def testChannelFitMats(self):
self.loadBall()
cm = CompartmentFitter(self.tree)
cm.setCTree([(1, .5)])
# check if reversals are correct
for key in set(cm.ctree[0].currents) - {'L'}:
assert np.abs(cm.ctree[0].currents[key][1] - \
self.tree[1].currents[key][1]) < 1e-10
# fit the passive model
cm.fitPassive(use_all_channels=False)
fit_mats_cm_na = cm.evalChannel('Na_Ta', parallel=False)
fit_mats_cm_k = cm.evalChannel('Kv3_1', parallel=False)
fit_mats_control_na, fit_mats_control_k = self.reduceExplicit()
# test whether potassium fit matrices agree
for fm_cm, fm_control in zip(fit_mats_cm_k, fit_mats_control_k):
assert np.allclose(np.sum(fm_cm[0]),
fm_control[0][0, 0]) # feature matrices
assert np.allclose(fm_cm[1], fm_control[1]) # target vectors
# test whether sodium fit matrices agree
for fm_cm, fm_control in zip(fit_mats_cm_na[4:], fit_mats_control_na):
assert np.allclose(np.sum(fm_cm[0]),
fm_control[0][0, 0]) # feature matrices
assert np.allclose(fm_cm[1], fm_control[1]) # target vectors
def testPassiveFit(self):
self.loadTTree()
fit_locs = [(1, .5), (4, 1.), (5, .5), (8, .5)]
# fit a tree directly from CompartmentTree
greens_tree = self.tree.__copy__(new_tree=GreensTree())
greens_tree.setCompTree()
freqs = np.array([0.])
greens_tree.setImpedance(freqs)
z_mat = greens_tree.calcImpedanceMatrix(fit_locs)[0].real
ctree = greens_tree.createCompartmentTree(fit_locs)
ctree.computeGMC(z_mat)
sov_tree = self.tree.__copy__(new_tree=SOVTree())
sov_tree.calcSOVEquations()
alphas, phimat = sov_tree.getImportantModes(locarg=fit_locs)
ctree.computeC(-alphas[0:1].real * 1e3, phimat[0:1, :].real)
# fit a tree with compartment fitter
cm = CompartmentFitter(self.tree)
cm.setCTree(fit_locs)
cm.fitPassive()
cm.fitCapacitance()
cm.fitEEq()
# check whether both trees are the same
self._checkPasCondProps(ctree, cm.ctree)
self._checkPasCaProps(ctree, cm.ctree)
self._checkEL(cm.ctree, -75.)
# test whether all channels are used correctly for passive fit
self.loadBall()
fit_locs = [(1, .5)]
# fit ball model with only leak
greens_tree = self.tree.__copy__(new_tree=GreensTree())
greens_tree.channel_storage = {}
for n in greens_tree:
n.currents = {'L': n.currents['L']}
greens_tree.setCompTree()
freqs = np.array([0.])
greens_tree.setImpedance(freqs)
z_mat = greens_tree.calcImpedanceMatrix(fit_locs)[0].real
ctree_leak = greens_tree.createCompartmentTree(fit_locs)
ctree_leak.computeGMC(z_mat)
sov_tree = greens_tree.__copy__(new_tree=SOVTree())
sov_tree.calcSOVEquations()
alphas, phimat = sov_tree.getImportantModes(locarg=fit_locs)
ctree_leak.computeC(-alphas[0:1].real * 1e3, phimat[0:1, :].real)
# make ball model with leak based on all channels
tree = self.tree.__copy__()
tree.asPassiveMembrane()
greens_tree = tree.__copy__(new_tree=GreensTree())
greens_tree.setCompTree()
freqs = np.array([0.])
greens_tree.setImpedance(freqs)
z_mat = greens_tree.calcImpedanceMatrix(fit_locs)[0].real
ctree_all = greens_tree.createCompartmentTree(fit_locs)
ctree_all.computeGMC(z_mat)
sov_tree = tree.__copy__(new_tree=SOVTree())
sov_tree.calcSOVEquations()
alphas, phimat = sov_tree.getImportantModes(locarg=fit_locs)
ctree_all.computeC(-alphas[0:1].real * 1e3, phimat[0:1, :].real)
# new compartment fitter
cm = CompartmentFitter(self.tree)
cm.setCTree(fit_locs)
# test fitting
cm.fitPassive(use_all_channels=False)
cm.fitCapacitance()
cm.fitEEq()
self._checkPasCondProps(ctree_leak, cm.ctree)
self._checkPasCaProps(ctree_leak, cm.ctree)
with pytest.raises(AssertionError):
self._checkEL(cm.ctree, self.tree[1].currents['L'][1])
cm.fitPassive(use_all_channels=True)
cm.fitCapacitance()
cm.fitEEq()
self._checkPasCondProps(ctree_all, cm.ctree)
self._checkPasCaProps(ctree_all, cm.ctree)
self._checkEL(cm.ctree, greens_tree[1].currents['L'][1])
with pytest.raises(AssertionError):
self._checkEL(cm.ctree, self.tree[1].currents['L'][1])
with pytest.raises(AssertionError):
self._checkPasCondProps(ctree_leak, ctree_all)
