First commit
This commit is contained in:
139
bulkloading.py
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139
bulkloading.py
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from os import write
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import sys
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import csv
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_DIVISORS = [180.0 / 2 ** n for n in range(32)]
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class MBR:
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def __init__(self, id, xlow, xhigh, ylow, yhigh):
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self.xlow = xlow
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self.xhigh = xhigh
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self.ylow = ylow
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self.yhigh = yhigh
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self.id = id
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self.zcurve = self.findZcurve()
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def findZcurve(self):
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x_median = (self.xlow + self.xhigh) / 2
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y_median = (self.ylow + self.yhigh) / 2
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return interleave_latlng(y_median, x_median)
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def interleave_latlng(lat, lng):
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if lng > 180:
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x = (lng % 180) + 180.0
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elif lng < -180:
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x = (-((-lng) % 180)) + 180.0
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else:
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x = lng + 180.0
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if lat > 90:
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y = (lat % 90) + 90.0
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elif lat < -90:
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y = (-((-lat) % 90)) + 90.0
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else:
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y = lat + 90.0
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morton_code = ""
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for dx in _DIVISORS:
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digit = 0
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if y >= dx:
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digit |= 2
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y -= dx
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if x >= dx:
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digit |= 1
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x -= dx
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morton_code += str(digit)
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return morton_code
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# Given a set of coordinates find the MBR
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def findMBR(objId, points):
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x_min = min(points, key=lambda p: p[0])[0]
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x_max = max(points, key=lambda p: p[0])[0]
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y_min = min(points, key=lambda p: p[1])[1]
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y_max = max(points, key=lambda p: p[1])[1]
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return MBR(objId, x_min, x_max, y_min, y_max)
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# Given a set of MBRs find the MBR
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def createMBR(nodeId, mbrs):
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x_min = min(mbr.xlow for mbr in mbrs)
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x_max = max(mbr.xhigh for mbr in mbrs)
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y_min = min(mbr.ylow for mbr in mbrs)
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y_max = max(mbr.yhigh for mbr in mbrs)
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return MBR(nodeId, x_min, x_max, y_min, y_max)
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# Read data from input files
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def inputReader(filename1, filename2):
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set_of_points = []
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with open(filename1, 'r') as offsets, open(filename2, 'r') as coords:
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reader = csv.reader(offsets, delimiter=',', quoting=csv.QUOTE_NONE)
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for row in reader:
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points = []
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for i in range(int(row[2]) - int(row[1]) + 1):
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points.append([float(x) for x in coords.readline().split(',')])
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set_of_points.append([row[0], points])
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return set_of_points
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# Write data into output file
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def outputWriter(filename, rTree):
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with open(filename, 'w') as rtree:
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numNode = 0
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leaves = 0
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for level in rTree:
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for node in level:
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rtree.write("[{}, {}, [[".format(leaves, numNode))
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for i in range(len(node) - 1):
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rtree.write("{}, [{}, {}, {}, {}]],[".format(
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node[i].id, node[i].xlow, node[i].xhigh, node[i].ylow, node[i].yhigh))
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rtree.write("{}, [{}, {}, {}, {}]]]]".format(
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node[-1].id, node[-1].xlow, node[-1].xhigh, node[-1].ylow, node[-1].yhigh))
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rtree.write("\n")
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numNode += 1
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leaves = 1
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#
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def makeRtree(collection):
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level = [] # list of levels(of nodes) of nodes(of mbrs) of mbrs(of points)
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nodeId = 0
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rank = 0
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# Until we reach the root node
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while len(collection) > 1:
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# Split the mbr collection into nodes of 20
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nodes = [collection[x:x+20] for x in range(0, len(collection), 20)]
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# If the last node has less than 8 mbrs, fill with mbrs of the previous
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balance = 8 - len(nodes[-1])
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if balance > 0 and len(nodes) > 1:
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migrate = len(nodes[-2])
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nodes[-1] = nodes[-2][migrate-balance:] + nodes[-1]
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nodes[-2] = nodes[-2][:migrate-balance]
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# Make the new MBRs based on the corners of each 20-piece
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collection = []
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for node in nodes: #for every 20 MBRs in 500 MBRs
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collection.append(createMBR(nodeId, node))
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nodeId += 1
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level.append(nodes)
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print("{} nodes at level {}".format(len(nodes), rank))
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rank += 1
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return level
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if __name__ == '__main__':
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# Read the coordinates of the polygons points
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set_of_points = inputReader(filename1=sys.argv[1], filename2=sys.argv[2])
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# Create the mbrs of the polygons
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mbrs = []
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for sp in set_of_points:
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mbrs.append(findMBR(sp[0], sp[1]))
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# Sort the mbrs based on the Z curve
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mbrs.sort(key=lambda ld: ld.zcurve)
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# Make the Rtree
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rTree = makeRtree(mbrs)
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outputWriter("Rtree.txt", rTree)
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116
knnqueries.py
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116
knnqueries.py
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import sys
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import ast
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import heapq as hq
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from math import sqrt
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class Point:
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def __init__(self, x, y):
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self.x = x
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self.y = y
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class MBR:
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def __init__(self, id, xlow, xhigh, ylow, yhigh):
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self.xlow = xlow
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self.xhigh = xhigh
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self.ylow = ylow
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self.yhigh = yhigh
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self.id = id
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self.obj = False
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def setDistance(self, qp):
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self.distance = self.findDistance(qp)
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def findDistance(self, qp):
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dx = dy = 0
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if qp.x < self.xlow:
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dx = self.xlow - qp.x
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elif qp.x > self.xhigh:
