[Numpy-discussion] avoid a line...
Dear sir, I am try to read a file of the following format, I want to avoid the first line and read the remaining as 'float' . Please help me... RainWindTempPrSal 0.11.10.020.2 0.2 0.50. 0. 0.4 0.8 0.55.51.50.5 1.5 3.50.51.55.0 2.6 5.14.13.22.3 1.5 4.40.91.52.2.3 -- DILEEPKUMAR. R J R F, IIT DELHI ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] avoid a line...
Hi, On Thu, Mar 17, 2011 at 9:36 AM, dileep kunjaai dileepkunj...@gmail.comwrote: Dear sir, I am try to read a file of the following format, I want to avoid the first line and read the remaining as 'float' . Please help me... RainWindTempPrSal 0.11.10.020.2 0.2 0.50. 0. 0.4 0.8 0.55.51.50.5 1.5 3.50.51.55.0 2.6 5.14.13.22.3 1.5 4.40.91.52.2.3 You may use loadtxt(), with skiprows argument. (See more on http://docs.scipy.org/doc/numpy/reference/generated/numpy.loadtxt.html). Regards, eat -- DILEEPKUMAR. R J R F, IIT DELHI ___ 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] Norm of array of vectors
Dear all, Sorry if that's a noob question, but anyway. I have several thousands of vectors stacked in 2d array. I'd like to get new array containing Euclidean norms of these vectors and get the vector with minimal norm. Is there more efficient way to do this than argmin(array([sqrt(dot(x,x)) for x in vec_array]))? Thanks in advance. Andrey. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Norm of array of vectors
Hi, On Thu, Mar 17, 2011 at 10:44 AM, Andrey N. Sobolev inco...@list.ru wrote: Dear all, Sorry if that's a noob question, but anyway. I have several thousands of vectors stacked in 2d array. I'd like to get new array containing Euclidean norms of these vectors and get the vector with minimal norm. Is there more efficient way to do this than argmin(array([sqrt(dot(x,x)) for x in vec_array]))? Try argmin(sum(vec_array** 2, 0)** 0.5) Regards, eat Thanks in advance. Andrey. ___ 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] Norm of array of vectors
How about argmin(add.reduce((a*a),axis=1)) In [5]: a Out[5]: array([[ 0.24202827, 0.01269182, 0.95162307], [ 0.02979253, 0.454 , 0.49650111], [ 0.52626565, 0.08363861, 0.56444878], [ 0.89639659, 0.54259354, 0.29245881], [ 0.75301013, 0.6248646 , 0.24565827], [ 0.67501358, 0.58920861, 0.37420961], [ 0.8776001 , 0.58055258, 0.16623637], [ 0.26271551, 0.24441225, 0.47543652], [ 0.12793549, 0.88453877, 0.8479841 ], [ 0.49148293, 0.45352964, 0.65575962]]) In [6]: argmin(add.reduce((a*a),axis=1)) Out[6]: 7 In [7]: timeit argmin(array([sqrt(dot(x,x)) for x in a])) 1 loops, best of 3: 67.2 us per loop In [8]: timeit argmin(array([dot(x,x) for x in a])) 1 loops, best of 3: 36 us per loop In [9]: timeit argmin(add.reduce((a*a),axis=1)) 10 loops, best of 3: 13.6 us per loop Gary R On Thu, Mar 17, 2011 at 7:44 PM, Andrey N. Sobolev inco...@list.ru wrote: Dear all, Sorry if that's a noob question, but anyway. I have several thousands of vectors stacked in 2d array. I'd like to get new array containing Euclidean norms of these vectors and get the vector with minimal norm. Is there more efficient way to do this than argmin(array([sqrt(dot(x,x)) for x in vec_array]))? Thanks in advance. Andrey. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] avoid a line...
Thanks sir,, thanks a lot .. On Thu, Mar 17, 2011 at 1:16 PM, eat e.antero.ta...@gmail.com wrote: Hi, On Thu, Mar 17, 2011 at 9:36 AM, dileep kunjaai dileepkunj...@gmail.comwrote: Dear sir, I am try to read a file of the following format, I want to avoid the first line and read the remaining as 'float' . Please help me... RainWindTempPrSal 0.11.10.020.2 0.2 0.50. 0. 0.4 0.8 0.55.51.50.5 1.5 3.50.51.55.0 2.6 5.14.13.22.3 1.5 4.40.91.52.2.3 You may use loadtxt(), with skiprows argument. (See more on http://docs.scipy.org/doc/numpy/reference/generated/numpy.loadtxt.html). Regards, eat -- DILEEPKUMAR. R J R F, IIT DELHI ___ 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 -- DILEEPKUMAR. R J R F, IIT DELHI ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Build ERROR ConfigParser.MissingSectionHeaderError: File contains no section headers
Thanks Josef, that worked!
