def countdown(ax, signal):
bars = [[b['dt'].to_pydatetime(), b['open'],
b['close'], b['high'], b['low']] for b in signal['bars']]
finance.plot_day_summary(ax, bars)
for i, pos in enumerate(signal['signals']):
label_bar(ax, i, bars[pos])
return bars
def setup(ax, signal):
bars = signal['flip']['bars'] + signal['bars']
bars = [[b['dt'].to_pydatetime(), b['open'],
b['close'], b['high'], b['low']] for b in bars]
finance.plot_day_summary(ax, bars)
flip_end = len(signal['flip']['bars']) - 1
label_bar(ax, 'X', bars[0], True)
label_bar(ax, 'Y', bars[1], True)
label_bar(ax, "X'", bars[flip_end - 1], True,)
label_bar(ax, "Y'", bars[flip_end], True)
for i, bar in enumerate(bars[flip_end:], 1):
label_bar(ax, i, bar)
return bars
plot_day_summary, candlestick2
date1 = (2013, 10, 20)
date2 = (2013, 11, 10)
ticker = 'IBM'
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = DayLocator() # minor ticks on the days
weekFormatter = DateFormatter('%b %d') # e.g., Jan 12
dayFormatter = DateFormatter('%d') # e.g., 12
quotes = quotes_historical_yahoo(ticker, date1, date2)
if len(quotes) == 0:
raise SystemExit
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
ax.xaxis.set_minor_formatter(dayFormatter)
plot_day_summary(ax, quotes, ticksize=3)
candlestick(ax, quotes, width=0.6)
ax.xaxis_date()
ax.autoscale_view()
plt.setp(plt.gca().get_xticklabels(), rotation=80, horizontalalignment='right')
plt.figtext(0.35, 0.45, '10/29: Open, High, Low, Close')
plt.figtext(0.35, 0.42, ' 177.62, 182.32, 177.50, 182.12')
plt.figtext(0.35, 0.32, 'Black ==> Close > Open ')
plt.figtext(0.35, 0.28, 'Red ==> Close < Open ')
plt.title('Candlesticks for IBM from 10/20/2013 to 11/10/2013')
plt.ylabel('Price')
plt.xlabel('Date')
plt.show()
plt.figtext(0.9, 0.075, "$x$")
plt.figtext(0.075, 0.9, "$f(x)$")
ax.set_xticks((a, b))
ax.set_xticklabels(("$a$", "$b$"))
ax.set_yticks([func(a), func(b)])
ax.set_yticklabels(("$f(a)$", "$f(b)$"))
plt.grid(True)
import matplotlib.finance as mpf
start = (2014, 5, 1)
end = (2014, 6, 30)
quotes = mpf.quotes_historical_yahoo("^GDAXI", start, end)
fig, ax = plt.subplots(figsize=(8, 5))
mpf.plot_day_summary(ax, quotes, colorup="b", colordown="r")
plt.grid(True)
ax.xaxis_date()
plt.title("DAX Index")
plt.ylabel("index level")
plt.setp(plt.gca().get_xticklabels(), rotation=30)
quotes = np.array(mpf.quotes_historical_yahoo("YHOO", start, end))
fig, (ax1, ax2) = plt.subplots(2, sharex=True, figsize=(8, 6))
mpf.candlestick(ax1, quotes, width=0.6, colorup="b", colordown="r")
ax1.set_title("Yahoo Inc.")
ax1.set_ylabel("index level")
ax1.grid(True)
