I have 2 PCs with 2 different installs:
ActivePython 2.4.3 Build 12 with numpy version '1.0b1'
and
Enthought 2.4.3 (1.0.0 #69) with numpy version '0.9.7.2476'
The attached runs Ok on numpy v1.0, but on Enthought's, print a1[0]
gives:
IndexError: 0-d arrays can't be indexed.
It seems that the 0.9.7 numpy.asarray is not creating a true array
from Dummy class in the code below. Enthought only comes with
0.9.9.2706 (now).
When was the asarray behavior supported, or, is there some other
issue I'm missing?
I'll use Activestate's distro if needed, but I'd like to keep
Enthought for that one...
def fromaddress(address, dtype, shape, strides=None):
""" Create a numpy array from an integer address, a dtype
or dtype string, a shape tuple, and possibly strides.
"""
import numpy
# Make sure our dtype is a dtype, not just "f" or whatever.
dtype = numpy.dtype(dtype)
class Dummy(object):
pass
d = Dummy()
d.__array_interface__ = dict(
data = (address, False),
typestr = dtype.str,
descr = dtype.descr,
shape = shape,
strides = strides,
version = 3,
)
return numpy.asarray(d)
Thanks,
Ray""" nFromAddress.py
"""
def fromaddress(address, dtype, shape, strides=None):
""" Create a numpy array from an integer address, a dtype
or dtype string, a shape tuple, and possibly strides.
"""
import numpy
# Make sure our dtype is a dtype, not just "f" or whatever.
dtype = numpy.dtype(dtype)
class Dummy(object):
pass
d = Dummy()
d.__array_interface__ = dict(
data = (address, False),
typestr = dtype.str,
descr = dtype.descr,
shape = shape,
strides = strides,
version = 3,
)
return numpy.asarray(d)
##Numeric example, with address kludge
import Numeric, numpy, ctypes, string
a0 = Numeric.zeros((10000), Numeric.Int16)
nAddress = int(string.split(repr(a0.__copy__))[-1][:-1], 16)
tmp=(ctypes.c_long*1)(0)
ctypes.memmove(tmp, nAddress+8, 4)
nAddress = tmp[0]
a1 = fromaddress(nAddress, numpy.int16, (10000,))
a0[0] = 5
print a1[0]
## numpy example
a2 = numpy.zeros(10000, numpy.int16)
nAddress = a2.__array_interface__['data'][0]
nType = a2.__array_interface__['typestr']
nShape = a2.__array_interface__['shape']
a3 = fromaddress(nAddress, nType, nShape)
a2[0] = 5
print a3[0]_______________________________________________
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