def showCandles(stock, days):
quotes = []
prices = stock.prices[len(stock.prices)-days:]
for day in prices:
date = map(int,tuple(day['date'].split('-')))
date = date2num(datetime.date(*date))
quotes.append((date, float(day['open']), float(day['close']),float(day['high']),float(day['low'])))
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = DayLocator() # minor ticks on the days
weekFormatter = DateFormatter('%b %d') # Eg, Jan 12
dayFormatter = DateFormatter('%d') # Eg, 12
fig = figure()
fig.subplots_adjust(bottom=0.2)
ax = fig.add_subplot(111)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
#ax.xaxis.set_minor_formatter(dayFormatter)
candlestick(ax, quotes, width=0.6)
ax.xaxis_date()
ax.autoscale_view()
setp( gca().get_xticklabels(), rotation=45, horizontalalignment='right')
show()
def generateGraph(self, quotes):
self.clearGraphData()
#print "DEBUG:"
#print "\tquotes = %s" % quotes
#for i in range(len(highs)):
# print "DEBUG: (%s, %s, %s, %s)" %(lows[i], opens[i], closes[i], highs[i])
# print "DEBUG: diffs h/l: %s o/c: %s" %(lows[i] - highs[i], opens[i] - closes[i])
self.ax = self.fig.add_subplot(111)
self.ax.set_title(_("Session candlestick graph"))
#Set axis labels and grid overlay properites
self.ax.set_xlabel(_("Sessions"), fontsize=12)
self.ax.set_ylabel("$", fontsize=12)
self.ax.grid(color='g', linestyle=':', linewidth=0.2)
candlestick(self.ax,
quotes,
width=0.50,
colordown='r',
colorup='g',
alpha=1.00)
self.graphBox.add(self.canvas)
self.canvas.show()
self.canvas.draw()
def printKline(stock):
re = getFullQuoteByStock(stock)
re = re.set_index('date')
#re.index = pd.to_datetime(re.index)
data_list = []
re = re.drop('index', 1)
for dates, row in re.iterrows():
date_time = datetime.datetime.strptime(dates, '%Y-%m-%d')
t = date2num(date_time)
open, high, low, close = row[:4]
datas = (t, open, high, low, close)
data_list.append(datas)
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
ax.xaxis_date()
plt.xticks(rotation=45)
plt.yticks()
plt.title("STOCK:" + stock)
plt.xlabel("time")
plt.ylabel("price")
mpf.candlestick(ax, data_list, width=1.5, colorup='r', colordown='green')
plt.grid()
plt.show()
plt.savefig('/Users/momo/Programs/python/result/' + stock + '.png')
def candlePlot(self,ax,quotes, width=0.6,colorup='r', colordown='g',alpha=0.5):
if sys.version > '3':
PY3 = True
else:
PY3 = False
if (PY3 == True):
mpf.candlestick_ohlc(ax, quotes, width,colorup, colordown,alpha)
else:
#opens, closes, highs, lows,
time = quotes[:,0]
opens = quotes[:,1]
closes= quotes[:,4]
highs = quotes[:,2]
lows = quotes[:,3]
quotesNew = np.vstack((time,opens,closes,highs,lows))
mpf.candlestick(ax, quotesNew.T, width,colorup, colordown,alpha)
ax.xaxis_date()
ax.autoscale_view()
#self.addText(ax,quotes[:,0],quotes[:,4])
for label in ax.xaxis.get_ticklabels():
label.set_color("red")
label.set_rotation(30)
label.set_fontsize(12)
ax.grid(True)
def __init__(self, ticker):
gtk.VBox.__init__(self)
startdate = datetime.date(2001, 1, 1)
today = enddate = datetime.date.today()
date1 = datetime.date(2011, 1, 1)
date2 = datetime.date.today()
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = DayLocator() # minor ticks on the days
weekFormatter = DateFormatter("%b %d") # Eg, Jan 12
dayFormatter = DateFormatter("%d") # Eg, 12
quotes = quotes_historical_yahoo(ticker, date1, date2)
if len(quotes) == 0:
raise SystemExit
fig = Figure(facecolor="white", figsize=(5, 4), dpi=100)
fig.subplots_adjust(bottom=0.2)
ax = fig.add_subplot(111)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
candlestick(ax, quotes, width=0.6)
ax.xaxis_date()
ax.autoscale_view()
pylab.setp(pylab.gca().get_xticklabels(), rotation=45, horizontalalignment="right")
canvas = FigureCanvas(fig) # a gtk.DrawingArea
self.pack_start(canvas)
toolbar = NavigationToolbar(canvas, win)
self.pack_start(toolbar, False, False)
def candlestickExample():
# (Year, month, day) tuples suffice as args for quotes_historical_yahoo
date1 = ( 2004, 2, 1)
date2 = ( 2004, 4, 12 )
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('INTC', 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=45, horizontalalignment='right')
print quotes
plt.show()
def QueryAndShowData(ins, beginTime, num): dics = GetMarketData(ins, beginTime, num) datas = [] i = 1 for item in dics: data = [] data.append(i) i = i + 1 data.append(item['openPrice']) data.append(item['closePrice']) data.append(item['highPrice']) data.append(item['lowPrice']) datas.append(data) fig = plt.figure(figsize = (18, 9)) ax = fig.add_subplot(211) candlestick(ax, datas, width = 0.4, colorup = 'r', colordown = 'g') ax.autoscale_view() volumeX = fig.add_subplot(212) datas = [] index = [] i = 1 for item in dics: index.append(i) i = i + 1 datas.append(item['volume']) volumeX.set_xlim(0, num) plt.bar(index, datas, 0.5, color = 'r', label = '成交量') plt.show()
def plot_chart(*tfs, norm=True, realtime=True, markers = None):
import matplotlib.dates as mdt
fig, ax = plt.subplots()
if len(tfs) == 1 and norm is True:
y = [(mdt.date2num(candle.DateTime), candle.Open, candle.Close, candle.High, candle.Low) for candle in tfs[0].container]
candlestick(ax, y, width=0.4, colorup='r', colordown='b')
ax.xaxis_date()
plt.title(tfs[0].symbol + " chart")
if markers is not None:
marker_y, marker_x = [], []
for elem in tfs[0].container:
if elem.DateTime in markers:
marker_y.append(.5*(elem.Open+elem.Close))
marker_x.append(mdt.date2num(elem.DateTime))
plt.plot(marker_x, marker_y, 'gD')
else:
for tf in tfs:
if realtime is True:
x = tf.get_Time_list()
else:
x = range(len(tf))
y = np.array(tf.get_C_list())
if norm is True:
y -= y.min()
y /= y.max()
plt.plot(x, y, label=tf.symbol)
plt.title("Charts graph")
plt.legend(loc='upper center', shadow=True)
plt.xlabel("Time")
plt.ylabel("Price")
plt.grid()
plt.show()
def plot_data(data,stock):
ticks = eg.choicebox(msg = 'choose ticks for the plot',choices = ['day','week','month'])
if ticks == 'month':
loc = MonthLocator()
elif ticks == 'week':
loc = WeekdayLocator(byweekday=MONDAY)
elif ticks == 'day':
loc = DayLocator()
weekFormatter = DateFormatter('%b %d')
dayFormatter = DateFormatter('%d')
# if candle_chart == 1:
fig = plt.figure()
ax1 = fig.add_subplot(211)
datelist = [matplotlib.dates.date2num(x) for x in data['Time']]
Prices = []
for idx in xrange(len(data)):
Prices.append((datelist[idx],data['Open'].ix[idx],data['Close'].ix[idx],data['High'].ix[idx],data['Low'].ix[idx]))
# candlestick(ax1,[datelist,data['Open'],data['Close'],data['High'],data['Low']])
candlestick(ax1,Prices)
ax1.set_xlabel('Date')
ax1.set_ylabel('$')
ax1.set_title('Candlestick plot for %s' %stock)
ax2 = fig.add_subplot(212)
ax2.plot(datelist,data['Adj Close'],'-r',label = 'Adj. Close')
ax2.set_ylabel('$')
ax2.legend()
ax3 = ax2.twinx()
ax3.bar(data['Time'],data['Volume'])
ax3.set_ylabel('Shares')
ax1.xaxis_date()
ax2.xaxis_date()
ax3.xaxis_date()
plt.show()
return
def candlestick(self,
index,
open,
high,
low,
close,
width=0.3,
secondary_y=False,
*args,
**kwargs):
"""
Takes a df and plots a candlestick.
