def ogden_1(self, sample=10, range=None, plot=False):
if range is None:
range = [-5.0, 5.0]
m1_space = np.linspace(range[0], range[1], sample)
a1_space = np.linspace(range[0], range[1], sample)
param_data = []
discarded = []
for m in m1_space:
for a in a1_space:
model = Nonlinear.Ogden("Ogden 1-term", 1, [m], [a])
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(
MechanicalTests.Uniaxial, [0.01, 5.])
if np.min(H[0, 0]) > 0.0:
title = model.name + ' m1=' + format(
m, '.2f') + ' a1=' + format(a, '.2f')
if plot:
self.plot_energy(title, l, W, dW, H)
param_data.append([m, a])
print('min(H)={} > 0.0 [m1={}, a1={}]'.format(
np.min(H[0, 0]), m, a))
else:
discarded.append([m, a])
param_data = np.asarray(param_data)
discarded = np.asarray(discarded)
self.plot_space("Ogden 1-term", param_data, discarded, range)
print('param_data = ', param_data)
print('discarded = ', discarded)
np.save('./data/params_included_Ogden1.npy', param_data)
np.save('./data/params_discarded_Ogden1.npy', discarded)
return param_data, discarded
def mooney_rivlin(self, sample=10, range=None, plot=False):
if range is None:
range = [-5.0, 5.0]
c1_space = np.linspace(range[0], range[1], sample)
c2_space = np.linspace(range[0], range[1], sample)
param_data = []
discarded = []
for c1 in c1_space:
for c2 in c2_space:
model = Nonlinear.MooneyRivlin("Mooney-Rivlin", c1, c2)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(
MechanicalTests.Uniaxial, [0.01, 5.])
if np.min(H[0, 0]) > 0.0:
title = model.name + ' c1=' + format(
c1, '.2f') + ' c2=' + format(c2, '.2f')
if plot:
self.plot_energy(title, l, W, dW, H)
param_data.append([c1, c2])
print('min(H)={} > 0.0 [c1={}, c2={}]'.format(
np.min(H[0, 0]), c1, c2))
else:
discarded.append([c1, c2])
param_data = np.asarray(param_data)
discarded = np.asarray(discarded)
self.plot_space("Mooney-Rivlin", param_data, discarded, range)
print('param_data = ', param_data)
print('discarded = ', discarded)
return param_data, discarded
def neo_hookean(self, sample=10, plot=False):
mu_space = np.linspace(-5.0, 5.0, sample)
param_data = []
discarded = []
for mu in mu_space:
model = Nonlinear.NeoHookean("Neo-Hookean", mu)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(
MechanicalTests.Uniaxial, [0.01, 5.])
if np.min(H[0, 0]) > 0.0:
if plot:
self.plot_energy(
model.name + ' mu=' + str(format(mu, '.2f')), l, W, dW,
H)
param_data.append(mu)
print('min(H)={} > 0.0 [mu={}]'.format(np.min(H[0, 0]), mu))
else:
discarded.append(mu)
param_data = np.asarray(param_data)
discarded = np.asarray(discarded)
print('mu_data = ', param_data)
print('discarded = ', discarded)
return param_data, discarded
def ogden_2(self, sample=10, range1=None, range2=None, plot=False):
if range1 is None:
range1 = [-5.0, 5.0]
if range2 is None:
range2 = [-5.0, 5.0]
m_space = np.linspace(range1[0], range1[1], sample)
a_space = np.linspace(range2[0], range2[1], sample)
param_data = []
discarded = []
for m1 in m_space:
for m2 in m_space:
for a1 in a_space:
for a2 in a_space:
if (m1 == 0. and m2 == 0.) or a1 == 0. or a2 == 0.:
# print('m1={} m2={} a1={} a2={}'.format(m1, m2, a1, a2))
continue
model = Nonlinear.Ogden("Ogden 2-term", 2, [m1, m2],
[a1, a2])
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(
MechanicalTests.Uniaxial, [0.01, 5.])
