Add spherical sky region classes#618
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Awesome to see this finally implemented! The jupyter notebook is great. I agree, it needs to be chunked out into docs. For serialization, we are defining a new standard here, afaik. I recommend we make something that is still compatible with CARTA/DS9 serializations but, when read with astropy, can be interpreted as SphericalSkyRegions instead of projected sky regions. The big concern is that, for very large images loaded into ds9/carta, there will be inconsistency between the astropy & viewer interpretation of the same file, and I don't like introducing that. So... yeah, there's an argument that we serialize in a way that ds9/carta will ignore these regions rather than show potentially incorrect regions. I'd recommend splitting out the serialization and distortion questions into separate issues to handle after the main functionality is merged. |
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Definitely, will chunk it out! That sounds very reasonable as far as serialization and distortion (for planar -> spherical). I'll note for completeness that I did implement distortion for spherical->planar (which I'd argue is good to keep in this PR and not split out; but perhaps I'm reading too much into your comment). |
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No need to split that out, imo. I meant this bullet: "Decision on whether or not (and how) to implement planar -> spherical conversion if boundary distortions are to be included." should be a separate issue |
pllim
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I don't see any tests. Do you plan to add them?
I can't really do any meaningful review of the contents but maybe @mcara (maintainer of spherical-geometry) and @perrygreenfield can, or point to people who can.
Thanks!
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@pllim -- Thanks! Re tests: I was holding off on implementing proper tests until there was consensus that this draft pull request is something that the maintainers would want to include in the package. I definitely plan to add tests as soon as there is go-ahead consensus! (Also before finalizing, I would remove the demo NB and all changes to .pre-commit-config.yaml from the repo -- those were only temporary measures to get the NB into my fork for discussion purposes.) |
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Sounds good. Thanks! I added a "todo" section in your OP above, please update as needed. I will do a general technical re-review when this PR is at final stage. Good luck! |
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I've moved the demo notebook into a separate branch on my fork for reference, and to "clean up" the draft pull-request branch. (https://github.com/sedonaprice/regions/blob/add-spherical-regions-with-demo-NB/demo_spherical_regions.ipynb; also updated to this link in the initial comment) Splitting the demo notebook out into separate topical docs sections is on the to-do list, along with the test suite (pending discussion of the big picture as above). |
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(Demo notebook + precommit changes squashed out of this branch) |
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Thank you for working on this! I can help review this in September once I am back at work 😊 |
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Quick note: I've gone ahead and implemented tests for the code as it stands right now. (And found a few fairly minimal logic bugs to fix, while I was at it.) Looking forward to feedback & further discussion! |
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I've had a chance to take a look at this, and while I am not one of the regions maintainers, I think it would be great to include this so I would encourage you to proceed with writing the docs etc. This is very useful functionality! 💯
I agree with @keflavich that we should worry about serialization after this PR though, because I think the main code/functionality is needed irrespective of whether we find ways to serialize it to some of the formats where there might be ambiguities.
At this point, the only thing I am not sure about API wise is the transformation of sky regions to other systems. In particular, while it's cool that this works:
>>> lonlat_range_transf = lonlat_range.transform_to("icrs")
>>> lonlat_range_transf
<RangeSphericalSkyRegion(
frame=<class 'astropy.coordinates.builtin_frames.icrs.ICRS'>,
longitude_bounds=<LuneSphericalSkyRegion(center_gc1=<SkyCoord (ICRS): (ra, dec) in deg
(288.42757587, 10.72370325)>, center_gc2=<SkyCoord (ICRS): (ra, dec) in deg
(217.98010947, -60.49575721)>)>,
latitude_bounds=<CircleAnnulusSphericalSkyRegion(center=<SkyCoord (ICRS): (ra, dec) in deg
(192.85947789, 27.12825241)>, inner_radius=45.0 deg, outer_radius=90.0 deg)>
)>
It looks pretty complex (in particular the use of nested regions) and I'm not sure I understand the benefit of this. If someone accesses the vertices, they can always convert these between different frames, but I'm not sure that it makes sense to transform the whole spherical sky region. I guess fundamentally, what is the value in allowing sky regions to be transformed between frames since they are still fundamentally the same region? For instance, contains should work regardless of frames, and if someone does to_pixel for plotting they have to pass a WCS anyway. What use cases require transform_to?
