def drawChart():
global timeStamps, volData, highData, lowData, openData, closeData
global compareData, resolution
# In this demo, we just assume we plot up to the latest time. So end date is now.
endDate = chartTime2(time.time())
# If the trading day has not yet started (before 9:30am), or if the end date is on on Sat or
# Sun, we set the end date to 4:00pm of the last trading day
while (endDate % 86400 < 9 * 3600 + 30 * 60) or (
getChartWeekDay(endDate) == 0) or (getChartWeekDay(endDate) == 6):
endDate = endDate - endDate % 86400 - 86400 + 16 * 3600
# The duration selected by the user
durationInDays = int(query["TimeRange"].value)
# Compute the start date by subtracting the duration from the end date.
startDate = endDate
if durationInDays >= 30:
# More or equal to 30 days - so we use months as the unit
YMD = getChartYMD(endDate)
startMonth = int(YMD / 100) % 100 - int(durationInDays / 30)
startYear = int(YMD / 10000)
while startMonth < 1:
startYear = startYear - 1
startMonth = startMonth + 12
startDate = chartTime(startYear, startMonth, 1)
else:
# Less than 30 days - use day as the unit. The starting point of the axis is always at the
# start of the day (9:30am). Note that we use trading days, so we skip Sat and Sun in
# counting the days.
startDate = endDate - endDate % 86400 + 9 * 3600 + 30 * 60
for i in range(1, durationInDays):
if getChartWeekDay(startDate) == 1:
startDate = startDate - 3 * 86400
else:
startDate = startDate - 86400
# The moving average periods selected by the user.
avgPeriod1 = 0
try:
avgPeriod1 = int(query["movAvg1"].value)
except:
pass
avgPeriod2 = 0
try:
avgPeriod2 = int(query["movAvg2"].value)
except:
pass
if avgPeriod1 < 0:
avgPeriod1 = 0
elif avgPeriod1 > 300:
avgPeriod1 = 300
if avgPeriod2 < 0:
avgPeriod2 = 0
elif avgPeriod2 > 300:
avgPeriod2 = 300
# We need extra leading data points in order to compute moving averages.
extraPoints = 20
if avgPeriod1 > extraPoints:
extraPoints = avgPeriod1
if avgPeriod2 > extraPoints:
extraPoints = avgPeriod2
# Get the data series to compare with, if any.
compareKey = string.strip(query["CompareWith"].value)
compareData = None
if getData(compareKey, startDate, endDate, durationInDays, extraPoints):
compareData = closeData
# The data series we want to get.
tickerKey = string.strip(query["TickerSymbol"].value)
if not getData(tickerKey, startDate, endDate, durationInDays, extraPoints):
return errMsg("Please enter a valid ticker symbol")
# We now confirm the actual number of extra points (data points that are before the start date)
# as inferred using actual data from the database.
extraPoints = len(timeStamps)
for i in range(0, len(timeStamps)):
if timeStamps[i] >= startDate:
extraPoints = i
break
# Check if there is any valid data
if extraPoints >= len(timeStamps):
# No data - just display the no data message.
return errMsg("No data available for the specified time period")
# In some finance chart presentation style, even if the data for the latest day is not fully
# available, the axis for the entire day will still be drawn, where no data will appear near the
# end of the axis.
if resolution < 86400:
# Add extra points to the axis until it reaches the end of the day. The end of day is
# assumed to be 16:00 (it depends on the stock exchange).
lastTime = timeStamps[len(timeStamps) - 1]
extraTrailingPoints = int((16 * 3600 - lastTime % 86400) / resolution)
for i in range(0, extraTrailingPoints):
timeStamps.append(lastTime + resolution * (i + 1))
#
# At this stage, all data are available. We can draw the chart as according to user input.
#
#
# Determine the chart size. In this demo, user can select 4 different chart sizes. Default is
# the large chart size.
#
width = 780
mainHeight = 255
indicatorHeight = 80
size = query["ChartSize"].value
if size == "S":
# Small chart size
width = 450
mainHeight = 160
indicatorHeight = 60
elif size == "M":
# Medium chart size
width = 620
mainHeight = 215
indicatorHeight = 70
elif size == "H":
# Huge chart size
width = 1000
mainHeight = 320
indicatorHeight = 90
# Create the chart object using the selected size
m = FinanceChart(width)
# Set the data into the chart object
m.setData(timeStamps, highData, lowData, openData, closeData, volData,
extraPoints)
