def test_set_symtable(self):
# test that we use Parameter.set(value=XXX) and have
# that new value be used in constraint expressions
pars = Parameters()
pars.add('x', value=1.0)
pars.add('y', expr='x + 1')
assert_(isclose(pars['y'].value, 2.0))
pars['x'].set(value=3.0)
assert_(isclose(pars['y'].value, 4.0))
def test_set_symtable(self):
# test that we use Parameter.set(value=XXX) and have
# that new value be used in constraint expressions
pars = Parameters()
pars.add('x', value=1.0)
pars.add('y', expr='x + 1')
assert_(isclose(pars['y'].value, 2.0))
pars['x'].set(value=3.0)
assert_(isclose(pars['y'].value, 4.0))
def test_isclose(self):
assert_(isclose(1., 1+1e-5, atol=1e-4, rtol=0))
assert_(not isclose(1., 1+1e-5, atol=1e-6, rtol=0))
assert_(isclose(1e10, 1.00001e10, rtol=1e-5, atol=1e-8))
assert_(not isclose(0, np.inf))
assert_(not isclose(-np.inf, np.inf))
assert_(isclose(np.inf, np.inf))
assert_(not isclose(np.nan, np.nan))
def test_expr_with_bounds(self):
"test an expression with bounds, without value"
pars = Parameters()
pars.add('c1', value=0.2)
pars.add('c2', value=0.2)
pars.add('c3', value=0.2)
pars.add('csum', value=0.8)
# this should not raise TypeError:
pars.add('c4', expr='csum-c1-c2-c3', min=0, max=1)
assert_(isclose(pars['c4'].value, 0.2))
def test_dumps_loads_parameters(self):
# test that we can dumps() and then loads() a Parameters
pars = Parameters()
pars.add('x', value=1.0)
pars.add('y', value=2.0)
pars['x'].expr = 'y / 2.0'
dumps = pars.dumps()
newpars = Parameters().loads(dumps)
newpars['y'].value = 100.0
assert_(isclose(newpars['x'].value, 50.0))
def test_dumps_loads_parameters(self):
# test that we can dumps() and then loads() a Parameters
pars = Parameters()
pars.add('x', value=1.0)
pars.add('y', value=2.0)
pars['x'].expr = 'y / 2.0'
dumps = pars.dumps()
newpars = Parameters().loads(dumps)
newpars['y'].value = 100.0
assert_(isclose(newpars['x'].value, 50.0))
def test_params_usersyms(self):
# test passing usersymes to Parameters()
def myfun(x):
return x**3
params = Parameters(usersyms={"myfun": myfun})
params.add("a", value=2.3)
params.add("b", expr="myfun(a)")
xx = np.linspace(0, 1, 10)
yy = 3 * xx + np.random.normal(scale=0.002, size=len(xx))
model = Model(lambda x, a: a * x)
result = model.fit(yy, params=params, x=xx)
assert_(isclose(result.params['a'].value, 3.0, rtol=0.025))
assert_(result.nfev > 3)
assert_(result.nfev < 300)
