<filename>src/fswAlgorithms/attDetermination/okeefeEKF/_UnitTest/test_okeefeEKF.py
''' '''
'''
 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 as np
import pytest

filename = inspect.getframeinfo(inspect.currentframe()).filename
path = os.path.dirname(os.path.abspath(filename))
splitPath = path.split('FswAlgorithms')
sys.path.append(splitPath[0] + '/modules')
sys.path.append(splitPath[0] + '/PythonModules')

import SunLineOEKF_test_utilities as FilterPlots
from Basilisk.fswAlgorithms import okeefeEKF
from Basilisk.utilities import SimulationBaseClass
from Basilisk.simulation import alg_contain
from Basilisk.fswAlgorithms import cssComm
from Basilisk.utilities import macros
from Basilisk.utilities import unitTestSupport  # general support file with common unit test functions
from Basilisk.fswAlgorithms import fswMessages


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

    filterObject.sensorUseThresh = 0.
    filterObject.state = [1.0, 1.0, 1.0]
    filterObject.omega = [0.1, 0.2, 0.1]
    filterObject.x = [1.0, 0.0, 1.0]
    filterObject.covar = [0.4, 0.0, 0.0,
                          0.0, 0.4, 0.0,
                          0.0, 0.0, 0.4]

    filterObject.qProcVal = 0.1**2
    filterObject.qObsVal = 0.001
    filterObject.eKFSwitch = 5. #If low (0-5), the CKF kicks in easily, if high (>10) it's mostly only EKF

def test_all_functions_oekf(show_plots):
    [testResults, testMessage] = sunline_individual_test()
    assert testResults < 1, testMessage
    [testResults, testMessage] = StatePropStatic()
    assert testResults < 1, testMessage
    [testResults, testMessage] = StatePropVariable(show_plots)
    assert testResults < 1, testMessage

# 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(True)

# The following 'parametrize' function decorator provides the parameters and expected results for each
#   of the multiple test runs for this test.
@pytest.mark.parametrize("SimHalfLength, AddMeasNoise , testVector1 , testVector2, stateGuess", [
    (200, True ,[-0.7, 0.7, 0.0] ,[0.8, 0.9, 0.0], [0.7, 0.7, 0.0]),
    (2000, True ,[-0.7, 0.7, 0.0] ,[0.8, 0.9, 0.0], [0.7, 0.7, 0.0]),
    (200, False ,[-0.7, 0.7, 0.0] ,[0.8, 0.9, 0.0], [0.7, 0.7, 0.0]),
    (200, False ,[0., 0.4, -0.4] ,[0., 0.7, 0.2], [0.3, 0.0, 0.6]),
    (200, True ,[0., 0.4, -0.4] ,[0.4, 0.5, 0.], [0.7, 0.7, 0.0]),
    (200, True ,[-0.7, 0.7, 0.0] ,[0.8, 0.9, 0.0], [0.7, 0.7, 0.0])
])


# 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_
def test_all_sunline_oekf(show_plots, SimHalfLength, AddMeasNoise, testVector1, testVector2, stateGuess):
    [testResults, testMessage] = StateUpdateSunLine(show_plots, SimHalfLength, AddMeasNoise, testVector1, testVector2, stateGuess)
    assert testResults < 1, testMessage


def sunline_individual_test():
    # 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

    NUMSTATES = 3
    ###################################################################################
    ## Testing dynamics matrix computation
    ###################################################################################

    inputOmega = [0.1, 0.2, 0.1]
    dt =0.5

    expDynMat = - np.array([[0., -inputOmega[2], inputOmega[1]],
                            [inputOmega[2], 0., -inputOmega[0]],
                            [ -inputOmega[1], inputOmega[0], 0.]])


    dynMat = okeefeEKF.new_doubleArray(3*3)
    for i in range(9):
        okeefeEKF.doubleArray_setitem(dynMat, i, 0.0)
    okeefeEKF.sunlineDynMatrix(inputOmega, dt, dynMat)

    DynOut = []
    for i in range(NUMSTATES*NUMSTATES):
        DynOut.append(okeefeEKF.doubleArray_getitem(dynMat, i))

    DynOut = np.array(DynOut).reshape(3, 3)
    errorNorm = np.linalg.norm(expDynMat - DynOut)
    if(errorNorm > 1.0E-12):
        print errorNorm
        testFailCount += 1
        testMessages.append("Dynamics Matrix generation Failure \n")


    ###################################################################################
    ## Testing omega computation
    ###################################################################################

    inputStates = [2,1,0.75]
    inputPrevStates = [1,0.1,0.5]
    norm1 = np.linalg.norm(np.array(inputStates))
    norm2 =  np.linalg.norm(np.array(inputPrevStates))
    dt =0.5

    expOmega = 1./dt*np.cross(np.array(inputStates),np.array(inputPrevStates))/(norm1*norm2)*np.arccos(np.dot(np.array(inputStates),np.array(inputPrevStates))/(norm1*norm2))

    omega = okeefeEKF.new_doubleArray(NUMSTATES)
    for i in range(3):
        okeefeEKF.doubleArray_setitem(omega, i, 0.0)
    okeefeEKF.sunlineRateCompute(inputStates, dt, inputPrevStates, omega)

    omegaOut = []
    for i in range(NUMSTATES):
        omegaOut.append(okeefeEKF.doubleArray_getitem(omega, i))

    omegaOut = np.array(omegaOut)
    errorNorm = np.linalg.norm(expOmega - omegaOut)
    if(errorNorm > 1.0E-12):
        print errorNorm
        testFailCount += 1
        testMessages.append("Dynamics Matrix generation Failure \n")

    ###################################################################################
    ## STM and State Test
    ###################################################################################

    inputStates = [2,1,0.75]
    inputOmega = [0.1, 0.2, 0.1]
    dt =0.5
    stateTransition = okeefeEKF.new_doubleArray(NUMSTATES*NUMSTATES)
    states = okeefeEKF.new_doubleArray(NUMSTATES)
    prev_states = okeefeEKF.new_doubleArray(NUMSTATES)
    for i in range(NUMSTATES):
        okeefeEKF.doubleArray_setitem(states, i, inputStates[i])
        for j in range(NUMSTATES):
            if i==j:
                okeefeEKF.doubleArray_setitem(stateTransition, NUMSTATES*i+j, 1.0)
            else:
                okeefeEKF.doubleArray_setitem(stateTransition, NUMSTATES*i+j, 0.0)

    okeefeEKF.sunlineStateSTMProp(expDynMat.flatten().tolist(), dt, inputOmega, states, prev_states, stateTransition)

    PropStateOut = []
    PropSTMOut = []
    for i in range(NUMSTATES):
        PropStateOut.append(okeefeEKF.doubleArray_getitem(states, i))
    for i in range(NUMSTATES*NUMSTATES):
        PropSTMOut.append(okeefeEKF.doubleArray_getitem(stateTransition, i))

    STMout = np.array(PropSTMOut).reshape([NUMSTATES,NUMSTATES])
    StatesOut = np.array(PropStateOut)

    expectedSTM = dt*np.dot(expDynMat, np.eye(NUMSTATES)) + np.eye(NUMSTATES)
    expectedStates = np.zeros(NUMSTATES)
    inputStatesArray = np.array(inputStates)
    ## Equations when removing the unobservable states from d_dot
    expectedStates[0:3] = np.array(inputStatesArray - dt*(np.cross(np.array(inputOmega), np.array(inputStatesArray))))
    errorNormSTM = np.linalg.norm(expectedSTM - STMout)
    errorNormStates = np.linalg.norm(expectedStates - StatesOut)

    if(errorNormSTM > 1.0E-12):
        print errorNormSTM
        testFailCount += 1
        testMessages.append("STM Propagation Failure \n")


    if(errorNormStates > 1.0E-12):
        print errorNormStates
        testFailCount += 1
        testMessages.append("State Propagation Failure \n")



    ###################################################################################
    # ## Test the H and yMeas matrix generation as well as the observation count
    # ###################################################################################
    numCSS = 4
    cssCos = [np.cos(np.deg2rad(10.)), np.cos(np.deg2rad(25.)), np.cos(np.deg2rad(5.)), np.cos(np.deg2rad(90.))]
    sensorTresh = np.cos(np.deg2rad(50.))
    cssNormals = [1.,0.,0.,0.,1.,0., 0.,0.,1., 1./np.sqrt(2), 1./np.sqrt(2),0.]
    cssBias = [1.0 for i in range(numCSS)]

    measMat = okeefeEKF.new_doubleArray(8*NUMSTATES)
    obs = okeefeEKF.new_doubleArray(8)
    yMeas = okeefeEKF.new_doubleArray(8)
    numObs = okeefeEKF.new_intArray(1)

    for i in range(8*NUMSTATES):
        okeefeEKF.doubleArray_setitem(measMat, i, 0.)
    for i in range(8):
        okeefeEKF.doubleArray_setitem(obs, i, 0.0)
        okeefeEKF.doubleArray_setitem(yMeas, i, 0.0)

    okeefeEKF.sunlineHMatrixYMeas(inputStates, numCSS, cssCos, sensorTresh, cssNormals, cssBias, obs, yMeas, numObs, measMat)

    obsOut = []
    yMeasOut = []
    numObsOut = []
    HOut = []
    for i in range(8*NUMSTATES):
        HOut.append(okeefeEKF.doubleArray_getitem(measMat, i))
    for i in range(8):
        yMeasOut.append(okeefeEKF.doubleArray_getitem(yMeas, i))
        obsOut.append(okeefeEKF.doubleArray_getitem(obs, i))
    numObsOut.append(okeefeEKF.intArray_getitem(numObs, 0))

