def test_plot():
class MockOrder:
def __init__(self, reason_code):
self.reason_code = reason_code
class MockTrade:
def __init__(self, timestamp, qty, price, reason_code):
self.timestamp = timestamp
self.qty = qty
self.price = price
self.order = MockOrder(reason_code)
def __repr__(self):
return f'{self.date} {self.qty} {self.price}'
set_defaults()
timestamps = np.array([
'2018-01-08 15:00:00', '2018-01-09 15:00:00', '2018-01-10 15:00:00',
'2018-01-11 15:00:00'
],
dtype='M8[ns]')
pnl_timestamps = np.array([
'2018-01-08 15:00:00', '2018-01-09 14:00:00', '2018-01-10 15:00:00',
'2018-01-15 15:00:00'
],
dtype='M8[ns]')
positions = (pnl_timestamps, np.array([0., 5., 0., -10.]))
trade_timestamps = np.array(
['2018-01-09 14:00:00', '2018-01-10 15:00:00', '2018-01-15 15:00:00'],
dtype='M8[ns]')
trade_price = [9., 10., 9.5]
trade_qty = [5, -5, -10]
reason_codes = [
ReasonCode.ENTER_LONG, ReasonCode.EXIT_LONG, ReasonCode.ENTER_SHORT
]
trades = [
MockTrade(trade_timestamps[i], trade_qty[i], trade_price[i],
reason_codes[i]) for i, d in enumerate(trade_timestamps)
]
ind_subplot = Subplot([
TimeSeries('slow_support',
timestamps=timestamps,
values=np.array([8.9, 8.9, 9.1, 9.1]),
line_type='--'),
TimeSeries('fast_support',
timestamps=timestamps,
values=np.array([8.9, 9.0, 9.1, 9.2]),
line_type='--'),
TimeSeries('slow_resistance',
timestamps=timestamps,
values=np.array([9.2, 9.2, 9.4, 9.4]),
line_type='--'),
TimeSeries('fast_resistance',
timestamps=timestamps,
values=np.array([9.2, 9.3, 9.4, 9.5]),
line_type='--'),
TimeSeries('secondary_y_test',
timestamps=timestamps,
values=np.array([150, 160, 162, 135]),
line_type='--'),
TradeBarSeries('price',
timestamps=timestamps,
o=np.array([8.9, 9.1, 9.3, 8.6]),
h=np.array([9.0, 9.3, 9.4, 8.7]),
l=np.array([8.8, 9.0, 9.2, 8.4]),
c=np.array([8.95, 9.2, 9.35, 8.5]),
v=np.array([200, 100, 150, 300]),
vwap=np.array([8.9, 9.15, 9.3, 8.55]))
] + trade_sets_by_reason_code(trades),
secondary_y=['secondary_y_test'],
ylabel="Price",
height_ratio=0.3)
sig_subplot = Subplot(TimeSeries('trend',
timestamps=timestamps,
values=np.array([1, 1, -1, -1])),
height_ratio=0.1,
ylabel='Trend')
equity_subplot = Subplot(
TimeSeries('equity',
timestamps=pnl_timestamps,
values=[1.0e6, 1.1e6, 1.2e6, 1.3e6]),
height_ratio=0.1,
ylabel='Equity',
date_lines=[
DateLine(date=np.datetime64('2018-01-09 14:00:00'),
name='drawdown',
color='red'),
DateLine(date=np.datetime64('2018-01-10 15:00:00'), color='red')
],
horizontal_lines=[HorizontalLine(y=0, name='zero', color='green')])
pos_subplot = Subplot(TimeSeries('position',
timestamps=positions[0],
values=positions[1],
plot_type='filled_line'),
height_ratio=0.1,
ylabel='Position')
annual_returns_subplot = Subplot(BucketedValues(
'annual returns', ['2017', '2018'],
bucket_values=[
np.random.normal(0, 1, size=(250, )),
np.random.normal(0, 1, size=(500, ))
]),
height_ratio=0.1,
ylabel='Annual Returns')
x = np.random.rand(10)
y = np.random.rand(10)
xy_subplot = Subplot(XYData('2d test',
x,
y,
plot_type='scatter',
marker='X'),
xlabel='x',
ylabel='y',
height_ratio=0.2,
title='XY Plot')
z = x**2 + y**2
xyz_subplot = Subplot(XYZData(
'3d test',
x,
y,
z,
),
xlabel='x',
ylabel='y',
zlabel='z',
height_ratio=0.3)
subplot_list = [
ind_subplot, sig_subplot, pos_subplot, equity_subplot,
annual_returns_subplot, xy_subplot, xyz_subplot
]
plot = Plot(subplot_list, figsize=(20, 20), title='Plot Test', hspace=0.35)
plot.draw()
plot = Plot(subplot_list, figsize=(20, 20), title='Plot Test', hspace=0.35)
plot.draw()
import matplotlib.dates as mdates
import matplotlib.ticker as mtick
import matplotlib.lines as mlines
import matplotlib.patches as mptch
import matplotlib.gridspec as gridspec
import matplotlib.path as path
from mpl_toolkits import mplot3d
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.cm as cm
from scipy.interpolate import griddata
from mpl_toolkits.axes_grid1 import make_axes_locatable
from IPython.display import display
from pyqstrat.pq_utils import set_defaults, ReasonCode, series_to_array, strtup2date, has_display, resample_ts, resample_trade_bars
set_defaults()
_VERBOSE = False
class DateFormatter(mtick.Formatter):
'''
Formats timestamps on plot axes. See matplotlib Formatter
'''
def __init__(self, timestamps, fmt):
self.timestamps = timestamps
self.fmt = fmt
def __call__(self, x, pos=0):
'Return the label for time x at position pos'
ind = int(np.round(x))