Mailman 3 May 2009 - NumPy-Discussion

[review] py3k_bootstrap branch
by David Cournapeau 06 May '09

06 May '09

Hi, I spent some more time on making numpy.distutils runnable under python 3. I finally made up to the point where it breaks at C code compilation, so we can start working on the hard part. The branch is there for review http://github.com/cournape/numpy/commits/py3k_bootstrap The code is quite ugly to be honest, but I have not found a better way; suggestions are welcomed. The biggest pain is by far exception catching (you can't do except IOError, e in python 3), and then print. Most other things can be handled by careful application of 2to3 with the fixers which keep python2 compatibility (print is unfortunately not one of them). There are also a few python 3.* bugs in distutils (I guess few C-based extensions made it for python 3 already). The rationale for making numpy.distutils runnable under both python2 and python3 (instead of just applying 2to3 on it): - it enables us to bootstrap our build process through the distutils 2to3 command (which is supposed to convert code to python 3 from python 2 sources on the fly). - The few informations I found on non trivial port all made sure their setup.py was python 2 and 3 compatible - which means numpy.distutils for us. - 2to3 is very slow (takes 5 minutes for me on numpy), so having to apply it every time from pristine source for python 3 support would be very painful IMHO. cheers, David

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difficult optimization problem
by Mathew Yeates 06 May '09

06 May '09

Hi I'm trying to solve an optimization problem where the search domain is limited. Suppose I want to minimize the function f(x,y) but f(x,y) is only valid over a subset (unknown without calling f) of (x,y)? I tried looking at OpenOpt but ... kind of unusable without some documentation. Thanks Mathew

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Re: [Numpy-discussion] How to convert a list into a structured array?
by Wei Su 06 May '09

