feat: handle some more types

Author: ntamas

doc/NOTES.md

@@ -15,3 +15,6 @@
   name of the edge attribute storing the weights?
 
 - Shall we treat the `weight` edge attribute implicitly as edge weights?
+
+- Shall we allow dicts mapping vertex names to floats to be treated as a
+  `VERTEX_QTY` abstract type?

src/codegen/types.yaml

@@ -111,11 +111,20 @@ VERTEX_INDEX_PAIRS:
 VERTEX_SELECTOR:
   PY_TYPE: VertexSelector
   INCONV:
-    IN: "%C% = vertex_selector_to_igraph_vs_t(%I%, %C1%)"
+    IN: "%C% = vertex_selector_to_igraph_vs_t(%I%, %I1%)"
   DEFAULT:
     ALL: '"all"'
   CALL: "%C%.unwrap()"
 
+VERTEX_QTY:
+  PY_TYPE: Iterable[float]
+  PY_RETURN_TYPE: npt.NDArray[np_type_of_igraph_real_t]
+  INCONV:
+    IN: "%C% = vertex_qty_to_igraph_vector_t_view(%I%, %I1%)"
+    INOUT: "%C% = vertex_qty_to_igraph_vector_t(%I%, %I1%)"
+    OUT: "%C% = _Vector.create(0)"
+  OUTCONV: "%I% = igraph_vector_t_to_numpy_array(%C%)"
+
 EDGE:
   PY_TYPE: EdgeLike
   PY_RETURN_TYPE: int
@@ -134,7 +143,7 @@ EDGE_INDICES:
 EDGE_SELECTOR:
   PY_TYPE: EdgeSelector
   INCONV:
-    IN: "%C% = edge_selector_to_igraph_es_t(%I%, %C1%)"
+    IN: "%C% = edge_selector_to_igraph_es_t(%I%, %I1%)"
   DEFAULT:
     ALL: '"all"'
   CALL: "%C%.unwrap()"
@@ -143,8 +152,8 @@ EDGEWEIGHTS:
   PY_TYPE: Iterable[float]
   PY_RETURN_TYPE: npt.NDArray[np_type_of_igraph_real_t]
   INCONV:
-    IN: "%C% = edge_weights_to_igraph_vector_t_view(%I%)"
-    INOUT: "%C% = edge_weights_to_igraph_vector_t(%I%)"
+    IN: "%C% = edge_weights_to_igraph_vector_t_view(%I%, %I1%)"
+    INOUT: "%C% = edge_weights_to_igraph_vector_t(%I%, %I1%)"
     OUT: "%C% = _Vector.create(0)"
   OUTCONV: "%I% = igraph_vector_t_to_numpy_array(%C%)"
 
@@ -176,6 +185,11 @@ STAR_MODE:
   INCONV:
     IN: "%C% = c_int(%I%)"
 
+TRANSITIVITY_MODE:
+  PY_TYPE: TransitivityMode
+  INCONV:
+    IN: "%C% = c_int(%I%)"
+
 TREE_MODE:
   PY_TYPE: TreeMode
   INCONV:

src/igraph_ctypes/_internal/conversion.py

@@ -98,6 +98,8 @@
     "vertexlike_to_igraph_integer_t",
     "vertex_pairs_to_igraph_vector_int_t",
     "vertex_selector_to_igraph_vs_t",
+    "vertex_qty_to_igraph_vector_t",
+    "vertex_qty_to_igraph_vector_t_view",
 )
 
 
@@ -142,15 +144,15 @@ def edge_selector_to_igraph_es_t(
         return _EdgeSelector.create_with(igraph_es_1, index)
 
 
-def edge_weights_to_igraph_vector_t(weights: Iterable[float]) -> _Vector:
+def edge_weights_to_igraph_vector_t(weights: Iterable[float], graph: _Graph) -> _Vector:
     """Converts a Python iterable of floating-point numbers to a vector of
     edge weights.
     """
     return iterable_to_igraph_vector_t(weights)
 
 
 def edge_weights_to_igraph_vector_t_view(
-    weights: Optional[Iterable[float]],
+    weights: Optional[Iterable[float]], graph: _Graph
 ) -> Optional[_Vector]:
     """Converts a Python iterable of floating-point numbers to a vector of
     edge weights, possibly creating a shallow view if the input is an
@@ -159,7 +161,9 @@ def edge_weights_to_igraph_vector_t_view(
     When the input is `None`, the return value will also be `None`, which is
     interpreted by the C core of igraph as all edges having equal weight.
     """
-    return edge_weights_to_igraph_vector_t(weights) if weights is not None else None
+    return (
+        edge_weights_to_igraph_vector_t(weights, graph) if weights is not None else None
+    )
 
 
 def iterable_edge_indices_to_igraph_vector_int_t(
@@ -439,6 +443,28 @@ def vertex_selector_to_igraph_vs_t(
         return _VertexSelector.create_with(igraph_vs_1, index)
 
 
+def vertex_qty_to_igraph_vector_t(weights: Iterable[float], graph: _Graph) -> _Vector:
+    """Converts a Python iterable of floating-point numbers to a vector of
+    vertex-related quantities.
+    """
+    return iterable_to_igraph_vector_t(weights)
+
+
+def vertex_qty_to_igraph_vector_t_view(
+    weights: Optional[Iterable[float]], graph: _Graph
+) -> Optional[_Vector]:
+    """Converts a Python iterable of floating-point numbers to a vector of
+    vertex-related quantities, possibly creating a shallow view if the input is
+    an appropriate NumPy array.
+
+    When the input is `None`, the return value will also be `None`, which is
+    interpreted by the C core of igraph as all edges having equal weight.
+    """
+    return (
+        vertex_qty_to_igraph_vector_t(weights, graph) if weights is not None else None
+    )
+
+
 ################################################################################
 # Conversion from igraph data types to Python                                  #
 ################################################################################

src/igraph_ctypes/_internal/enums.py

@@ -7,6 +7,7 @@
     "MatrixStorage",
     "NeighborMode",
     "StarMode",
+    "TransitivityMode",
     "TreeMode",
     "VertexSequenceType",
     "WheelMode",
@@ -75,6 +76,13 @@ class StarMode(IntEnum):
     MUTUAL = 3
 
 
+class TransitivityMode(IntEnum):
+    """Python counterpart of an ``igraph_transitivity_mode_t`` enum."""
+
+    NAN = 0
+    ZERO = 1
+
+
 class TreeMode(IntEnum):
     """Python counterpart of an ``igraph_tree_mode_t`` enum."""