File update-tests-for-numpy-123.patch of Package python-librosa

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File update-tests-for-numpy-123.patch of Package python-librosa (Revision 8151e1765236fb72f771f3927f49fce1)

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From 5dd212036667a524cf29480d5351ee5e5eca5693 Mon Sep 17 00:00:00 2001
From: Brian McFee <brian.mcfee@nyu.edu>
Date: Mon, 26 Sep 2022 13:26:26 -0400
Subject: [PATCH] updated tests for numpy 1.23 compatibility

---
 tests/test_core.py         | 2 ++
 tests/test_multichannel.py | 6 +++---
 tests/test_util.py         | 6 +++---
 3 files changed, 8 insertions(+), 6 deletions(-)

diff --git a/tests/test_core.py b/tests/test_core.py
index 57c3458aee..d83f5b6e5a 100644
--- a/tests/test_core.py
+++ b/tests/test_core.py
@@ -2122,6 +2122,8 @@ def test_pcen_stream_multi(axis):
     slice2 = [slice(None)] * x.ndim
     slice2[axis] = slice(10, None)
 
+    slice1 = tuple(slice1)
+    slice2 = tuple(slice2)
     # Compute pcen piecewise
     p1, zf1 = librosa.pcen(x[slice1], return_zf=True, axis=axis)
     p2, zf2 = librosa.pcen(x[slice2], zi=zf1, return_zf=True, axis=axis)
diff --git a/tests/test_multichannel.py b/tests/test_multichannel.py
index 19531842fd..8a0490bd82 100644
--- a/tests/test_multichannel.py
+++ b/tests/test_multichannel.py
@@ -65,13 +65,13 @@ def test_sync_multi(aggregate, ndim, axis):
     idx = [slice(None)] * ndim
     idx[axis] = 0
     if aggregate is np.sum:
-        assert np.allclose(dsync[idx], 2)
+        assert np.allclose(dsync[tuple(idx)], 2)
     else:
-        assert np.allclose(dsync[idx], 1)
+        assert np.allclose(dsync[tuple(idx)], 1)
 
     # The second slice will sum to 1 and have mean 1
     idx[axis] = 1
-    assert np.allclose(dsync[idx], 1)
+    assert np.allclose(dsync[tuple(idx)], 1)
 
 
 def test_stft_multi(y_multi):
diff --git a/tests/test_util.py b/tests/test_util.py
index 1b90087611..eebbf432c2 100644
--- a/tests/test_util.py
+++ b/tests/test_util.py
@@ -877,13 +877,13 @@ def test_sync(aggregate, ndim, axis):
     idx = [slice(None)] * ndim
     idx[axis] = 0
     if aggregate is np.sum:
-        assert np.allclose(dsync[idx], 2)
+        assert np.allclose(dsync[tuple(idx)], 2)
     else:
-        assert np.allclose(dsync[idx], 1)
+        assert np.allclose(dsync[tuple(idx)], 1)
 
     # The second slice will sum to 1 and have mean 1
     idx[axis] = 1
-    assert np.allclose(dsync[idx], 1)
+    assert np.allclose(dsync[tuple(idx)], 1)
 
 
 @pytest.mark.parametrize("aggregate", [np.mean, np.max])

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File update-tests-for-numpy-123.patch of Package python-librosa (Revision 8151e1765236fb72f771f3927f49fce1)

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