import numpy as np
from numpy import random
from argparse import ArgumentParser

def cluster_num(datapoints,iters=10):
    datapoints = np.genfromtxt(samplesfile, 
                               delimiter=",", dtype='float')
    
    point1 = np.random.randint(len(datapoints))
    point2 = np.random.randint(len(datapoints))
    point3 = np.random.randint(len(datapoints))

    #random starting points
    rsp = np.array([[datapoints[point1,0],datapoints[point1,1]],
                   [datapoints[point2,0],datapoints[point2,1]],
                   [datapoints[point3,0],datapoints[point3,1]]])

    #storing array
    str_ary = np.empty(len(datapoints))
    
 
    for j in range(iters):
        a=datapoints-rsp[0]
        b=datapoints-rsp[1]
        c=datapoints-rsp[2]
        nearest1 = np.hypot(a[:,0],a[:,1])
        nearest2 = np.hypot(b[:,0],b[:,1])
        nearest3 = np.hypot(c[:,0],c[:,1])
        stacked_matrix = np.stack((nearest1,nearest2,nearest3))
        str_ary = np.argmin(stacked_matrix, axis=0)
            
        rsp[0]=np.sum(datapoints[np.argwhere(str_ary==0)],axis=0)/len(np.argwhere(str_ary==0))
        rsp[1]=np.sum(datapoints[np.argwhere(str_ary==1)],axis=0)/len(np.argwhere(str_ary==1))
        rsp[2]=np.sum(datapoints[np.argwhere(str_ary==2)],axis=0)/len(np.argwhere(str_ary==2))


    print("Cluster 1 is centred at " + str(rsp[0]) + " and has " + str(len(np.argwhere(str_ary==0))) + " points.")
    print("Cluster 2 is centred at " + str(rsp[1]) + " and has " + str(len(np.argwhere(str_ary==1))) + " points.")
    print("Cluster 3 is centred at " + str(rsp[2]) + " and has " + str(len(np.argwhere(str_ary==2))) + " points.")
    
if __name__ == "__main__":
    parser = ArgumentParser(description='clustering_numpy.py')
    parser.add_argument('samplesfile', type=str, 
                        help='Please give file path to samples.csv')
    parser.add_argument('--iters', default=10, type=int,
                        help='Please give number of iterations')
    arguments = parser.parse_args()
    samplesfile=arguments.samplesfile
    iters=arguments.iters
    datapoints = np.genfromtxt(samplesfile, delimiter=",", dtype='float')
    cluster_num(datapoints,iters)
56c629e1a7188a112f7bc9eebae57743c0f7058e
<mask token>

<mask token>


def cluster_num(datapoints, iters=10):
    datapoints = np.genfromtxt(samplesfile, delimiter=',', dtype='float')
    point1 = np.random.randint(len(datapoints))
    point2 = np.random.randint(len(datapoints))
    point3 = np.random.randint(len(datapoints))
    rsp = np.array([[datapoints[point1, 0], datapoints[point1, 1]], [
        datapoints[point2, 0], datapoints[point2, 1]], [datapoints[point3, 
        0], datapoints[point3, 1]]])
    str_ary = np.empty(len(datapoints))
    for j in range(iters):
        a = datapoints - rsp[0]
        b = datapoints - rsp[1]
        c = datapoints - rsp[2]
        nearest1 = np.hypot(a[:, 0], a[:, 1])
        nearest2 = np.hypot(b[:, 0], b[:, 1])
        nearest3 = np.hypot(c[:, 0], c[:, 1])
        stacked_matrix = np.stack((nearest1, nearest2, nearest3))
        str_ary = np.argmin(stacked_matrix, axis=0)
        rsp[0] = np.sum(datapoints[np.argwhere(str_ary == 0)], axis=0) / len(np
            .argwhere(str_ary == 0))
        rsp[1] = np.sum(datapoints[np.argwhere(str_ary == 1)], axis=0) / len(np
            .argwhere(str_ary == 1))
        rsp[2] = np.sum(datapoints[np.argwhere(str_ary == 2)], axis=0) / len(np
            .argwhere(str_ary == 2))
    print('Cluster 1 is centred at ' + str(rsp[0]) + ' and has ' + str(len(
        np.argwhere(str_ary == 0))) + ' points.')
    print('Cluster 2 is centred at ' + str(rsp[1]) + ' and has ' + str(len(
        np.argwhere(str_ary == 1))) + ' points.')
    print('Cluster 3 is centred at ' + str(rsp[2]) + ' and has ' + str(len(
        np.argwhere(str_ary == 2))) + ' points.')


