''' '''
'''
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.okeefeEKF import okeefeEKF
from Basilisk.utilities import SimulationBaseClass
from Basilisk.simulation.alg_contain import alg_contain
from Basilisk.fswAlgorithms.cssComm import cssComm
from Basilisk.utilities import macros
from Basilisk.utilities import unitTestSupport # general support file with common unit test functions
from Basilisk.fswAlgorithms.fswMessages 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
[docs]def test_all_functions_oekf(show_plots):
"""Module Unit Test"""
[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()
# 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()
# 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()
# 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", list(range(3)))
covarLog = unitTestSim.pullMessageLogData('sunline_filter_data' + ".covar", list(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", list(range(3)))
postFitLog = unitTestSim.pullMessageLogData('sunline_filter_data' + ".postFitRes", list(range(8)))
covarLog = unitTestSim.pullMessageLogData('sunline_filter_data' + ".covar", list(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)