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gh-136: Implementation of variable depth #535
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… classes which incorporate variable depth These classes alter output the ratio in the galaxy counts between the case where variable depth occurs and without variable depth
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Thanks for the amazing work on this, @mwiet! This PR will require some design changes and adhering to good practices (tests, PEP8 conventions, ...), but I think we can discuss those once the functionality is ready and approved.
pre-commit.ci autofix |
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Sorry quite a lot of changes, but we can iterate.
As a minimum we need all CI to pass. Have a look at pre-commit. That is currently failing. You can run pre-commit run -a
locally.
Also as @Saransh-cpp says we really need tests to go with this work.
Co-authored-by: Patrick J. Roddy <patrickjamesroddy@gmail.com>
Co-authored-by: Patrick J. Roddy <patrickjamesroddy@gmail.com>
Co-authored-by: Patrick J. Roddy <patrickjamesroddy@gmail.com>
…ed them to the bibliography.rst
I have fixed most of the typing, naming convention and documentation issues. The only outstanding issue flagged by pre-commit is In terms of tests, I will try to add some useful test functions to |
Thanks so much for doing that! Appreciate there were few things in there, but that has been a lot of development velocity in the last six months.
Ah, don't worry about that. Simple functions are something to strive for, but it is not always possible. You can suppress that error using |
Co-authored-by: Patrick J. Roddy <patrickjamesroddy@gmail.com>
Co-authored-by: Patrick J. Roddy <patrickjamesroddy@gmail.com>
docs/examples.rst
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@@ -46,3 +46,4 @@ More advanced examples doing multiple things at the same time. | |||
examples/2-advanced/cosmic_shear.ipynb | |||
examples/2-advanced/stage_4_galaxies.ipynb | |||
examples/2-advanced/legacy-mode.ipynb | |||
examples/2-advanced/variable_depth_example.ipynb |
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Not sure if we want this public, was more for making sure the docs CI passed
This reverts commit eb412f7.
Thanks for the fantastic work @mwiet! From your side, I think we are all set, you can tick the box on the to-do list :) For us, I believe we should align this more closely with the overall roadmap for sampling galaxies in GLASS. I see a couple of tasks before merging: We do not need the two classes. The base class checks for a valid index before accessing an array of maps; numpy does that for us, we can therefore simply use the stack of matrices. The work that the other class does in And, importantly, a lot of the "variable depth functionality" is actually happening in the notebook, not in the library. Creating the stack of depth maps from a tracer, for example, is something that we need to provide. Think of it this way: how would a user go about creating the inputs for variable depth? Everything they would need to copy and paste verbatim from the example notebook should be provided by GLASS, I believe. |
"Ob = 0.05\n", | ||
"\n", | ||
"# basic parameters of the simulation\n", | ||
"nside = lmax = 64\n", |
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The resolution was initially 1024. I have had to drop it to 64 as otherwise this notebook takes a really long time. 128 would be suitable, but the pre-allocation array step becomes too big in CI (based on GH runners), so went with 64. Still gives similar results (by eye).
"metadata": {}, | ||
"outputs": [ | ||
{ | ||
"data": { | ||
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This section was initially
for i in range(nbins):
for j in range(len(zbins)):
and displayed every single hp.mollview
. This took a long time and made the notebook huge, so I have just made it one.