06 May '09

Hi, Stephen: This is fantastic. I shall read your codes carefully next week. (I am taking the rest of the week off for vacation.) Hopefully I am not so dumb that I need to ask again. Regards, Wei Su --- On Wed, 5/6/09, Stephen Simmons <mail(a)stevesimmons.com> wrote: From: Stephen Simmons <mail(a)stevesimmons.com> Subject: Re: [Numpy-discussion] How to convert a list into a structured array? To: "Discussion of Numerical Python" <numpy-discussion(a)scipy.org> Date: Wednesday, May 6, 2009, 5:46 AM Wei Su wrote: Hi, Francesc: Thanks a lot for offering me help. My code is really simple as of now. ********************************************************************************** from pyodbc import * from rpy import * cnxn = connect('DRIVER={SQL Server};SERVER=srdata01\\sql2k5;DATABASE=Qai;UID=;PWD=') cursor = cnxn.cursor() cursor.execute("select IsrCode, MstrName from qai..qaiLinkBase") data = cursor.fetchall() cursor.close() *************************************************** The result, data, I got from the above code tends to be a giant list, which is very hard to handle. My goal is to to turn it into a record array so that i can access the field directly by name or by index. My data is typically numerical, character and datetime variables. no other complications. >From the above code, you can also see that I used R for some time. But I have to switch to something else because I sometimes cannot even download all my data via R due to its memory limit under windows. I thought NumPy might be the solution. But I am not sure. Anybody can let me know whether Python has a memory limit? or can I use virtual memory by calling some Python module? Thanks in advance. Wei Su Hi Wei Su, Below is an example from the code I use to read text files into recarrays. The same approach can be used for your SQL data by redefining the inner iterator(path) function to execute your SQL query. If your data is really big, you could also use the PyTables package (written by Francesc actually) to store SQL extracts as numpy-compatible HDF tables. The HDF format can compress the data transparently, so the resulting data files are 1/10 the size of an equivalent text dump. You can then read any or all rows into memory for subsequent process using table.read[row_from, row_to], thereby avoiding running out of memory if your dataset is really big. PyTables/HDF is also really fast for reading. As an example, my three year old laptop with slow hard drive achieves up to 250,000 row per second speeds on GROUP BY-style subtotals. This uses PyTables for storing the data and numpy's bincount() function for doing the aggregation. Stephen def text_file_to_sorted_numpy_array(path, dtype, row_fn, max_rows=None, header=None, order_by=None, min_row_length=None): """ Read a database extract into a numpy recarray, which is possibly sorted then returned. path Path to the text file. dtype String giving column names and numpy data types e.g. 'COL1,S8 COL2,i4' row_fn Optional function splitting a row into a list that is compatible with the numpy array's dtype. The function can indicate the row should be skipped by returning None. If not given, the row has leading and trailing whitespace removed and then is split on '|'. order_by Optional list of column names used to sort the array. header Optional prefix for a header line. If given, there must be a line with this prefix within the first 20 lines. Any leading whitespace is removed before checking. max_rows Optional maximum number of rows that a file will contain. min_row_length Optional length of row in text file, used to estimate upper bound on size of final array. One or both of max_rows and min_row_length must be given. """ # Create a numpy array large enough to hold the entire file in memory if min_row_length: file_size = os.stat(path).st_size num_rows_upper_bound = file_size/min_row_length else: num_rows_upper_bound = max_rows if num_rows_upper_bound is None: raise ValueError('No information given about size of the final array') if max_rows and num_rows_upper_bound>max_rows: raise ValueError("'%s' is %d bytes long, too large to fit in memory" % (os.path.basename(path), file_size)) # Define an iterator that reads the data file def iterator(path): # Read the file with file(path, 'rU') as fh: ftype, prefix = os.path.splitext(os.path.basename(path))[0].split('-', 2) pb = ProgressBar(prefix=prefix) # Read the data lines ctr = idx = 0 for s in fh: s = s.strip() if s in ('\x1A', '-', '') or s.startswith('-------'): # Empty lines after end of real data continue res = row_fn(s) if res: yield res ctr+=1 if ctr%1000==0: total_rows = float(file_size*ctr)/float(fh.tell()) pb(ctr, total=total_rows) pb(ctr, last=True) # Create an empty array to hold all data, then fill in blocks of 5000 rows # Doing this by blocks is 4x faster than adding one row at a time.. dtype = list( tuple(x.split(',')) for x in dtype.split() ) arr = numpy.zeros(num_rows_upper_bound, dtype) def block_iterator(iterator, blk_size): "Group iterator into lists with blk_size elements" res = [] for i in iterator: res.append(i) if len(res)==blk_size: yield res res = [] if res: yield res # Now fill the array i = 0 try: for blk in block_iterator(iterator(path), 5000): b = len(blk) tmp = numpy.rec.fromrecords(blk, dtype=dtype, shape=b) arr[i:i+b] = tmp i+=b except KeyboardInterrupt: pass arr = arr[:i] # Remove unused rows at the end of the array # Sort array if required if order_by: print " Sorting %d-row array on %r" % (len(arr), order_by) arr.sort(order=order_by) # Return the final array return arr -----Inline Attachment Follows----- _______________________________________________ Numpy-discussion mailing list Numpy-discussion(a)scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion

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Re: [Numpy-discussion] How to convert a list into a structured array?
by Wei Su 06 May '09

