Adding validation tests for TwoPoint compute_theory_vector with a win…

…dow function. (#407)

The benchmark was computed using v1.6.0 and agrees with versions 1.5.0 -- 1.8.0a.
For version 1.5.0 the used pyccl was 2.8.0 and the tests agree with larger relative difference (~1.0e-4).
The other versions agree with better relative difference (~1.0e-8).

tests/test_bug398.py

@@ -2,47 +2,206 @@
 
 import os
 import sacc
+import pyccl
+
+from numpy.testing import assert_allclose
 
 import firecrown.likelihood.gauss_family.statistic.source.weak_lensing as wl
 from firecrown.likelihood.gauss_family.statistic.two_point import TwoPoint
 from firecrown.likelihood.gauss_family.gaussian import ConstGaussian
 from firecrown.modeling_tools import ModelingTools
-from firecrown.likelihood.likelihood import Likelihood
+from firecrown.likelihood.likelihood import Likelihood, NamedParameters
+from firecrown.parameters import ParamsMap
 
 
-def build_likelihood(build_parameters) -> tuple[Likelihood, ModelingTools]:
+def build_likelihood(
+    build_parameters: NamedParameters,
+) -> tuple[Likelihood, ModelingTools]:
     """Sample build_likelihood function for this test."""
     # Load sacc file
-    sacc_data = build_parameters["sacc_data"]
+    sacc_data = build_parameters.get_string("sacc_data")
     if isinstance(sacc_data, str):
         sacc_data = sacc.Sacc.load_fits(sacc_data)
 
-    tracer = wl.WeakLensing(sacc_tracer="src0")
+    src2 = wl.WeakLensing(sacc_tracer="src2")
+    lens0 = wl.WeakLensing(sacc_tracer="lens0")
 
-    stat = TwoPoint(
-        source0=tracer,
-        source1=tracer,
+    src2_src2 = TwoPoint(
+        source0=src2,
+        source1=src2,
         sacc_data_type="galaxy_shear_cl_ee",
     )
+    lens0_src2 = TwoPoint(
+        source0=lens0,
+        source1=src2,
+        sacc_data_type="galaxy_shearDensity_cl_e",
+    )
+    lens0_lens0 = TwoPoint(
+        source0=lens0,
+        source1=lens0,
+        sacc_data_type="galaxy_density_cl",
+    )
 
     modeling_tools = ModelingTools()
-    likelihood = ConstGaussian(statistics=[stat])
+    likelihood = ConstGaussian(statistics=[src2_src2, lens0_lens0, lens0_src2])
 
     likelihood.read(sacc_data)
 
     return likelihood, modeling_tools
 
 
 SACC_FILE = f"{os.environ.get('FIRECROWN_DIR')}/tests/bug_398.sacc.gz"
+SRC2_SRC2_CL_VANILLA_LCDM = [
+    1.69967963e-08,
+    1.38304980e-08,
+    1.11710737e-08,
+    8.71397605e-09,
+    6.68547501e-09,
+    5.09033805e-09,
+    3.77901452e-09,
+    2.76406946e-09,
+    2.04066288e-09,
+    1.50726429e-09,
+    1.12124517e-09,
+    8.46301538e-10,
+    6.42890014e-10,
+    4.92175018e-10,
+    3.78141820e-10,
+    2.89146863e-10,
+    2.18883359e-10,
+    1.63234403e-10,
+    1.19329161e-10,
+    8.52290961e-11,
+]
+LENS0_SRC2_CL_VANILLA_LCDM = [
+    7.03230915e-09,
+    5.49457937e-09,
+    4.31384700e-09,
+    3.26079168e-09,
+    2.41076958e-09,
+    1.78545473e-09,
+    1.32078595e-09,
+    9.79735232e-10,
+    7.36331539e-10,
+    5.58205184e-10,
+    4.27474837e-10,
+    3.30625472e-10,
+    2.55229767e-10,
+    1.96190406e-10,
+    1.49387782e-10,
+    1.11823128e-10,
+    8.19932945e-11,
+    5.87369958e-11,
+    4.10027651e-11,
+    2.78742176e-11,
+]
+LENS0_LENS0_CL_VANILLA_LCDM = [
+    4.37776266e-09,
+    3.37609715e-09,
+    2.61446339e-09,
+    1.94567058e-09,
+    1.42725712e-09,
+    1.06135857e-09,
+    7.91131823e-10,
+    5.92201116e-10,
+    4.50680940e-10,
+    3.45536945e-10,
+    2.66780679e-10,
+    2.06964268e-10,
+    1.59341776e-10,
+    1.21456419e-10,
+    9.12602758e-11,
+    6.71391079e-11,
+    4.82457923e-11,
+    3.38192742e-11,
+    2.30934916e-11,
+    1.53693074e-11,
+]
 
