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Fix bounds handling in parametric regression fit_options #1677

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Fix bounds handling in parametric regression fit_options #1677

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6 changes: 5 additions & 1 deletion lifelines/fitters/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1948,6 +1948,9 @@ def _fit_model(
if _initial_point.shape[0] != Xs.columns.size:
raise ValueError("initial_point is not the correct shape.")

scipy_fit_options = {**self._scipy_fit_options, **fit_options}
bounds = scipy_fit_options.pop("bounds", getattr(self, "_bounds", None))

with warnings.catch_warnings():
warnings.simplefilter("ignore")
results = minimize(
Expand All @@ -1957,7 +1960,8 @@ def _fit_model(
method=self._scipy_fit_method,
jac=True,
args=(Ts, E, weights, entries, utils.DataframeSlicer(Xs)),
options={**{"disp": show_progress}, **self._scipy_fit_options, **fit_options},
bounds=bounds,
options={**{"disp": show_progress}, **scipy_fit_options},
callback=self._scipy_fit_callback,
)

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9 changes: 9 additions & 0 deletions lifelines/tests/test_estimation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2201,6 +2201,15 @@ def test_print_summary(self):
pew = PiecewiseExponentialRegressionFitter(breakpoints=[25, 40]).fit(df, "week", "arrest")
pew.print_summary()

def test_fit_options_bounds_are_passed_to_minimize(self):
df = pd.DataFrame({"T": [1.0, 2.0, 3.0, 4.0], "E": [1, 1, 0, 1]})
model = PiecewiseExponentialRegressionFitter(breakpoints=[2.0])
bounds = [(0.0, None)] * len(model._fitted_parameter_names)

fitted = model.fit(df, "T", "E", fit_options={"bounds": bounds})

assert fitted.params_.shape[0] == len(model._fitted_parameter_names)

def test_inference(self):

N, d = 80000, 2
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