Merge pull request #50 from larshinueber/feature/update-interfaces

Use recommended interfaces for body creation, result retrieval and imports

estimation/covariance_estimated_parameters.py

@@ -69,8 +69,6 @@
 To create the systems of bodies for the simulation, one first has to define a list of strings of all bodies that are to be included. Note that the default body settings (such as atmosphere, body shape, rotation model) are taken from the `SPICE` kernel.
 
 These settings, however, can be adjusted. Please refer to the [Available Environment Models](https://tudat-space.readthedocs.io/en/latest/_src_user_guide/state_propagation/environment_setup/create_models/available.html#available-environment-models) in the user guide for more details.
-
-Finally, the system of bodies is created using the settings. This system of bodies is stored into the variable `bodies`.
 """
 
 # Create default body settings for "Sun", "Earth", "Moon", "Mars", and "Venus"
@@ -82,37 +80,43 @@
 body_settings = environment_setup.get_default_body_settings(
     bodies_to_create, global_frame_origin, global_frame_orientation)
 
-# Create system of bodies
-bodies = environment_setup.create_system_of_bodies(body_settings)
-
 
 ### Create the vehicle and its environment interface
 """
 We will now create the satellite - called Delfi-C3 - for which an orbit will be simulated. Using an `empty_body` as a blank canvas for the satellite, we define mass of 400kg, a reference area (used both for aerodynamic and radiation pressure) of 4m$^2$, and a aerodynamic drag coefficient of 1.2. Idem for the radiation pressure coefficient. Finally, when setting up the radiation pressure interface, the Earth is set as a body that can occult the radiation emitted by the Sun.
 """
 
-# Create vehicle objects.
-bodies.create_empty_body("Delfi-C3")
-bodies.get("Delfi-C3").mass = 2.2
+# Create empty body settings for the satellite
+body_settings.add_empty_settings("Delfi-C3")
+
+body_settings.get("Delfi-C3").constant_mass = 2.2
 
 # Create aerodynamic coefficient interface settings
-reference_area = (4*0.3*0.1+2*0.1*0.1)/4  # Average projection area of a 3U CubeSat
+reference_area_drag = (4*0.3*0.1+2*0.1*0.1)/4  # Average projection area of a 3U CubeSat
 drag_coefficient = 1.2
 aero_coefficient_settings = environment_setup.aerodynamic_coefficients.constant(
-    reference_area, [drag_coefficient, 0.0, 0.0]
+    reference_area_drag, [drag_coefficient, 0.0, 0.0]
 )
-# Add the aerodynamic interface to the environment
-environment_setup.add_aerodynamic_coefficient_interface(bodies, "Delfi-C3", aero_coefficient_settings)
+
+# Add the aerodynamic interface to the body settings
+body_settings.get("Delfi-C3").aerodynamic_coefficient_settings = aero_coefficient_settings
 
 # Create radiation pressure settings
 reference_area_radiation = (4*0.3*0.1+2*0.1*0.1)/4  # Average projection area of a 3U CubeSat
 radiation_pressure_coefficient = 1.2
-occulting_bodies = ["Earth"]
-radiation_pressure_settings = environment_setup.radiation_pressure.cannonball(
-    "Sun", reference_area_radiation, radiation_pressure_coefficient, occulting_bodies
-)
-# Add the radiation pressure interface to the environment
-environment_setup.add_radiation_pressure_interface(bodies, "Delfi-C3", radiation_pressure_settings)
+occulting_bodies_dict = dict()
+occulting_bodies_dict["Sun"] = ["Earth"]
+vehicle_target_settings = environment_setup.radiation_pressure.cannonball_radiation_target(
+    reference_area_radiation, radiation_pressure_coefficient, occulting_bodies_dict )
+
+# Add the radiation pressure interface to the body settings
+body_settings.get("Delfi-C3").radiation_pressure_target_settings = vehicle_target_settings
+
+
+# Finally, the system of bodies is created using the settings. This system of bodies is stored into the variable `bodies`.
+
+# Create system of bodies
+bodies = environment_setup.create_system_of_bodies(body_settings)
 
 
 ## Set up the propagation
@@ -147,7 +151,7 @@
 # Define the accelerations acting on Delfi-C3
 accelerations_settings_delfi_c3 = dict(
     Sun=[
-        propagation_setup.acceleration.cannonball_radiation_pressure(),
+        propagation_setup.acceleration.radiation_pressure(),
         propagation_setup.acceleration.point_mass_gravity()
     ],
     Mars=[
@@ -350,8 +354,6 @@
     bodies)
 