"source": [ | ||
"for i in range(nbins):\n", | ||
" plt.plot(z_grid, tomo_nz[i] / n_arcmin2[i], label=f\"bin {i}\", c=\"k\")\n", | ||
" for j in range(n_vardepth_bins):\n", | ||
" plt.plot(\n", | ||
" z_grid,\n", | ||
" dndz_vd[i, j],\n", | ||
" label=f\"bin {i}, vd {j}\",\n", | ||
" alpha=0.5,\n", | ||
" color=f\"C{i}\",\n", | ||
" )\n", | ||
"plt.xlim(0, 1.5)\n", | ||
"plt.ylim(0, 2.3)\n", | ||
"plt.xlabel(\"z\")\n", | ||
"plt.ylabel(\"dN/dz [Normalised]\");" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [ | ||
{ | ||
"data": { | ||
"image/png": 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iqC3DhJRiKJWjXDlmHs9/7Gtnkouf2y44AEIIOJn7wc40//w7iYhowQ93aiU7FCKGnPsSKfYP0hgkSGVj0tiu0jWXY5u0P5B2HyQJbTxXOzk2X7KnKXuzkcrtXHPxmTZI45pzfWLQZ/tDGIFxAUEEWiUXQTkaMaQ1T4hxfvPF15eoefoo5srFrlMiV7c8jqg9IWQbH7jK7+o4wXEbuoZu7hpCHhsCCNRh4cU7sudDs0MpSuVi1wr53OLscfKxNOVv0r5G9rGEPT+p1MzVjkje9FUT24XvufF9+NI3nyNejjRPe88o7R5J0liuDNIXV/2j+PwASA0EEWgFUwjJgiZ8vVCIs1zoeqEYcwOXc5zURxPXXeLmn6N2HKL2s0GhBgmxjOOdbvlrIIRAOkxhNO7sUDWGPxvkMk+IMWvQjK+l7v5GJjH7JWnFkYSmJK+uA55vjqHldtovOyGMQBtAEIFGedVlf0ZEOhHjWy+kKWVTlZcl2FfI256dRVzcuu5xcgx/JssXu659dlMGCVJ5W5tADIEmyEVRU9kh1349KY0TfCVxOXYpnMvYIMTNLmSvo7bRzDNkfyJpryLtpq5SCZyr3I7Ibdhgjyu52ZltIIxAk0AQgeTkIignVAwR+df0aOMS1TdPSGWcEGPIUG3nb+M6n3KdUFNrhFKVxbXJ8tdcQ7d+4YDiGICm2fLiHYiI6NEj76FFP1rCtgnNDqXYcNUkNBvkGse+udZkhDSler7SMQ0uN7w6sbX9Q7NLmrI3jcudby5SuZ2r1E5TvdHvZfSFI/5JnAMAMUAQgWSYQkgrHHxrhrQlcerMiiN2qMFBHeOElC5ydqw2TBNi1wkRuc0PQvcNkswN2iQXQLd+4QCIIdAqW168Az165D1ERBVRFFMql9JWO2StkG8MbjyNaYOUadHOh9sHyGf84NoPSYN2jFAk0VQ3g8TN3ze+a0wzjrQHkwmEEUgFBBGojSsj5D4XZ6DgEjJa4wS7X6ho0YihGEMGeWxmLKUQksZx/eGnzgo1URo37ncuiB/QRXJh1EZ2qE6pXMwYXGmcz+ggH1OTwQkZv4njfAyN01wxp8BslMYUwjUPyThBa6Kg2RspH8dVWmfHhTACdYEgAtHYQignxXohrm9oeZs2dqjBgTbTkso4QWOaECKG2iyNa8owIeW7lu1wpwFiCHSZxZc8pTiuK4bcMdKUysUILs14mrE11DVsqEvtPYwCM0qubJJqPM+aJN+YdcwZIIxALBBEIJjXXP7/I6J6a3tcgijWPEEjhlKbJxD51wvFGCfUNU1IZaPdhBgyy+Jc7bjx6pbFSfsWaY8hhMAksfiSp7SSHZLK0lxlZJKNtq8kTlMOF1rKptmLyH7O40K7dxLbN7AEz2fioBrTkenhxtdmqXwxP3fEP7PzAUACggioyYUQUToxRORe16ONm2Kz1VDzBOkPJ9SQQSOGuHZ8X132yhfXfV4cIjqmO1Zwl2Rjm6x47do0EwGgRba5dPvKudTZoaYzQtp9jKSxQ/cpcpWCufZGij1uCsk8wbWHkaYEL8Y4oTwvd5mdPYb0nLiYNhBGQAsEEXBiiiATTcYmlYGCSwxp1gyFZpfUZguaNoGCSCOGum6aEHvdFz+UUIMGFxBDYJKxRZFGEGld5doQQz40GSFNVsUWRcPzZdtv+3HX0IislNkkl/V2nexRbHzu55UDcQRcQBABlpMu/1MiCl+DI7dpx0Chq+YJsWVydrtQMZRKCA2vhcUKb+Nt4o2fUvzc8vkDIYTAVLHNpdvTg8/+NRERbfvj7dSiRRINKTdZjV2PxO+X5M8C2fOSsjga5mhA89Rv/dhFaIbKl0Fjxwg0TgjJHpljSKV1sWYQEEaAA4IIlMiFEFEzYihVTN9