Fix long slicing from dask.keys() sorted issue

Fixes dask#452
mrocklin · Jul 21, 2015 · d4bb563 · d4bb563
1 parent c5a4b8c
commit d4bb563
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Showing 2 changed files with 13 additions and 6 deletions.
diff --git a/dask/array/slicing.py b/dask/array/slicing.py
@@ -218,7 +218,7 @@ def slice_slices_and_integers(out_name, in_name, blockdims, index):
     block_slices = list(map(_slice_1d, shape, blockdims, index))
 
     # (in_name, 1, 1, 2), (in_name, 1, 1, 4), (in_name, 2, 1, 2), ...
-    in_names = list(product([in_name], *[i.keys() for i in block_slices]))
+    in_names = list(product([in_name], *[sorted(i.keys()) for i in block_slices]))
 
     # (out_name, 0, 0, 0), (out_name, 0, 0, 1), (out_name, 0, 1, 0), ...
     out_names = list(product([out_name],

diff --git a/dask/array/tests/test_array_core.py b/dask/array/tests/test_array_core.py
@@ -1014,7 +1014,7 @@ def test_histogram():
     bins = np.arange(0, 1.01, 0.01)
     (a1, b1) = da.histogram(v, bins=bins)
     (a2, b2) = np.histogram(v, bins=bins)
-    
+
     # Check if the sum of the bins equals the number of samples
     assert a2.sum(axis=0) == n
     assert a1.sum(axis=0) == n
@@ -1046,20 +1046,20 @@ def test_histogram_extra_args_and_shapes():
     v = da.random.random(100, chunks=10)
     data = [(v, bins, da.ones(100, chunks=v.chunks) * 5),
             (da.random.random((50, 50), chunks=10), bins, da.ones((50, 50), chunks=10) * 5)]
-    
+
     for v, bins, w in data:
         # density
         assert eq(da.histogram(v, bins=bins, normed=True)[0],
                   np.histogram(v, bins=bins, normed=True)[0])
-        
+
         # normed
         assert eq(da.histogram(v, bins=bins, density=True)[0],
                   np.histogram(v, bins=bins, density=True)[0])
-        
+
         # weights
         assert eq(da.histogram(v, bins=bins, weights=w)[0],
                   np.histogram(v, bins=bins, weights=w)[0])
-        
+
         assert eq(da.histogram(v, bins=bins, weights=w, density=True)[0],
                   da.histogram(v, bins=bins, weights=w, density=True)[0])
 
@@ -1189,3 +1189,10 @@ def test_raise_on_bad_kwargs():
     except TypeError as e:
         assert 'minimum' in str(e)
         assert 'out' in str(e)
+
+
+def test_long_slice():
+    x = np.arange(10000)
+    d = da.from_array(x, chunks=1)
+
+    assert eq(d[8000:8200], x[8000:8200])