import numpy
X = numpy.loadtxt("spirals.csv", dtype = numpy.float, delimiter = ',')

from sklearn.cluster import SpectralClustering
spectral = SpectralClustering(n_clusters = 2, gamma = 4)    # larger gamma shrinks the kernel width
spectral.fit(X)

from matplotlib import pyplot
%matplotlib inline
cluster_labels = spectral.labels_
pyplot.scatter(X[:,0], X[:,1], c = cluster_labels)

output = open("predictions.csv", "w")
output.write("Id,Prediction\n")
index = 0
for i in range(len(cluster_labels) - 1):
    for j in range(i + 1, len(cluster_labels)):
        if (cluster_labels[i] == cluster_labels[j]):
            output.write(str(index) + ",1\n")    # same cluster
        else:
            output.write(str(index) + ",0\n")    # different clusters
        index = index + 1
output.close()