Re: [Numpy-discussion] read ascii file from complex fortran format() -- genfromtxt
On 21/09/2010 18:29, David Huard wrote: Have you tried http://code.google.com/p/python-fortranformat/ It's not officially released yet but it's probably worth a try. Well, I noticed it, bugt the website does say This is a work in progress, a working version is not yet available! Andrew David H. On Tue, Sep 21, 2010 at 8:25 AM, Andrew Jaffe a.h.ja...@gmail.com mailto:a.h.ja...@gmail.com wrote: Hi all, I've got an ascii file with a relatively complicated structure, originally written by fortran with the format: 135format(a12,1x,2(f10.5,1x),i3,1x,4(f9.3,1x),4(i2,1x),3x, 1 16(f7.2,1x),i3,3x,f13.5,1x,f10.5,1x,f10.6,1x,i3,1x, 2 4(f10.6,1x), 2 i2,1x,f5.2,1x,f10.3,1x,i3,1x,f7.2,1x,f7.2,3x,4(f7.4,1x), 3 4(f7.2,1x),3x,f7.2,1x,i4,3x,f10.3,1x,14(f6.2,1x),i3,1x, 1 3x,2f10.5,8f11.2,2f10.5,f12.3,3x, 4 2(a6,1x),a23,1x,a22,1x,a22) Note, in particular, that many of the strings contain white space. Is there a relatively straightforward way to translate this into dtype (and delimiter?) arguments for use with genfromtxt or do I just have to do it by hand? Andrew ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org mailto:NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] read ascii file from complex fortran format() -- genfromtxt
On Sep 21, 2010, at 2:25 PM, Andrew Jaffe wrote: Hi all, I've got an ascii file with a relatively complicated structure, originally written by fortran with the format: 135format(a12,1x,2(f10.5,1x),i3,1x,4(f9.3,1x),4(i2,1x),3x, 1 16(f7.2,1x),i3,3x,f13.5,1x,f10.5,1x,f10.6,1x,i3,1x, 2 4(f10.6,1x), 2 i2,1x,f5.2,1x,f10.3,1x,i3,1x,f7.2,1x,f7.2,3x,4(f7.4,1x), 3 4(f7.2,1x),3x,f7.2,1x,i4,3x,f10.3,1x,14(f6.2,1x),i3,1x, 1 3x,2f10.5,8f11.2,2f10.5,f12.3,3x, 4 2(a6,1x),a23,1x,a22,1x,a22) Note, in particular, that many of the strings contain white space. Is there a relatively straightforward way to translate this into dtype (and delimiter?) arguments for use with genfromtxt or do I just have to do it by hand? By hand might be the easiest. If possible, try to put the empty spaces at the beginning of the string (eg, your 3x,f13.5 would be 16 characters). Use `autostrip=True`. Use a sequence as delimiter (like in your case (12,11,11,3,10,10,10,10,3,3,10,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,4,16...)), that should be more efficient. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] dtype from |S10 to object in array?
On Wed, Sep 22, 2010 at 2:04 AM, keekychen.shared
keekychen.sha...@gmail.com wrote:
Dear All,
See below code pls,
import sicpy
import numpy as np
x = np.zeros((2,),dtype=('i4,f4,a10'))
x[:] = [(1,2.,'Hello'),(2,3.,World)]
y = x['f2']
#array(['Hello', 'World'],
dtype='|S10')
x['f2'] = y
x
#array([(1, 2.0, 'Hello'), (2, 3.0, 'World')],
dtype=[('f0', 'i4'), ('f1', 'f4'), ('f2', '|S10')])
y = y.astype('object')
y
array([Hello, World], dtype=object)
x['f2'] = y
array([(1, 2.0, 'HellWorld'), (2, 3.0, '\x00\x00\x00\x00\x00\x00\x18')],
dtype=[('f0', 'i4'), ('f1', 'f4'), ('f2', '|S10')])
##here comes the problem: the f2 col type has not been changed and the
data is not I wanted...
here is why I need using this:
suppose I have a datasource, csv, sql based db or what ever look like this:
1, 2.0, 'Hello'
2, 3.0, 'World'
3, 2.0, 'other string'
I want to read them to a numpy array and process it's columns, it has no
problem for processing the float or int type but string.
After reading the manual and found the object dtype may store variable
string then I want to exact the string col into an new array, try to
process it then store back to the numpy matrix then store it back to
the data source.
May I know how I can do that? I do not care performance now.
