Fix connections to single neurons

Multiplying an `n x 1` sparse matrix by a 1-vector was yielding
a vector rather than a matrix. Special-case this to ensure we get
a matrix back.

Fixes #274.

CHANGES.rst

@@ -127,6 +127,8 @@ Release history
   `#275 <https://github.com/nengo/nengo-loihi/pull/275>`__)
 - Fixed bug when probing sliced objects.
   (`#284 <https://github.com/nengo/nengo-loihi/pull/284>`__)
+- Fixed bug when connecting to a single neuron ensemble with a single scalar
+  weight. (`#287 <https://github.com/nengo/nengo-loihi/pull/287>`__)
 
 0.10.0 (November 25, 2019)
 ==========================

nengo_loihi/builder/sparse_matrix.py

@@ -28,6 +28,9 @@ def scale_matrix(matrix, scale):
         assert scale.size == matrix.shape[1]
         diag = scipy.sparse.dia_matrix((scale, 0), shape=(scale.size, scale.size))
         return matrix.dot(diag)
+    elif scale.size == 1:
+        # avoid bug where a sparse n x 1 matrix times a 1-vector gives a vector
+        return matrix * scale.item()
     else:
         return matrix * scale
 

nengo_loihi/tests/test_connection.py

@@ -785,3 +785,22 @@ def test_sparse_transforms_empty_neurons(Simulator):
     # only the first and third neurons should get input, not the second
     spikes = (sim.data[probe] > 0).sum(axis=0)
     assert np.array_equal(spikes > 0, [1, 0, 1])
+
+
+def test_single_neuron_connection(Simulator, allclose):
+    """Addresses https://github.com/nengo/nengo-loihi/issues/274"""
+
+    max_rate = 50.0
+    simtime = 0.4
+
+    with nengo.Network() as net:
+        inp = nengo.Node([1.0])
+        ens = nengo.Ensemble(1, 1, max_rates=[max_rate], intercepts=[-1.0])
+        nengo.Connection(inp, ens.neurons, synapse=None)
+        probe = nengo.Probe(ens.neurons)
+
+    with Simulator(net) as sim:
+        sim.run(simtime)
+
+    exp_rate = max_rate * simtime
+    assert allclose((sim.data[probe] > 0).sum(), exp_rate, rtol=0.1)