# you can specify dates in any format you have a converter for.
# matplotlib will convert everything under the hood to seconds since
# the epoch, but you shouldn't have to deal with this
date1 = datetime.date(2004, 2, 1)
date2 = datetime.date(2004, 4, 12)
# quotes in Eastern time zone
converter = PyDatetimeConverter()
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
hours = DayLocator() # minor ticks on the days
weekFormatter = DateFormatter('%b %d') # Eg, Jan 12
dayFormatter = DateFormatter('%d') # Eg, 12
quotes = quotes_historical_yahoo('INTC', date1, date2, converter)
if not quotes:
raise SystemExit
ax = subplot(111)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(hours)
ax.xaxis.set_major_formatter(weekFormatter)
#ax.xaxis.set_minor_formatter(dayFormatter)
plot_day_summary(ax, quotes, ticksize=3, converter=converter)
#candlestick(ax, quotes, width=0.6, converter=converter)
set(gca().get_xticklabels(), 'rotation', 45, 'horizontalalignment', 'right')
show()
# the epoch, but you shouldn't have to deal with this
date1 = datetime.date( 2004, 2, 1 )
date2 = datetime.date( 2004, 4, 12 )
# quotes in Eastern time zone
converter = PyDatetimeConverter()
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
hours = DayLocator() # minor ticks on the days
weekFormatter = DateFormatter('%b %d') # Eg, Jan 12
dayFormatter = DateFormatter('%d') # Eg, 12
quotes = quotes_historical_yahoo(
'INTC', date1, date2, converter)
if not quotes:
raise SystemExit
ax = subplot(111)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(hours)
ax.xaxis.set_major_formatter(weekFormatter)
#ax.xaxis.set_minor_formatter(dayFormatter)
plot_day_summary(ax, quotes, ticksize=3, converter=converter)
#candlestick(ax, quotes, width=0.6, converter=converter)
set( gca().get_xticklabels(), 'rotation', 45, 'horizontalalignment', 'right')
show()
plot_day_summary, candlestick2
date1 = ( 2013, 10, 20)
date2 = ( 2013, 11, 10 )
ticker='IBM'
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = DayLocator() # minor ticks on the days
weekFormatter = DateFormatter('%b %d') # e.g., Jan 12
dayFormatter = DateFormatter('%d') # e.g., 12
quotes = quotes_historical_yahoo(ticker, date1, date2)
if len(quotes) == 0:
raise SystemExit
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
ax.xaxis.set_minor_formatter(dayFormatter)
plot_day_summary(ax, quotes, ticksize=3)
candlestick(ax, quotes, width=0.6)
ax.xaxis_date()
ax.autoscale_view()
plt.setp( plt.gca().get_xticklabels(), rotation=80, horizontalalignment='right')
plt.figtext(0.35,0.45, '10/29: Open, High, Low, Close')
plt.figtext(0.35,0.42, ' 177.62, 182.32, 177.50, 182.12')
plt.figtext(0.35,0.32, 'Black ==> Close > Open ')
plt.figtext(0.35,0.28, 'Red ==> Close < Open ')
plt.title('Candlesticks for IBM from 10/20/2013 to 11/10/2013')
plt.ylabel('Price')
plt.xlabel('Date')
plt.show()
def plot_ticker(ticker, r, rsi, cmf, macd, ema):
prices = r.adj_close
dx = r.adj_close - r.close
low = r.low + dx
high = r.high + dx
ma10 = talib.SMA(r.adj_close, 10)
ma50 = talib.SMA(r.adj_close, 50)
last = r[-1]
volume = r.volume
vmax = volume.max()
prices = []
for row in r:
adj_ratio = row.adj_close/row.close
# line = dates.date2num(row.date),row.open*adj_ratio,row.close*adj_ratio,row.low*adj_ratio,row.high*adj_ratio,row.volume
line = dates.date2num(row.date),row.open*adj_ratio,row.close*adj_ratio,row.high*adj_ratio,row.low*adj_ratio,row.volume
prices.append(line)
### plot the figure
plt.rc('axes', grid=True)
plt.rc('grid', color='0.75', linestyle='-', linewidth=0.5)
textsize = 9
left, width = 0.1, 0.8
rect1 = [left, 0.8, width, 0.1]
rect2 = [left, 0.3, width, 0.5]
rect3 = [left, 0.2, width, 0.1]
rect4 = [left, 0.1, width, 0.1]
fig = plt.figure(facecolor='white')
axescolor = '#f6f6f6' # the axes background color
ax1 = fig.add_axes(rect1, axisbg=axescolor) #left, bottom, width, height