06 May '09

Hi, Francesc: Thanks a lot for offering me help. My code is really simple as of now. ********************************************************************************** from pyodbc import * from rpy import * cnxn = connect('DRIVER={SQL Server};SERVER=srdata01\\sql2k5;DATABASE=Qai;UID=;PWD=') cursor = cnxn.cursor() cursor.execute("select IsrCode, MstrName from qai..qaiLinkBase") data = cursor.fetchall() cursor.close() *************************************************** The result, data, I got from the above code tends to be a giant list, which is very hard to handle. My goal is to to turn it into a record array so that i can access the field directly by name or by index. My data is typically numerical, character and datetime variables. no other complications. >From the above code, you can also see that I used R for some time. But I have to switch to something else because I sometimes cannot even download all my data via R due to its memory limit under windows. I thought NumPy might be the solution. But I am not sure. Anybody can let me know whether Python has a memory limit? or can I use virtual memory by calling some Python module? Thanks in advance. Wei Su --- On Tue, 5/5/09, Francesc Alted <faltet(a)pytables.org> wrote: From: Francesc Alted <faltet(a)pytables.org> Subject: Re: [Numpy-discussion] How to convert a list into a structured array? To: "Discussion of Numerical Python" <numpy-discussion(a)scipy.org> Date: Tuesday, May 5, 2009, 7:10 AM Welcome Wei! A Monday 04 May 2009, Wei Su escrigué: > Hi,All: > > My first post! I am very excited to find out structured array (record > array) in Python. Since I do data manipulation every day, this is > truly great. However, I typically download data using pyodbc, the > default output is a big list. So I am wondering how to convert that > big list into a structured array? using array() will turn it into a > text array, afaik. it is even better if anybody can show me some > tricks to download the data directly as a structured array. > Thanks a lot for the help. Please, could you provide an example of the list that you are getting from your database? With that we can probably figure out your needs much better. > BTW: I am also interested in Python's ability to handle large data. > Any hints or suggestion is welcome. This is also a bit generic question. What kind of data you have to deal with? What sort of operations do you want to perform over it? Do you need a lot of speed or flexibility is more important? Some example? Cheers, -- Francesc Alted "One would expect people to feel threatened by the 'giant brains or machines that think'. In fact, the frightening computer becomes less frightening if it is used only to simulate a familiar noncomputer." -- Edsger W. Dykstra "On the cruelty of really teaching computer science" _______________________________________________ Numpy-discussion mailing list Numpy-discussion(a)scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion

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array membership test?
by Mark Wendell 06 May '09

06 May '09

Is there a numpy equivalent of python's membership test (eg, "5 in [1,3,4,5]" returns True)? I'd like a quick way to test if a given number is in an array, without stepping through the elements individually. I realize this can be tricky with floats, but if there is such a thing for ints, that would be great. thanks Mark -- -- Mark Wendell

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cannot build numpy from trunk
by Nils Wagner 06 May '09

06 May '09

... In file included from numpy/core/src/multiarray/ctors.c:16, from numpy/core/src/multiarray/multiarraymodule_onefile.c:13: numpy/core/src/multiarray/ctors.h: At top level: numpy/core/src/multiarray/ctors.h:68: warning: conflicting types for byte_swap_vector numpy/core/src/multiarray/ctors.h:68: error: static declaration of byte_swap_vector follows non-static declaration numpy/core/src/multiarray/scalarapi.c:640: error: previous implicit declaration of byte_swap_vector was here error: Command "/usr/bin/gcc -fno-strict-aliasing -DNDEBUG -fmessage-length=0 -O2 -Wall -D_FORTIFY_SOURCE=2 -fstack-protector -funwind-tables -fasynchronous-unwind-tables -g -fwrapv -fPIC -Inumpy/core/include -Ibuild/src.linux-x86_64-2.6/numpy/core/include/numpy -Inumpy/core/src/multiarray -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6 -Ibuild/src.linux-x86_64-2.6/numpy/core/src/multiarray -Ibuild/src.linux-x86_64-2.6/numpy/core/src/umath -c numpy/core/src/multiarray/multiarraymodule_onefile.c -o build/temp.linux-x86_64-2.6/numpy/core/src/multiarray/multiarraymodule_onefile.o" failed with exit status 1 Nils

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error building numpy: no file refecount.c
by dmitrey 06 May '09

06 May '09

Hi all, I've got the error during building numpy from latest svn snapshot - any ideas? D. ... executing numpy/core/code_generators/generate_numpy_api.py adding 'build/src.linux-x86_64-2.6/numpy/core/include/numpy/ __multiarray_api.h' to sources. numpy.core - nothing done with h_files = ['build/src.linux-x86_64-2.6/ numpy/core/include/numpy/config.h', 'build/src.linux-x86_64-2.6/numpy/ core/include/numpy/numpyconfig.h', 'build/src.linux-x86_64-2.6/numpy/ core/include/numpy/__multiarray_api.h'] building extension "numpy.core.multiarray" sources error: src/multiarray/refecount.c: No such file or directory

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How to download data directly from SQL into NumPy as a record array or structured array.
by Wei Su 05 May '09