if np.min(H[0, 0]) > 0.0:
title = model.name + ' m=[' + format(
m1, '.2f') + ',' + format(
m2, '.2f') + '] a=[' + format(
a1, '.2f') + ',' + format(a2,
'.2f') + ']'
if plot:
self.plot_energy(title, l, W, dW, H)
param_data.append([m1, m2, a1, a2])
print(
'INCLUDED:: min(H)={} > 0.0 [m1=<{},{}>, a1=<{},{}>]'
.format(np.min(H[0, 0]), format(m1, '.2f'),
format(m2, '.2f'), format(a1, '.2f'),
format(a2, '.2f')))
else:
print(
'DISCARDED:: min(H)={} > 0.0 [m1=<{},{}>, a1=<{},{}>]'
.format(np.min(H[0, 0]), format(m1, '.2f'),
format(m2, '.2f'), format(a1, '.2f'),
format(a2, '.2f')))
discarded.append([m1, m2, a1, a2])
param_data = np.asarray(param_data)
discarded = np.asarray(discarded)
print('param_data = ', param_data)
print('discarded = ', discarded)
np.save('./data/params_included_Ogden2.npy', param_data)
np.save('./data/params_discarded_Ogden2.npy', discarded)
self.plot_space("Ogden 2-term",
param_data,
discarded,
range1=range1,
range2=range2)
return param_data, discarded
def plot_metamodel_all(self):
# self.hyper_gen_model.select_cases_per_task()
# GM/E [27 29 31 33 36] WM/E [26 28 30 32 34] NH/E [37] AB/E [35]
# GM/L [8] WM/L [7] NH/L [ 0 1 4 5 12 13 14 15 16 17 18 19 21 22 24 25] AB/L [ 2 3 9 10 11 20 23]
# GM/H [55 56 59 60 63 64 67 68 71 72] WM/H [53 54 57 58 61 62 65 66 69 70] NH/H [38 39 40 41 42 43 44 45 46 47 48 49 50 51 52] AB/H [6]
c_h_gm, c_h_wm, c_h_nh, c_h_ab = np.asarray([71]), np.asarray(
[58]), np.asarray([45]), np.asarray([6])
c_all = np.concatenate((c_h_gm, c_h_wm, c_h_nh, c_h_ab), axis=0)
# self.hyper_gen_model.plot_cases(c_h_gm)
# self.hyper_gen_model.plot_cases(c_h_wm)
# self.hyper_gen_model.plot_cases(c_h_nh)
# self.hyper_gen_model.plot_cases(c_h_ab)
# self.hyper_gen_model.plot_cases(c_all)
kPa = Common.kPa
# mm_l = [self.metamodel_nh, self.metamodel_mr, self.metamodel_o1_l]
mm_l = [
self.metamodel_nh, self.metamodel_mr, self.metamodel_o1_l,
self.metamodel_o1_h
]
mm_h = [self.metamodel_nh, self.metamodel_mr, self.metamodel_o1_h]
print('\n\n>>>>> Neo-Hookean')
model = Nonlinear.Budday2017a("Neo-Hookean CC [Budday2017]",
0.99 * kPa, 0.29 * kPa)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(
MechanicalTests.Uniaxial, [0.001, 5.0])
self.hyper_gen_model.plot_cases_with_metamodels(
np.asarray([53]), l, W, mm_l)
print('\n\n>>>>> Mooney-Rivlin')
model = Nonlinear.Budday2017b("Mooney-Rivlin BG [Budday2017]",
1.27 * kPa, 0.0 * kPa, 0.57 * kPa,
0.29 * kPa)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(
MechanicalTests.Uniaxial, [0.001, 5.0])
self.hyper_gen_model.plot_cases_with_metamodels(
np.asarray([59]), l, W, mm_l)
print('\n\n>>>>> Ogden 1-term')
model = Nonlinear.Mihai2017a("Ogden 1-term [Mihai2017]", -0.0939 * kPa,
-4.0250)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(
MechanicalTests.Uniaxial, [0.001, 5.0])
self.hyper_gen_model.plot_cases_with_metamodels(
np.asarray([38]), l, W, mm_l)
print('\n\n>>>>> Ogden 2-terms')
model = Nonlinear.Budday2017e("Mod 1-term Ogden BG [Budday2017]",
0.83 * kPa, -15.5, 0.65 * kPa, -32.5)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(
MechanicalTests.Uniaxial, [0.001, 5.0])
self.hyper_gen_model.plot_cases_with_metamodels(
np.asarray([71]), l, W, mm_l)
print('\n\n>>>>> Ogden 3-terms')
model = Nonlinear.Mihai2015e("Ogden 3-term [Mihai2015]", 3,
[-3.543 * kPa, -2.723 * kPa, 0.654 * kPa],
[1, -1, 2])
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(
MechanicalTests.Uniaxial, [0.001, 5.0])
self.hyper_gen_model.plot_cases_with_metamodels(
np.asarray([44]), l, W, mm_l)
print('\n\n>>>>> Ogden 4-terms')
model = Nonlinear.Mihai2015e(
"Ogden 4-term [Mihai2015]", 4,
[-5.877 * kPa, -5.043 * kPa, 1.161 * kPa, 0.501 * kPa],
[1, -1, 2, -2])
