Source code for test_SunLineUKF

''' '''
'''
 ISC License

 Copyright (c) 2016, 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
import pytest
import math







from Basilisk.utilities import SimulationBaseClass, unitTestSupport, macros
import matplotlib.pyplot as plt
from Basilisk.fswAlgorithms.sunlineUKF import sunlineUKF
from Basilisk.fswAlgorithms.fswMessages import fswMessages
from Basilisk.fswAlgorithms.cssComm import cssComm
from Basilisk.simulation.coarse_sun_sensor import coarse_sun_sensor
import SunLineuKF_test_utilities as FilterPlots


def setupFilterData(filterObject):
    filterObject.navStateOutMsgName = "sunline_state_estimate"
    filterObject.filtDataOutMsgName = "sunline_filter_data"
    filterObject.cssDataInMsgName = "css_sensors_data"
    filterObject.cssConfigInMsgName = "css_config_data"

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

    filterObject.state = [1.0, 0.0, 0.0, 0.0, 0.0, 0.0]
    filterObject.covar = [0.4, 0.0, 0.0, 0.0, 0.0, 0.0,
                          0.0, 0.4, 0.0, 0.0, 0.0, 0.0,
                          0.0, 0.0, 0.4, 0.0, 0.0, 0.0,
                          0.0, 0.0, 0.0, 0.04, 0.0, 0.0,
                          0.0, 0.0, 0.0, 0.0, 0.04, 0.0,
                          0.0, 0.0, 0.0, 0.0, 0.0, 0.04]
    qNoiseIn = numpy.identity(6)
    qNoiseIn[0:3, 0:3] = qNoiseIn[0:3, 0:3]*0.01*0.01
    qNoiseIn[3:6, 3:6] = qNoiseIn[3:6, 3:6]*0.001*0.001
    filterObject.qNoise = qNoiseIn.reshape(36).tolist()
    filterObject.qObsVal = 0.001

# 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_all_sunline_kf(show_plots): """Module Unit Test""" [testResults, testMessage] = sunline_utilities_test(show_plots) assert testResults < 1, testMessage [testResults, testMessage] = testStatePropSunLine(show_plots) assert testResults < 1, testMessage [testResults, testMessage] = testStateUpdateSunLine(show_plots) assert testResults < 1, testMessage
def sunline_utilities_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 # Initialize the test module configuration data AMatrix = [0.488894, 0.888396, 0.325191, 0.319207, 1.03469, -1.14707, -0.754928, 0.312859, 0.726885, -1.06887, 1.3703, -0.86488, -0.303441, -0.809499, -1.71152, -0.0300513, 0.293871, -2.94428, -0.102242, -0.164879, -0.787283, 1.43838, -0.241447, 0.627707] RVector = sunlineUKF.new_doubleArray(len(AMatrix)) AVector = sunlineUKF.new_doubleArray(len(AMatrix)) for i in range(len(AMatrix)): sunlineUKF.doubleArray_setitem(AVector, i, AMatrix[i]) sunlineUKF.doubleArray_setitem(RVector, i, 0.0) sunlineUKF.ukfQRDJustR(AVector, 6, 4, RVector) RMatrix = [] for i in range(4*4): RMatrix.append(sunlineUKF.doubleArray_getitem(RVector, i)) RBaseNumpy = numpy.array(RMatrix).reshape(4,4) AMatNumpy = numpy.array(AMatrix).reshape(6,4) q,r = numpy.linalg.qr(AMatNumpy) for i in range(r.shape[0]): if r[i,i] < 0.0: r[i,:] *= -1.0 if numpy.linalg.norm(r - RBaseNumpy) > 1.0E-15: testFailCount += 1 testMessages.append("QR Decomposition accuracy failure") AMatrix = [1.09327, 1.10927, -0.863653, 1.32288, -1.21412, -1.1135, -0.00684933, -2.43508, -0.769666, 0.371379, -0.225584, -1.76492, -1.08906, 0.0325575, 0.552527, -1.6256, 1.54421, 0.0859311, -1.49159, 1.59683] RVector = sunlineUKF.new_doubleArray(len(AMatrix)) AVector = sunlineUKF.new_doubleArray(len(AMatrix)) for i in range(len(AMatrix)): sunlineUKF.doubleArray_setitem(AVector, i, AMatrix[i]) sunlineUKF.doubleArray_setitem(RVector, i, 