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This commit is contained in:
Jérôme Delacotte
2025-05-06 13:13:58 +02:00
parent 014289c2a0
commit 0bb7271121
3 changed files with 40 additions and 3 deletions
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6
Zeus_11.py
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@@ -369,7 +369,7 @@ class Zeus_11(IStrategy):
dataframe["percent48"] = (dataframe["close"] - dataframe["open"].shift(48)) / dataframe["open"].shift(48)
# print(metadata['pair'])
dataframe['rsi'] = talib.RSI(dataframe['close'], length=14)
dataframe['rsi'] = talib.RSI(dataframe['close'], timeperiod=14)
# Bollinger Bands
bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
@@ -436,7 +436,7 @@ class Zeus_11(IStrategy):
# informative["max_profit"] = dataframe["informative"].rolling(n_candles).max()
# informative["profit_hit"] = dataframe["informative"] >= informative["close"] * (1 + x_percent)
#
informative['rsi'] = talib.RSI(informative['close'], length=7)
informative['rsi'] = talib.RSI(informative['close'], timeperiod=7)
informative['rsi_diff'] = informative['rsi'] - informative['rsi'].shift(1)
informative['sma5'] = talib.SMA(informative, timeperiod=5)
@@ -445,7 +445,7 @@ class Zeus_11(IStrategy):
################### INFORMATIVE 1d
informative = self.dp.get_pair_dataframe(pair=metadata['pair'], timeframe="1d")
informative['rsi'] = talib.RSI(informative['close'], length=7)
informative['rsi'] = talib.RSI(informative['close'], timeperiod=7)
informative['rsi_diff'] = informative['rsi'] - informative['rsi'].shift(1)
informative['sma5'] = talib.SMA(informative, timeperiod=5)
informative['sma5_pct'] = 100 * (informative['sma5'] - informative['sma5'].shift(1)) / informative['sma5']

34
tools/graph.py Normal file
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@@ -0,0 +1,34 @@
import pandas as pd
import matplotlib.pyplot as plt
# Charger les fichiers
signals = pd.read_pickle('backtest-result-2025-04-06_21-30-24_signals.pkl')
exited = pd.read_pickle('backtest-result-2025-04-06_21-30-24_exited.pkl')
rejected = pd.read_pickle('backtest-result-2025-04-06_21-30-24_rejected.pkl') # facultatif
# Choisir un marché pour le graphique (ex : BTC/USDT)
pair = 'BTC/USDT'
df_signals = signals[signals['pair'] == pair]
df_exited = exited[exited['pair'] == pair]
# Charger les données de prix si besoin (par ex. OHLCV depuis Freqtrade)
# Ici on suppose que vous avez une DataFrame de prix : price_df avec ['date', 'close']
price_df = df_signals[['date', 'price']].rename(columns={'price': 'close'}).copy()
price_df.set_index('date', inplace=True)
# Affichage
plt.figure(figsize=(14, 6))
plt.plot(price_df.index, price_df['close'], label='Prix', color='gray')
# Ajouter les points d'entrée
plt.scatter(df_signals['date'], df_signals['price'], color='green', label='Signal', marker='^')
# Ajouter les points de sortie
plt.scatter(df_exited['exit_date'], df_exited['exit_price'], color='red', label='Sortie', marker='v')
plt.title(f"Graphique avec signaux pour {pair}")
plt.xlabel("Date")
plt.ylabel("Prix")
plt.legend()
plt.grid(True)
plt.tight_layout()
plt.show()

3
tools/test_pkl.py Normal file
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@@ -0,0 +1,3 @@
import pandas as pd
df = pd.read_pickle("backtest-result-2025-04-06_21-30-24_signals.pkl")
print(df.head())