Implementation of reduced shear in source selection for clusters by eduardojsbarroso · Pull Request #398 · LSSTDESC/TXPipe

eduardojsbarroso · 2025-08-01T11:38:49Z

So far, the cluster code only measures Delta Sigma from the select source galaxies around a cluster. We need to implement the same for gamma and we are also interested in using N(z) to select the galaxies behind the cluster instead of redshift PDF or zmode or zmean.

eduardojsbarroso · 2025-08-01T11:41:36Z

In this code. We set a maximum radius of search for galaxies around a cluster. Given the cluster redshift and a fiducial cosmology, we can transform this distance into an angle that changes for each cluster given their redshift.

If I do not want to assume any fiducial cosmology and search the galaxies by angle directly, should I use the same search angle for all clusters? Or is there some other approach to reescale this distance with redshift without using cosmology? @marina-ricci @joezuntz

joezuntz · 2025-08-01T13:56:03Z

There's definitely no way to convert a distance to an angle without knowing the cosmology. So I guess you would have to use the same angle, and make sure it's large enough. Why don't you want to use a fiducial cosmology? It shouldn't have a significant impact on the results at this level.

eduardojsbarroso · 2025-08-04T11:55:14Z

There's definitely no way to convert a distance to an angle without knowing the cosmology. So I guess you would have to use the same angle, and make sure it's large enough. Why don't you want to use a fiducial cosmology? It shouldn't have a significant impact on the results at this level.

Thank you for the reply Joe. I just wanted to know if there was any other way around it since we do not need the cosmology for the tangential signal. But ok, then I think I will leave this untouched and maybe add an option to use a constant angle if wanted

marina-ricci · 2025-09-22T14:45:51Z

@eduardojsbarroso for this special case I don't think it is a problem. Indeed we can use a fiducial cosmology just to define theta_max, it doesn't (should't) interfer with the "scientific" measurements. And even having radial binning in Mpc is not as much of a problem as having e.g. sigma_crit.

marina-ricci · 2025-09-22T14:58:16Z

Also, note for ourselves : we should through an error message when our binning is larger than the search radius (in case it's not hapening already)

marina-ricci · 2025-09-23T13:09:46Z

We decided it makes no sense to implement the N(z) method in source_compute_select, as it will be done more cleanly with the NG correlation.

eduardojsbarroso · 2025-09-26T14:33:27Z

@marina-ricci I have cleaned the option of Nz, as as discussed with @combet, we can implement this in another pull request, and a third one for the treecor option. Could you take a look at the code and check what you think?

eduardojsbarroso · 2025-09-26T14:33:46Z

Also, note for ourselves : we should through an error message when our binning is larger than the search radius (in case it's not hapening already)

I think this is already done in the make_ensemble_profile.py

            cat_max_distance = (clmm.utils.convert_units(np.max(bg_cat["distance_arcmin"]), "arcmin", "Mpc", z_cl, self.clmm_cosmo) if shear_units == "mpc" else np.max(bg_cat["distance_arcmin"]))
            if cat_max_distance < self.distance_bins[-1]:
                print ("!!! maximum distance of source smaller than distance_bins")

eduardojsbarroso · 2025-10-02T15:08:40Z

@marina-ricci I added a pipeline file to test this new functionalities and a notebook if you want to explore the results. Everything seems into place for me

joezuntz

In general I don't know enough to comment on the clusters code, so I will just review to make sure that things look structurally correct and don't cause any issues with the wider code.

This looks fine from that perspective, though I've added a note about a change you'll need to make because of other changes in the rest of the imports. I'm happy for you to merge it whenever the CL people are happy!

joezuntz · 2025-10-09T09:10:52Z

examples/cosmodc2/Cluster_pipelines/CLClusterReducedShear-20deg2-CL.yml

+    name: mini
+    interval: 3.0
+modules: >
+    txpipe


You will need to add txpipe.extensions here because of changes in the structuring of the code.

combet · 2026-02-06T13:57:09Z

examples/cosmodc2/Cluster_pipelines/config-20deg2-CL.yml

    nzbins: 301
-    columns_file: ./data/bpz_riz.columns
-    data_path: ./data/example/rail-bpz-inputs
+    columns_file: /sps/lsst/groups/clusters/cl_pipeline_project/TXPipe_data/bpz_riz.columns


Maybe avoid hard-coded paths (this is for cc-in2p3 only) so users may more easily use the examples. Or at least add a comment to explain how they should change it to match their setup.

combet · 2026-02-06T13:57:58Z

examples/cosmodc2/Cluster_pipelines/pipeline-20deg2-CL-in2p3.yml


-output_dir: ./data/cosmodc2/outputs-20deg2-CL
-config: ./examples/cosmodc2/Cluster_pipelines/config-20deg2-CL.yml
+output_dir: /sps/lsst/users/ebarroso/TXPipe/data/cosmodc2/outputs-20deg2-CL


