Added kappa lambda likelihood

external_chi2/kappa_lambda/chi2_kappa_lambda.py

@@ -0,0 +1,39 @@
+import jax.numpy as jnp
+import numpy as np
+from pathlib import Path
+import pickle
+
+# Get the directory of the current file
+current_dir = Path(__file__).parent
+
+
+class HLLHC_kappa_lambda_chi2:
+    def __init__(self, coefficients, rgemat=None):
+        self.wc = [
+            "Op",
+        ]
+        self.rgemat = rgemat
+        self.chi2_path = current_dir / "kappa_lambda_HL-LHC_likelihood.pkl"
+
+        # coefficients is a list with the names of the coefficients. We need to create a projection matrix
+        # that projects the coefficients to the basis of the observables
+        self.project = np.zeros((len(self.wc), coefficients.size))
+        for i, op in enumerate(self.wc):
+            if op in coefficients.name:
+                self.project[i, np.argwhere(coefficients.name == op)[0, 0]] = 1
+
+        if self.rgemat is not None:
+            self.project = jnp.einsum("ij,jk->ik", self.project, self.rgemat)
+
+        # load pickle file
+        with open(self.chi2_path, "rb") as f:
+            self.chi2 = pickle.load(f)
+
+    def compute_chi2(self, coefficient_values):
+        coeffs_vals = jnp.dot(self.project, coefficient_values)
+        # now we have to transform cphi in klambda
+        klambda = 1 - 0.47 * coeffs_vals
+
+        chi2_value = self.chi2(klambda).squeeze()
+
+        return chi2_value