[pypy-commit] pypy propogate-nans: porpogate various nan values across float conversions

[mattip]

Author: mattip <matti.picus at gmail.com>
Branch: propogate-nans
Changeset: r80508:ebaf0b23194a
Date: 2015-11-03 04:42 +0200
http://bitbucket.org/pypy/pypy/changeset/ebaf0b23194a/

Log:	porpogate various nan values across float conversions

diff --git a/pypy/module/micronumpy/test/test_ndarray.py b/pypy/module/micronumpy/test/test_ndarray.py
--- a/pypy/module/micronumpy/test/test_ndarray.py
+++ b/pypy/module/micronumpy/test/test_ndarray.py
@@ -1852,6 +1852,19 @@
         a = array([(1, 2)], dtype=[('a', 'int64'), ('b', 'int64')])
         assert a.view('S16')[0] == '\x01' + '\x00' * 7 + '\x02'
 
+    def test_half_conversions(self):
+        from numpy import array, arange
+        all_f16 = arange(0xff10, 0xff20, dtype='uint16')
+        all_f16.dtype = 'float16'
+        print all_f16.view(dtype='uint16')
+        all_f32 = array(all_f16, dtype='float32')
+        print all_f32.view(dtype='uint32')
+        b = array(all_f32, dtype='float16')
+        print b.view(dtype='uint16')
+        c = b.view(dtype='uint16')
+        d = all_f16.view(dtype='uint16')
+        assert (c == d).all()
+
     def test_ndarray_view_empty(self):
         from numpy import array, dtype
         x = array([], dtype=[('a', 'int8'), ('b', 'int8')])
diff --git a/rpython/rlib/rstruct/ieee.py b/rpython/rlib/rstruct/ieee.py
--- a/rpython/rlib/rstruct/ieee.py
+++ b/rpython/rlib/rstruct/ieee.py
@@ -6,6 +6,7 @@
 
 from rpython.rlib import rarithmetic, rfloat, objectmodel, jit
 from rpython.rlib.rarithmetic import r_ulonglong
+from rpython.rtyper.lltypesystem.rffi import DOUBLE, cast
 
 def round_to_nearest(x):
     """Python 3 style round:  round a float x to the nearest int, but
@@ -60,7 +61,10 @@
 
     if exp == MAX_EXP - MIN_EXP + 2:
         # nan or infinity
-        result = rfloat.NAN if mant else rfloat.INFINITY
+        if mant == 0:
+            result = rfloat.INFINITY
+        else:
+            result = rfloat.NAN #cast(DOUBLE, mant | 
     elif exp == 0:
         # subnormal or zero
         result = math.ldexp(mant, MIN_EXP - MANT_DIG)