I was confused because I was thinking of site.cfg as some sort of bash
script :)
Jose
On Thu, Mar 17, 2011 at 12:40 AM, josef.p...@gmail.com wrote:
On Thu, Mar 17, 2011 at 12:23 AM, Jose Borreguero borregu...@gmail.com
wrote:
Dear Numpy/SciPy users,
I have a build error with Numpy:
$ /usr/local/bin/python2.7 setup.py build
File /usr/local/lib/python2.7/ConfigParser.py, line 504, in _read
raise MissingSectionHeaderError(fpname, lineno, line)
ConfigParser.MissingSectionHeaderError: File contains no section headers.
file: /projects/tmp/numpy-1.5.1/site.cfg, line: 60
'library_dirs = /usr/local/lib\n'
The relevant lines in my site.cfg file:
I think you just need to uncomment all the section headers that you
use, that`s what the exception says
library_dirs = /usr/local/lib
include_dirs = /usr/local/include
[blas_opt]
libraries = f77blas, cblas, atlas
[lapack_opt]
libraries = lapack, f77blas, cblas, atlas
Josef
I have installed BLAS+LAPACK+ATLAS libraries under /usr/local/lib/atlas
I also installed UMFPACK+AMD+UFConfig+CHOLMOD
I would appreciate any comments. I'm stuck here :(
Best regards,
Jose M. Borreguero
Below is the full error traceback:
$ /usr/local/bin/python2.7 setup.py build
Running from numpy source directory.F2PY Version 1
Traceback (most recent call last):
File setup.py, line 211, in module
setup_package()
File setup.py, line 204, in setup_package
configuration=configuration )
File /projects/tmp/numpy-1.5.1/numpy/distutils/core.py, line 152, in
setup
config = configuration()
File setup.py, line 151, in configuration
config.add_subpackage('numpy')
File /projects/tmp/numpy-1.5.1/numpy/distutils/misc_util.py, line
972,
in add_subpackage
caller_level = 2)
File /projects/tmp/numpy-1.5.1/numpy/distutils/misc_util.py, line
941,
in get_subpackage
caller_level = caller_level + 1)
File /projects/tmp/numpy-1.5.1/numpy/distutils/misc_util.py, line
878,
in _get_configuration_from_setup_py
config = setup_module.configuration(*args)
File numpy/setup.py, line 9, in configuration
config.add_subpackage('core')
File /projects/tmp/numpy-1.5.1/numpy/distutils/misc_util.py, line
972,
in add_subpackage
caller_level = 2)
File /projects/tmp/numpy-1.5.1/numpy/distutils/misc_util.py, line
941,
in get_subpackage
caller_level = caller_level + 1)
File /projects/tmp/numpy-1.5.1/numpy/distutils/misc_util.py, line
878,
in _get_configuration_from_setup_py
config = setup_module.configuration(*args)
File numpy/core/setup.py, line 807, in configuration
blas_info = get_info('blas_opt',0)
File /projects/tmp/numpy-1.5.1/numpy/distutils/system_info.py, line
310,
in get_info
return cl().get_info(notfound_action)
File /projects/tmp/numpy-1.5.1/numpy/distutils/system_info.py, line
409,
in __init__
self.parse_config_files()
File /projects/tmp/numpy-1.5.1/numpy/distutils/system_info.py, line
416,
in parse_config_files
self.cp.read(self.files)
File /usr/local/lib/python2.7/ConfigParser.py, line 297, in read
self._read(fp, filename)
File /usr/local/lib/python2.7/ConfigParser.py, line 504, in _read
raise MissingSectionHeaderError(fpname, lineno, line)
ConfigParser.MissingSectionHeaderError: File contains no section headers.
file: /projects/tmp/numpy-1.5.1/site.cfg, line: 60
'library_dirs = /usr/local/lib\n'
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Re: [Numpy-discussion] Fortran was dead ... [was Re:rewriting NumPy code in C or C++ or similar]
On Wed, Mar 16, 2011 at 17:46, Dag Sverre Seljebotn d.s.seljeb...@astro.uio.no wrote: On 03/16/2011 10:14 PM, william ratcliff wrote: Related to this, what is the status of fwrap? Can it be used with fortran 95/2003 language features? There is a rather large code crystallographic codebase (fullprof) that is written in fortran 77 that the author has been porting to fortran 95/2003 and actually using modules for. I'd like to write python bindings for it to make it more scriptable... Fwrap 0.1.1 is out; it supports a subset of Fortran 95/2003, biggest limitation being modules not being present. Since then there's been quite a few unreleased improvements (like a much better and more flexible build based on waf instead of distutils). Does Fwrap support SCons? I use SCons everywhere :) Building binaries with distutil is annoying to me, and that's one of the reasons for me to stop using f2py. I am very interested in interfacing binaries with Python. I also started a thread for this topic at Convore: https://convore.com/python-scientific-computing/mixing-languages-with-python/ . For those who might not know, as a result of discussion at the recent PyCon scientific computing BOF, some people started an initiative for an online scientific community focusing on broader application of Python, not specifically to any Python package such as NumPy or SciPy. The Convore group is an early attempt. You can find some context in the following threads: https://convore.com/python-scientific-computing/my-domainspecialty-of-scientific-computing-doesnt-have-a-community/ and https://convore.com/python-scientific-computing/a-scientific-community-using-python/ . yyc I'm currently working on module support. Or, was ... I've put in a week this month, but then some simulation results grabbed my attention and I got derailed. Finishing up module support and making an Fwrap 0.2 release is #2 on my stack of things to work on, and once I get around to it I expect it to take about a week. So I think it will happen :-) If you (or anyone else) want to get involved and put in a day or two to help with polishing (command line interface, writing tests, documentation...) just email me. Dag Sverre ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion -- Yung-Yu Chen PhD candidate of Mechanical Engineering The Ohio State University, Columbus, Ohio +1 (614) 859 2436 http://solvcon.net/yyc/ ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Fortran was dead ... [was Re:rewriting NumPy code in C or C++ or similar]
On 03/17/2011 03:23 PM, Yung-Yu Chen wrote: On Wed, Mar 16, 2011 at 17:46, Dag Sverre Seljebotn d.s.seljeb...@astro.uio.no mailto:d.s.seljeb...@astro.uio.no wrote: On 03/16/2011 10:14 PM, william ratcliff wrote: Related to this, what is the status of fwrap? Can it be used with fortran 95/2003 language features? There is a rather large code crystallographic codebase (fullprof) that is written in fortran 77 that the author has been porting to fortran 95/2003 and actually using modules for. I'd like to write python bindings for it to make it more scriptable... Fwrap 0.1.1 is out; it supports a subset of Fortran 95/2003, biggest limitation being modules not being present. Since then there's been quite a few unreleased improvements (like a much better and more flexible build based on waf instead of distutils). Does Fwrap support SCons? I use SCons everywhere :) The current focus is on waf only. But support can mean a lot. Fwrap really simply generate .h, .f90 and .pyx files (the latter being Cython sources, which Cython use to generate .c sources). Oh, and there's also a small probe script that tries to probe whether a Fortran real*8 really is a iso_c_binding c_double, and generates some headers. So when I say we support waf, what is meant is we ship a default build system which makes it convenient to build the results of using Fwrap and/or invoke Fwrap on the fly. So supporting scons is certainly a possibility. Last time I checked the Fortran tools in waf were significantly better though (as a result of Kurt's Fwrap work, I believe). Myself I'll be migrating a project from scons to waf any day now. Since the numscons effort died/failed it just seems more promising for Python packaging (see Bento). Dag Sverre ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] avoid a line...
On 3/17/11 12:46 AM, eat wrote: I am try to read a file of the following format, I want to avoid the first line and read the remaining as 'float' . Please help me... RainWindTempPrSal 0.11.10.020.2 0.2 0.50. 0. 0.4 0.8 0.55.51.50.5 1.5 It's not as robust, but if performance matters, fromfile() should be faster: f.readline() # to skip the first line arr = np.fromfile(f, sep=' ', dtype=np.float64).reshape((-1, 5)) (untested) -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
[Numpy-discussion] ImportError: libatlas.so: cannot open shared object file: No such file or directory
Dear Numpy/Scipy users, I just installed numpy but I have an error when importing import numpy from numpy.linalg import lapack_lite ImportError: libatlas.so: cannot open shared object file: No such file or directory I have ATLAS libraries under /usr/local/atlas/lib libatlas.a libcblas.a libf77blas.a liblapack.a libptcblas.a libptf77blas.a libatlas.so libcblas.so libf77blas.so liblapack.so libptcblas.so libptf77blas.so Aso the header files in /usr/local/atlas/include This was my site.cfg file: [DEFAULT] library_dirs = /usr/local/atlas/lib include_dirs = /usr/local/atlas/include [blas_opt] libraries = ptf77blas, ptcblas, atlas [lapack_opt] libraries = lapack, ptf77blas, ptcblas, atlas This is the full Traceback: import numpy Traceback (most recent call last): File stdin, line 1, in module File /usr/local/lib/python2.7/site-packages/numpy/__init__.py, line 136, in module import add_newdocs File /usr/local/lib/python2.7/site-packages/numpy/add_newdocs.py, line 9, in module from numpy.lib import add_newdoc File /usr/local/lib/python2.7/site-packages/numpy/lib/__init__.py, line 13, in module from polynomial import * File /usr/local/lib/python2.7/site-packages/numpy/lib/polynomial.py, line 17, in module from numpy.linalg import eigvals, lstsq File /usr/local/lib/python2.7/site-packages/numpy/linalg/__init__.py, line 48, in module from linalg import * File /usr/local/lib/python2.7/site-packages/numpy/linalg/linalg.py, line 23, in module from numpy.linalg import lapack_lite ImportError: libatlas.so: cannot open shared object file: No such file or directory I don't understand why libatlas.so cannot be found. Please, any comments are welcomed! Jose M. Borreguero ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] ImportError: libatlas.so: cannot open shared object file: No such file or directory
