MNT: Apply refurb suggestion

[FURB113]: Use `x.extend(...)` instead of repeatedly calling `x.append()`

Author: DimitriPapadopoulos

nibabel/cifti2/tests/test_cifti2.py

@@ -326,8 +326,7 @@ def test_matrixindicesmap():
     parcel = ci.Cifti2Parcel()
 
     assert mim.volume is None
-    mim.append(volume)
-    mim.append(parcel)
+    mim.extend((volume, parcel))
 
 
     assert mim.volume == volume

nibabel/cifti2/tests/test_new_cifti2.py

@@ -232,8 +232,7 @@ def test_dtseries():
     series_map = create_series_map((0, ))
     geometry_map = create_geometry_map((1, ))
     matrix = ci.Cifti2Matrix()
-    matrix.append(series_map)
-    matrix.append(geometry_map)
+    matrix.extend((series_map, geometry_map))
     hdr = ci.Cifti2Header(matrix)
     data = np.random.randn(13, 10)
     img = ci.Cifti2Image(data, hdr)
@@ -254,8 +253,7 @@ def test_dscalar():
     scalar_map = create_scalar_map((0, ))
     geometry_map = create_geometry_map((1, ))
     matrix = ci.Cifti2Matrix()
-    matrix.append(scalar_map)
-    matrix.append(geometry_map)
+    matrix.extend((scalar_map, geometry_map))
     hdr = ci.Cifti2Header(matrix)
     data = np.random.randn(2, 10)
     img = ci.Cifti2Image(data, hdr)
@@ -276,8 +274,7 @@ def test_dlabel():
     label_map = create_label_map((0, ))
     geometry_map = create_geometry_map((1, ))
     matrix = ci.Cifti2Matrix()
-    matrix.append(label_map)
-    matrix.append(geometry_map)
+    matrix.extend((label_map, geometry_map))
     hdr = ci.Cifti2Header(matrix)
     data = np.random.randn(2, 10)
     img = ci.Cifti2Image(data, hdr)
@@ -318,8 +315,7 @@ def test_ptseries():
     series_map = create_series_map((0, ))
     parcel_map = create_parcel_map((1, ))
     matrix = ci.Cifti2Matrix()
-    matrix.append(series_map)
-    matrix.append(parcel_map)
+    matrix.extend((series_map, parcel_map))
     hdr = ci.Cifti2Header(matrix)
     data = np.random.randn(13, 4)
     img = ci.Cifti2Image(data, hdr)
@@ -340,8 +336,7 @@ def test_pscalar():
     scalar_map = create_scalar_map((0, ))
     parcel_map = create_parcel_map((1, ))
     matrix = ci.Cifti2Matrix()
-    matrix.append(scalar_map)
-    matrix.append(parcel_map)
+    matrix.extend((scalar_map, parcel_map))
     hdr = ci.Cifti2Header(matrix)
     data = np.random.randn(2, 4)
     img = ci.Cifti2Image(data, hdr)
@@ -362,8 +357,7 @@ def test_pdconn():
     geometry_map = create_geometry_map((0, ))
     parcel_map = create_parcel_map((1, ))
     matrix = ci.Cifti2Matrix()
-    matrix.append(geometry_map)
-    matrix.append(parcel_map)
+    matrix.extend((geometry_map, parcel_map))
     hdr = ci.Cifti2Header(matrix)
     data = np.random.randn(10, 4)
     img = ci.Cifti2Image(data, hdr)
@@ -384,8 +378,7 @@ def test_dpconn():
     parcel_map = create_parcel_map((0, ))
     geometry_map = create_geometry_map((1, ))
     matrix = ci.Cifti2Matrix()
-    matrix.append(parcel_map)
-    matrix.append(geometry_map)
+    matrix.extend((parcel_map, geometry_map))
     hdr = ci.Cifti2Header(matrix)
     data = np.random.randn(4, 10)
     img = ci.Cifti2Image(data, hdr)
@@ -406,8 +399,7 @@ def test_plabel():
     label_map = create_label_map((0, ))
     parcel_map = create_parcel_map((1, ))
     matrix = ci.Cifti2Matrix()
-    matrix.append(label_map)
-    matrix.append(parcel_map)
+    matrix.extend((label_map, parcel_map))
     hdr = ci.Cifti2Header(matrix)
     data = np.random.randn(2, 4)
     img = ci.Cifti2Image(data, hdr)
@@ -448,8 +440,7 @@ def test_pconnseries():
     series_map = create_series_map((2, ))
 
