def test_easy():
b_modes = 3
t_modes = 3
model_num = 1
p = rw.base_params(b_modes + t_modes + 1)
sm = mf.SymbolicModel.from_file(f'tests/{b_modes}B{t_modes}T-M{model_num}.py')
# Set HALE Specific parameters
p.rho.value = 0.0889
p.s_t.value = 16
p.c.value = 1
p.EI.value = 2e4
p.GJ.value = 1e4
p.rho_t.value = 0.75
p.e_0.value = 0.25
p.e_1.value = 0
# set Parameter permutations
vars_ls =[]
#vars_ls.append((p.m_factor,[0.5,1,1.5]))
#vars_ls.append((p.Lambda,np.deg2rad([10,17.5,25])))
#vars_ls.append((p.alpha_r,np.deg2rad([0,5,10])))
#vars_ls.append((p.ratio_fwt,[0,0.1,0.2,0.3]))
#vars_ls.append((p.V,np.linspace(0,200,201))) # ensure velocity last so that fixed points iterats up the velocity
vars_ls.append((p.m_factor,[1]))
vars_ls.append((p.Lambda,np.deg2rad([10])))
vars_ls.append((p.alpha_r,np.deg2rad([0,5,10])))
vars_ls.append((p.ratio_fwt,[0,0.1,0.2,0.3]))
vars_ls.append((p.V,np.linspace(0,40,80))) # ensure velocity last so that fixed points iterats up the velocity
# generate result
res = rw.eigen_perm_params(p,sm,vars_ls,np.isin(model_num,[1,2,3,4]))
assert (3==3)
def Model_Eigen(model_num, b_modes, t_modes):
print(f'Genrating data for model {model_num}')
try:
p = JEC()
dataset_name = 'JEC'
sm = mf.SymbolicModel.from_file(
f'{b_modes}B{t_modes}T-M{model_num}.py')
vars_ls = []
vars_ls.append((p.Lambda, np.deg2rad([10, 17.5, 25])))
#vars_ls.append((p.V,np.linspace(0,40,81))) # V must be second
vars_ls.append((p.V, np.linspace(0, 150, 151))) # V must be second
vars_ls.append((p.alpha_r, np.deg2rad([0, 5, 10])))
vars_ls.append((p.c_dmax, [0, 0.5, 1, 1.5]))
#vars_ls.append((p.ratio_fwt,[0,0.1,0.2,0.3]))
#vars_ls.append((p.ratio_DL,[0,0.05,0.1,0.2]))
vars_ls.append((p.m_factor, [0.5, 1, 1.5]))
calc_fixed = True if np.isin(model_num, np.array([1, 2, 3, 4, 5
])) else False
flutdf = rw.eigen_perm_params(p, sm, vars_ls, calc_fixed, jac=False)
flutdf.to_pickle(
f'Eigen_{b_modes}B{t_modes}T-M{model_num}_{dataset_name}.pkl')
print(f'Genrated data for model {model_num}')
except:
print(f'Model {model_num} exited with an error')