Plot accuracy and loss

plot_acc_loss.py

def plot_acc(history, ax = None, xlabel = 'Epoch #'):
    history = history.history
    history.update({'epoch':list(range(len(history['val_accuracy'])))})
    history = pd.DataFrame.from_dict(history)
    best_epoch = history.sort_values(by = 'val_accuracy', \
                                     ascending = False).iloc[0]['epoch']
    if not ax:
      f, ax = plt.subplots(1,1)
    sns.lineplot(x = 'epoch', y = 'val_accuracy', data = history \
                 label = 'Validation', ax = ax)
    sns.lineplot(x = 'epoch', y = 'accuracy', data = history\
                 label = 'Training', ax = ax)
    ax.axhline(0.5, linestyle = '--',color='red', label = 'Chance')
    ax.axvline(x = best_epoch, linestyle = '--', color = 'green', \
               label = 'Best Epoch')  
    ax.legend(loc = 1)    
    ax.set_ylim([0.4, 1])
    ax.set_xlabel(xlabel)
    ax.set_ylabel('Accuracy (Fraction)')
    plt.show()
    print("The highest validation accuracy was",history.sort_values\
          (by = 'val_accuracy', ascending = False).iloc[0]['val_accuracy'])
    print("The lowest validation accuracy was",history.sort_values\
          (by = 'val_accuracy', ascending = True).iloc[0]['val_accuracy'])
    
    
def plot_loss(history, ax = None, xlabel = 'Epoch #'):
    history = history.history
    history.update({'epoch':list(range(len(history['val_loss'])))})
    history = pd.DataFrame.from_dict(history)
    best_epoch = history.sort_values(by = 'val_loss',\
                                     ascending = True).iloc[0]['epoch']
    if not ax:
      f, ax = plt.subplots(1,1)
    sns.lineplot(x = 'epoch', y = 'val_loss', data = history,\
                 label = 'Validation', ax = ax)
    sns.lineplot(x = 'epoch', y = 'loss', data = history,\
                 label = 'Training', ax = ax)
    ax.axvline(x = best_epoch, linestyle = '--', color = 'green',\
               label = 'Best Epoch')  
    ax.legend(loc = 1)    
    ax.set_ylim([0.1, 1])
    ax.set_xlabel(xlabel)
    ax.set_ylabel('Loss (Fraction)')
    plt.show()
    print("The lowest validation loss was",history.sort_values\
          (by = 'val_loss', ascending = True).iloc[0]['val_loss'])
    print("The highest validation loss was",history.sort_values\
          (by = 'val_loss', ascending = False).iloc[0]['val_loss'])