def test_saveload_modelresult_roundtrip(method):
"""Test for modelresult.loads()/dumps() and repeating that"""
def mfunc(x, a, b):
return a * (x-b)
model = Model(mfunc)
params = model.make_params(a=0.1, b=3.0)
params['a'].set(min=.01, max=1, brute_step=0.01)
params['b'].set(min=.01, max=3.1, brute_step=0.01)
xx = np.linspace(-5, 5, 201)
yy = 0.5 * (xx - 0.22) + np.random.normal(scale=0.01, size=len(xx))
result1 = model.fit(yy, params=params, x=xx, method=method)
result2 = ModelResult(model, Parameters())
result2.loads(result1.dumps(), funcdefs={'mfunc': mfunc})
result3 = ModelResult(model, Parameters())
result3.loads(result2.dumps(), funcdefs={'mfunc': mfunc})
assert result3 is not None
assert_param_between(result2.params['a'], 0.48, 0.52)
assert_param_between(result2.params['b'], 0.20, 0.25)
assert_param_between(result3.params['a'], 0.48, 0.52)
assert_param_between(result3.params['b'], 0.20, 0.25)
def test_saveload_modelresult_roundtrip():
"""Test for modelresult.loads()/dumps() and repeating that"""
def mfunc(x, a, b):
return a * (x-b)
model = Model(mfunc)
params = model.make_params(a=0.0, b=3.0)
xx = np.linspace(-5, 5, 201)
yy = 0.5 * (xx - 0.22) + np.random.normal(scale=0.01, size=len(xx))
result1 = model.fit(yy, params, x=xx)
result2 = ModelResult(model, Parameters())
result2.loads(result1.dumps(), funcdefs={'mfunc': mfunc})
result3 = ModelResult(model, Parameters())
result3.loads(result2.dumps(), funcdefs={'mfunc': mfunc})
assert result3 is not None
assert_param_between(result2.params['a'], 0.48, 0.52)
assert_param_between(result2.params['b'], 0.20, 0.25)
assert_param_between(result3.params['a'], 0.48, 0.52)
assert_param_between(result3.params['b'], 0.20, 0.25)
def check_fit_results(result):
"""Check the result of optimization."""
assert result.nvarys == 8
assert_between(result.chisqr, 1000, 1500)
assert_between(result.aic, 400, 450)
pars = result.params
assert_param_between(pars['exp_decay'], 90, 92)
assert_param_between(pars['exp_amplitude'], 98, 101)
assert_param_between(pars['g1_sigma'], 16, 17)
assert_param_between(pars['g1_center'], 106, 109)
assert_param_between(pars['g1_amplitude'], 4100, 4500)
assert_param_between(pars['g1_fwhm'], 38, 42)
assert_param_between(pars['g1_height'], 100, 103)
assert_param_between(pars['g2_sigma'], 10, 15)
assert_param_between(pars['g2_center'], 150, 160)
assert_param_between(pars['g2_amplitude'], 2100, 2900)
assert_param_between(pars['g2_fwhm'], 30, 34)
assert_param_between(pars['g2_height'], 70, 75)
def test_saveload_usersyms():
"""Test save/load of modelresult with non-trivial user symbols,
this example uses a VoigtModel, wheree `wofz()` is used in a
constraint expression"""
x = np.linspace(0, 20, 501)
y = gaussian(x, 1.1, 8.5, 2) + lorentzian(x, 1.7, 8.5, 1.5)
np.random.seed(20)
y = y + np.random.normal(size=len(x), scale=0.025)
model = VoigtModel()
pars = model.guess(y, x=x)
result = model.fit(y, pars, x=x)
savefile = 'tmpvoigt_modelresult.sav'
save_modelresult(result, savefile)
assert_param_between(result.params['sigma'], 0.7, 2.1)
assert_param_between(result.params['center'], 8.4, 8.6)
assert_param_between(result.params['height'], 0.2, 1.0)
time.sleep(0.25)
result2 = load_modelresult(savefile)
assert_param_between(result2.params['sigma'], 0.7, 2.1)
assert_param_between(result2.params['center'], 8.4, 8.6)
assert_param_between(result2.params['height'], 0.2, 1.0)
def check_fit_results(result):
"""Check the result of optimization."""
assert result.nvarys == 8
assert_between(result.chisqr, 1000, 1500)
assert_between(result.aic, 400, 450)
pars = result.params
assert_param_between(pars['exp_decay'], 90, 92)
assert_param_between(pars['exp_amplitude'], 98, 101)
assert_param_between(pars['g1_sigma'], 16, 17)
assert_param_between(pars['g1_center'], 106, 109)
assert_param_between(pars['g1_amplitude'], 4100, 4500)
assert_param_between(pars['g1_fwhm'], 38, 42)
assert_param_between(pars['g1_height'], 100, 103)
assert_param_between(pars['g2_sigma'], 10, 15)
assert_param_between(pars['g2_center'], 150, 160)
assert_param_between(pars['g2_amplitude'], 2100, 2900)
assert_param_between(pars['g2_fwhm'], 30, 34)
assert_param_between(pars['g2_height'], 70, 75)