def write_current_matrix():
f = file("%s/%s_%03d.v" % (temporary_directory(), self._debug_matrix_file, step), "w")
x = v.reshape(len(self._p1.modules), len(self._p2.modules))
for i in xrange(len(self._p1.modules)):
for j in xrange(len(self._p2.modules)):
f.write("%f " % x[i, j])
f.write("\n")
f.close()
def write_current_matrix():
f = file(
'%s/%s_%03d.v' %
(temporary_directory(), self._debug_matrix_file, step), 'w')
x = v.reshape(len(self._p1.modules), len(self._p2.modules))
for i in xrange(len(self._p1.modules)):
for j in xrange(len(self._p2.modules)):
f.write('%f ' % x[i, j])
f.write('\n')
f.close()
def write_current_matrix():
f = file('%s/%s_%03d.v' % (temporary_directory(),
self._debug_matrix_file, step), 'w')
x = v.reshape(len(self._p1.modules),
len(self._p2.modules))
for i in xrange(len(self._p1.modules)):
for j in xrange(len(self._p2.modules)):
f.write('%f ' % x[i,j])
f.write('\n')
f.close()
def saveToHistory(self):
""" saveToHistory() -> None
Save the current contents to the history
"""
# Generate filename
current = datetime.datetime.now()
tmpDir = system.temporary_directory()
fn = (tmpDir + "hist_" +
current.strftime("%Y_%m_%d__%H_%M_%S") +
"_" + str(current.microsecond)+".png")
if self.saveToPNG(fn):
self._historyImages.append(fn)
def solve(self):
def write_debug_pipeline_positions(pipeline, mmap, f):
f.write('%d %d\n' %
(len(pipeline.modules), len(pipeline.connections)))
for k, v in mmap.iteritems():
f.write('%d %d\n' % (k, v))
c = pipeline_centroid(pipeline)
mn, mx = pipeline_bbox(pipeline)
f.write('%f %f %f %f\n' % (mn.x, mn.y, mx.x, mx.y))
for i, m in pipeline.modules.iteritems():
nc = m.center - c
f.write('%d %s %f %f\n' % (i, m.name, nc.x, nc.y))
for i, c in pipeline.connections.iteritems():
f.write('%d %d %d\n' % (i, c.sourceId, c.destinationId))
if self._debug:
out = file('%s/pipelines.txt' % temporary_directory(), 'w')
write_debug_pipeline_positions(self._p1, self._g1_vertex_map, out)
write_debug_pipeline_positions(self._p2, self._g2_vertex_map, out)
self.print_s8ys()
self._debug_matrix_file = 'input_matrix'
r_in = self.solve_v(self._input_vertex_s8y)
self._debug_matrix_file = 'output_matrix'
r_out = self.solve_v(self._output_vertex_s8y)
r_in = r_in.reshape(len(self._p1.modules), len(self._p2.modules))
r_out = r_out.reshape(len(self._p1.modules), len(self._p2.modules))
s = r_in.sum(1)
s[s == 0.0] = 1
r_in /= s
s = r_out.sum(1)
s[s == 0.0] = 1
r_out /= s
r_combined = scipy.multiply(r_in, r_out)
# Breaks ties on combined similarity
r_in = r_in * 0.9 + r_combined * 0.1
r_out = r_out * 0.9 + r_combined * 0.1
if self._debug:
print "== G1 =="
for (k, v) in sorted(self._g1_vertex_map.iteritems(),
key=operator.itemgetter(1)):
print v, k, self._p1.modules[k].name
print "== G2 =="
for (k, v) in sorted(self._g2_vertex_map.iteritems(),
key=operator.itemgetter(1)):
print v, k, self._p2.modules[k].name
print "input similarity"
self.pm(r_in, digits=3)
print "output similarity"
self.pm(r_out, digits=3)
print "combined similarity"
self.pm(r_combined, digits=3)
inputmap = dict([(self._g1_vertex_map.inverse[ix],
self._g2_vertex_map.inverse[v[0, 0]])
for (ix, v) in enumerate(r_in.argmax(1))])
outputmap = dict([(self._g1_vertex_map.inverse[ix],
self._g2_vertex_map.inverse[v[0, 0]])
for (ix, v) in enumerate(r_out.argmax(1))])
combinedmap = dict([(self._g1_vertex_map.inverse[ix],
self._g2_vertex_map.inverse[v[0, 0]])
for (ix, v) in enumerate(r_combined.argmax(1))])
# print inputmap
# print outputmap
return inputmap, outputmap, combinedmap
def solve(self):
def write_debug_pipeline_positions(pipeline, mmap, f):
f.write('%d %d\n' % (len(pipeline.modules),
len(pipeline.connections)))
for k, v in mmap.iteritems():
f.write('%d %d\n' % (k, v))
c = pipeline_centroid(pipeline)
mn, mx = pipeline_bbox(pipeline)
f.write('%f %f %f %f\n' % (mn.x, mn.y, mx.x, mx.y))
for i, m in pipeline.modules.iteritems():
nc = m.center - c
f.write('%d %s %f %f\n' % (i, m.name, nc.x, nc.y))
for i, c in pipeline.connections.iteritems():
f.write('%d %d %d\n' % (i, c.sourceId, c.destinationId))
if self._debug:
out = file('%s/pipelines.txt' % temporary_directory(), 'w')
write_debug_pipeline_positions(self._p1, self._g1_vertex_map, out)
write_debug_pipeline_positions(self._p2, self._g2_vertex_map, out)
self.print_s8ys()
self._debug_matrix_file = 'input_matrix'
r_in = self.solve_v(self._input_vertex_s8y)
self._debug_matrix_file = 'output_matrix'
r_out = self.solve_v(self._output_vertex_s8y)
r_in = r_in.reshape(len(self._p1.modules),
len(self._p2.modules))
r_out = r_out.reshape(len(self._p1.modules),
len(self._p2.modules))
s = r_in.sum(1)
s[s==0.0] = 1
r_in /= s
s = r_out.sum(1)
s[s==0.0] = 1
r_out /= s
r_combined = scipy.multiply(r_in, r_out)
# Breaks ties on combined similarity
r_in = r_in * 0.9 + r_combined * 0.1
r_out = r_out * 0.9 + r_combined * 0.1
if self._debug:
print "== G1 =="
for (k,v) in sorted(self._g1_vertex_map.iteritems(), key=operator.itemgetter(1)):
print v, k, self._p1.modules[k].name
print "== G2 =="
for (k,v) in sorted(self._g2_vertex_map.iteritems(), key=operator.itemgetter(1)):
print v, k, self._p2.modules[k].name
print "input similarity"
self.pm(r_in, digits=3)
print "output similarity"
self.pm(r_out, digits=3)
print "combined similarity"
self.pm(r_combined, digits=3)
inputmap = dict([(self._g1_vertex_map.inverse[ix],
self._g2_vertex_map.inverse[v[0,0]])
for (ix, v) in
enumerate(r_in.argmax(1))])
outputmap = dict([(self._g1_vertex_map.inverse[ix],
self._g2_vertex_map.inverse[v[0,0]])
for (ix, v) in
enumerate(r_out.argmax(1))])
combinedmap = dict([(self._g1_vertex_map.inverse[ix],
self._g2_vertex_map.inverse[v[0,0]])
for (ix, v) in
enumerate(r_combined.argmax(1))])
# print inputmap
# print outputmap
return inputmap, outputmap, combinedmap
