def transform_axis(null_basis,uch_basis,p): axis = get_axis(p) return ogp_util.transform_pts(null_basis,uch_basis,axis)
elif (side == 'back'):
near = 'Axial'
far = 'Stereo'
else:
print 'Invalid side'
sys.exit()
stepdict = ogp_util.getsteps(sys.argv[2])
fixture_basis = ogp_util.l123_basis()
meas_basis = ogp_util.get_measbasis(stepdict, fixture_basis)
points = ogp_util.get_points(stepdict, near, 7, 4)
#print points
points = ogp_util.transform_pts(meas_basis, fixture_basis, points)
#print points
[fiducials_nominal, p0] = ogp_util.l123_fiducials(side)
sol = scipy.optimize.leastsq(ogp_util.sensor_fitfunc,
p0,
args=(points, fiducials_nominal))[0]
print 'Sensor fit parameters: ' + str(sol)
print 'Sensor fit residuals (um): ' + str(
1000.0 * ogp_util.sensor_fitfunc(sol, points, fiducials_nominal))
sensor_origin = np.array(sol[0:3])
sensor_rotation = ogp_util.make_rotation(sol[3], sol[4], sol[5])
print 'Sensor origin: {0}'.format(sensor_origin)
norm_vec = sensor_rotation.T.dot([0.0, 0.0, 1.0])
elif side == "back":
near = "Axial"
far = "Stereo"
else:
print "Invalid side"
sys.exit()
stepdict = ogp_util.getsteps(sys.argv[2])
fixture_basis = ogp_util.l123_basis()
meas_basis = ogp_util.get_measbasis(stepdict, fixture_basis)
points = ogp_util.get_points(stepdict, near, 7, 4)
# print points
points = ogp_util.transform_pts(meas_basis, fixture_basis, points)
# print points
[fiducials_nominal, p0] = ogp_util.l123_fiducials(side)
sol = scipy.optimize.leastsq(ogp_util.sensor_fitfunc, p0, args=(points, fiducials_nominal))[0]
print "Sensor fit parameters: " + str(sol)
print "Sensor fit residuals (um): " + str(1000.0 * ogp_util.sensor_fitfunc(sol, points, fiducials_nominal))
sensor_origin = np.array(sol[0:3])
sensor_rotation = ogp_util.make_rotation(sol[3], sol[4], sol[5])
print "Sensor origin: {0}".format(sensor_origin)
norm_vec = sensor_rotation.T.dot([0.0, 0.0, 1.0])
print "Normal vector: {0}".format(norm_vec)
meas_vec = sensor_rotation.T.dot([1.0, 0.0, 0.0])
print "Strip vector: {0}".format(meas_vec)