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Hi @astrofrog -- For the specific case above ("range"), the issue with just using the vertices is that a lon/lat "range" is bounded by great circles along the lines of constant longitude, but small or great circles along the lines of constant latitude. A spherical polygon defined with the same vertices would end up "bulging out" past the lines of constant latitude, so isn't equivalent. I had added the "transforms_to()", including the nested regions, because circles transform neatly (as long as it's a spherical to spherical tranformation). Thus, since all spherical regions region can be represented as the appropriate circles (for polygons, indeed the transformation boils down to "transform the vertices and then remake the polygon, because great circles' centers transform easily; for small circles, again only the center transforms, the radius stays the same), yes the region is the same in all frames --- as long as the appropriate circle centers + radii are kept track of. As I've implemented it, "contains()" actually does work regardless of frame (because the SkyCoord to be evaluated will be transformed to the region frame, if necessary) The "transforms_to()" addresses the issue of "a user can define a region in their preferred non-ICRS frame, but needs to query against a database that only knows about ICRS" -- by transforming the region to ICRS, it's then possible to do bounding lon/lat in ICRS for search constraints, or a bounding circle (though of course the bounding circle transforms "easily". (Definitely plotting requires "to_pixel" and a WCS, but the use case this was implemented to address is database/table searches with mismatches in coordinate frame.) |
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Hi folks, I've gone through and put together (draft) documentation for spherical regions (and edits to existing sections where relevant). The changes are now in the PR branch, but are also visible "live" at https://sedonaprice.github.io/regions-docs-tmp/ (temporary; I wasn't sure about how other github actions from various branches in my fork would execute, so I created a separate repo for the build + temporary publication of these draft docs). Please let me know if you have and comments or suggestions on the docs! (Also, now that there is a full set of draft docs and a test suite, please let me know if it would be a good time to convert this from a draft PR to a normal PR.) |
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I don't maintain this package, so I am not qualified to review. Sorry and good luck! |
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@sedonaprice - I should have time to review this next week, could you rebase though to resolve the conflict? |
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@larrybradley @keflavich - since I'm not a maintainer of the package, one of you should obviously have a look at this too, so once I've reviewed this and am happy with this I'll approve but won't merge. |
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astrofrog
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Overall this looks good, but one remaining big picture comment/question in addition to a few in-line comments below: are we expecting that some of the to_spherical_sky operations that are currently NotImplementedError might be implemented in future? My understanding is that some of them will never be implemented because they don't make sense/can't be done. The Python docs say about NotImplementedError:
Note It should not be used to indicate that an operator or method is not meant to be supported at all – in that case either leave the operator / method undefined or, if a subclass, set it to None.
Basically we should not be using NotImplementedError and instead should just not add the method where it doesn't make sense. In addition, if it can't be implemented for include_boundary_distortions=True, I would suggest either removing that keyword argument altogether, or raising a ValueError if it's set to True.
Aside from this, please add an entry to the changelog.
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Hi @astrofrog -- Thank you! I'll work on addressing the review now, and add an entry to the changelog. That's a great point about raising a My thoughts on this are aggregated below: Would you agree with this categorization on which cases should raise a ValueError to indicate the transformation can't be done/doesn't make sense? This would involve the following changes from the original code:
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@astrofrog I've implemented:
I've also added an entry to the changelog. If too verbose, I can reduce it to point users to docs pages with relevant details. |
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Note: rebased as this had fallen behind the v0.11 release. Also fixed a bug in validation error raising (incorrectly had as assert) noted from CI/CD check failure (and then fixing an introduced logic mistake). |
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Lune boundary discretization was in CCW order; invert to fix for now. Note a TODO to enable proper CW order checking of all polygons at some future point (likely a shared method used in many places to validate/re-order polygon vertices).
Previous implementation discretized to n_points per edge. Change to discretize to a total of n_points vertices, for consistency with to_polygon. Update tests accordingly.
Apply a region's meta, visual to its the resulting PolygonSphericalSkyRegion when calling `discretize_boundary()`, for consistency with `to_polygon()`
Verify whole sky returns a NotImplementedError when calling `discretize_boundary()`
Implement a `to_polygon()` method that delegates to `discretize_boundary()`, for consistency with the newly-implemented planar regions `to_polygon()` method.
Update the docs to note the "boundary distortion" choice for spherical-to-planar and vice versa transformation captures all effects encoded in the WCS, not just "spherical-to-planar" projection effects.
Removing `discretize_kwargs` as a sky/pixel/spherical sky transformation input in favor of the streamlined `n_points=None` kwarg, as suggested/requested in astropy#618 (comment)
Change WholeSphericalSkyRegions errors for undefined methods to ValueError, as these will never be implemented.
