diff --git a/pandas/src/ujson/lib/ultrajson.h b/pandas/src/ujson/lib/ultrajson.h index 30e72d8f31eca..826e3fc8a53e1 100644 --- a/pandas/src/ujson/lib/ultrajson.h +++ b/pandas/src/ujson/lib/ultrajson.h @@ -80,7 +80,9 @@ Dictates and limits how much stack space for buffers UltraJSON will use before r typedef __int64 JSINT64; typedef unsigned __int64 JSUINT64; +#ifndef __MINGW32__ typedef unsigned __int32 uint32_t; +#endif typedef __int32 JSINT32; typedef uint32_t JSUINT32; typedef unsigned __int8 JSUINT8; diff --git a/pandas/src/ujson/python/objToJSON.c b/pandas/src/ujson/python/objToJSON.c index fa4de44bb47b0..5b7973874d335 100644 --- a/pandas/src/ujson/python/objToJSON.c +++ b/pandas/src/ujson/python/objToJSON.c @@ -2,8 +2,8 @@ #include "py_defines.h" #include +#include #include -#include #include #include #include @@ -138,15 +138,6 @@ static void *PyLongToINT64(JSOBJ _obj, JSONTypeContext *tc, void *outValue, size return NULL; } -static void *NpyHalfToDOUBLE(JSOBJ _obj, JSONTypeContext *tc, void *outValue, size_t *_outLen) -{ - PyObject *obj = (PyObject *) _obj; - unsigned long ctype; - PyArray_ScalarAsCtype(obj, &ctype); - *((double *) outValue) = npy_half_to_double (ctype); - return NULL; -} - static void *NpyFloatToDOUBLE(JSOBJ _obj, JSONTypeContext *tc, void *outValue, size_t *_outLen) { PyObject *obj = (PyObject *) _obj; @@ -1145,13 +1136,6 @@ void Object_beginTypeContext (JSOBJ _obj, JSONTypeContext *tc) return; } else - if (PyArray_IsScalar(obj, Half)) - { - PRINTMARK(); - pc->PyTypeToJSON = NpyHalfToDOUBLE; tc->type = JT_DOUBLE; - return; - } - else if (PyArray_IsScalar(obj, Datetime)) { PRINTMARK(); diff --git a/pandas/tests/test_ujson.py b/pandas/tests/test_ujson.py index 80612579772d0..96ae678035197 100644 --- a/pandas/tests/test_ujson.py +++ b/pandas/tests/test_ujson.py @@ -802,9 +802,6 @@ def testFloat(self): num = np.float(256.2013) self.assertEqual(np.float(ujson.decode(ujson.encode(num))), num) - num = np.float16(256.2013) - self.assertEqual(np.float16(ujson.decode(ujson.encode(num))), num) - num = np.float32(256.2013) self.assertEqual(np.float32(ujson.decode(ujson.encode(num))), num) @@ -820,17 +817,10 @@ def testFloatArray(self): outp = np.array(ujson.decode(ujson.encode(inpt, double_precision=15)), dtype=dtype) assert_array_almost_equal_nulp(inpt, outp) - inpt = np.arange(1.5, 21.5, 0.2, dtype=np.float16) - outp = np.array(ujson.decode(ujson.encode(inpt)), dtype=np.float16) - assert_array_almost_equal_nulp(inpt, outp) - def testFloatMax(self): num = np.float(np.finfo(np.float).max/10) assert_approx_equal(np.float(ujson.decode(ujson.encode(num))), num, 15) - num = np.float16(np.finfo(np.float16).max/10) - assert_approx_equal(np.float16(ujson.decode(ujson.encode(num))), num, 15) - num = np.float32(np.finfo(np.float32).max/10) assert_approx_equal(np.float32(ujson.decode(ujson.encode(num))), num, 15) diff --git a/setup.py b/setup.py index a625fc48c080e..6a0b2b8d1912f 100755 --- a/setup.py +++ b/setup.py @@ -74,8 +74,6 @@ msg = "pandas requires NumPy >= 1.6 due to datetime64 dependency" sys.exit(msg) -from numpy.distutils.misc_util import get_pkg_info, get_info - from distutils.extension import Extension from distutils.command.build import build from distutils.command.build_ext import build_ext @@ -378,11 +376,6 @@ def srcpath(name=None, suffix='.pyx', subdir='src'): sources=[srcpath('sparse', suffix=suffix)], include_dirs=[np.get_include()]) -npymath_info = get_info('npymath') - -npymath_libdir = npymath_info['library_dirs'][0] -npymath_libdir = npymath_libdir.replace('\\\\', '\\') - ujson_ext = Extension('pandas._ujson', sources=['pandas/src/ujson/python/ujson.c', 'pandas/src/ujson/python/objToJSON.c', @@ -395,10 +388,6 @@ def srcpath(name=None, suffix='.pyx', subdir='src'): 'pandas/src/ujson/lib', 'pandas/src/datetime', np.get_include()], - libraries=['npymath'], - library_dirs=[npymath_libdir], - # extra_link_args=[get_pkg_info('npymath').libs()] - #extra_info=get_info('npymath') ) sandbox_ext = Extension('pandas._sandbox',