Source code for test_relativeODuKF

''' '''
'''
 ISC License

 Copyright (c) 2016-2018, Autonomous Vehicle Systems Lab, University of Colorado at Boulder

 Permission to use, copy, modify, and/or distribute this software for any
 purpose with or without fee is hereby granted, provided that the above
 copyright notice and this permission notice appear in all copies.

 THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES
 WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF
 MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR
 ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
 WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
 ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF
 OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.

'''
import sys, os, inspect
import numpy as np
import pytest
import math

from Basilisk.utilities import SimulationBaseClass, macros, orbitalMotion
from Basilisk.fswAlgorithms.relativeODuKF import relativeODuKF  # import the module that is to be tested
from Basilisk.fswAlgorithms.fswMessages import fswMessages

import relativeODuKF_test_utilities as FilterPlots
import numpy as np

def rk4(f, t, x0):
    x = np.zeros([len(t),len(x0)+1])
    h = (t[len(t)-1] - t[0])/len(t)
    x[0,0] = t[0]
    x[0,1:] = x0
    for i in range(len(t)-1):
        h = t[i+1] - t[i]
        x[i,0] = t[i]
        k1 = h * f(t[i], x[i,1:])
        k2 = h * f(t[i] + 0.5 * h, x[i,1:] + 0.5 * k1)
        k3 = h * f(t[i] + 0.5 * h, x[i,1:] + 0.5 * k2)
        k4 = h * f(t[i] + h, x[i,1:] + k3)
        x[i+1,1:] = x[i,1:] + (k1 + 2.*k2 + 2.*k3 + k4) / 6.
        x[i+1,0] = t[i+1]
    return x

def twoBodyGrav(t, x, mu = 42828.314*1E9):
    dxdt = np.zeros(np.shape(x))
    dxdt[0:3] = x[3:]
    dxdt[3:] = -mu/np.linalg.norm(x[0:3])**3.*x[0:3]
    return dxdt


def setupFilterData(filterObject):
    filterObject.navStateOutMsgName = "relod_state_estimate"
    filterObject.filtDataOutMsgName = "relod_filter_data"
    filterObject.opNavInMsgName = "reold_opnav_meas"

    filterObject.planetIdInit = 2
    filterObject.alpha = 0.02
    filterObject.beta = 2.0
    filterObject.kappa = 0.0

    mu = 42828.314*1E9 #m^3/s^2
    elementsInit = orbitalMotion.ClassicElements()
    elementsInit.a = 4000*1E3 #m
    elementsInit.e = 0.2
    elementsInit.i = 10
    elementsInit.Omega = 0.001
    elementsInit.omega = 0.01
    elementsInit.f = 0.1
    r, v = orbitalMotion.elem2rv(mu, elementsInit)

    filterObject.stateInit = r.tolist() + v.tolist()
    filterObject.covarInit = [1000.*1E6, 0.0, 0.0, 0.0, 0.0, 0.0,
                              0.0, 1000.*1E6, 0.0, 0.0, 0.0, 0.0,
                              0.0, 0.0, 1000.*1E6, 0.0, 0.0, 0.0,
                              0.0, 0.0, 0.0, 5*1E6, 0.0, 0.0,
                              0.0, 0.0, 0.0, 0.0, 5*1E6, 0.0,
                              0.0, 0.0, 0.0, 0.0, 0.0, 5*1E6]

    qNoiseIn = np.identity(6)
    qNoiseIn[0:3, 0:3] = qNoiseIn[0:3, 0:3]*0.00001*0.00001*1E-6
    qNoiseIn[3:6, 3:6] = qNoiseIn[3:6, 3:6]*0.0001*0.0001*1E-6
    filterObject.qNoise = qNoiseIn.reshape(36).tolist()
    filterObject.noiseSF = 1

# uncomment this line is this test is to be skipped in the global unit test run, adjust message as needed
# @pytest.mark.skipif(conditionstring)
# uncomment this line if this test has an expected failure, adjust message as needed
# @pytest.mark.xfail() # need to update how the RW states are defined
# provide a unique test method name, starting with test_

