





This example demonstrates the rectangular and triangular wireframes of a surface at different interpolation levels, configured using SurfaceChart.setShadingMode and SurfaceChart.setInterpolation.
ChartDirector 5.1 (Python Edition)
Surface Wireframe
Source Code Listing
#!/usr/bin/python from pychartdir import * import math def createChart(img) : # The x and y coordinates of the grid dataX = [-2, -1, 0, 1, 2] dataY = [-2, -1, 0, 1, 2] # The values at the grid points. In this example, we will compute the values # using the formula z = square_root(15 - x * x - y * y). dataZ = [0] * (len(dataX) * len(dataY)) for yIndex in range(0, len(dataY)) : y = dataY[yIndex] for xIndex in range(0, len(dataX)) : x = dataX[xIndex] dataZ[yIndex * len(dataX) + xIndex] = math.sqrt(15 - x * x - y * y) # Create a SurfaceChart object of size 380 x 340 pixels, with white (ffffff) # background and grey (888888) border. c = SurfaceChart(380, 340, 0xffffff, 0x888888) # Demonstrate various wireframes with and without interpolation if img == "0" : # Original data without interpolation c.addTitle("5 x 5 Data Points\nStandard Shading", "arialbd.ttf", 12) c.setContourColor(0x80ffffff) elif img == "1" : # Original data, spline interpolated to 40 x 40 for smoothness c.addTitle("5 x 5 Points - Spline Fitted to 40 x 40\nStandard Shading", "arialbd.ttf", 12) c.setContourColor(0x80ffffff) c.setInterpolation(40, 40) elif img == "2" : # Rectangular wireframe of original data c.addTitle("5 x 5 Data Points\nRectangular Wireframe") c.setShadingMode(RectangularFrame) elif img == "3" : # Rectangular wireframe of original data spline interpolated to 40 x 40 c.addTitle("5 x 5 Points - Spline Fitted to 40 x 40\nRectangular Wireframe") c.setShadingMode(RectangularFrame) c.setInterpolation(40, 40) elif img == "4" : # Triangular wireframe of original data c.addTitle("5 x 5 Data Points\nTriangular Wireframe") c.setShadingMode(TriangularFrame) else : # Triangular wireframe of original data spline interpolated to 40 x 40 c.addTitle("5 x 5 Points - Spline Fitted to 40 x 40\nTriangular Wireframe") c.setShadingMode(TriangularFrame) c.setInterpolation(40, 40) # Set the center of the plot region at (200, 170), and set width x depth x height # to 200 x 200 x 150 pixels c.setPlotRegion(200, 170, 200, 200, 150) # Set the plot region wall thichness to 5 pixels c.setWallThickness(5) # Set the elevation and rotation angles to 20 and 30 degrees c.setViewAngle(20, 30) # Set the data to use to plot the chart c.setData(dataX, dataY, dataZ) # Output the chart c.makeChart("surfacewireframe%s.jpg" % img) createChart("0") createChart("1") createChart("2") createChart("3") createChart("4") createChart("5") |
#!/usr/bin/python from pychartdir import * import cgi, math # Get HTTP query parameters query = cgi.FieldStorage() # The x and y coordinates of the grid dataX = [-2, -1, 0, 1, 2] dataY = [-2, -1, 0, 1, 2] # The values at the grid points. In this example, we will compute the values using # the formula z = square_root(15 - x * x - y * y). dataZ = [0] * (len(dataX) * len(dataY)) for yIndex in range(0, len(dataY)) : y = dataY[yIndex] for xIndex in range(0, len(dataX)) : x = dataX[xIndex] dataZ[yIndex * len(dataX) + xIndex] = math.sqrt(15 - x * x - y * y) # Create a SurfaceChart object of size 380 x 340 pixels, with white (ffffff) # background and grey (888888) border. c = SurfaceChart(380, 340, 0xffffff, 0x888888) # Demonstrate various wireframes with and without interpolation if query["img"].value == "0" : # Original data without interpolation c.addTitle("5 x 5 Data Points\nStandard Shading", "arialbd.ttf", 12) c.setContourColor(0x80ffffff) elif query["img"].value == "1" : # Original data, spline interpolated to 40 x 40 for smoothness c.addTitle("5 x 5 Points - Spline Fitted to 40 x 40\nStandard Shading", "arialbd.ttf", 12) c.setContourColor(0x80ffffff) c.setInterpolation(40, 40) elif query["img"].value == "2" : # Rectangular wireframe of original data c.addTitle("5 x 5 Data Points\nRectangular Wireframe") c.setShadingMode(RectangularFrame) elif query["img"].value == "3" : # Rectangular wireframe of original data spline interpolated to 40 x 40 c.addTitle("5 x 5 Points - Spline Fitted to 40 x 40\nRectangular Wireframe") c.setShadingMode(RectangularFrame) c.setInterpolation(40, 40) elif query["img"].value == "4" : # Triangular wireframe of original data c.addTitle("5 x 5 Data Points\nTriangular Wireframe") c.setShadingMode(TriangularFrame) else : # Triangular wireframe of original data spline interpolated to 40 x 40 c.addTitle("5 x 5 Points - Spline Fitted to 40 x 40\nTriangular Wireframe") c.setShadingMode(TriangularFrame) c.setInterpolation(40, 40) # Set the center of the plot region at (200, 170), and set width x depth x height to # 200 x 200 x 150 pixels c.setPlotRegion(200, 170, 200, 200, 150) # Set the plot region wall thichness to 5 pixels c.setWallThickness(5) # Set the elevation and rotation angles to 20 and 30 degrees c.setViewAngle(20, 30) # Set the data to use to plot the chart c.setData(dataX, dataY, dataZ) # Output the chart print("Content-type: image/jpeg\n") binaryPrint(c.makeChart2(JPG)) |