    #Fill in expected values for test
    expectedH = np.zeros([8,NUMSTATES])
    expectedY = np.zeros(8)
    for j in range(3):
        expectedH[j,0:3] = np.eye(3)[j,:]
        expectedY[j] =np.array(cssCos[j]) - np.dot(np.array(inputStates)[0:3], np.array(cssNormals)[j*3:(j+1)*3])
    expectedObs = np.array([np.cos(np.deg2rad(10.)), np.cos(np.deg2rad(25.)), np.cos(np.deg2rad(5.)),0.,0.,0.,0.,0.])
    expectedNumObs = 3

    HOut = np.array(HOut).reshape([8, NUMSTATES])
    errorNorm = np.zeros(4)
    errorNorm[0] = np.linalg.norm(HOut - expectedH)
    errorNorm[1] = np.linalg.norm(yMeasOut - expectedY)
    errorNorm[2] = np.linalg.norm(obsOut - expectedObs)
    errorNorm[3] = np.linalg.norm(numObsOut[0] - expectedNumObs)
    for i in range(4):
        if(errorNorm[i] > 1.0E-12):
            testFailCount += 1
            testMessages.append("H and yMeas update failure \n")

    # ###################################################################################
    # ## Test the Kalman Gain
    # ###################################################################################

    numObs = 3
    h = [1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
         0., 0., 0., 0., 0., 0.]
    covar = [1., 0., 1.,
        0., 1., 0.,
        1., 0., 1. ]
    noise= 0.01

    Kalman = okeefeEKF.new_doubleArray(NUMSTATES * 8)

    for i in range(8 * NUMSTATES):
        okeefeEKF.doubleArray_setitem(Kalman, i, 0.)

    okeefeEKF.sunlineKalmanGain(covar, h, noise, numObs, Kalman)

    KalmanOut = []
    for i in range(8 * NUMSTATES):
        KalmanOut.append(okeefeEKF.doubleArray_getitem(Kalman, i))

    # Fill in expected values for test
    Hmat = np.array(h).reshape([8,NUMSTATES])
    Pk = np.array(covar).reshape([NUMSTATES,NUMSTATES])
    R = noise*np.eye(3)
    expectedK = np.dot(np.dot(Pk, Hmat[0:numObs,:].T), np.linalg.inv(np.dot(np.dot(Hmat[0:numObs,:], Pk), Hmat[0:numObs,:].T) + R[0:numObs,0:numObs]))

    KalmanOut = np.array(KalmanOut)[0:NUMSTATES*numObs].reshape([NUMSTATES, 3])
    errorNorm = np.linalg.norm(KalmanOut[:,0:numObs] - expectedK)


    if (errorNorm > 1.0E-12):
        print errorNorm
        testFailCount += 1
        testMessages.append("Kalman Gain update failure \n")

    # ###################################################################################
    # ## Test the EKF update
    # ###################################################################################

    KGain = [1.,2.,3., 0., 1., 2., 1., 0., 1.]
    for i in range(NUMSTATES*8-NUMSTATES*3):
        KGain.append(0.)
    inputStates = [2,1,0.75]
    xbar = [0.1, 0.2, 0.01]
    numObs = 3
    h = [1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0.,
         0., 0., 0., 0., 0., 0., 0., 0., 0.]
    covar = [1., 0., 1.,
             0., 1., 0.,
             1., 0., 1.,
             ]
    noise = 0.01
    inputY = np.zeros(3)
    for j in range(3):
        inputY[j] = np.array(cssCos[j]) - np.dot(np.array(inputStates)[0:3], np.array(cssNormals)[j * 3:(j + 1) * 3])
    inputY = inputY.tolist()

    stateError = okeefeEKF.new_doubleArray(NUMSTATES)
    covarMat = okeefeEKF.new_doubleArray(NUMSTATES*NUMSTATES)
    inputs = okeefeEKF.new_doubleArray(NUMSTATES)


    for i in range(NUMSTATES):
        okeefeEKF.doubleArray_setitem(stateError, i, 0.)
        okeefeEKF.doubleArray_setitem(inputs, i, inputStates[i])
        for j in range(NUMSTATES):
            okeefeEKF.doubleArray_setitem(covarMat,i+j,0.)

    okeefeEKF.okeefeEKFUpdate(KGain, covar, noise, numObs, inputY, h, inputs, stateError, covarMat)

    stateOut = []
    covarOut = []
    errorOut = []
    for i in range(NUMSTATES):
        stateOut.append(okeefeEKF.doubleArray_getitem(inputs, i))
        errorOut.append(okeefeEKF.doubleArray_getitem(stateError, i))
    for j in range(NUMSTATES*NUMSTATES):
        covarOut.append(okeefeEKF.doubleArray_getitem(covarMat, j))

    # Fill in expected values for test
    KK = np.array(KGain)[0:NUMSTATES*3].reshape([NUMSTATES,3])
    expectedStates = np.array(inputStates) + np.dot(KK, np.array(inputY))
    H = np.array(h).reshape([8,NUMSTATES])[0:3,:]
    Pk = np.array(covar).reshape([NUMSTATES, NUMSTATES])
    R = noise * np.eye(3)
    expectedP = np.dot(np.dot(np.eye(NUMSTATES) - np.dot(KK, H), Pk), np.transpose(np.eye(NUMSTATES) - np.dot(KK, H))) + np.dot(KK, np.dot(R,KK.T))

    errorNorm = np.zeros(2)
    errorNorm[0] = np.linalg.norm(np.array(stateOut) - expectedStates)
    errorNorm[1] = np.linalg.norm(expectedP - np.array(covarOut).reshape([NUMSTATES,NUMSTATES]))
    for i in range(2):
        if(errorNorm[i] > 1.0E-12):
            testFailCount += 1
            testMessages.append("EKF update failure \n")
    #
    # ###################################################################################
    # ## Test the CKF update
    # ###################################################################################

    KGain = [1., 2., 3.]
    for i in range(NUMSTATES * 8 - NUMSTATES * 3):
        KGain.append(0.)
    inputStates = [2, 1, 0.75]
    xbar = [0.1, 0.2, 0.01]
    numObs = 3
    h = [1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
         0., 0., 0., 0., 0., 0.]
    covar = [1., 0., 1.,
             0., 1., 0.,
             1., 0., 1.]
    noise =0.01
    inputY = np.zeros(3)
    for j in range(3):
        inputY[j] = np.array(cssCos[j]) - np.dot(np.array(inputStates)[0:3],
                                                 np.array(cssNormals)[j * 3:(j + 1) * 3])
    inputY = inputY.tolist()

    stateError = okeefeEKF.new_doubleArray(NUMSTATES)
    covarMat = okeefeEKF.new_doubleArray(NUMSTATES * NUMSTATES)

    for i in range(NUMSTATES):
        okeefeEKF.doubleArray_setitem(stateError, i, xbar[i])
        for j in range(NUMSTATES):
            okeefeEKF.doubleArray_setitem(covarMat, i + j, 0.)

    okeefeEKF.sunlineCKFUpdate(xbar, KGain, covar, noise, numObs, inputY, h, stateError, covarMat)

    covarOut = []
    errorOut = []
    for i in range(NUMSTATES):
        errorOut.append(okeefeEKF.doubleArray_getitem(stateError, i))
    for j in range(NUMSTATES*NUMSTATES):
        covarOut.append(okeefeEKF.doubleArray_getitem(covarMat, j))

    # Fill in expected values for test
    KK = np.array(KGain)[0:NUMSTATES * 3].reshape([NUMSTATES, 3])
    H = np.array(h).reshape([8, NUMSTATES])[0:3, :]
    expectedStateError = np.array(xbar) + np.dot(KK, (np.array(inputY) - np.dot(H, np.array(xbar))))
    Pk = np.array(covar).reshape([NUMSTATES, NUMSTATES])
    expectedP = np.dot(np.dot(np.eye(NUMSTATES) - np.dot(KK, H), Pk), np.transpose(np.eye(NUMSTATES) - np.dot(KK, H))) + np.dot(KK,
                                                                                                                np.dot(
                                                                                                                    R,
                                                                                                                    KK.T))

    errorNorm = np.zeros(2)
    errorNorm[0] = np.linalg.norm(np.array(errorOut) - expectedStateError)
    errorNorm[1] = np.linalg.norm(expectedP - np.array(covarOut).reshape([NUMSTATES, NUMSTATES]))
    for i in range(2):
        if (errorNorm[i] > 1.0E-12):
            testFailCount += 1
            testMessages.append("CKF update failure \n")

    # print out success message if no error were found
    if testFailCount == 0:
        print "PASSED: " + " EKF individual tests"

    # return fail count and join into a single string all messages in the list
    # testMessage
    return [testFailCount, ''.join(testMessages)]

