def test_saveload_modelresult_exception():
"""Make sure the proper exceptions are raised when needed."""
model, _pars = create_model_params(x, y)
save_model(model, SAVE_MODEL)
with pytest.raises(AttributeError, match=r'needs saved ModelResult'):
load_modelresult(SAVE_MODEL)
clear_savefile(SAVE_MODEL)
def test_saveload_modelresult_exception():
"""Make sure the proper exceptions are raised when needed."""
model, _pars = create_model_params(x, y)
save_model(model, SAVE_MODEL)
with pytest.raises(AttributeError, match=r'needs saved ModelResult'):
load_modelresult(SAVE_MODEL)
clear_savefile(SAVE_MODEL)
def do_save_model(with_dill=True):
x, y = XDAT, YDAT
if DILL_AVAILABLE and with_dill:
lmfit.jsonutils.HAS_DILL = True
else:
lmfit.jsonutils.HAS_DILL = False
model, params = create_model_params(x, y)
save_model(model, SAVE_MODEL)
file_exists = wait_for_file(SAVE_MODEL, timeout=10)
assert (file_exists)
text = ''
with open(SAVE_MODEL, 'r') as fh:
text = fh.read()
assert_between(len(text), 1000, 2500)
def test_save_load_model(dill):
"""Save/load Model with/without dill."""
if dill:
pytest.importorskip("dill")
else:
lmfit.jsonutils.HAS_DILL = False
# create/save Model and perform some tests
model, _pars = create_model_params(x, y)
save_model(model, SAVE_MODEL)
file_exists = wait_for_file(SAVE_MODEL, timeout=10)
assert file_exists
with open(SAVE_MODEL, 'r') as fh:
text = fh.read()
assert 1000 < len(text) < 2500
# load the Model, perform fit and assert results
saved_model = load_model(SAVE_MODEL)
params = saved_model.make_params()
params['exp_decay'].set(100)
params['exp_amplitude'].set(100)
params['g1_center'].set(105, min=75, max=125)
params['g1_sigma'].set(15, min=3)
params['g1_amplitude'].set(2000, min=10)
params['g2_center'].set(155, min=125, max=175)
params['g2_sigma'].set(15, min=3)
params['g2_amplitude'].set(2000, min=10)
result = saved_model.fit(y, params, x=x)
check_fit_results(result)
clear_savefile(SAVE_MODEL)
def test_save_load_model(dill):
"""Save/load Model with/without dill."""
if dill:
pytest.importorskip("dill")
else:
lmfit.jsonutils.HAS_DILL = False
# create/save Model and perform some tests
model, _pars = create_model_params(x, y)
save_model(model, SAVE_MODEL)
file_exists = wait_for_file(SAVE_MODEL, timeout=10)
assert file_exists
with open(SAVE_MODEL, 'r') as fh:
text = fh.read()
assert 1000 < len(text) < 2500
# load the Model, perform fit and assert results
saved_model = load_model(SAVE_MODEL)
params = saved_model.make_params()
params['exp_decay'].set(100)
params['exp_amplitude'].set(100)
params['g1_center'].set(105, min=75, max=125)
params['g1_sigma'].set(15, min=3)
params['g1_amplitude'].set(2000, min=10)
params['g2_center'].set(155, min=125, max=175)
params['g2_sigma'].set(15, min=3)
params['g2_amplitude'].set(2000, min=10)
result = saved_model.fit(y, params, x=x)
check_fit_results(result)
clear_savefile(SAVE_MODEL)
# <examples/doc_model_savemodel.py>
import numpy as np
from lmfit.model import Model, save_model
def mysine(x, amp, freq, shift):
return amp * np.sin(x * freq + shift)
sinemodel = Model(mysine)
pars = sinemodel.make_params(amp=1, freq=0.25, shift=0)
save_model(sinemodel, 'sinemodel.sav')
# <end examples/doc_model_savemodel.py>
#!/usr/bin/env python
# <examples/doc_mode_savemodel.py>
import numpy as np
from lmfit.model import Model, save_model
def mysine(x, amp, freq, shift):
return amp * np.sin(x*freq + shift)
sinemodel = Model(mysine)
pars = sinemodel.make_params(amp=1, freq=0.25, shift=0)
save_model(sinemodel, 'sinemodel.sav')
# <end examples/doc_model_savemodel.py>