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Refactor delay-space measurement code and add features #217
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This looks good to me. I have a couple of nitpicky stylistic comments but that's about it
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These changes look good to me overall. I spoke to @jrs65 on Friday and he mentioned having some thoughts about modifying the delay spectrum implementation to be split into multiple pipeline tasks. So I don't have anything else to change here, but we should let him weight in as well.
Hi, I am also checking this and it looks good to me. However, I have one suggestion to add the freq axis in the index_map of the DelaySpectrum and DelayTransform container. This is needed to estimate various cosmological quantities downstream. For example, we need redshift to estimate comoving distances to get the kperp and kpar axes. Probably something like this within the task -
And add this in the container -
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…ay_filter): use window functions from draco.util.tools
…oise covariance The previous code version took the inverse noise variance for each complex-valued measurement in frequency space, and assigned 2**-0.5 times this variance to the real and imaginary parts. However, for a circularly-symmetric complex Gaussian random number, the variances of the real and imaginary parts should each be 0.5 times the total variance, implying that the separate inverse variances should be 2 times the total inverse variance. The only impact of this error on previous output of the code is that the noise level assumed by the Gibbs sampler was slightly wrong.
…rumWienerEstimator): add parameter to boost noise weights
To distinguish between routines that deal with delay spectra instead of power spectra, we rename delay_spectrum_gibbs to delay_power_spectrum_gibbs, and also alias delay_spectrum_gibbs to the new name to preserve backwards compatibility.
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This is meant to supersede #176 and #216:
DelaySpectrumEstimator
,DelaySpectrumEstimatorBase
, andDelaySpectrumWienerBase
to eliminate repeated code blocks and enable future extensionsNotably, I've kept the scheme of compressing many axes into a
baseline
axis. I don't think this is ideal in the long run, but in the short term, I think it's higher-priority to get the Wiener filter and #216 features all merged coherently