05 May '09

Hi, Everyone: This is what I need to do everyday. Now I have to first save data as .csv file and the use csv2rec() to read the data as a record array. Anybody can give me some advice on how to directly get the data as record arrays? It will save me tons of time. Thanks in advance. Wei Su

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Structured array with no fields - possible?
by Matthew Brett 05 May '09

05 May '09

Hello, I'm trying to fix a bug in the scipy matlab loading routines, and this requires me to somehow represent an empty structured array. In matlab this is: >> a = struct() In numpy, you can do this: In [1]: dt = np.dtype([]) but then you can't use it: In [2]: np.zeros((),dtype=dt) --------------------------------------------------------------------------- ValueError Traceback (most recent call last) /home/mb312/tmp/<ipython console> in <module>() ValueError: Empty data-type Is there any way of representing a structured / record array, but with no fields? Thanks for any thoughts, Matthew

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linalg.svd not working?
by Muhammad Alkarouri 05 May '09

05 May '09

Hi everyone, I have installed numpy 1.3.0 on Python 2.5.1 in an x86_64 machine, and it hangs when I do a numpy.test(verbose=10) on test_pinv (test_defmatrix.TestProperties) ... which I believe hangs on a call to numpy.linalg.svd. Can you please help me with this problem? The installation and configuration is probably a bit non-standard, so I am including the output of python -m numpy.distutils.system_info below. In particular, all the installation was done using CC='gcc -m32' to enforce 32 bit executables, as Python is a 32 bit executable here. Regards, Muhammad Alkarouri lapack_info: libraries lapack not found in /GWD/appbase/common/lib libraries lapack not found in /usr/local/lib FOUND: libraries = ['lapack'] library_dirs = ['/usr/lib'] language = f77 lapack_opt_info: lapack_mkl_info: mkl_info: libraries mkl,vml,guide not found in /GWD/appbase/common/lib libraries mkl,vml,guide not found in /usr/local/lib libraries mkl,vml,guide not found in /usr/lib NOT AVAILABLE NOT AVAILABLE atlas_threads_info: Setting PTATLAS=ATLAS libraries lapack_atlas not found in /users/d88/ma856388/lib __main__.atlas_threads_info Setting PTATLAS=ATLAS Setting PTATLAS=ATLAS FOUND: libraries = ['lapack', 'ptf77blas', 'ptcblas', 'atlas'] library_dirs = ['/users/d88/ma856388/lib'] language = f77 customize GnuFCompiler Found executable /usr/bin/g77 gnu: no Fortran 90 compiler found gnu: no Fortran 90 compiler found customize GnuFCompiler gnu: no Fortran 90 compiler found gnu: no Fortran 90 compiler found customize GnuFCompiler using config compiling '_configtest.c': /* This file is generated from numpy/distutils/system_info.py */ void ATL_buildinfo(void); int main(void) { ATL_buildinfo(); return 0; } C compiler: gcc -m32 -fno-strict-aliasing -DNDEBUG -g -O3 -Wall -Wstrict-prototypes -fPIC compile options: '-c' gcc: _configtest.c gcc -m32 _configtest.o -m32 -fPIC -L/users/d88/ma856388/lib -llapack -lptf77blas -lptcblas -latlas -o _configtest ATLAS version 3.8.3 built by ma856388 on Fri May 1 14:56:25 BST 2009: UNAME : Linux stvwolx028 2.6.9-22.ELsmp #1 SMP Mon Sep 19 18:00:54 EDT 2005 x86_64 x86_64 x86_64 GNU/Linux INSTFLG : -1 0 -a 1 ARCHDEFS : -DATL_OS_Linux -DATL_ARCH_P4E -DATL_CPUMHZ=3200 -DATL_SSE3 -DATL_SSE2 -DATL_SSE1 -DATL_GAS_x8632 F2CDEFS : -DAdd__ -DF77_INTEGER=int -DStringSunStyle CACHEEDGE: 8388608 F77 : g77, version GNU Fortran (GCC) 3.4.4 20050721 (Red Hat 3.4.4-2) F77FLAGS : -fomit-frame-pointer -mfpmath=387 -O2 -falign-loops=4 -fPIC -m32 -fPIC -m32 SMC : gcc, version gcc (GCC) 3.4.4 20050721 (Red Hat 3.4.4-2) SMCFLAGS : -fomit-frame-pointer -mfpmath=387 -O2 -falign-loops=4 -fPIC -m32 SKC : gcc, version gcc (GCC) 3.4.4 20050721 (Red Hat 3.4.4-2) SKCFLAGS : -fomit-frame-pointer -mfpmath=387 -O2 -falign-loops=4 -fPIC -m32 success! removing: _configtest.c _configtest.o _configtest FOUND: libraries = ['lapack', 'ptf77blas', 'ptcblas', 'atlas'] library_dirs = ['/users/d88/ma856388/lib'] language = f77 define_macros = [('ATLAS_INFO', '"\\"3.8.3\\""')] wx_info: Could not locate executable wx-config File not found: None. Cannot determine wx info. NOT AVAILABLE lapack_atlas_info: libraries lapack_atlas,f77blas,cblas,atlas not found in /users/d88/ma856388/lib libraries lapack_atlas not found in /users/d88/ma856388/lib libraries lapack_atlas,f77blas,cblas,atlas not found in /GWD/appbase/common/lib libraries lapack_atlas not found in /GWD/appbase/common/lib libraries lapack_atlas,f77blas,cblas,atlas not found in /usr/local/lib libraries lapack_atlas not found in /usr/local/lib libraries lapack_atlas,f77blas,cblas,atlas not found in /usr/lib/sse2 libraries lapack_atlas not found in /usr/lib/sse2 libraries lapack_atlas,f77blas,cblas,atlas not found in /usr/lib libraries lapack_atlas not found in /usr/lib __main__.lapack_atlas_info NOT AVAILABLE umfpack_info: libraries umfpack not found in /GWD/appbase/common/lib libraries umfpack not found in /usr/local/lib libraries umfpack not found in /usr/lib NOT AVAILABLE _pkg_config_info: Found executable /usr/bin/pkg-config NOT AVAILABLE lapack_atlas_threads_info: Setting PTATLAS=ATLAS libraries lapack_atlas,ptf77blas,ptcblas,atlas not found in /users/d88/ma856388/lib libraries lapack_atlas not found in /users/d88/ma856388/lib libraries lapack_atlas,ptf77blas,ptcblas,atlas not found in /GWD/appbase/common/lib libraries lapack_atlas not found in /GWD/appbase/common/lib libraries lapack_atlas,ptf77blas,ptcblas,atlas not found in /usr/local/lib libraries lapack_atlas not found in /usr/local/lib libraries lapack_atlas,ptf77blas,ptcblas,atlas not found in /usr/lib/sse2 libraries lapack_atlas not found in /usr/lib/sse2 libraries lapack_atlas,ptf77blas,ptcblas,atlas not found in /usr/lib libraries lapack_atlas not found in /usr/lib __main__.lapack_atlas_threads_info NOT AVAILABLE x11_info: FOUND: libraries = ['X11'] library_dirs = ['/usr/X11R6/lib'] blas_info: libraries blas not found in /GWD/appbase/common/lib libraries blas not found in /usr/local/lib FOUND: libraries = ['blas'] library_dirs = ['/usr/lib'] language = f77 fftw_info: libraries fftw3 not found in /GWD/appbase/common/lib libraries fftw3 not found in /usr/local/lib libraries fftw3 not found in /usr/lib fftw3 not found libraries rfftw,fftw not found in /GWD/appbase/common/lib libraries rfftw,fftw not found in /usr/local/lib libraries rfftw,fftw not found in /usr/lib fftw2 not found NOT AVAILABLE f2py_info: FOUND: sources = ['/users/d88/ma856388/lib/python/numpy/f2py/src/fortranobject.c'] include_dirs = ['/users/d88/ma856388/lib/python/numpy/f2py/src'] gdk_pixbuf_xlib_2_info: FOUND: libraries = ['gdk_pixbuf_xlib-2.0', 'gdk_pixbuf-2.0', 'm', 'gobject-2.0', 'gmodule-2.0', 'dl', 'glib-2.0'] extra_link_args = ['-Wl,--export-dynamic'] define_macros = [('GDK_PIXBUF_XLIB_2_INFO', '"\\"2.4.13\\""'), ('GDK_PIXBUF_XLIB_VERSION_2_4_13', None)] include_dirs = ['/usr/include/gtk-2.0', '/usr/include/glib-2.0', '/usr/lib64/glib-2.0/include'] dfftw_threads_info: libraries drfftw_threads,dfftw_threads not found in /GWD/appbase/common/lib libraries drfftw_threads,dfftw_threads not found in /usr/local/lib libraries drfftw_threads,dfftw_threads not found in /usr/lib dfftw threads not found NOT AVAILABLE atlas_blas_info: FOUND: libraries = ['f77blas', 'cblas', 'atlas'] library_dirs = ['/users/d88/ma856388/lib'] language = c fftw3_info: libraries fftw3 not found in /GWD/appbase/common/lib libraries fftw3 not found in /usr/local/lib libraries fftw3 not found in /usr/lib fftw3 not found NOT AVAILABLE blas_opt_info: blas_mkl_info: libraries mkl,vml,guide not found in /GWD/appbase/common/lib libraries mkl,vml,guide not found in /usr/local/lib libraries mkl,vml,guide not found in /usr/lib NOT AVAILABLE atlas_blas_threads_info: Setting PTATLAS=ATLAS Setting PTATLAS=ATLAS Setting PTATLAS=ATLAS FOUND: libraries = ['ptf77blas', 'ptcblas', 'atlas'] library_dirs = ['/users/d88/ma856388/lib'] language = c customize GnuFCompiler gnu: no Fortran 90 compiler found gnu: no Fortran 90 compiler found customize GnuFCompiler gnu: no Fortran 90 compiler found gnu: no Fortran 90 compiler found customize GnuFCompiler using config compiling '_configtest.c': /* This file is generated from numpy/distutils/system_info.py */ void ATL_buildinfo(void); int main(void) { ATL_buildinfo(); return 0; } C compiler: gcc -m32 -fno-strict-aliasing -DNDEBUG -g -O3 -Wall -Wstrict-prototypes -fPIC compile options: '-c' gcc: _configtest.c gcc -m32 _configtest.o -m32 -fPIC -L/users/d88/ma856388/lib -lptf77blas -lptcblas -latlas -o _configtest ATLAS version 3.8.3 built by ma856388 on Fri May 1 14:56:25 BST 2009: UNAME : Linux stvwolx028 2.6.9-22.ELsmp #1 SMP Mon Sep 19 18:00:54 EDT 2005 x86_64 x86_64 x86_64 GNU/Linux INSTFLG : -1 0 -a 1 ARCHDEFS : -DATL_OS_Linux -DATL_ARCH_P4E -DATL_CPUMHZ=3200 -DATL_SSE3 -DATL_SSE2 -DATL_SSE1 -DATL_GAS_x8632 F2CDEFS : -DAdd__ -DF77_INTEGER=int -DStringSunStyle CACHEEDGE: 8388608 F77 : g77, version GNU Fortran (GCC) 3.4.4 20050721 (Red Hat 3.4.4-2) F77FLAGS : -fomit-frame-pointer -mfpmath=387 -O2 -falign-loops=4 -fPIC -m32 -fPIC -m32 SMC : gcc, version gcc (GCC) 3.4.4 