''' '''
'''
ISC License
Copyright (c) 2016-2018, Autonomous Vehicle Systems Lab, University of Colorado at Boulder
Permission to use, copy, modify, and/or distribute this software for any
purpose with or without fee is hereby granted, provided that the above
copyright notice and this permission notice appear in all copies.
THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES
WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF
MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR
ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF
OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
'''
import sys, os, inspect
import numpy as np
import pytest
import math
from Basilisk.utilities import SimulationBaseClass, macros, orbitalMotion, unitTestSupport
from Basilisk.fswAlgorithms import pixelLineBiasUKF # import the module that is to be tested
from Basilisk.utilities import RigidBodyKinematics as rbk
import relativeODuKF_test_utilities as FilterPlots
import numpy as np
def rk4(f, t, x0):
x = np.zeros([len(t),len(x0)+1])
h = (t[len(t)-1] - t[0])/len(t)
x[0,0] = t[0]
x[0,1:] = x0
for i in range(len(t)-1):
h = t[i+1] - t[i]
x[i,0] = t[i]
k1 = h * f(t[i], x[i,1:])
k2 = h * f(t[i] + 0.5 * h, x[i,1:] + 0.5 * k1)
k3 = h * f(t[i] + 0.5 * h, x[i,1:] + 0.5 * k2)
k4 = h * f(t[i] + h, x[i,1:] + k3)
x[i+1,1:] = x[i,1:] + (k1 + 2.*k2 + 2.*k3 + k4) / 6.
x[i+1,0] = t[i+1]
return x
def twoBodyGrav(t, x, mu = 42828.314*1E9):
dxdt = np.zeros(np.shape(x))
dxdt[0:3] = x[3:6]
dxdt[3:6] = -mu/np.linalg.norm(x[0:3])**3.*x[0:3]
return dxdt
def setupFilterData(filterObject):
filterObject.navStateOutMsgName = "relod_state_estimate"
filterObject.filtDataOutMsgName = "relod_filter_data"
filterObject.circlesInMsgName = "circles_data"
filterObject.cameraConfigMsgName = "camera_config_data"
filterObject.attInMsgName = "simple_att_nav_output"
filterObject.planetIdInit = 2
filterObject.alpha = 0.02
filterObject.beta = 2.0
filterObject.kappa = 0.0
filterObject.gamma = 0.9
mu = 42828.314*1E9 #m^3/s^2
elementsInit = orbitalMotion.ClassicElements()
elementsInit.a = 8000*1E3 #m
elementsInit.e = 0.2
elementsInit.i = 10
elementsInit.Omega = 0.001
elementsInit.omega = 0.01
elementsInit.f = 0.1
r, v = orbitalMotion.elem2rv(mu, elementsInit)
bias = [1,1,-2]
filterObject.stateInit = r.tolist() + v.tolist() + bias
filterObject.covarInit = [1000.*1E6, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 1000.*1E6, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 1000.*1E6, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 5*1E6, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 5*1E6, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 5*1E6, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 3.0,]
qNoiseIn = np.identity(9)
qNoiseIn[0:3, 0:3] = qNoiseIn[0:3, 0:3]*0.00001*0.00001*1E-6
qNoiseIn[3:6, 3:6] = qNoiseIn[3:6, 3:6]*0.0001*0.0001*1E-6
qNoiseIn[6:9, 6:9] = qNoiseIn[3:6, 3:6]*0.0001*0.0001
filterObject.qNoise = qNoiseIn.reshape(9*9).tolist()
# uncomment this line is this test is to be skipped in the global unit test run, adjust message as needed
# @pytest.mark.skipif(conditionstring)
# uncomment this line if this test has an expected failure, adjust message as needed
# @pytest.mark.xfail() # need to update how the RW states are defined
# provide a unique test method name, starting with test_
[docs]def test_methods_kf(show_plots):
"""Module Unit Test"""
[testResults, testMessage] = relOD_method_test(show_plots)
assert testResults < 1, testMessage
[docs]def test_propagation_kf(show_plots):
"""Module Unit Test"""
[testResults, testMessage] = StatePropRelOD(show_plots, 10.0)
assert testResults < 1, testMessage
def relOD_method_test(show_plots):