 
 def test_broken_window_function():
     likelihood, modeling_tools = build_likelihood(
-        build_parameters={"sacc_data": SACC_FILE}
+        build_parameters=NamedParameters({"sacc_data": SACC_FILE})
     )
     assert likelihood is not None
     assert modeling_tools is not None
 
 
+def test_eval_cl_window_src2_src2():
+    tools = ModelingTools()
+    cosmo = pyccl.CosmologyVanillaLCDM()
+    params = ParamsMap()
+
+    tools.update(params)
+    tools.prepare(cosmo)
+
+    sacc_data = sacc.Sacc.load_fits(SACC_FILE)
+    src2 = wl.WeakLensing(sacc_tracer="src2")
+
+    src2_src2 = TwoPoint(
+        source0=src2,
+        source1=src2,
+        sacc_data_type="galaxy_shear_cl_ee",
+    )
+
+    src2_src2.read(sacc_data)
+    src2_src2.update(params)
+
+    theory_vector = src2_src2.compute_theory_vector(tools)
+    assert_allclose(theory_vector, SRC2_SRC2_CL_VANILLA_LCDM, rtol=1e-8)
+
+
+def test_eval_cl_window_lens0_src2():
+    tools = ModelingTools()
+    cosmo = pyccl.CosmologyVanillaLCDM()
+    params = ParamsMap()
+
+    tools.update(params)
+    tools.prepare(cosmo)
+
+    sacc_data = sacc.Sacc.load_fits(SACC_FILE)
+    src2 = wl.WeakLensing(sacc_tracer="src2")
+    lens0 = wl.WeakLensing(sacc_tracer="lens0")
+
+    lens0_src2 = TwoPoint(
+        source0=lens0,
+        source1=src2,
+        sacc_data_type="galaxy_shearDensity_cl_e",
+    )
+
+    lens0_src2.read(sacc_data)
+    lens0_src2.update(params)
+
+    theory_vector = lens0_src2.compute_theory_vector(tools)
+    assert_allclose(theory_vector, LENS0_SRC2_CL_VANILLA_LCDM, rtol=1e-8)
+
+
+def test_eval_cl_window_lens0_lens0():
+    tools = ModelingTools()
+    cosmo = pyccl.CosmologyVanillaLCDM()
+    params = ParamsMap()
+
+    tools.update(params)
+    tools.prepare(cosmo)
+
+    sacc_data = sacc.Sacc.load_fits(SACC_FILE)
+    lens0 = wl.WeakLensing(sacc_tracer="lens0")
+
+    lens0_lens0 = TwoPoint(
+        source0=lens0,
+        source1=lens0,
+        sacc_data_type="galaxy_density_cl",
+    )
+
+    lens0_lens0.read(sacc_data)
+    lens0_lens0.update(params)
+
+    theory_vector = lens0_lens0.compute_theory_vector(tools)
+    assert_allclose(theory_vector, LENS0_LENS0_CL_VANILLA_LCDM, rtol=1e-8)
+
+
 if __name__ == "__main__":
     test_broken_window_function()
+    test_eval_cl_window_src2_src2()
+    test_eval_cl_window_lens0_src2()
+    test_eval_cl_window_lens0_lens0()