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example updates
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‎examples/api/date_demo.py‎

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#!/usr/bin/env python
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"""
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Simple example showing how to plot a time series with datetime objects
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Show how to make date plots in matplotlib using date tick locators and
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formatters. See major_minor_demo1.py for more information on
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controlling major and minor ticks
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All matplotlib date plotting is done by converting date instances into
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days since the 0001-01-01 UTC. The conversion, tick locating and
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formatting is done behind the scenes so this is most transparent to
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you. The dates module provides several converter functions date2num
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and num2date
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"""
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import datetime
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import matplotlib.pyplot as plt
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import matplotlib.dates as mdates
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import matplotlib.mlab as mlab
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years = mdates.YearLocator() # every year
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months = mdates.MonthLocator() # every month
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yearsFmt = mdates.DateFormatter('%Y')
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today = datetime.date.today()
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dates = [today+datetime.timedelta(days=i) for i in range(10)]
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r = mlab.csv2rec('../data/goog.csv')
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r.sort()
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fig = plt.figure()
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ax = fig.add_subplot(111)
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ax.plot(dates, range(10))
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ax.plot(r.date, r.adj_close)
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# format the ticks
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ax.xaxis.set_major_locator(years)
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ax.xaxis.set_major_formatter(yearsFmt)
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ax.xaxis.set_minor_locator(months)
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ax.autoscale_view()
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# format the coords message box
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def price(x): return '$%1.2f'%x
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ax.format_xdata = mdates.DateFormatter('%Y-%m-%d')
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ax.format_ydata = price
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ax.grid(True)
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# rotates and right aligns the x labels, and moves the bottom of the
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# axes up to make room for them
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fig.autofmt_xdate()
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plt.show()

‎examples/data/aapl.csv‎

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‎examples/data/goog.csv‎

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‎examples/data/msft_nasdaq_d.csv‎

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‎examples/pylab_examples/finance_work2.py‎

