locked, unlock

src/pint/models/parameter.py

@@ -1974,11 +1974,17 @@ def select_toa_mask(self, toas):
 
     def cache_toa_mask(self, toas):
         """Cache the TOA mask for this parameter. This will lead to exceptions and/or
-        wrong results if the TOAs object is mutated after this.
+        wrong results if the TOAs object is mutated after this. This can be undone using
+        the `clear_toa_mask_cache()` method.
         """
         self.__cache_mask = self.select_toa_mask(toas)
         self.__cache_toas = toas
 
+    def clear_toa_mask_cache(self):
+        """Clear the TOA mask cache. This will undo a `cache_toa_mask()` call."""
+        self.__cache_mask = None
+        self.__cache_toas = None
+
     def compare_key_value(self, other_param):
         """Compare if the key and value are the same with the other parameter.
 

src/pint/models/timing_model.py

@@ -499,6 +499,11 @@ def lock(self, toas):
             "undefined behavior if the TOAs object is mutated after this."
         )
 
+        if (toas.get_errors() == 0).any():
+            raise ValueError(
+                "Model cannot be locked since some TOAs have zero uncertainties."
+            )
+
         self.__locked = True
         self.__lock_toas = toas
 
@@ -507,6 +512,19 @@ def lock(self, toas):
             if mpar.key is not None:
                 mpar.cache_toa_mask(toas)
 
+    @property
+    def locked(self):
+        return self.__locked
+
+    def unlock(self):
+        self.__locked = False
+        self.__lock_toas = None
+
+        for mp in self.get_params_of_type_top("maskParameter"):
+            mpar = getattr(self, mp)
+            if mpar.key is not None:
+                mpar.clear_toa_mask_cache()
+
     def __getattr__(self, name):
         if name in ["components", "component_types", "search_cmp_attr"]:
             raise AttributeError
@@ -1451,15 +1469,15 @@ def scaled_toa_uncertainty(self, toas):
         """
         ntoa = toas.ntoas
         tbl = toas.table
-        result = np.zeros(ntoa) * u.us
+        result = np.zeros(ntoa)
+
         # When there is no noise model.
         if len(self.scaled_toa_uncertainty_funcs) == 0:
-            result += tbl["error"].quantity
-            return result
+            return tbl["error"].quantity.to(u.us)
 
         for nf in self.scaled_toa_uncertainty_funcs:
-            result += nf(toas)
-        return result
+            result += nf(toas).to_value(u.us)
+        return result << u.us
 
     def scaled_dm_uncertainty(self, toas):
         """Get the scaled DM data uncertainties noise models.

tests/test_mask_cache.py

@@ -1,6 +1,7 @@
 from pinttestdata import datadir
 from pint.models import get_model_and_toas
 from pint.residuals import Residuals
+import pytest
 
 
 def test_mask_cache():
@@ -12,8 +13,14 @@ def test_mask_cache():
     chi2_1 = res1.calc_chi2()
 
     model.lock(toas)
-
     res2 = Residuals(toas, model)
     chi2_2 = res2.calc_chi2()
-
     assert chi2_1 == chi2_2
+
+    model.unlock()
+    chi2_3 = res1.calc_chi2()
+    assert chi2_1 == chi2_3
+
+    toas.table["error"][0] = 0
+    with pytest.raises(ValueError):
+        model.lock(toas)