review

Author: dweindl

petab/v2/core.py

@@ -73,8 +73,11 @@ def _not_nan(v: float, info: ValidationInfo) -> float:
 
 
 def _convert_nan_to_none(v):
+    """Convert NaN or "" to None."""
     if isinstance(v, float) and np.isnan(v):
         return None
+    if isinstance(v, str) and v == "":
+        return None
     return v
 
 
@@ -503,12 +506,17 @@ class ExperimentPeriod(BaseModel):
     @field_validator("condition_ids", mode="before")
     @classmethod
     def _validate_ids(cls, condition_ids):
-        if condition_ids in [None, []]:
+        if condition_ids in [None, "", [], [""]]:
+            # unspecified, or "use-model-as-is"
             return []
 
         for condition_id in condition_ids:
-            if is_valid_identifier(condition_id):
-                raise ValueError(f"Invalid ID: `{condition_id}'")
+            # The empty condition ID for "use-model-as-is" has been handled
+            #  above. Having a combination of empty and non-empty IDs is an
+            #  error, since the targets of conditions to be combined must be
+            #  disjoint.
+            if not is_valid_identifier(condition_id):
+                raise ValueError(f"Invalid {C.CONDITION_ID}: `{condition_id}'")
         return condition_ids
 
 
@@ -899,7 +907,7 @@ def _validate_id(cls, v):
     @field_validator("prior_parameters", mode="before")
     @classmethod
     def _validate_prior_parameters(cls, v):
-        if pd.isna(v):
+        if isinstance(v, float) and np.isnan(v):
             return []
 
         if isinstance(v, str):
@@ -969,7 +977,7 @@ def _validate(self) -> Self:
 
     @property
     def prior_dist(self) -> Distribution:
-        """Get the pior distribution of the parameter."""
+        """Get the prior distribution of the parameter."""
         if self.estimate is False:
             raise ValueError(f"Parameter `{self.id}' is not estimated.")
 
@@ -997,6 +1005,13 @@ def prior_dist(self) -> Distribution:
                     "transformation."
                 )
             return cls(*self.prior_parameters, trunc=[self.lb, self.ub])
+
+        if cls == Uniform:
+            # `Uniform.__init__` does not accept the `trunc` parameter
+            low = max(self.prior_parameters[0], self.lb)
+            high = min(self.prior_parameters[1], self.ub)
+            return cls(low, high, log=log)
+
         return cls(*self.prior_parameters, log=log, trunc=[self.lb, self.ub])
 
 

petab/v2/lint.py

@@ -817,7 +817,17 @@ def run(self, problem: Problem) -> ValidationIssue | None:
                     f"({parameter.prior_parameters})."
                 )
 
-            # TODO: check distribution parameter domains
+            # TODO: check distribution parameter domains more specifically
+            try:
+                if parameter.estimate:
+                    # .prior_dist fails for non-estimated parameters
+                    _ = parameter.prior_dist.sample(1)
+            except Exception as e:
+                messages.append(
+                    f"Prior parameters `{parameter.prior_parameters}' "
+                    f"for parameter `{parameter.id}' are invalid "
+                    f"(hint: {e})."
+                )
 
         if messages:
             return ValidationError("\n".join(messages))

petab/v2/problem.py

@@ -1121,8 +1121,8 @@ def model_dump(self, **kwargs) -> dict[str, Any]:
                          'id': 'par',
                          'lb': 0.0,
                          'nominal_value': None,
-                         'prior_distribution': None,
-                         'prior_parameters': [],
+                         'prior_distribution': '',
+                         'prior_parameters': '',
                          'ub': 1.0}]}
         """
         res = {

tests/v2/test_core.py

@@ -212,7 +212,7 @@ def test_period():
     with pytest.raises(ValidationError, match="got inf"):
         ExperimentPeriod(time="inf", condition_ids=["p1"])
 
-    with pytest.raises(ValidationError, match="Invalid ID"):
+    with pytest.raises(ValidationError, match="Invalid conditionId"):
         ExperimentPeriod(time=1, condition_ids=["1_condition"])
 
     with pytest.raises(ValidationError, match="type=missing"):