stock_prediction_plotter.py

# Copyright 2020-2024 Jordi Corbilla. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
import os
import matplotlib.pyplot as plt


class Plotter:
    def __init__(self, blocking, project_folder, short_name, currency, stock_ticker):
        self.blocking = blocking
        self.project_folder = project_folder
        self.short_name = short_name
        self.currency = currency
        self.stock_ticker = stock_ticker

    def plot_histogram_data_split(self, training_data, test_data, validation_date):
        print("plotting Data and Histogram")
        plt.figure(figsize=(12, 5))
        plt.plot(training_data.Close, color='green')
        plt.plot(test_data.Close, color='red')
        plt.ylabel('Price [' + self.currency + ']')
        plt.xlabel("Date")
        plt.legend(["Training Data", "Validation Data >= " + validation_date.strftime("%Y-%m-%d")])
        plt.title(self.short_name)
        plt.savefig(os.path.join(self.project_folder, self.short_name.strip().replace('.', '') + '_price.png'))

        fig, ax = plt.subplots()
        training_data.hist(ax=ax)
        fig.savefig(os.path.join(self.project_folder, self.short_name.strip().replace('.', '') + '_hist.png'))

        plt.pause(0.001)
        plt.show(block=self.blocking)

    def plot_loss(self, history):
        print("plotting loss")
        plt.plot(history.history['loss'], label='loss')
        plt.plot(history.history['val_loss'], label='val_loss')
        plt.xlabel('Epoch')
        plt.ylabel('Loss')
        plt.title('Loss/Validation Loss')
        plt.legend(loc='upper right')
        plt.savefig(os.path.join(self.project_folder, 'loss.png'))
        plt.pause(0.001)
        plt.show(block=self.blocking)

    def plot_mse(self, history):
        print("plotting MSE")
        plt.plot(history.history['MSE'], label='MSE')
        plt.plot(history.history['val_MSE'], label='val_MSE')
        plt.xlabel('Epoch')
        plt.ylabel('MSE')
        plt.title('MSE/Validation MSE')
        plt.legend(loc='upper right')
        plt.savefig(os.path.join(self.project_folder, 'MSE.png'))
        plt.pause(0.001)
        plt.show(block=self.blocking)

    def project_plot_predictions(self, price_predicted, test_data):
        print("plotting predictions")
        plt.figure(figsize=(14, 5))
        plt.plot(price_predicted[self.stock_ticker + '_predicted'], color='red', label='Predicted [' + self.short_name + '] price')
        plt.plot(test_data.Close, color='green', label='Actual [' + self.short_name + '] price')
        plt.xlabel('Time')
        plt.ylabel('Price [' + self.currency + ']')
        plt.legend()
        plt.title('Prediction')
        plt.savefig(os.path.join(self.project_folder, self.short_name.strip().replace('.', '') + '_prediction.png'))
        plt.pause(0.001)
        plt.show(block=self.blocking)