20050721 (Red Hat 3.4.4-2) SMCFLAGS : -fomit-frame-pointer -mfpmath=387 -O2 -falign-loops=4 -fPIC -m32 SKC : gcc, version gcc (GCC) 3.4.4 20050721 (Red Hat 3.4.4-2) SKCFLAGS : -fomit-frame-pointer -mfpmath=387 -O2 -falign-loops=4 -fPIC -m32 success! removing: _configtest.c _configtest.o _configtest FOUND: libraries = ['ptf77blas', 'ptcblas', 'atlas'] library_dirs = ['/users/d88/ma856388/lib'] language = c define_macros = [('ATLAS_INFO', '"\\"3.8.3\\""')] sfftw_info: libraries srfftw,sfftw not found in /GWD/appbase/common/lib libraries srfftw,sfftw not found in /usr/local/lib libraries srfftw,sfftw not found in /usr/lib sfftw not found NOT AVAILABLE xft_info: FOUND: libraries = ['Xft', 'X11', 'freetype', 'Xrender', 'fontconfig'] library_dirs = ['/usr/X11R6/lib64'] define_macros = [('XFT_INFO', '"\\"2.1.2.2\\""'), ('XFT_VERSION_2_1_2_2', None)] include_dirs = ['/usr/X11R6/include', '/usr/include/freetype2', '/usr/include/freetype2/config'] fft_opt_info: fftw2_info: libraries rfftw,fftw not found in /GWD/appbase/common/lib libraries rfftw,fftw not found in /usr/local/lib libraries rfftw,fftw not found in /usr/lib fftw2 not found NOT AVAILABLE dfftw_info: libraries drfftw,dfftw not found in /GWD/appbase/common/lib libraries drfftw,dfftw not found in /usr/local/lib libraries drfftw,dfftw not found in /usr/lib dfftw not found NOT AVAILABLE djbfft_info: NOT AVAILABLE NOT AVAILABLE gdk_x11_2_info: FOUND: libraries = ['gdk-x11-2.0', 'gdk_pixbuf-2.0', 'm', 'pangoxft-1.0', 'pangox-1.0', 'pango-1.0', 'gobject-2.0', 'gmodule-2.0', 'dl', 'glib-2.0'] extra_link_args = ['-Wl,--export-dynamic'] define_macros = [('GDK_X11_2_INFO', '"\\"2.4.13\\""'), ('GDK_X11_VERSION_2_4_13', None), ('XTHREADS', None), ('_REENTRANT', None), ('XUSE_MTSAFE_API', None)] include_dirs = ['/usr/include/gtk-2.0', '/usr/lib64/gtk-2.0/include', '/usr/X11R6/include', '/usr/include/pango-1.0', '/usr/include/freetype2', '/usr/include/freetype2/config', '/usr/include/glib-2.0', '/usr/lib64/glib-2.0/include'] agg2_info: NOT AVAILABLE numarray_info: NOT AVAILABLE blas_src_info: NOT AVAILABLE fftw_threads_info: libraries rfftw_threads,fftw_threads not found in /GWD/appbase/common/lib libraries rfftw_threads,fftw_threads not found in /usr/local/lib libraries rfftw_threads,fftw_threads not found in /usr/lib fftw threads not found NOT AVAILABLE _numpy_info: FOUND: define_macros = [('NUMERIC_VERSION', '"\\"23.8\\""'), ('NUMERIC', None)] gdk_info: FOUND: libraries = ['gdk', 'Xi', 'Xext', 'X11', 'm', 'glib'] library_dirs = ['/usr/X11R6/lib64'] define_macros = [('GDK_INFO', '"\\"1.2.10\\""'), ('GDK_VERSION_1_2_10', None)] include_dirs = ['/usr/include/gtk-1.2', '/usr/X11R6/include', '/usr/include/glib-1.2', '/usr/lib64/glib/include'] gtkp_x11_2_info: FOUND: libraries = ['gtk-x11-2.0', 'gdk-x11-2.0', 'atk-1.0', 'gdk_pixbuf-2.0', 'm', 'pangoxft-1.0', 'pangox-1.0', 'pango-1.0', 'gobject-2.0', 'gmodule-2.0', 'dl', 'glib-2.0'] extra_link_args = ['-Wl,--export-dynamic'] define_macros = [('GTKP_X11_2_INFO', '"\\"2.4.13\\""'), ('GTK_X11_VERSION_2_4_13', None), ('XTHREADS', None), ('_REENTRANT', None), ('XUSE_MTSAFE_API', None)] include_dirs = ['/usr/include/gtk-2.0', '/usr/lib64/gtk-2.0/include', '/usr/X11R6/include', '/usr/include/atk-1.0', '/usr/include/pango-1.0', '/usr/include/freetype2', '/usr/include/freetype2/config', '/usr/include/glib-2.0', '/usr/lib64/glib-2.0/include'] sfftw_threads_info: libraries srfftw_threads,sfftw_threads not found in /GWD/appbase/common/lib libraries srfftw_threads,sfftw_threads not found in /usr/local/lib libraries srfftw_threads,sfftw_threads not found in /usr/lib sfftw threads not found NOT AVAILABLE boost_python_info: NOT AVAILABLE freetype2_info: FOUND: libraries = ['freetype', 'z'] define_macros = [('FREETYPE2_INFO', '"\\"9.7.3\\""'), ('FREETYPE2_VERSION_9_7_3', None)] include_dirs = ['/usr/include/freetype2'] gdk_2_info: FOUND: libraries = ['gdk-x11-2.0', 'gdk_pixbuf-2.0', 'm', 'pangoxft-1.0', 'pangox-1.0', 'pango-1.0', 'gobject-2.0', 'gmodule-2.0', 'dl', 'glib-2.0'] extra_link_args = ['-Wl,--export-dynamic'] define_macros = [('GDK_2_INFO', '"\\"2.4.13\\""'), ('GDK_VERSION_2_4_13', None), ('XTHREADS', None), ('_REENTRANT', None), ('XUSE_MTSAFE_API', None)] include_dirs = ['/usr/include/gtk-2.0', '/usr/lib64/gtk-2.0/include', '/usr/X11R6/include', '/usr/include/pango-1.0', '/usr/include/freetype2', '/usr/include/freetype2/config', '/usr/include/glib-2.0', '/usr/lib64/glib-2.0/include'] lapack_src_info: NOT AVAILABLE gtkp_2_info: FOUND: libraries = ['gtk-x11-2.0', 'gdk-x11-2.0', 'atk-1.0', 'gdk_pixbuf-2.0', 'm', 'pangoxft-1.0', 'pangox-1.0', 'pango-1.0', 'gobject-2.0', 'gmodule-2.0', 'dl', 'glib-2.0'] extra_link_args = ['-Wl,--export-dynamic'] define_macros = [('GTKP_2_INFO', '"\\"2.4.13\\""'), ('GTK_VERSION_2_4_13', None), ('XTHREADS', None), ('_REENTRANT', None), ('XUSE_MTSAFE_API', None)] include_dirs = ['/usr/include/gtk-2.0', '/usr/lib64/gtk-2.0/include', '/usr/X11R6/include', '/usr/include/atk-1.0', '/usr/include/pango-1.0', '/usr/include/freetype2', '/usr/include/freetype2/config', '/usr/include/glib-2.0', '/usr/lib64/glib-2.0/include'] gdk_pixbuf_2_info: FOUND: libraries = ['gdk_pixbuf-2.0', 'm', 'gobject-2.0', 'gmodule-2.0', 'dl', 'glib-2.0'] extra_link_args = ['-Wl,--export-dynamic'] define_macros = [('GDK_PIXBUF_2_INFO', '"\\"2.4.13\\""'), ('GDK_PIXBUF_VERSION_2_4_13', None)] include_dirs = ['/usr/include/gtk-2.0', '/usr/include/glib-2.0', '/usr/lib64/glib-2.0/include'] amd_info: libraries amd not found in /GWD/appbase/common/lib libraries amd not found in /usr/local/lib libraries amd not found in /usr/lib NOT AVAILABLE atlas_info: libraries lapack_atlas not found in /users/d88/ma856388/lib __main__.atlas_info FOUND: libraries = ['lapack', 'f77blas', 'cblas', 'atlas'] library_dirs = ['/users/d88/ma856388/lib'] language = f77 Numeric_info: FOUND: define_macros = [('NUMERIC_VERSION', '"\\"23.8\\""'), ('NUMERIC', None)] numerix_info: numpy_info: FOUND: define_macros = [('NUMPY_VERSION', '"\\"1.3.0\\""'), ('NUMPY', None)] FOUND: define_macros = [('NUMPY_VERSION', '"\\"1.3.0\\""'), ('NUMPY', None)]

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