Morris analysis

corrai/base/sampling.py

@@ -75,14 +75,7 @@ def get_parameters_intervals(self):
     def get_list_parameter_value_pairs(
         self, idx: int | list[int] | np.ndarray | slice = None
     ):
-        idx = slice(None) if idx is None else idx
-
-        if isinstance(idx, int) or (
-            isinstance(idx, list) and all(isinstance(x, bool) for x in idx)
-        ):
-            idx = np.array(idx)
-
-        selected_values = self.values[idx]
+        selected_values = self[idx]["values"]
 
         if selected_values.ndim == 1:
             selected_values = selected_values[np.newaxis, :]
@@ -92,6 +85,13 @@ def get_list_parameter_value_pairs(
             for row in selected_values
         ]
 
+    def get_dimension_less_values(
+        self, idx: int | list[int] | np.ndarray | slice = slice(None)
+    ):
+        values = self[idx]["values"]
+        intervals = self.get_parameters_intervals()
+        return (values - intervals[:, 0]) / (intervals[:, 1] - intervals[:, 0])
+
     def add_samples(self, values: np.ndarray, results: list[pd.DataFrame] = None):
         n_samples, n_params = values.shape
         assert n_params == len(self.parameters), "Mismatch in number of parameters"
@@ -106,6 +106,34 @@ def add_samples(self, values: np.ndarray, results: list[pd.DataFrame] = None):
 
         self.results = pd.concat([self.results, new_results], ignore_index=True)
 
+    def plot(
+        self,
+        indicator: str | None = None,
+        reference_timeseries: pd.Series | None = None,
+        title: str | None = None,
+        y_label: str | None = None,
+        x_label: str | None = None,
+        alpha: float = 0.5,
+        show_legends: bool = False,
+        round_ndigits: int = 2,
+    ) -> go.Figure:
+        if self.results is None:
+            raise ValueError("No results available to plot. Run a simulation first.")
+
+        return plot_sample(
+            results=self.results,
+            indicator=indicator,
+            reference_timeseries=reference_timeseries,
+            title=title,
+            y_label=y_label,
+            x_label=x_label,
+            alpha=alpha,
+            show_legends=show_legends,
+            parameter_values=self.values,
+            parameter_names=[p.name for p in self.parameters],
+            round_ndigits=round_ndigits,
+        )
+
 
 class Sampler(ABC):
     def __init__(
@@ -203,35 +231,6 @@ def get_aggregate_time_series(
             prefix,
         )
 
-    def plot_sample(
-        self,
-        indicator: str | None = None,
-        reference_timeseries: pd.Series | None = None,
-        title: str | None = None,
-        y_label: str | None = None,
-        x_label: str | None = None,
-        alpha: float = 0.5,
-        show_legends: bool = False,
-        round_ndigits: int = 2,
-    ) -> go.Figure:
-        if self.results is None:
-            raise ValueError("No results available to plot. Run a simulation first.")
-
-        return plot_sample(
-            results=self.results,
-            indicator=indicator,
-            reference_timeseries=reference_timeseries,
-            title=title,
-            y_label=y_label,
-            x_label=x_label,
-            alpha=alpha,
-            show_legends=show_legends,
-            parameter_values=self.values,
-            parameter_names=[p.name for p in self.parameters],
-            round_ndigits=round_ndigits,
-        )
-
-
 class RealSampler(Sampler, ABC):
     def __init__(
         self,
@@ -261,6 +260,7 @@ def __init__(
         self, parameters: list[Parameter], model: Model, simulation_options: dict = None
     ):
         super().__init__(parameters, model, simulation_options)
+        self._dimless_values = None
 
     def add_sample(
         self,