Will auto search for proper columns
"""
data = {}
data['open'] = open
data['high'] = high
data['low'] = low
data['close'] = close
df = pd.DataFrame(data, index=index)
if self.index is None:
self.index = index
# grab merged data
xax = np.arange(len(self.index))
quotes = izip(xax, df['open'], df['close'], df['high'], df['low'])
ax = self.find_ax(secondary_y, kwargs)
self.setup_datetime(index)
candlestick(ax, quotes, width=width, colorup='g')
def candlePlot(self,
ax,
quotes,
width=0.6,
colorup='r',
colordown='g',
alpha=0.5):
if sys.version > '3':
PY3 = True
else:
PY3 = False
if (PY3 == True):
mpf.candlestick_ohlc(ax, quotes, width, colorup, colordown, alpha)
else:
#opens, closes, highs, lows,
time = quotes[:, 0]
opens = quotes[:, 1]
closes = quotes[:, 4]
highs = quotes[:, 2]
lows = quotes[:, 3]
quotesNew = np.vstack((time, opens, closes, highs, lows))
mpf.candlestick(ax, quotesNew.T, width, colorup, colordown, alpha)
ax.xaxis_date()
ax.autoscale_view()
#self.addText(ax,quotes[:,0],quotes[:,4])
for label in ax.xaxis.get_ticklabels():
label.set_color("red")
label.set_rotation(30)
label.set_fontsize(12)
ax.grid(True)
def plot(key, day, title, filepath, inc24h=False):
data_raw = get_plot_data(key, day)
if inc24h:
if len(data_raw) > 0:
latest = dt.strptime(data_raw[-1][0], dt_fmt_time)
else:
latest = day
bef24h = latest - timedelta(days=1)
daya_yest = [ l for l in get_plot_data(key, bef24h) if
dt.strptime(l[0], dt_fmt_time) > bef24h ]
data_raw = daya_yest + data_raw
# openとcloseは温度計測インターバルで表示が崩れるので使わない。
# open == closeとし、平均値を表示する。
data = [ [mdates.date2num(dt.strptime(j[0],dt_fmt_time)),
float(j[1]), float(j[1]), float(j[2]), float(j[3])]
for j in data_raw ]
fig = plt.figure(figsize=(12, 4))
ax = fig.add_subplot(1, 1, 1)
ax.set_ymargin(0.001)
mpl_finance.candlestick(ax, data, width=0.005, alpha=0.5, colorup='r', colordown='b')
ax.grid()
locator = mdates.AutoDateLocator()
formatter = mdates.AutoDateFormatter(locator)
formatter.scaled[1.0/24] = '%H:%M'
ax.xaxis.set_major_locator(locator)
ax.xaxis.set_major_formatter(formatter)
ax.set_title(title)
plt.savefig(filepath)
def printKlines(stocks, savepath, fileName):
stockNum = len(stocks)
fig = plt.figure()
fig.set_size_inches(18.5, 18.5)
i = 1
for stock in stocks:
re = getFullQuoteByStock(stock)
re = re.set_index('date')
#re.index = pd.to_datetime(re.index)
data_list = []
re = re.drop('index', 1)
for dates, row in re.iterrows():
date_time = datetime.datetime.strptime(dates, '%Y-%m-%d')
t = date2num(date_time)
open, high, low, close = row[:4]
datas = (t, open, high, low, close)
data_list.append(datas)
ax = fig.add_subplot(stockNum, 1, i)
#fig.subplots_adjust(bottom=0.2)
ax.xaxis_date()
#plt.xticks(rotation=45)
plt.xticks()
plt.yticks()
plt.title("STOCK:" + stock)
plt.xlabel("time")
plt.ylabel("price")
mpf.candlestick(ax, data_list, width=1, colorup='r', colordown='green')
plt.grid()
i = i + 1
#plt.show()
plt.savefig(savepath + fileName, dpi=100)
def buildgraph(self):
left, width = 0.1, 0.9
rect1 = [left, 0.05, width, 0.99]
size = len(self.mts.getData()) * 0.2
if size >= 32768:
size = 31767
fig = figure(figsize = (size, 10))
axescolor = '#f6f6f6'
ax = fig.add_axes(rect1, axisbg=axescolor) #left, bottom, width, height
# build the series for candles
M = []
ts = self.mts.getData()#[0:self.graphperiod]
t = len(self.mts.getData())
for i in ts:
M.insert(0, (t, i[0], i[3], i[1], i[2], 0))
t -= 1
candlestick(ax, M, width=0.6)
M1 = []
M2 = []
M3 = []
t2 = 1
for i in ts:
if i[4] == None or i[5] == None:
t2 += 1
else:
M1.insert(0, i[4] + self.K2 * i[5])
M2.insert(0, i[4])
M3.insert(0, i[4] - self.K * i[5])
date=range(t2+t,t+t2+len(M1))
ax.plot(date, M1)
ax.plot(date, M2)
ax.plot(date, M3)
for i in self.open:
if i[0] >= t:
ax.plot([i[0]], [i[1]], 'o', color='cyan')
for i in self.close:
if i[2] == "stoploss" and i[0] >= t:
ax.plot([i[0]], [i[1]], 'o', color='red')
elif i[2] == "stopgain" and i[0] >= t:
ax.plot([i[0]], [i[1]], 'o', color='green')
elif i[2] == "timeout(open)" and i[0] >= t:
ax.plot([i[0]], [i[1]], 'o', color='blue')
elif i[2] == "timeout(close)" and i[0] >= t:
ax.plot([i[0]], [i[1]], 'o', color='blue')
now = datetime.today().strftime("-%Y-%m-%d-%H-%M-%S");
filename = "./charts/" + sys.argv[1] + "/" + sys.argv[1] + now + ".png"
fig.savefig(filename)
def gpcs_trade(series, trade):
"""Function to plot a candle graph from a given series"""
"""takes as input the security code, default TY"""
from matplotlib.dates import DateFormatter, WeekdayLocator, HourLocator, \
DayLocator, MONDAY
from matplotlib.finance import quotes_historical_yahoo, candlestick,\
plot_day_summary, candlestick2
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = DayLocator() # minor ticks on the days
monthFormatter = DateFormatter('%b %d') # Eg, Jan 12
dayFormatter = DateFormatter('%d') # Eg, 12
#quotes contains a list of tuples:
#(date, open, close, high, low, volume)
quotes = series
if len(quotes) == 0:
today = datetime.datetime.now()
date2 = (today.year, today.month, today.day)
date1 = ( today.year -1, today.month, 1)
quotes = quotes_historical_yahoo('fut_code', date1, date2)
if len(quotes) == 0:
raise SystemExit
fig = figure()
fig.subplots_adjust(bottom=0.2)
ax = fig.add_subplot(111)
#ax.xaxis.set_major_locator(mondays)
#ax.xaxis.set_minor_locator(mondays)
#ax.xaxis.set_major_formatter(monthFormatter)
#ax.xaxis.set_minor_formatter(dayFormatter)
#plot_day_summary(ax, quotes, ticksize=3)
dt, o, c, h, l, v = zip(*quotes)
dt2 = []
for d in dt:
dt2.append(datetime.datetime.fromordinal(int(d)))
ser = DataFrame(data = {0:o, 1:c, 2:h, 3:l, 4:v}, index = dt2)
tmdelta = len(ser[trade.trend.a:])
ax.plot([trade.trend.a, max(ser.index)], [trade.trend.c_reg, (tmdelta*trade.trend.m_reg + trade.trend.c_reg)], color='r', linestyle='-', linewidth=2)
ax.plot([trade.trend.a, max(ser.index)], [trade.trend.c_reg+trade.trend.stdev_p_reg, (trade.trend.stdev_p_reg +tmdelta*trade.trend.m_reg + trade.trend.c_reg)], color='g', linestyle='-', linewidth=2)
ax.plot([trade.trend.a, max(ser.index)], [trade.trend.c_reg-trade.trend.stdev_p_reg, (-trade.trend.stdev_p_reg +tmdelta*trade.trend.m_reg + trade.trend.c_reg)], color='g', linestyle='-', linewidth=2)
tmdelta = len(ser[trade.trend.a:trade.trend.e])
ax.plot([trade.trend.a, trade.trend.e], [trade.trend.c_reg, (tmdelta*trade.trend.m_reg + trade.trend.c_reg)], color='b', linestyle='-', linewidth=2)
candlestick(ax, quotes, width=0.6)
#ax.xaxis_date()
ax.autoscale_view()
setp( gca().get_xticklabels(), rotation=45, horizontalalignment='right')
show()
def plot(self, mplSubplot, dateTimes, color):
if self.__useCandleSticks:
values = []
for dateTime in dateTimes:
bar = self.getValue(dateTime)
values.append((dates.date2num(dateTime), bar.getOpen(), bar.getClose(), bar.getHigh(), bar.getLow()))
finance.candlestick(mplSubplot, values, width=0.5, colorup="g", colordown="r")
else:
Series.plot(self, mplSubplot, dateTimes, color)
def candlestick(self, df, width=0.3):
"""
"""
xax = np.arange(len(df.index))
quotes = izip(xax, df.open, df.close, df.high, df.low)
ax = self.ax
self.df = df
self.setup_datetime(df.index)
candlestick(ax, quotes, width=width, colorup="g")
def candlestick(self, df, width=0.3):
"""
"""
xax = np.arange(len(df.index))
quotes = izip(xax, df.open, df.close, df.high, df.low)
ax = self.ax
self.df = df
self.setup_datetime(df.index)
candlestick(ax, quotes, width=width, colorup='g')
def showTrade(self, position, instrumentName):
#beforeBars = 300
#afterBars = 100
#barsNum = beforeBars + afterBars + (position.closeTime - position.openTime).seconds * 60
secondsBeforeTrade = 60 * 60
secondsAfterTrade = 60
from datetime import timedelta
