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Approximate material grid smoothing (β=∞) #1951
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5fd8cf6
subpixel averaging for boundaries of variable-material objects
stevengj d67b1f2
rm obsolete references to meepgeom::is_file
stevengj 6a9f7dd
bugfix
stevengj bf5296c
undo spurious change
stevengj a480ffd
add proper kernels for sphere caps
smartalecH 5c38aa7
clean up comments
smartalecH bb07eaa
checkpoint
smartalecH 92499af
merge in previous updates from subpixel_varmat
smartalecH 1652a62
minor tweaks to kill errors
smartalecH ee071de
enable smoothing
smartalecH b544afd
get gradients working both with and without averaging
smartalecH 5f59014
adjust FD step
smartalecH 8bfbb77
fix boundary case when spatial gradient doesn't exist
smartalecH 1880b0d
refactor
smartalecH fa35e16
add duals
smartalecH 3aa3c09
fix interface artifacts and get gradients working
smartalecH b1fd007
Merge branch 'master' of https://github.com/NanoComp/meep into inf_sm…
smartalecH 5c07d78
minor formatting
smartalecH 25f9437
update makefile
smartalecH b69a5d1
fix bug in fill fraction
smartalecH 69265e9
rebase
smartalecH 7a558fd
fix matgrid test bug
smartalecH 9ac153e
fix damping test failure
smartalecH 3349aee
revamp matgrid test and add comments
smartalecH 35ec6d8
update tests and add comments to code
smartalecH fabd531
approximate material-grid smoothing
stevengj 9793cf5
reformat
stevengj c88ca4a
rebase
smartalecH 83fd9ef
add function to update m number
smartalecH 2dff39e
update change m number too
smartalecH 2230adb
precommit cleanup
smartalecH 33ea63a
precommit cleanup
smartalecH 1d78417
incorporate m changes
smartalecH d3f5ef9
add threshold check for normal vector to mitigate floating point sens…
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Original file line number | Diff line number | Diff line change |
---|---|---|
|
@@ -7,3 +7,4 @@ numpy | |
parameterized | ||
pytest | ||
scipy | ||
scikit-fmm |
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Is it necessary to include this additional module just for its signed distance function (rather than write our own or find a similar function in e.g. SciPy)? skfmm does not seem to be widely used which could make installing it a challenge for some users building from source.
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From their docs:
What's challenging about this particular package vs
numpy
,scipy
, etc.?It's convenient for testing, but we can remove it if it really is a challenge to install.
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I ran into some package conflicts during the
pip install
. In general, it is useful to keep the number of package dependencies, particularly smaller ones, to a minimum.