replace np.sctypes with np.core.sctypes

Author: Mathieu Scheltienne

nibabel/casting.py

@@ -714,7 +714,7 @@ def ok_floats():
     Remove longdouble if it has no higher precision than float64
     """
     # copy float list so we don't change the numpy global
-    floats = np.sctypes['float'][:]
+    floats = np.core.sctypes['float'][:]
     if best_float() != np.longdouble and np.longdouble in floats:
         floats.remove(np.longdouble)
     return sorted(floats, key=lambda f: type_info(f)['nmant'])
@@ -750,10 +750,10 @@ def able_int_type(values):
     mn = min(values)
     mx = max(values)
     if mn >= 0:
-        for ityp in np.sctypes['uint']:
+        for ityp in np.core.sctypes['uint']:
             if mx <= np.iinfo(ityp).max:
                 return ityp
-    for ityp in np.sctypes['int']:
+    for ityp in np.core.sctypes['int']:
         info = np.iinfo(ityp)
         if mn >= info.min and mx <= info.max:
             return ityp

nibabel/tests/test_arraywriters.py

@@ -24,10 +24,10 @@
 from ..testing import assert_allclose_safely, suppress_warnings
 from ..volumeutils import _dt_min_max, apply_read_scaling, array_from_file
 
-FLOAT_TYPES = np.sctypes['float']
-COMPLEX_TYPES = np.sctypes['complex']
-INT_TYPES = np.sctypes['int']
-UINT_TYPES = np.sctypes['uint']
+FLOAT_TYPES = np.core.sctypes['float']
+COMPLEX_TYPES = np.core.sctypes['complex']
+INT_TYPES = np.core.sctypes['int']
+UINT_TYPES = np.core.sctypes['uint']
 CFLOAT_TYPES = FLOAT_TYPES + COMPLEX_TYPES
 IUINT_TYPES = INT_TYPES + UINT_TYPES
 NUMERIC_TYPES = CFLOAT_TYPES + IUINT_TYPES

nibabel/tests/test_casting.py

@@ -24,8 +24,8 @@
 
 
 def test_shared_range():
-    for ft in np.sctypes['float']:
-        for it in np.sctypes['int'] + np.sctypes['uint']:
+    for ft in np.core.sctypes['float']:
+        for it in np.core.sctypes['int'] + np.core.sctypes['uint']:
             # Test that going a bit above or below the calculated min and max
             # either generates the same number when cast, or the max int value
             # (if this system generates that) or something smaller (because of
@@ -54,7 +54,7 @@ def test_shared_range():
                 assert np.all((bit_bigger == casted_mx) | (bit_bigger == imax))
             else:
                 assert np.all(bit_bigger <= casted_mx)
-            if it in np.sctypes['uint']:
+            if it in np.core.sctypes['uint']:
                 assert mn == 0
                 continue
             # And something larger for the minimum
@@ -90,8 +90,8 @@ def test_shared_range_inputs():
 
 
 def test_casting():
-    for ft in np.sctypes['float']:
-        for it in np.sctypes['int'] + np.sctypes['uint']:
+    for ft in np.core.sctypes['float']:
+        for it in np.core.sctypes['int'] + np.core.sctypes['uint']:
             ii = np.iinfo(it)
             arr = [ii.min - 1, ii.max + 1, -np.inf, np.inf, np.nan, 0.2, 10.6]
             farr_orig = np.array(arr, dtype=ft)
@@ -140,7 +140,7 @@ def test_casting():
 
 
 def test_int_abs():
-    for itype in np.sctypes['int']:
+    for itype in np.core.sctypes['int']:
         info = np.iinfo(itype)
         in_arr = np.array([info.min, info.max], dtype=itype)
         idtype = np.dtype(itype)
@@ -188,7 +188,7 @@ def test_able_int_type():
 
 def test_able_casting():
     # Check the able_int_type function guesses numpy out type
-    types = np.sctypes['int'] + np.sctypes['uint']
+    types = np.core.sctypes['int'] + np.core.sctypes['uint']
     for in_type in types:
         in_info = np.iinfo(in_type)
         in_mn, in_mx = in_info.min, in_info.max

nibabel/tests/test_floating.py

@@ -43,7 +43,7 @@ def dtt2dict(dtt):
 
