core: Fix type inference for tuple-index into ndarray

Fixes #420.

nac3core/src/typecheck/type_inferencer/mod.rs

@@ -1586,6 +1586,7 @@ impl<'a> Inferencer<'a> {
     fn infer_subscript_ndarray(
         &mut self,
         value: &ast::Expr<Option<Type>>,
+        slice: &ast::Expr<Option<Type>>,
         dummy_tvar: Type,
         ndims: Type,
     ) -> InferenceResult {
@@ -1604,48 +1605,66 @@ impl<'a> Inferencer<'a> {
 
         let ndims = values
             .iter()
-            .map(|ndim| match *ndim {
+            .map(|ndim| u64::try_from(ndim.clone()).map_err(|()| ndim.clone()))
-                SymbolValue::U64(v) => Ok(v),
+            .collect::<Result<Vec<_>, _>>()
-                SymbolValue::U32(v) => Ok(u64::from(v)),
+            .map_err(|val| {
-                SymbolValue::I32(v) => u64::try_from(v).map_err(|_| {
                 HashSet::from([format!(
-                        "Expected non-negative literal for ndarray.ndims, got {v}"
+                    "Expected non-negative literal for ndarray.ndims, got {}",
+                    i128::try_from(val).unwrap()
                 )])
-                }),
+            })?;
-                SymbolValue::I64(v) => u64::try_from(v).map_err(|_| {
-                    HashSet::from([format!(
-                        "Expected non-negative literal for ndarray.ndims, got {v}"
-                    )])
-                }),
-                _ => unreachable!(),
-            })
-            .collect::<Result<Vec<_>, _>>()?;
 
         assert!(!ndims.is_empty());
 
-        if ndims.len() == 1 && ndims[0] == 1 {
+        // The number of dimensions subscripted by the index expression.
-            // ndarray[T, Literal[1]] - Index always returns an object of type T
+        // Slicing a ndarray will yield the same number of dimensions, whereas indexing into a
+        // dimension will remove a dimension.
+        let subscripted_dims = match &slice.node {
+            ExprKind::Tuple { elts, .. } => elts.iter().fold(0, |acc, value_subexpr| {
+                if let ExprKind::Slice { .. } = &value_subexpr.node {
+                    acc
+                } else {
+                    acc + 1
+                }
+            }),
+
+            ExprKind::Slice { .. } => 0,
+            _ => 1,
+        };
+
+        if ndims.len() == 1 && ndims[0] - subscripted_dims == 0 {
+            // ndarray[T, Literal[1]] - Non-Slice index always returns an object of type T
 
             assert_ne!(ndims[0], 0);
 
             Ok(dummy_tvar)
         } else {
-            // ndarray[T, Literal[N]] where N != 1 - Index returns an object of type ndarray[T, Literal[N - 1]]
+            // Otherwise - Index returns an object of type ndarray[T, Literal[N - subscripted_dims]]
 
-            if ndims.iter().any(|v| *v == 0) {
+            // Disallow subscripting if any Literal value will subscript on an element
+            let new_ndims = ndims
+                .into_iter()
+                .map(|v| {
+                    let v = i128::from(v) - i128::from(subscripted_dims);
+                    u64::try_from(v)
+                })
+                .collect::<Result<Vec<_>, _>>()
+                .map_err(|_| {
+                    HashSet::from([format!(
+                        "Cannot subscript {} by {subscripted_dims} dimensions",
+                        self.unifier.stringify(value.custom.unwrap()),
+                    )])
+                })?;
+
+            if new_ndims.iter().any(|v| *v == 0) {
                 unimplemented!("Inference for ndarray subscript operator with Literal[0, ...] bound unimplemented")
             }
 
-            let ndims_min_one_ty = self.unifier.get_fresh_literal(
+            let ndims_ty = self
-                ndims.into_iter().map(|v| SymbolValue::U64(v - 1)).collect(),
+                .unifier
-                None,
+                .get_fresh_literal(new_ndims.into_iter().map(SymbolValue::U64).collect(), None);
-            );
+            let subscripted_ty =
-            let subscripted_ty = make_ndarray_ty(
+                make_ndarray_ty(self.unifier, self.primitives, Some(dummy_tvar), Some(ndims_ty));
-                self.unifier,
-                self.primitives,
-                Some(dummy_tvar),
-                Some(ndims_min_one_ty),
-            );
 
             Ok(subscripted_ty)
         }
@@ -1682,7 +1701,7 @@ impl<'a> Inferencer<'a> {
                     TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
                         let (_, ndims) =
                             unpack_ndarray_var_tys(self.unifier, value.custom.unwrap());
-                        self.infer_subscript_ndarray(value, ty, ndims)
+                        self.infer_subscript_ndarray(value, slice, ty, ndims)
                     }
                     _ => {
                         // the index is a constant, so value can be a sequence.
@@ -1725,10 +1744,7 @@ impl<'a> Inferencer<'a> {
                 }
 
                 let (_, ndims) = unpack_ndarray_var_tys(self.unifier, value.custom.unwrap());
-                let ndarray_ty =
+                self.infer_subscript_ndarray(value, slice, ty, ndims)
-                    make_ndarray_ty(self.unifier, self.primitives, Some(ty), Some(ndims));
-                self.constrain(value.custom.unwrap(), ndarray_ty, &value.location)?;
-                Ok(ndarray_ty)
             }
             _ => {
                 if let TypeEnum::TTuple { .. } = &*self.unifier.get_ty(value.custom.unwrap()) {
@@ -1763,7 +1779,7 @@ impl<'a> Inferencer<'a> {
                             .get_fresh_var_with_range(valid_index_tys.as_slice(), None, None)
                             .ty;
                         self.constrain(slice.custom.unwrap(), valid_index_ty, &slice.location)?;
-                        self.infer_subscript_ndarray(value, ty, ndims)
+                        self.infer_subscript_ndarray(value, slice, ty, ndims)
                     }
                     _ => unreachable!(),
                 }