# The __tracebackhide__ setting influences pytest showing of tracebacks:
# the mrp_steering_tracking() function will not be shown unless the
# --fulltrace command line option is specified.
__tracebackhide__ = True
testFailCount = 0 # zero unit test result counter
testMessages = [] # create empty list to store test log messages
state = [250, 32000, 1000, 5, 3, 2, 1, 1, 1]
covar = 10* np.eye(len(state))
dt = 10
mu = 42828.314
# Measurement Model Test
data = pixelLineBiasUKF.PixelLineBiasUKFConfig()
msg = pixelLineBiasUKF.CirclesOpNavMsg()
msg.circlesCenters = [100, 200]
msg.circlesRadii = [100]
msg.planetIds = [2]
data.cirlcesInMsg = msg
data.planetId = 2
data.countHalfSPs = len(state)
data.numStates = len(state)
# Dynamics Model Test
data.planetId = 2
stateIn = pixelLineBiasUKF.new_doubleArray(len(state))
for i in range(len(state)):
pixelLineBiasUKF.doubleArray_setitem(stateIn, i, state[i])
pixelLineBiasUKF.relODStateProp(data, stateIn, dt)
propedState = []
for i in range(len(state)):
propedState.append(pixelLineBiasUKF.doubleArray_getitem(stateIn, i))
expected = rk4(twoBodyGrav, [0, dt], np.array(state)*1E3)
expected[:,1:]*=1E-3
if np.linalg.norm((np.array(propedState) - expected[-1,1:])/(expected[-1,1:])) > 1.0E-15:
testFailCount += 1
testMessages.append("State Prop Failure")
# Set up a measurement test
data = pixelLineBiasUKF.PixelLineBiasUKFConfig()
# Set up a circle input message
msg = pixelLineBiasUKF.CirclesOpNavMsg()
msg.circlesCenters = [100, 200]
msg.circlesRadii = [100]
msg.planetIds = [2]
data.cirlcesInMsg = msg
data.planetId = 2
data.countHalfSPs = len(state)
data.numStates = len(state)
# Set up attitud message
att = pixelLineBiasUKF.NavAttIntMsg()
att.sigma_BN = [0, 0.2,-0.1]
att.omega_BN_B = [0.,0.,0.]
data.attInfo = att
# Set up a camera message
cam = pixelLineBiasUKF.CameraConfigMsg()
cam.sigma_CB = [-0.2, 0., 0.3]
cam.fieldOfView = 2.0 * np.arctan(10*1e-3 / 2.0 / (1.*1e-3) ) # 2*arctan(s/2 / f)
cam.resolution = [512, 512]
data.cameraSpecs = cam
# Populate sigma points
SP = np.zeros([len(state), 2*len(state) +1])
for i in range(2*len(state) + 1):
if i ==0:
SP[:, i] = np.array(state)
if i < len(state) + 1 and i>0:
SP[:,i] = np.array(state) + covar[:,i-1]
if i > len(state):
SP[:,i] = np.array(state) - covar[:,i-(len(state)+1)]
data.SP = np.transpose(SP).flatten().tolist()
data.state = state
pixelLineBiasUKF.pixelLineBiasUKFMeasModel(data)
yMeasOut = data.yMeas
expectedMeas = np.zeros([6, 2*len(state)+1])
dcm_CB = rbk.MRP2C(cam.sigma_CB)
dcm_BN = rbk.MRP2C(att.sigma_BN)
dcm_CN = np.dot(dcm_CB, dcm_BN)
pX = 2. * np.tan(cam.fieldOfView * cam.resolution[0] / cam.resolution[1] / 2.0)
pY = 2. * np.tan(cam.fieldOfView / 2.0)
X = pX / cam.resolution[0]
Y = pY / cam.resolution[1]
planetRad = 3396.19
obs = np.array([msg.circlesCenters[0], msg.circlesCenters[1], msg.circlesRadii[0], 0, 0, 0])
for i in range(2*len(state)+1):
r_C = np.dot(dcm_CN, SP[0:3,i])
rNorm = np.linalg.norm(SP[0:3,i])
r_C = -1./r_C[2]*r_C
centerX = r_C[0] / X
centerY = r_C[1] / Y
centerX += cam.resolution[0]/2 - 0.5
centerY += cam.resolution[1] / 2 - 0.5
rad = 1.0/X*np.tan(np.arcsin(planetRad/rNorm))
if i == 0:
obs[3:5] = np.array(msg.circlesCenters[0:2]) - obs[0:2]
obs[5] = rad - obs[2]
for j in range(3):
obs[3+j] = round(obs[3+j])
expectedMeas[0,i] = centerX - SP[6, i]
expectedMeas[1,i] = centerY - SP[7, i]
expectedMeas[2, i] = rad - SP[8, i]
expectedMeas[3:, i] = SP[6:, i]
yMeasTest = np.zeros([6, 2*len(state)+1])
for i in range(2*len(state)+1):
yMeasTest[:,i] = yMeasOut[i*6:i*6+6]
if np.linalg.norm((yMeasTest - expectedMeas))/np.linalg.norm(expectedMeas[:,0]) > 1.0E-15:
testFailCount += 1
testMessages.append("State Prop Failure")
return [testFailCount, ''.join(testMessages)]
def StatePropRelOD(show_plots, dt):
