def test_dist_stitcher2(self):
""" Test dist stitch with only 2 common nodes - not enough. """
src = self.setup_positions([[0, 1, 3, 4]])
dst = self.setup_positions([[0, 1, 2, 5, 6]])
self.transform(src, s_i=1) #transform src positions
stitcher = DistStitcher()
stitcher.stitch(dst, src)
self.assertTrue(len(dst)==2, 'Wrong number of subclusters.')
rms = get_rms(self.test_cluster, dst)
self.assertFalse(rms<0.001, 'Stitching was too good.')
# with align rms should be ok
rms_align = get_rms(self.test_cluster, dst, align=True)
self.assertTrue(rms_align<0.001, 'Stitching was not good enough.')
def test_dist_stitcher2(self):
""" Test dist stitch with only 2 common nodes - not enough. """
src = self.setup_positions([[0, 1, 3, 4]])
dst = self.setup_positions([[0, 1, 2, 5, 6]])
self.transform(src, s_i=1) #transform src positions
stitcher = DistStitcher()
stitcher.stitch(dst, src)
self.assertTrue(len(dst) == 2, 'Wrong number of subclusters.')
rms = get_rms(self.test_cluster, dst)
self.assertFalse(rms < 0.001, 'Stitching was too good.')
# with align rms should be ok
rms_align = get_rms(self.test_cluster, dst, align=True)
self.assertTrue(rms_align < 0.001, 'Stitching was not good enough.')
def draw_propagation_errors(self, locKey, net):
SCALE_FACTOR = 0.6
if not net:
net = self.net
if any([not locKey in node.memory for node in net.nodes()]):
self.propagation_error_collection = []
self.ini_error_collection = []
return
rms = {"iniRms": {}, "stitchRms": {}}
for node in net.nodes():
rms["iniRms"][node] = get_rms(self.net.pos, (node.memory["iniLocs"]), True) * SCALE_FACTOR
rms["stitchRms"][node] = get_rms(self.net.pos, node.memory[locKey], True) * SCALE_FACTOR
self.propagation_error_collection = self.draw_nodes(net=net, node_colors="g", node_radius=rms["stitchRms"])
self.ini_error_collection = self.draw_nodes(net=net, node_colors="b", node_radius=rms["iniRms"])
def on_actionShowLocalizedSubclusters_triggered(self):
if len(self.ui.nodeInspector.selectedIndexes()) == 1:
qModelIndex = self.ui.nodeInspector.selectedIndexes()[0]
treeItem = qModelIndex.internalPointer()
assert(isinstance(treeItem.itemDataValue, Positions))
estimated = deepcopy(treeItem.itemDataValue)
estimatedsub = estimated.subclusters[0]
# rotate, translate and optionally scale
# w.r.t. original positions (pos)
align_clusters(Positions.create(self.net.pos), estimated, True)
net = self.net.subnetwork(estimatedsub.keys(), pos=estimatedsub)
self.draw_network(net=net, drawMessages=False)
edge_pos = numpy.asarray([(self.net.pos[node], estimatedsub[node][:2])
for node in net])
error_collection = LineCollection(edge_pos, colors='r')
self.axes.add_collection(error_collection)
rms = get_rms(self.net.pos, estimated, scale=False)
self.update_log('rms = %.3f' % rms)
self.update_log('localized = %.2f%% (%d/%d)' %
(len(estimatedsub) * 1. / len(self.net.pos) * 100,
len(estimatedsub), len(self.net.pos)))
def on_actionShowLocalizedSubclusters_triggered(self):
if len(self.ui.nodeInspector.selectedIndexes()) == 1:
qModelIndex = self.ui.nodeInspector.selectedIndexes()[0]
treeItem = qModelIndex.internalPointer()
assert (isinstance(treeItem.itemDataValue, Positions))
estimated = deepcopy(treeItem.itemDataValue)
estimatedsub = estimated.subclusters[0]
# rotate, translate and optionally scale
# w.r.t. original positions (pos)
align_clusters(Positions.create(self.net.pos), estimated, True)
net = self.net.subnetwork(estimatedsub.keys(), pos=estimatedsub)
self.draw_network(net=net, drawMessages=False)
edge_pos = numpy.asarray([
(self.net.pos[node], estimatedsub[node][:2]) for node in net
])
error_collection = LineCollection(edge_pos, colors='r')
self.axes.add_collection(error_collection)
rms = get_rms(self.net.pos, estimated, scale=False)
self.update_log('rms = %.3f' % rms)
self.update_log('localized = %.2f%% (%d/%d)' %
(len(estimatedsub) * 1. / len(self.net.pos) * 100,
len(estimatedsub), len(self.net.pos)))
def test_dist_stitcher(self):
src = self.setup_positions([[0, 1, 2, 3, 4]])
dst = self.setup_positions([[0, 1, 2, 5, 6]])
self.transform(src, s_i=1)
stitcher = DistStitcher()
stitcher.stitch(dst, src)
self.assertTrue(len(dst) == 1, 'Wrong number of subclusters.')