 
-# <a id='covariance_section'></a>
-
 ## Perform the covariance analysis
 """
 Having simulated the observations and created the `Estimator` object - containing the variational equations for the parameters to estimate - we have defined everything to conduct the actual estimation. Realise that up to this point, we have not yet specified whether we want to perform a covariance analysis or the full estimation of all parameters. It should be stressed that the general setup for either path to be followed is entirely identical.

estimation/estimation_dynamical_models.py

@@ -66,23 +66,24 @@
 body_settings = environment_setup.get_default_body_settings(
     bodies_to_create, global_frame_origin, global_frame_orientation)
 
-# Create system of bodies
-bodies = environment_setup.create_system_of_bodies(body_settings)
-
 ### VEHICLE BODY ###
 # Create vehicle object
-bodies.create_empty_body("MEX")
-bodies.get("MEX").mass = 1000.0
+body_settings.add_empty_settings("MEX")
+body_settings.get("MEX").constant_mass = 1000.0
 
 # Create radiation pressure settings
 reference_area_radiation = (4*0.3*0.1+2*0.1*0.1)/4  # Average projection area of a 3U CubeSat
 radiation_pressure_coefficient = 1.2
-occulting_bodies = ["Mars"]
-radiation_pressure_settings = environment_setup.radiation_pressure.cannonball(
-    "Sun", reference_area_radiation, radiation_pressure_coefficient, occulting_bodies
-)
-# Add the radiation pressure interface to the environment
-environment_setup.add_radiation_pressure_interface(bodies, "MEX", radiation_pressure_settings)
+occulting_bodies_dict = dict()
+occulting_bodies_dict["Sun"] = ["Mars"]
+vehicle_target_settings = environment_setup.radiation_pressure.cannonball_radiation_target(
+    reference_area_radiation, radiation_pressure_coefficient, occulting_bodies_dict )
+
+# Add the radiation pressure interface to the body settings
+body_settings.get("MEX").radiation_pressure_target_settings = vehicle_target_settings
+
+# Create system of bodies
+bodies = environment_setup.create_system_of_bodies(body_settings)
 
 # Define bodies that are propagated
 bodies_to_propagate = ["MEX"]
@@ -250,7 +251,7 @@
     ],
     Sun=[
         propagation_setup.acceleration.point_mass_gravity(),
-        propagation_setup.acceleration.cannonball_radiation_pressure()
+        propagation_setup.acceleration.radiation_pressure()
     ])
 
 
@@ -302,7 +303,7 @@
 propagator_settings_simulation.processing_settings.set_integrated_result = True
 # Run propagation
 dynamics_simulator = create_dynamics_simulator(bodies, propagator_settings_simulation)
-state_history_simulated_observations = dynamics_simulator.state_history
+state_history_simulated_observations = dynamics_simulator.propagation_results.state_history
 
 # Create observation simulators
 observation_simulators = estimation_setup.create_observation_simulators(

estimation/estimation_with_mpc.py

@@ -12,12 +12,12 @@
 ## Import statements
 """
 # Tudat imports for propagation and estimation
-from tudatpy.kernel.interface import spice
-from tudatpy.kernel import numerical_simulation
-from tudatpy.kernel.numerical_simulation import environment_setup
-from tudatpy.kernel.numerical_simulation import propagation_setup
-from tudatpy.kernel.numerical_simulation import estimation, estimation_setup
-from tudatpy.kernel.numerical_simulation.estimation_setup import observation
+from tudatpy.interface import spice
+from tudatpy import numerical_simulation
+from tudatpy.numerical_simulation import environment_setup
+from tudatpy.numerical_simulation import propagation_setup
+from tudatpy.numerical_simulation import estimation, estimation_setup
+from tudatpy.numerical_simulation.estimation_setup import observation
 """
 
 # import MPC interface
@@ -232,14 +232,14 @@
 )
 
 # Add random offset for initial guess
-np.random.seed = 1
+rng = np.random.default_rng(seed=1)
 
 initial_position_offset = 1e6 * 1000
 initial_velocity_offset = 100
 
 initial_guess = initial_states.copy()
-initial_guess[0:3] += (2 * np.random.rand(3) - 1) * initial_position_offset
-initial_guess[3:6] += (2 * np.random.rand(3) - 1) * initial_velocity_offset
+initial_guess[0:3] += (2 * rng.random(3) - 1) * initial_position_offset
+initial_guess[3:6] += (2 * rng.random(3) - 1) * initial_velocity_offset
 
 print("Error between the real initial state and our initial guess:")
 print(initial_guess - initial_states)