[MAINT] fix flake8 (nilearn#3869)

* fix flake8

* pacify the linting gods

nilearn/glm/tests/test_first_level.py

@@ -323,7 +323,7 @@ def test_run_glm():
     assert results[0.0].theta.shape == (q, n)
     assert_almost_equal(results[0.0].theta.mean(), 0, 1)
     assert_almost_equal(results[0.0].theta.var(), 1. / p, 1)
-    assert type(results[labels[0]].model) == OLSModel
+    assert isinstance(results[labels[0]].model, OLSModel)
 
     # ar(1) case
     labels, results = run_glm(Y, X, 'ar1')
@@ -332,15 +332,15 @@ def test_run_glm():
     tmp = sum([val.theta.shape[1] for val in results.values()])
     assert tmp == n
     assert results[labels[0]].model.order == 1
-    assert type(results[labels[0]].model) == ARModel
+    assert isinstance(results[labels[0]].model, ARModel)
 
     # ar(3) case
     labels_ar3, results_ar3 = run_glm(Y, X, 'ar3', bins=10)
     assert len(labels_ar3) == n
     assert len(results_ar3.keys()) > 1
     tmp = sum([val.theta.shape[1] for val in results_ar3.values()])
     assert tmp == n
-    assert type(results_ar3[labels_ar3[0]].model) == ARModel
+    assert isinstance(results_ar3[labels_ar3[0]].model, ARModel)
     assert results_ar3[labels_ar3[0]].model.order == 3
     assert len(results_ar3[labels_ar3[0]].model.rho) == 3
 

nilearn/maskers/tests/test_masker_validation.py

@@ -88,7 +88,7 @@ def test_check_embedded_nifti_masker():
         masker = _check_embedded_nifti_masker(
             owner, multi_subject=multi_subject
         )
-        assert type(masker) == type(mask)
+        assert isinstance(masker, type(mask))
         for param_key in masker.get_params():
             if param_key not in [
                 "memory",

nilearn/plotting/img_plotting.py

@@ -289,7 +289,7 @@ class _MNI152Template(SpatialImage):
     """Constant pointing to the MNI152 Template provided by nilearn."""
 
     data = None
-    affine = None
+    _affine = None
     vmax = None
     _shape = None
     # Having a header is required by the load_niimg function

nilearn/plotting/tests/test_html_surface.py

@@ -103,7 +103,7 @@ def test_one_mesh_info():
     assert len(info['vertexcolor_left']) == len(surf_map)
     cmax = np.max(np.abs(surf_map))
     assert (info['cmin'], info['cmax']) == (-cmax, cmax)
-    assert type(info['cmax']) == float
+    assert isinstance(info['cmax'], float)
     json.dumps(info)
     assert info['black_bg']
     assert not info['full_brain_mesh']
@@ -129,7 +129,7 @@ def test_full_brain_info():
     assert info['cmin'] == - info['cmax']
     assert info['full_brain_mesh']
     assert not info['black_bg']
-    assert type(info['cmax']) == float
+    assert isinstance(info['cmax'], float)
     json.dumps(info)
     for hemi in ['left', 'right']:
         mesh = surface.load_surf_mesh(surfaces[f'pial_{hemi}'])

nilearn/reporting/glm_reporter.py

@@ -438,9 +438,9 @@ def _make_headings(contrasts, title, model):
         If title is user-supplied, then subheading is empty string.
 
     """
-    if type(model) == glm.first_level.FirstLevelModel:
+    if isinstance(model, glm.first_level.FirstLevelModel):
         model_type = "First Level Model"
-    elif type(model) == glm.second_level.SecondLevelModel:
+    elif isinstance(model, glm.second_level.SecondLevelModel):
         model_type = "Second Level Model"
 
     if title: