def createTree3(self, reinitialize=1, add_lin=True, v_eq=-75.):
"""
Create simple NET structure
6
4 5 |
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2 ---3--- |
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0------
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"""
self.v_eq = v_eq
# kernel constants
alphas = 1. / np.array([1.])
gammas = np.array([1.])
# nodes
node_0 = NETNode(0, [0, 1, 2, 3], [], z_kernel=(alphas, gammas))
node_1 = NETNode(1, [0, 1, 2], [], z_kernel=(alphas, gammas))
node_2 = NETNode(2, [0], [0], z_kernel=(alphas, gammas))
node_3 = NETNode(3, [1, 2], [], z_kernel=(alphas, gammas))
node_4 = NETNode(4, [1], [1], z_kernel=(alphas, gammas))
node_5 = NETNode(5, [2], [2], z_kernel=(alphas, gammas))
node_6 = NETNode(6, [3], [3], z_kernel=(alphas, gammas))
# add nodes to tree
net_py = NET()
net_py.setRoot(node_0)
net_py.addNodeWithParent(node_1, node_0)
net_py.addNodeWithParent(node_2, node_1)
net_py.addNodeWithParent(node_3, node_1)
net_py.addNodeWithParent(node_4, node_3)
net_py.addNodeWithParent(node_5, node_3)
net_py.addNodeWithParent(node_6, node_0)
# linear terms
alphas = 1. / np.array([1.])
gammas = np.array([1.])
self.lin_terms = {
1: Kernel((alphas, gammas)),
2: Kernel((alphas, gammas)),
3: Kernel((alphas, gammas))
} if add_lin else {}
# store
self.net_py = net_py
self.cnet = netsim.NETSim(net_py, lin_terms=self.lin_terms)
def testKernels(self):
# kernel 1
a1 = np.array([1., 10.])
c1 = np.array([2., 20.])
k1 = Kernel((a1, c1))
# kernel 2
a2 = np.array([1., 10.])
c2 = np.array([4., 40.])
k2 = Kernel({'a': a2, 'c': c2})
# kernel 3
k3 = Kernel(1.)
# kbar
assert np.abs(k1.k_bar - 4.) < 1e-12
assert np.abs(k2.k_bar - 8.) < 1e-12
assert np.abs(k3.k_bar - 1.) < 1e-12
# temporal kernel
t_arr = np.array([0., np.infty])
assert np.allclose(k1(t_arr), np.array([22., 0.]))
assert np.allclose(k2(t_arr), np.array([44., 0.]))
assert np.allclose(k3(t_arr), np.array([1., 0.]))
# frequency kernel
s_arr = np.array([0. * 1j, np.infty * 1j])
assert np.allclose(k1.ft(s_arr),
np.array([4. + 0j, np.nan * 1j]),
equal_nan=True)
assert np.allclose(k2.ft(s_arr),
np.array([8. + 0j, np.nan * 1j]),
equal_nan=True)
assert np.allclose(k3.ft(s_arr),
np.array([1. + 0j, np.nan * 1j]),
equal_nan=True)
# test addition
k4 = k1 + k2
assert np.abs(k4.k_bar - 12.) < 1e-12
assert len(k4.a) == 2
k5 = k1 + k3
assert np.abs(k5.k_bar - 5.) < 1e-12
assert len(k5.a) == 3
# test subtraction
k6 = k2 - k1
assert len(k6.a) == 2
assert np.allclose(k6.c, np.array([2., 20]))
assert np.abs(k6.k_bar - 4.) < 1e-12
k7 = k1 - k3
assert len(k7.a) == 3
assert np.allclose(k7.c, np.array([2., 20., -1.]))
assert np.abs(k7.k_bar - 3.) < 1e-12
def testNETDerivation(self):
# initialize
self.loadValidationTree()
self.tree.calcSOVEquations()
# construct the NET
net = self.tree.constructNET()
# initialize
self.loadTTree()
self.tree.calcSOVEquations()
# construct the NET
net = self.tree.constructNET(dz=20.)
