ChartDirector 7.0 (Python Edition)

Finance Chart (2)




This example demonstrate creating a full-featured finance chart, with candlesticks, moving averages, Donchian channel, volume bars, MACD and Stochastic indicators.

This example employs the FinanceChart library add-on to allow complex financial charts to be composed easily. In this example, the key steps are:

For simplicity and to allow this example to run without connecting to a real database, a RanTable object is used to simulate the data. RanTable is a ChartDirector utility class used for creating tables with random numbers.

Source Code Listing

pythondemo\finance2.py
#!/usr/bin/python # The ChartDirector for Python module is assumed to be in "../lib" import sys, os sys.path.insert(0, os.path.join(os.path.abspath(sys.path[0]), "..", "lib")) from FinanceChart import * # Create a finance chart demo containing 100 days of data noOfDays = 100 # To compute moving averages starting from the first day, we need to get extra data points before # the first day extraDays = 30 # In this exammple, we use a random number generator utility to simulate the data. We set up the # random table to create 6 cols x (noOfDays + extraDays) rows, using 9 as the seed. rantable = RanTable(9, 6, noOfDays + extraDays) # Set the 1st col to be the timeStamp, starting from Sep 4, 2002, with each row representing one # day, and counting week days only (jump over Sat and Sun) rantable.setDateCol(0, chartTime(2002, 9, 4), 86400, 1) # Set the 2nd, 3rd, 4th and 5th columns to be high, low, open and close data. The open value starts # from 100, and the daily change is random from -5 to 5. rantable.setHLOCCols(1, 100, -5, 5) # Set the 6th column as the vol data from 5 to 25 million rantable.setCol(5, 50000000, 250000000) # Now we read the data from the table into arrays timeStamps = rantable.getCol(0) highData = rantable.getCol(1) lowData = rantable.getCol(2) openData = rantable.getCol(3) closeData = rantable.getCol(4) volData = rantable.getCol(5) # Create a FinanceChart object of width 640 pixels c = FinanceChart(640) # Add a title to the chart c.addTitle("Finance Chart Demonstration") # Set the data into the finance chart object 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 c.makeChart("finance2.png")