def test_orisel():
"Check that dipolar models with orientation selection work"
Vmodel = dipolarmodel(t,r,dd_gauss,bg_hom3d,npathways=1)
Vmodelorisel = dipolarmodel(t,r,dd_gauss,bg_hom3d,npathways=1,orisel=lambda theta: np.ones_like(theta))
Vref = Vmodel(mean=3,width=0.2,mod=0.3,reftime=0,conc=200,scale=1e2)
Vorisel = Vmodelorisel(mean=3,width=0.2,mod=0.3,reftime=0,conc=200,scale=1e2)
assert np.allclose(Vref,Vorisel,rtol=1e-4)
def test_preservation():
"Check that the inputs models are not modified by the output model"
model = dipolarmodel(t,r,dd_gauss,bg_hom3d,npathways=2)
model.mean.par0 = 15
assert model.mean.par0==15 and dd_gauss.mean.par0!=15
def test_call_Pnonparametric():
"Check that the model with one dipolar pathway is correct"
Vmodel = dipolarmodel(t,r,Bmodel=bg_hom3d,npathways=1)
Vsim = Vmodel(mod=0.3,reftime=0.0,conc=50,P=1e5*dd_gauss(r,3,0.2))
assert np.allclose(Vsim,V1path)
def test_model_1harmonics():
"Check that the model with one harmonic is correct"
Vmodel = dipolarmodel(t,r,dd_gauss,bg_hom3d,npathways=1,harmonics=1)
Vsim = Vmodel(mod=0.3,reftime=0.0,conc=50,mean=3,width=0.2,scale=1e5)
assert np.allclose(Vsim,V1harm)
def test_fit_1pathways():
"Check that the model can be correctly fitted with one dipolar pathway"
Vmodel = dipolarmodel(t,r,dd_gauss,bg_hom3d,npathways=1)
result = fit(Vmodel,V1path,nonlin_tol=1e-3)
assert np.allclose(result.model,V1path)
def test_call_keywords():
"Check that the model called via keyword arguments responds correctly"
Vmodel = dipolarmodel(t,r,dd_gauss,bg_hom3d,npathways=1)
Vsim = Vmodel(mod=0.3,reftime=0.0,conc=50,mean=3,width=0.2,scale=1e5)
assert np.allclose(Vsim,V1path)
def test_fit_Pnonparametric():
"Check that the model with one dipolar pathway is correct"
Vmodel = dipolarmodel(t,r,Bmodel=bg_hom3d,npathways=1)
result = fit(Vmodel,V1path,nonlin_tol=1e-5)
assert ovl(result.P/1e5,Pr)>0.975
def test_names():
"Check that the model has correct parameter names"
model = dipolarmodel(t,r,dd_gauss,bg_hom3d,npathways=1)
parameters = ['mean','width','conc','mod','reftime','scale']
for param in parameters:
assert hasattr(model,param)
def test_phenomenological_Bmodel():
"Check model generation of a dipolar signal with a phenomelogical background"
Vmodel = dipolarmodel(t,r,dd_gauss,Bmodel=bg_exp,npathways=1)
Vsim = Vmodel(mod=0.3,reftime=0.0,mean=3,width=0.2,decay=0.1,scale=1e5)
assert np.allclose(Vsim,V1path_phenoB)
def test_ex_sifter_fit():
"Check the SIFTER experimental model in fitting."
experiment = ex_sifter(tau1,tau2)
Vmodel = dipolarmodel(tsifter,r,Bmodel=bg_hom3d,experiment=experiment)
result = fit(Vmodel,Vsifter,nonlin_tol=1e-3)
assert np.allclose(Vsifter,result.model,atol=1e-2) and ovl(result.P/1e5,Pr)>0.975
def test_ex_ridme_fit():
"Check the RIDME experimental model in fitting."
