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POCReate 3D elevations over a fixed Grid from a Cross section defined by a string of Points
 

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  1. POCReate 3D elevations over a fixed Grid from a Cross section defined by a string of Points
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    <p>I am trying to create a 3D surface on a fixed grid of say 1m or 0.5m spacing, where the surface is a channel defined by a cross section of a number of points. Ideally it should be any number of points. For example a cross section such as:</p> <p>PTS = [[0.0,10.0],[3.0,9.0],[30.0,8.5],[33.0,8.0],[35.0,7.8],[37.0,8.0],[40.0,8.5],[67.0,9.0],[70.0,10.0]] Where the channel here is 70 m wide and has a double trapezoidal section.</p> <p>I have tried, to code this but failed to date:</p> <p>I want to read the points, and then interpolate based on the spacing to provide a calculated elevation (Z value). This should populate the domain of X &amp; Y, thereby providing XYZ values of the 3D terrain</p> <p>This example is supposed to create a 1500m long channel that is 70 m wide</p> <p>CODE:</p> <hr> <h2> Setup computational domain</h2> <pre><code>length = 50.0 # change back to 3500 width = 30.0 #changed this dx = dy = 1.0 # Resolution: of grid on both axes h=2.21 # Constant depth slope_X=1/100 def topography(x,y): z = -x*slope_X PTS = [[0.0,10.0],[3.0,9.0],[30.0,8.5],[33.0,8.0],[35.0,7.8],[37.0,8.0],[40.0,8.5],[67.0,9.0],[70.0,10.0]] N = len(x) for i in range(N): # Construct Cross section from LIST of PTS for j in range(len(PTS)): if j == 0: pass else: m = (PTS[j][1]-PTS[j-1][1])/(PTS[j][0]-PTS[j-1][0]) b = PTS[j-1][1]-(PTS[j][1]-PTS[j-1][1])/(PTS[j][0]-PTS[j-1][0])*PTS[j-1][0] z[i]= m *y[i]+b if x[i]==10: print 'Z =', z[i] return z </code></pre> <p>As the code traverses over X, the basic Z provides a sloping bed, and then the cross section defined, creates the Z's over a range of Y's</p> <p>Ideally this could also be applied along a polyline, rather than apply it only in the x -direction. That way the channel could be produced along a curve, or a S- bend for example</p> <p>I hope some one has some clever ideas on how to resolve this... Thank you</p> <p>It was mentioned that scipy might be able to help here.... I will try to make sense of this, to create a function to interpolate between the points:</p> <blockquote> <blockquote> <blockquote> <p>from scipy.interpolate import interp1d</p> <p>x = np.linspace(0, 10, 10)</p> <p>y = np.exp(-x/3.0)</p> <p>f = interp1d(x, y)</p> <p>f2 = interp1d(x, y, kind=’cubic’)</p> <p>xnew = np.linspace(0, 10, 40)</p> <p>import matplotlib.pyplot as plt</p> <p>plt.plot(x,y,’o’,xnew,f(xnew),’-’, xnew, f2(xnew),’--’)</p> <p>plt.legend([’data’, ’linear’, ’cubic’], loc=’best’)</p> <p>plt.show()</p> </blockquote> </blockquote> </blockquote>
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