<mask token>

<mask token>


def cluster_num(datapoints, iters=10):
    datapoints = np.genfromtxt(samplesfile, delimiter=',', dtype='float')
    point1 = np.random.randint(len(datapoints))
    point2 = np.random.randint(len(datapoints))
    point3 = np.random.randint(len(datapoints))
    rsp = np.array([[datapoints[point1, 0], datapoints[point1, 1]], [
        datapoints[point2, 0], datapoints[point2, 1]], [datapoints[point3, 
        0], datapoints[point3, 1]]])
    str_ary = np.empty(len(datapoints))
    for j in range(iters):
        a = datapoints - rsp[0]
        b = datapoints - rsp[1]
        c = datapoints - rsp[2]
        nearest1 = np.hypot(a[:, 0], a[:, 1])
        nearest2 = np.hypot(b[:, 0], b[:, 1])
        nearest3 = np.hypot(c[:, 0], c[:, 1])
        stacked_matrix = np.stack((nearest1, nearest2, nearest3))
        str_ary = np.argmin(stacked_matrix, axis=0)
        rsp[0] = np.sum(datapoints[np.argwhere(str_ary == 0)], axis=0) / len(np
            .argwhere(str_ary == 0))
        rsp[1] = np.sum(datapoints[np.argwhere(str_ary == 1)], axis=0) / len(np
            .argwhere(str_ary == 1))
        rsp[2] = np.sum(datapoints[np.argwhere(str_ary == 2)], axis=0) / len(np
            .argwhere(str_ary == 2))
    print('Cluster 1 is centred at ' + str(rsp[0]) + ' and has ' + str(len(
        np.argwhere(str_ary == 0))) + ' points.')
    print('Cluster 2 is centred at ' + str(rsp[1]) + ' and has ' + str(len(
        np.argwhere(str_ary == 1))) + ' points.')
    print('Cluster 3 is centred at ' + str(rsp[2]) + ' and has ' + str(len(
        np.argwhere(str_ary == 2))) + ' points.')


if __name__ == '__main__':
    parser = ArgumentParser(description='clustering_numpy.py')
    parser.add_argument('samplesfile', type=str, help=
        'Please give file path to samples.csv')
    parser.add_argument('--iters', default=10, type=int, help=
        'Please give number of iterations')
    arguments = parser.parse_args()
    samplesfile = arguments.samplesfile
    iters = arguments.iters
    datapoints = np.genfromtxt(samplesfile, delimiter=',', dtype='float')
    cluster_num(datapoints, iters)