[docs]def test_methods_kf(show_plots): """Module Unit Test""" [testResults, testMessage] = relOD_method_test(show_plots) assert testResults < 1, testMessage
[docs]def test_propagation_kf(show_plots): """Module Unit Test""" [testResults, testMessage] = StatePropRelOD(show_plots, 10.0) assert testResults < 1, testMessage
[docs]def test_measurements_kf(show_plots): """Module Unit Test""" [testResults, testMessage] = StateUpdateRelOD(show_plots) assert testResults < 1, testMessage
def relOD_method_test(show_plots): # The __tracebackhide__ setting influences pytest showing of tracebacks: # the mrp_steering_tracking() function will not be shown unless the # --fulltrace command line option is specified. __tracebackhide__ = True testFailCount = 0 # zero unit test result counter testMessages = [] # create empty list to store test log messages state = [250, 32000, 1000, 5, 3, 2] dt = 10 mu = 42828.314 # Measurement Model Test data = relativeODuKF.RelODuKFConfig() msg = relativeODuKF.OpNavFswMsg() msg.r_BN_N = [300, 200, 100] data.planetId = 2 data.opNavInMsg = msg data.countHalfSPs = 6 data.noiseSF = 1 Covar = np.eye(6) SPexp = np.zeros([6, 2*6+1]) SPexp[:,0] = np.array(state) for i in range(1, 6+1): SPexp[:,i] = np.array(state) + Covar[:,i-1] SPexp[:, i+6] = np.array(state) - Covar[:,i-1] data.SP = np.transpose(SPexp).flatten().tolist() relativeODuKF.relODuKFMeasModel(data) measurements = data.yMeas if np.linalg.norm(np.array(measurements) - np.transpose(SPexp[0:3,:]).flatten()) > 1.0E-15: testFailCount += 1 testMessages.append("Measurement Model Failure") # Dynamics Model Test data.planetId = 2 stateIn = relativeODuKF.new_doubleArray(6) for i in range(len(state)): relativeODuKF.doubleArray_setitem(stateIn, i, state[i]) relativeODuKF.relODStateProp(data, stateIn, dt) propedState = [] for i in range(6): propedState.append(relativeODuKF.doubleArray_getitem(stateIn, i)) expected = rk4(twoBodyGrav, [0, dt], np.array(state)*1E3) expected[:,1:]*=1E-3 if np.linalg.norm((np.array(propedState) - expected[-1,1:])/(expected[-1,1:])) > 1.0E-15: testFailCount += 1 testMessages.append("State Prop Failure") return [testFailCount, ''.join(testMessages)] def StateUpdateRelOD(show_plots): # The __tracebackhide__ setting influences pytest showing of tracebacks: # the mrp_steering_tracking() function will not be shown unless the # --fulltrace command line option is specified. __tracebackhide__ = True testFailCount = 0 # zero unit test result counter testMessages = [] # create empty list to store test log messages unitTaskName = "unitTask" # arbitrary name (don't change) unitProcessName = "TestProcess" # arbitrary name (don't change) # Create a sim module as an empty container unitTestSim = SimulationBaseClass.SimBaseClass() # Create test thread dt = 1.0 t1 = 250 multT1 = 8 testProcessRate = macros.sec2nano(dt) # update process rate update time testProc = unitTestSim.CreateNewProcess(unitProcessName) testProc.addTask(unitTestSim.CreateNewTask(unitTaskName, testProcessRate)) # Construct algorithm and associated C++ container moduleConfig = relativeODuKF.RelODuKFConfig() moduleWrap = unitTestSim.setModelDataWrap(moduleConfig) moduleWrap.ModelTag = "relodSuKF" # Add test module to runtime call list