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https://github.com/chanzuckerberg/cellxgene.git
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anndata X indexing & version compatibility improvements (#1157)
* revert MatrixProxy; replace with correct use of adata slicing * work around 0.6 adata slicing bug * fix incorrect var slice * simplify slicing of X * add warning about performance impact of anndata<=0.7 * lint and remove unused code * improve comment * lint * correctly parse versions * temp files should preserve file suffix if possible - anndata 0.7 compat * update anndata dependency to 0.6.20 * resolve PR review comments
This commit is contained in:
Bruce Martin
@@ -1,177 +0,0 @@
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import unittest
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import numpy as np
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from server.app.util.matrix_proxy import MatrixProxyView, MatrixProxy
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class NdArrayProxyView(MatrixProxyView):
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"""
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Fake test class for matrix proxy - wraps ndarray
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"""
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@classmethod
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def __supports__(cls):
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return ("numpy.ndarray",)
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class MatrixProxyViewTest(unittest.TestCase):
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def test_ismatrixproxy(self):
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n = np.zeros((2, 4))
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mp = MatrixProxy.create(n)
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self.assertIsNotNone(n)
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self.assertIsNotNone(mp)
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self.assertTrue(isinstance(mp, NdArrayProxyView))
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self.assertFalse(MatrixProxy.ismatrixproxy(n))
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self.assertTrue(MatrixProxy.ismatrixproxy(mp))
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def test_params(self):
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n = np.arange(15, dtype=np.float32).reshape((3, 5))
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mp = MatrixProxy.create(n)
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self.assertTrue(MatrixProxy.ismatrixproxy(mp))
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self.assertEqual(mp.ndim, 2)
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self.assertEqual(mp.shape, (3, 5))
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self.assertEqual(mp.dtype, np.float32)
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mpt = mp.T
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self.assertTrue(MatrixProxy.ismatrixproxy(mpt))
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self.assertEqual(mpt.ndim, 2)
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self.assertEqual(mpt.shape, (5, 3))
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self.assertEqual(mpt.dtype, np.float32)
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def test_toarray(self):
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n = np.arange(15, dtype=np.float32).reshape((3, 5))
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mp = MatrixProxy.create(n)
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self.assertTrue(
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np.all(
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mp.toarray() == [[0.0, 1.0, 2.0, 3.0, 4.0], [5.0, 6.0, 7.0, 8.0, 9.0], [10.0, 11.0, 12.0, 13.0, 14.0]]
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)
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)
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self.assertTrue(
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np.all(
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mp.T.toarray()
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== [[0.0, 5.0, 10.0], [1.0, 6.0, 11.0], [2.0, 7.0, 12.0], [3.0, 8.0, 13.0], [4.0, 9.0, 14.0]]
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)
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)
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def test_indexing(self):
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"""
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[[ 0., 1., 2., 3., 4.],
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[ 5., 6., 7., 8., 9.],
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[10., 11., 12., 13., 14.]]
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"""
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n = np.arange(15, dtype=np.float32).reshape((3, 5))
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mp = MatrixProxy.create(n)
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# should support int or slice for one or both dimensions
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# int, int
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self.assertEqual(mp[0, 0], 0)
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self.assertEqual(mp.T[0, 0], 0)
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self.assertEqual(mp[2, 4], 14)
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self.assertEqual(mp.T[4, 2], 14)
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self.assertEqual(mp[1, 3], mp.T[3, 1])
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# int, slice
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self.assertTrue(np.all(mp[0].toarray() == [0, 1, 2, 3, 4]))
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self.assertTrue(np.all(mp[1, 1:].toarray() == [6, 7, 8, 9]))
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self.assertTrue(np.all(mp[2, 1::-1].toarray() == [11, 10]))
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self.assertTrue(np.all(mp.T[0].toarray() == [0, 5, 10]))
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self.assertTrue(np.all(mp.T[1, 1:].toarray() == [6, 11]))
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self.assertTrue(np.all(mp.T[2, 1::-1].toarray() == [7, 2]))
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# slice, int
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self.assertTrue(np.all(mp[:, 0].toarray() == [0, 5, 10]))
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self.assertTrue(np.all(mp[1:, 1].toarray() == [6, 11]))
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self.assertTrue(np.all(mp[1::-1, 2].toarray() == [7, 2]))
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self.assertTrue(np.all(mp.T[:, 0].toarray() == [0, 1, 2, 3, 4]))
