sty: Use a format template instead of % strings

Author: effigies

nibabel/benchmarks/bench_array_to_file.py

@@ -29,24 +29,25 @@ def bench_array_to_file():
     sys.stdout.flush()
     print_git_title('\nArray to file')
     mtime = measure('array_to_file(arr, BytesIO(), np.float32)', repeat)
-    print('%30s %6.2f' % ('Save float64 to float32', mtime))
+    fmt = '{:30s} {:6.2f}'.format
+    print(fmt('Save float64 to float32', mtime))
     mtime = measure('array_to_file(arr, BytesIO(), np.int16)', repeat)
-    print('%30s %6.2f' % ('Save float64 to int16', mtime))
+    print(fmt('Save float64 to int16', mtime))
     # Set a lot of NaNs to check timing
     arr[:, :, :, 1] = np.nan
     mtime = measure('array_to_file(arr, BytesIO(), np.float32)', repeat)
-    print('%30s %6.2f' % ('Save float64 to float32, NaNs', mtime))
+    print(fmt('Save float64 to float32, NaNs', mtime))
     mtime = measure('array_to_file(arr, BytesIO(), np.int16)', repeat)
-    print('%30s %6.2f' % ('Save float64 to int16, NaNs', mtime))
+    print(fmt('Save float64 to int16, NaNs', mtime))
     # Set a lot of infs to check timing
     arr[:, :, :, 1] = np.inf
     mtime = measure('array_to_file(arr, BytesIO(), np.float32)', repeat)
-    print('%30s %6.2f' % ('Save float64 to float32, infs', mtime))
+    print(fmt('Save float64 to float32, infs', mtime))
     mtime = measure('array_to_file(arr, BytesIO(), np.int16)', repeat)
-    print('%30s %6.2f' % ('Save float64 to int16, infs', mtime))
+    print(fmt('Save float64 to int16, infs', mtime))
     # Int16 input, float output
     arr = np.random.random_integers(low=-1000, high=1000, size=img_shape)
     arr = arr.astype(np.int16)
     mtime = measure('array_to_file(arr, BytesIO(), np.float32)', repeat)
-    print('%30s %6.2f' % ('Save Int16 to float32', mtime))
+    print(fmt('Save Int16 to float32', mtime))
     sys.stdout.flush()

nibabel/benchmarks/bench_finite_range.py

@@ -28,16 +28,17 @@ def bench_finite_range():
     sys.stdout.flush()
     print_git_title('\nFinite range')
     mtime = measure('finite_range(arr)', repeat)
-    print('%30s %6.2f' % ('float64 all finite', mtime))
+    fmt = '{:30s} {:6.2f}'.format
+    print(fmt('float64 all finite', mtime))
     arr[:, :, :, 1] = np.nan
     mtime = measure('finite_range(arr)', repeat)
-    print('%30s %6.2f' % ('float64 many NaNs', mtime))
+    print(fmt('float64 many NaNs', mtime))
     arr[:, :, :, 1] = np.inf
     mtime = measure('finite_range(arr)', repeat)
-    print('%30s %6.2f' % ('float64 many infs', mtime))
+    print(fmt('float64 many infs', mtime))
     # Int16 input, float output
     arr = np.random.random_integers(low=-1000, high=1000, size=img_shape)
     arr = arr.astype(np.int16)
     mtime = measure('finite_range(arr)', repeat)
-    print('%30s %6.2f' % ('int16', mtime))
+    print(fmt('int16', mtime))
     sys.stdout.flush()

nibabel/benchmarks/bench_load_save.py

@@ -34,20 +34,21 @@ def bench_load_save():
     print_git_title('Image load save')
     hdr.set_data_dtype(np.float32)
     mtime = measure('sio.truncate(0); img.to_file_map()', repeat)
-    print('%30s %6.2f' % ('Save float64 to float32', mtime))
+    fmt = '{:30s} {:6.2f}'.format
+    print(fmt('Save float64 to float32', mtime))
     mtime = measure('img.from_file_map(img.file_map)', repeat)
-    print('%30s %6.2f' % ('Load from float32', mtime))
+    print(fmt('Load from float32', mtime))
     hdr.set_data_dtype(np.int16)
     mtime = measure('sio.truncate(0); img.to_file_map()', repeat)
-    print('%30s %6.2f' % ('Save float64 to int16', mtime))
+    print(fmt('Save float64 to int16', mtime))
     mtime = measure('img.from_file_map(img.file_map)', repeat)
-    print('%30s %6.2f' % ('Load from int16', mtime))
+    print(fmt('Load from int16', mtime))
     # Set a lot of NaNs to check timing
     arr[:, :, :20] = np.nan
     mtime = measure('sio.truncate(0); img.to_file_map()', repeat)
-    print('%30s %6.2f' % ('Save float64 to int16, NaNs', mtime))
+    print(fmt('Save float64 to int16, NaNs', mtime))
     mtime = measure('img.from_file_map(img.file_map)', repeat)
-    print('%30s %6.2f' % ('Load from int16, NaNs', mtime))
+    print(fmt('Load from int16, NaNs', mtime))
     # Int16 input, float output
     arr = np.random.random_integers(low=-1000, high=1000, size=img_shape)
     arr = arr.astype(np.int16)
@@ -57,5 +58,5 @@ def bench_load_save():
     hdr = img.header
     hdr.set_data_dtype(np.float32)
     mtime = measure('sio.truncate(0); img.to_file_map()', repeat)
-    print('%30s %6.2f' % ('Save Int16 to float32', mtime))
+    print(fmt('Save Int16 to float32', mtime))
     sys.stdout.flush()