TEST: Purge get_data() from algorithms.tests.*

Author: effigies

nipype/algorithms/tests/test_CompCor.py

@@ -124,7 +124,7 @@ def test_tcompcor_no_percentile(self):
         ccinterface = TCompCor(num_components=6, realigned_file=self.realigned_file)
         ccinterface.run()
 
-        mask = nb.load("mask_000.nii.gz").get_data()
+        mask = nb.load("mask_000.nii.gz").dataobj
         num_nonmasked_voxels = np.count_nonzero(mask)
         assert num_nonmasked_voxels == 1
 
@@ -153,7 +153,7 @@ def test_tcompcor_asymmetric_dim(self):
         )
 
         TCompCor(realigned_file=asymmetric_data).run()
-        assert nb.load("mask_000.nii.gz").get_data().shape == asymmetric_shape[:3]
+        assert nb.load("mask_000.nii.gz").shape == asymmetric_shape[:3]
 
     def test_compcor_bad_input_shapes(self):
         # dim 0 is < dim 0 of self.mask_files (2)
@@ -183,12 +183,12 @@ def test_tcompcor_merge_intersect_masks(self):
             ).run()
             if method == "union":
                 assert np.array_equal(
-                    nb.load("mask_000.nii.gz").get_data(),
+                    nb.load("mask_000.nii.gz").dataobj,
                     ([[[0, 0], [0, 0]], [[0, 0], [1, 0]]]),
                 )
             if method == "intersect":
                 assert np.array_equal(
-                    nb.load("mask_000.nii.gz").get_data(),
+                    nb.load("mask_000.nii.gz").dataobj,
                     ([[[0, 0], [0, 0]], [[0, 1], [0, 0]]]),
                 )
 
@@ -197,8 +197,7 @@ def test_tcompcor_index_mask(self):
             realigned_file=self.realigned_file, mask_files=self.mask_files, mask_index=1
         ).run()
         assert np.array_equal(
-            nb.load("mask_000.nii.gz").get_data(),
-            ([[[0, 0], [0, 0]], [[0, 1], [0, 0]]]),
+            nb.load("mask_000.nii.gz").dataobj, ([[[0, 0], [0, 0]], [[0, 1], [0, 0]]])
         )
 
     def test_tcompcor_multi_mask_no_index(self):

nipype/algorithms/tests/test_normalize_tpms.py

@@ -19,7 +19,7 @@
 def test_normalize_tpms(tmpdir):
 
     in_mask = example_data("tpms_msk.nii.gz")
-    mskdata = nb.load(in_mask, mmap=NUMPY_MMAP).get_data()
+    mskdata = np.asanyarray(nb.load(in_mask, mmap=NUMPY_MMAP).dataobj)
     mskdata[mskdata > 0.0] = 1.0
 
     mapdata = []
@@ -32,8 +32,8 @@ def test_normalize_tpms(tmpdir):
         out_files.append(tmpdir.join("normtpm_%02d.nii.gz" % i).strpath)
 
         im = nb.load(mapname, mmap=NUMPY_MMAP)
-        data = im.get_data()
-        mapdata.append(data.copy())
+        data = im.get_fdata()
+        mapdata.append(data)
 
         nb.Nifti1Image(2.0 * (data * mskdata), im.affine, im.header).to_filename(
             filename
@@ -45,7 +45,7 @@ def test_normalize_tpms(tmpdir):
     sumdata = np.zeros_like(mskdata)
 
     for i, tstfname in enumerate(out_files):
-        normdata = nb.load(tstfname, mmap=NUMPY_MMAP).get_data()
+        normdata = nb.load(tstfname, mmap=NUMPY_MMAP).get_fdata()
         sumdata += normdata
         assert np.all(normdata[mskdata == 0] == 0)
         assert np.allclose(normdata, mapdata[i])

nipype/algorithms/tests/test_splitmerge.py

@@ -15,8 +15,9 @@ def test_split_and_merge(tmpdir):
 
     in_mask = example_data("tpms_msk.nii.gz")
     dwfile = tmpdir.join("dwi.nii.gz").strpath
-    mskdata = nb.load(in_mask, mmap=NUMPY_MMAP).get_data()
-    aff = nb.load(in_mask, mmap=NUMPY_MMAP).affine
+    mask_img = nb.load(in_mask, mmap=NUMPY_MMAP)
+    mskdata = np.asanyarray(mask_img.dataobj)
+    aff = mask_img.affine
 
     dwshape = (mskdata.shape[0], mskdata.shape[1], mskdata.shape[2], 6)
     dwdata = np.random.normal(size=dwshape)
@@ -25,7 +26,7 @@ def test_split_and_merge(tmpdir):
 
     resdw, resmsk, resid = split_rois(dwfile, in_mask, roishape=(20, 20, 2))
     merged = merge_rois(resdw, resid, in_mask)
-    dwmerged = nb.load(merged, mmap=NUMPY_MMAP).get_data()
+    dwmerged = nb.load(merged, mmap=NUMPY_MMAP).get_fdata(dtype=np.float32)
 
     dwmasked = dwdata * mskdata[:, :, :, np.newaxis]
 

nipype/algorithms/tests/test_stats.py

@@ -19,7 +19,7 @@ def test_ActivationCount(tmpdir):
     diff = nb.load(res.outputs.out_file)
     pos = nb.load(res.outputs.acm_pos)
     neg = nb.load(res.outputs.acm_neg)
-    assert np.allclose(diff.get_data(), pos.get_data() - neg.get_data())
+    assert np.allclose(diff.get_fdata(), pos.get_fdata() - neg.get_fdata())
 
 
 @pytest.mark.parametrize(
@@ -43,8 +43,8 @@ def test_ActivationCount_normaldistr(tmpdir, threshold, above_thresh):
     pos = nb.load(res.outputs.acm_pos)
     neg = nb.load(res.outputs.acm_neg)
     assert np.isclose(
-        pos.get_data().mean(), above_thresh * 1.0e-2, rtol=0.1, atol=1.0e-4
+        pos.get_fdata().mean(), above_thresh * 1.0e-2, rtol=0.1, atol=1.0e-4
     )
     assert np.isclose(
-        neg.get_data().mean(), above_thresh * 1.0e-2, rtol=0.1, atol=1.0e-4
+        neg.get_fdata().mean(), above_thresh * 1.0e-2, rtol=0.1, atol=1.0e-4
     )