fix(fitter): stop referencing removed detector_response module

fitter/model.py

@@ -11,13 +11,12 @@ Usage:
 
 from __future__ import annotations
 
-from typing import TYPE_CHECKING, Optional
+from typing import TYPE_CHECKING, Any, Optional
 
 import numpy as np
 
 if TYPE_CHECKING:
     from beta_spectrum.spectrum import BetaSpectrum
-    from beta_spectrum.components.detector_response import DetectorResponse
     from exp_data.spectrum import ExpSpectrum
 
 
@@ -39,8 +38,11 @@ class SpectrumModel:
     ----------
     spectrum : BetaSpectrum
         Theoretical spectrum calculator.
-    detector_response : DetectorResponse, optional
-        Detector response function. If None, no convolution is applied.
+    detector_response : optional
+        Detector response object exposing ``channel_energies`` and
+        ``convolve`` (duck-typed: the DetectorResponse module was removed
+        from beta_spectrum and is pending a restore-or-delete decision).
+        If None, no convolution is applied.
     channel_energies : np.ndarray, optional
         Energy values for detector channels (keV). Used to set up
         the response if detector_response is None.
@@ -49,7 +51,7 @@ class SpectrumModel:
     def __init__(
         self,
         spectrum: "BetaSpectrum",
-        detector_response: Optional["DetectorResponse"] = None,
+        detector_response: Optional[Any] = None,
         channel_energies: Optional[np.ndarray] = None,
     ):
         self.spectrum = spectrum
@@ -79,11 +81,10 @@ class SpectrumModel:
         if energies_keV is not None:
             W = self._keV_to_W(energies_keV)
             return self.spectrum(W)
-        return self.spectrum(
-            self.spectrum._W_grid
-            if hasattr(self.spectrum, "_W_grid") and self.spectrum._W_grid is not None
-            else np.array([])
-        )
+        w_grid = getattr(self.spectrum, "_W_grid", None)
+        if w_grid is None:
+            return np.array([], dtype=np.float64)
+        return self.spectrum(w_grid)
 
     def _keV_to_W(self, energies_keV: np.ndarray) -> np.ndarray:
         """Convert kinetic energy in keV to total energy in m_e units."""