####################################################################################
# Test for the time and update with static states (zero d_dot)
####################################################################################
def StatePropStatic():
    # 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

    NUMSTATES=3
    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()
    unitTestSim.TotalSim.terminateSimulation()

    # 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 = okeefeEKF.okeefeEKFConfig()
    moduleWrap = alg_contain.AlgContain(moduleConfig,
                                        okeefeEKF.Update_okeefeEKF,
                                        okeefeEKF.SelfInit_okeefeEKF,
                                        okeefeEKF.CrossInit_okeefeEKF,
                                        okeefeEKF.Reset_okeefeEKF)
    moduleWrap.ModelTag = "okeefeEKF"

    # Add test module to runtime call list
    unitTestSim.AddModelToTask(unitTaskName, moduleWrap, moduleConfig)

    setupFilterData(moduleConfig)
    moduleConfig.omega = [0.,0.,0.]
    unitTestSim.AddVariableForLogging('okeefeEKF.covar', testProcessRate * 10, 0, 8)
    unitTestSim.AddVariableForLogging('okeefeEKF.state', testProcessRate * 10, 0, 2)
    unitTestSim.InitializeSimulation()
    unitTestSim.ConfigureStopTime(macros.sec2nano(8000.0))
    unitTestSim.ExecuteSimulation()

    stateLog = unitTestSim.GetLogVariableData('okeefeEKF.state')


    for i in range(NUMSTATES):
        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("Static state propagation failure \n")

    unitTestSim.terminateSimulation()

    # print out success message if no error were found
    if testFailCount == 0:
        print "PASSED: " + "EKF static state propagation"

    # return fail count and join into a single string all messages in the list
    # testMessage
    return [testFailCount, ''.join(testMessages)]


####################################################################################
# Test for the time and update with changing states non-zero omega
####################################################################################
def StatePropVariable(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

    NUMSTATES=3

    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()
    unitTestSim.TotalSim.terminateSimulation()

    # 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 = okeefeEKF.okeefeEKFConfig()
    moduleWrap = alg_contain.AlgContain(moduleConfig,
                                        okeefeEKF.Update_okeefeEKF,
                                        okeefeEKF.SelfInit_okeefeEKF,
                                        okeefeEKF.CrossInit_okeefeEKF,
                                        okeefeEKF.Reset_okeefeEKF)
    moduleWrap.ModelTag = "okeefeEKF"



    # Add test module to runtime call list
    unitTestSim.AddModelToTask(unitTaskName, moduleWrap, moduleConfig)

    setupFilterData(moduleConfig)

    InitialState = moduleConfig.state
    Initialx = moduleConfig.x
    InitialCovar = moduleConfig.covar
    InitOmega = moduleConfig.omega

    moduleConfig.state = InitialState
    unitTestSim.AddVariableForLogging('okeefeEKF.covar', testProcessRate, 0, 8)
    unitTestSim.AddVariableForLogging('okeefeEKF.stateTransition', testProcessRate, 0, 8)
    unitTestSim.AddVariableForLogging('okeefeEKF.state', testProcessRate , 0, 2)
    unitTestSim.AddVariableForLogging('okeefeEKF.x', testProcessRate , 0, 2)
    unitTestSim.AddVariableForLogging('okeefeEKF.omega', testProcessRate , 0, 2)
    unitTestSim.InitializeSimulation()
    unitTestSim.ConfigureStopTime(macros.sec2nano(1000.0))
    unitTestSim.ExecuteSimulation()


    covarLog = unitTestSim.GetLogVariableData('okeefeEKF.covar')
    stateLog = unitTestSim.GetLogVariableData('okeefeEKF.state')
    stateErrorLog = unitTestSim.GetLogVariableData('okeefeEKF.x')
    stmLog = unitTestSim.GetLogVariableData('okeefeEKF.stateTransition')
    omegaLog = unitTestSim.GetLogVariableData('okeefeEKF.omega')

    dt = 0.5
    expectedOmega = np.zeros([2001, (NUMSTATES + 1)])
    expectedStateArray = np.zeros([2001,(NUMSTATES+1)])
    expectedPrevArray = np.zeros([2001,(NUMSTATES+1)])
    expectedStateArray[0,1:(NUMSTATES+1)] = np.array(InitialState)
    expectedOmega[0,1:(NUMSTATES+1)] = np.array(InitOmega)

    expectedXBar = np.zeros([2001,NUMSTATES+1])
    expectedXBar[0,1:(NUMSTATES+1)] = np.array(Initialx)

    expectedSTM = np.zeros([2001,NUMSTATES,NUMSTATES])
    expectedSTM[0,:,:] = np.eye(NUMSTATES)

    expectedCovar = np.zeros([2001,NUMSTATES*NUMSTATES+1])
    expectedCovar[0,1:(NUMSTATES*NUMSTATES+1)] = np.array(InitialCovar)

    expDynMat = np.zeros([2001,NUMSTATES,NUMSTATES])
    Gamma = dt ** 2. / 2. * np.eye(3)
    ProcNoiseCovar = np.dot(Gamma, np.dot(moduleConfig.qProcVal*np.eye(3),Gamma.T))

    for i in range(1,2001):
        expectedStateArray[i,0] = dt*i*1E9
        expectedPrevArray[i,0] = dt*i*1E9
        expectedOmega[i,0] = dt*i*1E9
        expectedCovar[i,0] =  dt*i*1E9
        expectedXBar[i,0] = dt*i*1E9

        #Simulate sunline Dyn Mat
        expDynMat[i-1, :, :] = - np.array([[0., -expectedOmega[i-1, 3], expectedOmega[i-1,2]],
                                         [expectedOmega[i-1,3], 0., -expectedOmega[i-1,1]],
                                         [ -expectedOmega[i-1,2], expectedOmega[i-1,1], 0.]])

        #Simulate STM State prop
        expectedStateArray[i,1:(NUMSTATES+1)] =  np.array(expectedStateArray[i-1,1:(NUMSTATES+1)] - dt*(np.cross(np.array(expectedOmega[i-1,1:(NUMSTATES+1)]), np.array(expectedStateArray[i-1,1:(NUMSTATES+1)]))))
        expectedPrevArray[i, 1:(NUMSTATES + 1)] = expectedStateArray[i-1,1:(NUMSTATES+1)]
        expectedSTM[i,:,:] = dt * np.dot(expDynMat[i-1,:,:], np.eye(NUMSTATES)) + np.eye(NUMSTATES)

        # Simulate Rate compute
        normdk = np.linalg.norm(expectedStateArray[i, 1:(NUMSTATES + 1)])
        nomrdkmin1 = np.linalg.norm(expectedPrevArray[i, 1:(NUMSTATES + 1)])
        arg = np.dot(expectedStateArray[i, 1:(NUMSTATES + 1)], expectedPrevArray[i , 1:(NUMSTATES + 1)]) / (normdk * nomrdkmin1)
        if arg>1:
            expectedOmega[i, 1:(NUMSTATES + 1)] = 1./dt*np.cross(expectedStateArray[i, 1:(NUMSTATES + 1)],
                                                           expectedPrevArray[i, 1:(NUMSTATES + 1)]) / (normdk * nomrdkmin1) * np.arccos(1)
        elif arg<-1:
            expectedOmega[i, 1:(NUMSTATES + 1)] = 1./dt*np.cross(expectedStateArray[i, 1:(NUMSTATES + 1)],
                                                           expectedPrevArray[i, 1:(NUMSTATES + 1)]) / (
                                                  normdk * nomrdkmin1) * np.arccos(-1)

        else:
            expectedOmega[i, 1:(NUMSTATES + 1)] = 1./dt*np.cross(expectedStateArray[i, 1:(NUMSTATES + 1)],expectedPrevArray[i, 1:(NUMSTATES + 1)]) / (normdk * nomrdkmin1) * np.arccos(arg)

        expectedXBar[i, 1:(NUMSTATES+1)] = np.dot(expectedSTM[i, :, :], expectedXBar[i - 1, 1:(NUMSTATES+1)])
        expectedCovar[i,1:(NUMSTATES*NUMSTATES+1)] = (np.dot(expectedSTM[i,:,:], np.dot(np.reshape(expectedCovar[i-1,1:(NUMSTATES*NUMSTATES+1)],[NUMSTATES,NUMSTATES]), np.transpose(expectedSTM[i,:,:])))+ ProcNoiseCovar).flatten()

    FilterPlots.StatesVsExpected(stateLog, expectedStateArray, show_plots)
    FilterPlots.StatesPlotCompare(stateErrorLog, expectedXBar, covarLog, expectedCovar, show_plots)
    FilterPlots.OmegaVsExpected(expectedOmega, omegaLog, show_plots)

    for j in range(1,2001):
        for i in range(NUMSTATES):
            if (abs(stateLog[j, i + 1] - expectedStateArray[j, i + 1]) > 1.0E-10):
                testFailCount += 1
                testMessages.append("General state propagation failure: State Prop \n")
            if (abs(stateErrorLog[j, i + 1] - expectedXBar[j, i + 1]) > 1.0E-10):
                testFailCount += 1
                testMessages.append("General state propagation failure: State Error Prop \n")

        for i in range(NUMSTATES*NUMSTATES):
            if (abs(covarLog[j, i + 1] - expectedCovar[j, i + 1]) > 1.0E-8):
                print abs(covarLog[j, i + 1] - expectedCovar[j, i + 1])
                abs(covarLog[j, i + 1] - expectedCovar[j, i + 1])
                testFailCount += 1
                # testMessages.append("General state propagation failure: Covariance Prop \n")
            if (abs(stmLog[j, i + 1] - expectedSTM[j,:].flatten()[i]) > 1.0E-10):
                testFailCount += 1
                testMessages.append("General state propagation failure: STM Prop \n")

