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Plots and hyperopt

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This commit is contained in:
Nicolas Papp 2022-04-11 16:41:48 -03:00
parent 178240aa6c
commit c8e4687833
3 changed files with 34 additions and 14 deletions
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3
freqtrade/data/btanalysis.py
View File

@ -445,6 +445,9 @@ def _calc_drawdown_series(profit_results: pd.DataFrame, *, date_col: str, value_
cumulative_balance = starting_balance + max_drawdown_df['cumulative']
max_balance = starting_balance + max_drawdown_df['high_value']
max_drawdown_df['drawdown_relative'] = ((max_balance - cumulative_balance) / max_balance)
else:
# This is not completely accurate,
max_drawdown_df['drawdown_relative'] = ((max_drawdown_df['high_value'] - max_drawdown_df['cumulative']) / max_drawdown_df['high_value'])
return max_drawdown_df

44
freqtrade/plot/plotting.py
View File

@ -1,6 +1,7 @@
import logging
from pathlib import Path
from typing import Any, Dict, List, Optional
from numpy import number
import pandas as pd
@ -158,12 +159,12 @@ def add_profit(fig, row, data: pd.DataFrame, column: str, name: str) -> make_sub
def add_max_drawdown(fig, row, trades: pd.DataFrame, df_comb: pd.DataFrame,
timeframe: str) -> make_subplots:
timeframe: str, starting_balance: number) -> make_subplots:
"""
Add scatter points indicating max drawdown
"""
try:
_, highdate, lowdate, _, _, max_drawdown = calculate_max_drawdown(trades)
_, highdate, lowdate, _, _, max_drawdown = calculate_max_drawdown(trades, starting_balance=starting_balance)
drawdown = go.Scatter(
x=[highdate, lowdate],
@ -188,22 +189,33 @@ def add_max_drawdown(fig, row, trades: pd.DataFrame, df_comb: pd.DataFrame,
return fig
def add_underwater(fig, row, trades: pd.DataFrame) -> make_subplots:
def add_underwater(fig, row, trades: pd.DataFrame, starting_balance: number) -> make_subplots:
"""
Add underwater plot
Add underwater plots
"""
try:
underwater = calculate_underwater(trades, value_col="profit_abs")
underwater = calculate_underwater(trades, value_col="profit_abs", starting_balance=starting_balance)
underwater = go.Scatter(
underwater_plot = go.Scatter(
x=underwater['date'],
y=underwater['drawdown'],
name="Underwater Plot",
fill='tozeroy',
fillcolor='#cc362b',
line={'color': '#cc362b'},
line={'color': '#cc362b'}
)
fig.add_trace(underwater, row, 1)
underwater_plot_relative = go.Scatter(
x=underwater['date'],
y=(-underwater['drawdown_relative']),
name="Underwater Plot (%)",
fill='tozeroy',
fillcolor='green',
line={'color': 'green'}
)
fig.add_trace(underwater_plot, row, 1)
fig.add_trace(underwater_plot_relative, row+1, 1)
except ValueError:
logger.warning("No trades found - not plotting underwater plot")
return fig
@ -506,7 +518,8 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
def generate_profit_graph(pairs: str, data: Dict[str, pd.DataFrame],
trades: pd.DataFrame, timeframe: str, stake_currency: str) -> go.Figure:
trades: pd.DataFrame, timeframe: str, stake_currency: str,
starting_balance: number) -> go.Figure:
# Combine close-values for all pairs, rename columns to "pair"
try:
df_comb = combine_dataframes_with_mean(data, "close")
@ -530,8 +543,8 @@ def generate_profit_graph(pairs: str, data: Dict[str, pd.DataFrame],
name='Avg close price',
)
fig = make_subplots(rows=5, cols=1, shared_xaxes=True,
row_heights=[1, 1, 1, 0.5, 1],
fig = make_subplots(rows=6, cols=1, shared_xaxes=True,
row_heights=[1, 1, 1, 0.5, 0.75, 0.75],
vertical_spacing=0.05,
subplot_titles=[
"AVG Close Price",
@ -539,6 +552,7 @@ def generate_profit_graph(pairs: str, data: Dict[str, pd.DataFrame],
"Profit per pair",
"Parallelism",
"Underwater",
"Relative Drawdown",
])
fig['layout'].update(title="Freqtrade Profit plot")
fig['layout']['yaxis1'].update(title='Price')
@ -546,14 +560,16 @@ def generate_profit_graph(pairs: str, data: Dict[str, pd.DataFrame],
fig['layout']['yaxis3'].update(title=f'Profit {stake_currency}')
fig['layout']['yaxis4'].update(title='Trade count')
fig['layout']['yaxis5'].update(title='Underwater Plot')
fig['layout']['yaxis6'].update(title='Underwater Plot Relative (%)', tickformat=',.2%')
fig['layout']['xaxis']['rangeslider'].update(visible=False)
fig.update_layout(modebar_add=["v1hovermode", "toggleSpikeLines"])
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, timeframe)
fig = add_max_drawdown(fig, 2, trades, df_comb, timeframe, starting_balance)
fig = add_parallelism(fig, 4, trades, timeframe)
fig = add_underwater(fig, 5, trades)
# Two rows consumed
fig = add_underwater(fig, 5, trades, starting_balance)
for pair in pairs:
profit_col = f'cum_profit_{pair}'
@ -668,7 +684,7 @@ def plot_profit(config: Dict[str, Any]) -> None:
# this could be useful to gauge the overall market trend
fig = generate_profit_graph(plot_elements['pairs'], plot_elements['ohlcv'],
trades, config['timeframe'],
config.get('stake_currency', ''))
config.get('stake_currency', ''), config['available_capital'])
store_plot_file(fig, filename='freqtrade-profit-plot.html',
directory=config['user_data_dir'] / 'plot',
auto_open=config.get('plot_auto_open', False))

1
tests/optimize/test_hyperoptloss.py
View File

@ -85,6 +85,7 @@ def test_loss_calculation_has_limited_profit(hyperopt_conf, hyperopt_results) ->
"SharpeHyperOptLoss",
"SharpeHyperOptLossDaily",
"MaxDrawDownHyperOptLoss",
"MaxDrawDownRelativeHyperOptLoss",
"CalmarHyperOptLoss",
"ProfitDrawDownHyperOptLoss",