def __create_sequences(self):
input_sequence = []
output_sequence = []
percent_values = self.__percentage_changes
for start_day in range(len(percent_values) - self.sequence_length - 1):
input_sequence.append(percent_values[start_day: start_day + self.sequence_length])
output_sequence.append(percent_values[start_day + self.sequence_length])
np_input = np.array(input_sequence)
print_shape(np_input, "debug_np_input")
np_output = np.array(output_sequence)
print_shape(np_output, "debug_np_output")
np_input = np.reshape(np_input, (len(np_input), self.sequence_length, 1))
np_output = np.reshape(np_output, (len(np_output), 1))
x_train = np_input[:-self.__days_to_predict]
x_test = np_input[-self.__days_to_predict:]
y_train = np_output[:-self.__days_to_predict]
y_test = np_output[-self.__days_to_predict:]
return x_train, y_train, x_test, y_test
def __create_sequences(self):
input_sequence = []
output_sequence = []
price_values = self.__all_data_grouped_by_date.values
for start_day in range(len(price_values) - self.__sequence_length - 1):
input_sequence.append(price_values[start_day:start_day +
self.__sequence_length])
output_sequence.append(price_values[start_day +
self.__sequence_length])
np_input = np.array(input_sequence)
print_shape(np_input, "debug_np_input")
np_output = np.array(output_sequence)
print_shape(np_output, "debug_np_output")
np_output = np.reshape(np_output, (len(np_output), 1))
x_train = np_input[:-self.__days_to_predict]
x_test = np_input[-self.__days_to_predict:]
y_train = np_output[:-self.__days_to_predict]
y_test = np_output[-self.__days_to_predict:]
x_train = np.reshape(x_train,
(len(x_train) * self.__sequence_length, 1))
x_test = np.reshape(x_test, (len(x_test) * self.__sequence_length, 1))
x_train = self.__min_max_scaler.fit_transform(x_train)
x_test = self.__min_max_scaler.transform(x_test)
y_train = self.__min_max_scaler.transform(y_train)
y_test = self.__min_max_scaler.transform(y_test)
x_train = np.reshape(x_train, (len(x_train) // self.__sequence_length,
self.__sequence_length, 1))
x_test = np.reshape(
x_test,
(len(x_test) // self.__sequence_length, self.__sequence_length, 1))
return x_train, y_train, x_test, y_test
def log_data_shapes(self):
print("Data loaded:")
print_shape(self.x_train, "x_train")
print_shape(self.y_train, "y_train")
print_shape(self.x_test, "x_test")
print_shape(self.y_test, "y_test")