    # print out success message if no error were found
    if testFailCount == 0:
        print "PASSED: " + "EKF general state propagation"

    # return fail count and join into a single string all messages in the list
    # testMessage
    return [testFailCount, ''.join(testMessages)]


####################################################################################
# Test for the full filter with time and measurement update
####################################################################################
def StateUpdateSunLine(show_plots, SimHalfLength, AddMeasNoise, testVector1, testVector2, stateGuess):
    # 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
    NUMSTATES=3

    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()
    unitTestSim.TotalSim.terminateSimulation()

    # 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 = okeefeEKF.okeefeEKFConfig()
    moduleWrap = alg_contain.AlgContain(moduleConfig,
                                        okeefeEKF.Update_okeefeEKF,
                                        okeefeEKF.SelfInit_okeefeEKF,
                                        okeefeEKF.CrossInit_okeefeEKF,
                                        okeefeEKF.Reset_okeefeEKF)
    moduleWrap.ModelTag = "okeefeEKF"

    # Add test module to runtime call list
    unitTestSim.AddModelToTask(unitTaskName, moduleWrap, moduleConfig)
    setupFilterData(moduleConfig)
    moduleConfig.omega = [0.,0.,0.]

    # Set up some test parameters

    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],
    ]
    CSSBias = [1.0 for i in range(len(CSSOrientationList))]
    totalCSSList = []
    i=0
    for CSSHat in CSSOrientationList:
        newCSS = fswMessages.CSSUnitConfigFswMsg()
        newCSS.CBias = CSSBias[i]
        newCSS.nHat_B = CSSHat
        totalCSSList.append(newCSS)
        i = i + 1
    cssConstelation.nCSS = len(CSSOrientationList)
    cssConstelation.cssVals = totalCSSList
    msgSize = cssConstelation.getStructSize()
    inputData = cssComm.CSSArraySensorIntMsg()


    inputMessageSize = inputData.getStructSize()
    unitTestSim.TotalSim.CreateNewMessage("TestProcess", "css_config_data",
                                          msgSize, 2, "CSSConstellation")
    unitTestSim.TotalSim.CreateNewMessage(unitProcessName,
                                          moduleConfig.cssDataInMsgName,
                                          inputMessageSize,
                                          2)  # number of buffers (leave at 2 as default, don't make zero)
    unitTestSim.TotalSim.WriteMessageData("css_config_data", msgSize, 0, cssConstelation)



    dt =0.5
    stateTarget1 = testVector1
    moduleConfig.state = stateGuess
    moduleConfig.x = (np.array(stateTarget1) - np.array(stateGuess)).tolist()
    unitTestSim.TotalSim.logThisMessage('sunline_filter_data', testProcessRate)
    unitTestSim.AddVariableForLogging('okeefeEKF.x', testProcessRate , 0, 2, 'double')

    unitTestSim.InitializeSimulation()



    for i in range(SimHalfLength):
        if i > 20:
            dotList = []
            for element in CSSOrientationList:
                if AddMeasNoise:
                    dotProd = np.dot(np.array(element), np.array(testVector1)[0:3]) + np.random.normal(0., moduleConfig.qObsVal)
                else:
                    dotProd = np.dot(np.array(element), np.array(testVector1)[0:3])
                dotList.append(dotProd)
            inputData.CosValue = dotList

            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", range(3))
    covarLog = unitTestSim.pullMessageLogData('sunline_filter_data' + ".covar", range(3*3))


    if not AddMeasNoise:
        for i in range(NUMSTATES):
            if (abs(covarLog[-1, i * NUMSTATES + 1 + i] - covarLog[0, i * NUMSTATES + 1 + i] / 100.) > 1E-1):
                testFailCount += 1
                testMessages.append("Covariance update failure")
            if (abs(stateLog[-1, i + 1] - stateTarget1[i]) > 1.0E-10):
                testFailCount += 1
                testMessages.append("State update failure")
    else:
        for i in range(NUMSTATES):
            if (abs(covarLog[-1, i * NUMSTATES + 1 + i] - covarLog[0, i * NUMSTATES + 1 + i] / 100.) > 1E-1):
                testFailCount += 1
                testMessages.append("Covariance update failure with noise")
            if (abs(stateLog[-1, i + 1] - stateTarget1[i]) > 1.0E-2):
                testFailCount += 1
                testMessages.append("State update failure with noise")


    stateTarget2 = testVector2

    inputData = cssComm.CSSArraySensorIntMsg()
    for i in range(SimHalfLength):
        if i > 20:
            dotList = []
            for element in CSSOrientationList:
                if AddMeasNoise:
                    dotProd = np.dot(np.array(element), np.array(testVector2)[0:3])  + np.random.normal(0., moduleConfig.qObsVal)
                else:
                    dotProd = np.dot(np.array(element), np.array(testVector2)[0:3])
                dotList.append(dotProd)
            inputData.CosValue = dotList

            unitTestSim.TotalSim.WriteMessageData(moduleConfig.cssDataInMsgName,
                                                  inputMessageSize,
                                                  unitTestSim.TotalSim.CurrentNanos,
                                                  inputData)
        unitTestSim.ConfigureStopTime(macros.sec2nano((i + SimHalfLength+1) * 0.5))
        unitTestSim.ExecuteSimulation()

    stateLog = unitTestSim.pullMessageLogData('sunline_filter_data' + ".state", range(3))
    postFitLog = unitTestSim.pullMessageLogData('sunline_filter_data' + ".postFitRes", range(8))
    covarLog = unitTestSim.pullMessageLogData('sunline_filter_data' + ".covar", range(3*3))
    stateErrorLog = unitTestSim.GetLogVariableData('okeefeEKF.x')


    if not AddMeasNoise:
        for i in range(NUMSTATES):
            if (abs(covarLog[-1, i * NUMSTATES + 1 + i] - covarLog[0, i * NUMSTATES + 1 + i] / 100.) > 1E-1):
                testFailCount += 1
                testMessages.append("Covariance update failure")
            if (abs(stateLog[-1, i + 1] - stateTarget2[i]) > 1.0E-10):
                testFailCount += 1
                testMessages.append("State update failure")
    else:
        for i in range(NUMSTATES):
            if (abs(covarLog[-1, i * NUMSTATES + 1 + i] - covarLog[0, i * NUMSTATES + 1 + i] / 100.) > 1E-1):
                testFailCount += 1
                testMessages.append("Covariance update failure")
            if (abs(stateLog[-1, i + 1] - stateTarget2[i]) > 1.0E-2):
                testFailCount += 1
                testMessages.append("State update failure")


    target1 = np.array(testVector1)
    target2 = np.array(testVector2)
    FilterPlots.StatesPlot(stateErrorLog, covarLog, show_plots)
    FilterPlots.StatesVsTargets(target1, target2, stateLog, show_plots)
    FilterPlots.PostFitResiduals(postFitLog, moduleConfig.qObsVal, show_plots)

    # print out success message if no error were found
    if testFailCount == 0:
        print "PASSED: " + "EKF full test"

    # return fail count and join into a single string all messages in the list
    # testMessage
    return [testFailCount, ''.join(testMessages)]



if __name__ == "__main__":
    # StateUpdateSunLine(True, 200, True ,[-0.7, 0.7, 0.0] ,[0.8, 0.9, 0.0], [0.7, 0.7, 0.0])
    # sunline_individual_test()
    #StatePropStatic()
    StatePropVariable(True)
<filename>src/fswAlgorithms/attDetermination/okeefeEKF/_UnitTest/test_okeefeEKF.py
''' '''
'''
 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 as np
import pytest

filename = inspect.getframeinfo(inspect.currentframe()).filename
path = os.path.dirname(os.path.abspath(filename))
splitPath = path.split('FswAlgorithms')
sys.path.append(splitPath[0] + '/modules')
sys.path.append(splitPath[0] + '/PythonModules')

import SunLineOEKF_test_utilities as FilterPlots
from Basilisk.fswAlgorithms import okeefeEKF
from Basilisk.utilities import SimulationBaseClass
from Basilisk.simulation import alg_contain
from Basilisk.fswAlgorithms import cssComm
from Basilisk.utilities import macros
from Basilisk.utilities import unitTestSupport  # general support file with common unit test functions
from Basilisk.fswAlgorithms import fswMessages