It looks like atlas wasn't linked right. If you /usr/local/atlas/lib to your LIBRARY_PATH environment variable it should work. - Ilan On Thu, Mar 17, 2011 at 12:23 PM, Jose Borreguero borregu...@gmail.com wrote: Dear Numpy/Scipy users, I just installed numpy but I have an error when importing import numpy from numpy.linalg import lapack_lite ImportError: libatlas.so: cannot open shared object file: No such file or directory I have ATLAS libraries under /usr/local/atlas/lib libatlas.a libcblas.a libf77blas.a liblapack.a libptcblas.a libptf77blas.a libatlas.so libcblas.so libf77blas.so liblapack.so libptcblas.so libptf77blas.so Aso the header files in /usr/local/atlas/include This was my site.cfg file: [DEFAULT] library_dirs = /usr/local/atlas/lib include_dirs = /usr/local/atlas/include [blas_opt] libraries = ptf77blas, ptcblas, atlas [lapack_opt] libraries = lapack, ptf77blas, ptcblas, atlas This is the full Traceback: import numpy Traceback (most recent call last): File stdin, line 1, in module File /usr/local/lib/python2.7/site-packages/numpy/__init__.py, line 136, in module import add_newdocs File /usr/local/lib/python2.7/site-packages/numpy/add_newdocs.py, line 9, in module from numpy.lib import add_newdoc File /usr/local/lib/python2.7/site-packages/numpy/lib/__init__.py, line 13, in module from polynomial import * File /usr/local/lib/python2.7/site-packages/numpy/lib/polynomial.py, line 17, in module from numpy.linalg import eigvals, lstsq File /usr/local/lib/python2.7/site-packages/numpy/linalg/__init__.py, line 48, in module from linalg import * File /usr/local/lib/python2.7/site-packages/numpy/linalg/linalg.py, line 23, in module from numpy.linalg import lapack_lite ImportError: libatlas.so: cannot open shared object file: No such file or directory I don't understand why libatlas.so cannot be found. Please, any comments are welcomed! Jose M. Borreguero ___ 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] ImportError: libatlas.so: cannot open shared object file: No such file or directory
Unfortunately it didn't work. I did: export LIBRARY_PATH=$LIBRARY_PATH:/usr/local/atlas/lib python setup.py build python setup.py install Then in another terminal export LIBRARY_PATH=$LIBRARY_PATH:/usr/local/atlas/lib python import numpy ... from numpy.linalg import lapack_lite ImportError: libatlas.so: cannot open shared object file: No such file or directory However, I used a different environment variable: export LD_LIBRARY_PATH=/usr/local/atlas/lib python import numpy ... from numpy.linalg import lapack_lite ImportError: libifport.so.5: cannot open shared object file: No such file or directory I located libifport.so.5 and added the directory to LD_LIBRARY_PATH: export LD_LIBRARY_PATH=/usr/local/atlas/lib:/opt/intel/Compiler/11.1/069/lib/ia32 python import numpy ... from numpy.linalg import lapack_lite from numpy.linalg import lapack_lite ImportError: /usr/local/lib/python2.7/site-packages/numpy/linalg/lapack_lite.so: undefined symbol: _gfortran_concat_string I googled this error, I found some comments on mixing fortran compilers. I haven't advance much because go from error to error. Maybe I'm mixing things up by adding directories to LD_LIBRARY_PATH :( Jose On Thu, Mar 17, 2011 at 1:35 PM, Ilan Schnell ischn...@enthought.comwrote: It looks like atlas wasn't linked right. If you /usr/local/atlas/lib to your LIBRARY_PATH environment variable it should work. - Ilan On Thu, Mar 17, 2011 at 12:23 PM, Jose Borreguero borregu...@gmail.com wrote: Dear Numpy/Scipy users, I just installed numpy but I have an error when importing import numpy from numpy.linalg import lapack_lite ImportError: libatlas.so: cannot open shared object file: No such file or directory I have ATLAS libraries under /usr/local/atlas/lib libatlas.a libcblas.a libf77blas.a liblapack.a libptcblas.a libptf77blas.a libatlas.so libcblas.so libf77blas.so liblapack.so libptcblas.so libptf77blas.so Aso the header files in /usr/local/atlas/include This was my site.cfg file: [DEFAULT] library_dirs = /usr/local/atlas/lib include_dirs = /usr/local/atlas/include [blas_opt] libraries = ptf77blas, ptcblas, atlas [lapack_opt] libraries = lapack, ptf77blas, ptcblas, atlas This is the full Traceback: import numpy Traceback (most recent call last): File stdin, line 1, in module File /usr/local/lib/python2.7/site-packages/numpy/__init__.py, line 136, in module import add_newdocs File /usr/local/lib/python2.7/site-packages/numpy/add_newdocs.py, line 9, in module from numpy.lib import add_newdoc File /usr/local/lib/python2.7/site-packages/numpy/lib/__init__.py, line 13, in module from polynomial import * File /usr/local/lib/python2.7/site-packages/numpy/lib/polynomial.py, line 17, in module from numpy.linalg import eigvals, lstsq File /usr/local/lib/python2.7/site-packages/numpy/linalg/__init__.py, line 48, in module from linalg import * File /usr/local/lib/python2.7/site-packages/numpy/linalg/linalg.py, line 23, in module from numpy.linalg import lapack_lite ImportError: libatlas.so: cannot open shared object file: No such file or directory I don't understand why libatlas.so cannot be found. Please, any comments are welcomed! Jose M. Borreguero ___ 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] hashing dtypes, new variation, old theme
On Wed, Mar 16, 2011 at 15:21, Mark Wiebe mwwi...@gmail.com wrote:
That sounds like a good fix to me. Whenever objects compare equal, they
should hash to the same value.
