Revert some of copilots work

Author: arm61

kinisi/fitting.py

@@ -181,7 +181,7 @@ def prior_transform(self, parameters: tuple[float]) -> tuple[float]:
             x[i] = self.priors[i].ppf(parameters[i])
         return x
 
-    def max_likelihood(self):
+    def max_likelihood(self) -> None:
         """Find the max likelihood fit parameters for the model."""
         if self.priors is not None:
             x0 = [p.mean() for p in self.priors]
@@ -191,7 +191,7 @@ def max_likelihood(self):
         for i, name in enumerate(self.parameter_names):
             self.data_group[name] = result[i] * self.parameter_units[i]
 
-    def max_aposteriori(self):
+    def max_aposteriori(self) -> None:
         """Find the max aposteriori fit parameters for the model."""
         if self.priors is not None:
             x0 = [p.mean() for p in self.priors]

kinisi/tests/test_yeh_hummer.py

@@ -106,7 +106,7 @@ def test_yeh_hummer_priors(self):
         # Custom priors
         priors = (
             uniform(4e-5, 7e-5),  # D_0 prior
-            uniform(1e-4, 1e-2),  # viscosity prior
+            uniform(1e-4, 1e-2),  # slope prior
         )
 
         yh = YehHummer(td, temperature=sc.scalar(298, unit='K'), priors=priors)

kinisi/yeh_hummer.py

@@ -41,8 +41,8 @@ class YehHummer(FittingBase):
 
     :param diffusion: sc.DataArray with diffusion coefficients and box_length coordinate
     :param temperature: Temperature (will be extracted from coords if not provided)
-    :param priors: Optional priors for [D_0, viscosity] parameters using scipy.stats objects
-        (viscosity in Pa*s)
+    :param priors: Optional priors for [D_0, viscosity] parameters using scipy.stats objects,
+        where viscosity has units Pa*s.
     """
 
     def __init__(self, diffusion, temperature: sc.Variable, priors=None):
@@ -65,7 +65,7 @@ def __init__(self, diffusion, temperature: sc.Variable, priors=None):
         # Compute priors: use provided or defaults
         if priors is None:
             D_max = np.max(diffusion.values)
-            D_prior = uniform(D_max * 0.8, (D_max * 2.0) - (D_max - 0.8))
+            D_prior = uniform(D_max * 0.8, D_max * 1.2)
             visc_lower, visc_upper = 1e-5 * sc.Unit('Pa*s'), 1e-1 * sc.Unit('Pa*s')
 
             # Higher viscosity = lower slope, so bounds are inverted