def plot_percentiles(self, *args, **kwargs):
out = super().plot_percentiles(*args, **kwargs)
a = out[1]
def num2month(pos, num):
month = [
'', 'J', 'F', 'M', 'A', 'M', 'J', 'J', 'A', 'S', 'O', 'N', 'D',
'', ''
]
return month[num]
if self.frequency == 'M':
a.xaxis.set_major_formatter(_FuncFormatter(num2month))
a.set_xlim(0.5, 12.5)
a.set_xlabel('Month of year')
return out
def earnings(returns, start_balance=1e5, mode="comp",
grayscale=False, figsize=(10, 6),
title='Portfolio Earnings',
fontname='Arial', lw=1.5,
subtitle=True, savefig=None, show=True):
colors = _GRAYSCALE_COLORS if grayscale else _FLATUI_COLORS
alpha = .5 if grayscale else .8
returns = _utils.make_portfolio(returns, start_balance, mode)
if figsize is None:
size = list(_plt.gcf().get_size_inches())
figsize = (size[0], size[0]*.55)
fig, ax = _plt.subplots(figsize=figsize)
fig.suptitle(title, fontsize=14, y=.995,
fontname=fontname, fontweight='bold', color='black')
if subtitle:
ax.set_title("\n%s - %s ; P&L: %s (%s) " % (
returns.index.date[1:2][0].strftime('%e %b \'%y'),
returns.index.date[-1:][0].strftime('%e %b \'%y'),
_utils._score_str("${:,}".format(
round(returns.values[-1]-returns.values[0], 2))),
_utils._score_str("{:,}%".format(
round((returns.values[-1]/returns.values[0]-1)*100, 2)))
), fontsize=12, color='gray')
mx = returns.max()
returns_max = returns[returns == mx]
ix = returns_max[~_np.isnan(returns_max)].index[0]
returns_max = _np.where(returns.index == ix, mx, _np.nan)
ax.plot(returns.index, returns_max, marker='o', lw=0,
alpha=alpha, markersize=12, color=colors[0])
ax.plot(returns.index, returns, color=colors[1],
lw=1 if grayscale else lw)
ax.set_ylabel('Value of ${:,.0f}'.format(start_balance),
fontname=fontname, fontweight='bold', fontsize=12)
ax.yaxis.set_major_formatter(_FuncFormatter(_core.format_cur_axis))
ax.yaxis.set_label_coords(-.1, .5)
fig.set_facecolor('white')
ax.set_facecolor('white')
fig.autofmt_xdate()
try:
_plt.subplots_adjust(hspace=0)
except Exception:
pass
try:
fig.tight_layout(w_pad=0, h_pad=0)
except Exception:
pass
if savefig:
if isinstance(savefig, dict):
_plt.savefig(**savefig)
else:
_plt.savefig(savefig)
if show:
_plt.show(fig)
_plt.close()
if not show:
return fig
def plot_returns_bars(returns,
benchmark=None,
returns_label="Strategy",
hline=None,
hlw=None,
hlcolor="red",
hllabel="",
resample="A",
title="Returns",
match_volatility=False,
log_scale=False,
figsize=(10, 6),
grayscale=False,
fontname='Arial',
ylabel=True,
subtitle=True,
savefig=None,
show=True):
if match_volatility and benchmark is None:
raise ValueError('match_volatility requires passing of ' 'benchmark.')