0.0) sunlineUKF.ukfQRDJustR(AVector, 5, 4, RVector) RMatrix = [] for i in range(4*4): RMatrix.append(sunlineUKF.doubleArray_getitem(RVector, i)) RBaseNumpy = numpy.array(RMatrix).reshape(4,4) AMatNumpy = numpy.array(AMatrix).reshape(5,4) q,r = numpy.linalg.qr(AMatNumpy) for i in range(r.shape[0]): if r[i,i] < 0.0: r[i,:] *= -1.0 if numpy.linalg.norm(r - RBaseNumpy) > 1.0E-14: testFailCount += 1 testMessages.append("QR Decomposition accuracy failure") AMatrix = [ 0.2236, 0, 0, 0.2236, -0.2236, 0, 0, -0.2236, 0.0170, 0, 0, 0.0170] RVector = sunlineUKF.new_doubleArray(len(AMatrix)) AVector = sunlineUKF.new_doubleArray(len(AMatrix)) for i in range(len(AMatrix)): sunlineUKF.doubleArray_setitem(AVector, i, AMatrix[i]) sunlineUKF.doubleArray_setitem(RVector, i, 0.0) sunlineUKF.ukfQRDJustR(AVector, 6, 2, RVector) RMatrix = [] for i in range(2*2): RMatrix.append(sunlineUKF.doubleArray_getitem(RVector, i)) RBaseNumpy = numpy.array(RMatrix).reshape(2,2) AMatNumpy = numpy.array(AMatrix).reshape(6,2) q,r = numpy.linalg.qr(AMatNumpy) for i in range(r.shape[0]): if r[i,i] < 0.0: r[i,:] *= -1.0 if numpy.linalg.norm(r - RBaseNumpy) > 1.0E-15: testFailCount += 1 testMessages.append("QR Decomposition accuracy failure") LUSourceMat = [8,1,6,3,5,7,4,9,2] LUSVector = sunlineUKF.new_doubleArray(len(LUSourceMat)) LVector = sunlineUKF.new_doubleArray(len(LUSourceMat)) UVector = sunlineUKF.new_doubleArray(len(LUSourceMat)) intSwapVector = sunlineUKF.new_intArray(3) for i in range(len(LUSourceMat)): sunlineUKF.doubleArray_setitem(LUSVector, i, LUSourceMat[i]) sunlineUKF.doubleArray_setitem(UVector, i, 0.0) sunlineUKF.doubleArray_setitem(LVector, i, 0.0) exCount = sunlineUKF.ukfLUD(LUSVector, 3, 3, LVector, intSwapVector) #sunlineUKF.ukfUInv(LUSVector, 3, 3, UVector) LMatrix = [] UMatrix = [] #UMatrix = [] for i in range(3): currRow = sunlineUKF.intArray_getitem(intSwapVector, i) for j in range(3): if(j<i): LMatrix.append(sunlineUKF.doubleArray_getitem(LVector, i*3+j)) UMatrix.append(0.0) elif(j>i): LMatrix.append(0.0) UMatrix.append(sunlineUKF.doubleArray_getitem(LVector, i*3+j)) else: LMatrix.append(1.0) UMatrix.append(sunlineUKF.doubleArray_getitem(LVector, i*3+j)) # UMatrix.append(sunlineUKF.doubleArray_getitem(UVector, i)) LMatrix = numpy.array(LMatrix).reshape(3,3) UMatrix = numpy.array(UMatrix).reshape(3,3) outMat = numpy.dot(LMatrix, UMatrix) outMatSwap = numpy.zeros((3,3)) for i in range(3): currRow = sunlineUKF.intArray_getitem(intSwapVector, i) outMatSwap[i,:] = outMat[currRow, :] outMat[currRow,:] = outMat[i, :] LuSourceArray = numpy.array(LUSourceMat).reshape(3,3) if(numpy.linalg.norm(outMatSwap - LuSourceArray) > 1.0E-14): testFailCount += 1 testMessages.append("LU Decomposition accuracy failure") EqnSourceMat = [2.0, 1.0, 3.0, 2.0, 6.0, 8.0, 6.0, 8.0, 18.0] BVector = [1.0, 3.0, 5.0] EqnVector = sunlineUKF.new_doubleArray(len(EqnSourceMat)) EqnBVector = sunlineUKF.new_doubleArray(len(LUSourceMat)//3) EqnOutVector = sunlineUKF.new_doubleArray(len(LUSourceMat)//3) for i in range(len(EqnSourceMat)): sunlineUKF.doubleArray_setitem(EqnVector, i, EqnSourceMat[i]) sunlineUKF.doubleArray_setitem(EqnBVector, i//3, BVector[i//3]) sunlineUKF.intArray_setitem(intSwapVector, i//3, 0) sunlineUKF.doubleArray_setitem(LVector, i, 0.0) exCount = sunlineUKF.ukfLUD(EqnVector, 3, 