kopia lustrzana https://github.com/evil-mad/EggBot
Code cleanup: uniform indents (tabs)
git-svn-id: https://eggbotcode.googlecode.com/svn/trunk@92 72233254-1b6c-9e9c-5072-401df62706fbpull/47/head
craig.trader@gmail.com
rodzic
2410291d96
commit
d968d29a9d
Plik diff jest za duży
Load Diff
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@ -30,137 +30,136 @@ import string
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import math
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import random
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def dist(x0, y0, x1, y1):
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return math.sqrt( (x1 - x0)**2 + (y1 - y0)**2 )
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def dist( x0, y0, x1, y1 ):
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return math.sqrt( ( x1 - x0 ) ** 2 + ( y1 - y0 ) ** 2 )
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# Takes a list of (id, (startX, startY, endX, endY)), and finds the best ordering.
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# Doesn't handle anything fancy, like reversing the ordering, but it's useful for now.
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# Returns a list of JUST THE IDs, in a better order, as well as the original and optimized
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# "air distance" which is just the distance traveled in the air. Perhaps we want to make
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# these comparison distances into something more relevant such as degrees traveled?
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def find_ordering_naive(objlist):
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def find_ordering_naive( objlist ):
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# let's figure out the default in-air length, so we know how much we improved
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air_length_default = 0
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try:
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oldx = objlist[0][1][2]
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oldy = objlist[0][1][3]
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except:
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inkex.errormsg(gettext.gettext(str(objlist[0])))
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sys.exit(1)
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for id, coords in objlist[1:]:
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air_length_default += dist(oldx, oldy, coords[0], coords[1])
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oldx = coords[2]
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oldy = coords[3]
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#fid.write("Default air distance: %d\n" % air_length_default)
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# let's figure out the default in-air length, so we know how much we improved
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air_length_default = 0
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try:
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oldx = objlist[0][1][2]
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oldy = objlist[0][1][3]
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except:
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inkex.errormsg( gettext.gettext( str( objlist[0] ) ) )
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sys.exit( 1 )
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for id, coords in objlist[1:]:
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air_length_default += dist( oldx, oldy, coords[0], coords[1] )
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oldx = coords[2]
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oldy = coords[3]
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#fid.write("Default air distance: %d\n" % air_length_default)
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air_length_ordered = 0
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# for now, start with a random one:
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sort_list = []
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random_index = random.randint(0, len(objlist) - 1)
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sort_list.append(objlist[random_index])
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objlist.remove(objlist[random_index])
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# for now, do this in the most naive way:
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# for the previous end point, iterate over each remaining path and pick the closest starting point
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while len(objlist) > 0:
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min_distance = 100000000 # TODO put something else here better?
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for path in objlist:
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# instead of having a prevX, prevY, we just look at the last item in sort_list
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this_distance = dist(sort_list[-1][1][2], sort_list[-1][1][3], path[1][0], path[1][1])
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# this is such a common thing to do, you'd think there would be a name for it...
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if this_distance < min_distance:
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min_distance = this_distance
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min_path = path
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air_length_ordered += min_distance
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sort_list.append(min_path)
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objlist.remove(min_path)
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air_length_ordered = 0
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# for now, start with a random one:
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sort_list = []
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random_index = random.randint( 0, len( objlist ) - 1 )
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sort_list.append( objlist[random_index] )
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objlist.remove( objlist[random_index] )
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# for now, do this in the most naive way:
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# for the previous end point, iterate over each remaining path and pick the closest starting point
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while len( objlist ) > 0:
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min_distance = 100000000 # TODO put something else here better?
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for path in objlist:
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# instead of having a prevX, prevY, we just look at the last item in sort_list
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this_distance = dist( sort_list[-1][1][2], sort_list[-1][1][3], path[1][0], path[1][1] )
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# this is such a common thing to do, you'd think there would be a name for it...