Gq764dcwTmjZOKI2VUAzVKWObBDGUAgggMEts/+Nt2fOSILIZV3ZIY5AQut6nbtZnjsazvkgjjjRoM0uqWIH7JdUxUQiND2EEJCCIABGVhVBOKrODuoLIW+KWwDxBM49Q84SwNuXHdfYW4uYZK4ZiSuTq7CWkIWU2yARiCMwitihqQwyF7CWkia8tgdNkTYrxrawMEamyNyHkY3PleaHri+apX5qn5phDMx+tVXjK7E6oMYMv/hODuSLm+Yf/C/tagNkCgmjGef0Vb1J9CxNrduAyUPDFUK25idjENVQM+YSQFFPXhrxt1PGV/fxjiV0UfXUCqNfTjxUaPwaIITDLmKKoTUFkx9PsIcTH1gmR0CyQJHBSGitoaNKsITTDpI3tM22ozCOwzM5nzBBaxkcEYTTrQBDNKK+/4k3Fcawgcmd16q8ZUgmKQPMEO443k+S4Js0rdr2QVmRos0KumNK1NsQQkd4+u6lsUA6EEAAjllz25OK47qarkimBT2CFWHe7YkpZDkmExGR3bFzZldD5cNSJXzf7pJkP36Zb2aPS84IwAgYQRDOITwzVLZXTfDNU10DBN8cUYogojZNcqIucdC6VcYLrWqyLXJOlcU0BMQRAlVwUaQVR/k08J4Zs0mWbZKOEkAyMVO4WYrvNz685a+6UWaLQvpoSQi6uxsCBKD67kzJ79IfBHBFBFM0iEEQzhCmEcrg3C2cb8VsgtyAKzeRIYkgzR9c8JfHiy7rEiqFqG7aJ1zxhnGJoHHbaEEMAjI8dLt9avMZlb2xSCKI65XG+DIwmG1TXZCF1dqgOPnEkzSU0k0SkK8HL44Zmj0rjODJSrjEr55n4fxjMFfP6z2d+iu0Hpg8Iohngj35yOi9SArMubJ/K47BSOY2QCTFQ0IgSdR/HvLpgqw0xpGPFa9fSLZ8/sDgGAPgxRdE9RzxUPM7Fy7ic5LTlcaUxNmUwOHMBrr8mw5RyjVA+R3Nuqey3TXzizPeFpytbZhNj4DD8N132KKbETtocFsJo+oEgmmL+6CenF8eS7aRJnTVD7DgBGSdVdiUig+XLtoSKoVgnubb2GIIYKgMBBEA6dr5icXEcK4gk84RS28DskEsE5cc+YrI1vnFDibXuTmW9bRJbfuciJHtUPhdn0CDFMcWW5n4Iwmg2gCCaQkwhlOMTRCkc5SrjBKzziRFEvuySJovjWjNkX++KrTY3z9S22m2JoSzrUW/TTUWsGOKMGno9iCEAmmDnKxbXyg65zBOqa5H89twakwRfRsg+drXJr7lK3kLtr+tYd9v4Yqey4TYf25/lPiMHzRyktUcpDRpC1h3Z8f7tsH9lXy8wuUAQTRGnXvlG9puR1NkhuQ0vhmLjhdhre/t7+kh/BP7MT5gYqmOrXbT19HOdL7eRzmv6cq93mJ12imyQNM5uJ0EMAdAUu16xFXs+v/mVTA9Slcf5StI0BgmajJArfso9iVJZaIfEk2JzwiikVE+zXskHN5bmS9jSeU+JnSqG8Vo9kf8+W/EgjKYHCKIp4NQr31gcSzaSo3OWEIlYkxO6big0Xoi9dh2zA58gSl0qFypefPOLEUO+v/bYzVZj7bTrADEEwPiwRRFnrW1ndlKYJ8QYJsRmhFyEZIFC5qI55qgTTxJGmuflK4Nzff6G2ICbwohdAxSQPapj7f1E1q/EgyiaDiCIJhhTCBH5xdDwvFyCVrmuuFGvK4bs8ynEkB3HW1rnmRM3L91aJXlO7n7++Y1DDMXGDY3nGseVgYIQAqB9cmFkZoc4QrJDMeVxdmbGlQ3yZY1cGRGNVbd2HA1zvQHNb/qcDT0OxZU98mWrfBkzTZbK10Zr8z06z6wZSrwxrBmvTxl9+rBPSy8R6DgQRBOILYRyxi2I6mabfHsNaeKldpOzY+rGZMaIzGSFOMmNQwxpYofGc41hZ6AgggDoDst+sihIEMU4yVXiKp3jpHghmSZ7HGlMH5os1BzzGsxn/eK8dCwRK5I4Ysr4pAxPSJbIFEaatU/Vc/WtvV1LEMyYEEaTBwTRBHHalacRUfWPN6Ym1ic2dI/1jnKhpXIpxJBvfKL6Yqjaxn09JHaIGJLOa/+6QwVWaHxtvJAxIIYA6B4rrtyyci42O+TLqkiiRTZ3qJojmHF8Bgdc5kJT0ubL5riup4YTUnWyTqFrn1y24lI833h5XCleCmtvV+boiU2buXLzgjCaHCCIJgRODEnWkkRCKZsgOHyZIM1ixhAB4xMWofbamjU4PsERuxYpdNNVbVx7fq5Y8hj8fELnJ/fTxdfGCxkDYgiA7mKKolgjhZB1POX+bjEUEismjhg/QtxoMj8pqZNpkgRhSDYpJNujuc7F09zPFOcCbb3NO 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This section was very slow in the initial implementation. By pre-allocating the catalogue, it is significantly quicker.
