Scattered Data Contour Chart

This example demonstrates using scattered data to create a ContourLayer.

In the previous Contour Chart example, the data points lie on a grid. ChartDirector also supports using scattered data points, which means the data points can be at irregular positions. To distinguish between the two case, if the number of z coordinates is equal to the product of the number of x and y coordinates, ChartDirector will assume the x and y coordinates define the grid and the z coordinates are values of the points on the grid. If the number of x, y and z coordinates are equal, ChartDirector will assume they represent scatter points.

In this example, in additional to a ContourLayer added using XYChart.addContourLayer, there is also a ScatterLayer added using XYChart.addScatterLayer to show the positions of the data points.

pythondemo\scattercontour.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 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", "Arial Italic", 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", "Arial Bold Italic", 10)
c.yAxis().setTitle("Y-Axis Title Place Holder", "Arial Bold Italic", 10)

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

# 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", "Arial Bold Italic", 10)

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

# 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")