def test_simultaneous_minimization_profile():
'''
Test the calculation of minimization profiles by the minimizers.
'''
g1 = helpers.default_gaussian('g1', 'x1', 'c1', 's1')
g2 = helpers.default_gaussian('g2', 'x2', 'c2', 's2')
c1 = g1.args.get('c1')
s2 = g2.args.get('s2')
# Change the bounds to avoid evaluations to zero
c1.bounds = (-2, +2)
s2.bounds = (0.5, 1.5)
d1 = g1.generate(1000)
d2 = g2.generate(1000)
cats = [minkit.Category('uml', g1, d1), minkit.Category('uml', g2, d2)]
cv = np.linspace(*c1.bounds, 10)
sv = np.linspace(*s2.bounds, 10)
mp = tuple(a.flatten() for a in np.meshgrid(cv, sv))
with minkit.simultaneous_minimizer(cats) as minimizer:
minimizer.minimize()
minimizer.minos_profile('c1')
minimizer.minimization_profile('c1', cv)
minimizer.minimization_profile(['c1', 's2'], mp)
def test_simultaneous_minimizer():
'''
Test the "simultaneous_minimizer" function.
'''
m = minkit.Parameter('m', bounds=(10, 20))
# Common mean
s = minkit.Parameter('s', 1, bounds=(0.1, +3))
# First Gaussian
c1 = minkit.Parameter('c1', 15, bounds=(10, 20))
g1 = minkit.Gaussian('g1', m, c1, s)
data1 = g1.generate(size=1000)
# Second Gaussian
c2 = minkit.Parameter('c2', 15, bounds=(10, 20))
g2 = minkit.Gaussian('g2', m, c2, s)
data2 = g2.generate(size=10000)
categories = [
minkit.Category('uml', g1, data1),
minkit.Category('uml', g2, data2)
]
with helpers.fit_test(categories, simultaneous=True) as test:
with minkit.simultaneous_minimizer(categories,
minimizer='minuit') as minuit:
test.result = minuit.migrad()
def test_simultaneous_fcn_profile():
'''
Test the calculations of profiles in simultaneous minimizers.
'''
g1 = helpers.default_gaussian('g1', 'x1', 'c1', 's1')
g2 = helpers.default_gaussian('g2', 'x2', 'c2', 's2')
d1 = g1.generate(1000)
d2 = g2.generate(1000)
cats = [minkit.Category('uml', g1, d1), minkit.Category('uml', g2, d2)]
cv = np.linspace(*g1.args.get('c1').bounds, 10)
sv = np.linspace(*g2.args.get('s2').bounds, 10)
mp = tuple(a.flatten() for a in np.meshgrid(cv, sv))
with minkit.simultaneous_minimizer(cats) as minimizer:
minimizer.fcn_profile('c1', cv)
minimizer.fcn_profile(['c1', 's2'], mp)
def test_category():
'''
Test the "Category" class.
'''
with pytest.raises(TypeError):
c = minkit.Category()