unitTestSim.AddModelToTask(unitTaskName, moduleWrap, moduleConfig) setupFilterData(moduleConfig) moduleConfig.noiseSF = 1 unitTestSim.TotalSim.logThisMessage('relod_filter_data', testProcessRate) time = np.linspace(0, int(multT1*t1), int(multT1*t1//dt)+1) dydt = np.zeros(6) energy = np.zeros(len(time)) expected=np.zeros([len(time), 7]) expected[0,1:] = moduleConfig.stateInit mu = 42828.314*1E9 energy[0] = -mu/(2*orbitalMotion.rv2elem(mu, expected[0,1:4], expected[0,4:]).a) kick = np.array([0., 0., 0., -0.01, 0.01, 0.02]) * 10 *1E3 expected[0:t1,:] = rk4(twoBodyGrav, time[0:t1], moduleConfig.stateInit) expected[t1:multT1*t1+1, :] = rk4(twoBodyGrav, time[t1:len(time)], expected[t1-1, 1:] + kick) for i in range(1, len(time)): energy[i] = - mu / (2 * orbitalMotion.rv2elem(mu, expected[i, 1:4], expected[i, 4:]).a) inputData = relativeODuKF.OpNavFswMsg() inputMessageSize = inputData.getStructSize() unitTestSim.TotalSim.CreateNewMessage(unitProcessName, moduleConfig.opNavInMsgName, inputMessageSize, 2) # number of buffers (leave at 2 as default, don't make zero) inputData.planetID = 2 inputData.r_BN_B = expected[0, 1:4] unitTestSim.InitializeSimulation() for i in range(t1): if i > 0 and i % 50 == 0: inputData.timeTag = macros.sec2nano(i * dt) inputData.r_BN_N = expected[i,1:4] + np.random.normal(0, 5*1E-2, 3) inputData.valid = 1 inputData.covar_N = [5.*1E-2, 0., 0., 0., 5.*1E-2, 0., 0., 0., 5.*1E-2] unitTestSim.TotalSim.WriteMessageData(moduleConfig.opNavInMsgName, inputMessageSize, unitTestSim.TotalSim.CurrentNanos, inputData) unitTestSim.ConfigureStopTime(macros.sec2nano((i + 1) * dt)) unitTestSim.ExecuteSimulation() covarLog = unitTestSim.pullMessageLogData('relod_filter_data' + ".covar", list(range(6 * 6))) for i in range(6): if (covarLog[t1, i * 6 + 1 + i] > covarLog[0, i * 6 + 1 + i] / 100): testFailCount += 1 testMessages.append("Covariance update failure at " + str(t1)) for i in range(t1, multT1*t1): if i % 50 == 0: inputData.timeTag = macros.sec2nano(i * dt + 1) inputData.r_BN_N = expected[i,1:4] + np.random.normal(0, 5*1E-2, 3) inputData.valid = 1 inputData.covar_N = [5.*1E-2, 0.,0., 0., 5.*1E-2, 0., 0., 0., 5.*1E-2] unitTestSim.TotalSim.WriteMessageData(moduleConfig.opNavInMsgName, inputMessageSize, unitTestSim.TotalSim.CurrentNanos, inputData) unitTestSim.ConfigureStopTime(macros.sec2nano((i + 1)*dt)) unitTestSim.ExecuteSimulation() stateLog = unitTestSim.pullMessageLogData('relod_filter_data' + ".state", list(range(6))) stateErrorLog = unitTestSim.pullMessageLogData('relod_filter_data' + ".stateError", list(range(6))) postFitLog = unitTestSim.pullMessageLogData('relod_filter_data' + ".postFitRes", list(range(3))) covarLog = unitTestSim.pullMessageLogData('relod_filter_data' + ".covar", list(range(6 * 6))) diff = np.copy(stateLog) diff[:,1:]-=expected[:,1:] FilterPlots.EnergyPlot(time, energy, 'Update', show_plots) FilterPlots.StateCovarPlot(stateLog, covarLog, 'Update', show_plots) FilterPlots.StatePlot(diff, 'Update', show_plots) FilterPlots.plot_TwoOrbits(expected[:,0:4], stateLog[:,0:4]) FilterPlots.PostFitResiduals(postFitLog, np.sqrt(5*1E-2*1E6), 'Update', show_plots) for i in range(6): if (covarLog[t1*multT1, i * 6 + 1 + i] > covarLog[0, i * 6 + 1 + i] / 100): testFailCount += 1 testMessages.append("Covariance update failure at " + str(t1*multT1)) if (np.linalg.norm(diff[-1, 