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(
MechanicalTests.Uniaxial, [0.001, 5.0])
self.hyper_gen_model.plot_cases_with_metamodels(
np.asarray([45]), l, W, mm_l)
print('\n\n>>>>> Ogden 8-terms')
model = Nonlinear.Mihai2015e("Ogden 8-term [Mihai2015]", 8, [
-639.530 * kPa, -544.840 * kPa, 322.660 * kPa, 237.040 * kPa,
-88.640 * kPa, -57.830 * kPa, 10.150 * kPa, 6.080 * kPa
], [1, -1, 2, -2, 3, -3, 4, -4])
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(
MechanicalTests.Uniaxial, [0.001, 5.0])
self.hyper_gen_model.plot_cases_with_metamodels(
np.asarray([49]), l, W, mm_l)
def Process():
# output
data_l = np.zeros((1, s))
data_W = np.zeros((1, s))
data_dW = np.zeros((1, s))
data_H = np.zeros((1, s))
data_sigma = np.zeros((1, s))
data_P = np.zeros((1, p), dtype=bool)
data_offset = []
data_Y = [""]
data_C = []
data_A = []
data_M = []
# [Yousefi2013]
# E +- 0.25
# v +- 0.145
model = Linear.Generic(
"Linear pathological region growing --brain-- [Yousefi2013]", 0,
3.0 * kPa, 0.45)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l[0, :] = l
data_W[0, :] = W
data_dW[0, :] = dW[0]
data_H[0, :] = H[0, 0]
data_sigma[0, :] = sigma[0]
data_P[0, :] = P
data_offset.append(offset)
data_Y[0] = "Pathos-Yousefi2013"
data_C.append(c)
data_A.append(Common.NH)
data_M.append(Common.LIN)
stretches = model.stretches
# [Prastawa2009]
model = Linear.Generic(
"Linear pathological region growing --brain-- [Prastawa2009]", 0,
0.694 * kPa, 0.4)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Pathos-Prastawa2009")
data_C.append(c)
data_A.append(Common.NH)
data_M.append(Common.LIN)
# model = Linear.Generic("Linear pathological region growing --falx-- [Prastawa2009]", 0, 200.0 * kPa, 0.4)
# model.Compute()
# l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial, [0.9,1.1])
# data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
# data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
# data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
# data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
# data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
# data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
# data_offset.append(offset)
# data_Y.append("Pathos-falx-Prastawa2009")
# data_C.append(c)
# data_A.append(Common.AB)
# data_M.append(Common.LIN)
# [Kyriacou1999]
# TODO MICCAI exclusion
# model = Nonlinear.Mihai2015a("Neo-Hookean --WM-- [Kyriacou1999]", 3.0 * kPa)
# model.Compute()
# l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial, [0.8,1.2])
# data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
# data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
# data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
# data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
# data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
# data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
# data_offset.append(offset)
# data_Y.append("Pathos-WM-Kyriacou1999")
# data_C.append(c)
# data_A.append(Common.WM)
# data_M.append(Common.HYP)
# TODO MICCAI exclusion
# model = Nonlinear.Mihai2015a("Neo-Hookean --GM-- [Kyriacou1999]", 30.0 * kPa)
# model.Compute()
# l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial, [0.8,1.2])
# data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
# data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
# data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
# data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
# data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
# data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
# data_offset.append(offset)
# data_Y.append("Pathos-GM-Kyriacou1999")
# data_C.append(c)
# data_A.append(Common.GM)
# data_M.append(Common.HYP)
# [6]
model = Nonlinear.Mihai2015a("Neo-Hookean --Tumour-- [Kyriacou1999]",
