def has_converter(source, target=Validator(type=None, format=None)):
"""Determines if any converters exist from a given type, and optionally format.
Underneath, this just traverses the edges until it finds one which matches
the arguments.
:param source: ``Validator`` tuple indicating the type/format being
converted `from`.
:param target: ``Validator`` tuple indicating the type/format being
converted `to`.
:returns: ``True`` if it can converter from ``source`` to ``target``,
``False`` otherwise.
"""
sources = []
for node in conv_graph.nodes():
if ((source.type is None) or (source.type == node.type)) and \
((source.format is None) or (source.format == node.format)):
sources.append(node)
for u in sources:
reachable = single_source_shortest_path(conv_graph, u)
del reachable[u] # Ignore path to self, since there are no self loops
for v in reachable:
if ((target.type is None) or (target.type == v.type)) and \
((target.format is None) or (target.format == v.format)):
return True
return False
def has_converter(source, target=Validator(type=None, format=None)):
"""Determines if any converters exist from a given type, and optionally format.
Underneath, this just traverses the edges until it finds one which matches
the arguments.
:param source: ``Validator`` tuple indicating the type/format being
converted `from`.
:param target: ``Validator`` tuple indicating the type/format being
converted `to`.
:returns: ``True`` if it can converter from ``source`` to ``target``,
``False`` otherwise.
"""
sources = []
for node in conv_graph.nodes():
if ((source.type is None) or (source.type == node.type)) and \
((source.format is None) or (source.format == node.format)):
sources.append(node)
for u in sources:
reachable = single_source_shortest_path(conv_graph, u)
del reachable[u] # Ignore path to self, since there are no self loops
for v in reachable:
if ((target.type is None) or (target.type == v.type)) and \
((target.format is None) or (target.format == v.format)):
return True
return False
def print_conversion_table():
"""
Print a table of supported conversion paths in CSV format with ``'from'``
and ``'to'`` columns to standard output.
"""
print 'from,to'
for node in conv_graph.nodes():
paths = single_source_shortest_path(conv_graph, node)
reachable_conversions = [p for p in paths.keys() if p != node]
for dest in reachable_conversions:
print '%s:%s,%s:%s' % (node[0], node[1], dest[0], dest[1])
def print_conversion_table():
"""
Print a table of supported conversion paths in CSV format with ``'from'``
and ``'to'`` columns to standard output.
"""
print 'from,to'
for node in conv_graph.nodes():
paths = single_source_shortest_path(conv_graph, node)
reachable_conversions = [p for p in paths.keys() if p != node]
for dest in reachable_conversions:
print '%s:%s,%s:%s' % (node[0], node[1], dest[0], dest[1])
def print_conversion_graph():
"""
Print a graph of supported conversion paths in DOT format to standard
output.
"""
print 'digraph g {'
for node in conv_graph.nodes():
paths = single_source_shortest_path(conv_graph, node)
reachable_conversions = [p for p in paths.keys() if p != node]
for dest in reachable_conversions:
print '"%s:%s" -> "%s:%s"' % (node[0], node[1], dest[0], dest[1])
print '}'
def print_conversion_graph():
"""
Print a graph of supported conversion paths in DOT format to standard
output.
"""
print 'digraph g {'
for node in conv_graph.nodes():
paths = single_source_shortest_path(conv_graph, node)
reachable_conversions = [p for p in paths.keys() if p != node]
for dest in reachable_conversions:
print '"%s:%s" -> "%s:%s"' % (node[0], node[1], dest[0], dest[1])
print '}'
def shortestPathLength(source, target, seed, part2=False):
PT = PathTimer()
CM = CubicleMaze(seed)
cutoff = sum(target)
if part2:
paths = single_source_shortest_path(CM, source, cutoff=cutoff)
path = paths.keys()
else:
manhattan = lambda c1, c2: abs(c1[0] - c2[0]) + abs(c1[1] - c2[1])
path = astar_path(CM,
source,
target,
heuristic=manhattan,
weight="weight")
CM.plotPath(cutoff, cutoff, path)
return len(path) if part2 else len(path) - 1
def find_shortest_paths_from_source(sentence, start_token):
g = build_networkXGraph_from_spaCy_depGraph(sentence)
shortest_paths_from_source = single_source_shortest_path(g, start_token)
return shortest_paths_from_source
# we've hit everything
complete = True
break
direction, newpos = breadcrumbs.pop()
# print(f"attempting to backtrack to {newpos}")
output = droid.run([direction])
if direction > 0:
pos = newpos
# print(grid)
gridpoints = grid.keys()
minrow = min(x[0] for x in gridpoints)
maxrow = max(x[0] for x in gridpoints)
mincol = min(x[1] for x in gridpoints)
maxcol = max(x[1] for x in gridpoints)
grid[target] = "^"
for row in range(minrow, maxrow + 1):
for col in range(mincol, maxcol + 1):
print(grid[(row, col)], end="")
print()
print(target)
print(shortest_path(gridnet, (0, 0), target))
print(len(shortest_path(gridnet, (0, 0), target)))
paths = single_source_shortest_path(gridnet, target)
print(max(len(x) for x in paths.values()))
