FIX: Try again [build wheels]

nitime/tests/test_timeseries.py

@@ -916,20 +916,20 @@ def test_index_int64():
     assert repr(b[0]) == repr(b[np.int32(0)])
 
 
-def test_timearray_math_functions():
+@pytest.mark.parametrize('f', ['min', 'max', 'mean', 'ptp', 'sum'])
+@pytest.mark.parametrize('tu', ['s', 'ms', 'ps', 'D'])
+def test_timearray_math_functions(f, tu):
     "Calling TimeArray.min() .max(), mean() should return TimeArrays"
     a = np.arange(2, 11)
-    for f in ['min', 'max', 'mean', 'ptp', 'sum']:
-        for tu in ['s', 'ms', 'ps', 'D']:
-            b = ts.TimeArray(a, time_unit=tu)
-            npt.assert_(getattr(b, f)().__class__ == ts.TimeArray)
-            npt.assert_(getattr(b, f)().time_unit == b.time_unit)
-            # comparison with unitless should convert to the TimeArray's units
-            if f == "ptp":
-                want = np.ptp(a)  # ndarray.ptp removed in 2.0
-            else:
-                want = getattr(a, f)()
-            npt.assert_(getattr(b, f)() == want)
+    b = ts.TimeArray(a, time_unit=tu)
+    if f == "ptp" and ts._NP_2:
+        with pytest.raises(AttributeError, match='`ptp` was removed'):
+            a.ptp()  # ndarray.ptp removed in 2.0
+        return
+    npt.assert_(getattr(b, f)().__class__ == ts.TimeArray)
+    npt.assert_(getattr(b, f)().time_unit == b.time_unit)
+    # comparison with unitless should convert to the TimeArray's units
+    npt.assert_(getattr(b, f)() == getattr(a, f)())
 
 
 def test_timearray_var_prod():

nitime/timeseries.py

@@ -33,6 +33,11 @@
 # Our own
 from nitime import descriptors as desc
 
+try:
+    _NP_2 = int(np.__version__.split(".")[0]) >= 2
+except Exception:
+    _NP_2 = True
+
 #-----------------------------------------------------------------------------
 # Module globals
 #-----------------------------------------------------------------------------
@@ -112,7 +117,9 @@ def __new__(cls, data, time_unit=None, copy=True):
             which are SI units of time. Default: 's'
 
         copy : bool, optional
-            Whether to create this instance by  copy of a
+            Whether to create this instance by copy of a. If False,
+            a copy will not be forced but might still be required depending
+            on the data array.
 
         Note
         ----
@@ -309,7 +316,12 @@ def mean(self, *args, **kwargs):
         return ret
 
     def ptp(self, *args, **kwargs):
-        ret = TimeArray(np.ptp(self, *args, **kwargs),
+        if _NP_2:
+            raise AttributeError(
+                "`ptp` was removed from the ndarray class in NumPy 2.0. "
+                "Use np.ptp(arr, ...) instead."
+            )
+        ret = TimeArray(np.ndarray.ptp(self, *args, **kwargs),
                         time_unit=base_unit)
         ret.convert_unit(self.time_unit)
         return ret

pyproject.toml

@@ -62,6 +62,12 @@ skip = "pp* cp38-*_aarch64 cp38-musllinux_*"
 # don't bother unless someone asks
 archs = ["native"]
 
+test-requires = [
+    "pytest",
+    "pytest-cov",
+]
+test-command = "pytest {project}/tests"
+
 [tool.cibuildwheel.linux]
 archs = ["x86_64", "aarch64"]