import numpy as np
from numpy import random
from argparse import ArgumentParser


def cluster_num(datapoints, iters=10):
    datapoints = np.genfromtxt(samplesfile, delimiter=',', dtype='float')
    point1 = np.random.randint(len(datapoints))
    point2 = np.random.randint(len(datapoints))
    point3 = np.random.randint(len(datapoints))
    rsp = np.array([[datapoints[point1, 0], datapoints[point1, 1]], [
        datapoints[point2, 0], datapoints[point2, 1]], [datapoints[point3, 
        0], datapoints[point3, 1]]])
    str_ary = np.empty(len(datapoints))
    for j in range(iters):
        a = datapoints - rsp[0]
        b = datapoints - rsp[1]
        c = datapoints - rsp[2]
        nearest1 = np.hypot(a[:, 0], a[:, 1])
        nearest2 = np.hypot(b[:, 0], b[:, 1])
        nearest3 = np.hypot(c[:, 0], c[:, 1])
        stacked_matrix = np.stack((nearest1, nearest2, nearest3))
        str_ary = np.argmin(stacked_matrix, axis=0)
        rsp[0] = np.sum(datapoints[np.argwhere(str_ary == 0)], axis=0) / len(np
            .argwhere(str_ary == 0))
        rsp[1] = np.sum(datapoints[np.argwhere(str_ary == 1)], axis=0) / len(np
            .argwhere(str_ary == 1))
        rsp[2] = np.sum(datapoints[np.argwhere(str_ary == 2)], axis=0) / len(np
            .argwhere(str_ary == 2))
    print('Cluster 1 is centred at ' + str(rsp[0]) + ' and has ' + str(len(
        np.argwhere(str_ary == 0))) + ' points.')
    print('Cluster 2 is centred at ' + str(rsp[1]) + ' and has ' + str(len(
        np.argwhere(str_ary == 1))) + ' points.')
    print('Cluster 3 is centred at ' + str(rsp[2]) + ' and has ' + str(len(
        np.argwhere(str_ary == 2))) + ' points.')


if __name__ == '__main__':
    parser = ArgumentParser(description='clustering_numpy.py')
    parser.add_argument('samplesfile', type=str, help=
        'Please give file path to samples.csv')
    parser.add_argument('--iters', default=10, type=int, help=
        'Please give number of iterations')
    arguments = parser.parse_args()
    samplesfile = arguments.samplesfile
    iters = arguments.iters
    datapoints = np.genfromtxt(samplesfile, delimiter=',', dtype='float')
    cluster_num(datapoints, iters)

import numpy as np
from numpy import random
from argparse import ArgumentParser

def cluster_num(datapoints,iters=10):
    datapoints = np.genfromtxt(samplesfile, 
                               delimiter=",", dtype='float')
    
    point1 = np.random.randint(len(datapoints))
    point2 = np.random.randint(len(datapoints))
    point3 = np.random.randint(len(datapoints))

    #random starting points
    rsp = np.array([[datapoints[point1,0],datapoints[point1,1]],
                   [datapoints[point2,0],datapoints[point2,1]],
                   [datapoints[point3,0],datapoints[point3,1]]])

    #storing array
    str_ary = np.empty(len(datapoints))
    
 
    for j in range(iters):
        a=datapoints-rsp[0]
        b=datapoints-rsp[1]
        c=datapoints-rsp[2]
        nearest1 = np.hypot(a[:,0],a[:,1])
        nearest2 = np.hypot(b[:,0],b[:,1])
        nearest3 = np.hypot(c[:,0],c[:,1])
        stacked_matrix = np.stack((nearest1,nearest2,nearest3))
        str_ary = np.argmin(stacked_matrix, axis=0)
            
        rsp[0]=np.sum(datapoints[np.argwhere(str_ary==0)],axis=0)/len(np.argwhere(str_ary==0))
        rsp[1]=np.sum(datapoints[np.argwhere(str_ary==1)],axis=0)/len(np.argwhere(str_ary==1))
        rsp[2]=np.sum(datapoints[np.argwhere(str_ary==2)],axis=0)/len(np.argwhere(str_ary==2))


    print("Cluster 1 is centred at " + str(rsp[0]) + " and has " + str(len(np.argwhere(str_ary==0))) + " points.")
    print("Cluster 2 is centred at " + str(rsp[1]) + " and has " + str(len(np.argwhere(str_ary==1))) + " points.")
    print("Cluster 3 is centred at " + str(rsp[2]) + " and has " + str(len(np.argwhere(str_ary==2))) + " points.")
    
if __name__ == "__main__":
    parser = ArgumentParser(description='clustering_numpy.py')
    parser.add_argument('samplesfile', type=str, 
                        help='Please give file path to samples.csv')
    parser.add_argument('--iters', default=10, type=int,
                        help='Please give number of iterations')
    arguments = parser.parse_args()
    samplesfile=arguments.samplesfile
    iters=arguments.iters
    datapoints = np.genfromtxt(samplesfile, delimiter=",", dtype='float')
    cluster_num(datapoints,iters)