 def test_type_info():
     # Test routine to get min, max, nmant, nexp
-    for dtt in np.sctypes['int'] + np.sctypes['uint']:
+    for dtt in np.core.sctypes['int'] + np.core.sctypes['uint']:
         info = np.iinfo(dtt)
         infod = type_info(dtt)
         assert infod == dict(
@@ -212,7 +212,7 @@ def test_int_to_float():
 def test_as_int_np_fix():
     # Test as_int works for integers.  We need as_int for integers because of a
     # numpy 1.4.1 bug such that int(np.uint32(2**32-1) == -1
-    for t in np.sctypes['int'] + np.sctypes['uint']:
+    for t in np.core.sctypes['int'] + np.core.sctypes['uint']:
         info = np.iinfo(t)
         mn, mx = np.array([info.min, info.max], dtype=t)
         assert (mn, mx) == (as_int(mn), as_int(mx))

nibabel/tests/test_image_api.py

@@ -403,7 +403,7 @@ def _check_array_caching(self, imaker, meth_name, caching):
             return
         # Return original array from get_fdata only if the input array is the
         # requested dtype.
-        float_types = np.sctypes['float']
+        float_types = np.core.sctypes['float']
         if arr_dtype not in float_types:
             return
         for float_type in float_types:

nibabel/tests/test_proxy_api.py

@@ -146,7 +146,9 @@ def validate_array_interface_with_dtype(self, pmaker, params):
             context.__enter__()
             warnings.simplefilter('ignore', np.ComplexWarning)
 
-        for dtype in np.sctypes['float'] + np.sctypes['int'] + np.sctypes['uint']:
+        for dtype in (
+            np.core.sctypes["float"] + np.core.sctypes["int"] + np.core.sctypes["uint"]
+        ):
             # Directly coerce with a dtype
             direct = dtype(prox)
             # Half-precision is imprecise. Obviously. It's a bad idea, but don't break

nibabel/tests/test_round_trip.py

@@ -102,7 +102,7 @@ def test_round_trip():
     rng = np.random.RandomState(20111121)
     N = 10000
     sd_10s = range(-20, 51, 5)
-    iuint_types = np.sctypes['int'] + np.sctypes['uint']
+    iuint_types = np.core.sctypes['int'] + np.core.sctypes['uint']
     # Remove types which cannot be set into nifti header datatype
     nifti_supported = supported_np_types(Nifti1Header())
     iuint_types = [t for t in iuint_types if t in nifti_supported]

nibabel/tests/test_scaling.py

@@ -177,8 +177,8 @@ def test_array_file_scales(in_type, out_type):
     ],
 )
 def test_scaling_in_abstract(category0, category1, overflow):
-    for in_type in np.sctypes[category0]:
-        for out_type in np.sctypes[category1]:
+    for in_type in np.core.sctypes[category0]:
+        for out_type in np.core.sctypes[category1]:
             if overflow:
                 with suppress_warnings():
                     check_int_a2f(in_type, out_type)
@@ -191,7 +191,7 @@ def check_int_a2f(in_type, out_type):
     big_floater = np.maximum_sctype(np.float64)
     info = type_info(in_type)
     this_min, this_max = info['min'], info['max']
-    if not in_type in np.sctypes['complex']:
+    if not in_type in np.core.sctypes['complex']:
         data = np.array([this_min, this_max], in_type)
         # Bug in numpy 1.6.2 on PPC leading to infs - abort
         if not np.all(np.isfinite(data)):

nibabel/tests/test_spm99analyze.py

@@ -35,7 +35,7 @@
 from ..volumeutils import _dt_min_max, apply_read_scaling
 from . import test_analyze
 
-# np.sctypes values are lists of types with unique sizes
+# np.core.sctypes values are lists of types with unique sizes
 # For testing, we want all concrete classes of a type
 # Key on kind, rather than abstract base classes, since timedelta64 is a signedinteger
 sctypes = {}

nibabel/tests/test_testing.py

@@ -48,7 +48,7 @@ def test_assert_allclose_safely():
     with pytest.raises(AssertionError):
         assert_allclose_safely(a, b)
     # Test allcloseness of inf, especially np.float128 infs
-    for dtt in np.sctypes['float']:
+    for dtt in np.core.sctypes['float']:
         a = np.array([-np.inf, 1, np.inf], dtype=dtt)
         b = np.array([-np.inf, 1, np.inf], dtype=dtt)
         assert_allclose_safely(a, b)