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Update plotting to use entry/exit terminology

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This commit is contained in:
Matthias
2022-07-16 22:28:46 +02:00
parent 9347677c60
commit 05a5ae4fcf
2 changed files with 29 additions and 29 deletions
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22
freqtrade/plot/plotting.py
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@@ -255,18 +255,18 @@ def plot_trades(fig, trades: pd.DataFrame) -> make_subplots:
"""
# Trades can be empty
if trades is not None and len(trades) > 0:
# Create description for sell summarizing the trade
# Create description for exit summarizing the trade
trades['desc'] = trades.apply(
lambda row: f"{row['profit_ratio']:.2%}, " +
(f"{row['enter_tag']}, " if row['enter_tag'] is not None else "") +
f"{row['exit_reason']}, " +
f"{row['trade_duration']} min",
axis=1)
trade_buys = go.Scatter(
trade_entries = go.Scatter(
x=trades["open_date"],
y=trades["open_rate"],
mode='markers',
name='Trade buy',
name='Trade entry',
text=trades["desc"],
marker=dict(
symbol='circle-open',
@@ -277,12 +277,12 @@ def plot_trades(fig, trades: pd.DataFrame) -> make_subplots:
)
)
trade_sells = go.Scatter(
trade_exits = go.Scatter(
x=trades.loc[trades['profit_ratio'] > 0, "close_date"],
y=trades.loc[trades['profit_ratio'] > 0, "close_rate"],
text=trades.loc[trades['profit_ratio'] > 0, "desc"],
mode='markers',
name='Sell - Profit',
name='Exit - Profit',
marker=dict(
symbol='square-open',
size=11,
@@ -290,12 +290,12 @@ def plot_trades(fig, trades: pd.DataFrame) -> make_subplots:
color='green'
)
)
trade_sells_loss = go.Scatter(
trade_exits_loss = go.Scatter(
x=trades.loc[trades['profit_ratio'] <= 0, "close_date"],
y=trades.loc[trades['profit_ratio'] <= 0, "close_rate"],
text=trades.loc[trades['profit_ratio'] <= 0, "desc"],
mode='markers',
name='Sell - Loss',
name='Exit - Loss',
marker=dict(
symbol='square-open',
size=11,
@@ -303,9 +303,9 @@ def plot_trades(fig, trades: pd.DataFrame) -> make_subplots:
color='red'
)
)
fig.add_trace(trade_buys, 1, 1)
fig.add_trace(trade_sells, 1, 1)
fig.add_trace(trade_sells_loss, 1, 1)
fig.add_trace(trade_entries, 1, 1)
fig.add_trace(trade_exits, 1, 1)
fig.add_trace(trade_exits_loss, 1, 1)
else:
logger.warning("No trades found.")
return fig
@@ -444,7 +444,7 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
Generate the graph from the data generated by Backtesting or from DB
Volume will always be ploted in row2, so Row 1 and 3 are to our disposal for custom indicators
:param pair: Pair to Display on the graph
:param data: OHLCV DataFrame containing indicators and buy/sell signals
:param data: OHLCV DataFrame containing indicators and entry/exit signals
:param trades: All trades created
:param indicators1: List containing Main plot indicators
:param indicators2: List containing Sub plot indicators