diff --git a/embroider.py b/embroider.py index c207c6705..bd4d1abe2 100644 --- a/embroider.py +++ b/embroider.py @@ -24,7 +24,8 @@ import os import subprocess from copy import deepcopy import time -from itertools import chain, izip +from itertools import chain, izip, groupby +from collections import deque import inkex import simplepath import simplestyle @@ -37,6 +38,7 @@ import lxml.etree as etree import shapely.geometry as shgeo import shapely.affinity as affinity import shapely.ops +import networkx from pprint import pformat import PyEmb @@ -49,7 +51,6 @@ SVG_PATH_TAG = inkex.addNS('path', 'svg') SVG_DEFS_TAG = inkex.addNS('defs', 'svg') SVG_GROUP_TAG = inkex.addNS('g', 'svg') - class Param(object): def __init__(self, name, description, unit=None, values=[], type=None, group=None, inverse=False, default=None): self.name = name @@ -309,8 +310,11 @@ class Fill(EmbroideryElement): def north(self, angle): return self.east(angle).rotate(math.pi / 2) + def row_num(self, point, angle, row_spacing): + return round((point * self.north(angle)) / row_spacing) + def adjust_stagger(self, stitch, angle, row_spacing, max_stitch_length): - row_num = round((stitch * self.north(angle)) / row_spacing) + row_num = self.row_num(stitch, angle, row_spacing) row_stagger = row_num % self.staggers stagger_offset = (float(row_stagger) / self.staggers) * max_stitch_length offset = ((stitch * self.east(angle)) - stagger_offset) % max_stitch_length @@ -448,6 +452,55 @@ class Fill(EmbroideryElement): return runs + def stitch_row(self, patch, beg, end, angle, row_spacing, max_stitch_length): + # We want our stitches to look like this: + # + # ---*-----------*----------- + # ------*-----------*-------- + # ---------*-----------*----- + # ------------*-----------*-- + # ---*-----------*----------- + # + # Each successive row of stitches will be staggered, with + # num_staggers rows before the pattern repeats. A value of + # 4 gives a nice fill while hiding the needle holes. The + # first row is offset 0%, the second 25%, the third 50%, and + # the fourth 75%. + # + # Actually, instead of just starting at an offset of 0, we + # can calculate a row's offset relative to the origin. This + # way if we have two abutting fill regions, they'll perfectly + # tile with each other. That's important because we often get + # abutting fill regions from pull_runs(). + + + beg = PyEmb.Point(*beg) + end = PyEmb.Point(*end) + + row_direction = (end - beg).unit() + segment_length = (end - beg).length() + + # only stitch the first point if it's a reasonable distance away from the + # last stitch + if not patch.stitches or (beg - patch.stitches[-1]).length() > 0.5 * self.options.pixels_per_mm: + patch.add_stitch(beg) + + first_stitch = self.adjust_stagger(beg, angle, row_spacing, max_stitch_length) + + # we might have chosen our first stitch just outside this row, so move back in + if (first_stitch - beg) * row_direction < 0: + first_stitch += row_direction * max_stitch_length + + offset = (first_stitch - beg).length() + + while offset < segment_length: + patch.add_stitch(beg + offset * row_direction) + offset += max_stitch_length + + if (end - patch.stitches[-1]).length() > 0.1 * self.options.pixels_per_mm: + patch.add_stitch(end) + + def section_to_patch(self, group_of_segments, angle=None, row_spacing=None, max_stitch_length=None): if max_stitch_length is None: max_stitch_length = self.max_stitch_length @@ -466,58 +519,13 @@ class Fill(EmbroideryElement): last_end = None for segment in group_of_segments: - # We want our stitches to look like this: - # - # ---*-----------*----------- - # ------*-----------*-------- - # ---------*-----------*----- - # ------------*-----------*-- - # ---*-----------*----------- - # - # Each successive row of stitches will be staggered, with - # num_staggers rows before the pattern repeats. A value of - # 4 gives a nice fill while hiding the needle holes. The - # first row is offset 0%, the second 25%, the third 50%, and - # the fourth 75%. - # - # Actually, instead of just starting at an offset of 0, we - # can calculate a row's offset relative to the origin. This - # way if we have two abutting fill regions, they'll perfectly - # tile with each other. That's important because we often get - # abutting fill regions from pull_runs(). - (beg, end) = segment if (swap): (beg, end) = (end, beg) - beg = PyEmb.Point(*beg) - end = PyEmb.Point(*end) + self.stitch_row(patch, beg, end, angle, row_spacing, max_stitch_length) - row_direction = (end - beg).unit() - segment_length = (end - beg).length() - - # only