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dx = qp.x - self.xhigh
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else:
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dx = 0
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if qp.y < self.ylow:
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dy = self.ylow - qp.y
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elif qp.y > self.yhigh:
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dy = qp.y - self.yhigh
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else:
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dy = 0
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return sqrt(dx**2 + dy**2)
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def makeObject(self):
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self.obj = True
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def __lt__(self, other):
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if self.distance < other.distance:
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return True
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return False
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class Node:
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def __init__(self, leaf, id, list_of_mbrs):
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self.leaf = leaf
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self.id = id
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self.list_of_mbrs = list_of_mbrs
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def parseRtree(filename):
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with open(filename, 'r') as f:
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nodes = []
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for line in f:
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node = ast.literal_eval(line)
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mbrs = []
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for mbr in node[2]:
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mbrs.append(MBR(int(mbr[0]), float(mbr[1][0]), float(mbr[1][1]),
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float(mbr[1][2]), float(mbr[1][3])))
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nodes.append(Node(node[0], node[1], mbrs))
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return nodes
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# Read and execute all the NN queries assigned to the r tree
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def parseQuery(rtree, filename, k):
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with open(filename, 'r') as f:
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num = 0
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for line in f:
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[x, y] = line.split()
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findKNN(rtree, Point(float(x), float(y)), k, num)
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num += 1
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# Search for the neareset k neighboors
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def findKNN(rtree, qp, k, num):
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# List to put our k nn objects
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results = []
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# Initialize a priority queue
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pq = []
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# Put the root nodes into the priority queue
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for mbr in rtree[-1].list_of_mbrs:
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mbr.setDistance(qp)
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hq.heappush(pq, mbr)
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while len(pq) > 0 and len(results) < k:
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# Retrieve the next node and remove it from the queue
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e = hq.heappop(pq)
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if e.obj == True:
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hq.heappush(results, e)
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continue
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# At a leaf node
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if rtree[e.id].leaf == 0:
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for mbr in rtree[e.id].list_of_mbrs:
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mbr.setDistance(qp)
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mbr.makeObject()
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hq.heappush(pq, mbr)
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# At an intermediate node
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else:
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for node in rtree[e.id].list_of_mbrs:
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node.setDistance(qp)
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hq.heappush(pq, node)
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print("{}:".format(num), end=' ')
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for r in range(k-1):
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nn = hq.heappop(results)
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print("{},".format(nn.id), end='')
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nn = hq.heappop(results)
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print(nn.id)
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if __name__ == '__main__':
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rtree = parseRtree(sys.argv[1])
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parseQuery(rtree, sys.argv[2], int(sys.argv[3]))
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78
rangequeries.py
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78
rangequeries.py
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import sys
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import ast
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class MBR:
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def __init__(self, id, xlow, xhigh, ylow, yhigh):
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self.xlow = xlow
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self.xhigh = xhigh
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self.ylow = ylow
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self.yhigh = yhigh
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self.id = id
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def intersects(self, other):
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if self.xlow > other.xhigh or self.xhigh < other.xlow:
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return False
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if self.ylow > other.yhigh or self.yhigh < other.ylow:
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return False
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return True
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class Node:
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def __init__(self, leaf, id, list_of_mbrs):
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self.leaf = leaf
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self.id = id
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self.list_of_mbrs = list_of_mbrs
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def parseRtree(filename):
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with open(filename, 'r') as f:
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nodes = []
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for line in f:
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node = ast.literal_eval(line)
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mbrs = []
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for mbr in node[2]:
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mbrs.append(MBR(int(mbr[0]), float(mbr[1][0]), float(mbr[1][1]),
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float(mbr[1][2]), float(mbr[1][3])))
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nodes.append(Node(node[0], node[1], mbrs))
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return nodes
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# Read and execute all the range queries assigned to the r tree
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def parseQuery(rtree, filename):
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with open(filename, 'r') as f:
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i = 0
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for line in f:
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[xlow, ylow, xhigh, yhigh] = line.split()
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results = []
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rangeQuery(rtree, MBR(int(i), float(xlow), float(xhigh),
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float(ylow), float(yhigh)), results)
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print("{} ({}):".format(i, len(results)), end=' ')
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for r in range(len(results) - 1):
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print("{},".format(results[r].id), end='')
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if len(results) != 0:
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print(results[-1].id)
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else:
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print(' ')
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i += 1
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# Find the intersecting rectangles
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def rangeQuery(rtree, window, results, node=None):
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# At the root node
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if node == None:
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node = rtree[-1]
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for n in node.list_of_mbrs:
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if window.intersects(n) or n.intersects(window):
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rangeQuery(rtree, window, results, rtree[n.id])
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# At an intermediate node
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elif node.leaf == 1:
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for n in node.list_of_mbrs:
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if window.intersects(n) or n.intersects(window):
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rangeQuery(rtree, window, results, rtree[n.id])
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# At a leaf node
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else:
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for mbr in node.list_of_mbrs:
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if window.intersects(mbr) or mbr.intersects(window):
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results.append(mbr)
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if __name__ == '__main__':
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rtree = parseRtree(sys.argv[1])
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parseQuery(rtree, sys.argv[2])
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Reference in New Issue
Block a user