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Adds choose method to dask.array.Array #2584

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merged 4 commits into from Aug 5, 2017
Merged

Adds choose method to dask.array.Array #2584

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63f2a01
Adds choose method to dask.array.Array
jrbourbeau Aug 2, 2017
d67ae69
Fixes small error in test_array_core.py
jrbourbeau Aug 2, 2017
538a9b9
Makes the choose function call the choose method on input dask arrays
jrbourbeau Aug 4, 2017
9b23d8d
Switches to having the choose method call the choose function
jrbourbeau Aug 4, 2017
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4 changes: 4 additions & 0 deletions dask/array/core.py
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Expand Up @@ -1307,6 +1307,10 @@ def ravel(self):

flatten = ravel

@wraps(np.choose)
def choose(self, choices):
return elemwise(variadic_choose, self, *choices)
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Would it make sense for this to just call the function implementation or vice versa?

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That's a good point! It probably makes more sense to just implement choose on a dask Array once. I'll change the PR to have the choose function simply call the choose method on an input dask array.

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Personal preference, but I'd rather have the method call the function (smaller diff too). Not a big deal though, up to you.

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Hey @jcrist, yeah I can switch it so that the method calls the function. I don't have a strong preference either way.

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Just for completeness, the argument for the function calling the method would be to handle inheritance from Dask Array. That said, I have no strong preferences here either and it can always be changed if there is a need.


@wraps(np.reshape)
def reshape(self, *shape):
from .reshape import reshape
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7 changes: 7 additions & 0 deletions dask/array/tests/test_array_core.py
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Expand Up @@ -709,12 +709,19 @@ def test_norm():


def test_choose():
# test choose function
x = np.random.randint(10, size=(15, 16))
d = from_array(x, chunks=(4, 5))

assert_eq(choose(d > 5, [0, d]), np.choose(x > 5, [0, x]))
assert_eq(choose(d > 5, [-d, d]), np.choose(x > 5, [-x, x]))

# test choose method
index_dask = d > 5
index_numpy = x > 5
assert_eq(index_dask.choose([0, d]), index_numpy.choose([0, x]))
assert_eq(index_dask.choose([-d, d]), index_numpy.choose([-x, x]))


def test_argwhere():
for shape, chunks in [(0, ()), ((0, 0), (0, 0)), ((15, 16), (4, 5))]:
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