Most problems fixed (except: recording from subgroups, changing dt fo…

…r spikequeue)

brian2/groups/poissongroup.py

@@ -31,10 +31,10 @@ class PoissonGroup(Group, SpikeSource):
     add_to_magic_network = True
 
     @check_units(rates=Hz)
-    def __init__(self, N, rates, clock=None, name='poissongroup*',
-                 codeobj_class=None):
+    def __init__(self, N, rates, dt=None, when='thresholds', order=0,
+                 name='poissongroup*', codeobj_class=None):
 
-        Group.__init__(self, when=clock, name=name)
+        Group.__init__(self, dt=dt, when=when, order=order, name=name)
 
         self.codeobj_class = codeobj_class
 

brian2/tests/test_base.py

@@ -20,9 +20,7 @@ def test_base():
     x.contained_objects.append(y)
     assert_equal(len(x.contained_objects), 1)
     assert x.contained_objects[0] is y
-
-    assert x.clock is defaultclock
-
+
     assert_equal(x.active, True)
     assert_equal(y.active, True)
     y.active = False

brian2/tests/test_functions.py

@@ -40,6 +40,7 @@ def test_math_functions():
     Test that math functions give the same result, regardless of whether used
     directly or in generated Python or C++ code.
     '''
+    default_dt = brian_prefs.core.default_dt
     test_array = np.array([-1, -0.5, 0, 0.5, 1])
 
     with catch_logs() as _:  # Let's suppress warnings about illegal values        
@@ -68,7 +69,7 @@ def test_math_functions():
                 G.variable = test_array
                 mon = StateMonitor(G, 'func', record=True)
                 net = Network(G, mon)
-                net.run(clock.dt)
+                net.run(default_dt)
 
                 assert_allclose(numpy_result, mon.func_.flatten(),
                                 err_msg='Function %s did not return the correct values' % func.__name__)
@@ -84,16 +85,14 @@ def test_math_functions():
 
                 # Calculate the result in a somewhat complicated way by using a
                 # subexpression in a NeuronGroup
-                clock = Clock()
                 G = NeuronGroup(len(test_array),
                                 '''func = variable {op} scalar : 1
                                    variable : 1'''.format(op=operator),
-                                   clock=clock,
                                    codeobj_class=codeobj_class)
                 G.variable = test_array
                 mon = StateMonitor(G, 'func', record=True)
                 net = Network(G, mon)
-                net.run(clock.dt)
+                net.run(default_dt)
 
                 assert_allclose(numpy_result, mon.func_.flatten(),
                                 err_msg='Function %s did not return the correct values' % func.__name__)