Added the biopython implementation to the timing benchmark.

alignementseq_tests.py

@@ -145,8 +145,13 @@ class PerformanceTestCase(AlignmentSeqTestCase):
 
     def test_performance(self):
         from alignementseq import align, vec_align
+        def biopython_align(seq1, seq2):
+            return Bio.pairwise2.align.globalds(
+                seq1.seq, seq2.seq, blosum62, -8, -8,
+                one_alignment_only=True)[0]
 
-        methods = (vec_align, align)
+
+        methods = (vec_align, align, biopython_align)
         times = pd.DataFrame(columns=("length1", "length2", "method", "time"),
                 dtype=float)
         for s1, s2, filename in self.get_dataset_heads():
@@ -162,7 +167,7 @@ class PerformanceTestCase(AlignmentSeqTestCase):
         
         ax = None
         cmap = matplotlib.cm.inferno
-        colors = [ cmap(i/2) for i in range(2) ]
+        colors = [ cmap(i/len(methods)) for i in range(len(methods)) ]
         for im, method in enumerate(methods):
             ax = times.loc[times.method == method.__name__].plot.scatter(
                     'length_product', 'time', c=colors[im],