# The __tracebackhide__ setting influences pytest showing of tracebacks:
# the mrp_steering_tracking() function will not be shown unless the
# --fulltrace command line option is specified.
__tracebackhide__ = True
testFailCount = 0 # zero unit test result counter
testMessages = [] # create empty list to store test log messages
unitTaskName = "unitTask" # arbitrary name (don't change)
unitProcessName = "TestProcess" # arbitrary name (don't change)
# Create a sim module as an empty container
unitTestSim = SimulationBaseClass.SimBaseClass()
# Create test thread
state = [250, 32000, 1000, 5, 3, 2, 1, 1, 1]
testProcessRate = macros.sec2nano(dt) # update process rate update time
testProc = unitTestSim.CreateNewProcess(unitProcessName)
testProc.addTask(unitTestSim.CreateNewTask(unitTaskName, testProcessRate))
# Construct algorithm and associated C++ container
moduleConfig = pixelLineBiasUKF.PixelLineBiasUKFConfig()
moduleWrap = unitTestSim.setModelDataWrap(moduleConfig)
moduleWrap.ModelTag = "relodSuKF"
# Add test module to runtime call list
unitTestSim.AddModelToTask(unitTaskName, moduleWrap, moduleConfig)
setupFilterData(moduleConfig)
# Create the input messages.
inputCamera = pixelLineBiasUKF.CameraConfigMsg()
inputAtt = pixelLineBiasUKF.NavAttIntMsg()
# Set camera
inputCamera.fieldOfView = 2.0 * np.arctan(10*1e-3 / 2.0 / 0.01) # 2*arctan(s/2 / f)
inputCamera.resolution = [512, 512]
inputCamera.sigma_CB = [1., 0.3, 0.1]
unitTestSupport.setMessage(unitTestSim.TotalSim, unitProcessName, moduleConfig.cameraConfigMsgName, inputCamera)
# Set attitude
inputAtt.sigma_BN = [0.6, 1., 0.1]
unitTestSupport.setMessage(unitTestSim.TotalSim, unitProcessName, moduleConfig.attInMsgName, inputAtt)
unitTestSim.TotalSim.logThisMessage('relod_filter_data', testProcessRate)
timeSim = 60
unitTestSim.InitializeSimulation()
unitTestSim.ConfigureStopTime(macros.min2nano(timeSim))
unitTestSim.ExecuteSimulation()
time = np.linspace(0, timeSim*60, (int) (timeSim*60/dt+1))
dydt = np.zeros(len(moduleConfig.stateInit))
energy = np.zeros(len(time))
expected=np.zeros([len(time), len(moduleConfig.stateInit)+1])
expected[0,1:] = moduleConfig.stateInit
mu = 42828.314*1E9
energy[0] = -mu/(2*orbitalMotion.rv2elem(mu, expected[0,1:4], expected[0,4:7]).a)
expected = rk4(twoBodyGrav, time, moduleConfig.stateInit)
for i in range(1, len(time)):
energy[i] = - mu / (2 * orbitalMotion.rv2elem(mu, expected[i, 1:4], expected[i, 4:7]).a)
stateLog = unitTestSim.pullMessageLogData('relod_filter_data' + ".state", range(len(moduleConfig.stateInit)))
covarLog = unitTestSim.pullMessageLogData('relod_filter_data' + ".covar", range(len(moduleConfig.stateInit) * len(moduleConfig.stateInit)))
diff = np.copy(stateLog)
diff[:,1:]-=expected[:,1:]
FilterPlots.plot_TwoOrbits(expected[:,0:4], stateLog[:,0:4])
FilterPlots.EnergyPlot(time, energy, 'Prop', show_plots)
FilterPlots.StateCovarPlot(stateLog, covarLog, 'Prop', show_plots)
FilterPlots.StatePlot(diff, 'Prop', show_plots)
if (np.linalg.norm(diff[-1,1:]/expected[-1,1:]) > 1.0E-10):
testFailCount += 1
testMessages.append("State propagation failure")
if (energy[0] - energy[-1])/energy[0] > 1.0E-10:
testFailCount += 1
testMessages.append("State propagation failure")
# print out success message if no error were found
if testFailCount == 0:
print("PASSED: " + moduleWrap.ModelTag + " state propagation")
# return fail count and join into a single string all messages in the list
# testMessage
return [testFailCount, ''.join(testMessages)]
if __name__ == "__main__":
# relOD_method_test(True)
StatePropRelOD(True, 1.0)