tetration 0.1.9

Chunked tensor .tet format, tet CLI, and optional C ABI (tetration-ffi)
Documentation 
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//! Resolve operation axis labels (dimension names → decimal indices) using footer metadata.

use std::collections::BTreeMap;

use crate::catalog::DatasetMetadataV1;
use crate::query::types::{Operation, QueryDocument, TetError};

/// True when `label` is a non-negative decimal axis index (`"0"`, `"12"`, …).
#[must_use]
pub(crate) fn is_decimal_axis_label(label: &str) -> bool {
    !label.is_empty() && label.chars().all(|c| c.is_ascii_digit())
}

/// True when `label` is a dimension **name** token (Phase 9); resolved against `dim_names` at plan time.
#[must_use]
pub(crate) fn is_dimension_name_label(label: &str) -> bool {
    let Some(first) = label.chars().next() else {
        return false;
    };
    (first.is_ascii_alphabetic() || first == '_')
        && label
            .chars()
            .all(|c| c.is_ascii_alphanumeric() || c == '_' || c == '-')
}

/// Parse-time check: axis label is either a decimal index or a dimension name pending resolution.
pub(crate) fn validate_axis_label_token(label: &str) -> Result<(), TetError> {
    if is_decimal_axis_label(label) || is_dimension_name_label(label) {
        return Ok(());
    }
    Err(TetError::Validation(format!(
        "invalid axis label {label:?} (use a non-negative decimal index or a dimension name)"
    )))
}

/// Replace dimension names in [`QueryDocument::operation`] with decimal indices using footer `dim_names`.
///
/// # Errors
///
/// [`TetError::Validation`] when a name is unknown, `dim_names` is missing, or rank does not match.
pub(crate) fn resolve_query_document_axes(
    doc: &mut QueryDocument,
    dataset_meta: Option<&DatasetMetadataV1>,
    ndim: usize,
) -> Result<(), TetError> {
    let Some(op) = doc.operation.as_mut() else {
        return Ok(());
    };
    let dim_names = dataset_meta.and_then(|m| m.dim_names.as_deref());
    resolve_operation_axes(op, dim_names, ndim)?;
    if let Some(attrs) = dataset_meta.map(|m| &m.attrs) {
        resolve_null_count_fill(op, attrs)?;
    } else {
        resolve_null_count_fill(op, &BTreeMap::new())?;
    }
    Ok(())
}

/// Fill [`Operation::NullCount::fill`] from query JSON or dataset attrs (`_FillValue`, …).
pub(crate) fn resolve_null_count_fill(
    op: &mut Operation,
    attrs: &BTreeMap<String, String>,
) -> Result<(), TetError> {
    let Operation::NullCount { fill, .. } = op else {
        return Ok(());
    };
    if fill.is_some() {
        return Ok(());
    }
    for key in ["_FillValue", "missing_value", "fill_value"] {
        if let Some(raw) = attrs.get(key) {
            *fill = Some(parse_fill_attr(raw)?);
            return Ok(());
        }
    }
    Err(TetError::Validation(
        "null_count requires `fill` in the query or dataset attr (_FillValue, missing_value, fill_value)".into(),
    ))
}

fn parse_fill_attr(raw: &str) -> Result<f64, TetError> {
    let trimmed = raw.trim();
    if trimmed.eq_ignore_ascii_case("nan") {
        return Ok(f64::NAN);
    }
    trimmed
        .parse::<f64>()
        .map_err(|_| TetError::Validation(format!("invalid fill value {raw:?}")))
}

fn resolve_operation_axes(
    op: &mut Operation,
    dim_names: Option<&[String]>,
    ndim: usize,
) -> Result<(), TetError> {
    for label in op.axes_mut() {
        *label = resolve_one_axis_label(label, dim_names, ndim)?;
    }
    Ok(())
}

fn resolve_one_axis_label(
    label: &str,
    dim_names: Option<&[String]>,
    ndim: usize,
) -> Result<String, TetError> {
    if is_decimal_axis_label(label) {
        let v: usize = label
            .parse()
            .map_err(|_| TetError::Validation(format!("invalid axis index {label:?}")))?;
        if v >= ndim {
            return Err(TetError::Validation(format!(
                "operation axis index {v} out of range for rank {ndim}"
            )));
        }
        return Ok(label.to_owned());
    }
    if !is_dimension_name_label(label) {
        return Err(TetError::Validation(format!(
            "invalid axis label {label:?}"
        )));
    }
    let names = dim_names.ok_or_else(|| {
        TetError::Validation(format!(
            "dimension name `{label}` requires footer metadata `dim_names` for this dataset"
        ))
    })?;
    if names.len() != ndim {
        return Err(TetError::Validation(format!(
            "metadata dim_names length {} does not match dataset rank {ndim}",
            names.len()
        )));
    }
    let mut matches = names
        .iter()
        .enumerate()
        .filter(|(_, n)| n.as_str() == label);
    let (idx, _) = matches.next().ok_or_else(|| {
        TetError::Validation(format!(
            "unknown dimension name `{label}` (dim_names: {})",
            names.join(", ")
        ))
    })?;
    if matches.next().is_some() {
        return Err(TetError::Validation(format!(
            "ambiguous dimension name `{label}` (duplicate dim_names entries)"
        )));
    }
    Ok(idx.to_string())
}