Optionally include measurements in plot_observable_trajectories (#2381

)

If some `ExpData` is provided, `plot_observable_trajectories` will now also visualize the measurements.

python/sdist/amici/plotting.py

@@ -12,6 +12,7 @@
 import seaborn as sns
 from matplotlib.axes import Axes
 
+import amici
 from . import Model, ReturnDataView
 from .numpy import StrOrExpr, evaluate
 
@@ -66,10 +67,11 @@ def plot_state_trajectories(
 
     for ix, label in zip(state_indices, labels):
         ax.plot(rdata["t"], rdata["x"][:, ix], marker=marker, label=label)
-        ax.set_xlabel("$t$")
-        ax.set_ylabel("$x(t)$")
-        ax.legend()
-        ax.set_title("State trajectories")
+
+    ax.set_xlabel("$t$")
+    ax.set_ylabel("$x(t)$")
+    ax.legend()
+    ax.set_title("State trajectories")
 
 
 def plot_observable_trajectories(
@@ -79,6 +81,7 @@ def plot_observable_trajectories(
     model: Model = None,
     prefer_names: bool = True,
     marker=None,
+    edata: Union[amici.ExpData, amici.ExpDataView] = None,
 ) -> None:
     """
     Plot observable trajectories.
@@ -97,8 +100,12 @@ def plot_observable_trajectories(
     :param marker:
         Point marker for plotting (see
         `matplotlib documentation <https://matplotlib.org/stable/api/markers_api.html>`_).
-
+    :param edata:
+        Experimental data to be plotted (no event observables yet).
     """
+    if isinstance(edata, amici.amici.ExpData):
+        edata = amici.ExpDataView(edata)
+
     if not ax:
         fig, ax = plt.subplots()
     if not observable_indices:
@@ -125,11 +132,30 @@ def plot_observable_trajectories(
         labels = np.asarray(rdata.ptr.observable_ids)[list(observable_indices)]
 
     for iy, label in zip(observable_indices, labels):
-        ax.plot(rdata["t"], rdata["y"][:, iy], marker=marker, label=label)
-        ax.set_xlabel("$t$")
-        ax.set_ylabel("$y(t)$")
-        ax.legend()
-        ax.set_title("Observable trajectories")
+        (l,) = ax.plot(
+            rdata["t"], rdata["y"][:, iy], marker=marker, label=label
+        )
+
+        if edata is not None:
+            ax.plot(
+                edata.ts,
+                edata.observedData[:, iy],
+                "x",
+                label=f"exp. {label}",
+                color=l.get_color(),
+            )
+            ax.errorbar(
+                edata.ts,
+                edata.observedData[:, iy],
+                yerr=rdata.sigmay[:, iy],
+                fmt="none",
+                color=l.get_color(),
+            )
+
+    ax.set_xlabel("$t$")
+    ax.set_ylabel("$y(t)$")
+    ax.set_title("Observable trajectories")
+    ax.legend()
 
 
 def plot_jacobian(rdata: ReturnDataView):