Enh: draw std of cf.data (only cortical profiles). Fix: cf.data missing brackets

Author: AhmetNSimsek

siibra/features/feature.py

@@ -792,7 +792,7 @@ def _get_merged_feature(self) -> Feature:
 
     @property
     def data(self):
-        return self._get_merged_feature.data
+        return self._get_merged_feature().data
 
     @property
     def indexing_attributes(self) -> Tuple[str]:

siibra/features/tabular/cortical_profile.py

@@ -161,9 +161,11 @@ def _layers(self):
     def data(self):
         """Return a pandas Series representing the profile."""
         self._check_sanity()
-        return pd.DataFrame(
-            self._values, index=self._depths, columns=[f"{self.modality} ({self.unit})"]
-        )
+        if self._values.shape[1] == 2:
+            columns = [f"{self.modality} mean ({self.unit})", "std"]
+        else:
+            columns = [f"{self.modality} ({self.unit})"]
+        return pd.DataFrame(self._values, index=self._depths, columns=columns)
 
     @classmethod
     def _merge_elements(
@@ -175,12 +177,13 @@ def _merge_elements(
     ):
         assert all(np.array_equal(elements[0]._depths, f._depths) for f in elements)
         assert len({f.unit for f in elements}) == 1
+        values_stacked = np.stack([f._values for f in elements])
         return CorticalProfile(
             description=description,
             modality=modality,
             anchor=anchor,
-            depths=elements[0]._depths,
-            values=np.stack([f._values for f in elements]).mean(0),
+            depths=np.stack([f._depths for f in elements]).mean(0),
+            values=np.stack([values_stacked.mean(0), values_stacked.std(0)]).T,
             unit=elements[0].unit,
             boundary_positions=None,
         )
@@ -202,11 +205,14 @@ def plot(self, *args, backend="matplotlib", **kwargs):
         kwargs["title"] = kwargs.get("title", "\n".join(wrap(self.name, wrapwidth)))
         layercolor = kwargs.pop("layercolor", "gray")
 
+        ymax = max(0, self._values.max() if self._values.shape[1] == 1 else self._values[:, 0].max() + self._values[:, 1].max())
         if backend == "matplotlib":
+            if self._values.shape[1] == 2:
+                kwargs["yerr"] = kwargs.get("yerr", "std")
             kwargs["xlabel"] = kwargs.get("xlabel", "Cortical depth")
             kwargs["ylabel"] = kwargs.get("ylabel", self.unit)
             kwargs["grid"] = kwargs.get("grid", True)
-            kwargs["ylim"] = kwargs.get("ylim", (0, max(self._values)))
+            kwargs["ylim"] = kwargs.get("ylim", ymax),
             axs = self.data.plot(*args, **kwargs, backend=backend)
 
             if self.boundaries_mapped:
@@ -225,6 +231,8 @@ def plot(self, *args, backend="matplotlib", **kwargs):
             axs.set_title(axs.get_title(), fontsize="medium")
             return axs
         elif backend == "plotly":
+            if self._values.shape[1] == 2:
+                kwargs["error_y"] = kwargs.get("error_y", "std")
             kwargs["title"] = kwargs["title"].replace("\n", "<br>")
             kwargs["labels"] = {
                 "index": kwargs.pop("xlabel", None) or kwargs.pop("index", "Cortical depth"),
@@ -241,7 +249,7 @@ def plot(self, *args, backend="matplotlib", **kwargs):
                     )
             fig.update_layout(
                 showlegend=False,
-                yaxis_range=(0, max(self._values)),
+                yaxis_range=(0, ymax),
                 title=dict(
                     automargin=True, yref="container", xref="container",
                     pad=dict(t=40), xanchor="left", yanchor="top"