remove some style errors in bench code.

Author: amueller

benchmarks/bench_multilabel_metrics.py

@@ -139,7 +139,7 @@ def _plot(results, metrics, formats, title, x_ticks, x_label,
     ap = argparse.ArgumentParser()
     ap.add_argument('metrics', nargs='*', default=sorted(METRICS),
                     help='Specifies metrics to benchmark, defaults to all. '
-                         'Choices are: '.format(sorted(METRICS)))
+                         'Choices are: {}'.format(sorted(METRICS)))
     ap.add_argument('--formats', nargs='+', choices=sorted(FORMATS),
                     help='Specifies multilabel formats to benchmark '
                          '(defaults to all).')

benchmarks/bench_sparsify.py

@@ -58,7 +58,7 @@ def sparsity_ratio(X):
 X = np.random.randn(n_samples, n_features)
 inds = np.arange(n_samples)
 np.random.shuffle(inds)
-X[inds[n_features/1.2:]] = 0  # sparsify input
+X[inds[int(n_features / 1.2):]] = 0  # sparsify input
 print("input data sparsity: %f" % sparsity_ratio(X))
 coef = 3 * np.random.randn(n_features)
 inds = np.arange(n_features)
@@ -81,17 +81,18 @@ def sparsity_ratio(X):
 clf.fit(X_train, y_train)
 print("model sparsity: %f" % sparsity_ratio(clf.coef_))
 
-@profile
+
 def benchmark_dense_predict():
     for _ in range(300):
         clf.predict(X_test)
 
-@profile
+
 def benchmark_sparse_predict():
     X_test_sparse = csr_matrix(X_test)
     for _ in range(300):
         clf.predict(X_test_sparse)
 
+
 def score(y_test, y_pred, case):
     r2 = r2_score(y_test, y_pred)
     print("r^2 on test data (%s) : %f" % (case, r2))