# Copyright 2023, MetaQuotes Ltd.
# https://www.mql5.com

import MetaTrader5 as mt5
import numpy as np
import onnxruntime as ort
import pandas as pd
from sys import argv

if not mt5.initialize():
    print("initialize() failed, error code =",mt5.last_error())
    quit()

# you code here
#
data_path=argv[0]
last_index=data_path.rfind("\\")+1
data_path=data_path[0:last_index]
print("data path to load onnx model",data_path)

eurusd_rates = mt5.copy_rates_from_pos("EURUSD", mt5.TIMEFRAME_H1, 1, 10)
#print(eurusd_rates)
df = pd.DataFrame(eurusd_rates)
X = df[['open', 'high', 'low', 'close']].values
X = np.expand_dims(X, axis=0)
#print(X)

m = X.mean(axis=1, keepdims=True)
#print(m)
s = X.std(axis=1, keepdims=True)
#print(s)
X_norm = (X - m) / s
#print(X_norm)

model_path = data_path+"model2.onnx"
ort_sess = ort.InferenceSession(model_path)
output_names = [out.name for out in ort_sess.get_outputs()]

outputs = ort_sess.run(output_names, {'lstm_input': X_norm.astype(np.float32)})
y_pred_norm = outputs[0]
print("raw output:",y_pred_norm)

# --- y_pred ---{
# y_pred = np.round(y_pred_norm.flatten() * ((s[:, 0, 1] - s[:, 0, 0]) - (s[:, 0, 0] - s[:, 0, 2])) + ((m[:, 0, 1] - m[:, 0, 0]) - (m[:, 0, 0] - m[:, 0, 2])), decimals=5)
# ---
y_pred = np.round(y_pred_norm.flatten(), decimals=5)
# --- y_pred ---}
print("predicted:",y_pred)

mt5.shutdown()