30.0 * kPa)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.8, 1.2])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Pathos-TUMOUR-Kyriacou1999")
data_C.append(c)
data_A.append(Common.AB)
data_M.append(Common.HYP)
# [Takizawa1994]
# model = Linear.Generic("Linear pathological region growing --CSF-- [Takizawa1994]", 0, 1.0 * kPa, 0.47)
# model.Compute()
# l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial, [0.9,1.1])
# data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
# data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
# data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
# data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
# data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
# data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
# data_offset.append(offset)
# data_Y.append("Pathos-CSF-Takizawa1994")
# data_C.append(c)
# data_A.append(Common.AB)
# data_M.append(Common.LIN)
# model = Linear.Generic("Linear pathological region growing --falx-- [Takizawa1994]", 0, 100.0 * kPa, 0.47)
# model.Compute()
# l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial, [0.9,1.1])
# data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
# data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
# data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
# data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
# data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
# data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
# data_offset.append(offset)
# data_Y.append("Pathos-falx-Takizawa1994")
# data_C.append(c)
# data_A.append(Common.AB)
# data_M.append(Common.LIN)
model = Linear.Generic(
"Linear pathological region growing --WM-- [Takizawa1994]", 0,
4.0 * kPa, 0.47)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Pathos-WM-Takizawa1994")
data_C.append(c)
data_A.append(Common.WM)
data_M.append(Common.LIN)
model = Linear.Generic(
"Linear pathological region growing --GM-- [Takizawa1994]", 0,
8.0 * kPa, 0.47)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Pathos-GM-Takizawa1994")
data_C.append(c)
data_A.append(Common.GM)
data_M.append(Common.LIN)
# [Dumpuri2006,Chen2011]
model = Linear.Generic(
"Linear pathological region growing --tumour-- [Dumpuri2006,Chen2011]",
0, 100.0 * kPa, 0.45)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Pathos-Tumour-Dumpuri2006")
data_C.append(c)
data_A.append(Common.AB)
data_M.append(Common.LIN)
model = Linear.Generic(
"Linear brain-shift compensation for ablation --tumour-- [Miller2013]",
0, 9.0 * kPa, 0.45)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("BrainShift-tumour-Miller2013")
data_C.append(c)
data_A.append(Common.AB)
data_M.append(Common.LIN)
model = Linear.Generic(
"Linear brain-shift compensation for ablation --tumour-- [Morin2016]",
0, 10.0 * kPa, 0.45)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("BrainShift-tumour-Morin2016")
data_C.append(c)
data_A.append(Common.AB)
data_M.append(Common.LIN)
PlotMaterial.Groups("Pathological Region Growing", stretches, data_l,
data_W, data_dW, data_H, data_sigma, data_Y)
return data_l, data_W, data_dW, data_H, data_sigma, data_P, data_offset, data_Y, data_C, data_A, data_M
def Process():
# output
data_l = np.zeros((1, s))
data_W = np.zeros((1, s))
data_dW = np.zeros((1, s))
data_H = np.zeros((1, s))
data_sigma = np.zeros((1, s))
data_P = np.zeros((1, p), dtype=bool)
data_offset = []
data_Y = [""]
data_C = []
data_A = []
data_M = []
''' [Mihai2017] [38] '''
# TODO check - too flat and fitting is bad
# TODO Recent papers to add
model = Nonlinear.Mihai2017a("Ogden 1-term [Mihai2017]", -0.0939 * kPa,