ax2 = fig.add_axes(rect2, axisbg=axescolor, sharex=ax1)
ax2t = ax2.twinx()
ax3 = fig.add_axes(rect3, axisbg=axescolor, sharex=ax1)
ax4 = fig.add_axes(rect4, axisbg=axescolor, sharex=ax1)
### plot the relative strength indicator
fillcolor = 'darkgoldenrod'
print len(rsi)
print len(cmf)
ax1.plot(r.date, rsi, color=fillcolor)
ax1.axhline(70, color=fillcolor)
ax1.axhline(30, color=fillcolor)
ax1.fill_between(r.date, rsi, 70, where=(rsi>=70), facecolor=fillcolor, edgecolor=fillcolor)
ax1.fill_between(r.date, rsi, 30, where=(rsi<=30), facecolor=fillcolor, edgecolor=fillcolor)
ax1.text(0.6, 0.9, '>70 = overbought', va='top', transform=ax1.transAxes, fontsize=textsize)
ax1.text(0.6, 0.1, '<30 = oversold', transform=ax1.transAxes, fontsize=textsize)
ax1.set_ylim(0, 100)
ax1.set_yticks([30,70])
ax1.text(0.025, 0.95, 'RSI (%d)'%settings['rsi']['timeperiod'], va='top', transform=ax1.transAxes, fontsize=textsize)
ax1.set_title('%s daily'%ticker)
### plot the chaikin money flow
ax4.plot(r.date, cmf, color=fillcolor)
ax4.axhline(0, color=fillcolor)
ax4.fill_between(r.date, cmf, 0, where=None, facecolor=fillcolor, edgecolor=fillcolor)
ax4.set_yticks([-0.5, 0, 0.5])
ax4.text(0.025, 0.95, 'CMF (%d)'%settings['cmf']['timeperiod'], va='top', transform=ax4.transAxes, fontsize=textsize)
### plot the price and volume data
plot_day_summary(ax2, prices, colorup='#53c156', colordown='#ff1717')
s = '%s O:%1.2f H:%1.2f L:%1.2f C:%1.2f, V:%1.1fM Chg:%+1.2f' % (
last.date,
last.open, last.high,
last.low, last.close,
last.volume*1e-6,
last.close-last.open )
t4 = ax2.text(0.3, 0.9, s, transform=ax2.transAxes, fontsize=textsize)
ax2.plot(r.date, ma10, color='blue', lw=1, label='MA (10)')
ax2.plot(r.date, ma50, color='pink', lw=1, label='MA (50)')
props = font_manager.FontProperties(size=10)
leg = ax2.legend(loc='upper left', shadow=True, fancybox=True, prop=props)
leg.get_frame().set_alpha(0.5)
poly = ax2t.fill_between(r.date, volume, 0, label='Volume', facecolor=fillcolor, edgecolor=fillcolor)
ax2t.set_ylim(0, 5*vmax)
ax2t.set_yticks([])
### plot the MACD indicator
fillcolor = 'darkslategrey'
ax3.plot(r.date, macd, color='blue', lw=1)
ax3.plot(r.date, ema, color='green', lw=1)
ax3.fill_between(r.date, macd-ema, 0, alpha=0.5, facecolor=fillcolor, edgecolor=fillcolor)
ax3.text(0.025, 0.95, 'MACD (%d, %d, %d)'%(settings['macd']['fastperiod'], settings['macd']['slowperiod'], settings['macd']['signalperiod']), va='top', transform=ax3.transAxes, fontsize=textsize)
#ax3.set_yticks([])
# turn off upper axis tick labels, rotate the lower ones, etc
for ax in ax1, ax2, ax2t, ax3:
if ax!=ax3:
for label in ax.get_xticklabels():
label.set_visible(False)
else:
for label in ax.get_xticklabels():
label.set_rotation(30)
label.set_horizontalalignment('right')
ax.fmt_xdata = mdates.DateFormatter('%Y-%m-%d')
class MyLocator(mticker.MaxNLocator):
def __init__(self, *args, **kwargs):
mticker.MaxNLocator.__init__(self, *args, **kwargs)
def __call__(self, *args, **kwargs):
return mticker.MaxNLocator.__call__(self, *args, **kwargs)
# at most 5 ticks, pruning the upper and lower so they don't overlap
# with other ticks
#ax2.yaxis.set_major_locator(mticker.MaxNLocator(5, prune='both'))
#ax3.yaxis.set_major_locator(mticker.MaxNLocator(5, prune='both'))
ax2.yaxis.set_major_locator(MyLocator(5, prune='both'))
ax3.yaxis.set_major_locator(MyLocator(5, prune='both'))
plt.show()
#ticker='AAPL'
#DATA_DIR = 'data/'
#
#fh = open(DATA_DIR + ticker)
## a numpy record array with fields: date, open, high, low, close, volume, adj_close)
#r = mlab.csv2rec(fh)
#fh.close()
#r.sort()
#
#### compute everything
#rsi = talib.RSI(r.adj_close)
#macd, macdsignal, macdhist = talib.MACD(r.adj_close, fastperiod=nfast, slowperiod=nslow)
#ema = talib.EMA(macd, nema)
#
#plot_ticker(ticker, r, rsi, macd, ema)