There is a limit to how far we can actually satisfy this requirement.
For the implementation of np.dtype.__eq__(), we coerce the other
argument to a dtype object.
[~]
|1 np.dtype(int) == int
True
[~]
|2 np.dtype(int) == 'i4'
True
[~]
|3 hash(int) != hash('i4')
True
As long as we define np.dtype.__eq__() in that way, we cannot satisfy
the requirement. The best we can do is make sure that for all true
dtype objects, if they compare equal then they hash equal. So you
could make a well-behaved dict with true dtypes as keys, but not
dtypes and dtype-coercable objects.
--
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] hashing dtypes, new variation, old theme
On Thu, Mar 17, 2011 at 2:35 PM, Robert Kern robert.k...@gmail.com wrote:
On Wed, Mar 16, 2011 at 15:21, Mark Wiebe mwwi...@gmail.com wrote:
That sounds like a good fix to me. Whenever objects compare equal, they
should hash to the same value.
There is a limit to how far we can actually satisfy this requirement.
For the implementation of np.dtype.__eq__(), we coerce the other
argument to a dtype object.
[~]
|1 np.dtype(int) == int
True
[~]
|2 np.dtype(int) == 'i4'
True
[~]
|3 hash(int) != hash('i4')
True
As long as we define np.dtype.__eq__() in that way, we cannot satisfy
the requirement. The best we can do is make sure that for all true
dtype objects, if they compare equal then they hash equal. So you
could make a well-behaved dict with true dtypes as keys, but not
dtypes and dtype-coercable objects.
Dtypes being mutable looks like a serious bug to me, it's violating the
definition of 'hashable' given here:
http://docs.python.org/glossary.html#term-hashable. This can be used to make
an impossible situation:
t = np.dtype('i4,i4')
d = {t : 3}
t.names = ('a','b')
d[t] = 4
d
{dtype([('a', 'i4'), ('b', 'i4')]): 3, dtype([('a', 'i4'), ('b',
'i4')]): 4}
-Mark
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[Numpy-discussion] Nonzero behaving strangely?
Hello all, I am new to Numpy. I used to program before in matlab and am getting used to Numpy. I have a array like: res array([[ 33.35053669, 49.4615004 , 44.27631299, 1., 2. ], [ 32.84263059, 50.24752036, 43.92291659, 1., 0. ], [ 33.68999668, 48.90554673, 43.51746687, 1., 0. ], [ 34.11564931, 49.77487763, 44.83843076, 1., 0. ], [ 32.4641859 , 48.65469145, 45.09300791, 1., 3. ], [ 32.15428526, 49.26922262, 45.92959026, 1., 0. ], [ 31.23860825, 48.21824628, 44.30816331, 1., 0. ], [ 30.71171138, 47.45600573, 44.9282456 , 1., 0. ], [ 30.53843426, 49.07713258, 44.20899822, 1., 0. ], [ 31.54722284, 47.61953925, 42.95235178, 1., 0. ], [ 32.44334635, 48.10500653, 42.51103537, 1., 0. ], [ 31.77269609, 46.53603145, 43.06468455, 1., 0. ], [ 30.1820843 , 47.80819604, 41.77667819, 1., 0. ], [ 30.78652668, 46.82907769, 40.38586451, 1., 0. ], [ 30.05963091, 46.84268609, 39.54583693, 1., 0. ], [ 31.75239177, 47.22768463, 40.00717713, 1., 0. ], [ 30.94617127, 45.76986265, 40.68226643, 1., 0. ], [ 33.20069679, 47.42127403, 45.66738249, 1., 0. ], [ 34.39608116, 47.25481126, 45.4438599 , 1., 0. ]]) The array is 19X5. When I do: nid = (res[:,4]==2).nonzero() nid tuple turns out to be empty. But the very first row satisfies the criteria. nid = (res[:,4]==3).nonzero(), works out and finds the 5th row. Am i doing something wrong? I basically want to find the rows whose fifth coloumn(4th in numpy matrix format) is 2. Any suggestions? Thanks Santhosh ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Nonzero behaving strangely?
