# -*- coding: utf-8 -*-
"""
Created on Mon Jan  4 18:02:01 2021

@author: Melis
"""

##Install MiniSom Package
"""

!pip install MiniSom

"""## Importing the libraries"""
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd


"""## Importing the dataset"""
dataset = pd.read_csv('Credit_Card_Applications.csv')
X = dataset.iloc[:,:-1].values
y = dataset.iloc[:,-1].values

"""## Feature Scaling"""
from sklearn.preprocessing import MinMaxScaler
sc = MinMaxScaler(feature_range = (0,1))
X = sc.fit_transform(X)

"""##Training the SOM"""
from minisom import MiniSom
som = MiniSom( x=10, y=10, input_len = 15, sigma = 1.0, learning_rate = 0.5)
som.random_weights_init(X)
som.train_random(data = X, num_iteration = 100)

"""##Visualizing the results"""
"""i is going to be all the indexes of cust and x the vectors of cust"""
""" w[0] = x coordinate of the winNeuron, w[1] = y"""
from pylab import bone, pcolor, colorbar, plot, show
bone()
pcolor(som.distance_map().T)
colorbar()
markers = ['o','s']
colors = ['r','g']
for i,x in enumerate(X):
    w = som.winner(x)
    plot(w[0]+0.5,  
         w[1]+0.5,
         markers[y[i]],
         markeredgecolor = colors[y[i]],
         markerfacecolor = 'None',
         markersize = 10,
         markeredgewidth = 2)
show()


"""## Finding the frauds"""
mappings = som.win_map(X)
frauds = np.concatenate((mappings[1,1],mappings[6,8]),axis = 0)
frauds = sc.inverse_transform(frauds)