experiment = ex_ridme(tau1,tau2, pathways=[1,2,3])
Vmodel = dipolarmodel(tridme,r,Bmodel=bg_hom3d,experiment=experiment)
result = fit(Vmodel,Vridme,nonlin_tol=1e-3)
assert np.allclose(Vridme,result.model,atol=1e-2) and ovl(result.P/1e5,Pr)>0.975
def test_ex_fwd5pdeer_fit():
"Check the forward 5-pulse DEER experimental model in fitting."
experiment = ex_fwd5pdeer(tau1,tau2,tau3, pathways=[1,2,3])
Vmodel = dipolarmodel(tdeer,r,Bmodel=bg_hom3d,experiment=experiment)
result = fit(Vmodel,Vfwd5pdeer,nonlin_tol=1e-3)
assert np.allclose(Vfwd5pdeer,result.model,atol=1e-2) and ovl(result.P/1e5,Pr)>0.975
def test_ex_4pdeer_fit():
"Check the 4-pulse DEER experimental model."
experiment = ex_4pdeer(tau1,tau2, pathways=[1,2])
Vmodel = dipolarmodel(tdeer,r,Bmodel=bg_hom3d,experiment=experiment)
result = fit(Vmodel,V4pdeer,nonlin_tol=1e-3)
assert np.allclose(V4pdeer,result.model,atol=1e-2) and ovl(result.P/1e5,Pr)>0.975
def test_no_Bmodel():
"Check model generation of a dipolar signal without background"
Vmodel = dipolarmodel(t,r,dd_gauss,None,npathways=1)
Vsim = Vmodel(mod=0.3,reftime=0.0,mean=3,width=0.2,scale=1e5)
assert np.allclose(Vsim,V1path_noB)
def test_call_positional():
"Check that the model called via positional arguments responds correctly"
Vmodel = dipolarmodel(t,r,dd_gauss,bg_hom3d,npathways=1)
Vsim = Vmodel(0.3,0.0,50,3,0.2,1e5)
assert np.allclose(Vsim,V1path)
def test_model_2harmonics():
"Check that the model with two different harmonics is correct"
Vmodel = dipolarmodel(t,r,dd_gauss,bg_hom3d,npathways=2,harmonics=[1,2])
Vsim = Vmodel(lam1=0.3,reftime1=0.0,lam2=0.1,
reftime2=2,conc=50,mean=3,width=0.2,scale=1e5)
assert np.allclose(Vsim,V2harm)
def test_model_3pathways():
"Check that the model with three dipolar pathways is correct"
Vmodel = dipolarmodel(t,r,dd_gauss,bg_hom3d,npathways=3)
Vsim = Vmodel(lam1=0.3,reftime1=0.0,
lam2=0.1,reftime2=2, lam3=0.1, reftime3=5,
conc=50,mean=3,width=0.2,scale=1e5)
assert np.allclose(Vsim,V3path)
def test_fit_2pathways():
"Check that the model can be correctly fitted with two dipolar pathways"
Vmodel = dipolarmodel(t,r,dd_gauss,bg_hom3d,npathways=2)
Vmodel.reftime1.freeze(0)
Vmodel.reftime2.freeze(2)
result = fit(Vmodel,V2path,nonlin_tol=1e-3)
assert np.allclose(result.model,V2path)
def test_ex_5pdeer_fit():
"Check the 5-pulse DEER experimental model in fitting."
experiment = ex_5pdeer(tau1, tau2, tau3)
Vmodel = dipolarmodel(t,
r,
Bmodel=bg_hom3d,
npathways=2,
experiment=experiment)
result = fit(Vmodel, V5pulse, nonlin_tol=1e-3)
assert np.allclose(V5pulse, result.model,
atol=1e-2) and ovl(result.P / 1e5, Pr) > 0.975
def test_Nparam_2():
"Check that the function has the correct number of nonlinear parameters"
model = dipolarmodel(t,r,dd_gauss2,bg_hom3d,npathways=2)
assert model.Nnonlin==9 and model.Nlin==2 and model.Nparam==11
def test_type():
"Check that the function returns a valid model type"
model = dipolarmodel(t,r,dd_gauss,bg_hom3d,npathways=1)
assert isinstance(model,Model)
