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147 lines
6.1 KiB
Python
147 lines
6.1 KiB
Python
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"""
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This is the ball sim complete with integration loop converted to python
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This input file demonstrates the ability to create an entire simulation in an input file.
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Do not try this at home!
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"""
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import math
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# BallForce class flattened to remove input and output subclasses
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class BallForce:
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def __init__(self):
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self.origin = [ 0.0 , 2.0 ]
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self.input_force = 8.0
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self.output_force = [ 0.0 , 0.0 ]
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# BallState class flattened to remove input and output subclasses
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class BallState:
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def __init__(self):
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self.mass = 10.0
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self.speed = 3.5
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self.elevation = 0.785398163
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self.input_position = [ 5.0 , 5.0 ]
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self.output_position = [ 0.0 , 0.0 ]
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self.output_velocity = [ 0.0 , 0.0 ]
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self.output_acceleration = [ 0.0 , 0.0 ]
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self.external_force = [ 0.0 , 0.0 ]
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# Ball class includes a BallForce and BallState
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class Ball:
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def __init__(self):
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self.state = BallState()
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self.force = BallForce()
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# state_init is an initialization job. It is translated from the C++ version
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def state_init(self):
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#print "here in state_init"
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self.state.output_position = self.state.input_position
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self.state.output_velocity = [ self.state.speed * math.cos(self.state.elevation) , \
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self.state.speed * math.sin( self.state.elevation ) ]
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return(0)
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# force_field is a derivative job. It is translated from the C++ version
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def force_field(self):
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#print "here in force_field"
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rel_pos = [ self.force.origin[0] - float(self.state.output_position[0]) , \
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self.force.origin[1] - float(self.state.output_position[1]) ]
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mag = math.sqrt( rel_pos[0] * rel_pos[0] + rel_pos[1] * rel_pos[1] )
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unit = [ rel_pos[0] / mag , rel_pos[1] / mag ]
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self.force.output_force = [ self.force.input_force * unit[0] , self.force.input_force * unit[1] ]
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return(0)
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# state_deriv is a derivative job. It is translated from the C++ version
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def state_deriv(self):
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#print "here in state_deriv"
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self.state.external_force = self.force.output_force
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self.state.output_acceleration = [ self.state.external_force[0] / self.state.mass , \
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self.state.external_force[1] / self.state.mass ]
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return(0)
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# state_integ is an integration job. It is translated from the C++ version
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def state_integ(self):
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#print "here in state_integ"
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trick.load_indexed_state(0 , self.state.output_position[0])
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trick.load_indexed_state(1 , self.state.output_position[1])
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trick.load_indexed_state(2 , self.state.output_velocity[0])
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trick.load_indexed_state(3 , self.state.output_velocity[1])
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trick.load_indexed_deriv(0 , self.state.output_velocity[0])
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trick.load_indexed_deriv(1 , self.state.output_velocity[1])
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trick.load_indexed_deriv(2 , self.state.output_acceleration[0])
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trick.load_indexed_deriv(3 , self.state.output_acceleration[1])
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trick.integrate()
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self.state.output_position[0] = trick.unload_indexed_state(0)
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self.state.output_position[1] = trick.unload_indexed_state(1)
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self.state.output_velocity[0] = trick.unload_indexed_state(2)
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self.state.output_velocity[1] = trick.unload_indexed_state(3)
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return(trick.get_intermediate_step())
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# state_print is a scheduled job. It is translated from the C++ version
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def state_print(self):
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#print "time = " , trick.exec_get_sim_time() , " , position = " , self.state.output_position
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trick.message_publish(trick.MSG_NORMAL, "time = " + str(trick.exec_get_sim_time()) + " , position = " + str(self.state.output_position) + "\n")
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return(0)
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my_ball = Ball()
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# ball_call_function is our glue function from the Trick scheduler to our python code above
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# The scheduler calls InputProcessSimObject::call_function which in turn calls this function
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# with the job id to run. It is up to the user to keep these ids in this function and the
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# add jobs calls below in sync.
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def ball_call_function(id):
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if id == 3: ret = my_ball.state_init()
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if id == 4: ret = my_ball.force_field()
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if id == 5: ret = my_ball.state_deriv()
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if id == 6: ret = my_ball.state_integ()
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if id == 7: ret = my_ball.state_print()
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ball_ips.return_value = ret
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return(0)
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# declare a new InputProcessSimObject and use ball_call_function as the glue between C++ and python
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ball_ips = trick.InputProcessSimObject("ball_call_function")
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# create a new Runge Kutta 2 integrator with 4 states
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#my_integ = trick.getIntegrator(trick.Runge_Kutta_2, 4 , 1.0)
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# The add job call below requires an "Integrator **". my_integ is an "Integrator *"
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# This wrap_ptr function adds the second pointer
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#my_integ_ptr = trick.wrap_ptr(my_integ)
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# add the ball jobs to the sim_object
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ball_ips.add_job(0,3,"initialization",None,1.0,"ball_ips.state_init")
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ball_ips.add_job(0,4,"derivative",None,1.0,"ball_ips.force_field")
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ball_ips.add_job(0,5,"derivative",None,1.0,"ball_ips.state_deriv")
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ball_ips.add_job(0,6,"integration",None,1.0,"ball_ips.state_integ")
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ball_ips.add_job(0,7,"scheduled",None,10.0,"ball_ips.state_print")
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trick.exec_add_sim_object(ball_ips, "ball_ips")
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# declare a new Integrator loop sim object
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my_integ_loop = trick.IntegLoopSimObject(0.01, 0, ball_ips, None) ;
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# create a new Runge Kutta 2 integrator with 4 states
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my_integ_loop.getIntegrator(trick.Runge_Kutta_2, 4)
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# add the ball sim_object to the scheduler
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# add the integrator sim_object to the scheduler
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trick.exec_add_sim_object(my_integ_loop, "my_integ_loop")
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my_integ_loop.integ_sched.rebuild_jobs()
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# trick system defaults for this sim
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#trick.exec_set_enable_freeze(0)
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trick.exec_set_terminate_time(trick.exec_get_sim_time() + 300.0)
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# This input file can be sent to the simulation through the variable server.
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# If the sim is inputted this way, the sim will be in freeze so these
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# jobs must be called because we are past the point where they would have been called.
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if trick.exec_get_mode() == trick.Freeze:
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my_ball.state_init()
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my_ball.force_field()
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my_ball.state_deriv()
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trick.exec_run()
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