Multi-constellation #4
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…lass; draft for LISALIA detector
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Not sure if test notebooks and npy_saves are to be added to the repo. Also, the new LISA and ALIA classes (using the LISAlike detector superclass) are named LISADetector2 and ALIADetector2 (for testing purposes). Should probably change this and delete the original classes. |
damonge
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damonge
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OK, thanks a lot @Alseidon I've left a few questions in comments below. Here are a couple of questions to understand better what you've been doing:
- You have
LISADetector,LISAlikeDetector,ALIADetector,LISADetector2andALIADetector2. Can you explain briefly what the motivation is for each of these? - When building a constellation, instead of creating new detector classes like
TwoLISADetectororMultipleLISADetector, would it have been possible to just concatenate detectors into a network connected with the appropriate noise correlation matrix?
schnell/correlation.py
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| static=det.detector.static, | ||
| include_GCN=det.detector.include_GCN, | ||
| mission_duration=det.detector.mission_duration) | ||
| LISA2det = LISADetector2(0, is_L5Gm=det.is_L5Gm, |
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Do you really need two copies of this?
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Not at all, I will change this
schnell/correlation.py
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| mission_duration=det.detector.mission_duration) | ||
| self.psdaL1 = LISA1det.psd_A | ||
| self.psdxL1 = LISA1det.psd_X | ||
| self.psdaL2 = LISA2det.psd_A |
schnell/correlation.py
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| x = self.psdxL1(f) | ||
| return x/a | ||
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| def _rhoL2(self, f): |
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Or this? Is this notthe same as _rhoL1?
schnell/correlation.py
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| mat[:, j, i] = rL2 | ||
| return mat | ||
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| class NoiseCorrelationMultipleLISA(NoiseCorrelationBase): |
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Do you need the TwoLISA case if you have this?
schnell/detector.py
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| array_like: array of PSD values in units of \ | ||
| 1/Hz. | ||
| """ | ||
| return self.psd_A(f) + self.GCN(f) |
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Any reason why this is not added in the psd_A method directly?
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I wasn't sure where to add it, if it makes more sense in psd_A then let's do this
schnell/mapping.py
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| NoiseCorrelationConstantIdentity, | ||
| NoiseCorrelationConstantR) | ||
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| from concurrent.futures import ProcessPoolExecutor as Pool |
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Did you need this in the end?
| return gls | ||
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| def get_G_ell_part(self, t, f, nside, indices, no_autos=False, deltaOmega_norm=True, |
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What are these two functions supposed to do exactly?
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They just allowed me to compute a part of the sum over the detectors in Nell^-1 and were mainly for checking purposes ; maybe I should delete them
schnell/space_detector.py
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| import scipy.integrate as integr | ||
| from .detector import Detector, LISAlikeDetector | ||
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| class LISADetector2(LISAlikeDetector): |
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So the difference wrt the default LISA is adding the GCN?
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The default LISA was just there as a safeguard, in case the LISAlike superclass didn't work. It should be deleted now (and LISADetector2 renamed to LISADetector)
Same for ALIA
schnell/space_detector.py
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| def _pos_single(self, t, n): | ||
| if n in [0, 1, 2]: | ||
| detect = LISADetector2(0, is_L5Gm=self.is_L5Gm, |
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Humm, could you have used self.detector instead if you checked if n == self.i_d? Just wondering if having to define a new detector every time will slow things down.
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I am not sure how much time we would gain, but it's really easy to do so I will probably implement this soon
schnell/space_detector.py
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| for i in range(6)]) | ||
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| def _pos_single(self, t, n): | ||
| detect = LISADetector2(0, is_L5Gm=self.is_L5Gm, |
…oiseCorrelationMultipleSpaceDetectors
@Alseidon 's modifications