add method to compute confusion matrix between binarized counts and m…

…odify todo statement comments

src/dialect/models/interaction.py

@@ -1,6 +1,7 @@
 import logging
 import numpy as np
 from scipy.optimize import minimize
+from sklearn.metrics import confusion_matrix
 
 from dialect.models.gene import Gene
 
@@ -76,7 +77,19 @@ def verify_pi_values(self, pi_a, pi_b):
     # ---------------------------------------------------------------------------- #
     #                        Likelihood & Metric Evaluation                        #
     # ---------------------------------------------------------------------------- #
-    # TODO: Add additional metrics (KL, MI, etc.) for further exploration
+    # TODO (LOW PRIORITY): Add additional metrics (KL, MI, etc.)
+
+    def compute_contingency_table(self):
+        """
+        Compute the contingency table (confusion matrix) for binarized counts
+        between gene_a and gene_b.
+
+        :return: A 2x2 numpy array representing the contingency table.
+        """
+        gene_a_mutations = (self.gene_a.counts > 0).astype(int)
+        gene_b_mutations = (self.gene_b.counts > 0).astype(int)
+        cm = confusion_matrix(gene_a_mutations, gene_b_mutations, labels=[0, 1])
+        return cm
 
     def compute_joint_probability(self, tau, u, v):
         joint_probability = np.array(
@@ -153,6 +166,7 @@ def compute_log_likelihood(self, taus):
         a_counts, b_counts = self.gene_a.counts, self.gene_b.counts
         a_bmr_pmf, b_bmr_pmf = self.gene_a.bmr_pmf, self.gene_b.bmr_pmf
         tau_00, tau_01, tau_10, tau_11 = taus
+        # TODO: Moddify all passenger key access to not default to 0
         log_likelihood = sum(
             np.log(
                 a_bmr_pmf.get(c_a, 0) * b_bmr_pmf.get(c_b, 0) * tau_00
@@ -374,7 +388,6 @@ def negative_log_likelihood(tau):
             f"Estimated tau parameters for interaction {self.name}: tau_00={self.tau_00}, tau_01={self.tau_01}, tau_10={self.tau_10}, tau_11={self.tau_11}"
         )
 
-    # TODO: Implement this method
     def estimate_tau_with_em_from_scratch(
         self, max_iter=1000, tol=1e-6, tau_init=[0.25, 0.25, 0.25, 0.25]
     ):