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
Exemple #2
0
# 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 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 HLOC symbols to the main chart, using green/red for up/down days
c.addHLOC(0x008000, 0xcc0000)

# 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 12-days momentum indicator chart (75 pixels high) using blue (0000ff) color.
c.addTitle("Finance Chart Demonstration")

# 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 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 HLOC symbols to the main chart, using green/red for up/down days
c.addHLOC(0x008000, 0xcc0000)

# 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)
c.addTitle("Finance Chart Demonstration")

# 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 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 HLOC symbols to the main chart, using green/red for up/down days
c.addHLOC('0x008000', '0xcc0000')

# 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')