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From 0ab3cf0ffcdb364a8a75e71acfb267e5aaabc0a0 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Micha=C5=82=20G=C3=B3rny?= <mgorny@gentoo.org>
Date: Mon, 10 Jun 2024 03:55:47 +0200
Subject: [PATCH 1/2] Fix data types in tests for NumPy 2
Fix a number of test compatibility issues with NumPy 2. That is:
- replace `np.float_` with `np.float64`,
- replace `np.complex_` with `np.complex128`,
- remove `np.unicode_` as equivalent to `np.str_`.
The LHS types are also aliases to the RHS types in NumPy 1.x, so this
is NFC on NumPy 1.x. These aliases were removed in 2.x, so the code
needs to be updated for tests to pass on NumPy 2.x.
---
tests/numpy_test.py | 7 ++-----
tests/pandas_test.py | 13 +++++--------
2 files changed, 7 insertions(+), 13 deletions(-)
diff --git a/tests/numpy_test.py b/tests/numpy_test.py
index e271725..dd50d5e 100644
--- a/tests/numpy_test.py
+++ b/tests/numpy_test.py
@@ -32,9 +32,7 @@ def test_dtype_roundtrip():
dtypes = [
np.int_,
np.int32,
- np.float_,
np.float64,
- np.complex_,
np.complex128,
np.str_,
np.object_,
@@ -86,15 +84,14 @@ def test_generic_roundtrip():
values = [
np.int_(1),
np.int32(-2),
- np.float_(2.5),
+ np.float64(2.5),
np.nan,
-np.inf,
np.inf,
np.datetime64('2014-01-01'),
np.str_('foo'),
- np.unicode_('bar'),
np.object_({'a': 'b'}),
- np.complex_(1 - 2j),
+ np.complex128(1 - 2j),
]
for value in values:
decoded = roundtrip(value)
diff --git a/tests/pandas_test.py b/tests/pandas_test.py
index 532563f..414bd65 100644
--- a/tests/pandas_test.py
+++ b/tests/pandas_test.py
@@ -34,14 +34,13 @@ def test_series_roundtrip():
ser = pd.Series(
{
'an_int': np.int_(1),
- 'a_float': np.float_(2.5),
+ 'a_float': np.float64(2.5),
'a_nan': np.nan,
'a_minus_inf': -np.inf,
'an_inf': np.inf,
'a_str': np.str_('foo'),
- 'a_unicode': np.unicode_('bar'),
'date': np.datetime64('2014-01-01'),
- 'complex': np.complex_(1 - 2j),
+ 'complex': np.complex128(1 - 2j),
# TODO: the following dtypes are not currently supported.
# 'object': np.object_({'a': 'b'}),
}
@@ -54,14 +53,13 @@ def test_dataframe_roundtrip():
df = pd.DataFrame(
{
'an_int': np.int_([1, 2, 3]),
- 'a_float': np.float_([2.5, 3.5, 4.5]),
+ 'a_float': np.float64([2.5, 3.5, 4.5]),
'a_nan': np.array([np.nan] * 3),
'a_minus_inf': np.array([-np.inf] * 3),
'an_inf': np.array([np.inf] * 3),
'a_str': np.str_('foo'),
- 'a_unicode': np.unicode_('bar'),
'date': np.array([np.datetime64('2014-01-01')] * 3, dtype="datetime64[s]"),
- 'complex': np.complex_([1 - 2j, 2 - 1.2j, 3 - 1.3j]),
+ 'complex': np.complex128([1 - 2j, 2 - 1.2j, 3 - 1.3j]),
# TODO: the following dtypes are not currently supported.
# 'object': np.object_([{'a': 'b'}]*3),
}
@@ -76,12 +74,11 @@ def test_multindex_dataframe_roundtrip():
'idx_lvl0': ['a', 'b', 'c'],
'idx_lvl1': np.int_([1, 1, 2]),
'an_int': np.int_([1, 2, 3]),
- 'a_float': np.float_([2.5, 3.5, 4.5]),
+ 'a_float': np.float64([2.5, 3.5, 4.5]),
'a_nan': np.array([np.nan] * 3),
'a_minus_inf': np.array([-np.inf] * 3),
'an_inf': np.array([np.inf] * 3),
'a_str': np.str_('foo'),
- 'a_unicode': np.unicode_('bar'),
}
)
df = df.set_index(['idx_lvl0', 'idx_lvl1'])
From 8bc2bdd42bc111d90edbcef8005640d5a51627bf Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Micha=C5=82=20G=C3=B3rny?= <mgorny@gentoo.org>
Date: Mon, 10 Jun 2024 04:02:17 +0200
Subject: [PATCH 2/2] Fix `newbyteorder()` use for NumPy 2.x
Replace the `arr.newbyteorder()` use with:
arr.view(arr.dtype.newbyteorder())
as suggested in the exception that's raised when the tests are run
in NumPy 2.x. With this change, the code works both with NumPy 1.x
and NumPy 2.x.
---
tests/numpy_test.py | 24 ++++++++++++++----------
1 file changed, 14 insertions(+), 10 deletions(-)
diff --git a/tests/numpy_test.py b/tests/numpy_test.py
index dd50d5e..2e6725b 100644
--- a/tests/numpy_test.py
+++ b/tests/numpy_test.py
@@ -306,18 +306,22 @@ def test_immutable():
def test_byteorder():
"""Test the byteorder for text and binary encodings"""
# small arr is stored as text
- a = np.arange(10).newbyteorder()
- b = a[:].newbyteorder()
- _a, _b = roundtrip([a, b])
- npt.assert_array_equal(a, _a)
- npt.assert_array_equal(b, _b)
+ a = np.arange(10)
+ av = a.view(a.dtype.newbyteorder())
+ b = a[:]
+ bv = b.view(b.dtype.newbyteorder())
+ _av, _bv = roundtrip([av, bv])
+ npt.assert_array_equal(av, _av)
+ npt.assert_array_equal(bv, _bv)
# bigger arr is stored as binary
- a = np.arange(100).newbyteorder()
- b = a[:].newbyteorder()
- _a, _b = roundtrip([a, b])
- npt.assert_array_equal(a, _a)
- npt.assert_array_equal(b, _b)
+ a = np.arange(100)
+ av = a.view(a.dtype.newbyteorder())
+ b = a[:]
+ bv = b.view(b.dtype.newbyteorder())
+ _av, _bv = roundtrip([av, bv])
+ npt.assert_array_equal(av, _av)
+ npt.assert_array_equal(bv, _bv)
def test_zero_dimensional_array():
|