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if this_distance < min_distance:
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min_distance = this_distance
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min_path = path
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air_length_ordered += min_distance
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sort_list.append( min_path )
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objlist.remove( min_path )
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#fid.write("optimized air distance: %d\n" % air_length_ordered)
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#fid.write("optimized air distance: %d\n" % air_length_ordered)
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# remove the extraneous info from the list order
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sort_order = [id for id, coords in sort_list]
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return sort_order, air_length_default, air_length_ordered
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# remove the extraneous info from the list order
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sort_order = [id for id, coords in sort_list]
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return sort_order, air_length_default, air_length_ordered
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# not used currently, but can be used to apply a translation matrix to an (x, y) pair
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# I'm sure there is a better way to do this using simpletransform or it's ilk
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def conv(x, y, trans_matrix=None):
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if trans_matrix:
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xt = trans_matrix[0][0]*x + trans_matrix[0][1]*y + trans_matrix[0][2]
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yt = trans_matrix[1][0]*x + trans_matrix[1][1]*y + trans_matrix[1][2]
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return xt, yt
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else:
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return x, y
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def conv( x, y, trans_matrix=None ):
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if trans_matrix:
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xt = trans_matrix[0][0] * x + trans_matrix[0][1] * y + trans_matrix[0][2]
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yt = trans_matrix[1][0] * x + trans_matrix[1][1] * y + trans_matrix[1][2]
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return xt, yt
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else:
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return x, y
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class EggBotReorderPaths(inkex.Effect):
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def __init__(self):
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inkex.Effect.__init__(self)
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self.OptionParser.add_option('-r', '--reverse', action='store', type="inkbool",
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dest="reverse", default=True, help="Enable 'reverse path direction' optimizations")
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self.OptionParser.add_option('-w', '--wrap', action='store', type="inkbool",
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dest="wrap", default=True, help="Enable 'wrap egg axis' optimizations")
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class EggBotReorderPaths( inkex.Effect ):
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def __init__( self ):
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inkex.Effect.__init__( self )
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self.OptionParser.add_option( '-r', '--reverse', action='store', type="inkbool",
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dest="reverse", default=True, help="Enable 'reverse path direction' optimizations" )
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self.OptionParser.add_option( '-w', '--wrap', action='store', type="inkbool",
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dest="wrap", default=True, help="Enable 'wrap egg axis' optimizations" )
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# Given a node, return the start and end points
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def get_start_end(self, node, transform):
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d = node.get('d')
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sp = simplepath.parsePath(d)
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# simplepath converts coordinates to absolute and cleans them up, but
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# these are still some big assumptions here, are they always valid? TODO
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startX = sp[0][1][0]
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startY = sp[0][1][1]
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if sp[-1][0] == 'Z':
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# go back to start
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endX = startX
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endY = startY
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else:
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endX = sp[-1][1][-2]
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endY = sp[-1][1][-1]
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# Given a node, return the start and end points
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def get_start_end( self, node, transform ):
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d = node.get( 'd' )
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sp = simplepath.parsePath( d )
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# simplepath converts coordinates to absolute and cleans them up, but
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# these are still some big assumptions here, are they always valid? TODO
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startX = sp[0][1][0]
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startY = sp[0][1][1]
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if sp[-1][0] == 'Z':
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# go back to start
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endX = startX
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endY = startY
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else:
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endX = sp[-1][1][-2]
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endY = sp[-1][1][-1]
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sx, sy = conv(startX, startY, transform)
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ex, ey = conv(endX, endY, transform)
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return (sx, sy, ex, ey)
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sx, sy = conv( startX, startY, transform )
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ex, ey = conv( endX, endY, transform )
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return ( sx, sy, ex, ey )
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# This is the main entry point
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def effect(self):
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# based partially on the restack.py extension
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if len(self.selected) > 0:
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svg = self.document.getroot()
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# TODO check for non-path elements?
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# TODO it seems like the order of selection is not consistent
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# This is the main entry point
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def effect( self ):
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# based partially on the restack.py extension
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if len( self.selected ) > 0:
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svg = self.document.getroot()
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# TODO check for non-path elements?
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# TODO it seems like the order of selection is not consistent
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#fid = open("/home/matthew/debug.txt", "w")
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#fid = open("/home/matthew/debug.txt", "w")
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# for each selected item - TODO make this be all objects, everywhere
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# I can think of two options:
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# 1. Iterate over all paths in root, then iterate over all layers, and their paths
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# 2. Some magic with xpath? (would this limit us to specific node types?)
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objlist = []
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for id, node in self.selected.iteritems():
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transform = node.get('transform')
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if transform:
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transform = simpletransform.parseTransform(transform)
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# for each selected item - TODO make this be all objects, everywhere
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# I can think of two options:
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# 1. Iterate over all paths in root, then iterate over all layers, and their paths
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# 2. Some magic with xpath? (would this limit us to specific node types?)
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objlist = []
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for id, node in self.selected.iteritems():
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transform = node.get( 'transform' )
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if transform:
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transform = simpletransform.parseTransform( transform )
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item = (id, self.get_start_end(node, transform))
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objlist.append(item)
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# sort / order the objects
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sort_order, air_distance_default, air_distance_ordered = find_ordering_naive(objlist)
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item = ( id, self.get_start_end( node, transform ) )
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objlist.append( item )
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for id in sort_order:
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# There's some good magic here, that you can use an
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# object id to index into self.selected. Brilliant!
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self.current_layer.append(self.selected[id])
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# sort / order the objects
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sort_order, air_distance_default, air_distance_ordered = find_ordering_naive( objlist )
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for id in sort_order:
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# There's some good magic here, that you can use an
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# object id to index into self.selected. Brilliant!
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self.current_layer.append( self.selected[id] )
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#fid.close()
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if air_distance_default > 0 : #don't divide by zero. :P
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improvement_pct = 100 * ( ( air_distance_default - air_distance_ordered ) / ( air_distance_default ) )
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inkex.errormsg( gettext.gettext( "Okay, selected paths have been reordered and optimized for quicker Eggbot plotting.\n\nOriginal air-distance: %d\nOptimized air-distance: %d\nDistance reduced by: %1.2d%%\n\nHave a nice day!" % ( air_distance_default, air_distance_ordered, improvement_pct ) ) )
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else:
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inkex.errormsg( gettext.gettext( "doh-- need to have multiple distinct paths selected!" ) )
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#fid.close()
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if air_distance_default > 0 : #don't divide by zero. :P
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improvement_pct = 100 * ((air_distance_default - air_distance_ordered) / (air_distance_default))
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inkex.errormsg(gettext.gettext("Okay, selected paths have been reordered and optimized for quicker Eggbot plotting.\n\nOriginal air-distance: %d\nOptimized air-distance: %d\nDistance reduced by: %1.2d%%\n\nHave a nice day!" % (air_distance_default, air_distance_ordered, improvement_pct)))
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else:
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inkex.errormsg(gettext.gettext("doh-- need to have multiple distinct paths selected!"))
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e = EggBotReorderPaths()
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e.affect()
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