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# check the shape of the output | |||
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np.testing.assert_array_equal(binned_nz.shape, (len(zbins), len(z))) | |||
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@pytest.mark.parametrize( |
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I started to add tests yesterday before @ntessore's review. It feels pointless continuing these given the proposed changes.
Some notes @mwiet sent me, which I think would be good to have here so they don't get lost.
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This actually closes #136, not 413. |
This merge request implements variable depth's effect on the galaxy density in the angular and line-of-sight directions into GLASS. This closes #136.
This code allows for functionality similar to SALMO. The implementation adds two novel features:
The
glass.observations.angular_variable_depth_mask
implements the basic structure and functionality for the object, but only outputs the variable depth masks in the angular direction as they have been input.The
angular_los_variable_depth_mask
expends upon this functionality by implementing the aformentioned features. Hence, when sampling galaxies usingglass.points.positions_from_delta
, one can multiply the givenvis
visibility mask by the output ofangular_los_variable_depth_mask
for a given tomographic bin and redshift shell index.Tests with KiDS-1000-like mock
Testing this implementation with KiDS-1000 data (see here) gives results consistent with previous mocks on the same data:
Overall redshift distributions are consistent with inputs:

Local redshift distributions are shifted due to variable depth (e.g. North vs. South field):

Between 2% and 10% (on average) of additional power is added to the measured pseudo-Cls from the realised galaxy fields:

Performance
The inclusion of the
angular_los_variable_depth_mask
when sampling the KiDS-1000-like galaxies added an additional 14 seconds to the total runtime on my local machine (from 7m 14s to 7m 28s, i.e. a 3.2% increase). In this time,angular_los_variable_depth_mask
was evaluated 165 times (n_bins x n_shells = 5 x 33).Potential extensions
Note that this implementation does not include the variability in the intrinsic shapes of galaxies which may be caused by variable depth. Additional features will be necessary for this in
glass.shapes
to allow the inputsigma
to vary per pixel.