let rank = extent.len();
        let coordinates = coordinates(&attrs).filter(|ids| ids.len() == rank && rank > 0);
        let source = match (own, coordinates) {
            (Some(dim), _) if rank == 1 => DimSource::OwnScale(dim),
            (_, Some(ids)) => DimSource::Coordinates(ids, own),
            _ => match dimension::dimension_list(self.file, &attrs) {
                Some(scales)
                    if scales.len() == rank && scales.first().is_some_and(Option::is_some) =>
                {
                    DimSource::Scales(scales, own)
                }
                _ => DimSource::Phony(own),
            },
        };
        let (name, non_coord) = match name.strip_prefix(NON_COORD_PREFIX) {
            Some(rest) if !rest.is_empty() => (rest.to_string(), true),
            _ => (name, false),
        };
        self.model.groups[g].vars.push(Var {
            name,
            non_coord,
            address,
            nc_type,
            extent,
            unlimited,
            source,
            dims: Vec::new(),
        });
    }

    fn take_id(&mut self) -> i64 {
        let id = self.next_id;
        self.next_id = self.next_id.saturating_add(1);
        id
    }

    fn add_dim(&mut self, g: usize, dim: Dim) -> usize {
        let index = self.model.dims.len();
        self.model.dims.push(dim);
        self.model.groups[g].dims.push(index);
        index
    }

    /// Pass 2 (`rec_match_dimscales`): subgroups first, then the group's
    /// variables in order.
    fn match_dims(&mut self, g: usize) {
        let children: Vec<usize> = self.model.groups[g]
            .children
            .iter()
            .map(|&(_, c)| c)
            .collect();
        for child in children {
            self.match_dims(child);
        }
        for v in 0..self.model.groups[g].vars.len() {
            let var = &self.model.groups[g].vars[v];
            let rank = var.extent.len();
            let mut found: Vec<Option<usize>> = vec![None; rank];
            match &var.source {
                DimSource::OwnScale(dim) => found[0] = Some(*dim),
                DimSource::Coordinates(ids, own) => {
                    for (slot, id) in found.iter_mut().zip(ids) {
                        *slot = self.dim_by_id(*id);
                    }
                    if found[0].is_none() {
                        found[0] = *own;
                    }
                }
                DimSource::Scales(scales, own) => {
                    for (slot, scale) in found.iter_mut().zip(scales) {
                        *slot = scale.and_then(|s| self.dim_by_scale(g, s));
                    }
                    if found[0].is_none() {
                        found[0] = *own;
                    }
                }
                DimSource::Phony(own) => {
                    if rank > 0 {
                        found[0] = *own;
                    }
                }
            }
            let mut dims: Vec<usize> = Vec::with_capacity(rank);
            for (axis, found) in found.into_iter().enumerate() {
                let dim = match found {
                    Some(dim) => dim,
                    None => {
                        let var = &self.model.groups[g].vars[v];
                        let (len, unlimited) = (var.extent[axis], var.unlimited[axis]);
                        self.phony_dim(g, len, unlimited, &dims)
                    }
                };
                dims.push(dim);
            }
            self.model.groups[g].vars[v].dims = dims;
        }
    }

    /// The dimension with id `id`: the last one created with it
    /// (`nc4_find_dim` looks ids up in a file-wide table, where a later
    /// dimension of the same id replaces an earlier one).
    fn dim_by_id(&self, id: i64) -> Option<usize> {
        self.model.dims.iter().rposition(|d| d.id == id)
    }

    /// The dimension of the scale at `address`, in group `g` or the nearest
    /// parent that has it.
    fn dim_by_scale(&self, g: usize, address: u64) -> Option<usize> {
        let mut group = Some(g);
        while let Some(i) = group {
            let found = self.model.groups[i]
                .dims
                .iter()
                .copied()
                .find(|&d| self.model.dims[d].scale == Some(address));
            if found.is_some() {
                return found;
            }
            group = self.model.groups[i].parent;
        }
        None
    }

