def test_gc (n):
G = nx.Graph()
T12 = make_obs()
T23 = make_obs()
for _ in xrange(n):
T1 = make_obs()
noise1 = make_obs(0.01,0.02)
T2 = T1.dot(T12).dot(noise1)
noise2 = make_obs(0.01,0.02)
T3 = T2.dot(T23).dot(noise2)
tfms = {1:T1,2:T2,3:T3}
gc.update_graph_from_observations(G, tfms)
G_opt = gc.compute_relative_transforms (G, 3, n)
print "T12"
print "Original:"
print T12
print "Calculated:"
print G_opt.edge[1][2]['tfm'], '\n'
print "T23"
print "Original:"
print T23
print "Calculated:"
print G_opt.edge[2][3]['tfm'], '\n'
print "T31"
print "Original:"
print nlg.inv(T12.dot(T23))
print "Calculated:"
print G_opt.edge[3][1]['tfm'], '\n'
def test_gc2 (n, add_noise=False):
##
# Markers 1,2,3 are on l finger
# Markers 4,5,6 are on r finger
# 7 and 8 are on the middle
##
### Initializing everything
# create calib info
calib_info = {"master": {"ar_markers":[7,8],
"master_group":True,
"angle_scale":0},
"l": {"ar_markers":[1,2,3],
"angle_scale":1},
"r": {"ar_markers":[4,5,6],
"angle_scale":-1}}
masterGraph = nx.DiGraph()
# Setup the groups
for group in calib_info:
masterGraph.add_node(group)
masterGraph.node[group]["graph"] = nx.Graph()
masterGraph.node[group]["angle_scale"] = calib_info[group]['angle_scale']
if calib_info[group].get("ar_markers") is None:
calib_info[group]["ar_markers"] = []
if calib_info[group].get("hydras") is None:
calib_info[group]["hydras"] = []
if calib_info[group].get("ps_markers") is None:
calib_info[group]["ps_markers"] = []
if calib_info[group].get("master_group") is not None:
masterGraph.node[group]["master"] = 1
masterGraph.node[group]['angle_scale'] = 0
masterGraph.node[group]["markers"] = calib_info[group]["ar_markers"] + calib_info[group]["hydras"] + calib_info[group]["ps_markers"]
masterGraph.node[group]["calib_info"] = calib_info[group]
### Done initializing.
T12 = make_obs()
T23 = make_obs()
T45 = make_obs()
T56 = make_obs()
T78 = make_obs()
T7cor = make_obs()
Tcor1 = make_obs()
Tcor4 = make_obs()
zaxis = np.array([0,0,1])
for _ in range(n):
theta = -15 + np.random.random()*30
theta2 = utils.rad_angle(theta)
T7 = make_obs()
R1 = np.eye(4)
R1[0:3,0:3] = rotation_matrix(zaxis,theta2)
R4 = np.eye(4)
R4[0:3,0:3] = rotation_matrix(zaxis,-theta2)
if add_noise:
Tcor = T7.dot(T7cor)
noise = make_obs(0.01,0.01)
T1 = Tcor.dot(R1).dot(Tcor1).dot(noise)
noise = make_obs(0.01,0.01)
T2 = T1.dot(T12).dot(noise)
noise = make_obs(0.01,0.01)
T3 = T2.dot(T23).dot(noise)
noise = make_obs(0.01,0.01)
T4 = Tcor.dot(R4).dot(Tcor4).dot(noise)
noise = make_obs(0.01,0.01)
T5 = T4.dot(T45).dot(noise)
noise = make_obs(0.01,0.01)
T6 = T5.dot(T56).dot(noise)
noise = make_obs(0.01,0.01)
T8 = T7.dot(T78).dot(noise)
else:
noise = np.eye(4)
Tcor = T7.dot(T7cor)
T1 = Tcor.dot(R1).dot(Tcor1).dot(noise)
T2 = T1.dot(T12).dot(noise)
T3 = T2.dot(T23).dot(noise)
T4 = Tcor.dot(R4).dot(Tcor4).dot(noise)
T5 = T4.dot(T45).dot(noise)
T6 = T5.dot(T56).dot(noise)
T8 = T7.dot(T78).dot(noise)
# Randomly sample a few until done maybe?
tfms = {1:T1,2:T2,3:T3,4:T4,5:T5,6:T6,7:T7,8:T8}
gc.update_groups_from_observations(masterGraph, tfms, theta)
init = np.zeros(36)
init[0:12] = nlg.inv(T78).dot(T7cor)[0:3,:].reshape(12,order='F')
init[12:24] = nlg.inv(Tcor4)[0:3,:].reshape(12,order='F')
init[24:36] = nlg.inv(Tcor1)[0:3,:].reshape(12,order='F')
G_opt = gc.compute_relative_transforms(masterGraph, 5)#, init)
# 7,8 markers
group = G_opt.node["master"]
G = group["graph"]
print "T78"
print "Original:"
print T78
print "Calculated:"
print G.edge[7][8]['tfm'], '\n'
# 1,2,3 markers
group = G_opt.node["l"]
G = group["graph"]
print "T12"
print "Original:"
print T12
print "Calculated:"
print G.edge[1][2]['tfm'], '\n'
print "T23"
print "Original:"
print T23
print "Calculated:"
print G.edge[2][3]['tfm'], '\n'
print "T31"
print "Original:"
print nlg.inv(T12.dot(T23))
print "Calculated:"
print G.edge[3][1]['tfm'], '\n'
# 4,5,6 markers
group = G_opt.node["r"]
G = group["graph"]
print "T45"
print "Original:"
print T45
print "Calculated:"
print G.edge[4][5]['tfm'], '\n'
print "T56"
print "Original:"
print T56
print "Calculated:"
print G.edge[5][6]['tfm'], '\n'
print "T64"
print "Original:"
print nlg.inv(T45.dot(T56))
print "Calculated:"
print G.edge[6][4]['tfm'], '\n'
# Let's try random angles:
theta = -15 + np.random.random()*30
theta2 = utils.rad_angle(theta)
R1 = np.eye(4)
R1[0:3,0:3] = rotation_matrix(zaxis,theta2)
print "T71"
print "Original:"
print T7cor.dot(R1).dot(Tcor1)
print "Calculated:"
print G_opt.edge["master"]["l"]['tfm_func'](7,1,theta), '\n'
print "norm diff:", nlg.norm(G_opt.edge["master"]["l"]['tfm_func'](7,1,theta)-T7cor.dot(R1).dot(Tcor1)), '\n'
print "Difference between cors"
T7cor_calib = G_opt.node["master"]["graph"].edge[7]["cor"]["tfm"]
print nlg.inv(T7cor).dot(T7cor_calib)