def testCreateTreeGF(self):
self.loadBall()
cm = CompartmentFitter(self.tree)
# create tree with only 'L'
tree_pas = cm.createTreeGF()
self._checkChannels(tree_pas, [])
# create tree with only 'Na_Ta'
tree_na = cm.createTreeGF(['Na_Ta'])
self._checkChannels(tree_na, ['Na_Ta'])
# create tree with only 'Kv3_1'
tree_k = cm.createTreeGF(['Kv3_1'])
self._checkChannels(tree_k, ['Kv3_1'])
# create tree with all channels
tree_all = cm.createTreeGF(['Na_Ta', 'Kv3_1'])
self._checkChannels(tree_all, ['Na_Ta', 'Kv3_1'])
def testRecalcImpedanceMatrix(self, g_inp=np.linspace(0., 0.01, 20)):
self.loadBall()
fit_locs = [(1, .5)]
cm = CompartmentFitter(self.tree)
cm.setCTree(fit_locs)
# test only leak
# compute impedances explicitly
greens_tree = cm.createTreeGF(channel_names=[])
greens_tree.setEEq(-75.)
greens_tree.setImpedancesInTree()
z_mat = greens_tree.calcImpedanceMatrix(fit_locs,
explicit_method=False)[0]
z_test = z_mat[:, :,
None] / (1. + z_mat[:, :, None] * g_inp[None, None, :])
# compute impedances with compartmentfitter function
z_calc = np.array([ \
cm.recalcImpedanceMatrix('fit locs', [g_i], \
channel_names=[]
) \
for g_i in g_inp \
])
z_calc = np.swapaxes(z_calc, 0, 2)
assert np.allclose(z_calc, z_test)
# test with z based on all channels (passive)
# compute impedances explicitly
greens_tree = cm.createTreeGF(
channel_names=list(cm.tree.channel_storage.keys()))
greens_tree.setEEq(-75.)
greens_tree.setImpedancesInTree()
z_mat = greens_tree.calcImpedanceMatrix(fit_locs,
explicit_method=False)[0]
z_test = z_mat[:, :,
None] / (1. + z_mat[:, :, None] * g_inp[None, None, :])
# compute impedances with compartmentfitter function
z_calc = np.array([ \
cm.recalcImpedanceMatrix('fit locs', [g_i], \
channel_names=list(cm.tree.channel_storage.keys())) \
for g_i in g_inp \
])
z_calc = np.swapaxes(z_calc, 0, 2)
assert np.allclose(z_calc, z_test)
def testSynRescale(self, g_inp=np.linspace(0., 0.01, 20)):
e_rev, v_eq = 0., -75.
self.loadBallAndStick()
fit_locs = [(4, .7)]
syn_locs = [(4, 1.)]
cm = CompartmentFitter(self.tree)
cm.setCTree(fit_locs)
# compute impedance matrix
greens_tree = cm.createTreeGF(channel_names=[])
greens_tree.setEEq(-75.)
greens_tree.setImpedancesInTree()
z_mat = greens_tree.calcImpedanceMatrix(fit_locs + syn_locs)[0]
# analytical synapse scale factors
beta_calc = 1. / (1. + (z_mat[1, 1] - z_mat[0, 0]) * g_inp)
beta_full = z_mat[0,1] / z_mat[0,0] * (e_rev - v_eq) / \
((1. + (z_mat[1,1] - z_mat[0,0]) * g_inp ) * (e_rev - v_eq))
# synapse scale factors from compartment fitter
beta_cm = np.array([cm.fitSynRescale(fit_locs, syn_locs, [0], [g_i], e_revs=[0.])[0] \
for g_i in g_inp])
assert np.allclose(beta_calc, beta_cm, atol=.020)
assert np.allclose(beta_full, beta_cm, atol=.015)