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Merged
Parent: Preparation for 2.0.0 release
merged 2 commits into from
Sep 2, 2024
Merged

Add support lmfit scipy least square #70

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b922c8f
added support for scipy least square
andped10 Sep 2, 2024
b9e1f25
fix to tests
andped10 Sep 2, 2024
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3 changes: 3 additions & 0 deletions src/easyscience/fitting/available_minimizers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -39,6 +39,7 @@ class AvailableMinimizers(Enum):
LMFit_powell = auto()
LMFit_cobyla = auto()
LMFit_differential_evolution = auto()
LMFit_scipy_least_squares = auto()

if bumps_engine_available:
Bumps = auto()
Expand All @@ -63,6 +64,8 @@ def from_string_to_enum(minimizer_name: str) -> AvailableMinimizers:
minmizer_enum = AvailableMinimizers.LMFit_cobyla
elif minimizer_name == 'LMFit_differential_evolution':
minmizer_enum = AvailableMinimizers.LMFit_differential_evolution
elif minimizer_name == 'LMFit_scipy_least_squares':
minmizer_enum = AvailableMinimizers.LMFit_scipy_least_squares

elif minimizer_name == 'Bumps':
minmizer_enum = AvailableMinimizers.Bumps
Expand Down
2 changes: 2 additions & 0 deletions src/easyscience/fitting/minimizers/factory.py
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Expand Up @@ -23,6 +23,8 @@ def factory(minimizer_enum: AvailableMinimizers, fit_object, fit_function: Calla
minimizer = LMFit(obj=fit_object, fit_function=fit_function, method='cobyla')
elif minimizer_enum == AvailableMinimizers.LMFit_differential_evolution:
minimizer = LMFit(obj=fit_object, fit_function=fit_function, method='differential_evolution')
elif minimizer_enum == AvailableMinimizers.LMFit_scipy_least_squares:
minimizer = LMFit(obj=fit_object, fit_function=fit_function, method='least_squares')

elif minimizer_enum == AvailableMinimizers.Bumps:
minimizer = Bumps(obj=fit_object, fit_function=fit_function, method='amoeba')
Expand Down
7 changes: 4 additions & 3 deletions tests/unit_tests/Fitting/minimizers/test_factory.py
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Expand Up @@ -12,7 +12,7 @@ def pull_minminizer(self, minimizer: AvailableMinimizers) -> MinimizerBase:
minimizer = factory(minimizer, mock_fit_object, mock_fit_function)
return minimizer

@pytest.mark.parametrize('minimizer_method,minimizer_enum', [('leastsq', AvailableMinimizers.LMFit), ('leastsq', AvailableMinimizers.LMFit_leastsq), ('powell', AvailableMinimizers.LMFit_powell), ('cobyla', AvailableMinimizers.LMFit_cobyla)])
@pytest.mark.parametrize('minimizer_method,minimizer_enum', [('leastsq', AvailableMinimizers.LMFit), ('leastsq', AvailableMinimizers.LMFit_leastsq), ('powell', AvailableMinimizers.LMFit_powell), ('cobyla', AvailableMinimizers.LMFit_cobyla), ('differential_evolution', AvailableMinimizers.LMFit_differential_evolution), ('least_squares', AvailableMinimizers.LMFit_scipy_least_squares)])
def test_factory_lm_fit(self, minimizer_method, minimizer_enum):
minimizer = self.pull_minminizer(minimizer_enum)
assert minimizer._method == minimizer_method
Expand All @@ -31,7 +31,7 @@ def test_factory_dfo_fit(self, minimizer_method, minimizer_enum):
assert minimizer.wrapping == 'dfo'


@pytest.mark.parametrize('minimizer_name,expected', [('LMFit', AvailableMinimizers.LMFit), ('LMFit_leastsq', AvailableMinimizers.LMFit_leastsq), ('LMFit_powell', AvailableMinimizers.LMFit_powell), ('LMFit_cobyla', AvailableMinimizers.LMFit_cobyla), ])
@pytest.mark.parametrize('minimizer_name,expected', [('LMFit', AvailableMinimizers.LMFit), ('LMFit_leastsq', AvailableMinimizers.LMFit_leastsq), ('LMFit_powell', AvailableMinimizers.LMFit_powell), ('LMFit_cobyla', AvailableMinimizers.LMFit_cobyla), ('LMFit_differential_evolution', AvailableMinimizers.LMFit_differential_evolution), ('LMFit_scipy_least_squares', AvailableMinimizers.LMFit_scipy_least_squares) ])
def test_from_string_to_enum_lmfit(minimizer_name, expected):
assert from_string_to_enum(minimizer_name) == expected