data = self.getHistoryBarsByTime(instrumentName, position.openTime - timedelta(seconds=secondsBeforeTrade), position.closeTime + timedelta(seconds=secondsAfterTrade))
from matplotlib.finance import candlestick
fig = figure()
fig.subplots_adjust(bottom=0.2)
ax = fig.add_subplot(111)
data = self.quotesToCandlestick(data)
from matplotlib.lines import Line2D
from matplotlib.dates import date2num
color = 'red'
if position.order.orderType is 1:
color='green'
candlestick(ax, data, width=0.00006, colorup='g', colordown='r')
enter = Line2D(
xdata=(date2num(position.openTime), date2num(position.closeTime)), ydata=(position.openPrice, position.closePrice),
color=color,
linewidth=5,
antialiased=True,
)
if position.order.target is not 0:
tp = Line2D(
xdata=(date2num(position.openTime), date2num(position.closeTime)), ydata=(position.order.target, position.order.target),
color='g',
linewidth=0.5,
antialiased=True,
)
ax.add_line(tp)
if position.order.stop is not 0:
sl = Line2D(
xdata=(date2num(position.openTime), date2num(position.closeTime)), ydata=(position.order.stop, position.order.stop),
color='r',
linewidth=0.5,
antialiased=True,
)
ax.add_line(sl)
ax.add_line(enter)
ax.autoscale_view()
show()
def plotStats():
#columns: time, opening, close, high, low
candlestick_data = 5
quotes = [(0, 103.62, 102.01, 103.62, 101.90),
(1, 102.24, 102.90, 103.16, 102.09),
(2, 100.89, 102.59, 102.86, 100.51)]
fig, ax = plt.subplots()
candlestick(ax, quotes, width=0.5, colorup='g', colordown='r')
plt.show()
def plot(self, mplSubplot, dateTimes, color):
if self.__useCandleSticks:
values = []
for dateTime in dateTimes:
bar = self.getValue(dateTime)
if bar:
values.append((dates.date2num(dateTime), bar.getOpen(), bar.getClose(), bar.getHigh(), bar.getLow()))
finance.candlestick(mplSubplot, values, width=0.5, colorup='g', colordown='r',)
else:
Series.plot(self, mplSubplot, dateTimes, color)
def graphDataCandlestick(ticker, date, openp, highp, lowp, closep, volume, intradata):
fig = plt.figure() # facecolor='#07000d'
ax1 = plt.subplot2grid((6,4), (1,0), rowspan=4, colspan=4) #, axisbg='#07000d'
candlestick(ax1, intradata[-len(intradata):], width=.0005, colorup='#53c156', colordown='#ff1717')
#plot_day_summary2_ochl(ax1, openp, closep, closep, lowp, ticksize=4, colorup='k', colordown='r')
# CUSTOMIZE AXES 1
ax1.grid(True)
ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d %H:%M:%S'))
ax1.xaxis.set_major_locator(mticker.MaxNLocator(10))
ax1.set_ylim(0.75 * lowp.min(), 1.25 * highp.max())
plt.ylabel('Stock price and Volume')
# Colors
ax1.yaxis.label.set_color('w')
ax1.spines['bottom'].set_color('#5998ff')
ax1.spines['left'].set_color('#5998ff')
ax1.spines['right'].set_color('#5998ff')
ax1.spines['top'].set_color('#5998ff')
ax1.tick_params(axis='y', colors='w')
ax1.tick_params(axis='x', colors='w')
for label in ax1.xaxis.get_ticklabels():
label.set_rotation(45)
volumeMin = 0
ax1v = ax1.twinx()
ax1v.axes.yaxis.set_ticklabels([])
ax1v.grid(False)
ax1v.set_ylim(0, 3*volume.max())
ax1v.axes.yaxis.set_ticklabels([])
# Colors
ax1v.spines['bottom'].set_color('#5998ff')
ax1v.spines['left'].set_color('#5998ff')
ax1v.spines['right'].set_color('#5998ff')
ax1v.spines['top'].set_color('#5998ff')
ax1v.tick_params(axis='y', colors='w')
ax1v.tick_params(axis='x', colors='w')
ax1v.bar(date, volume, color='w', width=.0005)
#ax2 = plt.subplot2grid((4,4), (5,0), rowspan=2, colspan=4) # 3 rows down
#ax2.grid(True)
#plt.ylabel('Volume')
# Formats the plot
plt.subplots_adjust(left=.09, bottom=.18, right=.94, top=.95, wspace=.20, hspace=0)
plt.setp(ax1.get_xticklabels(), visible=True)
plt.xlabel('Date')
plt.show()
def peakValleyPlot(self):
fig = py.figure()
fig.subplots_adjust(bottom=0.2)
ax = fig.add_subplot(111)
candlestick(ax,self.quotes, width=0.6)
ax.xaxis_date()
ax.autoscale_view()
setp( gca().get_xticklabels(), rotation=45, horizontalalignment='right')
# plot the peaks and valleys
plot(self.quotes[:,0],self.peakPrices,'go',markersize = 6)
plot(self.quotes[:,0],self.valleyPrices,'r^', markersize = 6)
def graphData(datafile, MA1, MA2):
def bytedate2num(fmt):
def converter(b):
return mdates.strpdate2num(fmt)(b.decode('utf8'))
return converter
datep, openp, highp, lowp, closep, volume = \
np.loadtxt(datafile, unpack=True , usecols=(0,2,3,4,5,6), \
converters={ 0: bytedate2num("%Y-%m-%d")})
candleAr = []
#while x < y:
for x in range(len(datep)):
appendLine = datep[x],openp[x],closep[x],highp[x],lowp[x],volume[x] #highp[x],lowp[x],closep[x],volume[x]
candleAr.append(appendLine)
#print (candleAr)
AV1 = movingaverage(closep, MA1)
AV2 = movingaverage(closep, MA2)
SP = len(datep[MA2-1:])
fig = plt.figure()
ax1 = plt.subplot2grid((5,4),(0,0),rowspan=4, colspan=4)
candlestick(ax1, candleAr, width=0.5, colorup='g', colordown='r')
ax1.plot(datep[-SP:],AV1[-SP:])
ax1.plot(datep[-SP:],AV2[-SP:])
#ax1.plot(datep, openp)
#ax1.plot(datep, highp)
#ax1.plot(datep, lowp)
#ax1.plot(x=datep, y=closep)
ax1.xaxis.set_major_locator(mticker.MaxNLocator(10))
ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
plt.ylabel('Stock price')
ax1.grid(True)
ax2 = plt.subplot2grid((5,4),(4,0), sharex=ax1, rowspan=1, colspan=4)
ax2.bar(datep, volume)
ax2.axes.yaxis.set_ticklabels([])
plt.ylabel('Volume')
ax2.grid(True)
for label in ax2.xaxis.get_ticklabels():
label.set_rotation(45)
plt.subplots_adjust(left=.10,bottom=.19,right=.93,top=.95, wspace=.20, hspace=.07)
plt.xlabel('Date')
plt.suptitle('GAZP')
plt.setp(ax1.get_xticklabels(), visible=False)
#fig.savefig('example.png')
plt.show()
def create_figure(quotes):
f = Figure(figsize=(5, 4), dpi=100)
a = f.add_subplot(111)
canvas = FigureCanvas(f) # a gtk.DrawingArea
canvas.set_size_request(800, 300)
a.xaxis_date()
finance.candlestick(a, quotes, width=0.5)
return f
def create_figure(quotes): f = Figure(figsize=(5,4), dpi=100) a = f.add_subplot(111) canvas = FigureCanvas(f) # a gtk.DrawingArea canvas.set_size_request(800,300) a.xaxis_date() finance.candlestick(a, quotes, width=0.5) return f
def plotByChange(self, savePic):
timeAxis=self.quotes[:,0]
fig = py.figure()
fig.subplots_adjust(bottom=0.2)
ax = fig.add_subplot(111)
candlestick(ax, self.quotes, width=0.6)
ax.xaxis_date()
ax.autoscale_view()
setp( gca().get_xticklabels(), rotation=45, horizontalalignment='right')
plot(timeAxis[self.flagPeaks],self.peakPrices,'go',markersize = 6)
plot(timeAxis[self.flagValleys],self.valleyPrices,'r^', markersize = 6)
if self.score != 0:
# check if the peak or trough flag the current price
for i in range(len(self.comparators)):
if sum(self.flagIndicatorsCounter,0)[i] == 0:
continue
else:
plot(timeAxis[self.comparatorIndices[i]], self.comparators[i], '*')
for e in self.annotation:
time = e[0]
price = e[1]
flag = e[2]
ax.annotate(str(price)+'('+flag+')',xy=(time,price))
#ax.annotate(str(round(self.quotes[-1,4],2)),xy=(timeAxis[-1],self.quotes[-1,4]))
ax.annotate(str(round(self.currentPriceWeCare,2)),xy=(timeAxis[-1],self.quotes[-1,4]))
currentTime = str(datetime.date.fromordinal(int(timeAxis[-1])))
title=['Flagging points for',self.tradeType,'trading strategy of',self.stock,currentTime]
py.title(' '.join(title))
py.grid()
if savePic==True:
if 1:
py.savefig('pic/all/'+self.stock+currentTime+'.png', format='png')
else:
py.savefig('pic/sell_ft/'+self.stock+currentTime+'.png', format='png')
py.clf()
py.close()
def graphData(stock):
try:
stockFile = 'data.csv'
date, closep, highp, lowp, openp, volume = np.loadtxt(
stockFile,
delimiter=',',
unpack=True,
converters={0: mdates.strpdate2num('%Y%m%d')})
x = 0
y = len(date)
candleAr = []
while x < y:
appendLine = date[x], openp[x], closep[x], highp[x], lowp[
x], volume[x]
