Exemple #1
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def buildRtree(dataSetName, *B):
    global root
    global Bvalue

    Bvalue = 25
    if len(B) == 1 and B[0] != None:
        Bvalue = B[0]

    f = open(dataSetName, 'rt')
    nextLine = f.readline()
    # size of date set
    size = int(nextLine.strip('\n'))
    # read the first point and build a root
    nextLine = f.readline()
    point = Rtree.Point(scanRange.getPoint(nextLine))
    root = Rtree.Leaf(Bvalue, 1, point)
    root.addChild(point)

    # add the remained points
    nextLine = f.readline()
    while nextLine != '':
        point = Rtree.Point(scanRange.getPoint(nextLine))
        insert(root, point)
        nextLine = f.readline()

    f.close()
    print('R-tree has been built. B is:', Bvalue, 'Highest level is:',
          root.level)
    return root
Exemple #2
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def buildRtree(dataSetName, *B):
    global root
    global Bvalue
    
    Bvalue = 25 # Upper limit of the node, initial 25.
    if len(B) == 1 and B[0] != None:
        Bvalue = B[0]
    f = open(dataSetName, 'rt')
    nextLine = f.readline()
    # size of date set
    size = int(nextLine.strip('\n'))
    # read the first point and build a root
    nextLine = f.readline()
    point = Rtree.Point(getPoint(nextLine))
    root = Rtree.Leaf(Bvalue, 1, point)
    root.addChild(point)
    # add the remained points
    nextLine = f.readline()
    while nextLine == '\n':
        nextLine = f.readline()
    while nextLine != '':
        point = Rtree.Point(getPoint(nextLine))
        insert(root, point)
        nextLine = f.readline()
        while nextLine == '\n':
            nextLine = f.readline()
    f.close()
    maintain(root)
    print('R-tree has been built. B is:', Bvalue,'. Highest level is:',root.level)
    '''print('第1层: ',root.attribute,'     ',root.bitmap)
    for child in root.childList:
        print('第2层: ',child.attribute,'    ',child.bitmap)
        for cc in child.childList:
            print('第3层: ', cc.attribute, '    ', cc.bitmap)
            for ccc in child.childList:
                print('第4层: ', ccc.attribute, '    ', ccc.bitmap)
                for aaa in ccc.childList:
                    print(aaa.x,' ',aaa.y,' ',aaa.attribute,aaa.bitmap)'''
                
    return root
Exemple #3
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def handleOverFlow(node):
    global root
    global Bvalue

    # split node into two new nodes
    nodes = node.split()
    # if root node is overflow, new root need to build
    if node.paren == None:
        root = Rtree.Branch(Bvalue, node.level + 1, nodes[0])
        root.addChild(nodes[0])
        root.addChild(nodes[1])
        root.childList[0].paren = root
        root.childList[1].paren = root
    else:
        # update the parent node
        parent = node.paren
        parent.childList.remove(node)
        parent.childList += nodes
        # check whether parent node is overflow
        if parent.isOverFlow():
            handleOverFlow(parent)
Exemple #4
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def basicTest():
    gen = MbrGenerator()
    mTree = Rtree(d=4, M=25, maxE=10 ** 6, reset=True, initOffset=0, partitionType=0)
    resFileName = "../results/Resultados Test.txt"
    f = open(resFileName, 'a+')
    f.write(datetime.datetime.now().strftime("%Y-%m-%d %H:%M"))
    f.write(" d=%d M=%d partitionType=%d\n" % (4, 25, 0))
    f.write("meanPartitionsPerNode meanInsertTime meanTotalNodes meanInternalNodes\n")
    # Construyo el Rtree con los elementos
    for s in range (10 ** 3):
        mTree.insert(gen.next(d=4))
    f.write("%f %f %f %f\n" % (mTree.getMeanNodePartitions(), mTree.meanInsertionTime, mTree.meanTotalNodes, mTree.meanInternalNodes))
    f.write("meanVisited meanQueryTime\n")
    f.close()
    fileName = "../results/busqueda test " + str(mTree.treeType) + " M" + str(mTree.M()) + " d" + str(mTree.d()) + ".bin"
    mTree = Rtree(d=4, M=25, maxE=10 ** 6, reset=False, initOffset=0, partitionType=0)
    # Construyo los elementos de consulta
    f = open(resFileName, 'a+')
    fb = open(fileName, 'a+')
    for s in range (100):
        mTree.search(gen.nextRadial(d=4, r=0.25 * 2), fb,False, True)
    f.write("%f %f\n" % (mTree.getMeanVisitedNodes(), mTree.meanSearchTime))
    f.close()
    fb.close()
Exemple #5
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from Rtree import *
from random import uniform
from time import time
import csv

