File nilearn-fix-aarch64.patch of Package python-nilearn

From 92ff7284c3e9ce921129d99ccb81f7a21572aa9f Mon Sep 17 00:00:00 2001
From: KamalakerDadi <dkamalakarreddy@gmail.com>
Date: Sat, 14 Nov 2020 05:15:53 +0100
Subject: [PATCH] FIX testing issues with nans and infs on ARM

---
 doc/whats_new.rst                                    | 8 ++++++++
 nilearn/input_data/tests/test_nifti_labels_masker.py | 5 +++--
 nilearn/masking.py                                   | 2 +-
 nilearn/regions/tests/test_region_extractor.py       | 5 +++--
 4 files changed, 15 insertions(+), 5 deletions(-)

diff --git a/doc/whats_new.rst b/doc/whats_new.rst
index d128ef5c0c..e2c6ce1b2e 100644
--- a/doc/whats_new.rst
+++ b/doc/whats_new.rst
@@ -1,3 +1,11 @@
+0.7.X
+=====
+
+Fixes
+-----
+
+- Fix testing issues on ARM machine.
+
 .. _v0.7.0:
 
 0.7.0
diff --git a/nilearn/input_data/tests/test_nifti_labels_masker.py b/nilearn/input_data/tests/test_nifti_labels_masker.py
index 6324b10cf7..b61a89a1ff 100644
--- a/nilearn/input_data/tests/test_nifti_labels_masker.py
+++ b/nilearn/input_data/tests/test_nifti_labels_masker.py
@@ -117,8 +117,9 @@ def test_nifti_labels_masker_with_nans_and_infs():
     labels_img = data_gen.generate_labeled_regions((13, 11, 12),
                                                    affine=np.eye(4),
                                                    n_regions=n_regions)
-    # nans
-    mask_data = get_data(mask_img)
+    # Introduce nans with data type float
+    # See issue: https://github.com/nilearn/nilearn/issues/2580
+    mask_data = get_data(mask_img).astype(np.float32)
     mask_data[:, :, 7] = np.nan
     mask_data[:, :, 4] = np.inf
     mask_img = nibabel.Nifti1Image(mask_data, np.eye(4))
diff --git a/nilearn/masking.py b/nilearn/masking.py
index c4c8ab36c3..a828e8a2e8 100644
--- a/nilearn/masking.py
+++ b/nilearn/masking.py
@@ -44,7 +44,7 @@ def _load_mask_img(mask_img, allow_empty=False):
         boolean version of the mask
     """
     mask_img = _utils.check_niimg_3d(mask_img)
-    mask = get_data(mask_img)
+    mask = _safe_get_data(mask_img, ensure_finite=True)
     values = np.unique(mask)
 
     if len(values) == 1:
diff --git a/nilearn/regions/tests/test_region_extractor.py b/nilearn/regions/tests/test_region_extractor.py
index d8e8a9b56c..6600336134 100644
--- a/nilearn/regions/tests/test_region_extractor.py
+++ b/nilearn/regions/tests/test_region_extractor.py
@@ -355,14 +355,15 @@ def test_connected_label_regions():
 
     # Test if unknown/negative integers are provided as labels in labels_img,
     # we raise an error and test the same whether error is raised.
-    labels_data = np.zeros(shape, dtype=np.int)
+    # Introduce data type of float, see issue: https://github.com/nilearn/nilearn/issues/2580
+    labels_data = np.zeros(shape, dtype=np.float32)
     h0 = shape[0] // 2
     h1 = shape[1] // 2
     h2 = shape[2] // 2
     labels_data[:h0, :h1, :h2] = 1
     labels_data[:h0, :h1, h2:] = 2
     labels_data[:h0, h1:, :h2] = 3
-    labels_data[:h0, h1:, h2:] = 4
+    labels_data[:h0, h1:, h2:] = -4
     labels_data[h0:, :h1, :h2] = 5
     labels_data[h0:, :h1, h2:] = 6
     labels_data[h0:, h1:, :h2] = np.nan