#
# We configure the title of the chart. In this demo chart design, we put the company name as the
# top line of the title with left alignment.
#
m.addPlotAreaTitle(TopLeft, tickerKey)
# We displays the current date as well as the data resolution on the next line.
resolutionText = ""
if resolution == 30 * 86400:
resolutionText = "Monthly"
elif resolution == 7 * 86400:
resolutionText = "Weekly"
elif resolution == 86400:
resolutionText = "Daily"
elif resolution == 900:
resolutionText = "15-min"
m.addPlotAreaTitle(
BottomLeft, "<*font=arial.ttf,size=8*>%s - %s chart" % (m.formatValue(
chartTime2(time.time()), "mmm dd, yyyy"), resolutionText))
# A copyright message at the bottom left corner the title area
m.addPlotAreaTitle(
BottomRight,
"<*font=arial.ttf,size=8*>(c) Advanced Software Engineering")
#
# Add the first techical indicator according. In this demo, we draw the first indicator on top
# of the main chart.
#
addIndicator(m, query["Indicator1"].value, indicatorHeight)
#
# Add the main chart
#
m.addMainChart(mainHeight)
#
# Set log or linear scale according to user preference
#
if query["LogScale"].value == "1":
m.setLogScale(1)
#
# Set axis labels to show data values or percentage change to user preference
#
if query["PercentageScale"].value == "1":
m.setPercentageAxis()
#
# Draw any price line the user has selected
#
mainType = query["ChartType"].value
if mainType == "Close":
m.addCloseLine(0x000040)
elif mainType == "TP":
m.addTypicalPrice(0x000040)
elif mainType == "WC":
m.addWeightedClose(0x000040)
elif mainType == "Median":
m.addMedianPrice(0x000040)
#
# Add comparison line if there is data for comparison
#
if compareData != None:
if len(compareData) > extraPoints:
m.addComparison(compareData, 0x0000ff, compareKey)
#
# Add moving average lines.
#
addMovingAvg(m, query["avgType1"].value, avgPeriod1, 0x663300)
addMovingAvg(m, query["avgType2"].value, avgPeriod2, 0x9900ff)
#
# Draw candlesticks or OHLC symbols if the user has selected them.
#
if mainType == "CandleStick":
m.addCandleStick(0x33ff33, 0xff3333)
elif mainType == "OHLC":
m.addHLOC(0x008800, 0xcc0000)
#
# Add parabolic SAR if necessary
#
if query["ParabolicSAR"].value == "1":
m.addParabolicSAR(0.02, 0.02, 0.2, DiamondShape, 5, 0x008800, 0x000000)
#
# Add price band/channel/envelop to the chart according to user selection
#
bandType = query["Band"].value
if bandType == "BB":
m.addBollingerBand(20, 2, 0x9999ff, 0xc06666ff)
elif bandType == "DC":
m.addDonchianChannel(20, 0x9999ff, 0xc06666ff)
elif bandType == "Envelop":
m.addEnvelop(20, 0.1, 0x9999ff, 0xc06666ff)
#
# Add volume bars to the main chart if necessary
#
if query["Volume"].value == "1":
m.addVolBars(indicatorHeight, 0x99ff99, 0xff9999, 0xc0c0c0)
#
# Add additional indicators as according to user selection.
#
addIndicator(m, query["Indicator2"].value, indicatorHeight)
addIndicator(m, query["Indicator3"].value, indicatorHeight)
addIndicator(m, query["Indicator4"].value, indicatorHeight)
return m
c.setData(timeStamps, highData, lowData, openData, closeData, volData, extraDays)
# Add a slow stochastic chart (75 pixels high) with %K = 14 and %D = 3
c.addSlowStochastic(75, 14, 3, 0x006060, 0x606000)
# Add the main chart with 240 pixels in height
c.addMainChart(240)
# Add a 10 period simple moving average to the main chart, using brown color
c.addSimpleMovingAvg(10, 0x663300)
# Add a 20 period simple moving average to the main chart, using purple color
c.addSimpleMovingAvg(20, 0x9900ff)
# Add candlestick symbols to the main chart, using green/red for up/down days
c.addCandleStick(0x00ff00, 0xff0000)
# Add 20 days donchian channel to the main chart, using light blue (9999ff) as the
# border and semi-transparent blue (c06666ff) as the fill color
c.addDonchianChannel(20, 0x9999ff, 0xc06666ff)
# Add a 75 pixels volume bars sub-chart to the bottom of the main chart, using
# green/red/grey for up/down/flat days
c.addVolBars(75, 0x99ff99, 0xff9999, 0x808080)