    /// `create_phony_dims` for one axis: the first dimension of group `g`
    /// of length `len` and unlimitedness `unlimited` that no earlier axis
    /// of the variable uses (`taken`), else a new `phony_dim_<id>`.
    fn phony_dim(&mut self, g: usize, len: u64, unlimited: bool, taken: &[usize]) -> usize {
        let dims = &self.model.dims;
        let existing = self.model.groups[g].dims.iter().copied().find(|&d| {
            let dim = &dims[d];
            dim.len == len
                && dim.unlimited == unlimited
                && !taken.iter().any(|&t| dims[t].id == dim.id)
        });
        if let Some(dim) = existing {
            return dim;
        }
        let id = self.take_id();
        self.add_dim(
            g,
            Dim {
                id,
                name: format!("phony_dim_{id}"),
                len,
                // `nc4_dim_list_add`: a length of 0 is NC_UNLIMITED.
                unlimited: unlimited || len == 0,
                scale: None,
            },
        )
    }

    /// Each unlimited dimension's length: the largest extent along it of
    /// the variables using it in its group and the groups below.
    fn unlimited_lengths(&mut self) {
        let mut owner = vec![0usize; self.model.dims.len()];
        for (g, group) in self.model.groups.iter().enumerate() {
            for &d in &group.dims {
                owner[d] = g;
            }
        }
        let mut lens = vec![0u64; self.model.dims.len()];
        for (g, group) in self.model.groups.iter().enumerate() {
            for var in &group.vars {
                for (&d, &e) in var.dims.iter().zip(&var.extent) {
                    if self.model.dims[d].unlimited && self.is_within(g, owner[d]) {
                        lens[d] = lens[d].max(e);
                    }
                }
            }
        }
        for (dim, len) in self.model.dims.iter_mut().zip(lens) {
            if dim.unlimited {
                dim.len = len;
            }
        }
    }

    /// Whether group `g` is `ancestor` or below it.
    fn is_within(&self, g: usize, ancestor: usize) -> bool {
        let mut group = Some(g);
        while let Some(i) = group {
            if i == ancestor {
                return true;
            }
            group = self.model.groups[i].parent;
        }
        false
    }
}

/// A group's entries in netCDF-C's order: creation order when the group
/// tracks it, else the byte order of the names.
fn ordered_entries(file: &clawhdf5::File, address: u64) -> Result<Vec<(String, u64)>, Error> {
    let mut entries = file.group_at(address).entries()?;
    let order = clawhdf5_format::group_v2::links_in_creation_order_in(
        file.storage(),
        file.superblock(),
        address,
    )
    .ok()
    .flatten();
    match order {
        Some(names) => {
            let position: HashMap<&str, usize> = names
                .iter()
                .enumerate()
                .map(|(i, n)| (n.as_str(), i))
                .collect();
            entries.sort_by_key(|(n, _)| position.get(n.as_str()).copied().unwrap_or(usize::MAX));
        }
        None => entries.sort_by(|a, b| a.0.as_bytes().cmp(b.0.as_bytes())),
    }
    Ok(entries)
}

fn is_group(header: &ObjectHeader) -> bool {
    use clawhdf5_format::message_type::MessageType;
    header.messages.iter().any(|m| {
        matches!(
            m.msg_type,
            MessageType::LinkInfo | MessageType::Link | MessageType::SymbolTable
        )
    })
}

/// The datatype a named datatype's header holds.
fn header_datatype(header: &ObjectHeader) -> Option<Datatype> {
    use clawhdf5_format::message_type::MessageType;
    let msg = header
        .messages
        .iter()
        .find(|m| m.msg_type == MessageType::Datatype)?;
    Datatype::parse_in_header(&msg.data, header.version)
        .ok()
        .map(|(dt, _)| dt)
}

/// A variable's `_Netcdf4Coordinates`: the id of the dimension of each
/// axis.
fn coordinates(attrs: &HashMap<String, AttrValue>) -> Option<Vec<i64>> {
    match attrs.get("_Netcdf4Coordinates")? {
        AttrValue::I64Array(ids) => Some(ids.clone()),
        AttrValue::I64(id) => Some(vec![*id]),
        AttrValue::U64Array(ids) => ids.iter().map(|&id| i64::try_from(id).ok()).collect(),
        AttrValue::U64(id) => Some(vec![i64::try_from(*id).ok()?]),
        _ => None,
    }
}