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

    filterObject.sensorUseThresh = 0.
    filterObject.state = [1.0, 1.0, 1.0]
    filterObject.omega = [0.1, 0.2, 0.1]
    filterObject.x = [1.0, 0.0, 1.0]
    filterObject.covar = [0.4, 0.0, 0.0,
                          0.0, 0.4, 0.0,
                          0.0, 0.0, 0.4]

    filterObject.qProcVal = 0.1**2
    filterObject.qObsVal = 0.001
    filterObject.eKFSwitch = 5. #If low (0-5), the CKF kicks in easily, if high (>10) it's mostly only EKF

def test_all_functions_oekf(show_plots):
    [testResults, testMessage] = sunline_individual_test()
    assert testResults < 1, testMessage
    [testResults, testMessage] = StatePropStatic()
    assert testResults < 1, testMessage
    [testResults, testMessage] = StatePropVariable(show_plots)
    assert testResults < 1, testMessage

# 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(True)

# The following 'parametrize' function decorator provides the parameters and expected results for each
#   of the multiple test runs for this test.
@pytest.mark.parametrize("SimHalfLength, AddMeasNoise , testVector1 , testVector2, stateGuess", [
    (200, True ,[-0.7, 0.7, 0.0] ,[0.8, 0.9, 0.0], [0.7, 0.7, 0.0]),
    (2000, True ,[-0.7, 0.7, 0.0] ,[0.8, 0.9, 0.0], [0.7, 0.7, 0.0]),
    (200, False ,[-0.7, 0.7, 0.0] ,[0.8, 0.9, 0.0], [0.7, 0.7, 0.0]),
    (200, False ,[0., 0.4, -0.4] ,[0., 0.7, 0.2], [0.3, 0.0, 0.6]),
    (200, True ,[0., 0.4, -0.4] ,[0.4, 0.5, 0.], [0.7, 0.7, 0.0]),
    (200, True ,[-0.7, 0.7, 0.0] ,[0.8, 0.9, 0.0], [0.7, 0.7, 0.0])
])


# 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_
def test_all_sunline_oekf(show_plots, SimHalfLength, AddMeasNoise, testVector1, testVector2, stateGuess):
    [testResults, testMessage] = StateUpdateSunLine(show_plots, SimHalfLength, AddMeasNoise, testVector1, testVector2, stateGuess)
    assert testResults < 1, testMessage


def sunline_individual_test():
    # 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

    NUMSTATES = 3
    ###################################################################################
    ## Testing dynamics matrix computation
    ###################################################################################

    inputOmega = [0.1, 0.2, 0.1]
    dt =0.5

    expDynMat = - np.array([[0., -inputOmega[2], inputOmega[1]],
                            [inputOmega[2], 0., -inputOmega[0]],
                            [ -inputOmega[1], inputOmega[0], 0.]])


    dynMat = okeefeEKF.new_doubleArray(3*3)
    for i in range(9):
        okeefeEKF.doubleArray_setitem(dynMat, i, 0.0)
    okeefeEKF.sunlineDynMatrix(inputOmega, dt, dynMat)

    DynOut = []
    for i in range(NUMSTATES*NUMSTATES):
        DynOut.append(okeefeEKF.doubleArray_getitem(dynMat, i))

    DynOut = np.array(DynOut).reshape(3, 3)
    errorNorm = np.linalg.norm(expDynMat - DynOut)
    if(errorNorm > 1.0E-12):
        print errorNorm
        testFailCount += 1
        testMessages.append("Dynamics Matrix generation Failure \n")


    ###################################################################################
    ## Testing omega computation
    ###################################################################################

    inputStates = [2,1,0.75]
    inputPrevStates = [1,0.1,0.5]
    norm1 = np.linalg.norm(np.array(inputStates))
    norm2 =  np.linalg.norm(np.array(inputPrevStates))
    dt =0.5

    expOmega = 1./dt*np.cross(np.array(inputStates),np.array(inputPrevStates))/(norm1*norm2)*np.arccos(np.dot(np.array(inputStates),np.array(inputPrevStates))/(norm1*norm2))

    omega = okeefeEKF.new_doubleArray(NUMSTATES)
    for i in range(3):
        okeefeEKF.doubleArray_setitem(omega, i, 0.0)
    okeefeEKF.sunlineRateCompute(inputStates, dt, inputPrevStates, omega)

    omegaOut = []
    for i in range(NUMSTATES):
        omegaOut.append(okeefeEKF.doubleArray_getitem(omega, i))

    omegaOut = np.array(omegaOut)
    errorNorm = np.linalg.norm(expOmega - omegaOut)
    if(errorNorm > 1.0E-12):
        print errorNorm
        testFailCount += 1
        testMessages.append("Dynamics Matrix generation Failure \n")

    ###################################################################################
    ## STM and State Test
    ###################################################################################

    inputStates = [2,1,0.75]
    inputOmega = [0.1, 0.2, 0.1]
    dt =0.5
    stateTransition = okeefeEKF.new_doubleArray(NUMSTATES*NUMSTATES)
    states = okeefeEKF.new_doubleArray(NUMSTATES)
    prev_states = okeefeEKF.new_doubleArray(NUMSTATES)
    for i in range(NUMSTATES):
        okeefeEKF.doubleArray_setitem(states, i, inputStates[i])
        for j in range(NUMSTATES):
            if i==j:
                okeefeEKF.doubleArray_setitem(stateTransition, NUMSTATES*i+j, 1.0)
            else:
                okeefeEKF.doubleArray_setitem(stateTransition, NUMSTATES*i+j, 0.0)

    okeefeEKF.sunlineStateSTMProp(expDynMat.flatten().tolist(), dt, inputOmega, states, prev_states, stateTransition)

    PropStateOut = []
    PropSTMOut = []
    for i in range(NUMSTATES):
        PropStateOut.append(okeefeEKF.doubleArray_getitem(states, i))
    for i in range(NUMSTATES*NUMSTATES):
        PropSTMOut.append(okeefeEKF.doubleArray_getitem(stateTransition, i))

    STMout = np.array(PropSTMOut).reshape([NUMSTATES,NUMSTATES])
    StatesOut = np.array(PropStateOut)

    expectedSTM = dt*np.dot(expDynMat, np.eye(NUMSTATES)) + np.eye(NUMSTATES)
    expectedStates = np.zeros(NUMSTATES)
    inputStatesArray = np.array(inputStates)
    ## Equations when removing the unobservable states from d_dot
    expectedStates[0:3] = np.array(inputStatesArray - dt*(np.cross(np.array(inputOmega), np.array(inputStatesArray))))
    errorNormSTM = np.linalg.norm(expectedSTM - STMout)
    errorNormStates = np.linalg.norm(expectedStates - StatesOut)

    if(errorNormSTM > 1.0E-12):
        print errorNormSTM
        testFailCount += 1
        testMessages.append("STM Propagation Failure \n")


    if(errorNormStates > 1.0E-12):
        print errorNormStates
        testFailCount += 1
        testMessages.append("State Propagation Failure \n")



    ###################################################################################
    # ## Test the H and yMeas matrix generation as well as the observation count
    # ###################################################################################
    numCSS = 4
    cssCos = [np.cos(np.deg2rad(10.)), np.cos(np.deg2rad(25.)), np.cos(np.deg2rad(5.)), np.cos(np.deg2rad(90.))]
    sensorTresh = np.cos(np.deg2rad(50.))
    cssNormals = [1.,0.,0.,0.,1.,0., 0.,0.,1., 1./np.sqrt(2), 1./np.sqrt(2),0.]
    cssBias = [1.0 for i in range(numCSS)]

    measMat = okeefeEKF.new_doubleArray(8*NUMSTATES)
    obs = okeefeEKF.new_doubleArray(8)
    yMeas = okeefeEKF.new_doubleArray(8)
    numObs = okeefeEKF.new_intArray(1)

    for i in range(8*NUMSTATES):
        okeefeEKF.doubleArray_setitem(measMat, i, 0.)
    for i in range(8):
        okeefeEKF.doubleArray_setitem(obs, i, 0.0)
        okeefeEKF.doubleArray_setitem(yMeas, i, 0.0)

    okeefeEKF.sunlineHMatrixYMeas(inputStates, numCSS, cssCos, sensorTresh, cssNormals, cssBias, obs, yMeas, numObs, measMat)

    obsOut = []
    yMeasOut = []
    numObsOut = []
    HOut = []
    for i in range(8*NUMSTATES):
        HOut.append(okeefeEKF.doubleArray_getitem(measMat, i))
    for i in range(8):
        yMeasOut.append(okeefeEKF.doubleArray_getitem(yMeas, i))
        obsOut.append(okeefeEKF.doubleArray_getitem(obs, i))
    numObsOut.append(okeefeEKF.intArray_getitem(numObs, 0))

    #Fill in expected values for test
    expectedH = np.zeros([8,NUMSTATES])
    expectedY = np.zeros(8)
    for j in range(3):
        expectedH[j,0:3] = np.eye(3)[j,:]
        expectedY[j] =np.array(cssCos[j]) - np.dot(np.array(inputStates)[0:3], np.array(cssNormals)[j*3:(j+1)*3])
    expectedObs = np.array([np.cos(np.deg2rad(10.)), np.cos(np.deg2rad(25.)), np.cos(np.deg2rad(5.)),0.,0.,0.,0.,0.])
    expectedNumObs = 3

    HOut = np.array(HOut).reshape([8, NUMSTATES])
    errorNorm = np.zeros(4)
    errorNorm[0] = np.linalg.norm(HOut - expectedH)
    errorNorm[1] = np.linalg.norm(yMeasOut - expectedY)
    errorNorm[2] = np.linalg.norm(obsOut - expectedObs)
    errorNorm[3] = np.linalg.norm(numObsOut[0] - expectedNumObs)
    for i in range(4):
        if(errorNorm[i] > 1.0E-12):
            testFailCount += 1
            testMessages.append("H and yMeas update failure \n")

