from generate_data import generate
from ap import AP
from config import MainCfg
import numpy as np
import os

def similarity(p1, p2):
    return -((p1[0] - p2[0])**2 + (p1[1] - p2[1])**2)

def main():
    if not os.path.exists("data"):
        os.makedirs("data")
    if not os.path.exists("output"):
        os.makedirs("output")
    if MainCfg.generate_new_data:
        generate()
    X = np.loadtxt("data/data.txt")
    ap = AP(X, similarity)
    ap.categorize(show_iterations=MainCfg.show_iterations, outfilename=MainCfg.outfilename, outgifname=MainCfg.outgifname)

if __name__ == "__main__":
    main()
    input()


0219449b1f5d69f9e50b7b294881006699600c36
<mask token>


def similarity(p1, p2):
    return -((p1[0] - p2[0]) ** 2 + (p1[1] - p2[1]) ** 2)


<mask token>

<mask token>


def similarity(p1, p2):
    return -((p1[0] - p2[0]) ** 2 + (p1[1] - p2[1]) ** 2)


def main():
    if not os.path.exists('data'):
        os.makedirs('data')
    if not os.path.exists('output'):
        os.makedirs('output')
    if MainCfg.generate_new_data:
        generate()
    X = np.loadtxt('data/data.txt')
    ap = AP(X, similarity)
    ap.categorize(show_iterations=MainCfg.show_iterations, outfilename=
        MainCfg.outfilename, outgifname=MainCfg.outgifname)


<mask token>

<mask token>


def similarity(p1, p2):
    return -((p1[0] - p2[0]) ** 2 + (p1[1] - p2[1]) ** 2)


def main():
    if not os.path.exists('data'):
        os.makedirs('data')
    if not os.path.exists('output'):
        os.makedirs('output')
    if MainCfg.generate_new_data:
        generate()
    X = np.loadtxt('data/data.txt')
    ap = AP(X, similarity)
    ap.categorize(show_iterations=MainCfg.show_iterations, outfilename=
        MainCfg.outfilename, outgifname=MainCfg.outgifname)


if __name__ == '__main__':
    main()
    input()

from generate_data import generate
from ap import AP
from config import MainCfg
import numpy as np
import os


def similarity(p1, p2):
    return -((p1[0] - p2[0]) ** 2 + (p1[1] - p2[1]) ** 2)


def main():
    if not os.path.exists('data'):
        os.makedirs('data')
    if not os.path.exists('output'):
        os.makedirs('output')
    if MainCfg.generate_new_data:
        generate()
    X = np.loadtxt('data/data.txt')
    ap = AP(X, similarity)
    ap.categorize(show_iterations=MainCfg.show_iterations, outfilename=
        MainCfg.outfilename, outgifname=MainCfg.outgifname)


if __name__ == '__main__':
    main()
    input()

from generate_data import generate
from ap import AP
from config import MainCfg
import numpy as np
import os

def similarity(p1, p2):
    return -((p1[0] - p2[0])**2 + (p1[1] - p2[1])**2)

def main():
    if not os.path.exists("data"):
        os.makedirs("data")
    if not os.path.exists("output"):
        os.makedirs("output")
    if MainCfg.generate_new_data:
        generate()
    X = np.loadtxt("data/data.txt")
    ap = AP(X, similarity)
    ap.categorize(show_iterations=MainCfg.show_iterations, outfilename=MainCfg.outfilename, outgifname=MainCfg.outgifname)

if __name__ == "__main__":
    main()
    input()