Hi, Did you try np.where(res[:,4]==2) ? Matthieu 2011/3/17 santhu kumar mesan...@gmail.com Hello all, I am new to Numpy. I used to program before in matlab and am getting used to Numpy. I have a array like: res array([[ 33.35053669, 49.4615004 , 44.27631299, 1., 2. ], [ 32.84263059, 50.24752036, 43.92291659, 1., 0. ], [ 33.68999668, 48.90554673, 43.51746687, 1., 0. ], [ 34.11564931, 49.77487763, 44.83843076, 1., 0. ], [ 32.4641859 , 48.65469145, 45.09300791, 1., 3. ], [ 32.15428526, 49.26922262, 45.92959026, 1., 0. ], [ 31.23860825, 48.21824628, 44.30816331, 1., 0. ], [ 30.71171138, 47.45600573, 44.9282456 , 1., 0. ], [ 30.53843426, 49.07713258, 44.20899822, 1., 0. ], [ 31.54722284, 47.61953925, 42.95235178, 1., 0. ], [ 32.44334635, 48.10500653, 42.51103537, 1., 0. ], [ 31.77269609, 46.53603145, 43.06468455, 1., 0. ], [ 30.1820843 , 47.80819604, 41.77667819, 1., 0. ], [ 30.78652668, 46.82907769, 40.38586451, 1., 0. ], [ 30.05963091, 46.84268609, 39.54583693, 1., 0. ], [ 31.75239177, 47.22768463, 40.00717713, 1., 0. ], [ 30.94617127, 45.76986265, 40.68226643, 1., 0. ], [ 33.20069679, 47.42127403, 45.66738249, 1., 0. ], [ 34.39608116, 47.25481126, 45.4438599 , 1., 0. ]]) The array is 19X5. When I do: nid = (res[:,4]==2).nonzero() nid tuple turns out to be empty. But the very first row satisfies the criteria. nid = (res[:,4]==3).nonzero(), works out and finds the 5th row. Am i doing something wrong? I basically want to find the rows whose fifth coloumn(4th in numpy matrix format) is 2. Any suggestions? Thanks Santhosh ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion -- Information System Engineer, Ph.D. Blog: http://matt.eifelle.com LinkedIn: http://www.linkedin.com/in/matthieubrucher ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] hashing dtypes, new variation, old theme
On 3/17/11 2:57 PM, Mark Wiebe wrote: Dtypes being mutable looks like a serious bug to me, it's violating the definition of 'hashable' given here: I can imagine other problems is would cause, as well -- is there any reason that dtypes should be mutable? -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] Nonzero behaving strangely?
On Thu, Mar 17, 2011 at 5:17 PM, santhu kumar mesan...@gmail.com wrote: Hello all, I am new to Numpy. I used to program before in matlab and am getting used to Numpy. I have a array like: res array([[ 33.35053669, 49.4615004 , 44.27631299, 1., 2. ], [ 32.84263059, 50.24752036, 43.92291659, 1., 0. ], [ 33.68999668, 48.90554673, 43.51746687, 1., 0. ], [ 34.11564931, 49.77487763, 44.83843076, 1., 0. ], [ 32.4641859 , 48.65469145, 45.09300791, 1., 3. ], [ 32.15428526, 49.26922262, 45.92959026, 1., 0. ], [ 31.23860825, 48.21824628, 44.30816331, 1., 0. ], [ 30.71171138, 47.45600573, 44.9282456 , 1., 0. ], [ 30.53843426, 49.07713258, 44.20899822, 1., 0. ], [ 31.54722284, 47.61953925, 42.95235178, 1., 0. ], [ 32.44334635, 48.10500653, 42.51103537, 1., 0. ], [ 31.77269609, 46.53603145, 43.06468455, 1., 0. ], [ 30.1820843 , 47.80819604, 41.77667819, 1., 0. ], [ 30.78652668, 46.82907769, 40.38586451, 1., 0. ], [ 30.05963091, 46.84268609, 39.54583693, 1., 0. ], [ 31.75239177, 47.22768463, 40.00717713, 1., 0. ], [ 30.94617127, 45.76986265, 40.68226643, 1., 0. ], [ 33.20069679, 47.42127403, 45.66738249, 1., 0. ], [ 34.39608116, 47.25481126, 45.4438599 , 1., 0. ]]) The array is 19X5. When I do: nid = (res[:,4]==2).nonzero() nid tuple turns out to be empty. But the very first row satisfies the criteria. nid = (res[:,4]==3).nonzero(), works out and finds the 5th row. Am i doing something wrong? I basically want to find the rows whose fifth coloumn(4th in numpy matrix format) is 2. Are you sure the value of res[0,4] is *exactly* 2.0, and not something like, say, 2.0009? Warren Any suggestions? Thanks Santhosh ___ 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] hashing dtypes, new variation, old theme
Thu, 17 Mar 2011 15:23:19 -0700, Christopher Barker wrote: On 3/17/11 2:57 PM, Mark Wiebe wrote: Dtypes being mutable looks like a serious bug to me, it's violating the definition of 'hashable' given here: I can imagine other problems is would cause, as well -- is there any reason that dtypes should be mutable? Changing field names via the `names` attribute. AFAIK, the other attributes in dtypes are not mutable, and mutability was added long ago as a workaround for `.view()` not handling name changes properly. There's possibly some code out there that touches the `names` attribute, so it's not clear if this can be fixed in the 1.x series. -- Pauli Virtanen ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Nonzero behaving strangely?
