mirror of https://github.com/VLSIDA/OpenRAM.git
268 lines
8.7 KiB
Python
268 lines
8.7 KiB
Python
import numpy as np
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from PIL import Image
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from itertools import tee
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import debug
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from vector3d import vector3d
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from cell import cell
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try:
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import Queue as Q # ver. < 3.0
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except ImportError:
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import queue as Q
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class grid:
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"""A two layer routing map. Each cell can be blocked in the vertical
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or horizontal layer.
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"""
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def __init__(self):
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""" Create a routing map of width x height cells and 2 in the z-axis. """
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self.NONPREFERRED_COST = 5
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self.VIA_COST = 3
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self.source = []
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self.target = []
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self.blocked = []
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# let's leave the map sparse, cells are created on demand
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self.map={}
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# priority queue for the maze routing
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self.q = Q.PriorityQueue()
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# def view(self,filename="test.png"):
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# """
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# View the data by creating an RGB array and mapping the data
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# structure to the RGB color palette.
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# """
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# v_map = np.zeros((self.width,self.height,3), 'uint8')
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# mid_map = np.ones((10,self.height,3), 'uint8')
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# h_map = np.ones((self.width,self.height,3), 'uint8')
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# # We shouldn't have a path greater than 50% the HPWL
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# # so scale all visited indices by this value for colorization
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# for x in range(self.width):
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# for y in range(self.height):
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# h_map[x,y] = self.map[vector3d(x,y,0)].get_color()
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# v_map[x,y] = self.map[vector3d(x,y,1)].get_color()
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# # This is just for scale
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# if x==0 and y==0:
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# h_map[x,y] = [0,0,0]
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# v_map[x,y] = [0,0,0]
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# v_img = Image.fromarray(v_map, 'RGB').rotate(90)
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# #v_img.show()
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# mid_img = Image.fromarray(mid_map, 'RGB').rotate(90)
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# h_img = Image.fromarray(h_map, 'RGB').rotate(90)
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# #h_img.show()
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# # concatenate them into a plot with the two layers
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# img = Image.new('RGB', (2*self.width+10, self.height))
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# img.paste(h_img, (0,0))
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# img.paste(mid_img, (self.width,0))
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# img.paste(v_img, (self.width+10,0))
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# #img.show()
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# img.save(filename)
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def set_property(self,ll,ur,z,name,value=True):
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for x in range(int(ll[0]),int(ur[0])+1):
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for y in range(int(ll[1]),int(ur[1])+1):
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n = vector3d(x,y,z)
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self.add_map(n)
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setattr (self.map[n], name, True)
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if n not in getattr(self, name):
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getattr(self, name).append(n)
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def add_blockage(self,ll,ur,z):
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debug.info(3,"Adding blockage ll={0} ur={1} z={2}".format(str(ll),str(ur),z))
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self.set_property(ll,ur,z,"blocked")
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def set_source(self,ll,ur,z):
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debug.info(1,"Adding source ll={0} ur={1} z={2}".format(str(ll),str(ur),z))
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self.set_property(ll,ur,z,"source")
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def set_target(self,ll,ur,z):
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debug.info(1,"Adding target ll={0} ur={1} z={2}".format(str(ll),str(ur),z))
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self.set_property(ll,ur,z,"target")
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def set_path(self,path):
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"""
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Mark the path in the routing grid for visualization
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"""
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for p in path:
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self.map[p].path=True
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def route(self,cost_bound=0):
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"""
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This does the A* maze routing with preferred direction routing.
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"""
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# We set a cost bound of 2.5 x the HPWL for run-time. This can be
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# over-ridden if the route fails due to pruning a feasible solution.