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self.assertTrue(np.all(mp.T[1:, 1].toarray() == [6, 7, 8, 9]))
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self.assertTrue(np.all(mp.T[1::-1, 2].toarray() == [11, 10]))
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# slice, slice
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self.assertTrue(np.all(mp[1:3, 2:4].toarray() == [[7, 8], [12, 13]]))
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self.assertTrue(
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np.all(mp[:3, :4].toarray() == [[0.0, 1.0, 2.0, 3.0], [5.0, 6.0, 7.0, 8.0], [10.0, 11.0, 12.0, 13.0]])
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)
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self.assertTrue(np.all(mp[::-1, ::-1].toarray() == [[14, 13, 12, 11, 10], [9, 8, 7, 6, 5], [4, 3, 2, 1, 0]]))
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self.assertTrue(np.all(mp[::-2, ::-2].toarray() == [[14, 12, 10], [4, 2, 0]]))
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self.assertTrue(np.all(mp.T[2:4, 1:3].toarray() == [[7, 12], [8, 13]]))
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self.assertTrue(np.all(mp.T[:4, :3].toarray() == [[0, 5, 10], [1, 6, 11], [2, 7, 12], [3, 8, 13]]))
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self.assertTrue(
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np.all(mp.T[::-1, ::-1].toarray() == [[14, 9, 4], [13, 8, 3], [12, 7, 2], [11, 6, 1], [10, 5, 0]])
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)
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self.assertTrue(np.all(mp.T[::-2, ::-2].toarray() == [[14, 4], [12, 2], [10, 0]]))
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def test_repeated_indexing(self):
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"""
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[[ 0., 1., 2., 3., 4.],
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[ 5., 6., 7., 8., 9.],
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[10., 11., 12., 13., 14.]]
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"""
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n = np.arange(15, dtype=np.float32).reshape((3, 5))
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mp = MatrixProxy.create(n)
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self.assertEqual(mp[0][1], 1)
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self.assertEqual(mp.T[0][1], 5)
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self.assertTrue(np.all(mp[0::-1, ::-1][0, 2:4].toarray() == [2, 1]))
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self.assertTrue(np.all(mp[0::-1, 1:5:1][0, 1:3:1].toarray() == [2, 3]))
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self.assertTrue(np.all(mp[0::-1, 1:5:1][0, 2:0:-1].toarray() == [3, 2]))
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self.assertTrue(np.all(mp[0::-1, 5:1:-1][0, 1:3:1].toarray() == [3, 2]))
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self.assertTrue(np.all(mp[0::-1, 5:1:-1][0, 2:0:-1].toarray() == [2, 3]))
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self.assertTrue(np.all(mp.T[::-1, 0::-1][2:4, 0].toarray() == [2, 1]))
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self.assertTrue(np.all(mp.T[0::-1, 1:5:1][0, 1:3:1].toarray() == [10]))
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self.assertTrue(np.all(mp.T[0::-1, 1:5:1][0, 2:0:-1].toarray() == [10]))
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self.assertTrue(np.all(mp.T[0::-1, 5:1:-1][0, 1:3:1].toarray() == []))
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self.assertTrue(np.all(mp.T[0::-1, 5:1:-1][0, 2:0:-1].toarray() == []))
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def test_dimension_drop(self):
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"""
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[[ 0., 1., 2., 3., 4.],
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[ 5., 6., 7., 8., 9.],
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[10., 11., 12., 13., 14.]]
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"""
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n = np.arange(15, dtype=np.float32).reshape((3, 5))
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mp = MatrixProxy.create(n)
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# drop both dimensions, to a scalar
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self.assertEqual(mp[0, 0], 0)
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# drop 1 dimension, to an array
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self.assertTrue(np.all(mp[0, :].toarray() == [0, 1, 2, 3, 4]))
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self.assertTrue(np.all(mp[:, 0].toarray() == [0, 5, 10]))
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# with .T
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self.assertTrue(np.all(mp[0:2].T[-1:].toarray() == [[4, 9]]))
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self.assertTrue(np.all(mp[0:2].T[-1].toarray() == [4, 9]))
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def test_iter(self):
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"""
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check that __iter__ is doing what we expect
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"""
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n = np.arange(15, dtype=np.float32).reshape((3, 5))
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mp = MatrixProxy.create(n)
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rows = [r for r in mp]
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self.assertEqual(len(rows), 3)
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self.assertTrue(np.all(rows[0].toarray() == [0, 1, 2, 3, 4]))
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for i, r in enumerate(rows):
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self.assertTrue(np.all(mp[i].toarray() == r.toarray()))
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cols = [c for c in mp.T]
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self.assertEqual(len(cols), 5)
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self.assertTrue(np.all(cols[0].toarray() == [0, 5, 10]))
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for i, c in enumerate(cols):
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self.assertTrue(np.all(mp.T[i].toarray() == c.toarray()))
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e = [e for e in mp[0]]
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self.assertEqual(len(e), 5)
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self.assertEqual(e, [0, 1, 2, 3, 4])
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