@@ -1823,38 +1823,3 @@ def test_scans():
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da = dask .array .from_array (array , chunks = 2 )
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actual = groupby_scan (da , by , ** kwargs )
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assert_equal (expected , actual )
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-
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-
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- # from numpy import nan
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-
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- # array = np.array([nan, 0., nan, nan, 0.], dtype=np.float32)
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- # group_idx = np.array([0, 0, 1, 0, 0])
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- # ffill.dtype = array.dtype
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- # dask_groupby_scan(dask.array.from_array(array, chunks=(1, 1, 1, 2)), group_idx, axes=(0,), agg=ffill).compute()
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- # dask_groupby_scan(dask.array.from_array(array, chunks=(2, 1, 2)), group_idx, axes=(0,), agg=ffill).compute()
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-
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-
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- # DASK/FLOX BUG?
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- # func = "ffill"
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- # array = array([[ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
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- # [ 0., 1., 0., 0., 0., 0., 0., 0., nan, 0.]], dtype=float32),
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- # group_idx= array([0, 0, 0, 0, 1, 1, 1, 1, 0, 0])
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- # chunks = ((2,), (1, 1, 2, 1, 5))
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-
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-
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- # NUMPY_GROUPIES BUG
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- # import numpy_groupies as npg
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-
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- # npg.aggregate_numpy.aggregate(
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- # array([1, 1, 1, 0, 0]),
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- # array([[ 5., 6., 7., 8., 9.],
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- # [ 0., 0., 0., nan, 0.]], dtype=float32),
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- # func="cumsum",
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- # axis=-1,
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- # )
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-
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- # numpy_array, group_idx = (
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- # array([1.6777218e07, 1.0000000e00, 0.0000000e00], dtype=float32),
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- # array([0, 1, 1]),
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- # )
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- # groupby_scan(numpy_array, group_idx, axis=-1, func="nancumsum")
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