if match_volatility and benchmark is not None:
bmark_vol = benchmark.loc[returns.index].std()
returns = (returns / returns.std()) * bmark_vol
# ---------------
colors, _, _ = _get_colors(grayscale)
df = _pd.DataFrame(index=returns.index, data={returns_label: returns})
if isinstance(benchmark, _pd.Series):
df['Benchmark'] = benchmark[benchmark.index.isin(returns.index)]
df = df[['Benchmark', returns_label]]
df = df.dropna()
if resample is not None:
df = df.resample(resample).apply(_stats.comp).resample(resample).last()
# ---------------
fig, ax = _plt.subplots(figsize=figsize)
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['left'].set_visible(False)
# use a more precise date string for the x axis locations in the toolbar
fig.suptitle(title + "\n",
y=.99,
fontweight="bold",
fontname=fontname,
fontsize=14,
color="black")
if subtitle:
ax.set_title("\n%s - %s " %
(df.index.date[:1][0].strftime('%Y'),
df.index.date[-1:][0].strftime('%Y')),
fontsize=12,
color='gray')
if benchmark is None:
colors = colors[1:]
df.plot(kind='bar', ax=ax, color=colors)
fig.set_facecolor('white')
ax.set_facecolor('white')
try:
ax.set_xticklabels(df.index.year)
years = sorted(list(set(df.index.year)))
except AttributeError:
ax.set_xticklabels(df.index)
years = sorted(list(set(df.index)))
# ax.fmt_xdata = _mdates.DateFormatter('%Y-%m-%d')
# years = sorted(list(set(df.index.year)))
if len(years) > 10:
mod = int(len(years) / 10)
_plt.xticks(
_np.arange(len(years)),
[str(year) if not i % mod else '' for i, year in enumerate(years)])
# rotate and align the tick labels so they look better
fig.autofmt_xdate()
if hline:
if grayscale:
hlcolor = 'gray'
ax.axhline(hline,
ls="--",
lw=hlw,
color=hlcolor,
label=hllabel,
zorder=2)
ax.axhline(0, ls="--", lw=1, color="#000000", zorder=2)
if isinstance(benchmark, _pd.Series) or hline:
ax.legend(fontsize=12)
_plt.yscale("symlog" if log_scale else "linear")
ax.set_xlabel('')
if ylabel:
ax.set_ylabel("Returns",
fontname=fontname,
fontweight='bold',
fontsize=12,
color="black")
ax.yaxis.set_label_coords(-.1, .5)
ax.yaxis.set_major_formatter(_FuncFormatter(format_pct_axis))
try:
_plt.subplots_adjust(hspace=0, bottom=0, top=1)
except Exception:
pass
try:
fig.tight_layout()
except Exception:
pass
if savefig:
if isinstance(savefig, dict):
_plt.savefig(**savefig)
else:
_plt.savefig(savefig)
if show:
_plt.show(block=False)
_plt.close()
if not show:
return fig
return None
def plot_longest_drawdowns(returns,
periods=5,
lw=1.5,
fontname='Arial',
grayscale=False,
log_scale=False,
figsize=(10, 6),
ylabel=True,
subtitle=True,
compounded=True,
savefig=None,
show=True):
colors = ['#348dc1', '#003366', 'red']
if grayscale:
colors = ['#000000'] * 3
dd = _stats.to_drawdown_series(returns.fillna(0))
dddf = _stats.drawdown_details(dd)
longest_dd = dddf.sort_values(by='days', ascending=False,
kind='mergesort')[:periods]
fig, ax = _plt.subplots(figsize=figsize)
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['left'].set_visible(False)
fig.suptitle("Worst %.0f Drawdown Periods\n" % periods,
y=.99,
fontweight="bold",
fontname=fontname,
fontsize=14,
color="black")
if subtitle:
ax.set_title("\n%s - %s " %
(returns.index.date[:1][0].strftime('%e %b \'%y'),
returns.index.date[-1:][0].strftime('%e %b \'%y')),
fontsize=12,
color='gray')
fig.set_facecolor('white')
ax.set_facecolor('white')
series = _stats.compsum(returns) if compounded else returns.cumsum()
ax.plot(series, lw=lw, label="Backtest", color=colors[0])
highlight = 'black' if grayscale else 'red'
for _, row in longest_dd.iterrows():
ax.axvspan(*_mdates.datestr2num([str(row['start']),
str(row['end'])]),
color=highlight,
alpha=.1)
# rotate and align the tick labels so they look better
fig.autofmt_xdate()
# use a more precise date string for the x axis locations in the toolbar
ax.fmt_xdata = _mdates.DateFormatter('%Y-%m-%d')
ax.axhline(0, ls="--", lw=1, color="#000000", zorder=2)
_plt.yscale("symlog" if log_scale else "linear")
if ylabel:
ax.set_ylabel("Cumulative Returns",
fontname=fontname,
fontweight='bold',
fontsize=12,
color="black")
ax.yaxis.set_label_coords(-.1, .5)
ax.yaxis.set_major_formatter(_FuncFormatter(format_pct_axis))
# ax.yaxis.set_major_formatter(_plt.FuncFormatter(
# lambda x, loc: "{:,}%".format(int(x*100))))
fig.autofmt_xdate()
try:
_plt.subplots_adjust(hspace=0, bottom=0, top=1)
except Exception:
pass
try:
fig.tight_layout()
except Exception:
pass
if savefig:
if isinstance(savefig, dict):
_plt.savefig(**savefig)
else:
_plt.savefig(savefig)
if show:
_plt.show(block=False)
_plt.close()
if not show:
return fig
return None
def plot_timeseries(returns,
benchmark=None,
title="Returns",
compound=False,
cumulative=True,
fill=False,
returns_label="Strategy",
hline=None,
hlw=None,
hlcolor="red",
hllabel="",
percent=True,
match_volatility=False,
log_scale=False,
resample=None,
lw=1.5,
figsize=(10, 6),
ylabel="",
grayscale=False,
fontname="Arial",
subtitle=True,
savefig=None,
show=True):
colors, ls, alpha = _get_colors(grayscale)
returns.fillna(0, inplace=True)
if isinstance(benchmark, _pd.Series):
benchmark.fillna(0, inplace=True)
if match_volatility and benchmark is None:
raise ValueError('match_volatility requires passing of ' 'benchmark.')