# Append a MACD(26, 12) indicator chart (75 pixels high) after the main chart, using
# 9 days for computing divergence.
c.addMACD(75, 26, 12, 9, 0x0000ff, 0xff00ff, 0x008000)
# Output the chart
print("Content-type: image/png\n")
# Add sell signal symbols to the main chart, using purple (0x9900cc) downward pointing arrows as
# symbols
sellLayer = mainChart.addScatterLayer(None, sellSignal, "Sell",
ArrowShape(180, 1, 0.4, 0.4), 11,
0x9900cc)
# Shift the symbol higher by 20 pixels
sellLayer.getDataSet(0).setSymbolOffset(0, -20)
# Add a 5 period simple moving average to the main chart, using brown color
c.addSimpleMovingAvg(5, 0x663300)
# Add a 20 period simple moving average to the main chart, using purple color
c.addSimpleMovingAvg(20, 0x9900ff)
# Add candlestick symbols to the main chart, using green/red for up/down days
c.addCandleStick(0x66ff66, 0xff6666)
# Add a volume indicator chart (75 pixels high) after the main chart, using green/red/grey for
# up/down/flat days
c.addVolIndicator(75, 0x99ff99, 0xff9999, 0x808080)
# Append a 14-days RSI indicator chart (75 pixels high) after the main chart. The main RSI line is
# purple (800080). Set threshold region to +/- 20 (that is, RSI = 50 +/- 25). The upper/lower
# threshold regions will be filled with red (ff0000)/blue (0000ff).
c.addRSI(75, 14, 0x800080, 20, 0xff0000, 0x0000ff)
# Output the chart
print("Content-type: image/png\n")
binaryPrint(c.makeChart2(PNG))
# Set the data into the finance chart object
c.setData(timeStamps, highData, lowData, openData, closeData, volData,
extraDays)
# Add the main chart with 240 pixels in height
c.addMainChart(240)
# Add a 10 period simple moving average to the main chart, using brown color
c.addSimpleMovingAvg(10, 0x663300)
# Add a 20 period simple moving average to the main chart, using purple color
c.addSimpleMovingAvg(20, 0x9900ff)
# Add candlestick symbols to the main chart, using green/red for up/down days
c.addCandleStick(0x00ff00, 0xff0000)
# Add 20 days bollinger band to the main chart, using light blue (9999ff) as the border and
# semi-transparent blue (c06666ff) as the fill color
c.addBollingerBand(20, 2, 0x9999ff, 0xc06666ff)
# Add a 75 pixels volume bars sub-chart to the bottom of the main chart, using green/red/grey for
# up/down/flat days
c.addVolBars(75, 0x99ff99, 0xff9999, 0x808080)
# Append a 14-days RSI indicator chart (75 pixels high) after the main chart. The main RSI line is
# purple (800080). Set threshold region to +/- 20 (that is, RSI = 50 +/- 25). The upper/lower
# threshold regions will be filled with red (ff0000)/blue (0000ff).
c.addRSI(75, 14, 0x800080, 20, 0xff0000, 0x0000ff)
# Append a MACD(26, 12) indicator chart (75 pixels high) after the main chart, using 9 days for
#c = FinanceChart(1024)
c = FinanceChart(2200)
# Add a title to the chart
c.addTitle("Basket Divergences - %s" % trade_date.strftime('%D (%a)'))
# Set the data into the finance chart object
c.setData(ts, es_high, es_low, es_open, es_close, es_vol, None)
# Add the main chart with 240 pixels in height
es_chart = c.addMainChart(600)
# Add HLOC symbols to the main chart, using green/red for up/down days
#c.addHLOC('0x008000', '0xcc0000')
c.addCandleStick('0x008000', '0xcc0000')
# Add a 75 pixels volume bars sub-chart to the bottom of the main chart, using
# green/red/grey for up/down/flat days
#c.addVolBars(75, '0x99ff99', '0xff9999', '0x808080')
#c.addVolIndicator(75, '0x99ff99', '0xff9999', '0x808080')
# Add the evolving high and low as line indicators to the chart
hod = [max(es_high[:i+1]) for i, v in enumerate(es_high)]
lod = [min(es_low[:i+1]) for i, v in enumerate(es_low)]
c.addLineIndicator2(es_chart, hod, '0xFF6600', 'HOD')
c.addLineIndicator2(es_chart, lod, '0xFF6600', 'LOD')
# Initial Balance High and Low
ib_high = [NoValue for x in xrange(60)] + [max(es_high[:60]) for x in xrange(390-60)]
ib_low = [NoValue for x in xrange(60)] + [min(es_low[:60]) for x in xrange(390-60)]
