Fix for a problem with anisotropic extracellular diffusion, found by @…

…alexsavulescu. (#946)

share/lib/python/neuron/rxd/species.py

@@ -1225,7 +1225,9 @@ def __init__(self, regions=None, d=0, name=None, charge=0, initial=None, atolsca
             else:
                 from .rxd import _domain_lookup
                 reglist = regions if hasattr(regions,'__len__') else [regions]
-                dims = [_domain_lookup(sec) for reg in reglist for sec in reg.secs]
+                dims = [_domain_lookup(sec) for reg in reglist 
+                            if not isinstance(reg, region.Extracellular)
+                            for sec in reg.secs]
                 if not all([dim == dims[0] for dim in dims]):
                     raise RxDException('Hybrid 1D/3D diffusion does not currently support anisotropy or inhomogeneous grids. For separate 1D and 3D diffusion please create separate regions and species for 3D and 1D sections') 
                 else:

test/rxd/ecs/test_ecs_pure_diffusion.py

@@ -5,7 +5,7 @@
 @pytest.fixture
 def ecs_diffusion(neuron_instance):
     h, rxd, data, save_path = neuron_instance
-    def make_model(nx, ny, nz, alpha, lambd):
+    def make_model(nx, ny, nz, alpha, lambd, d=1.0):
         dx = 10
         # the extracellular space
         ecs = rxd.Extracellular(
@@ -15,7 +15,7 @@ def make_model(nx, ny, nz, alpha, lambd):
         )
 
         # Who?
-        k = rxd.Species([ecs], name='k', d=1.0, charge=1,
+        k = rxd.Species([ecs], name='k', d=d, charge=1,
                         initial=lambda nd: 1 if nd.x3d**2 + nd.y3d**2 + nd.z3d**2 < (2*dx)**2 else 0)
 
         model = (ecs, k)
@@ -212,3 +212,27 @@ def test_ecs_diffusion_0d_cvode_alpha(ecs_diffusion):
     if not save_path:
         assert k[ecs].states3d[0] == 1.0
 
+
+def test_ecs_diffusion_anisotropic(ecs_diffusion):
+    neuron_instance, make_model = ecs_diffusion
+    model = make_model(11, 11, 11, 0.2, 1.6, d=(0.25,0.5,1.0))
+    h, rxd, data, save_path = neuron_instance
+    h.CVode().active(True)
+    h.finitialize(1000)
+    h.continuerun(10)
+    if not save_path:
+        max_err = compare_data(data)
+        assert max_err < tol
+
+def test_ecs_diffusion_cvode_anisotropic(ecs_diffusion):
+    neuron_instance, make_model = ecs_diffusion
+    model = make_model(11, 11, 11, 0.2, 1.6, d=(0.25,0.5,1.0))
+    h, rxd, data, save_path = neuron_instance
+    h.finitialize(1000)
+    h.continuerun(10)
+    if not save_path:
+        max_err = compare_data(data)
+        assert max_err < tol
+
+
+