/// The user-defined types netCDF-C has read so far, and the netCDF type of
/// a dataset.
///
/// netCDF-C keeps every type `read_type` meets in a file-wide list and
/// finds one again by `H5Tequal` on the native types — also a type it
/// failed to read: `read_type` adds the type (with its class, for a
/// compound, enum, variable-length or opaque type) before it looks at the
/// members or base type, and does not remove it when one of those fails.
/// So a dataset of a type netCDF-C skipped once becomes a variable the
/// second time (a compound with a reference member, say), and a compound
/// member of a type it skipped (a bit field) is accepted. This replays
/// that, except that a dataset whose skipped type has no class (a bit
/// field, time, array or complex type) stays hidden: netCDF-C lists the
/// second such dataset with an invalid type (class 0).
#[derive(Debug, Default)]
pub(crate) struct VarTypes {
    /// Every type read, with its class when it has one netCDF knows.
    known: Vec<(Datatype, Option<NcType>)>,
}

impl VarTypes {
    /// The netCDF type netCDF-C gives a dataset of type `dt`
    /// (`get_type_info2`), or `None` when it skips the dataset
    /// (`NC_EBADTYPID`): a reference, bit field, time or array type, a
    /// compound with a member, or an enum or variable-length type with a
    /// base type, that is not a netCDF atomic type or a type read before
    /// (see the type docs).
    ///
    /// Floats other than 4 and 8 bytes (half floats, bfloat16, the 4-, 6-
    /// and 8-bit floats, `long double`) are `Float` (up to 4 bytes) and
    /// `Double` here; netCDF-C 4.9.3 on libhdf5 1.14.6 labels them
    /// `NC_STRING` (their native type matches none of its own).
    pub fn nc_type(&mut self, dt: &Datatype) -> Option<NcType> {
        match dt {
            Datatype::FixedPoint { size, signed, .. } => int_type(*size, *signed),
            Datatype::FloatingPoint { size, .. } => Some(if *size <= 4 {
                NcType::Float
            } else {
                NcType::Double
            }),
            Datatype::String { size, .. } => Some(if *size > 1 {
                NcType::String
            } else {
                NcType::Char
            }),
            Datatype::VariableLength {
                is_string: true, ..
            } => Some(NcType::String),
            _ => match self.find(dt) {
                Some(class) => class,
                None => self.read_type(dt),
            },
        }
    }

    /// A named datatype of the file (`read_type` on a committed type).
    pub fn named(&mut self, dt: &Datatype) {
        if self.find(dt).is_none() {
            self.read_type(dt);
        }
    }

    /// The type read before that is `dt`, by its class.
    fn find(&self, dt: &Datatype) -> Option<Option<NcType>> {
        self.known
            .iter()
            .find(|(k, _)| native_eq(k, dt))
            .map(|&(_, class)| class)
    }

    /// `read_type`: remember `dt` (not a reference type), then its class if
    /// netCDF-C can represent its members or base type.
    fn read_type(&mut self, dt: &Datatype) -> Option<NcType> {
        let class = match dt {
            Datatype::Reference { .. } => return None,
            Datatype::Compound { .. } => Some(NcType::Compound),
            Datatype::VariableLength { .. } => Some(NcType::VLen),
            Datatype::Opaque { .. } => Some(NcType::Opaque),
            Datatype::Enumeration { .. } => Some(NcType::Enum),
            _ => None,
        };
        self.known.push((dt.clone(), class));
        let parts_ok = match dt {
            Datatype::Compound { members, .. } => members.iter().all(|m| match &m.datatype {
                Datatype::Array { base_type, .. } => self.is_member_type(base_type),
                other => self.is_member_type(other),
            }),
            Datatype::VariableLength { base_type, .. }
            | Datatype::Enumeration { base_type, .. } => self.is_member_type(base_type),
            _ => true,
        };
        class.filter(|_| parts_ok)
    }

    /// `get_netcdf_type`: whether netCDF-C takes `dt` as the type of a
    /// compound member or the base of an enum or variable-length type — an
    /// atomic type (4- and 8-byte floats only) or a type read before.
    fn is_member_type(&self, dt: &Datatype) -> bool {
        match dt {
            Datatype::FixedPoint { size, signed, .. } => int_type(*size, *signed).is_some(),
            Datatype::FloatingPoint { size: 4 | 8, .. }
            | Datatype::String { .. }
            | Datatype::VariableLength {
                is_string: true, ..
            } => true,
            _ => self.find(dt).is_some(),
        }
    }
}

