def test_state_variables():
'''
Test the setting and accessing of state variables.
'''
G = NeuronGroup(10, 'v : volt')
G.v = -70 * mV
assert_raises(DimensionMismatchError, lambda: G.__setattr__('v', -70))
G.v_ = float(-70 * mV)
# Numpy methods should be able to deal with state variables
# (discarding units)
assert_allclose(np.mean(G.v), float(-70 * mV))
# Getting the content should return a Quantity object which then natively
# supports numpy functions that access a method
assert_allclose(np.mean(G.v[:]), -70 * mV)
# You should also be able to set variables with a string
G.v = '-70*mV + i*mV'
assert_allclose(G.v[0], -70 * mV)
assert_allclose(G.v[9], -61 * mV)
assert_allclose(G.v[:], -70 * mV + np.arange(10) * mV)
# Calculating with state variables should work too
assert all(G.v - G.v == 0)
# And in-place modification should work as well
G.v += 10 * mV
G.v *= 2
# with unit checking
assert_raises(DimensionMismatchError, lambda: G.v.__iadd__(3 * second))
assert_raises(DimensionMismatchError, lambda: G.v.__iadd__(3))
assert_raises(DimensionMismatchError, lambda: G.v.__imul__(3 * second))
def test_state_variables():
'''
Test the setting and accessing of state variables.
'''
for codeobj_class in codeobj_classes:
G = NeuronGroup(10, 'v : volt', codeobj_class=codeobj_class)
# The variable N should be always present
assert G.N == 10
# But it should be read-only
assert_raises(TypeError, lambda: G.__setattr__('N', 20))
assert_raises(TypeError, lambda: G.__setattr__('N_', 20))
G.v = -70*mV
assert_raises(DimensionMismatchError, lambda: G.__setattr__('v', -70))
G.v_ = float(-70*mV)
assert_allclose(G.v[:], -70*mV)
G.v = -70*mV + np.arange(10)*mV
assert_allclose(G.v[:], -70*mV + np.arange(10)*mV)
G.v = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] * volt
assert_allclose(G.v[:], np.arange(10) * volt)
# incorrect size
assert_raises(ValueError, lambda: G.__setattr__('v', [0, 1]*volt))
assert_raises(ValueError, lambda: G.__setattr__('v', np.arange(11)*volt))
G.v = -70*mV
# Numpy methods should be able to deal with state variables
# (discarding units)
assert_allclose(np.mean(G.v), float(-70*mV))
# Getting the content should return a Quantity object which then natively
# supports numpy functions that access a method
assert_allclose(np.mean(G.v[:]), -70*mV)
# You should also be able to set variables with a string
G.v = '-70*mV + i*mV'
assert_allclose(G.v[0], -70*mV)
assert_allclose(G.v[9], -61*mV)
assert_allclose(G.v[:], -70*mV + np.arange(10)*mV)
# And it should raise an unit error if the units are incorrect
assert_raises(DimensionMismatchError,
lambda: G.__setattr__('v', '70 + i'))
assert_raises(DimensionMismatchError,
lambda: G.__setattr__('v', '70 + i*mV'))
# Calculating with state variables should work too
# With units
assert all(G.v - G.v == 0)
assert all(G.v - G.v[:] == 0*mV)
assert all(G.v[:] - G.v == 0*mV)
assert all(G.v + 70*mV == G.v[:] + 70*mV)
assert all(70*mV + G.v == G.v[:] + 70*mV)
assert all(G.v + G.v == 2*G.v)
assert all(G.v / 2.0 == 0.5*G.v)
assert all(1.0 / G.v == 1.0 / G.v[:])
assert_equal((-G.v)[:], -G.v[:])
assert_equal((+G.v)[:], G.v[:])
#Without units
assert all(G.v_ - G.v_ == 0)
assert all(G.v_ - G.v_[:] == 0)
assert all(G.v_[:] - G.v_ == 0)
assert all(G.v_ + float(70*mV) == G.v_[:] + float(70*mV))
assert all(float(70*mV) + G.v_ == G.v_[:] + float(70*mV))
assert all(G.v_ + G.v_ == 2*G.v_)
assert all(G.v_ / 2.0 == 0.5*G.v_)
assert all(1.0 / G.v_ == 1.0 / G.v_[:])
assert_equal((-G.v)[:], -G.v[:])
assert_equal((+G.v)[:], G.v[:])
# And in-place modification should work as well
G.v += 10*mV
G.v -= 10*mV
G.v *= 2
G.v /= 2.0
# with unit checking
assert_raises(DimensionMismatchError, lambda: G.v.__iadd__(3*second))
assert_raises(DimensionMismatchError, lambda: G.v.__iadd__(3))
assert_raises(DimensionMismatchError, lambda: G.v.__imul__(3*second))
# in-place modification with strings should not work
assert_raises(TypeError, lambda: G.v.__iadd__('string'))
assert_raises(TypeError, lambda: G.v.__imul__('string'))
assert_raises(TypeError, lambda: G.v.__idiv__('string'))
assert_raises(TypeError, lambda: G.v.__isub__('string'))