candleAr.append(appendLine)
x += 1
fig = plt.figure()
ax1 = plt.subplot2grid((5, 4), (0, 0), rowspan=4, colspan=4)
candlestick(ax1, candleAr, width=1, colorup='g', colordown='r')
ax1.grid(True)
ax1.xaxis.set_major_locator(mticker.MaxNLocator(10))
ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
plt.ylabel('Stock price')
ax2 = plt.subplot2grid((5, 4), (4, 0),
sharex=ax1,
rowspan=1,
colspan=4)
ax2.bar(date, volume, color='red', align='center')
ax2.grid(True)
plt.ylabel('Volume')
for label in ax2.xaxis.get_ticklabels():
label.set_rotation(45)
plt.xlabel('Date')
plt.suptitle(stock + ' Stock Price')
plt.setp(ax1.get_xticklabels(), visible=False)
plt.subplots_adjust(left=.09,
bottom=.18,
right=.94,
top=.94,
wspace=.20,
hspace=0)
plt.show()
except Exception, e:
print 'main loop', str(e)
def candleStickGraph(inputData):
fig = plt.figure()
fig.subplots_adjust(bottom=0.2)
ax = fig.add_subplot(111)
ax.set_xticklabels()
ax.set_title()
#ax.xaxis.set_minor_formatter(dayFormatter)
#plot_day_summary(ax, quotes, ticksize=3)
candlestick(ax, inputData, width=0.2)
ax.xaxis_date()
ax.autoscale_view()
plt.setp(plt.gca().get_xticklabels(), rotation=45, horizontalalignment='right')
def plotCandle(self,*args):
df = self.getData()
df['date'] = date2num(df.index)
fig, ax = subplots()
candlestick(ax, df[['date', 'Open', 'Close', 'High', 'Low']].values, width=.75, colorup='g',
colordown='r')
ax.xaxis_date()
plt.xlabel('Date')
#plt.suptitle(ticker)
ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
for label in ax.xaxis.get_ticklabels():
label.set_rotation(45)
ax.grid(True)
plt.show()
def plot(tickBarsPlot, ma, trades, plotCandle=True, plotMa=True):
# Create a numpy array for more manipulation flexibility
data = np.array(tickBarsPlot)
dataSwitched = data[:, 1][np.newaxis].T # Open
dataSwitched = np.append(dataSwitched, data[:, 4][np.newaxis].T, axis=1) # Close
dataSwitched = np.append(dataSwitched, data[:, 2][np.newaxis].T, axis=1) # High
dataSwitched = np.append(dataSwitched, data[:, 3][np.newaxis].T, axis=1) # Low
# This replaces the first column with numbers 0..size-1
data2 = np.append(np.arange(data[:,0].size)[:, np.newaxis], dataSwitched, axis=1)
data2tuple = [tuple(x) for x in data2]
# Chart ticks are on the hour
ticks = np.unique(np.trunc(data[:,0] / 10000), return_index=True)
fig = plt.figure(figsize=(10, 5))
# These numbers define margin from window edge
ax = fig.add_axes([0.1, 0.2, 0.85, 0.7])
ax.set_xticks(data2[ticks[1], 0])
ax.set_xticklabels(map(int, data[ticks[1], 0]), rotation=90)
# Plot prices
if plotCandle:
candlestick(ax, data2tuple, width=0.5, colorup='g', colordown='r')
else:
ax.plot(data[:,4])
# Plot moving average
if plotMa:
ax.plot(ma)
# Plot trades
buys = []
sells = []
for trade in trades:
timestampFloat = (float(trade.timestamp[0:2]) * 1000000 +
float(trade.timestamp[3:5]) * 10000 +
float(trade.timestamp[6:8]) * 100 +
float(trade.timestamp[9:11]))
if trade.quantity > 0:
buys.append(timestampFloat)
else:
sells.append(timestampFloat)
# Find index of buys in the data array before plotting
ix = np.where(np.in1d(data[:,0], buys))[0]
ax.plot(ix, data[:,4][ix], 'g^')
# Find index of sells in the data array before plotting
ix = np.where(np.in1d(data[:,0], sells))[0]
ax.plot(ix, data[:,4][ix], 'rv')
plt.show()
def graphData(stock):
try:
stockFile = stock+'.txt'
date, closep,highp,lowp,openp,volume = np.loadtxt(stockFile,delimiter=',',unpack=True,converters ={ 0: mdates.strpdate2num('%Y%m%d')})
x = 0
y = len(date)
candleAr = []
while x < y:
appendLine = date[x],openp[x],closep[x],highp[x],lowp[x],volume[x]
candleAr.append(appendLine)
x+=1
#
fig = plt.figure()
# ax1 = plot.subplot(2,1,1)#(2,3,1) would be position 1 in a 2 by 3 square
ax1 = plt.subplot2grid((5,4), (0,0), rowspan=4, colspan=4)
candlestick(ax1, candleAr, width=.75, colorup ='g', colordown='r')
ax1.grid(True)
ax1.xaxis.set_major_locator(mticker.MaxNLocator(10)) #max of 10 dates
ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
plt.ylabel('Stock price')
# ax2 = plt.subplot(2,1,2 sharex=ax1) #shares the zoomin
ax2 = plt.subplot2grid((5,4), (4,0), sharex=ax1, rowspan=1, colspan=4)
ax2.bar(date, volume)
ax2.axes.yaxis.set_ticklabels([])
ax2.grid(True)
plt.ylabel('Volume')
for label in ax2.xaxis.get_ticklabels():
label.set_rotation(45)
plt.xlabel('Date')
plt.ylabel('Stock Price')
plt.suptitle(stock+' Stock Price')
#ax1.axes.yaxis.set_visible(False) nope
#ax1.axes.xaxis.set_ticklabels([]) nope
plt.setp(ax1.get_xticklabels(), visible=False)
plt.subplots_adjust(left=.09,top = .94,bottom = .18, right = .94, wspace = .20, hspace = 0)
plt.show()
fig.savefig(stock+'.png')
except Exception,e:
print 'filed main loop',str(e)
def plot(self):
self.axes.clear()
self.axes.grid(True)
candlestick(self.axes, self.quotes, width=0.01)
self.axes.xaxis_date()
self.axes.autoscale_view()
x_labels = self.axes.get_xticklabels()
setp(x_labels, rotation=45, horizontalalignment='right')
if self.below_absolute_enabled:
self.axes.axhline(self.below_absolute_value)
if self.above_absolute_enabled:
self.axes.axhline(self.above_absolute_value)
self.draw()
def gpcs(series):
"""Function to plot a candle graph from a given series"""
"""takes as input the security code, default TY"""
from matplotlib.dates import DateFormatter, WeekdayLocator, HourLocator, \
DayLocator, MONDAY
from matplotlib.finance import quotes_historical_yahoo, candlestick,\
plot_day_summary, candlestick2
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = DayLocator() # minor ticks on the days
monthFormatter = DateFormatter('%b %d') # Eg, Jan 12
dayFormatter = DateFormatter('%d') # Eg, 12
#quotes contains a list of tuples:
#(date, open, close, high, low, volume)
quotes = series
if len(quotes) == 0:
today = datetime.datetime.now()
date2 = (today.year, today.month, today.day)
date1 = ( today.year -1, today.month, 1)
quotes = quotes_historical_yahoo('fut_code', date1, date2)
if len(quotes) == 0:
raise SystemExit
fig = figure()
fig.subplots_adjust(bottom=0.2)
ax = fig.add_subplot(111)
#ax.xaxis.set_major_locator(mondays)
#ax.xaxis.set_minor_locator(mondays)
#ax.xaxis.set_major_formatter(monthFormatter)
#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()
setp( gca().get_xticklabels(), rotation=45, horizontalalignment='right')
def draw_subgraph(self, stockdat, numt):
""" 绘制K线图 """
ohlc = list(
zip(np.arange(0, len(stockdat.index)), stockdat.Open,
stockdat.Close, stockdat.High, stockdat.Low)) #使用zip方法生成数据列表
mpf.candlestick(self.am, ohlc, width=0.5, colorup='r',
colordown='g') #绘制K线走势
''' 绘制均线 '''
self.am.plot(numt, stockdat['Ma20'], 'black', label='M20', lw=1.0)
self.am.plot(numt, stockdat['Ma60'], 'green', label='M60', lw=1.0)
self.am.plot(numt, stockdat['Ma120'], 'blue', label='M120', lw=1.0)
self.am.legend(loc='best', shadow=True, fontsize='10')
''' 绘制成交量 '''
self.vol.bar(numt,
stockdat.Volume,
color=[
'g' if stockdat.Open[x] > stockdat.Close[x] else 'r'
for x in range(0, len(stockdat.index))
])
''' 绘制MACD '''
#绘制BAR>0 柱状图
bar_red = np.where(stockdat['macd_bar'] > 0, 2 * stockdat['macd_bar'],
0)
#绘制BAR<0 柱状图
bar_green = np.where(stockdat['macd_bar'] < 0,
2 * stockdat['macd_bar'], 0)
self.macd.plot(numt, stockdat['macd_dif'], 'red',
label='macd dif') #dif
self.macd.plot(numt, stockdat['macd_dea'], 'blue',
label='macd dea') #dea
self.macd.bar(numt, bar_red, facecolor='red', label='hist bar')
self.macd.bar(numt, bar_green, facecolor='green', label='hist bar')
self.macd.legend(loc='best', shadow=True, fontsize='10')
#legend = self.macd.legend(loc='best',shadow=True, fontsize ='10')
#legend.get_frame().set_facecolor('#00FFCC')# Put a nicer background color on the legend.