# contruct the NET with linear terms
net, lin_terms = self.tree.constructNET(dz=20., add_lin_terms=True)
# check if correct
alphas, gammas = self.tree.getImportantModes(locarg='net eval',
eps=1e-4, sort_type='timescale')
for ii, lin_term in lin_terms.items():
z_k_trans = net.getReducedTree([0,ii]).getRoot().z_kernel + lin_term
assert np.abs(z_k_trans.k_bar - Kernel((alphas, gammas[:,0]*gammas[:,ii])).k_bar) < 1e-8
def createTree2(self, reinitialize=1, add_lin=True, v_eq=-75.):
'''
Create simple NET structure
3 4
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---0---
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'''
self.v_eq = v_eq
loc_ind = np.array([0, 1, 2])
# import btstructs
# import morphologyReader as morphR
# net_py = btstructs.STree()
# # node 0
# alphas = -1. / np.array([1.])
# gammas = np.array([1.])
# self.z_0 = - np.sum(gammas / alphas)
# node_0 = btstructs.SNode(0)
# node_0.set_content({'layerdata': morphR.layerData(loc_ind, alphas, gammas)})
# dat = node_0.get_content()['layerdata']
# dat.set_ninds(np.array([]))
# net_py.set_root(node_0)
# # node 1
# alphas = -1. / np.array([1.])
# gammas = np.array([1.])
# self.z_1 = - np.sum(gammas / alphas)
# node_1 = btstructs.SNode(1)
# node_1.set_content({'layerdata': morphR.layerData(loc_ind[0:1], alphas, gammas)})
# dat = node_1.get_content()['layerdata']
# dat.set_ninds(np.array([0]))
# net_py.add_node_with_parent(node_1, node_0)
# # node 2
# alphas = -1. / np.array([1.])
# gammas = np.array([1.])
# self.z_2 = - np.sum(gammas / alphas)
# node_2 = btstructs.SNode(2)
# node_2.set_content({'layerdata': morphR.layerData(loc_ind[1:], alphas, gammas)})
# dat = node_2.get_content()['layerdata']
# dat.set_ninds(np.array([]))
# net_py.add_node_with_parent(node_2, node_0)
# # node 3
# alphas = -1. / np.array([1.])
# gammas = np.array([1.])
# self.z_3 = - np.sum(gammas / alphas)
# node_3 = btstructs.SNode(3)
# node_3.set_content({'layerdata': morphR.layerData(loc_ind[1:2], alphas, gammas)})
# dat = node_3.get_content()['layerdata']
# dat.set_ninds(np.array([loc_ind[1]]))
# net_py.add_node_with_parent(node_3, node_2)
# # node 4
# alphas = -1. / np.array([1.])
# gammas = np.array([1.])
# node_4 = btstructs.SNode(4)
# self.z_4 = - np.sum(gammas / alphas)
# node_4.set_content({'layerdata': morphR.layerData(loc_ind[2:], alphas, gammas)})
# dat = node_4.get_content()['layerdata']
# dat.set_ninds(np.array([loc_ind[2]]))
# net_py.add_node_with_parent(node_4, node_2)
# # linear terms
# alphas = -1. / np.array([1.])
# gammas = np.array([1.])
# lin3 = morphR.linearLayerData([1], alphas, gammas)
# alphas = -1. / np.array([1.])
# gammas = np.array([1.])
# lin4 = morphR.linearLayerData([2], alphas, gammas)
# self.lin_terms = [lin3, lin4] if add_lin else []
# kernel constants
alphas = 1. / np.array([1.])
gammas = np.array([1.])
# nodes
node_0 = NETNode(0, [0, 1, 2], [], z_kernel=(alphas, gammas))
node_1 = NETNode(1, [0], [0], z_kernel=(alphas, gammas))
node_2 = NETNode(2, [1, 2], [], z_kernel=(alphas, gammas))
node_3 = NETNode(3, [1], [1], z_kernel=(alphas, gammas))
node_4 = NETNode(4, [2], [2], z_kernel=(alphas, gammas))
# add nodes to tree
net_py = NET()
net_py.setRoot(node_0)
net_py.addNodeWithParent(node_1, node_0)
net_py.addNodeWithParent(node_2, node_0)
net_py.addNodeWithParent(node_3, node_2)
net_py.addNodeWithParent(node_4, node_2)
# linear terms
alphas = 1. / np.array([1.])
gammas = np.array([1.])
self.lin_terms = {
1: Kernel((alphas, gammas)),
2: Kernel((alphas, gammas))
} if add_lin else {}
# store
self.net_py = net_py
self.cnet = netsim.NETSim(net_py,
lin_terms=self.lin_terms,
v_eq=self.v_eq)