stitch the first point if it's a reasonable distance away from the - # last stitch - if last_end is None or (beg - last_end).length() > 0.5 * self.options.pixels_per_mm: - patch.add_stitch(beg) - - first_stitch = self.adjust_stagger(beg, angle, row_spacing, max_stitch_length) - - # we might have chosen our first stitch just outside this row, so move back in - if (first_stitch - beg) * row_direction < 0: - first_stitch += row_direction * max_stitch_length - - offset = (first_stitch - beg).length() - - while offset < segment_length: - patch.add_stitch(beg + offset * row_direction) - offset += max_stitch_length - - if (end - patch.stitches[-1]).length() > 0.1 * self.options.pixels_per_mm: - patch.add_stitch(end) - - last_end = end swap = not swap return patch @@ -529,6 +537,9 @@ class Fill(EmbroideryElement): return [self.section_to_patch(group) for group in groups_of_segments] +class MaxQueueLengthExceeded(Exception): + pass + class AutoFill(Fill): @property @param('auto_fill', 'Automatically routed fill stitching', type='toggle', default=True) @@ -580,116 +591,421 @@ class AutoFill(Fill): @param('fill_underlay_max_stitch_length_mm', 'Max stitch length', unit='mm', group='AutoFill Underlay', type='float') @cache def fill_underlay_max_stitch_length(self): - return self.get_float_param("fill_underlay_max_stitch_length_mm" or self.max_stitch_length) + return self.get_float_param("fill_underlay_max_stitch_length_mm") or self.max_stitch_length - def validate(self): - if len(self.shape.boundary) > 1: - self.fatal("auto-fill: object %s cannot be auto-filled because it has one or more holes. Please disable auto-fill for this object or break it into separate objects without holes." % self.node.get('id')) + def which_outline(self, coords): + """return the index of the outline on which the point resides - def is_same_run(self, segment1, segment2): - if shgeo.Point(segment1[0]).distance(shgeo.Point(segment2[0])) > self.max_stitch_length: - return False + Index 0 is the outer boundary of the fill region. 1+ are the + outlines of the holes. + """ - if shgeo.Point(segment1[1]).distance(shgeo.Point(segment2[1])) > self.max_stitch_length: - return False + point = shgeo.Point(*coords) - return True + for i, outline in enumerate(self.shape.boundary): + # I'd use an intersection check, but floating point errors make it + # fail sometimes. + if outline.distance(point) < 0.00001: + return i - def perimeter_distance(self, p1, p2): - # how far around the perimeter (and in what direction) do I need to go - # to get from p1 to p2? + def project(self, coords, outline_index): + """project the point onto the specified outline - p1_projection = self.outline.project(shgeo.Point(p1)) - p2_projection = self.outline.project(shgeo.Point(p2)) + This returns the distance along the outline at which the point resides. + """ - distance = p2_projection - p1_projection + return self.shape.boundary.project(shgeo.Point(*coords)) - if abs(distance) > self.outline_length / 2.0: - # if we'd have to go more than halfway around, it's faster to go - # the other way - if distance < 0: - return distance + self.outline_length - elif distance > 0: - return distance - self.outline_length + def build_graph(self, segments, angle, row_spacing): + """build a graph representation of the grating segments + + This function builds a specialized graph (as in graph theory) that will + help us determine a stitching path. The idea comes from this paper: + + http://www.sciencedirect.com/science/article/pii/S0925772100000158 + + The goal is to build a graph that we know must have an Eulerian Path. + An Eulerian Path is a path from edge to edge in the graph that visits + every edge exactly once and ends at the node it started at. Algorithms + exist to build such a path, and we'll use Hierholzer's algorithm. + + A graph must have an Eulerian Path if every node in the graph has an + even number of edges touching it. Our goal here is to build a graph + that will have this property. + + Based on the paper linked above, we'll build the graph as follows: + + * nodes are the endpoints of the grating segments, where they meet + with the outer outline of the region the outlines of the interior + holes in the region. + * edges are: + * each section of the outer and inner outlines of the region, + between nodes + * double every other edge in the outer and inner hole outlines + + Doubling up on some of the edges seems as if it will just mean we have + to stitch those spots twice. This may be true, but it also ensures + that every node has 4 edges