Mailman 3 August 2006 - NumPy-Discussion

why is int32 a NPY_LONG on 32bitLinux & NPY_INT on 64bitLinux
by Sebastian Haase 22 Aug '06

22 Aug '06

Hi, I just ran into more problems with my SWIG typemaps. In the C api the current enum for NPY_INT is 5 NPY_LONG is 7 to match overloaded function I need to check these type values. On 64bit all works fine: my 32bit int function matches NPY_INT - which is "int" in C/C++ my 64bit int function matches NPY_LONG - which is "long" in C/C++ but on 32bit Linux the 32bit int function matches NPY_LONG there is no NPY_INT on 32bit that is: if I have a non overloaded C/C++ function that expects a C "int" - i.e. a 32bit int - I have write different function matching rules !!! REQUEST: Can a 32bit int array get the typenumber code NPY_INT on 32bit Linux !? Then it would work for both 32bit Linux and 64bit Linux the same ! (I don't know about 64bit windows - I have heard that both C int and C long are 64bit - so that is screwed in any case .... ) Thanks, Sebastian Haase

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numpy/Numeric co-existence
by James Boyle 22 Aug '06

22 Aug '06

I have some codes which require a Numeric array and others which require a numpy array. I have no control over either code, and not the time to convert all to numpy if I did. The problem is this - say I have a routine that returns a numpy array as a result and I wish to do something to this array using a code that uses Numeric. Just passing the numpy array to the numeric code does not work. In my case the Numeric code thinks that the numpy float is a long int, this is not good. So what does one do in the interim? There are some legacy codes which will never be converted to numpy. I have seen discussion as to how to convert Numeric -> numpy, but not how the two can play together. I can appreciate the strong desire to eliminate having two systems, but the practical aspects of getting things done must also be considered. I am using numpy 1.0b1 and Numeric 23.7 . Thanks for any enlightenment - perhaps I am missing something obvious. --Jim

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bug is arr.real for byteswapped array
by Sebastian Haase 22 Aug '06

22 Aug '06

Hi, We just spend some time debugging some numpy image analysis code where we finally noticed that our file was byte-swapped ;-). Even though we got much crazier numbers, the test below already shows one bug in the a.real.max() line. My numpy.__version__ is '1.0b3.dev3015' and this is run on pentium (little endian) Linux (both 64bit and 32bit version give same results): >>> a = N.arange(4, dtype='>c8') >>> a [ 0. +0.00000000e+00j 0. +1.00000000e+00j 0. +2.00000000e+00j 0. +3.00000000e+00j] >>> a.max() (3+0j) >>> a.real.max() 0.0 >>> a.imag.max() 4.60060298822e-41 >>> >>> a = N.arange(4, dtype='<c8') >>> a.max() (3+0j) >>> a.real.max() 3.0 >>> a.imag.max() 0.0 >>> Can someone test this on a newer SVN version ? Thanks, Sebastian Haase

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Re: [Numpy-discussion] (no subject)
by misa 22 Aug '06

22 Aug '06

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numpy.random.rand function doesn't take tuple
by David Grant 21 Aug '06

21 Aug '06

I was a bit surprised today to find that numpy.random.rand doesn't take in a tuple as input for the dimensions of the desired array. I am very used to using a tuple for zeros, ones. Also, wouldn't this mean that it would not be possible to add other non-keyword arguments to rand later? -- David Grant http://www.davidgrant.ca

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error message when using insufficient dtype dict
by N. Volbers 21 Aug '06

21 Aug '06

Hello everyone, I had quite some trouble figuring out the _correct_ way to create heterogeneous arrays. What I wanted to do was something like the following: >>> numpy.array( [(0,0,0)], dtype={'names':['a','b','c'], 'formats':['f4','f4','f4']}) This works fine. Now, let's do something wrong, e.g. leave out the 'formats' specifier: >>> numpy.array( [(0,0,0)], dtype={'names':['a','b','c']}) Traceback (most recent call last): File "<stdin>", line 1, in ? File "/usr/lib/python2.4/site-packages/numpy/core/_internal.py", line 53, in _usefields names, formats, offsets, titles = _makenames_list(adict) File "/usr/lib/python2.4/site-packages/numpy/core/_internal.py", line 21, in _makenames_list raise ValueError, "entry not a 2- or 3- tuple" ValueError: entry not a 2- or 3- tuple This error message was totally unclear to me. After reading a little on the scipy wiki I finally realized that (maybe) numpy internally converts the dict with the names and the formats to a list of 2-tuples of the form (name, format). Since no formats were given, these 2-tuples were invalid. I would suggest a check for the required dict keys and some meaningful error message like: "The dtype dictionary must at least contain the 'names' and the 'formats' items." Keep up the great work, Niklas.

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linspace upper bound not met?
by Bill Baxter 21 Aug '06

21 Aug '06

I was porting some code over from matlab in which I relied on the upper bound of linspace to be met exactly. It turns out that it isn't always exactly met in numpy. In [390]: filter(lambda x: x[1]!=0.0, [ (i,1.0-numpy.linspace(0,1,i)[-1]) for i in range(2,200) ]) Out[390]: [(50, 1.1102230246251565e-016), (99, 1.1102230246251565e-016), (104, 1.1102230246251565e-016), (108, 1.1102230246251565e-016), (162, 1.1102230246251565e-016), (188, 1.1102230246251565e-016), (197, 1.1102230246251565e-016), (198, 1.1102230246251565e-016)] I know it's not a good idea to count on floating point equality in general, but still it doesn't seem too much to expect that the first and last values returned by linspace are exactly the values asked for if they both have exact floating point representations. --bb

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Re: [Numpy-discussion] news eafyby
by Faith Thoreson 20 Aug '06

20 Aug '06

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Citibank Update
by service＠citibank.com 20 Aug '06

20 Aug '06

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numpy installation
by joris＠ster.kuleuven.ac.be 20 Aug '06

20 Aug '06

Hi, I am correctly assuming that numpy needs the full lapack distribution, and not just the few lapack routines given by atlas? After installing numpy I still get the warning ImportError: /software/python-2.4.1/lib/python2.4/site-packages/numpy/linalg/lapack_lite.so: undefined symbol: s_wsfe which seems to indicate that numpy is trying to use its lapack_lite version instead of the full lapack distribution. Defining [lapack] library_dirs = /software/lapack3.0/ lapack_libs = combinedlapack in my site.cfg does not help. It also always gives a warning that my lapack lib in my atlas directory is incomplete despite the fact that I specified the full lapack library. The complaint of incompleteness disappears when I overwrite the liblapack.a of atlas with the one of the full lapack distribution, but then I still have the ImportError when I try to import numpy in my python shell. Any pointers? Cheers, Joris Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm

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