3, LVector, intSwapVector) sunlineUKF.ukfLUBckSlv(LVector, 3, 3, intSwapVector, EqnBVector, EqnOutVector) expectedSol = [3.0/10.0, 4.0/10.0, 0.0] errorVal = 0.0 for i in range(3): errorVal += abs(sunlineUKF.doubleArray_getitem(EqnOutVector, i) -expectedSol[i]) if(errorVal > 1.0E-14): testFailCount += 1 testMessages.append("LU Back-Solve accuracy failure") InvSourceMat = [8,1,6,3,5,7,4,9,2] SourceVector = sunlineUKF.new_doubleArray(len(InvSourceMat)) InvVector = sunlineUKF.new_doubleArray(len(InvSourceMat)) for i in range(len(InvSourceMat)): sunlineUKF.doubleArray_setitem(SourceVector, i, InvSourceMat[i]) sunlineUKF.doubleArray_setitem(InvVector, i, 0.0) nRow = int(math.sqrt(len(InvSourceMat))) sunlineUKF.ukfMatInv(SourceVector, nRow, nRow, InvVector) InvOut = [] for i in range(len(InvSourceMat)): InvOut.append(sunlineUKF.doubleArray_getitem(InvVector, i)) InvOut = numpy.array(InvOut).reshape(nRow, nRow) expectIdent = numpy.dot(InvOut, numpy.array(InvSourceMat).reshape(3,3)) errorNorm = numpy.linalg.norm(expectIdent - numpy.identity(3)) if(errorNorm > 1.0E-14): testFailCount += 1 testMessages.append("LU Matrix Inverse accuracy failure") cholTestMat = [1.0, 0.0, 0.0, 0.0, 10.0, 5.0, 0.0, 5.0, 10.0] SourceVector = sunlineUKF.new_doubleArray(len(cholTestMat)) CholVector = sunlineUKF.new_doubleArray(len(cholTestMat)) for i in range(len(cholTestMat)): sunlineUKF.doubleArray_setitem(SourceVector, i, cholTestMat[i]) sunlineUKF.doubleArray_setitem(CholVector, i, 0.0) nRow = int(math.sqrt(len(cholTestMat))) sunlineUKF.ukfCholDecomp(SourceVector, nRow, nRow, CholVector) cholOut = [] for i in range(len(cholTestMat)): cholOut.append(sunlineUKF.doubleArray_getitem(CholVector, i)) cholOut = numpy.array(cholOut).reshape(nRow, nRow) cholComp = numpy.linalg.cholesky(numpy.array(cholTestMat).reshape(nRow, nRow)) errorNorm = numpy.linalg.norm(cholOut - cholComp) if(errorNorm > 1.0E-14): testFailCount += 1 testMessages.append("Cholesky Matrix Decomposition accuracy failure") InvSourceMat = [2.1950926119414667, 0.0, 0.0, 0.0, 1.0974804773131115, 1.9010439702743847, 0.0, 0.0, 0.0, 1.2672359635912551, 1.7923572711881284, 0.0, 1.0974804773131113, -0.63357997864171967, 1.7920348101787789, 0.033997451205364251] SourceVector = sunlineUKF.new_doubleArray(len(InvSourceMat)) InvVector = sunlineUKF.new_doubleArray(len(InvSourceMat)) for i in range(len(InvSourceMat)): sunlineUKF.doubleArray_setitem(SourceVector, i, InvSourceMat[i]) sunlineUKF.doubleArray_setitem(InvVector, i, 0.0) nRow = int(math.sqrt(len(InvSourceMat))) sunlineUKF.ukfLInv(SourceVector, nRow, nRow, InvVector) InvOut = [] for i in range(len(InvSourceMat)): InvOut.append(sunlineUKF.doubleArray_getitem(InvVector, i)) InvOut = numpy.array(InvOut).reshape(nRow, nRow) expectIdent = numpy.dot(InvOut, numpy.array(InvSourceMat).reshape(nRow,nRow)) errorNorm = numpy.linalg.norm(expectIdent - numpy.identity(nRow)) if(errorNorm > 1.0E-12): print(errorNorm) testFailCount += 1 testMessages.append("L Matrix Inverse accuracy failure") InvSourceMat = numpy.transpose(numpy.array(InvSourceMat).reshape(nRow, nRow)).reshape(nRow*nRow).tolist() SourceVector = sunlineUKF.new_doubleArray(len(InvSourceMat)) InvVector = sunlineUKF.new_doubleArray(len(InvSourceMat)) for i in range(len(InvSourceMat)): sunlineUKF.doubleArray_setitem(SourceVector, i, InvSourceMat[i]) sunlineUKF.doubleArray_setitem(InvVector, i, 0.0) nRow = int(math.sqrt(len(InvSourceMat))) sunlineUKF.ukfUInv(SourceVector, nRow, nRow, InvVector) InvOut = [] for i in range(len(InvSourceMat)): InvOut.append(sunlineUKF.doubleArray_getitem(InvVector, i)) InvOut = numpy.array(InvOut).reshape(nRow, nRow) expectIdent = numpy.dot(InvOut, numpy.array(InvSourceMat).reshape(nRow,nRow)) errorNorm = numpy.linalg.norm(expectIdent - numpy.identity(nRow)) if(errorNorm > 1.0E-12): print(errorNorm) testFailCount += 1 testMessages.append("U Matrix Inverse accuracy failure") # If the argument provided at commandline "--show_plots" evaluates as true, # plot all figures if show_plots: plt.show() plt.close('all') # print out success message if no error were found if testFailCount == 0: print("PASSED: " + " UKF utilities") # return fail count and join into a single string all messages in the list # testMessage return [testFailCount, ''.join(testMessages)] def testStateUpdateSunLine(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 testProcessRate = macros.sec2nano(0.5) # update process rate update time testProc = unitTestSim.CreateNewProcess(unitProcessName) testProc.addTask(unitTestSim.CreateNewTask(unitTaskName, testProcessRate)) # Construct algorithm and associated C++ container moduleConfig = sunlineUKF.SunlineUKFConfig() moduleWrap = unitTestSim.setModelDataWrap(moduleConfig) moduleWrap.ModelTag = "SunlineUKF" # Add test module to runtime call list unitTestSim.AddModelToTask(unitTaskName, moduleWrap, moduleConfig) setupFilterData(moduleConfig) cssConstelation = fswMessages.CSSConfigFswMsg() CSSOrientationList = [ [0.70710678118654746, -0.5, 0.5], [0.70710678118654746, -0.5, -0.5], [0.70710678118654746, 0.5, -0.5], [0.70710678118654746, 0.5, 0.5], [-0.70710678118654746, 0, 0.70710678118654757], [-0.70710678118654746, 0.70710678118654757, 0.0], [-0.70710678118654746, 0, -0.70710678118654757], [-0.70710678118654746, -0.70710678118654757, 0.0], ] totalCSSList = [] for CSSHat in CSSOrientationList: newCSS = fswMessages.CSSUnitConfigFswMsg() newCSS.CBias = 1.0 newCSS.nHat_B = CSSHat totalCSSList.append(newCSS) cssConstelation.nCSS = len(CSSOrientationList) cssConstelation.cssVals = totalCSSList unitTestSupport.setMessage(unitTestSim.TotalSim, unitProcessName, moduleConfig.cssConfigInMsgName, cssConstelation) testVector = numpy.array([-0.7, 0.7, 0.0]) inputData = cssComm.CSSArraySensorIntMsg() dotList = [] for element in CSSOrientationList: dotProd = numpy.dot(numpy.array(element), testVector) dotList.append(dotProd) inputData.CosValue = dotList inputMessageSize = inputData.getStructSize() unitTestSim.TotalSim.CreateNewMessage(unitProcessName, moduleConfig.cssDataInMsgName, inputMessageSize, 2) # number of buffers (leave at 2 as default, don't make zero) stateTarget = testVector.tolist() stateTarget.extend([0.0, 0.0, 0.0]) moduleConfig.state = [0.7, 0.7, 0.0] unitTestSim.TotalSim.logThisMessage('sunline_filter_data', testProcessRate) unitTestSim.InitializeSimulation() for i in range(400): if i > 20: unitTestSim.TotalSim.WriteMessageData(moduleConfig.cssDataInMsgName, inputMessageSize, unitTestSim.TotalSim.CurrentNanos, inputData) unitTestSim.ConfigureStopTime(macros.sec2nano((i+1)*0.5)) unitTestSim.ExecuteSimulation() stateLog = unitTestSim.pullMessageLogData('sunline_filter_data' + ".state", list(range(6))) postFitLog = unitTestSim.pullMessageLogData('sunline_filter_data' + ".postFitRes", list(range(8))) covarLog = unitTestSim.pullMessageLogData('sunline_filter_data' + ".covar", list(range(6*6))) for i in range(6): if(covarLog[-1, i*6+1+i] > covarLog[0, i*6+1+i]/100): testFailCount += 1 testMessages.append("Covariance update failure") if(abs(stateLog[-1, i+1] - stateTarget[i]) > 1.0E-5): print(abs(stateLog[-1, i+1] - stateTarget[i])) testFailCount += 1 testMessages.append("State update failure") testVector = numpy.array([-0.8, -0.9, 0.0]) inputData = cssComm.CSSArraySensorIntMsg() dotList = [] for element in CSSOrientationList: dotProd = numpy.dot(numpy.array(element), testVector) dotList.append(dotProd) inputData.CosValue = dotList for i in range(400): if i > 20: unitTestSim.TotalSim.WriteMessageData(moduleConfig.cssDataInMsgName, inputMessageSize, unitTestSim.TotalSim.CurrentNanos, inputData) unitTestSim.ConfigureStopTime(macros.sec2nano((i+401)*0.5)) unitTestSim.ExecuteSimulation() stateLog = unitTestSim.pullMessageLogData('sunline_filter_data' + ".state", list(range(6))) postFitLog = unitTestSim.pullMessageLogData('sunline_filter_data' + ".postFitRes", list(range(8))) covarLog = unitTestSim.pullMessageLogData('sunline_filter_data' + ".covar", list(range(6*6))) stateTarget = testVector.tolist() stateTarget.extend([0.0, 0.0, 0.0]) for i in range(6): if(covarLog[-1, i*6+1+i] > covarLog[0, i*6+1+i]/100): testFailCount += 1 testMessages.append("Covariance update failure") if(abs(stateLog[-1, i+1] - stateTarget[i]) > 1.0E-5): print(abs(stateLog[-1, i+1] - stateTarget[i])) testFailCount += 1 testMessages.append("State update failure") FilterPlots.StateCovarPlot(stateLog, covarLog, 'update', show_plots) FilterPlots.PostFitResiduals(postFitLog, moduleConfig.qObsVal, 'update', show_plots) # 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 testStatePropSunLine(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 testProcessRate = macros.sec2nano(0.5) # update process rate update time testProc = unitTestSim.CreateNewProcess(unitProcessName) testProc.addTask(unitTestSim.CreateNewTask(unitTaskName, testProcessRate)) # Construct algorithm and associated C++ container moduleConfig = sunlineUKF.SunlineUKFConfig() moduleWrap = unitTestSim.setModelDataWrap(moduleConfig) moduleWrap.ModelTag = "SunlineUKF" # Add test module to runtime call list unitTestSim.AddModelToTask(unitTaskName, moduleWrap, moduleConfig) setupFilterData(moduleConfig) unitTestSim.TotalSim.logThisMessage('sunline_filter_data', testProcessRate) unitTestSim.InitializeSimulation() unitTestSim.ConfigureStopTime(macros.sec2nano(8000.0)) unitTestSim.ExecuteSimulation() stateLog = unitTestSim.pullMessageLogData('sunline_filter_data' + ".state", list(range(6))) postFitLog = unitTestSim.pullMessageLogData('sunline_filter_data' + ".postFitRes", list(range(8))) covarLog = unitTestSim.pullMessageLogData('sunline_filter_data' + ".covar", list(range(6*6))) FilterPlots.StateCovarPlot(stateLog, covarLog, 'prop', show_plots) FilterPlots.PostFitResiduals(postFitLog, moduleConfig.qObsVal, 'prop', show_plots) for i in range(6): if(abs(stateLog[-1, i+1] - stateLog[0, i+1]) > 1.0E-10): print(abs(stateLog[-1, i+1] - stateLog[0, i+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 propagation") # return fail count and join into a single string all messages in the list # testMessage return [testFailCount, ''.join(testMessages)] if __name__ == "__main__": test_all_sunline_kf(False)