import numpy as np
import matplotlib.pyplot as plt
from minisom import MiniSom
from mpl_toolkits.mplot3d import Axes3D
from skimage import measure

with open("benc.txt") as f:
    data = [[float(i) for i in linia.split()] for linia in f]

data = np.reshape(data, (699, 9))
data /= np.max(data)

som = MiniSom(40, 40, 9, sigma=0.6, learning_rate=0.5, random_seed=13)
som.train_batch(data, 1000)


distMap = som.distance_map().T
plt.pcolor(distMap, cmap='afmhot')
plt.show()

thresh = 0.6
distMap[distMap < thresh] = 0
distMap[distMap >= thresh] = 1
distMap = 1 - distMap
distMap[0, :], distMap[39, :], distMap[:, 0], distMap[:, 39] = 0, 0, 0, 0

for cnt, wsp in enumerate(data):
    w = som.winner(wsp)
    print(w)
    plt.plot(w[0], w[1], 'o')

plt.xlim([0, 40])
plt.ylim([0, 40])
plt.show()

blobs = measure.label(distMap)
plt.pcolor(blobs, cmap='terrain')
plt.show()