    # ###################################################################################
    # ## Test the Kalman Gain
    # ###################################################################################

    numObs = 3
    h = [1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
         0., 0., 0., 0., 0., 0.]
    covar = [1., 0., 1.,
        0., 1., 0.,
        1., 0., 1. ]
    noise= 0.01

    Kalman = okeefeEKF.new_doubleArray(NUMSTATES * 8)

    for i in range(8 * NUMSTATES):
        okeefeEKF.doubleArray_setitem(Kalman, i, 0.)

    okeefeEKF.sunlineKalmanGain(covar, h, noise, numObs, Kalman)

    KalmanOut = []
    for i in range(8 * NUMSTATES):
        KalmanOut.append(okeefeEKF.doubleArray_getitem(Kalman, i))

    # Fill in expected values for test
    Hmat = np.array(h).reshape([8,NUMSTATES])
    Pk = np.array(covar).reshape([NUMSTATES,NUMSTATES])
    R = noise*np.eye(3)
    expectedK = np.dot(np.dot(Pk, Hmat[0:numObs,:].T), np.linalg.inv(np.dot(np.dot(Hmat[0:numObs,:], Pk), Hmat[0:numObs,:].T) + R[0:numObs,0:numObs]))

    KalmanOut = np.array(KalmanOut)[0:NUMSTATES*numObs].reshape([NUMSTATES, 3])
    errorNorm = np.linalg.norm(KalmanOut[:,0:numObs] - expectedK)


    if (errorNorm > 1.0E-12):
        print errorNorm
        testFailCount += 1
        testMessages.append("Kalman Gain update failure \n")

    # ###################################################################################
    # ## Test the EKF update
    # ###################################################################################

    KGain = [1.,2.,3., 0., 1., 2., 1., 0., 1.]
    for i in range(NUMSTATES*8-NUMSTATES*3):
        KGain.append(0.)
    inputStates = [2,1,0.75]
    xbar = [0.1, 0.2, 0.01]
    numObs = 3
    h = [1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0.,
         0., 0., 0., 0., 0., 0., 0., 0., 0.]
    covar = [1., 0., 1.,
             0., 1., 0.,
             1., 0., 1.,
             ]
    noise = 0.01
    inputY = np.zeros(3)
    for j in range(3):
        inputY[j] = np.array(cssCos[j]) - np.dot(np.array(inputStates)[0:3], np.array(cssNormals)[j * 3:(j + 1) * 3])
    inputY = inputY.tolist()

    stateError = okeefeEKF.new_doubleArray(NUMSTATES)
    covarMat = okeefeEKF.new_doubleArray(NUMSTATES*NUMSTATES)
    inputs = okeefeEKF.new_doubleArray(NUMSTATES)


    for i in range(NUMSTATES):
        okeefeEKF.doubleArray_setitem(stateError, i, 0.)
        okeefeEKF.doubleArray_setitem(inputs, i, inputStates[i])
        for j in range(NUMSTATES):
            okeefeEKF.doubleArray_setitem(covarMat,i+j,0.)

    okeefeEKF.okeefeEKFUpdate(KGain, covar, noise, numObs, inputY, h, inputs, stateError, covarMat)

    stateOut = []
    covarOut = []
    errorOut = []
    for i in range(NUMSTATES):
        stateOut.append(okeefeEKF.doubleArray_getitem(inputs, i))
        errorOut.append(okeefeEKF.doubleArray_getitem(stateError, i))
    for j in range(NUMSTATES*NUMSTATES):
        covarOut.append(okeefeEKF.doubleArray_getitem(covarMat, j))

    # Fill in expected values for test
    KK = np.array(KGain)[0:NUMSTATES*3].reshape([NUMSTATES,3])
    expectedStates = np.array(inputStates) + np.dot(KK, np.array(inputY))
    H = np.array(h).reshape([8,NUMSTATES])[0:3,:]
    Pk = np.array(covar).reshape([NUMSTATES, NUMSTATES])
    R = noise * np.eye(3)
    expectedP = np.dot(np.dot(np.eye(NUMSTATES) - np.dot(KK, H), Pk), np.transpose(np.eye(NUMSTATES) - np.dot(KK, H))) + np.dot(KK, np.dot(R,KK.T))

    errorNorm = np.zeros(2)
    errorNorm[0] = np.linalg.norm(np.array(stateOut) - expectedStates)
    errorNorm[1] = np.linalg.norm(expectedP - np.array(covarOut).reshape([NUMSTATES,NUMSTATES]))
    for i in range(2):
        if(errorNorm[i] > 1.0E-12):
            testFailCount += 1
            testMessages.append("EKF update failure \n")
    #
    # ###################################################################################
    # ## Test the CKF update
    # ###################################################################################

    KGain = [1., 2., 3.]
    for i in range(NUMSTATES * 8 - NUMSTATES * 3):
        KGain.append(0.)
    inputStates = [2, 1, 0.75]
    xbar = [0.1, 0.2, 0.01]
    numObs = 3
    h = [1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
         0., 0., 0., 0., 0., 0.]
    covar = [1., 0., 1.,
             0., 1., 0.,
             1., 0., 1.]
    noise =0.01
    inputY = np.zeros(3)
    for j in range(3):
        inputY[j] = np.array(cssCos[j]) - np.dot(np.array(inputStates)[0:3],
                                                 np.array(cssNormals)[j * 3:(j + 1) * 3])
    inputY = inputY.tolist()

    stateError = okeefeEKF.new_doubleArray(NUMSTATES)
    covarMat = okeefeEKF.new_doubleArray(NUMSTATES * NUMSTATES)

    for i in range(NUMSTATES):
        okeefeEKF.doubleArray_setitem(stateError, i, xbar[i])
        for j in range(NUMSTATES):
            okeefeEKF.doubleArray_setitem(covarMat, i + j, 0.)

    okeefeEKF.sunlineCKFUpdate(xbar, KGain, covar, noise, numObs, inputY, h, stateError, covarMat)

    covarOut = []
    errorOut = []
    for i in range(NUMSTATES):
        errorOut.append(okeefeEKF.doubleArray_getitem(stateError, i))
    for j in range(NUMSTATES*NUMSTATES):
        covarOut.append(okeefeEKF.doubleArray_getitem(covarMat, j))

    # Fill in expected values for test
    KK = np.array(KGain)[0:NUMSTATES * 3].reshape([NUMSTATES, 3])
    H = np.array(h).reshape([8, NUMSTATES])[0:3, :]
    expectedStateError = np.array(xbar) + np.dot(KK, (np.array(inputY) - np.dot(H, np.array(xbar))))
    Pk = np.array(covar).reshape([NUMSTATES, NUMSTATES])
    expectedP = np.dot(np.dot(np.eye(NUMSTATES) - np.dot(KK, H), Pk), np.transpose(np.eye(NUMSTATES) - np.dot(KK, H))) + np.dot(KK,
                                                                                                                np.dot(
                                                                                                                    R,
                                                                                                                    KK.T))

    errorNorm = np.zeros(2)
    errorNorm[0] = np.linalg.norm(np.array(errorOut) - expectedStateError)
    errorNorm[1] = np.linalg.norm(expectedP - np.array(covarOut).reshape([NUMSTATES, NUMSTATES]))
    for i in range(2):
        if (errorNorm[i] > 1.0E-12):
            testFailCount += 1
            testMessages.append("CKF update failure \n")

    # print out success message if no error were found
    if testFailCount == 0:
        print "PASSED: " + " EKF individual tests"

    # return fail count and join into a single string all messages in the list
    # testMessage
    return [testFailCount, ''.join(testMessages)]

####################################################################################
# Test for the time and update with static states (zero d_dot)
####################################################################################
def StatePropStatic():
    # 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

    NUMSTATES=3
    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()
    unitTestSim.TotalSim.terminateSimulation()

    # 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 = okeefeEKF.okeefeEKFConfig()
    moduleWrap = alg_contain.AlgContain(moduleConfig,
                                        okeefeEKF.Update_okeefeEKF,
                                        okeefeEKF.SelfInit_okeefeEKF,
                                        okeefeEKF.CrossInit_okeefeEKF,
                                        okeefeEKF.Reset_okeefeEKF)
    moduleWrap.ModelTag = "okeefeEKF"

    # Add test module to runtime call list
    unitTestSim.AddModelToTask(unitTaskName, moduleWrap, moduleConfig)

    setupFilterData(moduleConfig)
    moduleConfig.omega = [0.,0.,0.]
    unitTestSim.AddVariableForLogging('okeefeEKF.covar', testProcessRate * 10, 0, 8)
    unitTestSim.AddVariableForLogging('okeefeEKF.state', testProcessRate * 10, 0, 2)
    unitTestSim.InitializeSimulation()
    unitTestSim.ConfigureStopTime(macros.sec2nano(8000.0))
    unitTestSim.ExecuteSimulation()

    stateLog = unitTestSim.GetLogVariableData('okeefeEKF.state')


    for i in range(NUMSTATES):
        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("Static state propagation failure \n")

    unitTestSim.terminateSimulation()