if match_volatility and benchmark is not None:
bmark_vol = benchmark.std()
returns = (returns / returns.std()) * bmark_vol
# ---------------
if compound is True:
if cumulative:
returns = _stats.compsum(returns)
if isinstance(benchmark, _pd.Series):
benchmark = _stats.compsum(benchmark)
else:
returns = returns.cumsum()
if isinstance(benchmark, _pd.Series):
benchmark = benchmark.cumsum()
if resample:
returns = returns.resample(resample)
returns = returns.last() if compound is True else returns.sum()
if isinstance(benchmark, _pd.Series):
benchmark = benchmark.resample(resample)
benchmark = benchmark.last(
) if compound is True else benchmark.sum()
# ---------------
fig, ax = _plt.subplots(figsize=figsize)
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['left'].set_visible(False)
fig.suptitle(title + "\n",
y=.99,
fontweight="bold",
fontname=fontname,
fontsize=14,
color="black")
if subtitle:
ax.set_title("\n%s - %s " %
(returns.index.date[:1][0].strftime('%e %b \'%y'),
returns.index.date[-1:][0].strftime('%e %b \'%y')),
fontsize=12,
color='gray')
fig.set_facecolor('white')
ax.set_facecolor('white')
if isinstance(benchmark, _pd.Series):
ax.plot(benchmark, lw=lw, ls=ls, label="Benchmark", color=colors[0])
alpha = .25 if grayscale else 1
ax.plot(returns, lw=lw, label=returns_label, color=colors[1], alpha=alpha)
if fill:
ax.fill_between(returns.index, 0, returns, color=colors[1], alpha=.25)
# rotate and align the tick labels so they look better
fig.autofmt_xdate()
# use a more precise date string for the x axis locations in the toolbar
# ax.fmt_xdata = _mdates.DateFormatter('%Y-%m-%d')
if hline:
if grayscale:
hlcolor = 'black'
ax.axhline(hline,
ls="--",
lw=hlw,
color=hlcolor,
label=hllabel,
zorder=2)
ax.axhline(0, ls="-", lw=1, color='gray', zorder=1)
ax.axhline(0,
ls="--",
lw=1,
color='white' if grayscale else 'black',
zorder=2)
if isinstance(benchmark, _pd.Series) or hline:
ax.legend(fontsize=12)
_plt.yscale("symlog" if log_scale else "linear")
if percent:
ax.yaxis.set_major_formatter(_FuncFormatter(format_pct_axis))
# ax.yaxis.set_major_formatter(_plt.FuncFormatter(
# lambda x, loc: "{:,}%".format(int(x*100))))
ax.set_xlabel('')
if ylabel:
ax.set_ylabel(ylabel,
fontname=fontname,
fontweight='bold',
fontsize=12,
color="black")
ax.yaxis.set_label_coords(-.1, .5)
try:
_plt.subplots_adjust(hspace=0, bottom=0, top=1)
except Exception:
pass
try:
fig.tight_layout()
except Exception:
pass
if savefig:
if isinstance(savefig, dict):
_plt.savefig(**savefig)
else:
_plt.savefig(savefig)
if show:
_plt.show(block=False)
_plt.close()
if not show:
return fig
return None
def plot_longest_drawdowns(returns,
dicclrs,
periods=5,
lw=1.5,
fontname='Avenir Next',
grayscale=False,
log_scale=False,
figsize=(10, 6),
ylabel=True,
subtitle=True,
compounded=True,
savefig=None,
show=True):
#colors = ['#348dc1', '#003366', 'red'] #inially
colors = [dicclrs['arquant'], '#b5583c',
dicclrs['background']] #ARQuant, Brown, Light Peach
if grayscale: colors = ['#000000'] * 3
import matplotlib.pyplot as plt
import matplotlib.dates as _mdates
import quantstats.stats as _stats
from matplotlib.ticker import (FormatStrFormatter as _FormatStrFormatter,
FuncFormatter as _FuncFormatter)
dd = _stats.to_drawdown_series(returns.fillna(0))
dddf = _stats.drawdown_details(dd)
longest_dd = dddf.sort_values(by='days', ascending=False,
kind='mergesort')[:periods]
fig, ax = plt.subplots(figsize=figsize)
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['left'].set_visible(False)
# fig.suptitle("Top %.0f Drawdown Periods\n" %
# periods, y=1.1, x=0.25,
# fontweight="normal", fontname=fontname,
# fontsize=18, color=dicclrs['plotname'])
if subtitle:
# plt.rc('text', usetex=True)
# plt.title(r'\fontsize{30pt}{3em}\selectfont{}{Mean WRFv3.5 LHF\r}{\fontsize{18pt}{3em}\selectfont{}(September 16 - October 30, 2012)}')
plt.title(
