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Currently the loops in PROCAR parsing and spectral_function_from_weight_sets run over all bands/kpoints in the calculation.
In many cases, the bands extend over a very large energy range (e.g. in the Cs$_2$Sn/TiX$_6$ alloys from the docs example, the range is -37 to +8 eV), whereas we usually only want to plot within a much smaller energy range (e.g. -5 to +5 eV).
Given that the PROCARs are parsed each time when doing a projected band structure plot, and this is the most time-consuming part of the projected plotting, it could significantly speed up this step by only parsing bands with energies within the emin - emax range.
I implemented a (conceptually) similar masking approach in PyTASER recently (WMD-group/PyTASER@4b8ac4d) which gave a massive boost in efficiency.
Worth considering!
The text was updated successfully, but these errors were encountered:
Currently the loops in
PROCAR
parsing andspectral_function_from_weight_sets
run over all bands/kpoints in the calculation.In many cases, the bands extend over a very large energy range (e.g. in the Cs$_2$Sn/TiX$_6$ alloys from the docs example, the range is -37 to +8 eV), whereas we usually only want to plot within a much smaller energy range (e.g. -5 to +5 eV).
Given that the
PROCAR
s are parsed each time when doing a projected band structure plot, and this is the most time-consuming part of the projected plotting, it could significantly speed up this step by only parsing bands with energies within theemin
-emax
range.I implemented a (conceptually) similar masking approach in
PyTASER
recently (WMD-group/PyTASER@4b8ac4d) which gave a massive boost in efficiency.Worth considering!
The text was updated successfully, but these errors were encountered: