Bowl

Initial Gaussian hump sends out ripples in a symmetric bowl-shaped pond. Refinment is focused near one edge of the pond.

Create topography files and data files



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%run make_topo.py



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%run make_data.py

Run code in serial mode (will work, even if code is compiled with MPI)



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!bowl

Or, run code in parallel mode (command may need to be customized, depending your on MPI installation.)



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#!mpirun -n 4 bowl

Create PNG files for web-browser viewing, or animation.



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%run make_plots.py

View PNG files in browser, using URL above, or create an animation of all PNG files, using code below.



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%pylab inline



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import glob
from matplotlib import image
from clawpack.visclaw.JSAnimation import IPython_display
from matplotlib import animation

def init():
    im.set_data(image.imread(filenames[0]))
    return im,

def animate(i):
    image_i=image.imread(filenames[i])
    im.set_data(image_i)
    return im,

Plot figure 0, showing the entire solution. To see detailed plotting parameters, see file make_plots.py.



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figno = 0

fname = '_plots/*fig' + str(figno) + '.png'
filenames = sorted(glob.glob(fname))

fig = plt.figure()
im = plt.imshow(image.imread(filenames[0]))

animation.FuncAnimation(fig, animate, init_func=init,
                              frames=len(filenames), interval=500, blit=True)

Then plot figures 10 and 11 to compare the solution in the two refined regions.



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figno = 10

fname = '_plots/*fig' + str(figno) + '.png'
filenames = sorted(glob.glob(fname))

fig = plt.figure()
im = plt.imshow(image.imread(filenames[0]))

animation.FuncAnimation(fig, animate, init_func=init,
                              frames=len(filenames), interval=500, blit=True)