I *guess* that you can do this by changing only the type of the string
column to object
dt = np.dtype([('f0', 'i4'), ('f1', 'f4'), ('f2', object)])
x = np.zeros((2,),dtype=('i4,f4,O'))
x[:] = [(1,2.,'Hello'),(2,3.,World)]
x
array([(1, 2.0, 'Hello'), (2, 3.0, 'World')],
dtype=[('f0', 'i4'), ('f1', 'f4'), ('f2', '|O4')])
x['f2'] = 'hello'
x
array([(1, 2.0, 'hello'), (2, 3.0, 'hello')],
dtype=[('f0', 'i4'), ('f1', 'f4'), ('f2', '|O4')])
Josef
Thanks for any hints
Rgs,
KC
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[Numpy-discussion] searching binary data
A colleague of mine posed the following problem. He wants to search large files of binary data for sequences. I thought of using mmap (to avoid reading all data into memory at once) and then turning this into a numpy array (using buffer=). But, how to then efficiently find a sequence? Note that I'm not committed to using numpy or mmap as part of the solution. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] searching binary data
On Wed, Sep 22, 2010 at 11:10 PM, Neal Becker ndbeck...@gmail.com wrote: A colleague of mine posed the following problem. He wants to search large files of binary data for sequences. Is there a reason why you cannot use one of the classic string search algorithms applied to the bytestream ? David ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] searching binary data
David Cournapeau wrote: On Wed, Sep 22, 2010 at 11:10 PM, Neal Becker ndbeck...@gmail.com wrote: A colleague of mine posed the following problem. He wants to search large files of binary data for sequences. Is there a reason why you cannot use one of the classic string search algorithms applied to the bytestream ? What would you suggest? Keep in mind the file is to big to fit into memory all at once. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] printable random seed ?
On Wed, Sep 22, 2010 at 09:27, josef.p...@gmail.com wrote:
I would like to generate random numbers based on a random seed, for
example what numpy.random does if the seed is not specified. But I
would also like to print out the initial state, so I can replicate the
random numbers.
Can I get a human readable or printable version of the initial state?
[~]
|13 prng = np.random.RandomState()
[~]
|14 prng2 = np.random.RandomState()
[~]
|15 prng.randint(100, size=10)
array([74, 62, 56, 94, 86, 59, 69, 94, 42, 18])
[~]
|16 prng2.randint(100, size=10)
array([21, 58, 34, 55, 9, 81, 45, 3, 93, 62])
[~]
|17 prng2.set_state(prng.get_state())
[~]
|18 prng.randint(100, size=10)
array([37, 57, 2, 0, 68, 9, 75, 88, 11, 7])
[~]
|19 prng2.randint(100, size=10)
array([37, 57, 2, 0, 68, 9, 75, 88, 11, 7])
[~]
|20 prng.get_state()
('MT19937',
array([1368120112, 957462593, 2623310617, 4207155283, 446940397,
3506388262, 4104366519, 371500243, 4029407620, 899392379,
1843090101, 248497, 4085469971, 306955884, 23307203,
1640066622, 48186677, 637144011, 854838500], dtype=uint32),
26,
0,
2.5933437794758841e-288)
Alternatively, what's a good way to randomly generate an initial
state?
np.random.RandomState() will do the best thing on each platform.
--
Robert Kern
I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth.
-- Umberto Eco
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Re: [Numpy-discussion] searching binary data
On Wed, Sep 22, 2010 at 09:10, Neal Becker ndbeck...@gmail.com wrote:
A colleague of mine posed the following problem. He wants to search large
files of binary data for sequences.
I thought of using mmap (to avoid reading all data into memory at once) and
then turning this into a numpy array (using buffer=).
But, how to then efficiently find a sequence?
mmap objects have most of the usual string methods:
[~]
|2 f = open('./scratch/foo.py', 'r+b')
[~]
|4 m = mmap.mmap(f.fileno(), 0)
[~]
|6 m.find('import')
11
[~]
|7 m[11:17]
'import'
--
Robert Kern
I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth.