#legend.get_title().set_fontsize(fontsize = 20)
''' 绘制KDJ '''
self.devol.plot(numt, stockdat['K'], 'blue', label='K') #K
self.devol.plot(numt, stockdat['D'], 'g--', label='D') #D
self.devol.plot(numt, stockdat['J'], 'r-', label='J') #J
self.devol.legend(loc='best', shadow=True, fontsize='10')
def draw_graph(quotes, title, bull_market):
if not hasattr(draw_graph, "fig"):
draw_graph.fig = figure() # it doesn't exist yet, so initialize it
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = DayLocator() # minor ticks on the days
weekFormatter = DateFormatter('%b %d') # Eg, Jan 12
dayFormatter = DateFormatter('%d') # Eg, 12
draw_graph.fig.clear()
graph = draw_graph.fig.add_subplot(111)
graph.xaxis.set_major_locator(mondays)
graph.xaxis.set_minor_locator(alldays)
graph.xaxis.set_major_formatter(weekFormatter)
graph.xaxis_date()
graph.autoscale_view()
candlestick(graph, quotes, width=0.6)
setp(gca().get_xticklabels(), rotation=45, horizontalalignment='right')
draw_graph.fig.suptitle(title + " " + str(bull_market), fontsize=12)
draw_graph.fig.subplots_adjust(bottom=0.2)
draw_graph.fig.canvas.mpl_connect('key_press_event', press)
draw_graph.fig.canvas.draw()
def save_candlestick_chart(fname, quotes):
'''
quotes should have the following format: [(date1, open1, close1, high1, low1), (date2, open2, ...), (...), ...]
'''
mondays = WeekdayLocator(MONDAY)
alldays = DayLocator()
weekFormatter = DateFormatter('%b %d')
fig = pl.figure()
fig.subplots_adjust(bottom=0.2)
ax = fig.add_subplot(111)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
candlestick(ax, quotes, width=0.6, colorup='g')
ax.xaxis_date()
ax.autoscale_view()
pl.setp(pl.gca().get_xticklabels(), rotation=45, horizontalalignment='right')
pl.savefig(fname)
def plot(self):
if len(self.tdata) > self.maxt: # roll the arrays
self.tdata = self.tdata[-self.maxt:]
self.sdata = self.sdata[-self.maxt:]
self.mdata = self.mdata[-self.maxt:]
self.result = self.result[-self.maxt:]
# Plot the next set of line data
line_min = Line2D(self.tdata, self.sdata, color='r')
self.ax.add_line(line_min)
line_max = Line2D(self.tdata, self.mdata, color='g')
self.ax.add_line(line_max)
# Plot the next set of candlestick data
candlestick(self.ax, self.result, width=60 / 86400.0, colorup='g', colordown='r')
# Update the x-axis time date and limits
if len(self.tdata) > 1:
self.ax.set_xlim(self.tdata[0], self.tdata[-1])
# Update the y-axis limits
self.ax.set_ylim(min(self.sdata) * 0.99, max(self.mdata) * 1.01)
def plot(tickBarsPlot, ma, trades, candle=False):
# Create a numpy array for more manipulation flexibility
data = np.array(tickBarsPlot)
# This replaces the first column with numbers 1..size
data2 = np.hstack([np.arange(data[:, 0].size)[:, np.newaxis], data[:, 1:]])
# Ticks are on the hour
ticks = np.unique(np.trunc(data[:, 0] / 10000), return_index=True)
fig = plt.figure(figsize=(10, 5))
# These numbers define margin from window edge
ax = fig.add_axes([0.1, 0.2, 0.85, 0.7])
ax.set_xticks(data2[ticks[1], 0])
ax.set_xticklabels(data[ticks[1], 0], rotation=90)
# Plot prices
if candle:
candlestick(ax, data2, width=0.5, colorup='g', colordown='r')
else:
ax.plot(data[:, 4])
# Plot moving average
ax.plot(ma)
# Plot trades
buys = []
sells = []
for trade in trades:
timestampFloat = float(trade.timestamp[0:2]) * 10000 + float(
trade.timestamp[3:5]) * 100 + float(trade.timestamp[6:8])
if trade.tradeQuantity > 0:
buys.append(timestampFloat)
else:
sells.append(timestampFloat)
# Find index of buys in the data array before plotting
ix = np.where(np.in1d(data[:, 0], buys))[0]
ax.plot(ix, data[:, 4][ix], 'g^')
# Find index of sells in the data array before plotting
ix = np.where(np.in1d(data[:, 0], sells))[0]
ax.plot(ix, data[:, 4][ix], 'rv')
plt.show()
def candlestick(self, index, open, high, low, close, width=0.3, secondary_y=False,
*args, **kwargs):
"""
Takes a df and plots a candlestick.
Will auto search for proper columns
"""
data = {}
data['open'] = open
data['high'] = high
data['low'] = low
data['close'] = close
df = pd.DataFrame(data, index=index)
self.add_data(df)
# grab merged data
xax = np.arange(len(self.df.index))
quotes = izip(xax, self.df['open'], self.df['close'], self.df['high'], self.df['low'])
ax = self.find_ax(secondary_y, kwargs)
self.setup_datetime(index)
candlestick(ax, quotes, width=width, colorup='g')
def save_candlestick_chart(fname, quotes):
'''
quotes should have the following format: [(date1, open1, close1, high1, low1), (date2, open2, ...), (...), ...]