Implement the LuneSphericalSkyRegion transformations `to_sky()` and `to_pixel()` when `include_boundary_distortions=True`. (Also update to use common transformation validation, and correct some notes for possible future implementations on other shapes' transformation methods.)
Add a short visual demonstration of the difference between spherical and planar circles to "Getting started". Modifies the "Spherical Sky Regions" section to have a new "Spherical to planar region transformations" subsection. The text discussing spherical-to-planar transformations is moved to that subsection, and added a short discussion of the plot demo.
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@larrybradley review comments addressed!
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I like the new example and graphic. 👍 |
larrybradley
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Thanks again, @sedonaprice. I have a couple new comments about a private import and to_pixel needing wcs (along with a few typos).
Add a validation check to ensure both regions of a compound region have the same frame.
Separate _validate_frame() into separate logical pieces: * Standardize the frame into an astropy frame class with _standardize_frame() (static method). Called for both standardization in _validate_frame(), and upon setup for `RangeSphericalSkyRegion` * Only call _validate_frame() for frame transformations. Added an explicit check for whether the current frame can be transformed to the target frame.
Rename _validate_frame to _validate_frame_transformation to make method purpose more clear.
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@larrybradley Thanks! For the private method, I implemented a stand-alone port of I also took the opportunity to streamline internal frame checks (regions.core.core.py, L791-816 now), splitting into separate standardization and validation methods. (Previously the single method both standardized the frame input and held a placeholder to raise origin offset errors --- but this method was also being used to standardize the frame setup for |
Change spherical regions' to_pixel() method to take wcs as a positional argument, as wcs is always required for that method.
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@larrybradley wcs now a positional argument in |
larrybradley
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@sedonaprice Many thanks for seeing this through! 🎉
TL;DR: Proposed spherical regions classes (implemented, with demos); if greenlit, need to implement test suite, docs before this would be ready to mark as a "non-draft" pull request. I would be very grateful for initial feedback by ~mid Sept (09/15).
Hello!
First, a huge thank you to regions' developers, for making this extremely useful package available!
I'd like to propose an implementation of spherical sky regions, complementing the planar pixel and (implicitly planar) sky region classes. (I've seen a number of issues / past discussions on this topic and how it might be implemented, but my understanding is this development has not yet been done.)
I've discussed these proposed classes with @eteq, and I'm keen to get feedback from other key folks (gleaned from past issue discussions --- @pllim, @larrybradley, @keflavich, and of course anyone else!)
Some background: I originally developed these classes as part of my work at STScI. Specifically, I needed "helper class" functionality to help demonstrate how to specify a selection region in one coordinate frame, and then transform to a different frame (and from there, construct a database query in new frame). The infrastructure and general nature of this problem led me to first develop these classes within the regions framework -- and I hope these classes could be released to the broader astronomical community as part of the regions package. If these classes could be included in regions, this would be an ideal way of providing this spherical selection & transformation functionality needed as part of the Roman Research Nexus example user notebooks.
I've put together a demo jupyter notebook walking through the core functionality (including plot demos) here: https://github.com/sedonaprice/regions/blob/add-spherical-regions-with-demo-NB/demo_spherical_regions.ipynb
I have marked this as a draft pull request because I have "tested" this code in a few demos (including the one linked above), but some work is outstanding as follows (pending a green light):
Test suite for(complete)SphericalSkyRegionclassesCreate documentation pages + demos for the new functionality (and edit other doc pages as necessary) --- based on the below demo, but chunked out into separate topical entries.(completeDecision on handling of serialization for spherical regions (keyword switch to use spherical?), or add note to docs that serialization will default read in planarNo serialization support for now / for consideration in a future PR.SkyRegionclasses only.Decision on whether or not (and how) to implement planar -> spherical conversion if boundary distortions are to be included.For consideration in a future PR.If folks think these classes would be a good candidate for inclusion, I will implement the outstanding test suite and documentation (and other code additions, pending discussion on the points noted above).
Related issues:
These new classes would address the following issues:
and also help to achieve the aims in:
An implementation (to be done) supporting conversion from planar to spherical accounting for boundary distortions would also address #217 (I have ideas on how to implement this, based on the spherical region class discretization).
Thanks, and looking forward to any feedback! I'd be very grateful for initial feedback by mid Sept (09/15), so I can work on next steps (either on the outstanding tasks, or figuring out some other way of enabling the functionality for the RRN example notebooks).
TODO