-- Umberto Eco
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[Numpy-discussion] [PATCH] F2Py on Python 3
It seems that lib2to3 does not process the main f2py bootstrap script that gets autogenerated by f2py's setup.py. The trivial patch below replaces the print statements with sys.stderr.write() calls. After that change, f2py works just fine in Python 3.2 Index: numpy/f2py/setup.py === --- numpy/f2py/setup.py (revision 8716) +++ numpy/f2py/setup.py (working copy) @@ -62,7 +62,7 @@ except ValueError: pass os.environ[NO_SCIPY_IMPORT]=f2py if mode==g3-numpy: -print sys.stderr, G3 f2py support is not implemented, yet. +sys.stderr.write(G3 f2py support is not implemented, yet.\n) sys.exit(1) elif mode==2e-numeric: from f2py2e import main @@ -72,7 +72,7 @@ elif mode==2e-numpy: from numpy.f2py import main else: -print sys.stderr, Unknown mode:,`mode` +sys.stderr.write(Unknown mode: '%s'\n % mode) sys.exit(1) main() '''%(os.path.basename(sys.executable))) -- Lisandro Dalcin --- CIMEC (INTEC/CONICET-UNL) Predio CONICET-Santa Fe Colectora RN 168 Km 472, Paraje El Pozo Tel: +54-342-4511594 (ext 1011) Tel/Fax: +54-342-4511169 ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] searching binary data
On Wed, Sep 22, 2010 at 11:25 PM, Neal Becker ndbeck...@gmail.com wrote: David Cournapeau wrote: On Wed, Sep 22, 2010 at 11:10 PM, Neal Becker ndbeck...@gmail.com wrote: A colleague of mine posed the following problem. He wants to search large files of binary data for sequences. Is there a reason why you cannot use one of the classic string search algorithms applied to the bytestream ? What would you suggest? Keep in mind the file is to big to fit into memory all at once. Do you care about speed ? String search and even regular expression are supposed to work on mmap data, but I have never used them on large datasets, so I don't know how they would perform. Otherwise, depending on the data and whether you can afford pre-computing, algorithms like Knuth Morris Pratt can speed things up. But I would assume you would have to do it in C to hope any speed gain compared to python string search . cheers, David ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] [PATCH] F2Py on Python 3
On Wed, Sep 22, 2010 at 8:35 AM, Lisandro Dalcin dalc...@gmail.com wrote: It seems that lib2to3 does not process the main f2py bootstrap script that gets autogenerated by f2py's setup.py. The trivial patch below replaces the print statements with sys.stderr.write() calls. After that change, f2py works just fine in Python 3.2 Index: numpy/f2py/setup.py === --- numpy/f2py/setup.py (revision 8716) +++ numpy/f2py/setup.py (working copy) @@ -62,7 +62,7 @@ except ValueError: pass os.environ[NO_SCIPY_IMPORT]=f2py if mode==g3-numpy: -print sys.stderr, G3 f2py support is not implemented, yet. +sys.stderr.write(G3 f2py support is not implemented, yet.\n) sys.exit(1) elif mode==2e-numeric: from f2py2e import main @@ -72,7 +72,7 @@ elif mode==2e-numpy: from numpy.f2py import main else: -print sys.stderr, Unknown mode:,`mode` +sys.stderr.write(Unknown mode: '%s'\n % mode) sys.exit(1) main() '''%(os.path.basename(sys.executable))) Looks reasonable. Want to try running this through the git process just for practice? Of course, it is only two lines so if git seems a bit much I'll make the change for you. Chuck ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] slicing / indexing question
On 21 September 2010 19:20, Timothy W. Hilton hil...@meteo.psu.edu wrote: I have an 80x1200x1200 nd.array of floats this_par. I have a 1200x1200 boolean array idx, and an 80-element float array pars. For each element of idx that is True, I wish to replace the corresponding 80x1x1 slice of this_par with the elements of pars. I've tried lots of variations on the theme of this_par[idx[np.newaxis, ...]] = pars[:, np.newaxis, np.newaxis] but so far, no dice. How about this? In [1]: A = np.zeros((2,3,5)) In [2]: B = np.array([1,2]) In [3]: C = np.zeros((3,5), dtype=np.bool) In [4]: C[1,1] = True In [5]: C[2,3] = True In [6]: C Out[6]: array([[False, False, False, False, False], [False, True, False, False, False], [False, False, False, True, False]], dtype=bool) In [7]: A[:,C] = B[:,np.newaxis] In [8]: A Out[8]: array([[[ 0., 0., 0., 0., 0.], [ 0., 1., 0., 0., 0.], [ 0., 0., 0., 1., 0.]], [[ 0., 0., 0., 0., 0.], [ 0., 2., 0., 0., 0.], [ 0., 0., 0., 2., 0.]]]) The key is that indexing with C replaces the two axes C is indexing with only one; boolean indexing necessarily flattens the relevant axes. You can check this with (e.g.) A[:,C].shape. Be careful with these mixed indexing modes (partly fancy indexing, partly slicing) as they can sometimes seem to reorder your axes for you: In [16]: np.zeros((2,3,7))[:,np.ones(5,dtype=int),np.ones(5,dtype=int)].shape Out[16]: (2, 5) In [17]: np.zeros((2,3,7))[np.ones(5,dtype=int),:,np.ones(5,dtype=int)].shape Out[17]: (5, 3) In [18]: np.zeros((2,3,7))[np.ones(5,dtype=int),np.ones(5,dtype=int),:].shape Out[18]: (5, 7) Anne ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Removing numpy numpy-1.1.0 in Python 2.5
