code cleanup

symmer/operators/utils.py

@@ -59,7 +59,7 @@ def numba_binary_matmal_GF2(A: np.array, B: np.array) -> np.array:
                 acc ^= A[i, k] & B[k, j]
             C[i, j] = acc
     return C
-g
+
 @nb.njit('(bool_[:,::1],bool_[:,::1])', fastmath=True, cache=True)
 def numba_dot_matmal_GF2(A, B):
     """
@@ -75,40 +75,7 @@ def numba_dot_matmal_GF2(A, B):
     return np.asarray(np.dot(np.asarray(A, dtype = np.float64),
                              np.asarray(B, dtype = np.float64)
                              )%2, 
-                      dtype = np.bool_) 
-
-    """
-    custom GF(2) multiplication using numba. i.e. C = (A@B) mod 2.
-    
-    Note function uses fact that multiplication over GF2 doesn't require sums for each matrix element in C
-    instead it uses and AND operation (same as elementwise multiplicaiton of row,col pairs) 
-    followed by XOR operation (same as taking sum of row,col multiplied pairs)
-    
-    Args:
-        A (np.array): numpy boolean array
-        B (np.array): numpy boolean array
-    Returns:
-        C (np.array): numpy boolean array of (A@B) mod 2
-    """
-    C = np.empty((A.shape[0], B.shape[1]), dtype=np.bool_)
-    for i in nb.prange(C.shape[0]):
-        for j in range(C.shape[1]):
-
-            ## logical version 1 (slower) 
-            # C[i, j] = bool(np.sum(np.logical_and(A[i, :], B[:, j]))%2)
-
-            # # logical version 2 (slower) 
-            # parity = False
-            # for bit in np.logical_and(A[i, :], B[:, j]):
-            #     parity^=bit
-            # C[i, j] = parity
-
-            ## faster loop
-            acc = False
-            for k in range(B.shape[0]):
-                acc ^= A[i, k] & B[k, j]
-            C[i, j] = acc
-    return C
+                      dtype = np.bool_)
 
 def symplectic_to_string(symp_vec) -> str:
     """