On 3/17/11 3:17 PM, santhu kumar wrote: nid = (res[:,4]==2).nonzero() nid tuple turns out to be empty. But the very first row satisfies the criteria. it works for me: In [45]: arr Out[45]: array([[ 33.35053669, 49.4615004 , 44.27631299, 1., 2. ], [ 32.84263059, 50.24752036, 43.92291659, 1., 0. ], [ 33.68999668, 48.90554673, 43.51746687, 1., 0. ], [ 34.11564931, 49.77487763, 44.83843076, 1., 0. ], [ 32.4641859 , 48.65469145, 45.09300791, 1., 3. ], [ 32.15428526, 49.26922262, 45.92959026, 1., 0. ], [ 31.23860825, 48.21824628, 44.30816331, 1., 0. ], [ 30.71171138, 47.45600573, 44.9282456 , 1., 0. ], [ 30.53843426, 49.07713258, 44.20899822, 1., 0. ], [ 31.54722284, 47.61953925, 42.95235178, 1., 0. ], [ 32.44334635, 48.10500653, 42.51103537, 1., 0. ], [ 31.77269609, 46.53603145, 43.06468455, 1., 0. ], [ 30.1820843 , 47.80819604, 41.77667819, 1., 0. ], [ 30.78652668, 46.82907769, 40.38586451, 1., 0. ], [ 30.05963091, 46.84268609, 39.54583693, 1., 0. ], [ 31.75239177, 47.22768463, 40.00717713, 1., 0. ], [ 30.94617127, 45.76986265, 40.68226643, 1., 0. ], [ 33.20069679, 47.42127403, 45.66738249, 1., 0. ], [ 34.39608116, 47.25481126, 45.4438599 , 1., 0. ]]) In [46]: arr.shape Out[46]: (19, 5) In [47]: nid = (arr[:,4]==2).nonzero() In [48]: nid Out[48]: (array([0]),) Maybe you are having a floating point comparison problem -- i.e.e that 2.0 is really 1.99 or something. Checking equality with floating point numbers is fraught with problems. Also, y9ou amy not need teh nonzero: In [56]: arr[:,4]==2 Out[56]: array([ True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False], dtype=bool) that's a boolean array that can be used for indexing, operating with where, etc. HTH, -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] hashing dtypes, new variation, old theme
On Thu, Mar 17, 2011 at 3:30 PM, Pauli Virtanen p...@iki.fi wrote: Thu, 17 Mar 2011 15:23:19 -0700, Christopher Barker wrote: On 3/17/11 2:57 PM, Mark Wiebe wrote: Dtypes being mutable looks like a serious bug to me, it's violating the definition of 'hashable' given here: I can imagine other problems is would cause, as well -- is there any reason that dtypes should be mutable? Changing field names via the `names` attribute. AFAIK, the other attributes in dtypes are not mutable, and mutability was added long ago as a workaround for `.view()` not handling name changes properly. There's possibly some code out there that touches the `names` attribute, so it's not clear if this can be fixed in the 1.x series. Fixing ticket #1619 looks like it needs changes to dtype construction and __repr__, probably all these things should be fixed together at once. I agree they likely have too many ripple effects to change for 1.6. -Mark ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Nonzero behaving strangely?