'''
mondays = WeekdayLocator(MONDAY)
alldays = DayLocator()
weekFormatter = DateFormatter('%b %d')
fig = pl.figure()
fig.subplots_adjust(bottom=0.2)
ax = fig.add_subplot(111)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
candlestick(ax, quotes, width=0.6, colorup='g')
ax.xaxis_date()
ax.autoscale_view()
pl.setp(pl.gca().get_xticklabels(),
rotation=45,
horizontalalignment='right')
pl.savefig(fname)
def update(self, quotes, clear=False):
if clear:
# clear old data
self.ax.cla()
# axis formatting
d = []
for value in quotes:
data = value[0]
d.append(data)
self.ax.set_xlim([min(d), max(d) + 0.0010])
self.ax.xaxis.set_major_formatter(dates.DateFormatter('%H:%M:%S'))
# plot quotes
candlestick(self.ax, quotes, width=0.00005)
# more formatting
self.ax.xaxis_date()
self.ax.autoscale_view()
plt.setp(plt.gca().get_xticklabels(),
rotation=45,
horizontalalignment='right')
def update(self, quotes, clear=False):
if clear:
# clear old data
self.ax.cla()
# axis formatting
self.ax.xaxis.set_major_locator(mondays)
self.ax.xaxis.set_minor_locator(alldays)
self.ax.xaxis.set_major_formatter(weekFormatter)
# plot quotes
candlestick(self.ax, quotes, width=0.6)
# more formatting
self.ax.xaxis_date()
self.ax.autoscale_view()
plt.setp(plt.gca().get_xticklabels(),
rotation=45,
horizontalalignment='right')
# use draw() instead of show() to update the same window
plt.draw()
def generateGraph(self, quotes):
self.clearGraphData()
#print "DEBUG:"
#print "\tquotes = %s" % quotes
#for i in range(len(highs)):
# print "DEBUG: (%s, %s, %s, %s)" %(lows[i], opens[i], closes[i], highs[i])
# print "DEBUG: diffs h/l: %s o/c: %s" %(lows[i] - highs[i], opens[i] - closes[i])
self.ax = self.fig.add_subplot(111)
self.ax.set_title(_("Session candlestick graph"))
#Set axis labels and grid overlay properites
self.ax.set_xlabel(_("Sessions"), fontsize = 12)
self.ax.set_ylabel("$", fontsize = 12)
self.ax.grid(color='g', linestyle=':', linewidth=0.2)
candlestick(self.ax, quotes, width=0.50, colordown='r', colorup='g', alpha=1.00)
self.graphBox.add(self.canvas)
self.canvas.show()
self.canvas.draw()
def quote_track(stock_num):
from matplotlib.dates import DateFormatter, WeekdayLocator, DayLocator, MONDAY
from matplotlib.finance import quotes_historical_yahoo, candlestick
from matplotlib.font_manager import FontProperties
font = FontProperties(fname=r"c:\windows\fonts\simsun.ttc", size=18)
# 定义起始、终止日期和股票代码
date2 = datetime.date.today()
date1 = date2 - datetime.timedelta(days=30)
# 定义日期格式
mondays = WeekdayLocator(MONDAY)
alldays = DayLocator()
weekFormatter = DateFormatter('%b %d')
# 获取股票数据
quotes = quotes_historical_yahoo(stock_num, date1, date2)
if len(quotes) == 0:
raise SystemExit
print(quotes)
# 绘制蜡烛线或美国线
fig = figure()
fig.subplots_adjust(bottom=0.2)
ax = fig.add_subplot(111)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
#注释掉下面的其中一行，可以得到蜡烛线或美国线
candlestick(ax, quotes, width=0.6)
#plot_day_summary(ax, quotes, ticksize=3)
ax.xaxis_date()
ax.autoscale_view()
setp(gca().get_xticklabels(), rotation=45, horizontalalignment='right')
stockdata = get_stock_hexun(stock_num)
title(u'%s %s 昨收盘：%s 今开盘：%s 当前价：%s' %
(stock_num, stockdata['na'], stockdata['pc'], stockdata['op'],
stockdata['la']),
fontproperties=font)
show()
def main():
os.system('clear')
print('Program Start')
print('Scraping: NASDAQ for AAPL')
det_titles, det_open, det_high, det_low, det_close = stock_report()
print('Result: The following information has been pulled from NASDAQ')
prices = []
for detail_title, detail_open, detail_high, detail_low, detail_close in zip(det_titles, det_open, det_high, det_low, det_close):
date1 = detail_title
date1 = date2num(datetime.strptime(date1, '%b %d, %Y'))
tup = (date1, float(detail_open), float(detail_close), float(detail_high), float(detail_low))
prices.append(tup)
mondays = WeekdayLocator(MONDAY)
alldays = DayLocator()
weekFormatter = DateFormatter('%b %d')
dayFormatter = ('%d')
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)
candlestick(ax, prices, width=0.6)
ax.xaxis_date()
# ax.autoscale_view()
plt.setp(plt.gca().get_xticklabels(), rotation=45, horizontalalignment='right')
plt.show()
py.sign_in('chriskoh', 'yyy0hoavmt')
plot_url = py.plot_mpl(fig)
def showStock(stock_num, date1, date2):
# define the code number and begin end date
# date1 = ( 2012, 12, 25 )
# date2 = ( 2013, 6, 1 )
# stock_num = '000651.sz'
# define date format
# get the stock data
quotes = quotes_historical_yahoo(stock_num, date1, date2)
if len(quotes) == 0:
raise SystemExit
# draw k line of stock
fig = figure()
fig.subplots_adjust(bottom=0.2)
ax = fig.add_subplot(111)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
candlestick(ax, quotes, width=0.6)
# plot_day_summary(ax, quotes, ticksize=3)
ax.xaxis_date()
ax.autoscale_view()
setp(gca().get_xticklabels(), rotation=45, horizontalalignment='right')
title(u'2012,12,25-2013,6,1', fontproperties=font)
show()
def quote_track(stock_num):
from matplotlib.dates import DateFormatter, WeekdayLocator, DayLocator, MONDAY
from matplotlib.finance import quotes_historical_yahoo, candlestick
from matplotlib.font_manager import FontProperties
font = FontProperties(fname=r"c:\windows\fonts\simsun.ttc", size=18)
# 定义起始、终止日期和股票代码
date2 = datetime.date.today()
date1 = date2 - datetime.timedelta(days=30)
# 定义日期格式
mondays = WeekdayLocator(MONDAY)
alldays = DayLocator()
weekFormatter = DateFormatter('%b %d')
# 获取股票数据
quotes = quotes_historical_yahoo(stock_num, date1, date2)
if len(quotes) == 0:
raise SystemExit
print(quotes)
# 绘制蜡烛线或美国线
fig = figure()
fig.subplots_adjust(bottom=0.2)
ax = fig.add_subplot(111)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
#注释掉下面的其中一行，可以得到蜡烛线或美国线
candlestick(ax, quotes, width=0.6)
#plot_day_summary(ax, quotes, ticksize=3)
ax.xaxis_date()
ax.autoscale_view()
setp(gca().get_xticklabels(), rotation=45, horizontalalignment='right')
stockdata = get_stock_hexun(stock_num)
title(
u'%s %s 昨收盘：%s 今开盘：%s 当前价：%s' % (stock_num, stockdata['na'], stockdata['pc'], stockdata['op'], stockdata['la']),
fontproperties=font)
show()
def graphDataMACDRSI(stock, MA1, MA2, dateRange=365):
try:
stockFile = 'web2py/applications/blash/static/prices/' + stock + '.txt'
date, closep, highp, lowp, openp, volume = np.loadtxt(
stockFile,
delimiter=',',
unpack=True,
converters={0: mdates.strpdate2num('%Y%m%d')})
x = 0
y = len(date)
candleAr = []
#print date
while x < y:
appendLine = date[x], openp[x], closep[x], highp[x], lowp[
x], volume[x]
candleAr.append(appendLine)
x += 1
# using close data with either 12 or 26 day moving average
Av1 = movingaverage(closep, MA1)
Av2 = movingaverage(closep, MA2)
# Starting point of data since we need at least 12 or 26 data points to get an SMAS
SP = len(date[MA2 - 1:])
label1 = str(MA1) + ' SMA'
label2 = str(MA2) + ' SMA'
fig = plt.figure(facecolor='gray') # blue = '30414D'
# How many graphs appear on png, in this case, it has place for 2 and we are choosing slot 1
# ax1 = plt.subplot(2,1,1)
ax1 = plt.subplot2grid((6, 4), (1, 0),
rowspan=4,
colspan=4,
axisbg='#30414D')
#Black = #07000d Blue = #30414D
# Calling the Candlestick function made from the previous while loop
candlestick(ax1,
candleAr,
width=0.7,
colorup='#9eff15',
colordown='#ff1717')
# Graphing the date vs moving average starting from SP to current
ax1.plot(date[-SP:], Av1[-SP:], '#5998ff', label=label1, linewidth=1.5)
ax1.plot(date[-SP:], Av2[-SP:], '#e1edf9', label=label2, linewidth=1.5)
# Shows a max of 10 dates on x-axis, formats it it Year-Month-Day
#ax1.xaxis.set_major_locator(mticker.MaxNLocator(10))
#ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
ax1.yaxis.label.set_color("black")
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='black')
ax1.tick_params(axis='x', colors='black')
plt.ylabel('Stock price')
#ax1.set_xlim(left=735872.)
