Merge pull request #1272 from effigies/rf/remove-longdouble-hacks

RF: Deprecate longdouble<->int hacks

Author: effigies

nibabel/arraywriters.py

@@ -30,15 +30,7 @@ def __init__(self, array, out_dtype=None)
 """
 import numpy as np
 
-from .casting import (
-    as_int,
-    best_float,
-    floor_exact,
-    int_abs,
-    int_to_float,
-    shared_range,
-    type_info,
-)
+from .casting import best_float, floor_exact, int_abs, shared_range, type_info
 from .volumeutils import array_to_file, finite_range
 
 
@@ -152,9 +144,8 @@ def scaling_needed(self):
         # No scaling needed if data already fits in output type
         # But note - we need to convert to ints, to avoid conversion to float
         # during comparisons, and therefore int -> float conversions which are
-        # not exact.  Only a problem for uint64 though.  We need as_int here to
-        # work around a numpy 1.4.1 bug in uint conversion
-        if as_int(mn) >= as_int(info.min) and as_int(mx) <= as_int(info.max):
+        # not exact.  Only a problem for uint64 though.
+        if int(mn) >= int(info.min) and int(mx) <= int(info.max):
             return False
         return True
 
@@ -392,7 +383,7 @@ def _do_scaling(self):
         out_max, out_min = info.max, info.min
         # If left as int64, uint64, comparisons will default to floats, and
         # these are inexact for > 2**53 - so convert to int
-        if as_int(mx) <= as_int(out_max) and as_int(mn) >= as_int(out_min):
+        if int(mx) <= int(out_max) and int(mn) >= int(out_min):
             # already in range
             return
         # (u)int to (u)int scaling
@@ -410,7 +401,7 @@ def _iu2iu(self):
             # that deals with max neg ints. abs problem only arises when all
             # the data is set to max neg integer value
             o_min, o_max = shared_range(self.scaler_dtype, out_dt)
-            if mx <= 0 and int_abs(mn) <= as_int(o_max):  # sign flip enough?
+            if mx <= 0 and int_abs(mn) <= int(o_max):  # sign flip enough?
                 # -1.0 * arr will be in scaler_dtype precision
                 self.slope = -1.0
                 return
@@ -427,7 +418,7 @@ def _range_scale(self, in_min, in_max):
             # not lose precision because min/max are of fp type.
             out_min, out_max = np.array((out_min, out_max), dtype=big_float)
         else:  # (u)int
-            out_min, out_max = (int_to_float(v, big_float) for v in (out_min, out_max))
+            out_min, out_max = (big_float(v) for v in (out_min, out_max))
         if self._out_dtype.kind == 'u':
             if in_min < 0 and in_max > 0:
                 raise WriterError(
@@ -546,14 +537,13 @@ def to_fileobj(self, fileobj, order='F'):
 
     def _iu2iu(self):
         # (u)int to (u)int
-        mn, mx = (as_int(v) for v in self.finite_range())
+        mn, mx = (int(v) for v in self.finite_range())
         # range may be greater than the largest integer for this type.
-        # as_int needed to work round numpy 1.4.1 int casting bug
         out_dtype = self._out_dtype
         # Options in this method are scaling using intercept only.  These will
         # have to pass through ``self.scaler_dtype`` (because the intercept is
         # in this type).
-        o_min, o_max = (as_int(v) for v in shared_range(self.scaler_dtype, out_dtype))
+        o_min, o_max = (int(v) for v in shared_range(self.scaler_dtype, out_dtype))
         type_range = o_max - o_min
         mn2mx = mx - mn
         if mn2mx <= type_range:  # might offset be enough?
@@ -565,12 +555,12 @@ def _iu2iu(self):
             else:  # int output - take midpoint to 0
                 # ceil below increases inter, pushing scale up to 0.5 towards
                 # -inf, because ints have abs min == abs max + 1
-                midpoint = mn + as_int(np.ceil(mn2mx / 2.0))
+                midpoint = mn + int(np.ceil(mn2mx / 2.0))
                 # Floor exact decreases inter, so pulling scaled values more
                 # positive. This may make mx - inter > t_max
                 inter = floor_exact(midpoint, self.scaler_dtype)
             # Need to check still in range after floor_exact-ing
-            int_inter = as_int(inter)
+            int_inter = int(inter)
             assert mn - int_inter >= o_min
             if mx - int_inter <= o_max:
                 self.inter = inter
@@ -594,14 +584,13 @@ def _range_scale(self, in_min, in_max):
             in_min, in_max = np.array([in_min, in_max], dtype=big_float)
             in_range = np.diff([in_min, in_max])
         else:  # max possible (u)int range is 2**64-1 (int64, uint64)
-            # int_to_float covers this range.  On windows longdouble is the
-            # same as double so in_range will be 2**64 - thus overestimating
-            # slope slightly.  Casting to int needed to allow in_max-in_min to
-            # be larger than the largest (u)int value
-            in_min, in_max = as_int(in_min), as_int(in_max)
-            in_range = int_to_float(in_max - in_min, big_float)
+            # On windows longdouble is the same as double so in_range will be 2**64 -
+            # thus overestimating slope slightly.  Casting to int needed to allow
+            # in_max-in_min to be larger than the largest (u)int value
+            in_min, in_max = int(in_min), int(in_max)
+            in_range = big_float(in_max - in_min)
             # Cast to float for later processing.
-            in_min, in_max = (int_to_float(v, big_float) for v in (in_min, in_max))
+            in_min, in_max = (big_float(v) for v in (in_min, in_max))
         if out_dtype.kind == 'f':
             # Type range, these are also floats
             info = type_info(out_dtype)

