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#!/usr/bin/env python
# coding: utf-8
 
# In[28]:
from __future__ import division
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import numpy as np
 
 
def plot_confusion_matrix(cm, classes,
                          normalize=True,
                          title='Confusion matrix',
                          cmap=plt.cm.hot):
    """
    This function prints and plots the confusion matrix.
    Normalization can be applied by setting `normalize=True`.
    """
    if normalize:
        cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]
        print("Normalized confusion matrix")
    else:
        print('Confusion matrix, without normalization')
 
    print(cm)
 
    plt.imshow(cm, interpolation='nearest')
    # plt.title(title)
    plt.colorbar()
    tick_marks = np.arange(len(classes))
    plt.xticks(tick_marks, classes, rotation=90)
    plt.yticks(tick_marks, classes)
 
    # fmt = '.2f' if normalize else 'd'
    # thresh = cm.max() / 2.
    # for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):
    #     plt.text(j, i, format(cm[i, j], fmt),
    #              horizontalalignment="center",
    #              color="white" if cm[i, j] > thresh else "black")
 
 
data = pd.read_csv(r"experiment\61476-2000\confusion_matrix.csv")
 
all_categories = data.iloc[:,0]  
confusion = np.array(data.iloc[:,1:])
# print(confusion)
# Normalize by dividing every row by its sum
# for i in range(len(all_categories)):
#     for j in range(len(all_categories)):
#         confusion[i][j] = confusion[i][j] / confusion[i].sum()
 
#Set up plot
 
fig = plt.figure()
ax = fig.add_subplot(111)
cax = ax.matshow(confusion)
# fig.colorbar(cax)
 
# Set up axes
ax.set_xticklabels([''] + all_categories, rotation=90)
ax.set_yticklabels([''] + all_categories)
 
# Force label at every tick
ax.xaxis.set_major_locator(ticker.MultipleLocator(1))
ax.yaxis.set_major_locator(ticker.MultipleLocator(1))
plot_confusion_matrix(confusion, classes=list(all_categories), title="Confusion matrix")
# sphinx_gallery_thumbnail_number = 2
plt.show()