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# Tricontour Vs Griddata

Comparison of griddata and tricontour for an unstructured triangular grid.

Out:

    griddata and contour: 0.218058 seconds
    tricontour: 0.100136 seconds

    from __future__ import print_function
    import matplotlib.pyplot as plt
    import matplotlib.tri as tri
    import numpy as np
    import matplotlib.mlab as mlab
    import time

    np.random.seed(0)
    npts = 200
    ngridx = 100
    ngridy = 200
    x = np.random.uniform(-2, 2, npts)
    y = np.random.uniform(-2, 2, npts)
    z = x * np.exp(-x**2 - y**2)

    # griddata and contour.
    start = time.clock()
    plt.subplot(211)
    xi = np.linspace(-2.1, 2.1, ngridx)
    yi = np.linspace(-2.1, 2.1, ngridy)
    zi = mlab.griddata(x, y, z, xi, yi, interp='linear')
    plt.contour(xi, yi, zi, 15, linewidths=0.5, colors='k')
    plt.contourf(xi, yi, zi, 15,
                 norm=plt.Normalize(vmax=abs(zi).max(), vmin=-abs(zi).max()))
    plt.colorbar()  # draw colorbar
    plt.plot(x, y, 'ko', ms=3)
    plt.xlim(-2, 2)
    plt.ylim(-2, 2)
    plt.title('griddata and contour (%d points, %d grid points)' %
              (npts, ngridx * ngridy))
    print('griddata and contour: %f seconds' % (time.clock() - start))

    # tricontour.
    start = time.clock()
    plt.subplot(212)
    triang = tri.Triangulation(x, y)
    plt.tricontour(x, y, z, 15, linewidths=0.5, colors='k')
    plt.tricontourf(x, y, z, 15,
                    norm=plt.Normalize(vmax=abs(zi).max(), vmin=-abs(zi).max()))
    plt.colorbar()
    plt.plot(x, y, 'ko', ms=3)
    plt.xlim(-2, 2)
    plt.ylim(-2, 2)
    plt.title('tricontour (%d points)' % npts)
    print('tricontour: %f seconds' % (time.clock() - start))

    plt.subplots_adjust(hspace=0.5)

    plt.show()

Total running time of the script: ( 0 minutes 0.328 seconds)

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