nibabel/casting.py

@@ -10,6 +10,8 @@
 
 import numpy as np
 
+from .deprecated import deprecate_with_version
+
 
 class CastingError(Exception):
     pass
@@ -402,6 +404,7 @@ def _check_maxexp(np_type, maxexp):
         return np.isfinite(two ** (maxexp - 1)) and not np.isfinite(two**maxexp)
 
 
+@deprecate_with_version('as_int() is deprecated. Use int() instead.', '5.2.0', '7.0.0')
 def as_int(x, check=True):
     """Return python integer representation of number
 
@@ -411,9 +414,6 @@ def as_int(x, check=True):
     It is also useful to work around a numpy 1.4.1 bug in conversion of uints
     to python ints.
 
-    This routine will still raise an OverflowError for values that are outside
-    the range of float64.
-
     Parameters
     ----------
     x : object
@@ -439,30 +439,13 @@ def as_int(x, check=True):
     >>> as_int(2.1, check=False)
     2
     """
-    x = np.array(x)
-    if x.dtype.kind in 'iu':
-        # This works around a nasty numpy 1.4.1 bug such that:
-        # >>> int(np.uint32(2**32-1)
-        # -1
-        return int(str(x))
     ix = int(x)
-    if ix == x:
-        return ix
-    fx = np.floor(x)
-    if check and fx != x:
+    if check and ix != x:
         raise FloatingError(f'Not an integer: {x}')
-    if not fx.dtype.type == np.longdouble:
-        return int(x)
-    # Subtract float64 chunks until we have all of the number. If the int is
-    # too large, it will overflow
-    ret = 0
-    while fx != 0:
-        f64 = np.float64(fx)
-        fx -= f64
-        ret += int(f64)
-    return ret
+    return ix
 
 
+@deprecate_with_version('int_to_float(..., dt) is deprecated. Use dt() instead.', '5.2.0', '7.0.0')
 def int_to_float(val, flt_type):
     """Convert integer `val` to floating point type `flt_type`
 
@@ -484,18 +467,13 @@ def int_to_float(val, flt_type):
     -------
     f : numpy scalar
         of type `flt_type`
+
+    Examples
+    --------
+    >>> int_to_float(1, np.float32)
+    1.0
     """
-    if flt_type is not np.longdouble:
-        return flt_type(val)
-    # The following works around a nasty numpy 1.4.1 bug such that:
-    # >>> int(np.uint32(2**32-1)
-    val = int(val)
-    faval = np.longdouble(0)
-    while val != 0:
-        f64 = np.float64(val)
-        faval += f64
-        val -= int(f64)
-    return faval
+    return flt_type(val)
 