/// The netCDF integer type of an HDF5 integer: the native integer libhdf5
/// converts it to (`H5Tget_native_type`: the smallest at least as wide).
fn int_type(size: u32, signed: bool) -> Option<NcType> {
    Some(match (size, signed) {
        (1, true) => NcType::Byte,
        (1, false) => NcType::UByte,
        (2, true) => NcType::Short,
        (2, false) => NcType::UShort,
        (3..=4, true) => NcType::Int,
        (3..=4, false) => NcType::UInt,
        (5..=8, true) => NcType::Int64,
        (5..=8, false) => NcType::UInt64,
        _ => return None,
    })
}

/// Whether two datatypes have the same native type (`H5Tequal` after
/// `H5Tget_native_type`): byte order, padding and compound member offsets
/// do not count.
fn native_eq(a: &Datatype, b: &Datatype) -> bool {
    use Datatype as D;
    match (a, b) {
        (
            D::FixedPoint {
                size: s1,
                signed: g1,
                ..
            },
            D::FixedPoint {
                size: s2,
                signed: g2,
                ..
            },
        ) => g1 == g2 && int_type(*s1, *g1) == int_type(*s2, *g2),
        (D::FloatingPoint { size: s1, .. }, D::FloatingPoint { size: s2, .. }) => s1 == s2,
        (
            D::String {
                size: s1,
                padding: p1,
                charset: c1,
            },
            D::String {
                size: s2,
                padding: p2,
                charset: c2,
            },
        ) => s1 == s2 && p1 == p2 && c1 == c2,
        (
            D::VariableLength {
                is_string: i1,
                base_type: b1,
                charset: c1,
                ..
            },
            D::VariableLength {
                is_string: i2,
                base_type: b2,
                charset: c2,
                ..
            },
        ) => i1 == i2 && if *i1 { c1 == c2 } else { native_eq(b1, b2) },
        (D::Compound { members: m1, .. }, D::Compound { members: m2, .. }) => {
            m1.len() == m2.len()
                && m1
                    .iter()
                    .zip(m2)
                    .all(|(x, y)| x.name == y.name && native_eq(&x.datatype, &y.datatype))
        }
        (
            D::Enumeration {
                base_type: b1,
                members: m1,
                ..
            },
            D::Enumeration {
                base_type: b2,
                members: m2,
                ..
            },
        ) => {
            native_eq(b1, b2)
                && m1.len() == m2.len()
                && m1.iter().zip(m2).all(|(x, y)| {
                    x.name == y.name && enum_value(&x.value, b1) == enum_value(&y.value, b2)
                })
        }
        (D::Opaque { size: s1, tag: t1 }, D::Opaque { size: s2, tag: t2 }) => s1 == s2 && t1 == t2,
        (
            D::Array {
                base_type: b1,
                dimensions: d1,
            },
            D::Array {
                base_type: b2,
                dimensions: d2,
            },
        ) => d1 == d2 && native_eq(b1, b2),
        (
            D::Reference {
                size: s1,
                ref_type: r1,
            },
            D::Reference {
                size: s2,
                ref_type: r2,
            },
        ) => s1 == s2 && r1 == r2,
        (D::BitField { size: s1, .. }, D::BitField { size: s2, .. })
        | (D::Time { size: s1, .. }, D::Time { size: s2, .. }) => s1 == s2,
        (
            D::Complex {
                size: s1,
                base_type: b1,
            },
            D::Complex {
                size: s2,
                base_type: b2,
            },
        ) => s1 == s2 && native_eq(b1, b2),
        _ => false,
    }
}

/// An enum member's value, in the order of its base type's bytes.
fn enum_value(value: &[u8], base: &Datatype) -> Vec<u8> {
    let big = matches!(
        base,
        Datatype::FixedPoint {
            byte_order: DatatypeByteOrder::BigEndian,
            ..
        }
    );
    let mut v = value.to_vec();
    if big {
        v.reverse();
    }
    v
}