Wayne Watson wrote: I've considered it, but it's way too time consuming to work out the details. I spent a week some time ago dealing with a simple test program, maybe 10 lines of code, trying to get it to work, which I think I did. I just need to work what I've got. There is a lot to be said for something that works already. However, I think it is generally a bad idea to distribute software based on python that relies on the standard python install with particular packages -- this will only work if you assume that that machine will not use python for anything else -- if two pieces of software both do this, but need different versions of packages, you are guaranteed breakage. RedHat did it with python way back when (I have no idea if they've changed that -- but it was pain). ESRI (GIS system) delivers the standard Windows Python version something with its GIS tools, and things break if you upgrade parts of it. Apple uses its system Python for some of its admin tools, and again, relies on who knows which versions of which packages. All this points to delivering python to your users separately from the standard install. If it's one app, use py2exe, py2app, pyInstaller, bbfreeze, whatever. If it's a collection of apps, you may want to built it on a custom python install, and/or maybe virtualenv. Anyway, if you know your users, and know they will, for sure, not use Python for anything else, then it's not a problem, but I think it's hard to know that. py2exe can be a pain, but it's usually short term pain -- once you have it working for your project, it keeps working (untill you add a new package anyway...) -Chris -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/ORR(206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception chris.bar...@noaa.gov ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Asking for opinions: Priops
Hello Friedrich, I have read your proposal. You describe issues that I have also encountered several times. I believe that your priops approach would be an improvement over the current overloading of binary operators. That being said, I think the issue is not so much numpy but rather the way Python implements operator overloading using methods like __add__ and __radd__. Hence, your suggestion seems to be a Python Enhancement Proposal and should be discussed without any references to numpy or bugs related to numpy.set_numeric_ops. Maybe you could also have a look at Go's interfaces (Googles programming language) which seems to be somewhat related to your approach. Also, have you checked the Python mail archive? Issues like that tend to be discussed from time to time. On a more practical note: Why exactly do you use set_numeric_ops? You could also 1) use numpy.ndarrays with dtype=object 2) or create new numpy.ndarray -like class and set __array_priority__ 2 both approaches work well for me. just my 2 cents, Sebastian On Thu, Sep 16, 2010 at 2:02 PM, Friedrich Romstedt friedrichromst...@gmail.com wrote: I just ran across the problem of priorities with ndarrays again and it keeps biting me. I did once ago a workaround to get my ``undarray`` class's methods be called when being the second operand of e.g. ndarray + undarray. But since I wrote it, always Python crashes on exit with the message: Python-32(68665) malloc: *** error for object 0x239680: incorrect checksum for freed object - object was probably modified after being freed. *** set a breakpoint in malloc_error_break to debug (Of course only if I imported the module. Occasionally I also observed Bus errors, and even segfaults.) I overloaded the numpy ops via numpy.set_numeric_ops() with self-written classes, which are *not* derived from numpy.ufunc, and do not resemble numpy ufuncs completely. So I want to do it properly this time. I therefore started with writing a Letter of Intent, and put it online on http://github.com/friedrichromstedt/priops . Opinions? Friedrich P.S.: I will start coding anyway, but it would be nice. P.P.S.: The package this originates from is also online, under http://github.com/friedrichromstedt/upy, or http://upy.sourceforge.net. I will probably create a small example script demonstrating the crash. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] Indexing and lookup issues