"",
loc='left', #Top %.0f Drawdown Periods\n %periods
fontweight="medium",
fontname=fontname,
fontsize=18,
color=dicclrs['plotname'])
dates = " Top %.0f Drawdown Periods | %s - %s " % (
periods, returns.index.date[:1][0].strftime('%e %b \'%y'),
returns.index.date[-1:][0].strftime('%e %b \'%y'))
import json
with open('slide2.txt', 'w') as outfile:
json.dump(dates, outfile)
# plt.title(dates, loc='center')
# plt.text(0.45, 0.97, dates,
# fontdict=dict(fontweight='normal', fontname=fontname,
# fontsize=14, color=dicclrs['dates']),
# transform=fig.transFigure
# )
#Plot the line
fig.set_facecolor('white')
ax.set_facecolor('white')
series = _stats.compsum(returns) if compounded else returns.cumsum()
ax.plot(series, lw=lw, label="Backtest", color=colors[0])
#PLot spans
highlight = 'black' if grayscale else dicclrs[
'background'] # it was initially 'red'
for _, row in longest_dd.iterrows():
ax.axvspan(*_mdates.datestr2num([str(row['start']),
str(row['end'])]),
color=highlight,
alpha=.5)
## Horizontal line for 0%
ax.axhline(0, ls="-", lw=1, color="#000000", zorder=2)
## X -axis
# rotate and align the tick labels so they look better
# fig.autofmt_xdate()
fig.autofmt_xdate(bottom=0.2, rotation=0, ha='center', which=None)
# use a more precise date string for the x axis locations in the toolbar
ax.fmt_xdata = _mdates.DateFormatter('%Y-%m-%d')
ax.xaxis.set_tick_params(labelsize=8, color=dicclrs['dates'])
## Y -axis
plt.yscale("symlog" if log_scale else "linear")
if ylabel:
ax.set_ylabel("Cumulative Returns",
fontname=fontname,
fontweight='medium',
fontsize=12,
color="black")
ax.yaxis.set_label_coords(-.075, .5)
ax.yaxis.set_major_formatter(_FuncFormatter(format_pct_axis))
# ax.yaxis.set_major_formatter(plt.FuncFormatter(
# lambda x, loc: "{:,}%".format(int(x*100))))
ax.yaxis.set_tick_params(labelsize=8)
try:
plt.subplots_adjust(hspace=0, bottom=0, top=1)
except Exception:
pass
try:
fig.tight_layout()
except Exception:
pass
if savefig:
if isinstance(savefig, dict):
plt.savefig(**savefig, dpi=300)
else:
plt.savefig(savefig, dpi=300)
if show:
plt.show(block=False)
plt.close()
if not show:
return fig
return None
'''
from __future__ import division
from . import _np
from . import _signal
import scipy.constants as _const
from matplotlib import pyplot as _plt
_plt.ioff()
from matplotlib.ticker import FuncFormatter as _FuncFormatter
from matplotlib.widgets import Cursor as _Cursor
def _seconds_formatter(t, pos):
'''Assume that t is in seconds'''
return '%02d:%02d' % (t // 60, t % 60)
_x_axis_formatter = _FuncFormatter(_seconds_formatter)
_line_props = [{'color': '0'}, {'color': '0.5'}]
#detect screen resolution
import Tkinter as _Tk
_root = _Tk.Tk()
_res = (_root.winfo_screenwidth() / float(_root.winfo_screenmmwidth())
* 1000 * _const.inch)
_root.destroy()
class plotEEG:
def __init__(self, signals, ylabels, t, t_res=30, title = False):
"""Function to Plot EEG-Signals in of several channels
Def: PlotEEG(signals, ylabels, t, t_res, title = False)
Interaction:
from . import _np
from . import _signal
import scipy.constants as _const
from matplotlib import pyplot as _plt
_plt.ioff()
from matplotlib.ticker import FuncFormatter as _FuncFormatter
from matplotlib.widgets import Cursor as _Cursor
def _seconds_formatter(t, pos):
'''Assume that t is in seconds'''
return '%02d:%02d' % (t // 60, t % 60)
_x_axis_formatter = _FuncFormatter(_seconds_formatter)
_line_props = [{'color': 'k'}, {'color': 'r'}]
#detect screen resolution
import Tkinter as _Tk
_root = _Tk.Tk()
_res = (_root.winfo_screenwidth() / float(_root.winfo_screenmmwidth()) * 1000 *
_const.inch)
_root.destroy()
class plotEEG:
def __init__(self, signals, ylabels, t, t_res=30, title=False):
"""Function to Plot EEG-Signals in of several channels
Def: PlotEEG(signals, ylabels, t, t_res, title = False)