 
 def floor_exact(val, flt_type):
@@ -542,14 +520,14 @@ def floor_exact(val, flt_type):
     val = int(val)
     flt_type = np.dtype(flt_type).type
     sign = 1 if val > 0 else -1
-    try:  # int_to_float deals with longdouble safely
-        fval = int_to_float(val, flt_type)
+    try:
+        fval = flt_type(val)
     except OverflowError:
         return sign * np.inf
     if not np.isfinite(fval):
         return fval
     info = type_info(flt_type)
-    diff = val - as_int(fval)
+    diff = val - int(fval)
     if diff >= 0:  # floating point value <= val
         return fval
     # Float casting made the value go up

nibabel/conftest.py

@@ -1,3 +1,5 @@
+import sys
+
 import numpy as np
 import pytest
 
@@ -12,3 +14,18 @@ def legacy_printoptions():
 
     if Version(np.__version__) >= Version('1.22'):
         np.set_printoptions(legacy='1.21')
+
+
+@pytest.fixture
+def max_digits():
+    # Set maximum number of digits for int/str conversion for
+    # duration of a test
+    try:
+        orig_max_str_digits = sys.get_int_max_str_digits()
+        yield sys.set_int_max_str_digits
+        sys.set_int_max_str_digits(orig_max_str_digits)
+    except AttributeError:  # pragma: no cover
+        # Nothing to do for versions of Python that lack these methods
+        # They were added as DoS protection in Python 3.11 and backported to
+        # some other versions.
+        yield lambda x: None

nibabel/tests/test_analyze.py

@@ -26,7 +26,7 @@
 from .. import imageglobals
 from ..analyze import AnalyzeHeader, AnalyzeImage
 from ..arraywriters import WriterError
-from ..casting import as_int, sctypes_aliases
+from ..casting import sctypes_aliases
 from ..nifti1 import Nifti1Header
 from ..optpkg import optional_package
 from ..spatialimages import HeaderDataError, HeaderTypeError, supported_np_types
@@ -308,8 +308,7 @@ def test_shapes(self):
             assert hdr.get_data_shape() == shape
         # Check max works, but max+1 raises error
         dim_dtype = hdr.structarr['dim'].dtype
-        # as_int for safety to deal with numpy 1.4.1 int conversion errors
-        mx = as_int(np.iinfo(dim_dtype).max)
+        mx = int(np.iinfo(dim_dtype).max)
         shape = (mx,)
         hdr.set_data_shape(shape)
         assert hdr.get_data_shape() == shape

nibabel/tests/test_casting.py

@@ -10,12 +10,10 @@
 from ..casting import (
     CastingError,
     able_int_type,
-    as_int,
     best_float,
     float_to_int,
     floor_log2,
     int_abs,
-    int_to_float,
     longdouble_precision_improved,
     sctypes,
     shared_range,
@@ -42,7 +40,7 @@ def test_shared_range():
             if casted_mx != imax:
                 # The shared_range have told us that they believe the imax does
                 # not have an exact representation.
-                fimax = int_to_float(imax, ft)
+                fimax = ft(imax)
                 if np.isfinite(fimax):
                     assert int(fimax) != imax
                 # Therefore the imax, cast back to float, and to integer, will
@@ -68,7 +66,7 @@ def test_shared_range():
             if casted_mn != imin:
                 # The shared_range have told us that they believe the imin does
                 # not have an exact representation.
-                fimin = int_to_float(imin, ft)
+                fimin = ft(imin)
                 if np.isfinite(fimin):
                     assert int(fimin) != imin
                 # Therefore the imin, cast back to float, and to integer, will
@@ -101,11 +99,6 @@ def test_casting():
             mn, mx = shared_range(ft, it)
             with np.errstate(invalid='ignore'):
                 iarr = float_to_int(farr, it)
-            # Dammit - for long doubles we need to jump through some hoops not
-            # to round to numbers outside the range
-            if ft is np.longdouble:
-                mn = as_int(mn)
-                mx = as_int(mx)
             exp_arr = np.array([mn, mx, mn, mx, 0, 0, 11], dtype=it)
             assert_array_equal(iarr, exp_arr)
             # Now test infmax version
@@ -149,7 +142,7 @@ def test_int_abs():
         assert udtype.kind == 'u'
         assert idtype.itemsize == udtype.itemsize
         mn, mx = in_arr
-        e_mn = as_int(mx) + 1  # as_int needed for numpy 1.4.1 casting
+        e_mn = int(mx) + 1
         assert int_abs(mx) == mx
         assert int_abs(mn) == e_mn
         assert_array_equal(int_abs(in_arr), [e_mn, mx])