Allowing for cross-correlations in HOD power spectrum. (#1224)

* Allowing for cross-correlations in HOD power spectrum. * Adding tests for consistency with Profile2pt. --------- Co-authored-by: damonge <[email protected]>
LSSTDESC · Feb 13, 2025 · 4aa9c0b · 4aa9c0b
1 parent 406b548
commit 4aa9c0b
Show file tree

Hide file tree

Showing 3 changed files with 49 additions and 16 deletions.
diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
@@ -48,7 +48,7 @@ jobs:
           channel-priority: strict
           show-channel-urls: true
           miniforge-version: latest
-          miniforge-variant: Mambaforge
+          miniforge-variant: Miniforge3
 
       - name: "macOS: set env variables"
         if: matrix.label == 'osx-64'

diff --git a/pyccl/halos/profiles_2pt.py b/pyccl/halos/profiles_2pt.py
@@ -126,8 +126,9 @@ def fourier_2pt(self, cosmo, k, M, a, prof, *, prof2=None, diag=True):
             prof2 (:class:`~pyccl.halos.profiles.hod.HaloProfileHOD` or :obj:`None`):
                 second halo profile for which the second-order moment
                 is desired. If ``None``, the assumption is that you want
-                an auto-correlation. Note that only auto-correlations
-                are allowed in this case.
+                an auto-correlation. If the profiles are different we assume disjoint 
+                tracers and revert back to the usual Fourier-space two-point moment 
+                (see Profile2pt).
             diag (bool): If True, both halo profiles depend on the same k. If
                 False, they will depend on k and k', respectively and we will
                 approximate <uk uk'> to <uk><uk'>. The output dimension will
@@ -145,21 +146,33 @@ def fourier_2pt(self, cosmo, k, M, a, prof, *, prof2=None, diag=True):
         if prof2 is None:
             prof2 = prof
 
+        # If the profiles are different assume disjoint tracers
         if prof != prof2:
-            raise ValueError("prof and prof2 must be equivalent")
+            uk1 = prof.fourier(cosmo, k, M, a)
+            uk2 = prof2.fourier(cosmo, k, M, a)
+
         HOD = HaloProfileHOD
         if not (isinstance(prof, HOD) and isinstance(prof2, HOD)):
             raise TypeError("prof and prof2 must be HaloProfileHOD")
 
         # TODO: This should be implemented in _fourier_variance
         if (diag is True) or (isinstance(k, float)):
-            output = prof._fourier_variance(cosmo, k, M, a)
+            if prof == prof2:
+                output = prof._fourier_variance(cosmo, k, M, a)
+            else:
+                output = uk1 * uk2 * (1 + self.r_corr)
         elif isinstance(M, float):
-            uk1 = prof.fourier(cosmo, k, M, a)
-            output = uk1[None, :] * uk1[:, None] * (1 + self.r_corr)
+            if prof == prof2:
+                uk1 = prof.fourier(cosmo, k, M, a)
+                output = uk1[None, :] * uk1[:, None] * (1 + self.r_corr)
+            else:
+                output = uk1[None, :] * uk2[:, None] * (1 + self.r_corr)
         else:
-            uk1 = prof.fourier(cosmo, k, M, a)
-            output = uk1[:, None, :] * uk1[:, :, None] * (1 + self.r_corr)
+            if prof == prof2:
+                uk1 = prof.fourier(cosmo, k, M, a)
+                output = uk1[:, None, :] * uk1[:, :, None] * (1 + self.r_corr)
+            else:
+                output = uk1[:, None, :] * uk2[:, :, None] * (1 + self.r_corr)
 
         return output
 

diff --git a/pyccl/tests/test_profiles.py b/pyccl/tests/test_profiles.py
@@ -325,10 +325,12 @@ def test_hod_2pt():
     pgood = ccl.halos.HaloProfileHOD(mass_def='200c', concentration=c)
     pgood_b = ccl.halos.HaloProfileHOD(mass_def='200c', concentration=c)
     p2 = ccl.halos.Profile2ptHOD()
+    p2pt = ccl.halos.Profile2pt()
     F0 = p2.fourier_2pt(COSMO, 1., 1e13, 1., pgood, prof2=pgood)
     assert np.allclose(p2.fourier_2pt(COSMO, 1., 1e13, 1., pgood, prof2=None),
                        F0, rtol=0)
 
+    # raises for non-HOD profile
     with pytest.raises(TypeError):
         p2.fourier_2pt(COSMO, 1., 1E13, 1., pbad)
 
@@ -337,26 +339,44 @@ def test_hod_2pt():
 
     p2.fourier_2pt(COSMO, 1., 1E13, 1., pgood, prof2=pgood_b)
 
-    with pytest.raises(ValueError):
-        pgood_b.update_parameters(log10M0_0=10.)
-        p2.fourier_2pt(COSMO, 1., 1E13, 1., pgood, prof2=pgood_b)
+    # doesn't raise for two different HOD profiles
+    pgood_b.update_parameters(log10M0_0=10.)
+    F = p2.fourier_2pt(COSMO, 1., 1E13, 1., pgood, prof2=pgood_b)
 
-    with pytest.raises(ValueError):
+    # check consistency with Profile2pt
+    assert np.allclose(F, p2pt.fourier_2pt(COSMO, 1., 1E13, 1., pgood,
+                       prof2=pgood_b))
+
+    # raises for non-HOD profile
+    with pytest.raises(TypeError):
         p2.fourier_2pt(COSMO, 1., 1e13, 1., pgood, prof2=pbad)
 
     # Test diag = False
     F = p2.fourier_2pt(COSMO, 1., 1E13, 1., pgood, prof2=pgood, diag=False)
     assert np.ndim(F) == 0
+    # check consistency with Profile2pt
+    F = p2.fourier_2pt(COSMO, 1., 1E13, 1., pgood, prof2=pgood_b, diag=False)
+    assert np.allclose(F, p2pt.fourier_2pt(COSMO, 1., 1E13, 1., pgood,
+                       prof2=pgood_b, diag=False))
     F = p2.fourier_2pt(COSMO, [1., 2], 1E13, 1., pgood, prof2=pgood,
                        diag=False)
     assert F.shape == (2, 2)
+    # check consistency with Profile2pt
+    F = p2.fourier_2pt(COSMO, [1., 2], 1E13, 1., pgood, prof2=pgood_b,
+                       diag=False)
+    assert np.allclose(F, p2pt.fourier_2pt(COSMO, [1., 2], 1E13, 1., pgood,
+                       prof2=pgood_b, diag=False))
     F = p2.fourier_2pt(COSMO, [1., 2], [1e12, 5e12, 1e13], 1., pgood,
                        prof2=pgood, diag=False)
     assert F.shape == (3, 2, 2)
-    F2 = ccl.halos.Profile2pt().fourier_2pt(COSMO, [1., 2],
-                                            [1e12, 5e12, 1e13], 1., pgood,
-                                            diag=False)
+    F2 = p2pt.fourier_2pt(COSMO, [1., 2], [1e12, 5e12, 1e13], 1., pgood,
+                          diag=False)
     assert np.all(F == F2)
+    # check consistency with Profile2pt
+    F = p2.fourier_2pt(COSMO, [1., 2], [1e12, 5e12, 1e13], 1., pgood,
+                       prof2=pgood_b, diag=False)
+    assert np.allclose(F, p2pt.fourier_2pt(COSMO, [1., 2], [1e12, 5e12, 1e13],
+                       1., pgood, prof2=pgood_b, diag=False))
 
 
 def test_2pt_rcorr_smoke():