Hi everyone I suspect this is easy but I'm stuck say I have a 1D array: t = [10,11,12] and a 2D array: id = [[0,1,0] [0,2,0] [2,0,2]] In could in IDL do y = t[id] which would produce: y = [[10,11,10] [10,12,10] [12,10,12]] i.e. use the indexes in id on the lookup array t. Is there an easy way to do this in numpy? Cheers Ross -- Ross Williamson University of Chicago Department of Astronomy Astrophysics 773-834-9785 (office) 312-504-3051 (Cell) ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Indexing and lookup issues
On 22 September 2010 16:38, Ross Williamson rosswilliamson@gmail.com wrote: Hi everyone I suspect this is easy but I'm stuck say I have a 1D array: t = [10,11,12] and a 2D array: id = [[0,1,0] [0,2,0] [2,0,2]] In could in IDL do y = t[id] which would produce: y = [[10,11,10] [10,12,10] [12,10,12]] i.e. use the indexes in id on the lookup array t. Is there an easy way to do this in numpy? In [1]: t = np.array([10,11,12]) In [2]: id = np.array([[0,1,0], [0,2,0], [2,0,2]]) In [3]: t[id] Out[3]: array([[10, 11, 10], [10, 12, 10], [12, 10, 12]]) Anne ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Asking for opinions: Priops
On Wed, Sep 22, 2010 at 1:31 PM, Sebastian Walter sebastian.wal...@gmail.com wrote: Hello Friedrich, I have read your proposal. You describe issues that I have also encountered several times. I believe that your priops approach would be an improvement over the current overloading of binary operators. That being said, I think the issue is not so much numpy but rather the way Python implements operator overloading using methods like __add__ and __radd__. Hence, your suggestion seems to be a Python Enhancement Proposal and should be discussed without any references to numpy or bugs related to numpy.set_numeric_ops. Maybe you could also have a look at Go's interfaces (Googles programming language) which seems to be somewhat related to your approach. Also, have you checked the Python mail archive? Issues like that tend to be discussed from time to time. On a more practical note: Why exactly do you use set_numeric_ops? You could also 1) use numpy.ndarrays with dtype=object 2) or create new numpy.ndarray -like class and set __array_priority__ 2 both approaches work well for me. just my 2 cents, Sebastian On Thu, Sep 16, 2010 at 2:02 PM, Friedrich Romstedt friedrichromst...@gmail.com wrote: I just ran across the problem of priorities with ndarrays again and it keeps biting me. I did once ago a workaround to get my ``undarray`` class's methods be called when being the second operand of e.g. ndarray + undarray. But since I wrote it, always Python crashes on exit with the message: Python-32(68665) malloc: *** error for object 0x239680: incorrect checksum for freed object - object was probably modified after being freed. *** set a breakpoint in malloc_error_break to debug (Of course only if I imported the module. Occasionally I also observed Bus errors, and even segfaults.) I overloaded the numpy ops via numpy.set_numeric_ops() with self-written classes, which are *not* derived from numpy.ufunc, and do not resemble numpy ufuncs completely. So I want to do it properly this time. I therefore started with writing a Letter of Intent, and put it online on http://github.com/friedrichromstedt/priops . Opinions? Friedrich P.S.: I will start coding anyway, but it would be nice. P.P.S.: The package this originates from is also online, under http://github.com/friedrichromstedt/upy, or http://upy.sourceforge.net. I will probably create a small example script demonstrating the crash. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] [PATCH] F2Py on Python 3
