ChartDirector Ver 5.0 (Python Edition)

Scattered Data Contour Chart




This example demonstrates using scattered data for the contour layer.

In previous contour chart examples, the data are gridded, which means the data points lie on a rectangular grid.

ChartDirector also supports scattered data points, which means the data points can be at arbitrary positions. In this example, in additional to a contour layer added using XYChart.addContourLayer, there is also a scatter layer added using XYChart.addScatterLayer to show the positions of the data points.

Source Code Listing

[Standalone Version] pythondemo\scattercontour.py
#!/usr/bin/python
from pychartdir import *

# The (x, y, z) coordinates of the scattered data
dataX = [0.5, 1.9, 4.9, 1.0, 8.9, 9.8, 5.9, 2.9, 6.8, 9.0, 0.0, 8.9, 1.9, 4.8, 2.4,
    3.4, 7.9, 7.5, 4.8, 7.5, 9.5, 0.4, 8.9, 0.9, 5.4, 9.4, 2.9, 8.9, 0.9, 8.9, 10.0,
    1.0, 6.8, 3.8, 9.0, 5.3, 6.4, 4.9, 4.5, 2.0, 5.4, 0.0, 10.0, 3.9, 5.4, 5.9, 5.8,
    0.3, 4.4, 8.3]
dataY = [3.3, 3.0, 0.7, 1.0, 9.3, 4.5, 8.4, 0.1, 0.8, 0.1, 9.3, 1.8, 4.3, 1.3, 2.3,
    5.4, 6.9, 9.0, 9.8, 7.5, 1.8, 1.4, 4.5, 7.8, 3.8, 4.0, 2.9, 2.4, 3.9, 2.9, 2.3,
    9.3, 2.0, 3.4, 4.8, 2.3, 3.4, 2.3, 1.5, 7.8, 4.5, 0.9, 6.3, 2.4, 6.9, 2.8, 1.3,
    2.9, 6.4, 6.3]
dataZ = [6.6, 12.5, 7.4, 6.2, 9.6, 13.6, 19.9, 2.2, 6.9, 3.4, 8.7, 8.4, 7.8, 8.0,
    9.4, 11.9, 9.6, 15.7, 12.0, 13.3, 9.6, 6.4, 9.0, 6.9, 4.6, 9.7, 10.6, 9.2, 7.0,
    6.9, 9.7, 8.6, 8.0, 13.6, 13.2, 5.9, 9.0, 3.2, 8.3, 9.7, 8.2, 6.1, 8.7, 5.6,
    14.9, 9.8, 9.3, 5.1, 10.8, 9.8]

# Create a XYChart object of size 450 x 540 pixels
c = XYChart(450, 540)

# Add a title to the chart using 15 points Arial Italic font
c.addTitle("      Contour Chart with Scattered Data", "ariali.ttf", 15)

# Set the plotarea at (65, 40) and of size 360 x 360 pixels. Use semi-transparent
# black (c0000000) for both horizontal and vertical grid lines
c.setPlotArea(65, 40, 360, 360, -1, -1, -1, '0xc0000000', -1)

# Set x-axis and y-axis title using 12 points Arial Bold Italic font
c.xAxis().setTitle("X-Axis Title Place Holder", "arialbi.ttf", 10)
c.yAxis().setTitle("Y-Axis Title Place Holder", "arialbi.ttf", 10)

# Set x-axis and y-axis labels to use Arial Bold font
c.xAxis().setLabelStyle("arialbd.ttf")
c.yAxis().setLabelStyle("arialbd.ttf")

# When x-axis and y-axis color to transparent
c.xAxis().setColors(Transparent)
c.yAxis().setColors(Transparent)

# Add a scatter layer to the chart to show the position of the data points
c.addScatterLayer(dataX, dataY, "", Cross2Shape(0.2), 7, '0x000000')

# Add a contour layer using the given data
layer = c.addContourLayer(dataX, dataY, dataZ)

# Move the grid lines in front of the contour layer
c.getPlotArea().moveGridBefore(layer)

# Add a color axis (the legend) in which the top center is anchored at (245, 455).
# Set the length to 330 pixels and the labels on the top side.
cAxis = layer.setColorAxis(245, 455, TopCenter, 330, Top)

# Add a bounding box to the color axis using the default line color as border.
cAxis.setBoundingBox(Transparent, LineColor)

# Add a title to the color axis using 12 points Arial Bold Italic font
cAxis.setTitle("Color Legend Title Place Holder", "arialbi.ttf", 10)