    # print out success message if no error were found
    if testFailCount == 0:
        print "PASSED: " + "EKF static state propagation"

    # return fail count and join into a single string all messages in the list
    # testMessage
    return [testFailCount, ''.join(testMessages)]


####################################################################################
# Test for the time and update with changing states non-zero omega
####################################################################################
def StatePropVariable(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

    NUMSTATES=3

    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()
    unitTestSim.TotalSim.terminateSimulation()

    # 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 = okeefeEKF.okeefeEKFConfig()
    moduleWrap = alg_contain.AlgContain(moduleConfig,
                                        okeefeEKF.Update_okeefeEKF,
                                        okeefeEKF.SelfInit_okeefeEKF,
                                        okeefeEKF.CrossInit_okeefeEKF,
                                        okeefeEKF.Reset_okeefeEKF)
    moduleWrap.ModelTag = "okeefeEKF"



    # Add test module to runtime call list
    unitTestSim.AddModelToTask(unitTaskName, moduleWrap, moduleConfig)

    setupFilterData(moduleConfig)

    InitialState = moduleConfig.state
    Initialx = moduleConfig.x
    InitialCovar = moduleConfig.covar
    InitOmega = moduleConfig.omega

    moduleConfig.state = InitialState
    unitTestSim.AddVariableForLogging('okeefeEKF.covar', testProcessRate, 0, 8)
    unitTestSim.AddVariableForLogging('okeefeEKF.stateTransition', testProcessRate, 0, 8)
    unitTestSim.AddVariableForLogging('okeefeEKF.state', testProcessRate , 0, 2)
    unitTestSim.AddVariableForLogging('okeefeEKF.x', testProcessRate , 0, 2)
    unitTestSim.AddVariableForLogging('okeefeEKF.omega', testProcessRate , 0, 2)
    unitTestSim.InitializeSimulation()
    unitTestSim.ConfigureStopTime(macros.sec2nano(1000.0))
    unitTestSim.ExecuteSimulation()


    covarLog = unitTestSim.GetLogVariableData('okeefeEKF.covar')
    stateLog = unitTestSim.GetLogVariableData('okeefeEKF.state')
    stateErrorLog = unitTestSim.GetLogVariableData('okeefeEKF.x')
    stmLog = unitTestSim.GetLogVariableData('okeefeEKF.stateTransition')
    omegaLog = unitTestSim.GetLogVariableData('okeefeEKF.omega')

    dt = 0.5
    expectedOmega = np.zeros([2001, (NUMSTATES + 1)])
    expectedStateArray = np.zeros([2001,(NUMSTATES+1)])
    expectedPrevArray = np.zeros([2001,(NUMSTATES+1)])
    expectedStateArray[0,1:(NUMSTATES+1)] = np.array(InitialState)
    expectedOmega[0,1:(NUMSTATES+1)] = np.array(InitOmega)

    expectedXBar = np.zeros([2001,NUMSTATES+1])
    expectedXBar[0,1:(NUMSTATES+1)] = np.array(Initialx)

    expectedSTM = np.zeros([2001,NUMSTATES,NUMSTATES])
    expectedSTM[0,:,:] = np.eye(NUMSTATES)

    expectedCovar = np.zeros([2001,NUMSTATES*NUMSTATES+1])
    expectedCovar[0,1:(NUMSTATES*NUMSTATES+1)] = np.array(InitialCovar)

    expDynMat = np.zeros([2001,NUMSTATES,NUMSTATES])
    Gamma = dt ** 2. / 2. * np.eye(3)
    ProcNoiseCovar = np.dot(Gamma, np.dot(moduleConfig.qProcVal*np.eye(3),Gamma.T))

    for i in range(1,2001):
        expectedStateArray[i,0] = dt*i*1E9
        expectedPrevArray[i,0] = dt*i*1E9
        expectedOmega[i,0] = dt*i*1E9
        expectedCovar[i,0] =  dt*i*1E9
        expectedXBar[i,0] = dt*i*1E9

        #Simulate sunline Dyn Mat
        expDynMat[i-1, :, :] = - np.array([[0., -expectedOmega[i-1, 3], expectedOmega[i-1,2]],
                                         [expectedOmega[i-1,3], 0., -expectedOmega[i-1,1]],
                                         [ -expectedOmega[i-1,2], expectedOmega[i-1,1], 0.]])

        #Simulate STM State prop
        expectedStateArray[i,1:(NUMSTATES+1)] =  np.array(expectedStateArray[i-1,1:(NUMSTATES+1)] - dt*(np.cross(np.array(expectedOmega[i-1,1:(NUMSTATES+1)]), np.array(expectedStateArray[i-1,1:(NUMSTATES+1)]))))
        expectedPrevArray[i, 1:(NUMSTATES + 1)] = expectedStateArray[i-1,1:(NUMSTATES+1)]
        expectedSTM[i,:,:] = dt * np.dot(expDynMat[i-1,:,:], np.eye(NUMSTATES)) + np.eye(NUMSTATES)

        # Simulate Rate compute
        normdk = np.linalg.norm(expectedStateArray[i, 1:(NUMSTATES + 1)])
        nomrdkmin1 = np.linalg.norm(expectedPrevArray[i, 1:(NUMSTATES + 1)])
        arg = np.dot(expectedStateArray[i, 1:(NUMSTATES + 1)], expectedPrevArray[i , 1:(NUMSTATES + 1)]) / (normdk * nomrdkmin1)
        if arg>1:
            expectedOmega[i, 1:(NUMSTATES + 1)] = 1./dt*np.cross(expectedStateArray[i, 1:(NUMSTATES + 1)],
                                                           expectedPrevArray[i, 1:(NUMSTATES + 1)]) / (normdk * nomrdkmin1) * np.arccos(1)
        elif arg<-1:
            expectedOmega[i, 1:(NUMSTATES + 1)] = 1./dt*np.cross(expectedStateArray[i, 1:(NUMSTATES + 1)],
                                                           expectedPrevArray[i, 1:(NUMSTATES + 1)]) / (
                                                  normdk * nomrdkmin1) * np.arccos(-1)

        else:
            expectedOmega[i, 1:(NUMSTATES + 1)] = 1./dt*np.cross(expectedStateArray[i, 1:(NUMSTATES + 1)],expectedPrevArray[i, 1:(NUMSTATES + 1)]) / (normdk * nomrdkmin1) * np.arccos(arg)

        expectedXBar[i, 1:(NUMSTATES+1)] = np.dot(expectedSTM[i, :, :], expectedXBar[i - 1, 1:(NUMSTATES+1)])
        expectedCovar[i,1:(NUMSTATES*NUMSTATES+1)] = (np.dot(expectedSTM[i,:,:], np.dot(np.reshape(expectedCovar[i-1,1:(NUMSTATES*NUMSTATES+1)],[NUMSTATES,NUMSTATES]), np.transpose(expectedSTM[i,:,:])))+ ProcNoiseCovar).flatten()

    FilterPlots.StatesVsExpected(stateLog, expectedStateArray, show_plots)
    FilterPlots.StatesPlotCompare(stateErrorLog, expectedXBar, covarLog, expectedCovar, show_plots)
    FilterPlots.OmegaVsExpected(expectedOmega, omegaLog, show_plots)

    for j in range(1,2001):
        for i in range(NUMSTATES):
            if (abs(stateLog[j, i + 1] - expectedStateArray[j, i + 1]) > 1.0E-10):
                testFailCount += 1
                testMessages.append("General state propagation failure: State Prop \n")
            if (abs(stateErrorLog[j, i + 1] - expectedXBar[j, i + 1]) > 1.0E-10):
                testFailCount += 1
                testMessages.append("General state propagation failure: State Error Prop \n")

        for i in range(NUMSTATES*NUMSTATES):
            if (abs(covarLog[j, i + 1] - expectedCovar[j, i + 1]) > 1.0E-8):
                print abs(covarLog[j, i + 1] - expectedCovar[j, i + 1])
                abs(covarLog[j, i + 1] - expectedCovar[j, i + 1])
                testFailCount += 1
                # testMessages.append("General state propagation failure: Covariance Prop \n")
            if (abs(stmLog[j, i + 1] - expectedSTM[j,:].flatten()[i]) > 1.0E-10):
                testFailCount += 1
                testMessages.append("General state propagation failure: STM Prop \n")

    # print out success message if no error were found
    if testFailCount == 0:
        print "PASSED: " + "EKF general state propagation"

    # return fail count and join into a single string all messages in the list
    # testMessage
    return [testFailCount, ''.join(testMessages)]


####################################################################################
# Test for the full filter with time and measurement update
####################################################################################
def StateUpdateSunLine(show_plots, SimHalfLength, AddMeasNoise, testVector1, testVector2, stateGuess):
    # 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
    NUMSTATES=3

    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()
    unitTestSim.TotalSim.terminateSimulation()

    # 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 = okeefeEKF.okeefeEKFConfig()
    moduleWrap = alg_contain.AlgContain(moduleConfig,
                                        okeefeEKF.Update_okeefeEKF,
                                        okeefeEKF.SelfInit_okeefeEKF,
                                        okeefeEKF.CrossInit_okeefeEKF,
                                        okeefeEKF.Reset_okeefeEKF)
    moduleWrap.ModelTag = "okeefeEKF"

    # Add test module to runtime call list
    unitTestSim.AddModelToTask(unitTaskName, moduleWrap, moduleConfig)
    setupFilterData(moduleConfig)
    moduleConfig.omega = [0.,0.,0.]

    # Set up some test parameters

    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],
    ]
    CSSBias = [1.0 for i in range(len(CSSOrientationList))]
    totalCSSList = []
    i=0
    for CSSHat in CSSOrientationList:
        newCSS = fswMessages.CSSUnitConfigFswMsg()
        newCSS.CBias = CSSBias[i]
        newCSS.nHat_B = CSSHat
        totalCSSList.append(newCSS)
        i = i + 1
    cssConstelation.nCSS = len(CSSOrientationList)
    cssConstelation.cssVals = totalCSSList
    msgSize = cssConstelation.getStructSize()
    inputData = cssComm.CSSArraySensorIntMsg()


    inputMessageSize = inputData.getStructSize()
    unitTestSim.TotalSim.CreateNewMessage("TestProcess", "css_config_data",
                                          msgSize, 2, "CSSConstellation")
    unitTestSim.TotalSim.CreateNewMessage(unitProcessName,
                                          moduleConfig.cssDataInMsgName,
                                          inputMessageSize,
                                          2)  # number of buffers (leave at 2 as default, don't make zero)
    unitTestSim.TotalSim.WriteMessageData("css_config_data", msgSize, 0, cssConstelation)



    dt =0.5
    stateTarget1 = testVector1
    moduleConfig.state = stateGuess
    moduleConfig.x = (np.array(stateTarget1) - np.array(stateGuess)).tolist()
    unitTestSim.TotalSim.logThisMessage('sunline_filter_data', testProcessRate)
    unitTestSim.AddVariableForLogging('okeefeEKF.x', testProcessRate , 0, 2, 'double')

    unitTestSim.InitializeSimulation()



    for i in range(SimHalfLength):
        if i > 20:
            dotList = []
            for element in CSSOrientationList:
                if AddMeasNoise:
                    dotProd = np.dot(np.array(element), np.array(testVector1)[0:3]) + np.random.normal(0., moduleConfig.qObsVal)
                else:
                    dotProd = np.dot(np.array(element), np.array(testVector1)[0:3])
                dotList.append(dotProd)
            inputData.CosValue = dotList

            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", range(3))
    covarLog = unitTestSim.pullMessageLogData('sunline_filter_data' + ".covar", range(3*3))


    if not AddMeasNoise:
        for i in range(NUMSTATES):
            if (abs(covarLog[-1, i * NUMSTATES + 1 + i] - covarLog[0, i * NUMSTATES + 1 + i] / 100.) > 1E-1):
                testFailCount += 1
                testMessages.append("Covariance update failure")
            if (abs(stateLog[-1, i + 1] - stateTarget1[i]) > 1.0E-10):
                testFailCount += 1
                testMessages.append("State update failure")
    else:
        for i in range(NUMSTATES):
            if (abs(covarLog[-1, i * NUMSTATES + 1 + i] - covarLog[0, i * NUMSTATES + 1 + i] / 100.) > 1E-1):
                testFailCount += 1
                testMessages.append("Covariance update failure with noise")
            if (abs(stateLog[-1, i + 1] - stateTarget1[i]) > 1.0E-2):
                testFailCount += 1
                testMessages.append("State update failure with noise")


    stateTarget2 = testVector2

    inputData = cssComm.CSSArraySensorIntMsg()
    for i in range(SimHalfLength):
        if i > 20:
            dotList = []
            for element in CSSOrientationList:
                if AddMeasNoise:
                    dotProd = np.dot(np.array(element), np.array(testVector2)[0:3])  + np.random.normal(0., moduleConfig.qObsVal)
                else:
                    dotProd = np.dot(np.array(element), np.array(testVector2)[0:3])
                dotList.append(dotProd)
            inputData.CosValue = dotList

            unitTestSim.TotalSim.WriteMessageData(moduleConfig.cssDataInMsgName,
                                                  inputMessageSize,
                                                  unitTestSim.TotalSim.CurrentNanos,
                                                  inputData)
        unitTestSim.ConfigureStopTime(macros.sec2nano((i + SimHalfLength+1) * 0.5))
        unitTestSim.ExecuteSimulation()

    stateLog = unitTestSim.pullMessageLogData('sunline_filter_data' + ".state", range(3))
    postFitLog = unitTestSim.pullMessageLogData('sunline_filter_data' + ".postFitRes", range(8))
    covarLog = unitTestSim.pullMessageLogData('sunline_filter_data' + ".covar", range(3*3))
    stateErrorLog = unitTestSim.GetLogVariableData('okeefeEKF.x')


    if not AddMeasNoise:
        for i in range(NUMSTATES):
            if (abs(covarLog[-1, i * NUMSTATES + 1 + i] - covarLog[0, i * NUMSTATES + 1 + i] / 100.) > 1E-1):
                testFailCount += 1
                testMessages.append("Covariance update failure")
            if (abs(stateLog[-1, i + 1] - stateTarget2[i]) > 1.0E-10):
                testFailCount += 1
                testMessages.append("State update failure")
    else:
        for i in range(NUMSTATES):
            if (abs(covarLog[-1, i * NUMSTATES + 1 + i] - covarLog[0, i * NUMSTATES + 1 + i] / 100.) > 1E-1):
                testFailCount += 1
                testMessages.append("Covariance update failure")
            if (abs(stateLog[-1, i + 1] - stateTarget2[i]) > 1.0E-2):
                testFailCount += 1
                testMessages.append("State update failure")


    target1 = np.array(testVector1)
    target2 = np.array(testVector2)
    FilterPlots.StatesPlot(stateErrorLog, covarLog, show_plots)
    FilterPlots.StatesVsTargets(target1, target2, stateLog, show_plots)
    FilterPlots.PostFitResiduals(postFitLog, moduleConfig.qObsVal, show_plots)

    # print out success message if no error were found
    if testFailCount == 0:
        print "PASSED: " + "EKF full test"

    # return fail count and join into a single string all messages in the list
    # testMessage
    return [testFailCount, ''.join(testMessages)]



if __name__ == "__main__":
    # StateUpdateSunLine(True, 200, True ,[-0.7, 0.7, 0.0] ,[0.8, 0.9, 0.0], [0.7, 0.7, 0.0])
    # sunline_individual_test()
    #StatePropStatic()
    StatePropVariable(True)
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. # general support file with common unit test functions #If low (0-5), the CKF kicks in easily, if high (>10) it's mostly only EKF # 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(True) # The following 'parametrize' function decorator provides the parameters and expected results for each #   of the multiple test runs for this test. # 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_ # 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. # zero unit test result counter # create empty list to store test log messages ################################################################################### ## Testing dynamics matrix computation ################################################################################### ################################################################################### ## Testing omega computation ################################################################################### ################################################################################### ## STM and State Test ################################################################################### ## Equations when removing the unobservable states from d_dot ################################################################################### # ## Test the H and yMeas matrix generation as well as the observation count # ################################################################################### #Fill in expected values for test # ################################################################################### # ## Test the Kalman Gain # ################################################################################### # Fill in expected values for test # ################################################################################### # ## Test the EKF update # ################################################################################### # Fill in expected values for test # # ################################################################################### # ## Test the CKF update # ################################################################################### # Fill in expected values for test # print out success message if no error were found # return fail count and join into a single string all messages in the list # testMessage #################################################################################### # Test for the time and update with static states (zero d_dot) #################################################################################### # 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. # zero unit test result counter # create empty list to store test log messages # arbitrary name (don't change) # arbitrary name (don't change) #   Create a sim module as an empty container # Create test thread # update process rate update time # Construct algorithm and associated C++ container # Add test module to runtime call list # print out success message if no error were found # return fail count and join into a single string all messages in the list # testMessage #################################################################################### # Test for the time and update with changing states non-zero omega #################################################################################### # 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. # zero unit test result counter # create empty list to store test log messages # arbitrary name (don't change) # arbitrary name (don't change) #   Create a sim module as an empty container # Create test thread # update process rate update time # Construct algorithm and associated C++ container # Add test module to runtime call list #Simulate sunline Dyn Mat #Simulate STM State prop # Simulate Rate compute # testMessages.append("General state propagation failure: Covariance Prop \n") # print out success message if no error were found # return fail count and join into a single string all messages in the list # testMessage #################################################################################### # Test for the full filter with time and measurement update #################################################################################### # 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. # zero unit test result counter # create empty list to store test log messages # arbitrary name (don't change) # arbitrary name (don't change) #   Create a sim module as an empty container # Create test thread # update process rate update time # Construct algorithm and associated C++ container # Add test module to runtime call list # Set up some test parameters # number of buffers (leave at 2 as default, don't make zero) # print out success message if no error were found # return fail count and join into a single string all messages in the list # testMessage # StateUpdateSunLine(True, 200, True ,[-0.7, 0.7, 0.0] ,[0.8, 0.9, 0.0], [0.7, 0.7, 0.0]) # sunline_individual_test() #StatePropStatic()