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"""
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You need a additional files to run this example. Save the following
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in the same dir as this file
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http://matplotlib.sourceforge.net/screenshots/helpers.py
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http://matplotlib.sourceforge.net/screenshots/msft_nasdaq_d.csv
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http://matplotlib.sourceforge.net/screenshots/__init__.py
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"""
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import time, os, sys, datetime
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from matplotlib import rcParams
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from matplotlib.ticker import IndexLocator, FuncFormatter, NullFormatter, MultipleLocator
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from matplotlib.dates import IndexDateFormatter, date2num
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from matplotlib.finance import candlestick2, plot_day_summary2, \
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volume_overlay, index_bar
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from pylab import *
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rcParams['timezone'] = 'US/Eastern'
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rc('grid', color='0.75', linestyle='-', linewidth=0.5)
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def load_quotes(fname, maxq=None):
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"""
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Load quotes from the representative data files vineet sent If any
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of the values are missing I force all missing. Quotes are sorted
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in increasing time. Return value is a list of tuples
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(epoch, open, high, low, close, volume )
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"""
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quotes = []
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for i, line in enumerate(file(fname)):
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if maxq is not None and i>maxq: break
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ts,o,h,l,c,v = line.split(',')
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dt = datetime.datetime(*time.strptime(ts.strip('"'), '%Y%m%d%H%M%S')[:6]) # convert to float days
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d = date2num(dt)
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o,h,l,c,v = [float(val) for val in o,h,l,c,v]
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if o==-1 or h==-1 or l==-1 or c==-1 or v==-1:
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o,h,l,c,v = -1, -1, -1, -1,-1
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quotes.append((d,o,h,l,c,v))
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quotes.sort() # increasing time
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return quotes
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def ema(s, n):
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"""
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returns an n period exponential moving average for
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the time series s
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s is a list ordered from oldest (index 0) to most recent (index
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-1) n is an integer
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returns a numeric array of the exponential moving average
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"""
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s = array(s)
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ema = []
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j = 1
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#get n sma first and calculate the next n period ema
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sma = sum(s[:n]) / n
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multiplier = 2 / float(1 + n)
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ema.append(sma)
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#EMA(current) = ( (Price(current) - EMA(prev) ) xMultiplier) + EMA(prev)
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ema.append(( (s[n] - sma) * multiplier) + sma)
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#now calculate the rest of the values
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for i in s[n+1:]:
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tmp = ( (i - ema[j]) * multiplier) + ema[j]
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j = j + 1
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ema.append(tmp)
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return ema
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def movavg(s, n):
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"""
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returns an n period moving average for the time series s
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s is a list ordered from oldest (index 0) to most recent (index -1)
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n is an integer
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returns a numeric array of the moving average
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See also ema in this module for the exponential moving average.
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"""
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s = array(s)
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c = cumsum(s)
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return (c[n-1:] - c[:-n+1]) / float(n-1)
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def fill_over(ax, x, y, val, color, over=True):
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"""
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Plot filled x,y for all y over val
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if over = False, fill all areas < val
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"""
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ybase = asarray(y)-val
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crossings = nonzero(less(ybase[:-1] * ybase[1:],0))
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if ybase[0]>=0: fillon = over
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else: fillon = not over
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indLast = 0
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for ind in crossings:
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if fillon:
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thisX = x[indLast:ind+1]
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thisY = y[indLast:ind+1]
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thisY[0] = val
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thisY[-1] = val
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ax.fill(thisX, thisY, facecolor=color)
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fillon = not fillon
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indLast = ind
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def random_signal(N, tau):
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'generate a length N random signal with time constant tau'
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t = arange(float(N))
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filter = exp(-t/tau)
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return convolve( randn(N), filter, mode=2)[:len(t)]
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fname = '../data/msft_nasdaq_d.csv'
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quotes = load_quotes(fname, 200)
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times, opens, highs, lows, closes, volumes = zip(*quotes)
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def get_valid(x):
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return array([thisx for thisx in x if thisx!=-1])
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#valid opens, etc
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vopens = get_valid(opens)
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vcloses = get_valid(closes)
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vlows = get_valid(lows)
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vhighs = get_valid(highs)
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vvolumes = get_valid(volumes)
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vind = array([i for i, o in enumerate(opens) if o!=-1])
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assert(len(vopens)==len(vcloses)==len(vlows)==len(vhighs)==len(vvolumes))
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N = len(vopens)
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figBG = 'w' # the figure background color
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axesBG = '#f6f6f6' # the axies background color
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textsize = 8 # size for axes text
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# the demo data are intc from (2003, 9, 1) to (2004, 4, 12 ) with
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# dates as epoch; I saved these to a file for ease of debugginh
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ticker = 'MSFT'
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figure(1, facecolor=figBG)
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def get_locator():
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"""
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the axes cannot share the same locator, so this is a helper
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function to generate locators that have identical functionality
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"""
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return IndexLocator(10, 1)
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formatter = IndexDateFormatter(times, '%b %d %y')
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nullfmt = NullFormatter() # no labels
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def fmt_vol(x,pos):
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if pos>3: return '' # only label the first 3 ticks
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return '%dM' % int(x*1e-6)
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volumeFmt = FuncFormatter(fmt_vol)
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left, width = 0.1, 0.8
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rect1 = [left, 0.7, width, 0.2]
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rect2 = [left, 0.3, width, 0.4]
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rect3 = [left, 0.1, width, 0.2]
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axUpper = axes(rect1, axisbg=axesBG) #left, bottom, width, height
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axMiddle = axes(rect2, axisbg=axesBG, sharex=axUpper)
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axMiddleVol = axes(rect2, axisbg=axesBG, frameon=False, sharex=axUpper) # the volume overlay
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axLower = axes(rect3, axisbg=axesBG, sharex=axUpper)
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axUpper.xaxis.set_major_locator( get_locator() )
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axUpper.xaxis.set_major_formatter(nullfmt)
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axUpper.grid(True)
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# set up two scales on middle axes with left and right ticks
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axMiddle.yaxis.tick_left()
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axMiddle.xaxis.set_major_locator( get_locator() )
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axMiddle.yaxis.set_major_locator( MultipleLocator(5) )
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axMiddle.xaxis.set_major_formatter(nullfmt)
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axMiddleVol.yaxis.tick_right()
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axMiddleVol.xaxis.set_major_locator( get_locator() )
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axMiddleVol.xaxis.set_major_formatter(nullfmt)
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axMiddleVol.yaxis.set_major_formatter(volumeFmt)
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axMiddle.grid(True)
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axLower.xaxis.set_major_locator( get_locator() )
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axLower.xaxis.set_major_formatter( formatter )
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axLower.grid(True)
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if 1: ############### Upper axes #################
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# make up a pseudo signal
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purple = '#660033'
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s = random_signal(len(vind), tau=20)
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thresh = 4
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axUpper.plot(s, color=purple)
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# upper horiz line
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axUpper.plot( (0, N), [thresh, thresh], color=purple, linewidth=1)
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# lower horiz line
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axUpper.plot( (0, N), [-thresh, -thresh], color=purple, linewidth=1)
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# fill above threshold
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fill_over(axUpper, vind, s, thresh, purple, over=True)
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fill_over(axUpper, vind, s, -thresh, purple, over=False)
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t = axUpper.set_title('Microsoft Corp (MSFT)',
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fontsize=12)
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t.set_y(1.05) # move it up a bit higher than the default
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t.set_x(0) # align the title left, axes coords
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t.set_horizontalalignment('left') # align the title left, axes coords
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axUpper.yaxis.set_major_locator( MultipleLocator(5) )
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# now add some text
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left, height, top = 0.025, 0.06, 0.85
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t = axUpper.text(left, top, 'RSI(14) 51.0', fontsize=textsize,
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transform=axUpper.transAxes)
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if 1: ############### Middle axes #################
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#plot_day_summary2(axMiddle, opens, closes, highs, lows)
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candlestick2(axMiddle, opens, closes, highs, lows, width=0.9)
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# specify the text in axes (0,1) coords. 0,0 is lower left and 1,1 is
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# upper right
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left, height, top = 0.025, 0.06, 0.9
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t1 = axMiddle.text(left, top, '%s daily'%ticker, fontsize=textsize,
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transform=axMiddle.transAxes)
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t2 = axMiddle.text(left, top-height, 'MA(5)', color='b', fontsize=textsize,
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transform=axMiddle.transAxes)
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t3 = axMiddle.text(left, top-2*height, 'MA(20)', color='r', fontsize=textsize,
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transform=axMiddle.transAxes)
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s = '%s O:%1.2f H:%1.2f L:%1.2f C:%1.2f, V:%1.1fM Chg:%+1.2f' %(
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time.strftime('%d-%b-%Y'),
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vopens[-1], vhighs[-1],
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vlows[-1], vcloses[-1],
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vvolumes[-1]*1e-6,
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vcloses[-1]-vopens[-1])
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t4 = axMiddle.text(0.4, top, s, fontsize=textsize,
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transform=axMiddle.transAxes)
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# now do the moviing average. I'll use a convolution to simulate a
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# real moving average
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ma5 = movavg(vopens, 5)
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ma20 = movavg(vopens, 20)
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axMiddle.plot(vind[5-1:], ma5, 'b', linewidth=1)
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axMiddle.plot(vind[20-1:], ma20, 'r', linewidth=1)
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axMiddle.set_ylim((20, 32))
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axMiddle.set_yticks((25,30))
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# Now do the volume overlay
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bars = volume_overlay(axMiddleVol, opens, closes, volumes, alpha=0.5)
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axMiddleVol.set_ylim((0, 3*max(vvolumes))) # use only a third of the viewlim
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if 1: ############### Lower axes #################
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# make up two signals; I don't know what the signals are in real life
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# so I'll just illustrate the plotting stuff
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s1 = random_signal(len(vind), 10)
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s2 = random_signal(len(vind), 20)
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axLower.plot(vind, s1, color=purple)
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axLower.plot(vind, s2, color='k', linewidth=1.0)
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s3 = s2-s1
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axLower.plot(vind, s3, color='#cccc99') # wheat
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bars = index_bar(axLower, s3, width=2, alpha=0.5,
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facecolor='#3087c7', edgecolor='#cccc99')
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axLower.yaxis.set_major_locator(MultipleLocator(5))
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# now add some text
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left, height, top = 0.025, 0.06, 0.85
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t = axLower.text(left, top, 'MACD(12,26,9) -0.26', fontsize=textsize,
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transform=axLower.transAxes)
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# make sure everyone has the same axes limits
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setp(axLower.get_xticklabels(), 'rotation', 45,
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'horizontalalignment', 'right', fontsize=8)
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# force all the axes to have the same x data limits
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allAxes = (axUpper, axMiddle, axMiddleVol, axLower)
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xlim = 0, len(quotes)
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for a in allAxes:
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#a.dataLim.intervalx = xlim
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a.set_xlim(xlim)
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for ax in axUpper, axMiddle:
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for ticklabel in ax.get_xticklabels():
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ticklabel.set_visible(False)
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show()

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