Finish up Numpy 2.0 port

Author: matthew-brett

nipy/algorithms/diagnostics/tsdiffplot.py

@@ -5,6 +5,7 @@
 import numpy as np
 
 import nipy
+from ...utils import deprecate_with_doc
 
 from .timediff import time_slice_diffs
 
@@ -76,7 +77,7 @@ def xmax_labels(ax, val, xlabel, ylabel):
     return axes
 
 
-@np.deprecate_with_doc('Please see docstring for alternative code')
+@deprecate_with_doc('please see docstring for alternative code')
 def plot_tsdiffs_image(img, axes=None, show=True):
     ''' Plot time series diagnostics for image
 

nipy/algorithms/statistics/formula/formulae.py

@@ -123,14 +123,14 @@
 from nipy.algorithms.utils.matrices import full_rank, matrix_rank
 
 # Legacy repr printing from numpy.
-from nipy.utils import VisibleDeprecationWarning, _NoValue
+from nipy.utils import VisibleDeprecationWarning, _NoValue, deprecate_with_doc
 
 
 def _to_str(s):
     return s.decode('latin1') if isinstance(s, bytes) else str(s)
 
 
-@np.deprecate(message = "Please use sympy.Dummy instead of this function")
+@deprecate_with_doc("please use sympy.Dummy instead")
 def make_dummy(name):
     """ Make dummy variable of given name
 

nipy/algorithms/statistics/tests/test_intrinsic_volumes.py

@@ -8,6 +8,7 @@
 import pytest
 from numpy.testing import assert_almost_equal, assert_array_equal
 
+from nipy.utils import SCTYPES
 from .. import intvol
 
 
@@ -190,7 +191,7 @@ def test_ec():
         assert_almost_equal(f(box1), 1)
         # While we're here, test we can use different dtypes, and that values
         # other than 0 or 1 raise an error.
-        for dtt in sum([np.sctypes[t] for t in ('int', 'uint', 'float')], []):
+        for dtt in sum([SCTYPES[t] for t in ('int', 'uint', 'float')], []):
             box1_again = box1.copy().astype(dtt)
             assert_almost_equal(f(box1_again), 1)
             box1_again[(10,) * i] = 2

nipy/algorithms/statistics/tests/test_quantile.py

@@ -1,12 +1,15 @@
+""" Test quartile functions
+"""
 
 import numpy as np
 from numpy import median as np_median
 from numpy.testing import assert_array_almost_equal, assert_array_equal
 from scipy.stats import scoreatpercentile as sp_percentile
 
+from nipy.utils import SCTYPES
 from .._quantile import _median, _quantile
 
-NUMERIC_TYPES = sum([np.sctypes[t]
+NUMERIC_TYPES = sum([SCTYPES[t]
                      for t in ('int', 'uint', 'float', 'complex')],
                     [])
 

nipy/algorithms/statistics/tests/test_utils.py

@@ -9,7 +9,9 @@
 )
 from scipy.stats import norm
 
-from ..utils import check_cast_bin8, multiple_fast_inv, multiple_mahalanobis, z_score
+from nipy.utils import SCTYPES
+from ..utils import (check_cast_bin8, multiple_fast_inv, multiple_mahalanobis,
+                     z_score)
 
 
 def test_z_score():
@@ -59,13 +61,13 @@ def assert_equal_bin8(actual, expected):
 
 def test_check_cast_bin8():
     # Function to return np.uint8 array with check whether array is binary.
-    for in_dtype in np.sctypes['int'] + np.sctypes['uint']:
+    for in_dtype in SCTYPES['int'] + SCTYPES['uint']:
         assert_equal_bin8(np.array([0, 1, 1, 1], in_dtype), [0, 1, 1, 1])
         assert_equal_bin8(np.array([[0, 1], [1, 1]], in_dtype),
                           [[0, 1], [1, 1]])
         pytest.raises(ValueError, check_cast_bin8,
                       np.array([0, 1, 2], dtype=in_dtype))
-    for in_dtype in np.sctypes['float']:
+    for in_dtype in SCTYPES['float']:
         assert_equal_bin8(np.array([0, 1, 1, -0], np.float64), [0, 1, 1, 0])
         assert_equal_bin8(np.array([[0, 1], [1, -0]], np.float64),
                           [[0, 1], [1, 0]])

nipy/algorithms/utils/pca.py

@@ -17,6 +17,7 @@
 import numpy as np
 import numpy.linalg as npl
 
+from ...utils import SCTYPES
 from ...core.image.image import rollimg
 from ...core.reference.coordinate_map import (
     AxisError,
@@ -204,8 +205,8 @@ def _get_covariance(data, UX, rmse_scales_func, mask):
     C = np.zeros((rank, rank))
     # nan_to_num only for floating point masks
     if mask is not None:
-        nan_to_num = mask.dtype.type in (np.sctypes['float'] +
-                                         np.sctypes['complex'])
+        nan_to_num = mask.dtype.type in (SCTYPES['float'] +
+                                         SCTYPES['complex'])
     # loop over next dimension to save memory
     if data.ndim == 2:
         # If we have 2D data, just do the covariance all in one shot, by using

nipy/algorithms/utils/tests/test_pca.py

@@ -3,6 +3,7 @@
 import numpy as np
 import pytest
 
+from nipy.utils import SCTYPES
 from nipy.io.api import load_image
 from nipy.testing import (
     assert_almost_equal,
@@ -169,9 +170,9 @@ def test_PCAMask(data):
         assert_almost_equal(p['pcnt_var'].sum(), 100.)
     # Any reasonable datatype for mask
     for dt in ([np.bool_] +
-               np.sctypes['int'] +
-               np.sctypes['uint'] +
-               np.sctypes['float']):
+               SCTYPES['int'] +
+               SCTYPES['uint'] +
+               SCTYPES['float']):
         p = pca(arr4d, -1, mask3d.astype(dt), ncomp=ncomp)
         assert p['basis_vectors'].shape == (data['nimages'], ntotal)
         assert p['basis_projections'].shape == mask3d.shape + (ncomp,)

nipy/core/image/image.py

@@ -18,6 +18,8 @@
 import numpy as np
 from nibabel.onetime import auto_attr
 
+from ...utils import deprecate_with_doc
+
 # Legacy repr printing from numpy.
 from ..reference.array_coords import ArrayCoordMap
 
@@ -581,7 +583,7 @@ def fromarray(data, innames, outnames):
     return Image(data, coordmap)
 
 
-@np.deprecate_with_doc('Please use rollimg instead')
+@deprecate_with_doc('please use rollimg instead')
 def rollaxis(img, axis, inverse=False):
     """ Roll `axis` backwards, until it lies in the first position.
 

nipy/core/reference/coordinate_system.py

@@ -15,6 +15,8 @@
 
 import numpy as np
 
+from ...utils import SCTYPES
+
 
 class CoordinateSystemError(Exception):
     pass
@@ -115,8 +117,8 @@ def __init__(self, coord_names, name='', coord_dtype=np.float64):
         if len(set(coord_names)) != len(coord_names):
             raise ValueError('coord_names must have distinct names')
         # verify that the dtype is coord_dtype for sanity
-        sctypes = (np.sctypes['int'] + np.sctypes['float'] +
-                   np.sctypes['complex'] + np.sctypes['uint'] + [object])
+        sctypes = (SCTYPES['int'] + SCTYPES['float'] +
+                   SCTYPES['complex'] + SCTYPES['uint'] + [object])
         coord_dtype = np.dtype(coord_dtype)
         if coord_dtype not in sctypes:
             raise ValueError(f'Coordinate dtype should be one of {sctypes}')

nipy/core/reference/tests/test_coordinate_map.py

@@ -5,6 +5,8 @@
 
 import numpy as np
 
+from nipy.utils import SCTYPES
+
 # this import line is a little ridiculous...
 from ..coordinate_map import (
     AffineTransform,
@@ -35,8 +37,8 @@
 from numpy.testing import assert_almost_equal, assert_array_equal
 
 # Dtypes for testing coordinate map creation / processing
-_SYMPY_SAFE_DTYPES = (np.sctypes['int'] + np.sctypes['uint'] +
-                      np.sctypes['float'] + np.sctypes['complex'] +
+_SYMPY_SAFE_DTYPES = (SCTYPES['int'] + SCTYPES['uint'] +
+                      SCTYPES['float'] + SCTYPES['complex'] +
                       [object])
 # Sympy <= 1.1 does not handle numpy longcomplex correctly. See:
 # https://github.com/sympy/sympy/pull/12901
@@ -965,7 +967,7 @@ def test_dtype_cmap_inverses():
         coord = np.array(in_list, dtype=dt)
         out_coord = np.array(out_list, dtype=dt)
         # Expected output type of inverse, not preserving
-        if dt in np.sctypes['int'] + np.sctypes['uint']:
+        if dt in SCTYPES['int'] + SCTYPES['uint']:
             exp_i_dt = np.float64
         else:
             exp_i_dt = dt
@@ -1000,7 +1002,7 @@ def test_dtype_cmap_inverses():
     arr_p2 = arr_p1 * 2
     arr_p2[-1, -1] = 1
     out_list = [0, 4, 2]
-    for dt in np.sctypes['int'] + np.sctypes['uint']:
+    for dt in SCTYPES['int'] + SCTYPES['uint']:
         in_cs = CoordinateSystem('ijk', coord_dtype=dt)
         out_cs = CoordinateSystem('xyz', coord_dtype=dt)
         cmap = AffineTransform(in_cs, out_cs, arr_p2.astype(dt))

nipy/core/reference/tests/test_coordinate_system.py

@@ -6,6 +6,8 @@
 import numpy as np
 import pytest
 
+from nipy.utils import SCTYPES
+
 from ..coordinate_system import (
     CoordinateSystem,
     CoordinateSystemError,
@@ -60,15 +62,15 @@ def test_unique_coord_names():
 