Expand All @@ -52,10 +52,11 @@ def test_available_minimizers():
assert AvailableMinimizers.LMFit_powell
assert AvailableMinimizers.LMFit_cobyla
assert AvailableMinimizers.LMFit_differential_evolution
assert AvailableMinimizers.LMFit_scipy_least_squares
assert AvailableMinimizers.Bumps
assert AvailableMinimizers.Bumps_simplex
assert AvailableMinimizers.Bumps_newton
assert AvailableMinimizers.Bumps_lm
assert AvailableMinimizers.DFO
assert AvailableMinimizers.DFO_leastsq
assert len(AvailableMinimizers) == 11
assert len(AvailableMinimizers) == 12
9 changes: 4 additions & 5 deletions tests/unit_tests/Fitting/minimizers/test_minimizer_lmfit.py
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Expand Up @@ -3,7 +3,6 @@
from unittest.mock import MagicMock

import easyscience.fitting.minimizers.minimizer_lmfit
from easyscience.fitting import AvailableMinimizers
from easyscience.fitting.minimizers.minimizer_lmfit import LMFit
from easyscience.Objects.new_variable import Parameter
from lmfit import Parameter as LMParameter
Expand All @@ -16,7 +15,7 @@ def minimizer(self) -> LMFit:
minimizer = LMFit(
obj='obj',
fit_function='fit_function',
method='least_squares'
method='leastsq'
)
return minimizer

Expand Down Expand Up @@ -99,7 +98,7 @@ def test_fit(self, minimizer: LMFit) -> None:

# Expect
assert result == 'gen_fit_results'
mock_model.fit.assert_called_once_with(2.0, x=1.0, weights=0.7071067811865475, method='least_squares')
mock_model.fit.assert_called_once_with(2.0, x=1.0, weights=0.7071067811865475, method='leastsq')
minimizer._make_model.assert_called_once_with()
minimizer._set_parameter_fit_result.assert_called_once_with('fit', False)
minimizer._gen_fit_results.assert_called_once_with('fit')
Expand All @@ -116,7 +115,7 @@ def test_fit_model(self, minimizer: LMFit) -> None:
minimizer.fit(x=1.0, y=2.0, model=mock_model)

# Expect
mock_model.fit.assert_called_once_with(2.0, x=1.0, weights=0.7071067811865475, method='least_squares')
mock_model.fit.assert_called_once_with(2.0, x=1.0, weights=0.7071067811865475, method='leastsq')
minimizer._make_model.assert_not_called()

def test_fit_method(self, minimizer: LMFit) -> None:
Expand Down Expand Up @@ -148,7 +147,7 @@ def test_fit_kwargs(self, minimizer: LMFit) -> None:
minimizer.fit(x=1.0, y=2.0, minimizer_kwargs={'minimizer_key': 'minimizer_val'}, engine_kwargs={'engine_key': 'engine_val'})

# Expect
mock_model.fit.assert_called_once_with(2.0, x=1.0, weights=0.7071067811865475, method='least_squares', fit_kws={'minimizer_key': 'minimizer_val'}, engine_key='engine_val')
mock_model.fit.assert_called_once_with(2.0, x=1.0, weights=0.7071067811865475, method='leastsq', fit_kws={'minimizer_key': 'minimizer_val'}, engine_key='engine_val')

def test_fit_exception(self, minimizer: LMFit) -> None:
# When
Expand Down
2 changes: 1 addition & 1 deletion tests/unit_tests/Fitting/test_fitter.py
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Expand Up @@ -166,7 +166,7 @@ def test_available_minimizers(self, fitter: Fitter):

# Then Expect
assert minimizers == [
'LMFit', 'LMFit_leastsq', 'LMFit_powell', 'LMFit_cobyla', 'LMFit_differential_evolution',
'LMFit', 'LMFit_leastsq', 'LMFit_powell', 'LMFit_cobyla', 'LMFit_differential_evolution', 'LMFit_scipy_least_squares',
'Bumps', 'Bumps_simplex', 'Bumps_newton', 'Bumps_lm',
'DFO', 'DFO_leastsq'
]
Expand Down