X = np.asarray([[2.5, 2.5], [4, -1], [1, -4], [-3, 1.25], [-2, -4], [1, 5]]) #TOY DATASET
Y = [1, 1, 1, 0, 0, 0]

my_cmap = matplotlib.colors.LinearSegmentedColormap.from_list("", ["red","yellow","green"]) #for the contourf plot
sn=SigmoidNeuron() # object of class

def plot_sn(X,Y,sn,ax,wbb): # Creates contourf plot for the current value of "w" and "b"
  X1=np.linspace(-10,10,100)
  X2=np.linspace(-10,10,100)
  XX1,XX2=np.meshgrid(X1,X2)
  YY=np.zeros(XX1.shape)
  for i in range(X2.size):
    for j in range(X1.size):
      YY[i,j]=sn.sigmoid(sn.perceptron(np.asarray([X1[j],X2[i]])))
  ax.contourf(XX1,XX2,YY,cmap=my_cmap,alpha=0.6)
  ax.scatter(X[:,0],X[:,1],c=Y,cmap=my_cmap)
  ax.plot()




plt.figure(figsize=(10,20*6*5)) # initialize plot size
sn.fit([2.5,2.5],1,1,1,True,False)
ci=0
wbb=[]
for i in range(20):
  #ci=0
  for (x,y) in zip(X,Y):
    ci+=1
    ax=plt.subplot(20*6,1,ci)
    sn.fit(x,y,1,0.7,False,False)
    plot_sn(X,Y,sn,ax,wbb)