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Reject a user-defined dtype in from_networkx #647

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20 changes: 15 additions & 5 deletions graphblas/io/_networkx.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,8 +12,9 @@ def from_networkx(G, nodelist=None, dtype=None, weight="weight", name=None):
Graph to convert
nodelist : list, optional
List of nodes in the nx.Graph. If not provided, all nodes will be used.
dtype :
Data type
dtype : optional
A built-in data type (bool, int, float or complex). If not provided, it
is inferred from the weights.
weight : str, default="weight"
Weight attribute
name : str, optional
Expand All @@ -29,13 +30,22 @@ def from_networkx(G, nodelist=None, dtype=None, weight="weight", name=None):
If the graph has no nodes, or ``nodelist`` is empty, repeats a node, or
names one the graph does not have (as ``nx.to_scipy_sparse_array`` does).
ValueError
If a weight is not a bool, int (at most 64 bits), float or complex scalar.
If a weight is not a bool, int (at most 64 bits), float or complex scalar,
or ``dtype`` is a user-defined type.

"""
import networkx as nx

if dtype is not None:
dtype = lookup_dtype(dtype).np_type
dtype = lookup_dtype(dtype)
if dtype._is_udt:
# numpy reads the weights as the fields or elements of one value of
# the type, which built a matrix of the type's base dtype for some edge
# counts and raised unrelated errors for others (through scipy too).
raise ValueError(
f"dtype must be a built-in bool, int, float or complex type, not the UDT {dtype}"
)
dtype = dtype.np_type

# The node selection below mirrors nx.to_scipy_sparse_array so that empty
# graphs, nodelist subsets, missing nodes, and duplicate nodes raise the
Expand Down Expand Up @@ -68,7 +78,7 @@ def from_networkx(G, nodelist=None, dtype=None, weight="weight", name=None):
G = G.subgraph(nodelist)

index = dict(zip(nodelist, range(nlen), strict=True))
if weight is None and not G.is_multigraph() and (dtype is None or dtype.kind in "biufc"):
if weight is None and not G.is_multigraph():
# Every entry is 1, so read only the coordinates: row by row in nodelist
# order, straight from the adjacency, which for an undirected graph already
# holds both directions and each self-loop once. No tuple and no value per
Expand Down
18 changes: 18 additions & 0 deletions graphblas/tests/test_io.py
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Original file line number Diff line number Diff line change
Expand Up @@ -292,6 +292,24 @@ def test_from_networkx_structure_matches_the_general_path(graph_cls, dtype):
gb.io.from_networkx(G, nodelist=["a", "missing"], weight=None)


@pytest.mark.skipif("not nx")
@pytest.mark.parametrize("weight", [None, "weight"])
@pytest.mark.parametrize("nedges", [1, 2, 3])
@pytest.mark.parametrize("dtype", ["record", "FP64[2]", "INT64[3]"])
def test_from_networkx_rejects_udt_dtype(weight, nedges, dtype):
# numpy read the weights as the fields or elements of one UDT value, so a type
# whose element count matched the number of weights came back as its base
# dtype (FP64[2] with two edges gave FP64), and other counts raised unrelated
# numpy errors.
if dtype == "record":
dtype = dtypes.register_anonymous(
np.dtype([("from_networkx_x", np.int64), ("from_networkx_y", np.float64)])
)
G = nx.path_graph(nedges + 1)
with pytest.raises(ValueError, match="not the UDT"):
gb.io.from_networkx(G, weight=weight, dtype=dtype)


@pytest.mark.skipif("not nx")
@pytest.mark.parametrize("wt", [np.inf, -np.inf, 1e308])
def test_from_networkx_undirected_selfloop_keeps_its_weight(wt):
Expand Down
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