def net_value_plot(strategy_net_value: pd.Series,
benchmark: pd.Series or None = None,
strategy_name='strategy',
fill=None):
fig = go.Figure()
fig.add_trace(
net_value_line(strategy_net_value / strategy_net_value[0],
name=strategy_name,
fill=fill))
if benchmark is not None:
benchmark_copy = benchmark[
(benchmark.index >= strategy_net_value.index[0])
& (benchmark.index <= strategy_net_value.index[-1])]
fig.add_trace(
net_value_line(benchmark_copy / benchmark_copy[0],
color='#FFCC00',
name='benchmark'))
x_axis = fig.data[0].x
tick_value = [x_axis[i] for i in range(0, len(x_axis), len(x_axis) // 5)]
tick_text = [
x_axis[i][0:10] for i in range(0, len(x_axis),
len(x_axis) // 5)
]
fig.update_xaxes(ticktext=tick_text, tickvals=tick_value)
return fig
def maximum_drawdown_plot(drawdown_percent: pd.Series):
fig = go.Figure()
fig.add_trace(net_value_line(drawdown_percent, color='#73B839', name='underwater', fill='tozeroy'), )
fig.update_layout(
title="Underwater", )
x_axis = fig.data[0].x
tick_value = [x_axis[i] for i in range(0, len(x_axis), len(x_axis) // 5)]
tick_text = [x_axis[i][0:10] for i in range(0, len(x_axis), len(x_axis) // 5)]
fig.update_xaxes(ticktext=tick_text, tickvals=tick_value)
return fig
def entry_and_exit_plot(ohlc_df, traded: pd.DataFrame, symbol: str, ohlc_graph=True, price_key='close', ohlc_key=None,
entrust=False, ta_dict: None or dict = None):
# traded columns:
# code,order_time,order_price,order_qty,order_type,dealt_price,dealt_qty,order_direction,order_status,update_time,
# exchange_order_id,order_id,cash_inflow
subplot_num = 1
if ta_dict is not None:
subplot_num += len([i for i in ta_dict.values() if i is False])
row_heights = [1] * subplot_num
row_heights[0] = 2
fig = make_subplots(
rows=subplot_num, cols=1,
shared_xaxes=True,
vertical_spacing=0.03, row_heights=row_heights
)
# filter out unrelated trade
traded = traded[traded['code'] == symbol]
long = traded[traded['order_direction'] == 'LONG']
short = traded[traded['order_direction'] == 'SHORT']
if ohlc_graph:
candles = candlestick(ohlc_df, ohlc_key=ohlc_key, symbol=symbol)
fig.add_trace(candles, 1, 1)
else:
prices = net_value_line(ohlc_df[price_key], color='#FFA500', name=symbol)
fig.add_trace(prices, 1, 1)
long_dot = entry_exit_dot(long, True)
short_dot = entry_exit_dot(short, False)
fig.add_trace(long_dot, 1, 1)
fig.add_trace(short_dot, 1, 1)
if entrust:
entrust_long = entrust_dot(long, True)
entrust_short = entrust_dot(short, False)
fig.add_trace(entrust_long, 1, 1)
fig.add_trace(entrust_short, 1, 1)
if ta_dict is not None:
subplot_i = 2
for ta, overlap in ta_dict.items():
call_str = ta.replace('inputs', 'ohlc_df')
ta_indicator = eval(call_str)
ta_name = call_str.split('(')[0]
if isinstance(ta_indicator, pd.Series):
index = ta_indicator.index.strftime('%Y/%m/%d %H:%M:%S')
if overlap is True:
if ta_name == 'SAR':
fig.add_trace(sar_graph(ta_indicator, ohlc_df['close']), 1, 1)
else:
fig.add_trace(go.Scatter(x=index, y=ta_indicator, mode='lines', name=call_str), 1, 1)
else:
fig.add_trace(go.Scatter(x=index, y=ta_indicator, mode='lines', name=call_str), subplot_i, 1)
subplot_i += 1
elif isinstance(ta_indicator, pd.DataFrame):
index = ta_indicator.index.strftime('%Y/%m/%d %H:%M:%S')
if overlap is True:
for col in ta_indicator.columns:
fig.add_trace(go.Scatter(x=index, y=ta_indicator[col], mode='lines', name=col), 1, 1)
else:
if ta_name == 'MACD' or ta_name == 'MACDEXT' or ta_name == 'MACDFIX':
fig.add_traces(macd_graph(ta_indicator), [subplot_i] * 3, [1] * 3)
else:
for col in ta_indicator.columns:
fig.add_trace(go.Scatter(x=index, y=ta_indicator[col], mode='lines', name=col), subplot_i,
1)
subplot_i += 1
x_axis = fig.data[0].x
tick_value = [x_axis[i] for i in range(0, len(x_axis), len(x_axis) // 5)]
tick_text = [x_axis[i][0:10] for i in range(0, len(x_axis), len(x_axis) // 5)]
fig.update_xaxes(ticktext=tick_text, tickvals=tick_value)
# fig.update_layout(showlegend=True, xaxis_rangeslider_visible=False)
fig.update_layout(showlegend=True, height=175 * len(fig.data),
yaxis1=dict(autorange=True, fixedrange=False),
yaxis2=dict(autorange=True, fixedrange=False),
xaxis_rangeslider_visible=False, hovermode='x unified'
)
return fig