-4.0250)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.8, 1.2])
data_l[0, :] = l
data_W[0, :] = W
data_dW[0, :] = dW[0]
data_H[0, :] = H[0, 0]
data_sigma[0, :] = sigma[0]
data_P[0, :] = P
data_offset.append(offset)
data_Y[0] = "Hyperelastic-Ogden1-Mihai2017"
data_C.append(c)
data_A.append(Common.NH)
data_M.append(Common.HYP)
stretches = model.stretches
model = Nonlinear.Mihai2017b(
"3-term Mooney-Rivlin: Ogden 1-term + MR 2-term [Mihai2017]",
0.0653 * kPa, 7.1813, -3.8201 * kPa, 3.5376 * kPa)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.8, 1.2])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-MR3-Mihai2017")
data_C.append(c)
data_A.append(Common.NH)
data_M.append(Common.HYP)
# TODO check - negative
# model = Nonlinear.Mihai2017c("3-term Ogden [Mihai2017]", 3, [-5.5090 * kPa, 2.9269 * kPa, 1.4653 * kPa], [2, -2, 4])
# model.Compute()
# l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial, [0.8,1.2])
# data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
# data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
# data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
# data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
# data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
# data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
# data_offset.append(offset)
# data_Y.append("Hyperelastic-Ogden3-Mihai2017")
# data_C.append(c)
# data_A.append(Common.NH)
# data_M.append(Common.HYP)
''' [Mihai2015] '''
# model = Nonlinear.Mihai2015a("Neo-Hookean [Mihai2015]", 333.28 * kPa)
model = Nonlinear.Mihai2015a("Neo-Hookean [Mihai2015]", 0.33328 * kPa)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.6, 1.4])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-NH-Mihai2015")
data_C.append(c)
data_A.append(Common.NH)
data_M.append(Common.HYP)
# TODO check - prediction is poor
# model = Nonlinear.Mihai2015b("Mooney-Rivlin [Mihai2015]", 0.28 * kPa, 333.0 * kPa)
model = Nonlinear.Mihai2015b("Mooney-Rivlin [Mihai2015]", 0.28 * kPa,
0.333 * kPa)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.6, 1.4])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-MR-Mihai2015")
data_C.append(c)
data_A.append(Common.NH)
data_M.append(Common.HYP)
# TODO check - fit crashes
# model = Nonlinear.Mihai2015c("Fung [Mihai2015]", 166.64 * kPa, 2.4974)
model = Nonlinear.Mihai2015c("Fung [Mihai2015]", 0.16664 * kPa, 2.4974)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.6, 1.4])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-Fung-Mihai2015")
data_C.append(c)
data_A.append(Common.NH)
data_M.append(Common.HYP)
# TODO check fit nan
# model = Nonlinear.Mihai2015d("Gent [Mihai2015]", 333.28 * kPa, 0.9918)
model = Nonlinear.Mihai2015d("Gent [Mihai2015]", 0.33328 * kPa, 0.9918)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.6, 1.4])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-Gent-Mihai2015")
data_C.append(c)
data_A.append(Common.NH)
data_M.append(Common.HYP)
# TODO check - change optimisation params
# model = Nonlinear.Mihai2015e("Ogden 3-term [Mihai2015]", 3, [-3543 * kPa, -2723 * kPa, 654 * kPa], [1, -1, 2])
model = Nonlinear.Mihai2015e("Ogden 3-term [Mihai2015]", 3,
[-3.543 * kPa, -2.723 * kPa, 0.654 * kPa],
[1, -1, 2])
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.6, 1.4])
# l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial, [0.01, 5])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-Ogden3-Mihai2015")
data_C.append(c)
data_A.append(Common.NH)
data_M.append(Common.HYP)
# TODO check - strain curve starts from megative values (consider only narrower window)
# model = Nonlinear.Mihai2015e("Ogden 4-term [Mihai2015]", 4, [-5877 * kPa, -5043 * kPa, 1161 * kPa, 501 * kPa], [1, -1, 2, -2])
model = Nonlinear.Mihai2015e(
