From 464a0383f800ba0bd5f135136e28ae050f6c9f23 Mon Sep 17 00:00:00 2001
From: Alexandru Fikl <alexfikl@gmail.com>
Date: Tue, 13 Jul 2021 14:12:03 -0500
Subject: [PATCH] extend some tests to use complex inputs
---
test/test_arraycontext.py | 79 ++++++++++++++++++++++-----------------
1 file changed, 44 insertions(+), 35 deletions(-)
diff --git a/test/test_arraycontext.py b/test/test_arraycontext.py
index 4642806..c9c26e2 100644
--- a/test/test_arraycontext.py
+++ b/test/test_arraycontext.py
@@ -188,6 +188,22 @@ def _thaw_dofarray(ary, actx):
# {{{ assert_close_to_numpy*
+def randn(shape, dtype):
+ rng = np.random.default_rng()
+ dtype = np.dtype(dtype)
+
+ if dtype.kind == "c":
+ dtype = np.dtype(f"<f{dtype.itemsize // 2}")
+ return rng.standard_normal(shape, dtype) \
+ + 1j * rng.standard_normal(shape, dtype)
+ elif dtype.kind == "f":
+ return rng.standard_normal(shape, dtype)
+ elif dtype.kind == "i":
+ return rng.integers(0, 128, shape, dtype)
+ else:
+ raise TypeError(dtype.kind)
+
+
def assert_close_to_numpy(actx, op, args):
assert np.allclose(
actx.to_numpy(
@@ -236,37 +252,44 @@ def assert_close_to_numpy_in_containers(actx, op, args):
# {{{ np.function same as numpy
-@pytest.mark.parametrize(("sym_name", "n_args"), [
- ("sin", 1),
- ("exp", 1),
- ("arctan2", 2),
- ("minimum", 2),
- ("maximum", 2),
- ("where", 3),
- ("conj", 1),
- ("vdot", 2),
+@pytest.mark.parametrize(("sym_name", "n_args", "dtype"), [
+ ("sin", 1, np.float64),
+ ("sin", 1, np.complex128),
+ ("exp", 1, np.float64),
+ ("arctan2", 2, np.float64),
+ ("minimum", 2, np.float64),
+ ("maximum", 2, np.float64),
+ ("where", 3, np.float64),
+ ("conj", 1, np.float64),
+ ("conj", 1, np.complex128),
+ ("vdot", 2, np.float64),
+ ("vdot", 2, np.complex128),
+ ("abs", 1, np.float64),
+ ("abs", 1, np.complex128),
])
-def test_array_context_np_workalike(actx_factory, sym_name, n_args):
+def test_array_context_np_workalike(actx_factory, sym_name, n_args, dtype):
actx = actx_factory()
if not hasattr(actx.np, sym_name):
pytest.skip(f"'{sym_name}' not implemented on '{type(actx).__name__}'")
- ndofs = 5000
- args = [np.random.randn(ndofs) for i in range(n_args)]
+ ndofs = 512
+ args = [randn(ndofs, dtype) for i in range(n_args)]
+
assert_close_to_numpy_in_containers(
actx, lambda _np, *_args: getattr(_np, sym_name)(*_args), args)
-@pytest.mark.parametrize(("sym_name", "n_args"), [
- # ("empty_like", 1), # NOTE: fails np.allclose, obviously
- ("zeros_like", 1),
- ("ones_like", 1),
+@pytest.mark.parametrize(("sym_name", "n_args", "dtype"), [
+ ("zeros_like", 1, np.float64),
+ ("zeros_like", 1, np.complex128),
+ ("ones_like", 1, np.float64),
+ ("ones_like", 1, np.complex128),
])
-def test_array_context_np_like(actx_factory, sym_name, n_args):
+def test_array_context_np_like(actx_factory, sym_name, n_args, dtype):
actx = actx_factory()
- ndofs = 5000
- args = [np.random.randn(ndofs) for i in range(n_args)]
+ ndofs = 512
+ args = [randn(ndofs, dtype) for i in range(n_args)]
assert_close_to_numpy(
actx, lambda _np, *_args: getattr(_np, sym_name)(*_args), args)
@@ -469,6 +492,7 @@ def test_dof_array_arithmetic_same_as_numpy(actx_factory):
# {{{ reductions same as numpy
+
@pytest.mark.parametrize("op", ["sum", "min", "max"])
def test_dof_array_reductions_same_as_numpy(actx_factory, op):
actx = actx_factory()
@@ -794,7 +818,7 @@ def test_numpy_conversion(actx_factory):
@pytest.mark.parametrize("norm_ord", [2, np.inf])
def test_norm_complex(actx_factory, norm_ord):
actx = actx_factory()
- a = np.random.randn(2000) + 1j * np.random.randn(2000)
+ a = randn(2000, np.complex128)
norm_a_ref = np.linalg.norm(a, norm_ord)
norm_a = actx.np.linalg.norm(actx.from_numpy(a), norm_ord)
@@ -883,21 +907,6 @@ def test_container_equality(actx_factory):
# }}}
-# {{{ test_abs_complex
-
-def test_abs_complex(actx_factory):
- actx = actx_factory()
- a = np.random.randn(2000) + 1j * np.random.randn(2000)
-
- abs_a_ref = np.abs(a)
- abs_a = actx.np.abs(actx.from_numpy(a))
-
- assert abs_a.dtype == abs_a_ref.dtype
- np.testing.assert_allclose(actx.to_numpy(abs_a), abs_a_ref)
-
-# }}}
-
-
# {{{ test_leaf_array_type_broadcasting
@with_container_arithmetic(
--
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