touching it, ensuring that a valid stitch + path must exist. + """ + + graph = networkx.MultiGraph() + + # First, add the grating segments as edges. We'll use the coordinates + # of the endpoints as nodes, which networkx will add automatically. + for segment in segments: + # networkx allows us to label nodes with arbitrary data. We'll + # mark this one as a grating segment. + graph.add_edge(*segment, key="segment") + + for node in graph.nodes(): + outline_index = self.which_outline(node) + outline_projection = self.project(node, outline_index) + + # Tag each node with its index and projection. + graph.add_node(node, index=outline_index, projection=outline_projection) + + nodes = graph.nodes(data=True) + nodes.sort(key=lambda node: (node[1]['index'], node[1]['projection'])) + + for outline_index, nodes in groupby(nodes, key=lambda node: node[1]['index']): + nodes = [ node for node, data in nodes ] + + # heuristic: change the order I visit the nodes in the outline if necessary. + # If the start and endpoints are in the same row, I can't tell which row + # I should treat it as being in. + while True: + row0 = self.row_num(PyEmb.Point(*nodes[0]), angle, row_spacing) + row1 = self.row_num(PyEmb.Point(*nodes[1]), angle, row_spacing) + + if row0 == row1: + nodes = nodes[1:] + [nodes[0]] + else: + break + + # heuristic: it's useful to try to keep the duplicated edges in the same rows. + # this prevents the BFS from having to search a ton of edges. + row_num = min(row0, row1) + if row_num % 2 == 0: + edge_set = 0 else: - # this ought not happen, but just for completeness, return 0 if - # p1 and p0 are the same point - return 0 - else: - return distance + edge_set = 1 + + #print >> sys.stderr, outline_index, "es", edge_set, "rn", row_num, PyEmb.Point(*nodes[0]) * self.north(angle), PyEmb.Point(*nodes[1]) * self.north(angle) + + # add an edge between each successive node + for i, (node1, node2) in enumerate(zip(nodes, nodes[1:] + [nodes[0]])): + graph.add_edge(node1, node2, key="outline") + + # duplicate edges contained in every other row (exactly half + # will be duplicated) + row_num = min(self.row_num(PyEmb.Point(*node1), angle, row_spacing), + self.row_num(PyEmb.Point(*node2), angle, row_spacing)) + + # duplicate every other edge around this outline + if i % 2 == edge_set: + graph.add_edge(node1, node2, key="extra") + + + if not networkx.is_eulerian(graph): + raise Exception("something went wrong: graph is not eulerian") + + return graph + + def node_list_to_edge_list(self, node_list): + return zip(node_list[:-1], node_list[1:]) + + def bfs_for_loop(self, graph, starting_node, max_queue_length=2000): + to_search = deque() + to_search.appendleft(([starting_node], set(), 0)) + + while to_search: + if len(to_search) > max_queue_length: + raise MaxQueueLengthExceeded() + + path, visited_edges, visited_segments = to_search.pop() + ending_node = path[-1] + + # get a list of neighbors paired with the key of the edge I can follow to get there + neighbors = [ + (node, key) + for node, adj in graph.adj[ending_node].iteritems() + for key in adj + ] + + # heuristic: try grating segments first + neighbors.sort(key=lambda (dest, key): key == "segment", reverse=True) + + for next_node, key in neighbors: + # skip if I've already followed this edge + edge = (tuple(sorted((ending_node, next_node))), key) + if edge in visited_edges: + continue + + new_path = path + [next_node] + + if key == "segment": + new_visited_segments = visited_segments + 1 + else: + new_visited_segments = visited_segments + + if next_node == starting_node: + # ignore trivial loops (down and back a doubled edge) + if len(new_path) > 3: + return self.node_list_to_edge_list(new_path), new_visited_segments + + new_visited_edges = visited_edges.copy() + new_visited_edges.add(edge) + + to_search.appendleft((new_path, new_visited_edges, new_visited_segments)) + + def find_loop(self, graph, starting_nodes): + """find a loop in the graph that is connected to the existing path + + Start at a candidate node and search through edges to find a path + back to that node. We'll use a breadth-first search (BFS) in order to + find the shortest available loop. + + In most cases, the BFS should not need to search far to find a loop. + The queue should stay relatively short. + + An added heuristic will be used: if the BFS queue's length becomes + too long, we'll abort and try a different starting point. Due to + the way we've set up the graph, there's bound to be a better choice + somewhere else. + """ + + #loop = self.simple_loop(graph, starting_nodes[-2]) + + #if