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if (cost_bound==0):
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cost_bound = 2.5*self.cost_to_target(self.source[0])
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# Make sure the queue is empty if we run another route
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while not self.q.empty():
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self.q.get()
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# Put the source items into the queue
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self.init_queue()
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cheapest_path = None
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cheapest_cost = None
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# Keep expanding and adding to the priority queue until we are done
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while not self.q.empty():
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(cost,path) = self.q.get()
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debug.info(2,"Expanding: cost=" + str(cost) + " " + str(path))
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# expand the last element
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neighbors = self.expand_dirs(path)
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debug.info(4,"Neighbors: " + str(neighbors))
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for n in neighbors:
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newpath = path + [n]
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if n not in self.map.keys():
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self.map[n]=cell()
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self.map[n].visited=True
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# check if we hit the target and are done
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if self.is_target(n):
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return (newpath,self.cost(newpath))
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else:
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# potential path cost + predicted cost
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cost = self.cost(newpath) + self.cost_to_target(n)
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# only add the cost if it is less than our bound
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if (cost < cost_bound):
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self.q.put((cost,newpath))
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debug.error("Unable to route path. Expand area?",-1)
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def is_target(self,point):
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"""
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Point is in the target set, so we are done.
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"""
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return point in self.target
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def expand_dirs(self,path):
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"""
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Expand each of the four cardinal directions plus up or down
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but not expanding to blocked cells. Expands in all directions
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regardless of preferred directions.
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"""
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# expand from the last point
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point = path[-1]
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neighbors = []
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east = point + vector3d(1,0,0)
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self.add_map(east)
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if not self.map[east].blocked and not east in path:
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neighbors.append(east)
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west= point + vector3d(-1,0,0)
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self.add_map(west)
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if not self.map[west].blocked and not west in path:
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neighbors.append(west)
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up = point + vector3d(0,0,1)
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self.add_map(up)
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if up.z<2 and not self.map[up].blocked and not up in path:
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neighbors.append(up)
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north = point + vector3d(0,1,0)
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self.add_map(north)
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if not self.map[north].blocked and not north in path:
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neighbors.append(north)
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south = point + vector3d(0,-1,0)
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self.add_map(south)
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if not self.map[south].blocked and not south in path:
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neighbors.append(south)
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down = point + vector3d(0,0,-1)
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self.add_map(down)
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if down.z>=0 and not self.map[down].blocked and not down in path:
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neighbors.append(down)
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return neighbors
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def add_map(self,p):
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"""
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Add a point to the map if it doesn't exist.
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"""
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if p not in self.map.keys():
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self.map[p]=cell()
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def init_queue(self):
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"""
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Populate the queue with all the source pins with cost
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to the target. Each item is a path of the grid cells.
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We will use an A* search, so this cost must be pessimistic.
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Cost so far will be the length of the path.
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"""
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debug.info(4,"Initializing queue.")
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for s in self.source:
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cost = self.cost_to_target(s)
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debug.info(4,"Init: cost=" + str(cost) + " " + str([s]))
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self.q.put((cost,[s]))
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def cost_to_target(self,source):
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"""
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Find the cheapest HPWL distance to any target point
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"""
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cost = source.hpwl(self.target[0])
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for t in self.target:
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cost = min(source.hpwl(t),cost)
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return cost
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def cost(self,path):
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"""
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The cost of the path is the length plus a penalty for the number
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of vias.
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We assume that non-preferred direction is penalized 2x.
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"""
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# Ignore the source pin layer change, FIXME?
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def pairwise(iterable):
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"s -> (s0,s1), (s1,s2), (s2, s3), ..."
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a, b = tee(iterable)
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next(b, None)
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return zip(a, b)
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plist = pairwise(path)
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cost = 0
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for p0,p1 in plist:
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if p0.z != p1.z: # via
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cost += self.VIA_COST
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elif p0.x != p1.x: # horizontal
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cost += self.NONPREFERRED_COST if (p0.z == 1) else 1
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elif p0.y != p1.y: # vertical
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cost += self.NONPREFERRED_COST if (p0.z == 0) else 1
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else:
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debug.error("Non-changing direction!")
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return cost
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def get_inertia(self,p0,p1):
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"""
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Sets the direction based on the previous direction we came from.
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"""
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# direction (index) of movement
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if p0.x==p1.x:
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return 1
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elif p0.y==p1.y:
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return 0
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else:
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# z direction
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return 2
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