     matrix = ci.Cifti2Matrix()
-    matrix.append(parcel_map)
-    matrix.append(series_map)
+    matrix.extend((parcel_map, series_map))
     hdr = ci.Cifti2Header(matrix)
     data = np.random.randn(4, 4, 13)
     img = ci.Cifti2Image(data, hdr)
@@ -473,8 +464,7 @@ def test_pconnscalar():
     scalar_map = create_scalar_map((2, ))
 
     matrix = ci.Cifti2Matrix()
-    matrix.append(parcel_map)
-    matrix.append(scalar_map)
+    matrix.extend((parcel_map, scalar_map))
     hdr = ci.Cifti2Header(matrix)
     data = np.random.randn(4, 4, 2)
     img = ci.Cifti2Image(data, hdr)
@@ -499,8 +489,7 @@ def test_wrong_shape():
     brain_model_map = create_geometry_map((1, ))
 
     matrix = ci.Cifti2Matrix()
-    matrix.append(scalar_map)
-    matrix.append(brain_model_map)
+    matrix.extend((scalar_map, brain_model_map))
     hdr = ci.Cifti2Header(matrix)
 
     # correct shape is (2, 10)

nibabel/cmdline/dicomfs.py

@@ -117,8 +117,7 @@ def readdir(self, path, fh):
             return -errno.ENOENT
         logger.debug(f'matched {matched_path}')
         fnames = [k.encode('ascii', 'replace') for k in matched_path.keys()]
-        fnames.append('.')
-        fnames.append('..')
+        fnames.extend(('.', '..'))
         return [fuse.Direntry(f) for f in fnames]
 
     def getattr(self, path):

nibabel/streamlines/tck.py

@@ -249,12 +249,13 @@ def _write_header(fileobj, header):
                    Field.VOXEL_TO_RASMM,  # Streamlines are always in RAS+ mm.
                    "count", "datatype", "file"]  # Fields being replaced.
 
-        lines = []
-        lines.append(f"count: {header[Field.NB_STREAMLINES]:010}")
-        lines.append("datatype: Float32LE")  # Always Float32LE.
-        lines.extend([f"{k}: {v}"
-                      for k, v in header.items()
-                      if k not in exclude and not k.startswith("_")])
+        lines = [
+            f"count: {header[Field.NB_STREAMLINES]:010}",
+            "datatype: Float32LE",  # Always Float32LE.
+        ]
+        lines.extend(f"{k}: {v}"
+                     for k, v in header.items()
+                     if k not in exclude and not k.startswith("_"))
         out = "\n".join(lines)
 
         # Check the header is well formatted.

nibabel/tests/data/gen_standard.py

@@ -35,19 +35,17 @@ def _gen_straight_streamline(start, end, steps=3):
         return np.array(coords).T
 
     # Generate a 3D 'X' template fitting inside the voxel centered at (0,0,0).
-    X = []
-    X.append(_gen_straight_streamline((-0.5, -0.5, -0.5), (0.5, 0.5, 0.5)))
-    X.append(_gen_straight_streamline((-0.5, 0.5, -0.5), (0.5, -0.5, 0.5)))
-    X.append(_gen_straight_streamline((-0.5, 0.5, 0.5), (0.5, -0.5, -0.5)))
-    X.append(_gen_straight_streamline((-0.5, -0.5, 0.5), (0.5, 0.5, -0.5)))
+    X = [
+        _gen_straight_streamline((-0.5, -0.5, -0.5), (0.5, 0.5, 0.5)),
+        _gen_straight_streamline((-0.5, 0.5, -0.5), (0.5, -0.5, 0.5)),
+        _gen_straight_streamline((-0.5, 0.5, 0.5), (0.5, -0.5, -0.5)),
+        _gen_straight_streamline((-0.5, -0.5, 0.5), (0.5, 0.5, -0.5)),
+    ]
 
     # Get the coordinates of voxels 'on' in the mask.
     coords = np.array(zip(*np.where(mask)))
 
-    streamlines = []
-    for c in coords:
-        for line in X:
-            streamlines.append((line + c) * voxel_size)
+    streamlines = [(line + c) * voxel_size for line in X for c in coords]
 
     return streamlines