def fscore_match(self, sem1, sem2):
from jazzparser.formalisms.music_halfspan.harmstruct import \
semantics_to_dependency_graph
from jazzparser.data.dependencies import optimal_node_alignment, \
alignment_to_graph
from jazzparser.formalisms.music_halfspan.semantics import \
EnharmonicCoordinate
if sem1 is None:
max_score1 = 0.0
else:
graph1,timings1 = semantics_to_dependency_graph(sem1)
max_score1 = float(len(graph1))
if sem2 is None:
max_score2 = 0.0
else:
graph2,timings2 = semantics_to_dependency_graph(sem2)
max_score2 = float(len(graph2))
if sem1 is None or sem2 is None:
# Empty input: give zero score to everything
alignment_score = 0.0
alignment = []
transpose = None
else:
graph1,timings1 = semantics_to_dependency_graph(sem1)
graph2,timings2 = semantics_to_dependency_graph(sem2)
node_pairs = []
# Always align the root nodes to each other
node_pairs.append((min(graph1.nodes), min(graph2.nodes)))
# Align nodes that occur at the same time
time_nodes1 = dict([(time,node) for (node,time) in timings1.items()])
for node2,time in sorted(timings2.items(), key=lambda x:x[1]):
if time in time_nodes1:
node_pairs.append((time_nodes1[time], node2))
def _label_compare(label1, label2):
if isinstance(label1, EnharmonicCoordinate) and \
isinstance(label2, EnharmonicCoordinate):
return label1.zero_coord == label2.zero_coord
else:
return label1 == label2
# Get the graph of shared dependencies that results from aligning
# simultaneous nodes
graph,node_map1,node_map2 = alignment_to_graph(node_pairs,
graph1, graph2, label_compare=_label_compare)
# Score on the basis of the shared dependencies
alignment_score = len(graph)
return alignment_score,max_score1,max_score2
def fscore_match(self, sem1, sem2):
from jazzparser.formalisms.music_halfspan.harmstruct import \
semantics_to_dependency_graph
from jazzparser.data.dependencies import optimal_node_alignment, \
alignment_to_graph
from jazzparser.formalisms.music_halfspan.semantics import \
EnharmonicCoordinate
if sem1 is None:
max_score1 = 0.0
else:
graph1,timings1 = semantics_to_dependency_graph(sem1)
max_score1 = float(len(graph1))
if sem2 is None:
max_score2 = 0.0
else:
graph2,timings2 = semantics_to_dependency_graph(sem2)
max_score2 = float(len(graph2))
if sem1 is None or sem2 is None:
# Empty input: give zero score to everything
alignment_score = 0.0
alignment = []
transpose = None
else:
graph1,timings1 = semantics_to_dependency_graph(sem1)
graph2,timings2 = semantics_to_dependency_graph(sem2)
graphs = []
# Try all possible transpositions and assume the best
for transx in range(4):
for transy in range(3):
def _label_compare(label1, label2):
if isinstance(label1, EnharmonicCoordinate) and \
isinstance(label2, EnharmonicCoordinate):
coord1 = label1.zero_coord
x2,y2 = label2.zero_coord
return coord1 == ((x2+transx)%4, (y2+transy)%3)
else:
return label1 == label2
# Find the alignment of the nodes that matches most dependencies
alignment = optimal_node_alignment(graph1, graph2, label_compare=_label_compare)
# Get the common dependency graph
graph, node_map1, node_map2 = alignment_to_graph(alignment,
graph1, graph2, label_compare=_label_compare)
graphs.append(graph)
# Score on the basis of the shared dependencies
alignment_score,graph = max([(len(graph),graph) for graph in graphs], key=lambda x:x[0])
return alignment_score,max_score1,max_score2
if not options.latex:
print "Nodes aligned by time (gold -- result):"
for i,(node1,node2) in enumerate(node_pairs):
print "%d: %d -- %d" % (i, node1,node2)
def _label_compare(label1, label2):
if isinstance(label1, EnharmonicCoordinate) and \
isinstance(label2, EnharmonicCoordinate):
return label1.zero_coord == label2.zero_coord
else:
return label1 == label2
# Get the graph of shared dependencies that results from aligning
# simultaneous nodes
common_graph,node_map1,node_map2 = alignment_to_graph(node_pairs,
gold_graph, graph, label_compare=_label_compare)
if not options.latex:
print "Common dependencies:"
print common_graph
print "Graph size: %d" % len(common_graph)
print
if options.align_max:
graphs = []
# Try all possible transpositions and assume the best
for transx in range(4):
for transy in range(3):
def _label_compare(label1, label2):
if isinstance(label1, EnharmonicCoordinate) and \
isinstance(label2, EnharmonicCoordinate):
if not options.latex:
print "Nodes aligned by time (gold -- result):"
for i, (node1, node2) in enumerate(node_pairs):
print "%d: %d -- %d" % (i, node1, node2)
def _label_compare(label1, label2):
if isinstance(label1, EnharmonicCoordinate) and \
isinstance(label2, EnharmonicCoordinate):
return label1.zero_coord == label2.zero_coord
else:
return label1 == label2
# Get the graph of shared dependencies that results from aligning
# simultaneous nodes
common_graph, node_map1, node_map2 = alignment_to_graph(
node_pairs, gold_graph, graph, label_compare=_label_compare)
if not options.latex:
print "Common dependencies:"
print common_graph
print "Graph size: %d" % len(common_graph)
print
if options.align_max:
graphs = []
# Try all possible transpositions and assume the best
for transx in range(4):
for transy in range(3):
def _label_compare(label1, label2):
if isinstance(label1, EnharmonicCoordinate) and \
isinstance(label2, EnharmonicCoordinate):