root = Rtree(m=3, M=7)

stations = []

i = 0
with open("2013NRSC.csv", "rU") as csvfile:
    radioCsv = csv.reader(csvfile, delimiter=",", quotechar='"')
    for station in radioCsv:
        y = float(station[7])
        x = float(station[8])
        stations.append(
            node(
                MBR={
                    "xmin": x - 0.01,
                    "xmax": x + 0.01,
                    "ymin": y - 0.01,
                    "ymax": y + 0.01,
                },
                index=i,
            ))
        i = i + 1

for j in range(i):
    root = Insert(root, stations[j])
    print(type(root))
print(root.leaves)
Exemple #6
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#!/usr/bin/python
# -*- coding: utf-8 -*-
from Rtree import *
from random import uniform
from time import time

numRuns = 1000

data = {}
# Initialize 10000 coordinates (-1000, 1000), an area of ​​a rectangle 0.01.
for i in range(numRuns):
    x = uniform(-1000, 1000)
    y = uniform (-1000, 1000)
    data [i] = {'xmin': x, 'xmax': x + 0.01, 'ymin': y, 'ymax': y + 0.01}
# Set a root node, m = 3, M = 7
root = Rtree(m = 3, M = 7)
n = []

for i in range(numRuns):
    n.append(node(MBR = data[i], index = i))
t0 = time()
# Insert
for i in range(numRuns):
    root = Insert(root, n[i])
    print root
t1 = time()
print 'Inserting ...'
print t1 - t0
#search for
x = root.Search(merge(n[0].MBR, n[1].MBR))
print x
Exemple #7
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        mTree.search(gen.nextRadial(d=4, r=0.25 * 2), fb,False, True)
    f.write("%f %f\n" % (mTree.getMeanVisitedNodes(), mTree.meanSearchTime))
    f.close()
    fb.close()

if __name__ == '__main__':
#     basicTest()
    resFileName = "../results/Resultados.txt"
    for j in range(1, 11):
        k = 1
        for partitionType in [0, 1]:
#         for d in [2, 4, 8, 16]:
          for d in [4, 8, 16]:
              for M in [50, 100]:
                  gen = MbrGenerator()
                  mTree = Rtree(d=d, M=M, maxE=10 ** 6, reset=True, initOffset=0, partitionType=partitionType)
                  f = open(resFileName, 'a+')
                  f.write(datetime.datetime.now().strftime("%Y-%m-%d %H:%M"))
                  f.write(" d=%d M=%d partitionType=%d\n" % (d, M, partitionType))
                  f.write("meanPartitionsPerNode meanInsertTime meanTotalNodes meanInternalNodes\n")
                  # Construyo el Rtree con los elementos
                  for s in range (10 ** 5):
                      mTree.insert(gen.next(d=d))
                  f.write("%f %f %f %f\n" % (mTree.getMeanNodePartitions(), mTree.meanInsertionTime, mTree.meanTotalNodes, mTree.meanInternalNodes))
                  f.write("meanVisited meanQueryTime\n")
                  print("Insercion n:%d" % k)
                  k += 1
                  f.close()
                  fileName = "../results/busqueda " + str(mTree.treeType) + " M" + str(mTree.M()) + " d" + str(mTree.d()) + ".bin"
                  # Construyo los elementos de consulta
                  for radio in [0.25, 0.50, 0.75]: