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fix start/end at top or bottom of shape

pull/409/head
Lex Neva 2019-03-19 23:28:19 -04:00
rodzic 68590492f5
commit 685df3b3f0
1 zmienionych plików z 14 dodań i 5 usunięć
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19
lib/stitches/auto_fill.py
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@ -59,7 +59,7 @@ def auto_fill(shape,
fill_stitch_graph = build_fill_stitch_graph(shape, angle, row_spacing, end_row_spacing) fill_stitch_graph = build_fill_stitch_graph(shape, angle, row_spacing, end_row_spacing)
check_graph(fill_stitch_graph, shape, max_stitch_length) check_graph(fill_stitch_graph, shape, max_stitch_length)
travel_graph = build_travel_graph(fill_stitch_graph, shape, angle, underpath) travel_graph = build_travel_graph(fill_stitch_graph, shape, angle, underpath)
path = find_stitch_path(fill_stitch_graph, starting_point, ending_point) path = find_stitch_path(fill_stitch_graph, travel_graph, starting_point, ending_point)
result = path_to_stitches(path, travel_graph, fill_stitch_graph, angle, row_spacing, result = path_to_stitches(path, travel_graph, fill_stitch_graph, angle, row_spacing,
max_stitch_length, running_stitch_length, staggers, skip_last) max_stitch_length, running_stitch_length, staggers, skip_last)
@ -281,14 +281,14 @@ def check_graph(graph, shape, max_stitch_length):
"This most often happens because your shape is made up of multiple sections that aren't connected.")) "This most often happens because your shape is made up of multiple sections that aren't connected."))
def nearest_node_on_outline(graph, point): def nearest_node(graph, point):
point = shgeo.Point(*point) point = shgeo.Point(*point)
nearest = min(graph.nodes, key=lambda node: shgeo.Point(*node).distance(point)) nearest = min(graph.nodes, key=lambda node: shgeo.Point(*node).distance(point))
return nearest return nearest
def find_stitch_path(graph, starting_point=None, ending_point=None): def find_stitch_path(graph, travel_graph, starting_point=None, ending_point=None):
"""find a path that visits every grating segment exactly once """find a path that visits every grating segment exactly once
Theoretically, we just need to find an Eulerian Path in the graph. Theoretically, we just need to find an Eulerian Path in the graph.
@ -315,12 +315,13 @@ def find_stitch_path(graph, starting_point=None, ending_point=None):
if starting_point is None: if starting_point is None:
starting_point = graph.nodes.keys()[0] starting_point = graph.nodes.keys()[0]
starting_node = nearest_node_on_outline(graph, starting_point) starting_node = nearest_node(graph, starting_point)
if ending_point is None: if ending_point is None:
ending_point = starting_point
ending_node = starting_node ending_node = starting_node
else: else:
ending_node = nearest_node_on_outline(graph, ending_point) ending_node = nearest_node(graph, ending_point)
# The algorithm below is adapted from networkx.eulerian_circuit(). # The algorithm below is adapted from networkx.eulerian_circuit().
path = [] path = []
@ -354,6 +355,14 @@ def find_stitch_path(graph, starting_point=None, ending_point=None):
if starting_node is not ending_node: if starting_node is not ending_node:
path.insert(0, PathEdge((starting_node, ending_node), key="initial")) path.insert(0, PathEdge((starting_node, ending_node), key="initial"))
real_start = nearest_node(travel_graph, starting_point)
if real_start != starting_node:
path.insert(0, PathEdge((real_start, starting_node), key="outline"))
real_end = nearest_node(travel_graph, ending_point)
if real_end != ending_node:
path.append(PathEdge((ending_node, real_end), key="outline"))
return path return path