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Merge pull request #3127 from orehunt/max_drawdown_fix_db_plot 

use equality instead of index for row lookups
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Matthias 2020-04-06 20:10:23 +02:00 committed by GitHub
parent 4a85422ce0 20abb379aa
commit 9387585756
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2 changed files with 19 additions and 7 deletions
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13
freqtrade/data/btanalysis.py
View File

@ -151,13 +151,20 @@ def load_trades(source: str, db_url: str, exportfilename: Path,
return load_backtest_data(exportfilename)
def extract_trades_of_period(dataframe: pd.DataFrame, trades: pd.DataFrame) -> pd.DataFrame:
def extract_trades_of_period(dataframe: pd.DataFrame, trades: pd.DataFrame,
date_index=False) -> pd.DataFrame:
"""
Compare trades and backtested pair DataFrames to get trades performed on backtested period
:return: the DataFrame of a trades of period
"""
trades = trades.loc[(trades['open_time'] >= dataframe.iloc[0]['date']) &
(trades['close_time'] <= dataframe.iloc[-1]['date'])]
if date_index:
trades_start = dataframe.index[0]
trades_stop = dataframe.index[-1]
else:
trades_start = dataframe.iloc[0]['date']
trades_stop = dataframe.iloc[-1]['date']
trades = trades.loc[(trades['open_time'] >= trades_start) &
(trades['close_time'] <= trades_stop)]
return trades

13
freqtrade/plot/plotting.py
View File

@ -10,6 +10,7 @@ from freqtrade.data.btanalysis import (calculate_max_drawdown,
create_cum_profit,
extract_trades_of_period, load_trades)
from freqtrade.data.converter import trim_dataframe
from freqtrade.exchange import timeframe_to_prev_date
from freqtrade.data.history import load_data
from freqtrade.misc import pair_to_filename
from freqtrade.resolvers import StrategyResolver
@ -122,7 +123,8 @@ def add_profit(fig, row, data: pd.DataFrame, column: str, name: str) -> make_sub
return fig
def add_max_drawdown(fig, row, trades: pd.DataFrame, df_comb: pd.DataFrame) -> make_subplots:
def add_max_drawdown(fig, row, trades: pd.DataFrame, df_comb: pd.DataFrame,
timeframe: str) -> make_subplots:
"""
Add scatter points indicating max drawdown
"""
@ -132,8 +134,8 @@ def add_max_drawdown(fig, row, trades: pd.DataFrame, df_comb: pd.DataFrame) -> m
drawdown = go.Scatter(
x=[highdate, lowdate],
y=[
df_comb.loc[highdate, 'cum_profit'],
df_comb.loc[lowdate, 'cum_profit'],
df_comb.loc[timeframe_to_prev_date(timeframe, highdate), 'cum_profit'],
df_comb.loc[timeframe_to_prev_date(timeframe, lowdate), 'cum_profit'],
],
mode='markers',
name=f"Max drawdown {max_drawdown * 100:.2f}%",
@ -383,6 +385,9 @@ def generate_profit_graph(pairs: str, data: Dict[str, pd.DataFrame],
# Combine close-values for all pairs, rename columns to "pair"
df_comb = combine_dataframes_with_mean(data, "close")
# Trim trades to available OHLCV data
trades = extract_trades_of_period(df_comb, trades, date_index=True)
# Add combined cumulative profit
df_comb = create_cum_profit(df_comb, trades, 'cum_profit', timeframe)
@ -405,7 +410,7 @@ def generate_profit_graph(pairs: str, data: Dict[str, pd.DataFrame],
fig.add_trace(avgclose, 1, 1)
fig = add_profit(fig, 2, df_comb, 'cum_profit', 'Profit')
fig = add_max_drawdown(fig, 2, trades, df_comb)
fig = add_max_drawdown(fig, 2, trades, df_comb, timeframe)
for pair in pairs:
profit_col = f'cum_profit_{pair}'