Same as above regarding path

combet · 2026-02-06T14:01:58Z

txpipe/extensions/cluster_counts/convert_to_sacc.py

-        "r_min" : 0.2, #in Mpc
-        "r_max" : 5.0, #in Mpc
+        #distance bin definition
+        "d_min" : 0.5, #in Mpc or acrmin


To me, r_min and r_max is more intuitive than d_min, d_max. And 'radial bin' is more used I think, even when thinking of angular separation. Just a suggestion.

combet · 2026-02-06T14:04:34Z

txpipe/extensions/cluster_counts/convert_to_sacc.py

-        radius_edges = np.logspace(np.log10(rmin), np.log10(rmax), len(radius_centers) + 1)
-        for i in range(len(radius_edges) - 1):
-            bin_radius_dict[f'radius_{i}'] = (radius_edges[i], radius_edges[i+1], radius_centers[i])
+        distance_centers = np.array(data['bin_zbin_0_richbin_0']['clmm_cluster_ensemble'].stacked_data['radius'])


Similar comment as above. distance_centers is a bit cryptic. Maybe radial_bin_centers instead, or something along those lines?

combet · 2026-02-06T14:06:01Z

txpipe/extensions/cluster_counts/convert_to_sacc.py

-    def add_deltasigma_data(self, sacc_obj, data: dict, survey_name: str):
+    def add_shear_data(self, sacc_obj, data: dict, survey_name: str, profile_type: str):
        """
        Adds cluster shear (delta sigma) data to the SACC object.


Adds cluster reduced shear or delta sigma (depending on profile_type) profile to the SACC object.

combet · 2026-02-06T14:32:37Z

txpipe/extensions/cluster_counts/make_ensemble_profile.py

-        self.radial_bins = clmm.dataops.make_bins(self.config["r_min"], self.config["r_max"], nbins=self.config["nbins"], method="evenlog10width")
-        print (self.radial_bins) 
+        import clmm.cosmology.ccl 
+        if self.config["units"].lower() == "arcmin":


I find it a bit counter-intuitive to have a units keywords decide the type of radial binning (angular or in physical distance). Maybe there should be another keyword radial_bin_type (e.g. 'radius' or 'angle' ) or something like this to control it?

Good to keep the units information though, maybe to save it later as metadata in the sacc file?

combet · 2026-02-06T14:35:14Z

txpipe/extensions/cluster_counts/make_ensemble_profile.py

-
-            if (clmm.utils.convert_units(np.max(bg_cat["distance_arcmin"]), 'arcmin', 'Mpc', z_cl, self.clmm_cosmo)< self.radial_bins[-1]):
-                print ("!!! maximum radial distance of source smaller than radial_bins")
+            cat_max_distance = (clmm.utils.convert_units(np.max(bg_cat["distance_arcmin"]), "arcmin", "Mpc", z_cl, self.clmm_cosmo) if shear_units == "mpc" else np.max(bg_cat["distance_arcmin"]))


Need to find another name for shear_units. "shear" in this code is either dimensionless or surface mass density if working with DeltaSigma.

combet · 2026-02-06T14:35:55Z

txpipe/extensions/cluster_counts/make_ensemble_profile.py

            gc_object.make_radial_profile(
-                    "Mpc", 
-                    bins=self.radial_bins,
+                    shear_units, 


Same as above

Initial implementation of gamma and nz source selectio

ab5fb6c

eduardojsbarroso mentioned this pull request Sep 16, 2025

Tangential shear implementation in TXPipe data vector and N(z) source selection LSSTDESC/CLPipeline#12

Open

5 tasks

Continued make cluster ensemble implementation

0671897

eduardojsbarroso added 3 commits September 25, 2025 04:46

Initial clean of Nz choice

0737dd0

Cleaned and tested reduced shear

9468ec6

Cleaned Nz option and tested notebook

64de747

eduardojsbarroso changed the title ~~Implementation of reduced shear and N(z) in source selection for clusters~~ Implementation of reduced shear in source selection for clusters Sep 26, 2025

eduardojsbarroso requested a review from marina-ricci September 26, 2025 14:30

eduardojsbarroso closed this Sep 26, 2025

eduardojsbarroso reopened this Sep 26, 2025

eduardojsbarroso marked this pull request as ready for review September 26, 2025 14:35

eduardojsbarroso marked this pull request as draft September 29, 2025 09:10

Cleaned Notebook and added 20deg example

f9df36f

eduardojsbarroso marked this pull request as ready for review October 2, 2025 15:07

eduardojsbarroso requested a review from joezuntz October 3, 2025 08:06

joezuntz approved these changes Oct 9, 2025

View reviewed changes

eduardojsbarroso and others added 4 commits January 22, 2026 10:58

Merge branch 'master' into clusters_source_selection

dcd80ef

Fixed binning for angular binning

e6ff3aa

Fix typo

d2f07cf

Fix angle choice

2a67cb9

eduardojsbarroso requested a review from combet February 6, 2026 10:53

Updated notebook

a8cb73a

combet reviewed Feb 6, 2026

View reviewed changes

Changed covariance computation and save in sacc

8fdb79f

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eduardojsbarroso commented Aug 4, 2025 •

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