# Set color axis labels to use Arial Bold font
cAxis.setLabelStyle("arialbd.ttf")

# Set the color axis range as 0 to 20, with a step every 2 units
cAxis.setLinearScale(0, 20, 2)

# Output the chart
c.makeChart("scattercontour.png")

[CGI Version] pythondemo_cgi\scattercontour.py
#!/usr/bin/python
from pychartdir import *

# The (x, y, z) coordinates of the scattered data
dataX = [0.5, 1.9, 4.9, 1.0, 8.9, 9.8, 5.9, 2.9, 6.8, 9.0, 0.0, 8.9, 1.9, 4.8, 2.4,
    3.4, 7.9, 7.5, 4.8, 7.5, 9.5, 0.4, 8.9, 0.9, 5.4, 9.4, 2.9, 8.9, 0.9, 8.9, 10.0,
    1.0, 6.8, 3.8, 9.0, 5.3, 6.4, 4.9, 4.5, 2.0, 5.4, 0.0, 10.0, 3.9, 5.4, 5.9, 5.8,
    0.3, 4.4, 8.3]
dataY = [3.3, 3.0, 0.7, 1.0, 9.3, 4.5, 8.4, 0.1, 0.8, 0.1, 9.3, 1.8, 4.3, 1.3, 2.3,
    5.4, 6.9, 9.0, 9.8, 7.5, 1.8, 1.4, 4.5, 7.8, 3.8, 4.0, 2.9, 2.4, 3.9, 2.9, 2.3,
    9.3, 2.0, 3.4, 4.8, 2.3, 3.4, 2.3, 1.5, 7.8, 4.5, 0.9, 6.3, 2.4, 6.9, 2.8, 1.3,
    2.9, 6.4, 6.3]
dataZ = [6.6, 12.5, 7.4, 6.2, 9.6, 13.6, 19.9, 2.2, 6.9, 3.4, 8.7, 8.4, 7.8, 8.0,
    9.4, 11.9, 9.6, 15.7, 12.0, 13.3, 9.6, 6.4, 9.0, 6.9, 4.6, 9.7, 10.6, 9.2, 7.0,
    6.9, 9.7, 8.6, 8.0, 13.6, 13.2, 5.9, 9.0, 3.2, 8.3, 9.7, 8.2, 6.1, 8.7, 5.6,
    14.9, 9.8, 9.3, 5.1, 10.8, 9.8]

# Create a XYChart object of size 450 x 540 pixels
c = XYChart(450, 540)

# Add a title to the chart using 15 points Arial Italic font
c.addTitle("      Contour Chart with Scattered Data", "ariali.ttf", 15)

# Set the plotarea at (65, 40) and of size 360 x 360 pixels. Use semi-transparent
# black (c0000000) for both horizontal and vertical grid lines
c.setPlotArea(65, 40, 360, 360, -1, -1, -1, '0xc0000000', -1)

# Set x-axis and y-axis title using 12 points Arial Bold Italic font
c.xAxis().setTitle("X-Axis Title Place Holder", "arialbi.ttf", 10)
c.yAxis().setTitle("Y-Axis Title Place Holder", "arialbi.ttf", 10)

# Set x-axis and y-axis labels to use Arial Bold font
c.xAxis().setLabelStyle("arialbd.ttf")
c.yAxis().setLabelStyle("arialbd.ttf")

# When x-axis and y-axis color to transparent
c.xAxis().setColors(Transparent)
c.yAxis().setColors(Transparent)

# Add a scatter layer to the chart to show the position of the data points
c.addScatterLayer(dataX, dataY, "", Cross2Shape(0.2), 7, '0x000000')

# Add a contour layer using the given data
layer = c.addContourLayer(dataX, dataY, dataZ)

# Move the grid lines in front of the contour layer
c.getPlotArea().moveGridBefore(layer)

# Add a color axis (the legend) in which the top center is anchored at (245, 455).
# Set the length to 330 pixels and the labels on the top side.
cAxis = layer.setColorAxis(245, 455, TopCenter, 330, Top)

# Add a bounding box to the color axis using the default line color as border.
cAxis.setBoundingBox(Transparent, LineColor)

# Add a title to the color axis using 12 points Arial Bold Italic font
cAxis.setTitle("Color Legend Title Place Holder", "arialbi.ttf", 10)

# Set color axis labels to use Arial Bold font
cAxis.setLabelStyle("arialbd.ttf")

# Set the color axis range as 0 to 20, with a step every 2 units
cAxis.setLinearScale(0, 20, 2)

# Output the chart
print("Content-type: image/png\n")
binaryPrint(c.makeChart2(PNG))