Conversion float64->int bugged?
Hi all, The conversion from a numpy scalar to a python int is not consistent with python's native conversion (or numarray's): if the scalar is out of bounds for an int, python and numarray automatically create a long while numpy still creates an int... with the wrong value. N.B. I am new to numpy, so please forgive me if this issue has already been discussed. I've quickly searched the archives and Travis's "Guide to NumPy", with no success. e.g. (using numpy 1.0.3): Python 2.4.3 (#2, Apr 27 2006, 14:43:58) [GCC 4.0.3 (Ubuntu 4.0.3-1ubuntu5)] on linux2 Type "help", "copyright", "credits" or "license" for more information.
from numpy import * l= [1e3, 1e9, 1e15, -1e3, -1e9, -1e15] a= array(l) map(int, l) [1000, 1000000000, 1000000000000000L, -1000, -1000000000, -1000000000000000L] map(int, a) [1000, 1000000000, -2147483648, -1000, -1000000000, -2147483648] map(long, a) [1000L, 1000000000L, 1000000000000000L, -1000L, -1000000000L, -1000000000000000L]
IMHO, numpy's conversions to int should behave like Python's 'float_int' or 'long_int' functions (see $PYTHON_SRC_DIR/Objects/floatobject.c, $PYTHON_SRC_DIR/Objects/longobject.c): if it doesn't fit in an int, return a long. For now (svn), it seems that numpy is always using PyInt_FromLong after an implicit C cast to long (which silently fails; see $NUMPY_SRC_DIR/numpy/core/src/scalarmathmodule.c.src) Is there any reason not to change this? Thanks, Xavier Saint-Mleux
On 7/9/07, Xavier Saint-Mleux <saintmlx@apstat.com> wrote:
Hi all,
The conversion from a numpy scalar to a python int is not consistent with python's native conversion (or numarray's): if the scalar is out of bounds for an int, python and numarray automatically create a long while numpy still creates an int... with the wrong value.
N.B. I am new to numpy, so please forgive me if this issue has already been discussed. I've quickly searched the archives and Travis's "Guide to NumPy", with no success.
e.g. (using numpy 1.0.3):
Python 2.4.3 (#2, Apr 27 2006, 14:43:58) [GCC 4.0.3 (Ubuntu 4.0.3-1ubuntu5)] on linux2 Type "help", "copyright", "credits" or "license" for more information.
from numpy import * l= [1e3, 1e9, 1e15, -1e3, -1e9, -1e15] a= array(l) map(int, l) [1000, 1000000000, 1000000000000000L, -1000, -1000000000, -1000000000000000L] map(int, a) [1000, 1000000000, -2147483648, -1000, -1000000000, -2147483648] map(long, a) [1000L, 1000000000L, 1000000000000000L, -1000L, -1000000000L, -1000000000000000L]
IMHO, numpy's conversions to int should behave like Python's 'float_int' or 'long_int' functions (see $PYTHON_SRC_DIR/Objects/floatobject.c, $PYTHON_SRC_DIR/Objects/longobject.c): if it doesn't fit in an int, return a long. For now (svn), it seems that numpy is always using PyInt_FromLong after an implicit C cast to long (which silently fails; see $NUMPY_SRC_DIR/numpy/core/src/scalarmathmodule.c.src)
Is there any reason not to change this?
FWIW, it seems like a good idea to me. -- . __ . |-\ . . tim.hochberg@ieee.org
I opened a new ticket for this: http://projects.scipy.org/scipy/numpy/ticket/549 Xavier Timothy Hochberg wrote:
On 7/9/07, *Xavier Saint-Mleux* <saintmlx@apstat.com <mailto:saintmlx@apstat.com>> wrote:
Hi all,
The conversion from a numpy scalar to a python int is not consistent with python's native conversion (or numarray's): if the scalar is out of bounds for an int, python and numarray automatically create a long while numpy still creates an int... with the wrong value.
N.B. I am new to numpy, so please forgive me if this issue has already been discussed. I've quickly searched the archives and Travis's "Guide to NumPy", with no success.
e.g. (using numpy 1.0.3):
Python 2.4.3 (#2, Apr 27 2006, 14:43:58) [GCC 4.0.3 (Ubuntu 4.0.3-1ubuntu5)] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> from numpy import * >>> l= [1e3, 1e9, 1e15, -1e3, -1e9, -1e15] >>> a= array(l) >>> map(int, l) [1000, 1000000000, 1000000000000000L, -1000, -1000000000, -1000000000000000L] >>> map(int, a) [1000, 1000000000, -2147483648, -1000, -1000000000, -2147483648] >>> map(long, a) [1000L, 1000000000L, 1000000000000000L, -1000L, -1000000000L, -1000000000000000L] >>>
IMHO, numpy's conversions to int should behave like Python's 'float_int' or 'long_int' functions (see $PYTHON_SRC_DIR/Objects/floatobject.c, $PYTHON_SRC_DIR/Objects/longobject.c): if it doesn't fit in an int, return a long. For now (svn), it seems that numpy is always using PyInt_FromLong after an implicit C cast to long (which silently fails; see $NUMPY_SRC_DIR/numpy/core/src/scalarmathmodule.c.src)
Is there any reason not to change this?
FWIW, it seems like a good idea to me.
-- . __ . |-\ . . tim.hochberg@ieee.org <mailto:tim.hochberg@ieee.org>
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saintmlx -
Timothy Hochberg -
Xavier Saint-Mleux