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Vectorize signal generator functions #252
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Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## main #252 +/- ##
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+ Coverage 96.07% 96.14% +0.07%
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Files 31 31
Lines 3565 3581 +16
==========================================
+ Hits 3425 3443 +18
+ Misses 140 138 -2 ☔ View full report in Codecov by Sentry. |
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if precomps is None: | ||
precomps = generate_precomputes(L, -mm, sampling, nside, L_lower) | ||
precomps = generate_precomputes( | ||
L=L, | ||
spin=-mm, | ||
sampling=sampling, | ||
nside=nside, | ||
forward=False, | ||
L_lower=L_lower, | ||
) |
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elif n > 0: | ||
# Generate independent complex coefficients for positive n | ||
flmn[N - 1 + n, min_el:L, L - 1] = complex_normal( | ||
rng, L - min_el, var=2 | ||
) | ||
# For m = 0, n > 0 | ||
# flmn[N - 1 - n, el, L - 1] = (-1)**n * flmn[N - 1 + n, el, L - 1].conj | ||
flmn[N - 1 - n, min_el:L, L - 1] = (-1) ** n * ( | ||
flmn[N - 1 + n, min_el:L, L - 1].conj() | ||
) |
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Compared to previous implementation, here for m = 0
and abs(n) > 0
we generate complex coefficients rather than real, as the conjugate symmetry condition does not seem to enforce reality in this case - not sure if this is correct though?
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Nice! We originally just implemented these functions for testing purposes so didn't bother optimising them, but as you say definitely worth quickly updating them now.
When running some benchmarks with large
L
I noticed that the signal generation functions ins2fft.utils.signal_generator
become very slow for largeL
due to the nested for loops.This switches to using a vectorized implementation.
Currently implemented forgenerate_flm
only.EDIT: Now implemented for both
generate_flm
andgenerate_flmn
.