def test_link_linear_order():
"Check that the parameters are linked to the proper name"
model = dl.dd_gauss3
linkedmodel1 = link(model, amp=['amp1', 'amp3'])
linkedmodel2 = link(model, amp=['amp3', 'amp1'])
for linkedmodel in [linkedmodel1, linkedmodel2]:
assert hasattr(linkedmodel, 'amp') and not hasattr(
linkedmodel, 'amp1') and not hasattr(linkedmodel, 'amp3')
def test_link_Nparam_list():
"Check that the combined model has the right number of parameters"
model = dl.dd_gauss2
linkedmodel = link(model, mean=['mean1', 'mean2'])
assert linkedmodel.Nparam == len(linkedmodel._parameter_list())
def test_link_Nparam():
"Check that the parameters are linked resulting in proper number of parameters"
model = dl.dd_gauss2
linkedmodel = link(model, mean=['mean1', 'mean2'])
assert linkedmodel.Nparam == model.Nparam - 1
def test_vec_link_Nparam():
"Check that the parameters are linked resulting in proper number of parameters"
model = double_vec
linkedmodel = link(model, vec=['vec1', 'vec2'])
assert linkedmodel.Nparam == model.Nparam - 40
def test_link_name():
"Check that the parameters are linked to the proper name"
model = dl.dd_gauss2
linkedmodel = link(model, mean=['mean1', 'mean2'])
assert hasattr(linkedmodel, 'mean') and not hasattr(
linkedmodel, 'mean1') and not hasattr(linkedmodel, 'mean2')
def test_vec_link_name():
"Check that the parameters are linked to the proper name"
model = double_vec
linkedmodel = link(model, vec=['vec1', 'vec2'])
assert hasattr(linkedmodel, 'vec') and not hasattr(
linkedmodel, 'vec1') and not hasattr(linkedmodel, 'vec2')
def test_link_linear_name():
"Check that the parameters are linked to the proper name"
model = dl.dd_gauss3
linkedmodel = link(model, amp=['amp1', 'amp3'])
assert hasattr(linkedmodel, 'amp') and not hasattr(
linkedmodel, 'amp1') and not hasattr(linkedmodel, 'amp3')
def test_link_multiple():
"Check that multiple links can be established"
model = dl.dd_gauss3
linkedmodel = link(model,
mean1=['mean1', 'mean2'],
width2=['width2', 'width3'])
assert linkedmodel.Nparam == model.Nparam - 2
def test_link_signature():
"Check the model signature after linking"
model = dl.dd_gauss2
linkedmodel = link(model, mean=['mean1', 'mean2'])
assert linkedmodel.signature == [
'r', 'mean', 'width1', 'width2', 'amp1', 'amp2'
]
def test_link_call():
"Check that linked parameter models return the correct responses"
model = dl.dd_gauss2
linkedmodel = link(model, mean=['mean1', 'mean2'])
x = np.linspace(0, 10, 400)
ref = model(x, 4, 0.5, 4, 0.2, 1, 1)
response = linkedmodel(x, 4, 0.5, 0.2, 1, 1)
assert np.allclose(response, ref)
def test_vec_link_call():
"Check that linked parameter models return the correct responses"
model = double_vec
linkedmodel = link(model, vec=['vec1', 'vec2'])
x = np.linspace(0, 10, 40)
ref = model(1, 2, dl.dd_gauss(x, 3, 0.2), dl.dd_gauss(x, 3, 0.2))
response = linkedmodel(1, 2, dl.dd_gauss(x, 3, 0.2))
assert np.allclose(response, ref)
def test_link_linear_call():
"Check that linked parameter models return the correct responses"
model = dl.dd_gauss2
linkedmodel = link(model, amp=['amp1', 'amp2'])
x = np.linspace(0, 10, 400)
ref = model(x, 4, 0.5, 2, 0.2, 0.9, 0.9)
response = linkedmodel(x, 4, 0.5, 2, 0.2, 0.9)
assert np.allclose(response, ref)
def test_link_fit():
"Check that linked parameter models can be properly fitted"
model = dl.dd_gauss2
linkedmodel = link(model,
mean=['mean1', 'mean2'],
width=['width1', 'width2'])
linkedmodel.mean.par0 = 3
linkedmodel.width.par0 = 0.5
x = np.linspace(0, 10, 400)
ref = model(x, 3, 0.5, 3, 0.5, 1, 1)
result = fit(model, ref, x)
assert np.allclose(result.model, ref, atol=1e-5)
def test_vec_link_fit():
"Check that linked parameter models can be properly fitted"
model = double_vec
linkedmodel = link(model, vec=['vec1', 'vec2'])
linkedmodel.shift.par0 = 1
linkedmodel.scale.par0 = 2
linkedmodel.shift.freeze(1)
linkedmodel.scale.freeze(2)
x = np.linspace(0, 10, 40)
ref = model(1, 2, dl.dd_gauss(x, 3, 0.6), dl.dd_gauss(x, 3, 0.6))
result = fit(linkedmodel, ref, nonlin_tol=1e-3)
assert np.allclose(result.model, ref, atol=1e-2)