ax1.grid(True)
ax1.xaxis_date()
volumeMin = 0 #volume.min()
maLeg = plt.legend(loc=9, ncol=2, prop={'size': 10}, fancybox=True)
maLeg.get_frame().set_alpha(0.4)
textEd = pylab.gca().get_legend().get_texts()
pylab.setp(textEd[0:5], color='w')
ax0 = plt.subplot2grid((6, 4), (0, 0),
sharex=ax1,
rowspan=1,
colspan=4,
axisbg='#30414D')
rsi = rsiFunc(closep)
rsiBottomColor = 'green'
rsiTopColor = 'red'
ax0.plot(date, rsi, 'w', linewidth=1.5)
#ax0.axhline(70, color = rsiTopColor)
#ax0.axhline(70, color = rsiTopColor) # These did not work in mpld3
ax0.plot(date, constantFunc(70, date), 'red')
ax0.plot(date, constantFunc(30, date), color=rsiBottomColor)
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='x', colors='black')
ax0.tick_params(axis='y', colors='black')
ax0.set_yticks([30, 70])
ax0.yaxis.label.set_color('black')
ax0.xaxis_date()
#plt.gca().yaxis.set_major_locator(mticker.MaxNLocator(prune='both'))
plt.ylabel('RSI')
# Version 1.4: Volume Overlay
# -------------------------------------------------------------------------------------------
# Overlay, but it doesn't work in mpld3
'''
ax1v = ax1.twinx()
# Using the volumeMin to start as bottom, for stylistic purpose
ax1v.fill_between(date, volumeMin, volume, facecolor='#00ffe8', alpha=0.5)
ax1v.axes.yaxis.set_ticklabels([])
ax1v.grid(False)
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.set_ylim(0,5*volume.max())
ax1v.tick_params(axis='x', colors = 'black')
ax1v.tick_params(axis='y', colors = 'black')
'''
# Version 1.6: MACD
ax2 = plt.subplot2grid((6, 4), (5, 0),
sharex=ax1,
rowspan=1,
colspan=4,
axisbg='#30414D')
nslow = 26
nfast = 12
nema = 9
emaslow, emafast, macd = computeMACD(closep)
ema9 = ExpMovingAverage(macd, nema) # signal line
ax2.plot(date, macd, color='w', label='MACD')
ax2.plot(date, ema9, color='r', label='EMA')
ax2.plot(date, constantFunc(0, date), color='yellow')
ax2Legend = ax2.legend(loc='upper left',
ncol=2,
prop={'size': 8},
fancybox=True)
ax2Legend.get_frame().set_alpha(0.40)
ax2LegText = pylab.gca().get_legend().get_texts()
pylab.setp(ax2LegText[0:5], color='w')
#ax2.fill_between(date, macd-ema9, 0, alpha = 0.5, facecolor = 'red', edgecolor = 'w')
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='black')
ax2.tick_params(axis='y', colors='black')
ax2.xaxis.set_major_locator(mticker.MaxNLocator(5))
#ax2.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
ax2.xaxis_date()
for label in ax2.xaxis.get_ticklabels():
label.set_rotation(45)
plt.ylabel('MACD', color='black')
sortDate(date, dateRange)
# all adjustments on format of graph png
plt.subplots_adjust(left=.10,
bottom=.15,
right=.93,
top=.95,
wspace=.20,
hspace=0)
plt.xlabel('Date')
plt.suptitle(stock + ' Stock Price', color='black')
plt.setp(ax0.get_xticklabels(), visible=False)
plt.setp(ax1.get_xticklabels(), visible=False)
mpld3.save_html(
fig, 'web2py/applications/blash/static/prices/' + stock + '.html')
#pickle.dump(ax1, file(stock+'.pickle', 'w'))
#plt.show() # show the plot
#mpld3.show()
#fig.savefig('exampleRSI.png', facecolor=fig.get_facecolor())
except Exception, e:
print 'failed main loop', str(e)
quotes = _parse_delimited_data(_request())
ochl = np.array(
pd.DataFrame({
'0': range(1,
np.array(quotes['g1_o']).size + 1),
'1': np.array(quotes['g1_o']).astype(np.float),
'2': np.array(quotes['g1_c']).astype(np.float),
'3': np.array(quotes['g1_h']).astype(np.float),
'4': np.array(quotes['g1_l']).astype(np.float)
}))
quotes['g1_c'] = np.array(quotes['g1_c']).astype(np.float)
analysis = pd.DataFrame(index=quotes['date'])
analysis['sma_f'] = ta.SMA(quotes['g1_c'], SMA_FAST)
print analysis['sma_f']
analysis['sma_s'] = ta.SMA(quotes['g1_c'], SMA_SLOW)
print analysis['sma_s']
# Prepare plot
fig, ax = plt.subplots(1, 1, sharex=True)
ax.set_ylabel('SP500', size=20)
# Plot candles
candlestick(ax, ochl, width=0.5, colorup='g', colordown='r', alpha=1)
# Draw Moving Averages
analysis.sma_f.plot(c='g')
analysis.sma_s.plot(c='b')
# Show the picture!
plt.show()
def animate(i):
#Colors
green = "#53C156"
red = "#ff1717"
blue = "#3b5998"
macolor1 = "#e1edf9"
macolor2 = "#4ee6fd"
rsicolor = "#1a8762"
volumecolor = "#12e1b6"
macdcolor1 = "#4ee6fd"
macdcolor2 = "#e1edf9"
yellow = "#EDD415"
pink = "#E32DC2"
backgroundcolor = "#07001A"
bordercolor = "w"
ax1 = plt.subplot2grid((1,9), (0,0) ,colspan=8, axisbg=backgroundcolor)
ax1.clear()
candlestick(ax1, candleAr[-40:], width=.002, colorup = green, colordown = red)
ax1.tick_params(axis="x", colors="w")
ax1.grid(True, color = "w")
ax1.xaxis_date()
ax1.yaxis.label.set_color("w")
ax1.xaxis.label.set_color("w")
ax1.spines["bottom"].set_color(bordercolor)
ax1.spines["top"].set_color(bordercolor)
ax1.spines["left"].set_color(bordercolor)
ax1.spines["right"].set_color(bordercolor)
ax1.tick_params(axis="y", colors="w")
############
# Moving Average
############
smaTimePeriods = 15
dateAr = dateFunc()
sma = simpleMovingAverage(smaTimePeriods)
ax1.plot(dateAr[-40:],sma[-40:], color=macdcolor1,linewidth=1.5)
currentBid, currentBidVol, currentAsk, currentAskVol = bid_askTicker()
lastPrice = candleAr[-1]
lastPrice= lastPrice[2]
differenceAsk = currentAsk - lastPrice
differenceBid = lastPrice - currentBid
bidTxt ="Ask: \n%s" % round(currentAsk,2)
askTxt ="Bid: \n%s" % round(currentBid,2)
currentTimeText = "Current time: \n %s" % time.strftime('%H:%M:%S')
ax2 = plt.subplot2grid((1,9), (0,8), colspan=1, axisbg=backgroundcolor)
ax2.axis('off')
ax2.text(0.15,0.9,currentTimeText, color = "w",fontsize=20, )
ax2.text(0.15,0.7,bidTxt, color = green,fontsize=36, )
ax2.text(0.15,0.6,round(abs(differenceAsk),3), color = green,fontsize=20,)
ax2.text(0.15,0.5,lastPrice, color = "w", fontsize=36)
ax2.text(0.15,0.4,round(abs(differenceBid),3), color = red,fontsize=20,)
ax2.text(0.15,0.2,askTxt, color = red, fontsize=36, )
def graphData(stock,MA1,MA2):
try:
try:
print 'pulling data on',stock
urlToVisit = 'http://chartapi.finance.yahoo.com/instrument/1.0/'+stock+'/chartdata;type=quote;range=1y/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 organized pulled data'
except Exception, e:
print str(e), 'failed to pull price data'
date, closep, highp, lowp, openp, volume = np.loadtxt(stockFile,delimiter=',',unpack=True,converters={ 0: mdates.strpdate2num('%Y%m%d')})
### CANDLESTICK ###
x = 0
y = len(date)
candleAr = []
while x < y:
appendLine = date[x],openp[x],closep[x],highp[x],lowp[x],volume[x]
candleAr.append(appendLine)
x+=1
Av1 = movingaverage(closep, MA1)
Av2 = movingaverage(closep, MA2)
SP = len(date[MA2-1:])
label1=str(MA1)+' SMA'
label2=str(MA2)+' SMA'
fig = plt.figure(facecolor='#07000d')
ax1 = plt.subplot2grid((6,4), (1,0), rowspan=4, colspan=4, axisbg='#07000d')
candlestick(ax1, candleAr[-SP:], width=1, colorup='#53c156', colordown='#ff1717')
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'))
plt.gca().yaxis.set_major_locator(mticker.MaxNLocator(prune='both'))
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.ylabel('Stock price')
### LEGEND ###
maLeg = plt.legend(loc=9, ncol=2, prop={'size': 7}, fancybox=True, borderaxespad=0.)
