Fix log product formula for NCH (#336)

* Update distance.py

* Update pyriemann_qiskit/utils/distance.py

Co-authored-by: Quentin Barthélemy <q.barthelemy@gmail.com>

* Update distance.py

---------

Co-authored-by: Quentin Barthélemy <q.barthelemy@gmail.com>

pyriemann_qiskit/utils/distance.py

@@ -110,17 +110,17 @@ def weights_logeuclid_to_convex_hull(A, B, optimizer=ClassicalOptimizer()):
     n_matrices, _, _ = A.shape
     matrices = range(n_matrices)
 
-    def log_prod(m1, m2):
-        return np.nansum(logm(m1).flatten() * logm(m2).flatten())
+    def trace_prod_log(m1, m2):
+        return np.trace(logm(m1) @ logm(m2))
 
     prob = Model()
     optimizer = get_global_optimizer(optimizer)
     w = optimizer.get_weights(prob, matrices)
 
     wtLogAtLogAw = prob.sum(
-        w[i] * w[j] * log_prod(A[i], A[j]) for i in matrices for j in matrices
+        w[i] * w[j] * trace_prod_log(A[i], A[j]) for i in matrices for j in matrices
     )
-    wLogBLogA = prob.sum(w[i] * log_prod(B, A[i]) for i in matrices)
+    wLogBLogA = prob.sum(w[i] * trace_prod_log(B, A[i]) for i in matrices)
     objective = wtLogAtLogAw - 2 * wLogBLogA
 
     prob.set_objective("min", objective)