"Ogden 4-term [Mihai2015]", 4,
[-5.877 * kPa, -5.043 * kPa, 1.161 * kPa, 0.501 * kPa], [1, -1, 2, -2])
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.6, 1.4])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-Ogden4-Mihai2015")
data_C.append(c)
data_A.append(Common.NH)
data_M.append(Common.HYP)
# TODO check - consider only narrower window
# model = Nonlinear.Mihai2015e("Ogden 5-term [Mihai2015]", 5, [-34399 * kPa, -18718 * kPa, 14509 * kPa, 2947 * kPa, -2349 * kPa], [1, -1, 2, -2, 3])
model = Nonlinear.Mihai2015e("Ogden 5-term [Mihai2015]", 5, [
-34.399 * kPa, -18.718 * kPa, 14.509 * kPa, 2.947 * kPa, -2.349 * kPa
], [1, -1, 2, -2, 3])
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.6, 1.4])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-Ogden5-Mihai2015")
data_C.append(c)
data_A.append(Common.NH)
data_M.append(Common.HYP)
# model = Nonlinear.Mihai2015e("Ogden 6-term [Mihai2015]", 6, [1189 * kPa, 16855 * kPa, 1444 * kPa, -10108 * kPa, -458 * kPa, 1889 * kPa], [1, -1, 2, -2, 3, -3])
model = Nonlinear.Mihai2015e("Ogden 6-term [Mihai2015]", 6, [
1.189 * kPa, 16.855 * kPa, 1.444 * kPa, -10.108 * kPa, -0.458 * kPa,
1.889 * kPa
], [1, -1, 2, -2, 3, -3])
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.6, 1.4])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-Ogden6-Mihai2015")
data_C.append(c)
data_A.append(Common.NH)
data_M.append(Common.HYP)
# model = Nonlinear.Mihai2015e("Ogden 7-term [Mihai2015]", 7, [-187150 * kPa, -91970 * kPa, 109290 * kPa, 23200 * kPa, -33290 * kPa, -2290 * kPa, 4100 * kPa], [1, -1, 2, -2, 3, -3, 4])
model = Nonlinear.Mihai2015e("Ogden 7-term [Mihai2015]", 7, [
-187.150 * kPa, -91.970 * kPa, 109.290 * kPa, 23.200 * kPa,
-33.290 * kPa, -2.290 * kPa, 4.100 * kPa
], [1, -1, 2, -2, 3, -3, 4])
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.6, 1.4])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-Ogden7-Mihai2015")
data_C.append(c)
data_A.append(Common.NH)
data_M.append(Common.HYP)
# TODO check - consider only window
# model = Nonlinear.Mihai2015e("Ogden 8-term [Mihai2015]", 8, [-639530 * kPa, -544840 * kPa, 322660 * kPa, 237040 * kPa, -88640 * kPa, -57830 * kPa, 10150 * kPa, 6080 * kPa], [1, -1, 2, -2, 3, -3, 4, -4])
model = Nonlinear.Mihai2015e("Ogden 8-term [Mihai2015]", 8, [
-639.530 * kPa, -544.840 * kPa, 322.660 * kPa, 237.040 * kPa,
-88.640 * kPa, -57.830 * kPa, 10.150 * kPa, 6.080 * kPa
], [1, -1, 2, -2, 3, -3, 4, -4])
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.6, 1.4])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-Ogden8-Mihai2015")
data_C.append(c)
data_A.append(Common.NH)
data_M.append(Common.HYP)
''' [Laksari2012] from [Morin2017] '''
# TODO c10=[+-0.06], c01=[+-0.05], c11=[+-0.01], K=[+-0.26]
# model = Nonlinear.Laksari2012("Mooney Rivlin 3-term + Ogden 2-param [Laksari2012]", -1.34 * kPa, 1.83 * kPa, 0.29 * kPa, 46, 100, 0.49) # compressible
model = Nonlinear.Laksari2012(
"Mooney Rivlin 3-term + Ogden 2-param [Laksari2012]", -1.01 * kPa,
1.49 * kPa, 0.19 * kPa, 2.38, 100, 0.49) # incompressible
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.7, 1.3])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-MR3-Laksari2012")
data_C.append(c)
data_A.append(Common.NH)
data_M.append(Common.HYP)
''' [Schiavone2009] from [Morin2017] '''
# TODO MICCAI assumption for tension
model = Nonlinear.Schiavone2009("Mooney Rivlin 2-term [Schiavone2009]",
0.24 * kPa, 3.42 * kPa)
model.Compute()
# l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial, [1.0,1.45])
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.55, 1.45])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-MR2-Schiavone2009")