On Wed, Sep 22, 2010 at 12:08 PM, Lisandro Dalcin dalc...@gmail.com wrote: On 22 September 2010 13:48, Charles R Harris charlesr.har...@gmail.com wrote: On Wed, Sep 22, 2010 at 8:35 AM, Lisandro Dalcin dalc...@gmail.com wrote: It seems that lib2to3 does not process the main f2py bootstrap script that gets autogenerated by f2py's setup.py. The trivial patch below replaces the print statements with sys.stderr.write() calls. After that change, f2py works just fine in Python 3.2 Index: numpy/f2py/setup.py === --- numpy/f2py/setup.py (revision 8716) +++ numpy/f2py/setup.py (working copy) @@ -62,7 +62,7 @@ except ValueError: pass os.environ[NO_SCIPY_IMPORT]=f2py if mode==g3-numpy: -print sys.stderr, G3 f2py support is not implemented, yet. +sys.stderr.write(G3 f2py support is not implemented, yet.\n) sys.exit(1) elif mode==2e-numeric: from f2py2e import main @@ -72,7 +72,7 @@ elif mode==2e-numpy: from numpy.f2py import main else: -print sys.stderr, Unknown mode:,`mode` +sys.stderr.write(Unknown mode: '%s'\n % mode) sys.exit(1) main() '''%(os.path.basename(sys.executable))) I'm also wondering if we shouldn't raise an error instead of writing to stderr. sys.exit(1) below the sys.stderr.write() is supposed to exit Python with an error status to the invoker of f2py. So I think nothing more have to be done. Done in 29cccb6. Chuck ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] [PATCH] F2Py on Python 3
On Wed, Sep 22, 2010 at 7:16 PM, Charles R Harris charlesr.har...@gmail.com wrote: Done in 29cccb6. Mmh, I think it broke something: File /home/fperez/tmp/src/scipy/numpy/numpy/distutils/command/build.py, line 37, in run old_build.run(self) File /usr/lib/python2.6/distutils/command/build.py, line 135, in run self.run_command(cmd_name) File /usr/lib/python2.6/distutils/cmd.py, line 333, in run_command self.distribution.run_command(command) File /usr/lib/python2.6/distutils/dist.py, line 995, in run_command cmd_obj.run() File /home/fperez/tmp/src/scipy/numpy/numpy/distutils/command/build_scripts.py, line 39, in run self.scripts = self.generate_scripts(self.scripts) File /home/fperez/tmp/src/scipy/numpy/numpy/distutils/command/build_scripts.py, line 24, in generate_scripts script = func(build_dir) File numpy/f2py/setup.py, line 78, in generate_f2py_py '''%(os.path.basename(sys.executable))) TypeError: not enough arguments for format string If I revert to the previous commit, it installs fine again. Cheers, f ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] [PATCH] F2Py on Python 3
On Wed, Sep 22, 2010 at 9:14 PM, Fernando Perez fperez@gmail.comwrote: On Wed, Sep 22, 2010 at 7:16 PM, Charles R Harris charlesr.har...@gmail.com wrote: Done in 29cccb6. Mmh, I think it broke something: File /home/fperez/tmp/src/scipy/numpy/numpy/distutils/command/build.py, line 37, in run old_build.run(self) File /usr/lib/python2.6/distutils/command/build.py, line 135, in run self.run_command(cmd_name) File /usr/lib/python2.6/distutils/cmd.py, line 333, in run_command self.distribution.run_command(command) File /usr/lib/python2.6/distutils/dist.py, line 995, in run_command cmd_obj.run() File /home/fperez/tmp/src/scipy/numpy/numpy/distutils/command/build_scripts.py, line 39, in run self.scripts = self.generate_scripts(self.scripts) File /home/fperez/tmp/src/scipy/numpy/numpy/distutils/command/build_scripts.py, line 24, in generate_scripts script = func(build_dir) File numpy/f2py/setup.py, line 78, in generate_f2py_py '''%(os.path.basename(sys.executable))) TypeError: not enough arguments for format string If I revert to the previous commit, it installs fine again. I wondered about that, it is probably the old `mode` vs plain old mode. I had just hoped it was tested. Can you check that out? Chuck ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] [PATCH] F2Py on Python 3
On Wed, Sep 22, 2010 at 10:00 PM, Charles R Harris charlesr.har...@gmail.com wrote: On Wed, Sep 22, 2010 at 9:14 PM, Fernando Perez fperez@gmail.comwrote: On Wed, Sep 22, 2010 at 7:16 PM, Charles R Harris charlesr.har...@gmail.com wrote: Done in 29cccb6. Mmh, I think it broke something: File /home/fperez/tmp/src/scipy/numpy/numpy/distutils/command/build.py, line 37, in run old_build.run(self) File /usr/lib/python2.6/distutils/command/build.py, line 135, in run self.run_command(cmd_name) File /usr/lib/python2.6/distutils/cmd.py, line 333, in run_command self.distribution.run_command(command) File /usr/lib/python2.6/distutils/dist.py, line 995, in run_command cmd_obj.run() File /home/fperez/tmp/src/scipy/numpy/numpy/distutils/command/build_scripts.py, line 39, in run self.scripts = self.generate_scripts(self.scripts) File /home/fperez/tmp/src/scipy/numpy/numpy/distutils/command/build_scripts.py, line 24, in generate_scripts script = func(build_dir) File numpy/f2py/setup.py, line 78, in generate_f2py_py '''%(os.path.basename(sys.executable))) TypeError: not enough arguments for format string If I revert to the previous commit, it installs fine again. I wondered about that, it is probably the old `mode` vs plain old mode. I had just hoped it was tested. Can you check that out? Should be fixed in 8f6114b. Chuck ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
