Daniel Garcia
20d85c46a2
- Add remove-hanning-from-tests.patch gh#librosa/librosa#1548 OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-librosa?expand=0&rev=25
67 lines
2.2 KiB
Diff
67 lines
2.2 KiB
Diff
From 5dd212036667a524cf29480d5351ee5e5eca5693 Mon Sep 17 00:00:00 2001
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From: Brian McFee <brian.mcfee@nyu.edu>
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Date: Mon, 26 Sep 2022 13:26:26 -0400
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Subject: [PATCH] updated tests for numpy 1.23 compatibility
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---
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tests/test_core.py | 2 ++
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tests/test_multichannel.py | 6 +++---
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tests/test_util.py | 6 +++---
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3 files changed, 8 insertions(+), 6 deletions(-)
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diff --git a/tests/test_core.py b/tests/test_core.py
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index 57c3458aee..d83f5b6e5a 100644
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--- a/tests/test_core.py
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+++ b/tests/test_core.py
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@@ -2122,6 +2122,8 @@ def test_pcen_stream_multi(axis):
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slice2 = [slice(None)] * x.ndim
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slice2[axis] = slice(10, None)
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+ slice1 = tuple(slice1)
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+ slice2 = tuple(slice2)
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# Compute pcen piecewise
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p1, zf1 = librosa.pcen(x[slice1], return_zf=True, axis=axis)
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p2, zf2 = librosa.pcen(x[slice2], zi=zf1, return_zf=True, axis=axis)
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diff --git a/tests/test_multichannel.py b/tests/test_multichannel.py
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index 19531842fd..8a0490bd82 100644
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--- a/tests/test_multichannel.py
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+++ b/tests/test_multichannel.py
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@@ -65,13 +65,13 @@ def test_sync_multi(aggregate, ndim, axis):
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idx = [slice(None)] * ndim
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idx[axis] = 0
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if aggregate is np.sum:
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- assert np.allclose(dsync[idx], 2)
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+ assert np.allclose(dsync[tuple(idx)], 2)
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else:
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- assert np.allclose(dsync[idx], 1)
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+ assert np.allclose(dsync[tuple(idx)], 1)
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# The second slice will sum to 1 and have mean 1
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idx[axis] = 1
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- assert np.allclose(dsync[idx], 1)
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+ assert np.allclose(dsync[tuple(idx)], 1)
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def test_stft_multi(y_multi):
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diff --git a/tests/test_util.py b/tests/test_util.py
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index 1b90087611..eebbf432c2 100644
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--- a/tests/test_util.py
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+++ b/tests/test_util.py
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@@ -877,13 +877,13 @@ def test_sync(aggregate, ndim, axis):
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idx = [slice(None)] * ndim
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idx[axis] = 0
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if aggregate is np.sum:
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- assert np.allclose(dsync[idx], 2)
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+ assert np.allclose(dsync[tuple(idx)], 2)
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else:
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- assert np.allclose(dsync[idx], 1)
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+ assert np.allclose(dsync[tuple(idx)], 1)
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# The second slice will sum to 1 and have mean 1
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idx[axis] = 1
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- assert np.allclose(dsync[idx], 1)
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+ assert np.allclose(dsync[tuple(idx)], 1)
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@pytest.mark.parametrize("aggregate", [np.mean, np.max])
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