data_C.append(c)
data_A.append(Common.NH)
data_M.append(Common.HYP)
''' [Miller2002] '''
model = Nonlinear.Miller2002("Ogden mod 1-term [Miller2002]", 0.842 * kPa,
-4.7)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.7, 1.3])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-OgdenMod1-Miller2002")
data_C.append(c)
data_A.append(Common.NH)
data_M.append(Common.HYP)
# model = Nonlinear.Mihai2015e("Ogden 3-term Rubber", 3, [6300 * kPa, 1.2 * kPa, -10 * kPa], [1.3/2.0, 5.0/2.0, -2.0/2.0])
# model.Compute()
# # l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial, [0.8,1.2])
# l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial, [0.001, 5])
# data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
# data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
# data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
# data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
# data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
# data_P = np.concatenate((data_P, P.reshape(1,p)), axis=0)
# data_offset.append(offset)
# data_Y.append("Hyperelastic-Ogden3-Mihai2015")
# data_C.append(c)
# data_A.append(Common.NH)
# data_M.append(Common.HYP)
''' ############################################################################################# '''
''' Budday NH [53]'''
model = Nonlinear.Budday2017a("Neo-Hookean CC [Budday2017]", 0.99 * kPa,
0.29 * kPa)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-NH-CC-Budday2017")
data_C.append(c)
data_A.append(Common.WM)
data_M.append(Common.HYP)
model = Nonlinear.Budday2017a("Neo-Hookean CR [Budday2017]", 1.75 * kPa,
0.52 * kPa)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-NH-CR-Budday2017")
data_C.append(c)
data_A.append(Common.WM)
data_M.append(Common.HYP)
# [55]
model = Nonlinear.Budday2017a("Neo-Hookean BG [Budday2017]", 1.37 * kPa,
0.57 * kPa)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-NH-BG-Budday2017")
data_C.append(c)
data_A.append(Common.GM)
data_M.append(Common.HYP)
model = Nonlinear.Budday2017a("Neo-Hookean C [Budday2017]", 2.80 * kPa,
1.22 * kPa)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-NH-C-Budday2017")
data_C.append(c)
data_A.append(Common.GM)
data_M.append(Common.HYP)
''' Budday MR [57]'''
model = Nonlinear.Budday2017b("Mooney-Rivlin CC [Budday2017]", 0.92 * kPa,
0.0 * kPa, 0.29 * kPa, 0.13 * kPa)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-MR-CC-Budday2017")
data_C.append(c)
data_A.append(Common.WM)
data_M.append(Common.HYP)
model = Nonlinear.Budday2017b("Mooney-Rivlin CR [Budday2017]", 1.62 * kPa,
0.0 * kPa, 0.52 * kPa, 0.26 * kPa)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-MR-CR-Budday2017")
data_C.append(c)
data_A.append(Common.WM)
data_M.append(Common.HYP)
# [59]
model = Nonlinear.Budday2017b("Mooney-Rivlin BG [Budday2017]", 1.27 * kPa,
0.0 * kPa, 0.57 * kPa, 0.29 * kPa)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-MR-BG-Budday2017")
data_C.append(c)
data_A.append(Common.GM)
data_M.append(Common.HYP)
model = Nonlinear.Budday2017b("Mooney-Rivlin C [Budday2017]", 2.59 * kPa,
0.0 * kPa, 1.22 * kPa, 0.61 * kPa)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-MR-C-Budday2017")
data_C.append(c)
data_A.append(Common.GM)
data_M.append(Common.HYP)
''' Budday DMR [61] '''
model = Nonlinear.Budday2017c("Demiray CC [Budday2017]", 0.55 * kPa, 28.4,
0.28 * kPa, 1.29)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-DMR-CC-Budday2017")
data_C.append(c)
data_A.append(Common.WM)
data_M.append(Common.HYP)
model = Nonlinear.Budday2017c("Demiray CR [Budday2017]", 1.05 * kPa, 24.6,
0.48 * kPa, 4.37)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-DMR-CR-Budday2017")
data_C.append(c)
data_A.append(Common.WM)
data_M.append(Common.HYP)
# [63]
model = Nonlinear.Budday2017c("Demiray BG [Budday2017]", 0.97 * kPa, 17.1,
0.52 * kPa, 6.03)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-DMR-BG-Budday2017")
data_C.append(c)
data_A.append(Common.GM)
data_M.append(Common.HYP)
model = Nonlinear.Budday2017c("Demiray C [Budday2017]", 1.90 * kPa, 18.8,
0.91 * kPa, 16.7)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-DMR-C-Budday2017")
data_C.append(c)
data_A.append(Common.GM)
data_M.append(Common.HYP)
''' Budday Gnt [65] '''
model = Nonlinear.Budday2017d("Gent CC [Budday2017]", 0.62 * kPa, 0.06,
0.29 * kPa, 85.0)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-Gent-CC-Budday2017")
data_C.append(c)
data_A.append(Common.WM)
data_M.append(Common.HYP)
model = Nonlinear.Budday2017d("Gent CR [Budday2017]", 1.16 * kPa, 0.06,
0.48 * kPa, 0.23)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-Gent-CR-Budday2017")
data_C.append(c)
data_A.append(Common.WM)
data_M.append(Common.HYP)
# [67]
model = Nonlinear.Budday2017d("Gent BG [Budday2017]", 1.01 * kPa, 0.08,
0.52 * kPa, 0.18)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-Gent-BG-Budday2017")
data_C.append(c)
data_A.append(Common.GM)
data_M.append(Common.HYP)
model = Nonlinear.Budday2017d("Gent C [Budday2017]", 2.01 * kPa, 0.08,
0.92 * kPa, 0.08)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-Gent-C-Budday2017")
data_C.append(c)
data_A.append(Common.GM)
data_M.append(Common.HYP)
''' Budday Ogden [69] '''
# model = Nonlinear.Budday2017e("Mod 1-term Ogden CC [Budday2017]", 0.47 * kPa, -11.4, 0.33*kPa, -25.6)
model = Nonlinear.Budday2017e("Mod 1-term Ogden CC [Budday2017]",
0.43 * kPa, -22.8, 0.35 * kPa, -26.6)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-Ogden1-CC-Budday2017")
data_C.append(c)
data_A.append(Common.WM)
data_M.append(Common.HYP)
# model = Nonlinear.Budday2017e("Mod 1-term Ogden CR [Budday2017]", 0.86 * kPa, -19.9, 0.58 * kPa, -29.2)
model = Nonlinear.Budday2017e("Mod 1-term Ogden CR [Budday2017]",
0.85 * kPa, -20.5, 0.61 * kPa, -30.5)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-Ogden1-CR-Budday2017")
data_C.append(c)
data_A.append(Common.WM)
data_M.append(Common.HYP)
# [71]
# model = Nonlinear.Budday2017e("Mod 1-term Ogden BG [Budday2017]", 0.84 * kPa, -12.5, 0.64 * kPa, -30.0)
model = Nonlinear.Budday2017e("Mod 1-term Ogden BG [Budday2017]",
0.83 * kPa, -15.5, 0.65 * kPa, -32.5)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-Ogden1-BG-Budday2017")
data_C.append(c)
data_A.append(Common.GM)
data_M.append(Common.HYP)
# model = Nonlinear.Budday2017e("Mod 1-term Ogden C [Budday2017]", 1.63 * kPa, -16.5, 1.16 * kPa, -38.9)
model = Nonlinear.Budday2017e("Mod 1-term Ogden C [Budday2017]",
1.61 * kPa, -16.6, 1.20 * kPa, -43.6)
model.Compute()
l, W, dW, H, sigma, P, offset = model.Evaluate(MechanicalTests.Uniaxial,
[0.9, 1.1])
data_l = np.concatenate((data_l, l.reshape(1, s)), axis=0)
data_W = np.concatenate((data_W, W.reshape(1, s)), axis=0)
data_dW = np.concatenate((data_dW, dW[0].reshape(1, s)), axis=0)
data_H = np.concatenate((data_H, H[0, 0].reshape(1, s)), axis=0)
data_sigma = np.concatenate((data_sigma, sigma[0].reshape(1, s)), axis=0)
data_P = np.concatenate((data_P, P.reshape(1, p)), axis=0)
data_offset.append(offset)
data_Y.append("Hyperelastic-Ogden1-C-Budday2017")
data_C.append(c)
data_A.append(Common.GM)
data_M.append(Common.HYP)
PlotMaterial.Groups("Hyperelastic Nonlinear", stretches, data_l, data_W,
data_dW, data_H, data_sigma, data_Y)
return data_l, data_W, data_dW, data_H, data_sigma, data_P, data_offset, data_Y, data_C, data_A, data_M