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# Non-evolved remnant fits
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[[_TOC_]]
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# Non-evolved nrutils remnant fits
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To calculate the non-evolved remnant fits, we call the functions in `lalinference.imrtgr.nrutils`. You can see the wrapper for these functions in [`pesummary.gw.file.nrutils`](https://git.ligo.org/lscsoft/pesummary/-/blob/master/pesummary/gw/file/nrutils.py).
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To calculate the non-evolved remnant fits, we call the functions in `lalinference.imrtgr.nrutils`. You can see the wrapper for these functions in [`pesummary.gw.file.nrutils`](https://git.ligo.org/lscsoft/pesummary/-/blob/master/pesummary/gw/file/nrutils.py).
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... | @@ -72,9 +74,14 @@ Maximum difference for mf_nonevol: 7.958078640513122e-13 |
... | @@ -72,9 +74,14 @@ Maximum difference for mf_nonevol: 7.958078640513122e-13 |
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Maximum difference for e_rad_nonevol: 4.1033842990145786e-13
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Maximum difference for e_rad_nonevol: 4.1033842990145786e-13
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```
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```
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# Review comments
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## Related MRs
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## David Keitel 2020.03.04
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* !241
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* !242
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## Review comments
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### David Keitel 2020.03.04
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* inspected version: ed801a91
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* inspected version: ed801a91
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* [nrutils wrappers](https://git.ligo.org/lscsoft/pesummary/-/blob/master/pesummary/gw/file/nrutils.py):
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* [nrutils wrappers](https://git.ligo.org/lscsoft/pesummary/-/blob/master/pesummary/gw/file/nrutils.py):
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... | @@ -100,7 +107,7 @@ However, continuing to read in [conversions.py](https://git.ligo.org/lscsoft/pes |
... | @@ -100,7 +107,7 @@ However, continuing to read in [conversions.py](https://git.ligo.org/lscsoft/pes |
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* [ ] Similar for the spin evolution, I see that various functions already have a `evolved=False` placeholder switch, but how will that actually be decided? Will `generate_all_posterior_samples` get an extra switch argument (or as part of `self`), or will the evolved samples be generated in a step prior to calling this function and it will check for their presence, then use them if available?
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* [ ] Similar for the spin evolution, I see that various functions already have a `evolved=False` placeholder switch, but how will that actually be decided? Will `generate_all_posterior_samples` get an extra switch argument (or as part of `self`), or will the evolved samples be generated in a step prior to calling this function and it will check for their presence, then use them if available?
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> I was thinking of the latter: `will the evolved samples be generated in a step prior to calling this function and it will check for their presence, then use them if available?`. I think this is the cleanest way of solving this problem.
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> I was thinking of the latter: `will the evolved samples be generated in a step prior to calling this function and it will check for their presence, then use them if available?`. I think this is the cleanest way of solving this problem.
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## Nathan Johnson-McDaniel 2020.03.05
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### Nathan Johnson-McDaniel 2020.03.05
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Initial comments
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Initial comments
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... | @@ -120,7 +127,7 @@ Initial comments |
... | @@ -120,7 +127,7 @@ Initial comments |
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- [x] This is not really part of this review, but in [this code](https://git.ligo.org/lscsoft/pesummary/-/blob/review_comments/pesummary/gw/file/conversions.py#L1190) using a calculation like [here](https://git.ligo.org/lscsoft/pesummary/-/blob/review_comments/pesummary/gw/file/nrutils.py#L215) instead of `arccos` would presumably be faster, though perhaps less clean to read (and it's surely not a big performance issue). I would also recommend adding a comment about why things called `spin_magnitudes` in the code can be negative.
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- [x] This is not really part of this review, but in [this code](https://git.ligo.org/lscsoft/pesummary/-/blob/review_comments/pesummary/gw/file/conversions.py#L1190) using a calculation like [here](https://git.ligo.org/lscsoft/pesummary/-/blob/review_comments/pesummary/gw/file/nrutils.py#L215) instead of `arccos` would presumably be faster, though perhaps less clean to read (and it's surely not a big performance issue). I would also recommend adding a comment about why things called `spin_magnitudes` in the code can be negative.
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> I have kept `arccos` only because I think it is cleaner for readability and I do not think this will affect the performance of the code that much :) I have also changed `a_1` to be `spin_1z` which circumvents the need to explain why things called `spin_magnitudes` can be negative.
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> I have kept `arccos` only because I think it is cleaner for readability and I do not think this will affect the performance of the code that much :) I have also changed `a_1` to be `spin_1z` which circumvents the need to explain why things called `spin_magnitudes` can be negative.
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## Nathan Johnson-McDaniel 2020.03.08
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### Nathan Johnson-McDaniel 2020.03.08
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Comments on the revised version
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Comments on the revised version
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... | @@ -148,7 +155,7 @@ Comments on the revised version |
... | @@ -148,7 +155,7 @@ Comments on the revised version |
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* Minor:
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* Minor:
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- [ ] There should be a space between ergs and s^{-1} [here](https://git.ligo.org/lscsoft/pesummary/-/blob/review_comments/pesummary/gw/plots/latex_labels.py#L84). Additionally, things like "peak," "nonevol," "ergs," and "s" should all be set in Roman.
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- [ ] There should be a space between ergs and s^{-1} [here](https://git.ligo.org/lscsoft/pesummary/-/blob/review_comments/pesummary/gw/plots/latex_labels.py#L84). Additionally, things like "peak," "nonevol," "ergs," and "s" should all be set in Roman.
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## David Keitel 2020.03.04
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### David Keitel 2020.03.04
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* From Nathan:
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* From Nathan:
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> The _final_from_initial() function might also include IMRPhenomD as an option, interfacing with the Husa et al. fits used in this waveform.
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> The _final_from_initial() function might also include IMRPhenomD as an option, interfacing with the Husa et al. fits used in this waveform.
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... | @@ -159,7 +166,13 @@ Comments on the revised version |
... | @@ -159,7 +166,13 @@ Comments on the revised version |
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* [x] Also I'm somewhat confused now when/where the explicit fit arguments are passed, and when not. From the main generate_all_posterior_samples, it calls e.g. _final_spin_of_merger, which then calls final_spin_of_merger, which then has defaults method="NR", approximant="SEOBNRv4", NRfit="average". So it currently always uses those defaults, is that right? Any other options would be a future MR?
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* [x] Also I'm somewhat confused now when/where the explicit fit arguments are passed, and when not. From the main generate_all_posterior_samples, it calls e.g. _final_spin_of_merger, which then calls final_spin_of_merger, which then has defaults method="NR", approximant="SEOBNRv4", NRfit="average". So it currently always uses those defaults, is that right? Any other options would be a future MR?
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--> answer from Charlie: "Yes so it currently uses those defaults. And yes, for interests of time, I will save other options for a future MR."
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--> answer from Charlie: "Yes so it currently uses those defaults. And yes, for interests of time, I will save other options for a future MR."
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# Spin evolution for nrutils fits
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## Related MRs
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## Related MRs
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* !241
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* !245
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* !242 |
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\ No newline at end of file |
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## Review comments |
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\ No newline at end of file |