I updated the code and now it provides a graph, however, after giving me the graph, it gives the following error messages.
Warning (from the warning module): File "C: \ Python27 \ lib \ site-packages \ matplotlib \ collections.py", line 590 if self._edgecolors == str ('face'): FutureWarning: elementary comparison failed; instead returns a scalar, but in the future will perform elemental comparison
import urllib2 import time import datetime import numpy as np import matplotlib.pyplot as plt import matplotlib.ticker as mticker import matplotlib.dates as mdates from matplotlib.finance import candlestick_ochl import matplotlib import pylab matplotlib.rcParams.update({'font.size': 9}) def rsiFunc(prices, n=14): deltas = np.diff(prices) seed = deltas[:n+1] up = seed[seed>=0].sum()/n down = -seed[seed<0].sum()/n rs = up/down rsi = np.zeros_like(prices) rsi[:n] = 100. - 100./(1.+rs) for i in range(n, len(prices)): delta = deltas[i-1] # cause the diff is 1 shorter if delta>0: upval = delta downval = 0. else: upval = 0. downval = -delta up = (up*(n-1) + upval)/n down = (down*(n-1) + downval)/n rs = up/down rsi[i] = 100. - 100./(1.+rs) return rsi def movingaverage(values,window): weigths = np.repeat(1.0, window)/window smas = np.convolve(values, weigths, 'valid') return smas # as a numpy array def ExpMovingAverage(values, window): weights = np.exp(np.linspace(-1., 0., window)) weights /= weights.sum() a = np.convolve(values, weights, mode='full')[:len(values)] a[:window] = a[window] return a def computeMACD(x, slow=26, fast=12): """ compute the MACD (Moving Average Convergence/Divergence) using a fast and slow exponential moving avg' return value is emaslow, emafast, macd which are len(x) arrays """ emaslow = ExpMovingAverage(x, slow) emafast = ExpMovingAverage(x, fast) return emaslow, emafast, emafast - emaslow def graphData(stock,MA1,MA2): ''' Use this to dynamically pull a stock: ''' try: print 'Currently Pulling',stock print str(datetime.datetime.fromtimestamp(int(time.time())).strftime('%Y-%m-%d %H:%M:%S')) #Keep in mind this is close high low open data from Yahoo urlToVisit = 'http://chartapi.finance.yahoo.com/instrument/1.0/'+stock+'/chartdata;type=quote;range=10y/csv' stockFile =[] try: sourceCode = urllib2.urlopen(urlToVisit).read() splitSource = sourceCode.split('\n') for eachLine in splitSource: splitLine = eachLine.split(',') if len(splitLine)==6: if 'values' not in eachLine: stockFile.append(eachLine) except Exception, e: print str(e), 'failed to organize pulled data.' except Exception,e: print str(e), 'failed to pull pricing data' try: date, closep, highp, lowp, openp, volume = np.loadtxt(stockFile,delimiter=',', unpack=True, converters={ 0: mdates.strpdate2num('%Y%m%d')}) x = 0 y = len(date) newAr = [] while x < y: appendLine = date[x],openp[x],closep[x],highp[x],lowp[x],volume[x] newAr.append(appendLine) x+=1 Av1 = movingaverage(closep, MA1) Av2 = movingaverage(closep, MA2) SP = len(date[MA2-1:]) fig = plt.figure(facecolor='#07000d') ax1 = plt.subplot2grid((6,4), (1,0), rowspan=4, colspan=4, axisbg='#07000d') candlestick_ochl(ax1, newAr[-SP:], width=.6, colorup='#53c156', colordown='#ff1717')#width=.6, plot_day_summary_ohlc Label1 = str(MA1)+' SMA' Label2 = str(MA2)+' SMA' ax1.plot(date[-SP:],Av1[-SP:],'#e1edf9',label=Label1, linewidth=1.5) ax1.plot(date[-SP:],Av2[-SP:],'#4ee6fd',label=Label2, linewidth=1.5) ax1.grid(True, color='w') ax1.xaxis.set_major_locator(mticker.MaxNLocator(10)) ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d')) ax1.yaxis.label.set_color("w") ax1.spines['bottom'].set_color("#5998ff") ax1.spines['top'].set_color("#5998ff") ax1.spines['left'].set_color("#5998ff") ax1.spines['right'].set_color("#5998ff") ax1.tick_params(axis='y', colors='w') plt.gca().yaxis.set_major_locator(mticker.MaxNLocator(prune='upper')) #gca() ax1.tick_params(axis='x', colors='w') plt.ylabel('Stock price and Volume') maLeg = plt.legend(loc=9, ncol=2, prop={'size':7}, fancybox=True, borderaxespad=0.) maLeg.get_frame().set_alpha(0.4) textEd = plt.gca().get_legend().get_texts()#pylab.gca() changed to plt.gca() plt.setp(textEd[0:5], color = 'w')#changed pylab.setp to plt.setp volumeMin = 0 ax0 = plt.subplot2grid((6,4), (0,0), sharex=ax1, rowspan=1, colspan=4, axisbg='#07000d') rsi = rsiFunc(closep) rsiCol = '#c1f9f7' posCol = '#386d13' negCol = '#8f2020' ax0.plot(date[-SP:], rsi[-SP:], rsiCol, linewidth=1.5) ax0.axhline(70, color=negCol) ax0.axhline(30, color=posCol) ax0.fill_between(date[-SP:], rsi[-SP:], 70, where=(rsi[-SP:]>=70), facecolor=negCol, edgecolor=negCol, alpha=0.5) ax0.fill_between(date[-SP:], rsi[-SP:], 30, where=(rsi[-SP:]<=30), facecolor=posCol, edgecolor=posCol, alpha=0.5) ax0.set_yticks([30,70]) ax0.yaxis.label.set_color("w") ax0.spines['bottom'].set_color("#5998ff") ax0.spines['top'].set_color("#5998ff") ax0.spines['left'].set_color("#5998ff") ax0.spines['right'].set_color("#5998ff") ax0.tick_params(axis='y', colors='w') ax0.tick_params(axis='x', colors='w') plt.ylabel('RSI') ax1v = ax1.twinx() ax1v.fill_between(date[-SP:],volumeMin, volume[-SP:], facecolor='#00ffe8', alpha=.4) ax1v.axes.yaxis.set_ticklabels([]) ax1v.grid(False) ax1v.set_ylim(0, 3*volume.max()) ax1v.spines['bottom'].set_color("#5998ff") ax1v.spines['top'].set_color("#5998ff") ax1v.spines['left'].set_color("#5998ff") ax1v.spines['right'].set_color("#5998ff") ax1v.tick_params(axis='x', colors='w') ax1v.tick_params(axis='y', colors='w') ax2 = plt.subplot2grid((6,4), (5,0), sharex=ax1, rowspan=1, colspan=4, axisbg='#07000d') # START NEW INDICATOR CODE # # END NEW INDICATOR CODE # plt.gca().yaxis.set_major_locator(mticker.MaxNLocator(prune='upper')) ax2.spines['bottom'].set_color("#5998ff") ax2.spines['top'].set_color("#5998ff") ax2.spines['left'].set_color("#5998ff") ax2.spines['right'].set_color("#5998ff") ax2.tick_params(axis='x', colors='w') ax2.tick_params(axis='y', colors='w') ax2.yaxis.set_major_locator(mticker.MaxNLocator(nbins=5, prune='upper')) for label in ax2.xaxis.get_ticklabels(): label.set_rotation(45) plt.suptitle(stock.upper(),color='w') plt.setp(ax0.get_xticklabels(), visible=False) plt.setp(ax1.get_xticklabels(), visible=False) '''ax1.annotate('Big news!',(date[510],Av1[510]), xytext=(0.8, 0.9), textcoords='axes fraction', arrowprops=dict(facecolor='white', shrink=0.05), fontsize=14, color = 'w', horizontalalignment='right', verticalalignment='bottom')''' plt.subplots_adjust(left=.09, bottom=.14, right=.94, top=.95, wspace=.20, hspace=0) plt.show() fig.savefig('example.png',facecolor=fig.get_facecolor()) except Exception,e: print 'main loop',str(e) while True: stock = raw_input('Stock to plot: ') graphData(stock,10,50)