Simplify condition

1 files changed, 3 insertions, 1 deletions

diff --git a/train.py b/train.py
index 3b2b364..0b0ce0e 100755
--- a/train.py
+++ b/train.py
@@ -64,6 +64,7 @@ parser.add_argument("-2", "--grapheigen", help="Swow 2D graph of targets versus
 parser.add_argument("-p", "--pca", help="Use PCA", action='store_true')
 parser.add_argument("-l", "--lda", help="Use LDA", action='store_true')
 parser.add_argument("-r", "--reconstruct", help="Use PCA reconstruction, specify face NR", type=int, default=0)
+
 parser.add_argument("-q", "--pca_r", help="Use Reduced PCA", action='store_true')
 
 args = parser.parse_args()
@@ -85,7 +86,7 @@ sc = StandardScaler()
 
 explained_variances = ()
 
-if args.pca or (args.pca and args.lda) or args.pca_r:
+if args.pca or args.pca_r:
     # faces_pca containcts the principial components or the M most variant eigenvectors
     average_face = np.mean(faces_train, axis=0) 
     faces_train = normalise_faces(average_face, faces_train)
@@ -94,6 +95,7 @@ if args.pca or (args.pca and args.lda) or args.pca_r:
         e_vals, e_vecs = LA.eigh(np.cov(faces_train))
         e_vecs_original = e_vecs
         e_vecs = np.dot(faces_train.T, e_vecs) 
+        # e_vecs = normalise_faces(np.mean(e_vecs,axis=0), e_vecs)
         e_vecs = sc.fit_transform(e_vecs)
         ###TODO Maybe replace with our normalising function