Moved CompositeState and friends to dedicated file. Ran black.

docs/source/fun_figs.py

@@ -6,8 +6,9 @@
 
 sns.set_style("whitegrid")
 
+
 # %% Banana distribution plot
-def banana_plot(ax = None):
+def banana_plot(ax=None):
     N = 500
     x0 = nav.lib.SE2State([0.3, 3, 4], direction="right")
     covariance = np.diag([0.2**2, 0.05**2, 0.05**2])
@@ -38,15 +39,22 @@ def banana_plot(ax = None):
 
         # random greyscale color
         color = np.random.uniform(0.3, 0.9)
-        ax.plot(traj_pos[:, 0], traj_pos[:, 1], color=(color, color, color),zorder=1)
+        ax.plot(
+            traj_pos[:, 0],
+            traj_pos[:, 1],
+            color=(color, color, color),
+            zorder=1,
+        )
 
         # save the final state
         final_states.append(x_traj[-1])
-    
+
     final_positions = np.array([x.position for x in final_states])
-    ax.scatter(final_positions[:, 0], final_positions[:, 1], color="C0", zorder=2)
+    ax.scatter(
+        final_positions[:, 0], final_positions[:, 1], color="C0", zorder=2
+    )
 
-    # Propagate the mean with EKF 
+    # Propagate the mean with EKF
     kf = nav.ExtendedKalmanFilter(process_model)
     x0_hat = nav.StateWithCovariance(x0, covariance)
 
@@ -59,10 +67,12 @@ def banana_plot(ax = None):
     ax.plot(mean_traj[:, 0], mean_traj[:, 1], color="r", zorder=3, linewidth=3)
     ax.set_aspect("equal")
 
+
 # banana_plot()
 
+
 # %%
-def pose3d_plot(ax = None):
+def pose3d_plot(ax=None):
     N = 500
     x0 = nav.lib.SE3State([0.3, 3, 4, 0, 0, 0], direction="right")
     process_model = nav.lib.BodyFrameVelocity(np.zeros(6))
@@ -78,24 +88,27 @@ def pose3d_plot(ax = None):
         x = process_model.evaluate(x, u, dt)
         x_traj.append(x.copy())
 
-    fig, ax = nav.plot_poses(x_traj, ax = ax)
+    fig, ax = nav.plot_poses(x_traj, ax=ax)
 
 
 # pose3d_plot()
 
+
 # %%
-def three_sigma_plot(axs = None):
+def three_sigma_plot(axs=None):
     dataset = nav.lib.datasets.SimulatedPoseRangingDataset()
 
     estimates = nav.run_filter(
         nav.ExtendedKalmanFilter(dataset.process_model),
         dataset.get_ground_truth()[0],
         np.diag([0.1**2, 0.1**2, 0.1**2, 0.1**2, 0.1**2, 0.1**2]),
         dataset.get_input_data(),
-        dataset.get_measurement_data()
-        )
-
-    results = nav.GaussianResultList.from_estimates(estimates, dataset.get_ground_truth())
+        dataset.get_measurement_data(),
+    )
+
+    results = nav.GaussianResultList.from_estimates(
+        estimates, dataset.get_ground_truth()
+    )
 
     fig, axs = nav.plot_error(results[:, :3], axs=axs)
     axs[2].set_xlabel("Time (s)")
@@ -105,7 +118,6 @@ def three_sigma_plot(axs = None):
 
 
 if __name__ == "__main__":
-
     # Make one large figure which has all the plots. This will be a 1x3 grid, with the
     # last plot itself being a three vertically stacked plots.
 
@@ -119,13 +131,11 @@ def three_sigma_plot(axs = None):
 
     # which will be used here:
 
-
-
     fig = plt.figure(figsize=(20, 6))
     gs = fig.add_gridspec(1, 3, width_ratios=[1, 1, 1])
     ax1 = fig.add_subplot(gs[0])
-    ax2 = fig.add_subplot(gs[1], projection='3d')
-    
+    ax2 = fig.add_subplot(gs[1], projection="3d")
+
     # The last plot is a 3x1 grid
     gs2 = gs[2].subgridspec(3, 1, hspace=0.1)
     ax3 = fig.add_subplot(gs2[0])
@@ -141,25 +151,27 @@ def three_sigma_plot(axs = None):
     ax2.set_yticklabels([])
     ax2.set_zticklabels([])
 
-
     banana_plot(ax1)
     pose3d_plot(ax2)
     three_sigma_plot(np.array([ax3, ax4, ax5]))
 
-    # Set spacing to the above values 
+    # Set spacing to the above values
     fig.subplots_adjust(
         top=0.975,
         bottom=0.097,
         left=0.025,
         right=0.992,
         hspace=0.2,
-        wspace=0.117
+        wspace=0.117,
     )
 
-
     # Save the figure with transparent background, next to this file
-    import os 
-    fig.savefig(os.path.join(os.path.dirname(__file__), "fun_figs.png"), transparent=True)
+    import os
+
+    fig.savefig(
+        os.path.join(os.path.dirname(__file__), "fun_figs.png"),
+        transparent=True,
+    )
 
     plt.show()
 # %%

navlie/__init__.py

@@ -40,5 +40,11 @@
     jacobian,
 )
 
+from .composite import (
+    CompositeState,
+    CompositeProcessModel,
+    CompositeMeasurementModel,
+    CompositeInput,
+)
 
-from .lib.states import StampedValue # for backwards compatibility
+from .lib.states import StampedValue  # for backwards compatibility