examples: Interpolation tutorial notebook #2252
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examples/userapi/03_subdomains.ipynb
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Overall needs a lot comments to be more "educational", then we could have another iteration
injectionthat inject values at one or more given sparse positions (i.e point sources)interpolationthat reads the value of a field at one or more given sparse positions (i.e point measurments)
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Add comment like: Some variable declarations
introduce diff between f and u (what is save)
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Line #2. ax.imshow(u.data[1], vmin=0, vmax=1, cmap="jet", extent=[0,1,0,1])
Missing plt.show()
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Line #2. ax.imshow(u.data[1], vmin=0, vmax=2, cmap="jet", extent=[0,1,0,1])
Missing a plt.show()
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Line #3. coords = np.random.rand(npoint, 2)/2 + .25
Do you need to set a seed here? Otherwise this is going to be non-deterministic
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No, that's intentional. This way, you can see different scenarios (overlap, ...) when user runs it
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"a Devito object, representing a"
"and the data at those positions"
"is the dimensionality of the Grid"
Remove the first "at the sparse positions"
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Line #3. ax.imshow(u.data[1], vmin=0, vmax=1, cmap="jet", extent=[0,1,0,1])
A colourbar is needed here
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Line #11. ax.set_title("Off the grid sparse positions")
"Off-grid sparse positions"
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Line #3. ax.imshow(u.data[1], vmin=0, vmax=2, cmap="jet", extent=[0,1,0,1])
A colourbar is needed here
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Not sure how helpful this figure is.
Could be better probably with less points, to see understand weights better
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