 def test_dtypes():
     # invalid dtypes
-    dtypes = np.sctypes['others']
+    dtypes = SCTYPES['others']
     dtypes.remove(object)
     for dt in dtypes:
         pytest.raises(ValueError, CoordinateSystem, 'ijk', 'test', dt)
     # compound dtype
     dtype = np.dtype([('field1', '<f8'), ('field2', '<i4')])
     pytest.raises(ValueError, CoordinateSystem, 'ijk', 'test', dtype)
     # valid dtypes
-    dtypes = (np.sctypes['int'] + np.sctypes['float'] + np.sctypes['complex'] +
+    dtypes = (SCTYPES['int'] + SCTYPES['float'] + SCTYPES['complex'] +
               [object])
     for dt in dtypes:
         cs = CoordinateSystem('ij', coord_dtype=dt)
@@ -184,10 +186,10 @@ def test_safe_dtype():
     pytest.raises(TypeError, safe_dtype, str, np.float64)
     pytest.raises(TypeError, safe_dtype, [('x', 'f8')])
     valid_dtypes = []
-    valid_dtypes.extend(np.sctypes['complex'])
-    valid_dtypes.extend(np.sctypes['float'])
-    valid_dtypes.extend(np.sctypes['int'])
-    valid_dtypes.extend(np.sctypes['uint'])
+    valid_dtypes.extend(SCTYPES['complex'])
+    valid_dtypes.extend(SCTYPES['float'])
+    valid_dtypes.extend(SCTYPES['int'])
+    valid_dtypes.extend(SCTYPES['uint'])
     for dt in valid_dtypes:
         sdt = safe_dtype(dt)
         assert sdt == dt

nipy/labs/bindings/tests/test_numpy.py

@@ -5,6 +5,8 @@
 import numpy as np
 from numpy.testing import assert_almost_equal, assert_array_equal
 
+from nipy.utils import SCTYPES
+
 from .. import (
     c_types,
     copy_vector,
@@ -35,12 +37,12 @@ def random_shape(size):
 #
 
 def test_type_conversions_to_fff():
-    # use np.sctypes for testing numpy types, np.typeDict.values
+    # use SCTYPES for testing numpy types, np.typeDict.values
     # contains a lot of duplicates.  There are 140 values in
     # np.typeDict, but only 21 unique numpy types.  But only 11 fff
     # types in c_types.
-    for type_key in np.sctypes:
-        for npy_t in np.sctypes[type_key]:
+    for type_key in SCTYPES:
+        for npy_t in SCTYPES[type_key]:
             t, nbytes = fff_type(np.dtype(npy_t))
             if t != 'unknown type':
                 assert nbytes == np.dtype(npy_t).itemsize

nipy/labs/bindings/wrapper.pyx

@@ -162,7 +162,7 @@ def copy_via_iterators(ndarray Y, int axis=0):
     cdef fffpy_multi_iterator* multi
 
     # Allocate output array
-    Z = np.zeros_like(Y, dtype=np.float_)
+    Z = np.zeros_like(Y, dtype=np.float64)
 
     # Create a new array iterator
     multi = fffpy_multi_iterator_new(2, axis, <void*>Y, <void*>Z)

nipy/labs/meson.build

@@ -6,8 +6,10 @@ python_sources = [
   'mask.py',
   'statistical_mapping.py',
   'viz3d.py',
-  'viz.py'
+  'viz.py',
+  'conftest.py'
 ]
+
 py.install_sources(
   python_sources,
   pure: false,

nipy/utils/__init__.py

@@ -7,6 +7,11 @@
 wrote, that we ship, go in the nipy.externals tree.
 """
 
+import functools
+import warnings
+
+import numpy as np
+
 from nibabel.data import DataError, datasource_or_bomber, make_datasource
 
 # Module level datasource instances for convenience
@@ -48,3 +53,28 @@ class _NoValue:
     This class may be used as the default value assigned to a deprecated
     keyword in order to check if it has been given a user defined value.
     """
+
+
+# Numpy sctypes (np.sctypes removed in Numpy 2.0).
+SCTYPES = {'int': [np.int8, np.int16, np.int32, np.int64],
+           'uint': [np.uint8, np.uint16, np.uint32, np.uint64],
+           'float': [np.float16, np.float32, np.float64],
+           'complex': [np.complex64, np.complex128],
+           'others': [bool, object, bytes, str, np.void]}
+
+
+def deprecate_with_doc(msg):
+    # Adapted from: https://stackoverflow.com/a/30253848/1939576
+
+    def dep(func):
+
+        @functools.wraps(func)
+        def new_func(*args, **kwargs):
+            warnings.warn(
+                f"{func.__name__} deprecated, {msg}",
+                category=DeprecationWarning, stacklevel=2)
+            return func(*args, **kwargs)
+
+        return new_func
+
+    return dep

nipy/utils/tests/test_arrays.py

@@ -6,12 +6,13 @@
 from numpy.testing import assert_array_almost_equal, assert_array_equal
 
 from ..arrays import strides_from
+from nipy.utils import SCTYPES
 
 
 def test_strides_from():
     for shape in ((3,), (2,3), (2,3,4), (5,4,3,2)):
         for order in 'FC':
-            for dtype in sum(np.sctypes.values(), []):
+            for dtype in sum(SCTYPES.values(), []):
                 if dtype is bytes:
                     dtype = 'S3'
                 elif dtype is str: