Evaluate blueice_anchors expression

alea/examples/configs/unbinned_wimp_statistical_model_template_source_test.yaml

@@ -54,12 +54,7 @@ parameter_definition:
     uncertainty: 'stats.uniform(loc=-2, scale=4)'
     # relative_uncertainty: false
     fittable: true
-    blueice_anchors:
-      - -2
-      - -1
-      - 0
-      - 1
-      - 2
+    blueice_anchors: 'np.arange(-2, 3)'
     fit_limits:
       - -2
       - 2

alea/parameters.py

@@ -41,7 +41,7 @@ def __init__(
         ptype: Optional[str] = None,
         uncertainty: Optional[Union[float, str]] = None,
         relative_uncertainty: Optional[bool] = None,
-        blueice_anchors: Optional[List] = None,
+        blueice_anchors: Optional[Union[list, str]] = None,
         fit_limits: Optional[Tuple] = None,
         parameter_interval_bounds: Optional[Tuple[float, float]] = None,
         fit_guess: Optional[float] = None,
@@ -95,6 +95,22 @@ def uncertainty(self, value: Optional[Union[float, str]]) -> None:
                 )
         self._uncertainty = value
 
+    @property
+    def blueice_anchors(self) -> Any:
+        """Return the blueice_anchors of the parameter.
+
+        If the blueice_anchors is a string, it will be evaluated as a numpy or scipy function.
+
+        """
+        if isinstance(self._blueice_anchors, str):
+            return evaluate_numpy_scipy_expression(self._blueice_anchors).tolist()
+        else:
+            return self._blueice_anchors
+
+    @blueice_anchors.setter
+    def blueice_anchors(self, value: Optional[Union[list, str]]) -> None:
+        self._blueice_anchors = value
+
     @property
     def fit_guess(self) -> Optional[float]:
         """Return the initial guess for fitting the parameter."""