Thanks a lot for the replies. I have misunderstood the output. When it says (array[0]), i thought it did not find anything as opposed to the zeroth row. (Still getting used to matlab indexing i guess !! ) .. Sorry !! Thanks a lot for the sugestions though, Would keep it in mind .. From: santhu kumar mesan...@gmail.com Subject: [Numpy-discussion] Nonzero behaving strangely? To: numpy-discussion@scipy.org Message-ID: aanlktinnfb6cbrudb3guaqsmcoq0dkywqy77j9hmm...@mail.gmail.com Content-Type: text/plain; charset=iso-8859-1 Hello all, I am new to Numpy. I used to program before in matlab and am getting used to Numpy. I have a array like: res array([[ 33.35053669, 49.4615004 , 44.27631299, 1., 2. ], [ 32.84263059, 50.24752036, 43.92291659, 1., 0. ], [ 33.68999668, 48.90554673, 43.51746687, 1., 0. ], [ 34.11564931, 49.77487763, 44.83843076, 1., 0. ], [ 32.4641859 , 48.65469145, 45.09300791, 1., 3. ], [ 32.15428526, 49.26922262, 45.92959026, 1., 0. ], [ 31.23860825, 48.21824628, 44.30816331, 1., 0. ], [ 30.71171138, 47.45600573, 44.9282456 , 1., 0. ], [ 30.53843426, 49.07713258, 44.20899822, 1., 0. ], [ 31.54722284, 47.61953925, 42.95235178, 1., 0. ], [ 32.44334635, 48.10500653, 42.51103537, 1., 0. ], [ 31.77269609, 46.53603145, 43.06468455, 1., 0. ], [ 30.1820843 , 47.80819604, 41.77667819, 1., 0. ], [ 30.78652668, 46.82907769, 40.38586451, 1., 0. ], [ 30.05963091, 46.84268609, 39.54583693, 1., 0. ], [ 31.75239177, 47.22768463, 40.00717713, 1., 0. ], [ 30.94617127, 45.76986265, 40.68226643, 1., 0. ], [ 33.20069679, 47.42127403, 45.66738249, 1., 0. ], [ 34.39608116, 47.25481126, 45.4438599 , 1., 0. ]]) The array is 19X5. When I do: nid = (res[:,4]==2).nonzero() nid tuple turns out to be empty. But the very first row satisfies the criteria. nid = (res[:,4]==3).nonzero(), works out and finds the 5th row. Am i doing something wrong? I basically want to find the rows whose fifth coloumn(4th in numpy matrix format) is 2. Any suggestions? Thanks Santhosh -- next part -- An HTML attachment was scrubbed... URL: http://mail.scipy.org/pipermail/numpy-discussion/attachments/20110317/2f46f2c1/attachment-0001.html -- Message: 2 Date: Thu, 17 Mar 2011 23:19:42 +0100 From: Matthieu Brucher matthieu.bruc...@gmail.com Subject: Re: [Numpy-discussion] Nonzero behaving strangely? To: Discussion of Numerical Python numpy-discussion@scipy.org Message-ID: aanlktimeipz6cpamauy2f_0mpjwkwjdwe0oc4wm-l...@mail.gmail.com Content-Type: text/plain; charset=iso-8859-1 Hi, Did you try np.where(res[:,4]==2) ? Matthieu 2011/3/17 santhu kumar mesan...@gmail.com Hello all, I am new to Numpy. I used to program before in matlab and am getting used to Numpy. I have a array like: res array([[ 33.35053669, 49.4615004 , 44.27631299, 1., 2. ], [ 32.84263059, 50.24752036, 43.92291659, 1., 0. ], [ 33.68999668, 48.90554673, 43.51746687, 1., 0. ], [ 34.11564931, 49.77487763, 44.83843076, 1., 0. ], [ 32.4641859 , 48.65469145, 45.09300791, 1., 3. ], [ 32.15428526, 49.26922262, 45.92959026, 1., 0. ], [ 31.23860825, 48.21824628, 44.30816331, 1., 0. ], [ 30.71171138, 47.45600573, 44.9282456 , 1., 0. ], [ 30.53843426, 49.07713258, 44.20899822, 1., 0. ], [ 31.54722284, 47.61953925, 42.95235178, 1., 0. ], [ 32.44334635, 48.10500653, 42.51103537, 1., 0. ], [ 31.77269609, 46.53603145, 43.06468455, 1., 0. ], [ 30.1820843 , 47.80819604, 41.77667819, 1., 0. ], [ 30.78652668, 46.82907769, 40.38586451, 1., 0. ], [ 30.05963091, 46.84268609, 39.54583693, 1., 0. ], [ 31.75239177, 47.22768463, 40.00717713, 1., 0. ], [ 30.94617127, 45.76986265, 40.68226643, 1., 0. ], [ 33.20069679, 47.42127403, 45.66738249, 1., 0. ], [ 34.39608116, 47.25481126, 45.4438599 , 1., 0. ]]) The array is 19X5. When I do: nid = (res[:,4]==2).nonzero() nid tuple turns out to be empty. But the very first row satisfies the criteria. nid = (res[:,4]==3).nonzero(), works out and finds the 5th row. Am i doing something wrong? I basically want to find the rows whose fifth coloumn(4th in numpy
Re: [Numpy-discussion] Norm of array of vectors
Hi eat and Gary, Thanks a lot for your suggestions, I've tried them in my code and achieved similar speedup of ~270% for both of them. So I guess I'll stick to one of those. Regards, Andrey. Hi, On Thu, Mar 17, 2011 at 10:44 AM, Andrey N. Sobolev inco...@list.ru wrote: Dear all, Sorry if that's a noob question, but anyway. I have several thousands of vectors stacked in 2d array. I'd like to get new array containing Euclidean norms of these vectors and get the vector with minimal norm. Is there more efficient way to do this than argmin(array([sqrt(dot(x,x)) for x in vec_array]))? Try argmin(sum(vec_array** 2, 0)** 0.5) Regards, eat Thanks in advance. Andrey. ___ 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] split() for slices?
Hello, I really like the split() family of functions, but I have the need to split multiple arrays in a similar manner, and it would seem logical to me to have a split() function that would return a list of slice tuples that I could use on multiple arrays. Is there such a function? Thanks, Ben Root ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