loop: + # print >> sys.stderr, "simple_loop success" + # starting_nodes.pop() + # starting_nodes.pop() + # return loop + + loop = None + retry = [] + max_queue_length = 2000 + + while not loop: + while not loop and starting_nodes: + starting_node = starting_nodes.pop() + #print >> sys.stderr, "find loop from", starting_node + + try: + # Note: if bfs_for_loop() returns None, no loop can be + # constructed from the starting_node (because the + # necessary edges have already been consumed). In that + # case we discard that node and try the next. + loop = self.bfs_for_loop(graph, starting_node, max_queue_length) + + if not loop: + print >> dbg, "failed on", starting_node + dbg.flush() + except MaxQueueLengthExceeded: + print >> dbg, "gave up on", starting_node + dbg.flush() + # We're giving up on this node for now. We could try + # this node again later, so add it to the bottm of the + # stack. + retry.append(starting_node) + + # Darn, couldn't find a loop. Try harder. + starting_nodes.extendleft(retry) + max_queue_length *= 2 + + starting_nodes.extendleft(retry) + return loop + + def insert_loop(self, path, loop): + """insert a sub-loop into an existing path + + The path will be a series of edges describing a path through the graph + that ends where it starts. The loop will be similar, and its starting + point will be somewhere along the path. + + Insert the loop into the path, resulting in a longer path. + + Both the path and the loop will be a list of edges specified as a + start and end point. The points will be specified in order, such + that they will look like this: + + ((p1, p2), (p2, p3), (p3, p4) ... (pn, p1)) + + path will be modified in place. + """ + + loop_start = loop[0][0] + + for i, (start, end) in enumerate(path): + if start == loop_start: + break + + path[i:i] = loop + + def find_stitch_path(self, graph, segments): + """find a path that visits every grating segment exactly once + + Theoretically, we just need to find an Eulerian Path in the graph. + However, we don't actually care whether every single edge is visited. + The edges on the outline of the region are only there to help us get + from one grating segment to the next. + + We'll build a "cycle" (a path that ends where it starts) using + Hierholzer's algorithm. We'll stop once we've visited every grating + segment. + + Hierholzer's algorithm says to select an arbitrary starting node at + each step. In order to produce a reasonable stitch path, we'll select + the vertex carefully such that we get back-and-forth traversal like + mowing a lawn. + + To do this, we'll use a simple heuristic: try to start from nodes in + the order of most-recently-visited first. + """ + + graph = graph.copy() + num_segments = len(segments) + segments_visited = 0 + nodes_visited = deque() + + # start with a simple loop: down one segment and then back along the + # outer border to the starting point. + path = [segments[0], list(reversed(segments[0]))] + + graph.remove_edges_from(path) + + segments_visited += 1 + nodes_visited.extend(segments[0]) + + while segments_visited < num_segments: + result = self.find_loop(graph, nodes_visited) + + if not result: + print >> sys.stderr, "Unexpected error filling region. Please send your SVG to lexelby@github." + break + + loop, segments = result + + print >> dbg, "found loop:", loop + dbg.flush() + + segments_visited += segments + nodes_visited += [edge[0] for edge in loop] + graph.remove_edges_from(loop) + + self.insert_loop(path, loop) + + #if segments_visited >= 12: + # break + + return path + + def collapse_sequential_outline_edges(self, graph, path): + """collapse sequential edges that fall on the same outline + + When the path follows multiple edges along the outline of the region, + replace those edges with the starting and ending points. We'll use + these to stitch along the outline later on. + """ + + start_of_run = None + new_path = [] + + for edge in path: + if graph.has_edge(*edge, key="segment"): + if start_of_run: + # close off the last run + new_path.append((start_of_run, edge[0])) + start_of_run = None + + new_path.append(edge) + else: + if not start_of_run: + start_of_run = edge[0] + + if start_of_run: + # if we were still in a run, close it off + new_path.append((start_of_run, edge[1])) + + return new_path + + def connect_points(self, patch, start, end): + outline_index = self.which_outline(start) + outline = self.shape.boundary[outline_index] + + start = outline.project(shgeo.Point(*start)) + end = outline.project(shgeo.Point(*end)) + + direction = math.copysign(1.0, end - start) + + while (end - start) * direction > 0: + stitch = outline.interpolate(start) + patch.add_stitch(PyEmb.Point(stitch.x, stitch.y)) + + start += self.running_stitch_length * direction + + stitch = outline.interpolate(end) + end = PyEmb.Point(stitch.x, stitch.y) + if (end - patch.stitches[-1]).length() > 0.1 * self.options.pixels_per_mm: + patch.add_stitch(end) + + def path_to_patch(self, graph, path, angle, row_spacing, max_stitch_length): + path = self.collapse_sequential_outline_edges(graph, path) - def connect_points(self, p1, p2): patch = Patch(color=self.color) + #patch.add_stitch(PyEmb.Point(*path[0][0])) - pos = self.outline.project(shgeo.Point(p1)) - distance = self.perimeter_distance(p1, p2) - stitches = abs(int(distance / self.running_stitch_length)) + #for edge in path: + # patch.add_stitch(PyEmb.Point(*edge[1])) - direction = math.copysign(1.0, distance) - one_stitch = self.running_stitch_length * direction - - for i in xrange(stitches): - pos = (pos + one_stitch) % self.outline_length - - stitch = PyEmb.Point(*self.outline.interpolate(pos).coords[0]) - - # if we're moving along the fill direction, adjust the stitch to - # match the fill so it blends in - if patch.stitches: - if abs((stitch - patch.stitches[-1]) * self.north(self.angle)) < 0.01: - new_stitch = self.adjust_stagger(stitch, self.angle, self.row_spacing, self.max_stitch_length) - - # don't push the point past the end of this section of the outline - if self.outline.distance(shgeo.Point(new_stitch)) <= 0.01: - stitch = new_stitch - - patch.add_stitch(stitch) + for edge in path: + if graph.has_edge(*edge, key="segment"): + self.stitch_row(patch, edge[0], edge[1], angle, row_spacing, max_stitch_length) + else: + self.connect_points(patch, *edge) return patch - def get_corner_points(self, section): - return section[0][0], section[0][-1], section[-1][0], section[-1][-1] - - def nearest_corner(self, section, point): - return min(self.get_corner_points(section), - key=lambda corner: abs(self.perimeter_distance(point, corner))) - - def find_nearest_section(self, sections, point): - sections_with_nearest_corner = [(i, self.nearest_corner(section, point)) - for i, section in enumerate(sections)] - return min(sections_with_nearest_corner, - key=lambda(section, corner): abs(self.perimeter_distance(point, corner))) - - def section_from_corner(self, section, start_corner, angle, row_spacing, max_stitch_length): - if start_corner not in section[0]: - section = list(reversed(section)) - - if section[0][0] != start_corner: - section = [list(reversed(row)) for row in section] - - return self.section_to_patch(section, angle, row_spacing, max_stitch_length) - - def do_auto_fill(self, angle, row_spacing, max_stitch_length, starting_point=None): - rows_of_segments = self.intersect_region_with_grating(angle, row_spacing) - sections = self.pull_runs(rows_of_segments) - + def visualize_graph(self, graph): patches = [] - last_stitch = starting_point - while sections: - if last_stitch: - section_index, start_corner = self.find_nearest_section(sections, last_stitch) - patches.append(self.connect_points(last_stitch, start_corner)) - patches.append(self.section_from_corner(sections.pop(section_index), start_corner, angle, row_spacing, max_stitch_length)) - else: - patches.append(self.section_to_patch(sections.pop(0), angle, row_spacing, max_stitch_length)) - last_stitch = patches[-1].stitches[-1] + graph = graph.copy() + + for start, end, key in graph.edges_iter(keys=True): + if key == "extra": + patch = Patch(color="#FF0000") + patch.add_stitch(PyEmb.Point(*start)) + patch.add_stitch(PyEmb.Point(*end)) + patches.append(patch) return patches + + def do_auto_fill(self, angle, row_spacing, max_stitch_length, starting_point=None): + patches = [] + + rows_of_segments = self.intersect_region_with_grating(angle, row_spacing) + segments = [segment for row in rows_of_segments for segment in row] + + graph = self.build_graph(segments, angle, row_spacing) + path = self.find_stitch_path(graph, segments) + + # snip off the last one because it just unnecessarily returns to the start + path.pop() + + if starting_point: + patch = Patch(self.color) + self.connect_points(patch, starting_point, path[0][0]) + patches.append(patch) + + patches.append(self.path_to_patch(graph, path, angle, row_spacing, max_stitch_length)) + + return patches + + def to_patches(self, last_patch): - print >> dbg, "autofill" - self.validate() + print >> dbg, "autofill", self.max_stitch_length, self.fill_underlay_max_stitch_length patches = []