rms = get_rms(self.test_cluster, dst)
self.assertTrue(rms < 0.001, 'Stitching was not good enough.')
def test_dist_stitcher(self):
src = self.setup_positions([[0, 1, 2, 3, 4]])
dst = self.setup_positions([[0, 1, 2, 5, 6]])
self.transform(src, s_i=1)
stitcher = DistStitcher()
stitcher.stitch(dst, src)
self.assertTrue(len(dst)==1, 'Wrong number of subclusters.')
rms = get_rms(self.test_cluster, dst)
self.assertTrue(rms<0.001, 'Stitching was not good enough.')
def draw_propagation_errors(self, locKey, net):
SCALE_FACTOR = 0.6
if not net:
net = self.net
if any([not locKey in node.memory for node in net.nodes()]):
self.propagation_error_collection = []
self.ini_error_collection = []
return
rms = {'iniRms': {}, 'stitchRms': {}}
for node in net.nodes():
rms['iniRms'][node] = get_rms(self.net.pos,
(node.memory['iniLocs']), True) * \
SCALE_FACTOR
rms['stitchRms'][node] = get_rms(self.net.pos, node.memory[locKey],
True) * SCALE_FACTOR
self.propagation_error_collection = \
self.draw_nodes(net=net, node_colors='g',
node_radius=rms['stitchRms'])
self.ini_error_collection = self.draw_nodes(net=net,
node_colors='b',
node_radius=rms['iniRms'])
def test_dist_intrastitch(self):
"""
Test dist intrastitch
Clusters are setup so that first stitch is src[0] with dst[1] and
then dst[0] and dst[1] can be intrastitched.
"""
src = self.setup_positions([[1, 2, 4, 5, 6]])
dst = self.setup_positions([[0, 2, 3, 4], [0, 1, 2, 6]])
self.transform(src, s_i=1) #transform src positions
self.transform(dst, s_i=1) #transform src positions
stitcher = DistStitcher()
stitcher.stitch(dst, src)
self.assertTrue(len(dst) == 1, 'Wrong number of subclusters.')
# without align new subcluster should be wrongly (not) rotated
rms = get_rms(self.test_cluster, dst)
self.assertFalse(rms < 0.001, 'Stitching was too good.')
# with align rms should be ok
rms_align = get_rms(self.test_cluster, dst, align=True)
self.assertTrue(rms_align < 0.001, 'Stitching was not good enough.')
def test_dist_intrastitch(self):
"""
Test dist intrastitch
Clusters are setup so that first stitch is src[0] with dst[1] and
then dst[0] and dst[1] can be intrastitched.
"""
src = self.setup_positions([[1, 2, 4, 5, 6]])
dst = self.setup_positions([[0, 2, 3, 4], [0, 1, 2, 6]])
self.transform(src, s_i=1) #transform src positions
self.transform(dst, s_i=1) #transform src positions
stitcher = DistStitcher()
stitcher.stitch(dst, src)
self.assertTrue(len(dst)==1, 'Wrong number of subclusters.')
# without align new subcluster should be wrongly (not) rotated
rms = get_rms(self.test_cluster, dst)
self.assertFalse(rms<0.001, 'Stitching was too good.')
# with align rms should be ok
rms_align = get_rms(self.test_cluster, dst, align=True)
self.assertTrue(rms_align<0.001, 'Stitching was not good enough.')
def test_aoa_stitcher(self):
src = self.setup_positions([[0, 1, 2, 3, 4]])
dst = self.setup_positions([[0, 1, 2, 5, 6]])
#theta = 60/180.*pi
#R = array([[cos(theta), -sin(theta)], [sin(theta), cos(theta)]]) #ccw
#self.transform(src, R, [-1.62, -0.8], 0.5) #transform src positions
self.transform(src)
stitcher = AoAStitcher()
stitcher.stitch(dst, src)
rms = get_rms(self.test_cluster, dst)
self.assertTrue(rms < 0.001, 'Stitching was not good enough.')
self.assertTrue(len(dst) == 1, 'Wrong number of subclusters.')
def test_aoa_stitcher(self):
src = self.setup_positions([[0, 1, 2, 3, 4]])
dst = self.setup_positions([[0, 1, 2, 5, 6]])
#theta = 60/180.*pi
#R = array([[cos(theta), -sin(theta)], [sin(theta), cos(theta)]]) #ccw
#self.transform(src, R, [-1.62, -0.8], 0.5) #transform src positions
self.transform(src)
stitcher = AoAStitcher()
stitcher.stitch(dst, src)
rms = get_rms(self.test_cluster, dst)
self.assertTrue(rms<0.001, 'Stitching was not good enough.')
self.assertTrue(len(dst)==1, 'Wrong number of subclusters.')
