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Implementation of std and var. #327

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Implementation of std and var. #327

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97514e3
Implementation of `std` and `var`.
alxmrs Nov 21, 2023
253204d
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Nov 21, 2023
75bbd7b
List order follows import order.
alxmrs Nov 21, 2023
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4 changes: 2 additions & 2 deletions cubed/array_api/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -262,9 +262,9 @@

__all__ += ["argmax", "argmin", "where"]

from .statistical_functions import max, mean, min, prod, sum
from .statistical_functions import max, mean, min, prod, std, sum, var

__all__ += ["max", "mean", "min", "prod", "sum"]
__all__ += ["max", "mean", "min", "prod", "std", "sum", "var"]

from .utility_functions import all, any

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10 changes: 10 additions & 0 deletions cubed/array_api/statistical_functions.py
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Expand Up @@ -15,6 +15,7 @@
uint64,
)
from cubed.backend_array_api import namespace as nxp
from cubed.array_api.elementwise_functions import sqrt, square, subtract
from cubed.core import reduction


Expand Down Expand Up @@ -184,3 +185,12 @@ def sum(
split_every=split_every,
extra_func_kwargs=extra_func_kwargs,
)


def var(x, /, *, axis=None, keepdims=False):
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This doesn't match the signature in the specification since it's missing a correction parameter. Similarly for std.

mu = mean(x, axis=axis, keepdims=True)
return mean(square(subtract(x, mu)), axis=axis, keepdims=keepdims)


def std(x, /, *, axis=None, keepdims=False):
return sqrt(var(x, axis=axis, keepdims=keepdims))
68 changes: 68 additions & 0 deletions cubed/tests/test_array_api.py
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Expand Up @@ -728,6 +728,74 @@ def test_sum_axis_0(spec, executor):
assert_array_equal(b.compute(executor=executor), np.array([12, 15, 18]))


def test_var(spec, executor):
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Can you parameterize all these tests for var for different axes, and for keepdims? There are other tests in the test suite that do this.

a = xp.asarray(
[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]], chunks=(2, 2), spec=spec
)
b = xp.var(a)
assert_array_equal(
b.compute(executor=executor),
np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]]).var(),
)


def test_var_axis_0(spec, executor):
a = xp.asarray(
[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]], chunks=(2, 2), spec=spec
)
b = xp.var(a, axis=0)
assert_array_equal(
b.compute(executor=executor),
np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]]).var(axis=0),
)


def test_var_axis_1(spec, executor):
a = xp.asarray(
[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]], chunks=(2, 2), spec=spec
)
b = xp.var(a, axis=1)
assert_array_equal(
b.compute(executor=executor),
np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]]).var(axis=1),
)


def test_var_keepdims_true(spec, executor):
a = xp.asarray(
[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]], chunks=(2, 2), spec=spec
)
b = xp.var(a, keepdims=True)
assert_array_equal(
b.compute(executor=executor),
np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]]).var(
keepdims=True
),
)


def test_std(spec, executor):
a = xp.asarray(
[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]], chunks=(2, 2), spec=spec
)
b = xp.std(a)
assert_array_equal(
b.compute(executor=executor),
np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]]).std(),
)


def test_std_axis_0(spec, executor):
a = xp.asarray(
[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]], chunks=(2, 2), spec=spec
)
b = xp.std(a, axis=0)
assert_array_equal(
b.compute(executor=executor),
np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]]).std(axis=0),
)


# Utility functions


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