Add Hartlap correction to CrossCorrelation likelihoods (#94)

* added hartlap ncovsims to crosscorrelation

* Implement tests with tox-conda (#92)

* added configuration for tox-conda

* run tests with tox-conda

* data file locations and test skips

* make tests run in workflow

* add pytest-cov

* removed codestyle env typo

* added codestyle to envlist

* tox-conda version for codestyle

* added python version to codestyle workflow

* codestyle on 3.10 specifically

* flake8 fixes

* do not install everything for codestyle

* added temp fix for flaky sklearn install

* modified installation and testing instructions

* update action versions

* remove inapplicable parts of astropy cookie cutter, mention conda env in INSTALL.rst

* add make to conda deps

* test ncovsims

* added hartlap test

soliket/CrossCorrelationLikelihood.yaml

@@ -9,6 +9,8 @@ z_nuisance_mode: null
 m_nuisance_mode: null
 ia_mode: null
 
+ncovsims: null
+
 params:
   b1: 
     prior:

soliket/cross_correlation.py

@@ -21,7 +21,7 @@ def initialize(self):
 
             x, y, dy = self._get_data()
             cov = np.diag(dy**2)
-            self.data = GaussianData("CrossCorrelation", x, y, cov)
+            self.data = GaussianData("CrossCorrelation", x, y, cov, self.ncovsims)
         else:
             self._get_sacc_data()
 
@@ -53,7 +53,7 @@ def _get_sacc_data(self, **params_values):
         self.y = self.sacc_data.mean
         self.cov = self.sacc_data.covariance.covmat
 
-        self.data = GaussianData(self.name, self.x, self.y, self.cov)
+        self.data = GaussianData(self.name, self.x, self.y, self.cov, self.ncovsims)
 
     def _construct_ell_bins(self):
 

soliket/tests/test_cross_correlation.py

@@ -123,6 +123,46 @@ def test_shearkappa_like(request):
     assert np.isclose(loglikes, 637.64473666)
 
 
+def test_shearkappa_hartlap(request):
+
+    from soliket.cross_correlation import ShearKappaLikelihood
+
+    rootdir = request.config.rootdir
+
+    cs82_file = "soliket/tests/data/cs82_gs-planck_kappa_binned.sim.sacc.fits"
+    test_datapath = os.path.join(rootdir, cs82_file)
+
+    info["likelihood"] = {
+        "ShearKappaLikelihood": {"external": ShearKappaLikelihood,
+                                 "datapath": test_datapath}
+    }
+
+    # Cosmological parameters for the test data, digitized from
+    # Fig. 3 and Eq. 8 of Hall & Taylor (2014).
+    # See https://github.com/simonsobs/SOLikeT/pull/58 for validation plots
+    info['params'] = {"omch2": 0.118,  # Planck + lensing + WP + highL
+                      "ombh2": 0.0222,
+                      "H0": 68.0,
+                      "ns": 0.962,
+                      # "As": 2.1e-9,
+                      "As": 2.5e-9, # offset the theory to upweight inv_cov in loglike
+                      "tau": 0.094,
+                      "mnu": 0.0,
+                      "nnu": 3.046,
+                      "s1": 0.4,
+                      "b1": 1.0}
+
+    model = get_model(info)
+    loglikes, derived = model.loglikes()
+
+    info["likelihood"]["ShearKappaLikelihood"]["ncovsims"] = 5
+
+    model = get_model(info)
+    loglikes_hartlap, derived = model.loglikes()
+
+    assert np.isclose(np.abs(loglikes - loglikes_hartlap), 0.00104092)
+
+
 def test_shearkappa_deltaz(request):
 
     from soliket.cross_correlation import ShearKappaLikelihood