1  # Copyright 2020 Jordi Corbilla. All Rights Reserved.
   2  #
   3  # Licensed under the Apache License, Version 2.0 (the "License");
   4  # you may not use this file except in compliance with the License.
   5  # You may obtain a copy of the License at
   6  #
   7  #     http://www.apache.org/licenses/LICENSE-2.0
   8  #
   9  # Unless required by applicable law or agreed to in writing, software
  10  # distributed under the License is distributed on an "AS IS" BASIS,
  11  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  12  # See the License for the specific language governing permissions and
  13  # limitations under the License.
  14  # ==============================================================================
  15  import os
  16  import matplotlib.pyplot as plt
  17  
  18  
  19  class Plotter:
  20      def __init__(self, blocking, project_folder, short_name, currency, stock_ticker):
  21          self.blocking = blocking
  22          self.project_folder = project_folder
  23          self.short_name = short_name
  24          self.currency = currency
  25          self.stock_ticker = stock_ticker
  26  
  27      def plot_histogram_data_split(self, training_data, test_data, validation_date):
  28          print("plotting Data and Histogram")
  29          plt.figure(figsize=(12, 5))
  30          plt.plot(training_data.Close, color='green')
  31          plt.plot(test_data.Close, color='red')
  32          plt.ylabel('Price [' + self.currency + ']')
  33          plt.xlabel("Date")
  34          plt.legend(["Training Data", "Validation Data >= " + validation_date.strftime("%Y-%m-%d")])
  35          plt.title(self.short_name)
  36          plt.savefig(os.path.join(self.project_folder, self.short_name.strip().replace('.', '') + '_price.png'))
  37  
  38          fig, ax = plt.subplots()
  39          training_data.hist(ax=ax)
  40          fig.savefig(os.path.join(self.project_folder, self.short_name.strip().replace('.', '') + '_hist.png'))
  41  
  42          plt.pause(0.001)
  43          plt.show(block=self.blocking)
  44  
  45      def plot_loss(self, history):
  46          print("plotting loss")
  47          plt.plot(history.history['loss'], label='loss')
  48          plt.plot(history.history['val_loss'], label='val_loss')
  49          plt.xlabel('Epoch')
  50          plt.ylabel('Loss')
  51          plt.title('Loss/Validation Loss')
  52          plt.legend(loc='upper right')
  53          plt.savefig(os.path.join(self.project_folder, 'loss.png'))
  54          plt.pause(0.001)
  55          plt.show(block=self.blocking)
  56  
  57      def plot_mse(self, history):
  58          print("plotting MSE")
  59          plt.plot(history.history['MSE'], label='MSE')
  60          plt.plot(history.history['val_MSE'], label='val_MSE')
  61          plt.xlabel('Epoch')
  62          plt.ylabel('MSE')
  63          plt.title('MSE/Validation MSE')
  64          plt.legend(loc='upper right')
  65          plt.savefig(os.path.join(self.project_folder, 'MSE.png'))
  66          plt.pause(0.001)
  67          plt.show(block=self.blocking)
  68  
  69      def project_plot_predictions(self, price_predicted, test_data):
  70          print("plotting predictions")
  71          plt.figure(figsize=(14, 5))
  72          plt.plot(price_predicted[self.stock_ticker + '_predicted'], color='red', label='Predicted [' + self.short_name + '] price')
  73          plt.plot(test_data.Close, color='green', label='Actual [' + self.short_name + '] price')
  74          plt.xlabel('Time')
  75          plt.ylabel('Price [' + self.currency + ']')
  76          plt.legend()
  77          plt.title('Prediction')
  78          plt.savefig(os.path.join(self.project_folder, self.short_name.strip().replace('.', '') + '_prediction.png'))
  79          plt.pause(0.001)
  80          plt.show(block=self.blocking)
  81