1:]/expected[-1,1:]) > 1.0E-1): testFailCount += 1 testMessages.append("State propagation failure") # print out success message if no error were found if testFailCount == 0: print("PASSED: " + moduleWrap.ModelTag + " state update") # return fail count and join into a single string all messages in the list # testMessage return [testFailCount, ''.join(testMessages)] def StatePropRelOD(show_plots, dt): # The __tracebackhide__ setting influences pytest showing of tracebacks: # the mrp_steering_tracking() function will not be shown unless the # --fulltrace command line option is specified. __tracebackhide__ = True testFailCount = 0 # zero unit test result counter testMessages = [] # create empty list to store test log messages unitTaskName = "unitTask" # arbitrary name (don't change) unitProcessName = "TestProcess" # arbitrary name (don't change) # Create a sim module as an empty container unitTestSim = SimulationBaseClass.SimBaseClass() # Create test thread testProcessRate = macros.sec2nano(dt) # update process rate update time testProc = unitTestSim.CreateNewProcess(unitProcessName) testProc.addTask(unitTestSim.CreateNewTask(unitTaskName, testProcessRate)) # Construct algorithm and associated C++ container moduleConfig = relativeODuKF.RelODuKFConfig() moduleWrap = unitTestSim.setModelDataWrap(moduleConfig) moduleWrap.ModelTag = "relodSuKF" # Add test module to runtime call list unitTestSim.AddModelToTask(unitTaskName, moduleWrap, moduleConfig) setupFilterData(moduleConfig) moduleConfig.noiseSF = 1 unitTestSim.TotalSim.logThisMessage('relod_filter_data', testProcessRate) timeSim = 60 unitTestSim.InitializeSimulation() unitTestSim.ConfigureStopTime(macros.min2nano(timeSim)) unitTestSim.ExecuteSimulation() time = np.linspace(0, int(timeSim*60), int(timeSim*60//dt)+1) dydt = np.zeros(6) energy = np.zeros(len(time)) expected=np.zeros([len(time), 7]) expected[0,1:] = moduleConfig.stateInit mu = 42828.314*1E9 energy[0] = -mu/(2*orbitalMotion.rv2elem(mu, expected[0,1:4], expected[0,4:]).a) expected = rk4(twoBodyGrav, time, moduleConfig.stateInit) for i in range(1, len(time)): energy[i] = - mu / (2 * orbitalMotion.rv2elem(mu, expected[i, 1:4], expected[i, 4:]).a) stateLog = unitTestSim.pullMessageLogData('relod_filter_data' + ".state", list(range(6))) covarLog = unitTestSim.pullMessageLogData('relod_filter_data' + ".covar", list(range(6 * 6))) diff = np.copy(stateLog) diff[:,1:]-=expected[:,1:] FilterPlots.plot_TwoOrbits(expected[:,0:4], stateLog[:,0:4]) FilterPlots.EnergyPlot(time, energy, 'Prop', show_plots) FilterPlots.StateCovarPlot(stateLog, covarLog, 'Prop', show_plots) FilterPlots.StatePlot(diff, 'Prop', show_plots) if (np.linalg.norm(diff[-1,1:]/expected[-1,1:]) > 1.0E-10): testFailCount += 1 testMessages.append("State propagation failure") if (energy[0] - energy[-1])/energy[0] > 1.0E-10: testFailCount += 1 testMessages.append("State propagation failure") # print out success message if no error were found if testFailCount == 0: print("PASSED: " + moduleWrap.ModelTag + " state propagation") # return fail count and join into a single string all messages in the list # testMessage return [testFailCount, ''.join(testMessages)] if __name__ == "__main__": # relOD_method_test(True) # StatePropRelOD(True, 1.0) StateUpdateRelOD(True)