maLeg.get_frame().set_alpha(0.4)
textEd = pylab.gca().get_legend().get_texts()
pylab.setp(textEd[0:5], color = 'w')
### RELATIVE STRENGTH INDEX ###
ax0 = plt.subplot2grid((6,4), (0,0), sharex=ax1, rowspan=1, colspan=4, axisbg='#07000d')
rsiCol = '#c1f9f7'
posCol = '#386d14'
negCol = '#5f2020'
midCol = '#bdbdb1'
rsi = rsiFunc(closep)
ax0.plot(date[-SP:],rsi[-SP:],rsiCol,linewidth=1.5)
ax0.axhline(70, color = negCol)
ax0.axhline(30, color = posCol)
ax0.axhline(50, color = midCol)
ax0.fill_between(date[-SP:],rsi[-SP:], 70, where=(rsi[-SP:]>=70), facecolor=negCol, edgecolor=negCol)
ax0.fill_between(date[-SP:],rsi[-SP:], 30, where=(rsi[-SP:]<=30), facecolor=posCol, edgecolor=posCol)
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.text(0.015, 0.95, 'RSI (14)', va='top', color='w', transform=ax0.transAxes)
ax0.tick_params(axis='x', colors='w')
ax0.tick_params(axis='y', colors='w')
ax0.set_yticks([30,70])
ax0.yaxis.label.set_color('w')
#plt.gca().yaxis.set_major_locator(mticker.MaxNLocator(prune='lower'))
### VOLUME ###
volumeMin = 0
ax1v = ax1.twinx()
ax1v.fill_between(date[-SP:],volumeMin, volume[-SP:], facecolor='#00ffe8', alpha=.5)
ax1v.axes.yaxis.set_ticklabels([])
ax1v.grid(False)
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.set_ylim(0, 2*volume.max())
ax1v.tick_params(axis='x', colors='w')
ax1v.tick_params(axis='y', colors='w')
### MACD ###
ax2 = plt.subplot2grid((6,4), (5,0), sharex=ax1, rowspan=1, colspan=4, axisbg='#07000d')
fillcolor = '#00ffe8'
nslow = 26
nfast = 12
nema = 9
emaslow, emafast, macd = computeMACD(closep)
ema9 = ExpMovingAverage(macd, nema)
ax2.plot(date[-SP:], macd[-SP:], color='#e1edf9', lw=2)
ax2.plot(date[-SP:], ema9[-SP:], color='#4eeffd', lw=1)
ax2.fill_between(date[-SP:], macd[-SP:] -ema9[-SP:], 0, alpha=0.5, facecolor=fillcolor, edgecolor=fillcolor)
ax2.text(0.015, 0.95, 'MACD (12, 26, 9)', va='top', color='w', transform=ax2.transAxes)
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 + ' Stock Price', color='w')
plt.setp(ax0.get_xticklabels(), visible=False)
plt.setp(ax1.get_xticklabels(), visible=False)
plt.subplots_adjust(left=.09, bottom=.14, right=.94, top=.95, wspace=.20, hspace=.00)
plt.show()
fig.savefig(stock + '.png',facecolor=fig.get_facecolor())
def _plot(data, ax, **kwds):
candles = candlestick(ax, data.values, **kwds)
return candles
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(ax1,
newAr[-SP:],
width=.6,
colorup='#53c156',
colordown='#ff1717')
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")
date1 = ( 2004, 2, 1)
date2 = ( 2004, 4, 12 )
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = 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)
if len(quotes) == 0:
raise SystemExit
fig = figure()
fig.subplots_adjust(bottom=0.2)
ax = fig.add_subplot(111)
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()
setp( gca().get_xticklabels(), rotation=45, horizontalalignment='right')
show()
def graphData(stock, MA1, MA2):
#######################################
#######################################
'''
Use this to dynamically pull a stock:
'''
try:
print('Currently Pulling', stock)
netIncomeAr = []
revAr = []
ROCAr = []
endLink = 'sort_order=asc&auth_token=a3fpXxHfsiN7AF4gjakQ'
try:
print('running urlopen')
netIncome = urlopen(
'http://www.quandl.com/api/v1/datasets/OFDP/DMDRN_' +
stock.upper() + '_NET_INC.csv?&' + endLink).read()
revenue = urlopen(
'http://www.quandl.com/api/v1/datasets/OFDP/DMDRN_' +
stock.upper() + '_REV_LAST.csv?&' + endLink).read()
ROC = urlopen('http://www.quandl.com/api/v1/datasets/OFDP/DMDRN_' +
stock.upper() + '_ROC.csv?&' + endLink).read()
print('GOT HERE 1')
splitNI = netIncome.split('\n')
print('Net Income:')
for eachNI in splitNI[1:-1]:
print(eachNI)
netIncomeAr.append(eachNI)
print('_________')
splitRev = revenue.split('\n')
print('Revenue:')
for eachRev in splitRev[1:-1]:
print(eachRev)
revAr.append(eachRev)
print('_________')
splitROC = ROC.split('\n')
print('Return on Capital:')
for eachROC in splitROC[1:-1]:
print(eachROC)
ROCAr.append(eachROC)
incomeDate, income = np.loadtxt(
netIncomeAr,
delimiter=',',
unpack=True,
converters={0: mdates.strpdate2num('%Y-%m-%d')})
revDate, revenue = np.loadtxt(
revAr,
delimiter=',',
unpack=True,
converters={0: mdates.strpdate2num('%Y-%m-%d')})
rocDate, ROC = np.loadtxt(
ROCAr,
delimiter=',',
unpack=True,
converters={0: mdates.strpdate2num('%Y-%m-%d')})
except Exception:
print('failed in the quandl grab')
print(str(Exception))
time.sleep(555)
print(
str(
datetime.datetime.fromtimestamp(int(
time.time())).strftime('%Y-%m-%d %H:%M:%S')))
#Keep in mind this is close high low open, lol.
urlToVisit = 'http://chartapi.finance.yahoo.com/instrument/1.0/' + stock + '/chartdata;type=quote;range=10y/csv'
stockFile = []
try:
sourceCode = 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:
print(str(e), 'failed to organize pulled data.')
except Exception:
print(str(Exception), '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((9, 4), (1, 0),
rowspan=4,
colspan=4,
axisbg='#07000d')
candlestick(ax1,
newAr[-SP:],
width=.6,
colorup='#53c156',
colordown='#ff1717')
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'))
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 = pylab.gca().get_legend().get_texts()
pylab.setp(textEd[0:5], color='w')
volumeMin = 0
ax0 = plt.subplot2grid((9, 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)
###Edit this to 3, so it's a bit larger
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((9, 4), (5, 0),
sharex=ax1,
rowspan=1,
colspan=4,
axisbg='#07000d')
fillcolor = '#00ffe8'
nslow = 26
nfast = 12
nema = 9
emaslow, emafast, macd = computeMACD(closep)
ema9 = ExpMovingAverage(macd, nema)
ax2.plot(date[-SP:], macd[-SP:], color='#4ee6fd', lw=2)
ax2.plot(date[-SP:], ema9[-SP:], color='#e1edf9', lw=1)
ax2.fill_between(date[-SP:],
macd[-SP:] - ema9[-SP:],
0,
alpha=0.5,
facecolor=fillcolor,
edgecolor=fillcolor)
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')
plt.ylabel('MACD', color='w')
ax2.yaxis.set_major_locator(mticker.MaxNLocator(nbins=5,
prune='upper'))
######################################
######################################
ax3 = plt.subplot2grid((9, 4), (6, 0),
sharex=ax1,
rowspan=1,
colspan=4,
axisbg='#07000d')
ax3.plot(incomeDate, income, '#4ee6fd')
ax3.spines['bottom'].set_color("#5998ff")
ax3.spines['top'].set_color("#5998ff")
ax3.spines['left'].set_color("#5998ff")
ax3.spines['right'].set_color("#5998ff")
ax3.tick_params(axis='x', colors='w')
ax3.tick_params(axis='y', colors='w')
ax3.yaxis.set_major_locator(mticker.MaxNLocator(nbins=4,
prune='upper'))
plt.ylabel('NI', color='w')
ax4 = plt.subplot2grid((9, 4), (7, 0),
sharex=ax1,
rowspan=1,
colspan=4,
axisbg='#07000d')
ax4.plot(revDate, revenue, '#4ee6fd')
ax4.spines['bottom'].set_color("#5998ff")
ax4.spines['top'].set_color("#5998ff")
ax4.spines['left'].set_color("#5998ff")
ax4.spines['right'].set_color("#5998ff")
ax4.tick_params(axis='x', colors='w')
ax4.tick_params(axis='y', colors='w')
ax4.yaxis.set_major_locator(mticker.MaxNLocator(nbins=4,
prune='upper'))
plt.ylabel('Rev', color='w')
ax5 = plt.subplot2grid((9, 4), (8, 0),
rowspan=1,
sharex=ax1,
colspan=4,
axisbg='#07000d')
ax5.plot(rocDate, ROC, '#4ee6fd')
ax5.spines['bottom'].set_color("#5998ff")
ax5.spines['top'].set_color("#5998ff")
ax5.spines['left'].set_color("#5998ff")
ax5.spines['right'].set_color("#5998ff")
ax5.tick_params(axis='x', colors='w')
ax5.tick_params(axis='y', colors='w')
ax5.yaxis.set_major_locator(mticker.MaxNLocator(nbins=4,
prune='upper'))
plt.ylabel('ROC', color='w')
for label in ax5.xaxis.get_ticklabels():
label.set_rotation(45)
plt.suptitle(stock, color='w')
plt.setp(ax0.get_xticklabels(), visible=False)
### add this ####
plt.setp(ax1.get_xticklabels(), visible=False)
plt.setp(ax2.get_xticklabels(), visible=False)
plt.setp(ax3.get_xticklabels(), visible=False)
plt.setp(ax4.get_xticklabels(), visible=False)
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:
print('main loop', str(Exception))
# Tick locator and formatter
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('%Y-%m-%d') # e.g., 12
#dayFormatter = DateFormatter('%b %d %Y')
# Plot
fig = plt.figure(facecolor='#07000d')
ax1 = plt.subplot2grid((4,4), (0,0), rowspan=3, colspan=4, axisbg='#07000d')
ax1.grid(True, color='w')
#fig.autofmt_xdate()
ax1.plot(ind, uband, '#2E2EFE', label='Bollinger Band')
ax1.plot(ind, lband, '#2E2EFE')
ax1.plot(ind, mavg, '#FE9A2E', label='SMA')
candlestick(ax1, dataAr, width=0.8, colorup='#9eff15', colordown='#ff1717')
# Convert back to date
ax1.xaxis.set_major_formatter(ticker.FuncFormatter(format_date))
# Axis and tick setting
ax1.yaxis.label.set_color('w')
ax1.yaxis.set_major_formatter(ticker.FormatStrFormatter('%.2f'))
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')
# Legend
leg1 = ax1.legend(loc=2, prop={'size':8})
for text in leg1.get_texts():
text.set_color('w')
frame1 = leg1.get_frame()