Files
catalyst/catalyst/exchange/live_graph_clock.py
T

234 lines
6.8 KiB
Python

import pandas as pd
from catalyst.gens.sim_engine import (
BAR,
SESSION_START
)
from logbook import Logger
from catalyst.constants import LOG_LEVEL
from catalyst.exchange.exchange_errors import \
MismatchingBaseCurrenciesExchanges
log = Logger('LiveGraphClock', level=LOG_LEVEL)
class LiveGraphClock(object):
"""Realtime clock for live trading.
This class is a drop-in replacement for
:class:`zipline.gens.sim_engine.MinuteSimulationClock`.
This mixes the clock with a live graph.
Notes
-----
This seemingly awkward approach allows us to run the program using a single
thread. This is important because Matplotlib does not play nice with
multi-threaded environments. Zipline probably does not either.
Matplotlib has a pause() method which is a wrapper around time.sleep()
used in the SimpleClock. The key difference is that users
can still interact with the chart during the pause cycles. This is
what enables us to keep a single thread. This is also why we are not using
the 'animate' callback of Matplotlib. We need to direct access to the
__iter__ method in order to yield events to Zipline.
The :param:`time_skew` parameter represents the time difference between
the exchange and the live trading machine's clock. It's not used currently.
"""
def __init__(self, sessions, context, time_skew=pd.Timedelta('0s')):
global mdates, plt # TODO: Could be cleaner
import matplotlib.dates as mdates
from matplotlib import pyplot as plt
from matplotlib import style
self.sessions = sessions
self.time_skew = time_skew
self._last_emit = None
self._before_trading_start_bar_yielded = True
self.context = context
self.fmt = mdates.DateFormatter('%Y-%m-%d %H:%M')
style.use('dark_background')
fig = plt.figure()
fig.canvas.set_window_title('Enigma Catalyst: {}'.format(
self.context.algo_namespace))
self.ax_pnl = fig.add_subplot(311)
self.ax_custom_signals = fig.add_subplot(312, sharex=self.ax_pnl)
self.ax_exposure = fig.add_subplot(313, sharex=self.ax_pnl)
if len(context.minute_stats) > 0:
self.draw_pnl()
self.draw_custom_signals()
self.draw_exposure()
# rotates and right aligns the x labels, and moves the bottom of the
# axes up to make room for them
fig.autofmt_xdate()
fig.subplots_adjust(hspace=0.5)
plt.tight_layout()
plt.ion()
plt.show()
def format_ax(self, ax):
"""
Trying to assign reasonable parameters to the time axis.
Parameters
----------
ax:
"""
# TODO: room for improvement
ax.xaxis.set_major_locator(mdates.DayLocator(interval=1))
ax.xaxis.set_major_formatter(self.fmt)
locator = mdates.HourLocator(interval=4)
locator.MAXTICKS = 5000
ax.xaxis.set_minor_locator(locator)
datemin = pd.Timestamp.utcnow()
ax.set_xlim(datemin)
ax.grid(True)
def set_legend(self, ax):
"""
Set legend on the chart.
Parameters
----------
ax
"""
ax.legend(loc='upper left', ncol=1, fontsize=10, numpoints=1)
def draw_pnl(self):
"""
Draw p&l line on the chart.
"""
ax = self.ax_pnl
df = self.context.pnl_stats
ax.clear()
ax.set_title('Performance')
ax.plot(df.index, df['performance'], '-',
color='green',
linewidth=1.0,
label='Performance'
)
def perc(val):
return '{:2f}'.format(val)
ax.format_ydata = perc
self.set_legend(ax)
self.format_ax(ax)
def draw_custom_signals(self):
"""
Draw custom signals on the chart.
"""
ax = self.ax_custom_signals
df = self.context.custom_signals_stats
colors = ['blue', 'green', 'red', 'black', 'orange', 'yellow', 'pink']
ax.clear()
ax.set_title('Custom Signals')
for index, column in enumerate(df.columns.values.tolist()):
ax.plot(df.index, df[column], '-',
color=colors[index],
linewidth=1.0,
label=column
)
self.set_legend(ax)
self.format_ax(ax)
def draw_exposure(self):
"""
Draw exposure line on the chart.
"""
ax = self.ax_exposure
context = self.context
df = context.exposure_stats
# TODO: list exchanges in graph
base_currency = None
positions = []
for exchange_name in context.exchanges:
exchange = context.exchanges[exchange_name]
if not base_currency:
base_currency = exchange.base_currency
elif base_currency != exchange.base_currency:
raise MismatchingBaseCurrenciesExchanges(
base_currency=base_currency,
exchange_name=exchange.name,
exchange_currency=exchange.base_currency
)
positions += exchange.portfolio.positions
ax.clear()
ax.set_title('Exposure')
ax.plot(df.index, df['base_currency'], '-',
color='green',
linewidth=1.0,
label='Base Currency: {}'.format(base_currency.upper())
)
symbols = []
for position in positions:
symbols.append(position.symbol)
ax.plot(df.index, df['long_exposure'], '-',
color='blue',
linewidth=1.0,
label='Long Exposure: {}'.format(', '.join(symbols).upper()))
self.set_legend(ax)
self.format_ax(ax)
def __iter__(self):
yield pd.Timestamp.utcnow(), SESSION_START
while True:
current_time = pd.Timestamp.utcnow()
current_minute = current_time.floor('1 min')
if self._last_emit is None or current_minute > self._last_emit:
log.debug('emitting minutely bar: {}'.format(current_minute))
self._last_emit = current_minute
yield current_minute, BAR
try:
self.draw_pnl()
self.draw_custom_signals()
self.draw_exposure()
plt.draw()
except Exception as e:
log.warn('Unable to update the graph: {}'.format(e))
else:
# I can't use the "animate" reactive approach here because
# I need to yield from the main loop.
# Workaround: https://stackoverflow.com/a/33050617/814633
plt.pause(1)