James,
Your code doesn't seem to work as expected:
$ python demo.py 10
Traceback (most recent call last):
File "demo.py", line 11, in <module>
f = autowrap(summation, args=(x,))
File
"/opt/jump/x86_64/Python-2.7.3/lib/python2.7/site-packages/sympy/utilities/autowrap.py",
line 387, in autowrap
routine = Routine('autofunc', expr, args)
File
"/opt/jump/x86_64/Python-2.7.3/lib/python2.7/site-packages/sympy/utilities/codegen.py",
line 229, in __init__
new_args.append(InputArgument(symbol))
File
"/opt/jump/x86_64/Python-2.7.3/lib/python2.7/site-packages/sympy/utilities/codegen.py",
line 350, in __init__
Variable.__init__(self, name, datatype, dimensions, precision)
File
"/opt/jump/x86_64/Python-2.7.3/lib/python2.7/site-packages/sympy/utilities/codegen.py",
line 300, in __init__
raise TypeError("The first argument must be a sympy symbol.")
TypeError: The first argument must be a sympy symbol.
It appears to me that sum(x) has type int.
On Thursday, September 25, 2014 7:52:12 PM UTC-5, James Crist wrote:
>
> I'd hazard that it's a limit in the internals of numpy for how they handle
> broadcasting, but I can't be certain on that.
>
> However, we can handle this, you just need to frame your problem in a
> better way. You're trying to do optimization, so generally you'd frame your
> optimal condition as a vector. In SymPy you should do the same (using a
> MatrixSymbol). You also don't need ufuncify, because you're not doing any
> broadcasting. Instead, you can use `autowrap` to create a function. ufuncs
> can't broadcast arrays, so ufuncify won't work for functions that require a
> vector as an input for a single iteration. The resulting expression will be
> just as fast as a ufunc for a single iteration though, so no harm done.
>
> Here's your toy example, done as described:
>
> import sympyfrom sympy.utilities.autowrap import autowrapimport sys
>
> N = int(sys.argv[1])
>
> x = sympy.MatrixSymbol('x', N, 1)
> summation = sum(x)
> values = list(range(N))
>
> f = autowrap(summation, args=(x,))print f(values)
>
>
> This works regardless of how large N is. For your real problem, you can
> formulate your expression using symbols, and use subs to form them into a
> single vector input. Or you can work directly with the vector by using
> elements of it as variables. It's up to you how to formulate it.
>
> -Jim
>
> On Thursday, September 25, 2014 6:55:31 PM UTC-5, Jason Moore wrote:
>>
>> I'm not saying that SymPy isn't well suited for this task. I'm just
>> saying that we don't have an implementation for code generation for
>> summations that would help with your problem. You could certainly add one.
>>
>> I use SymPy for optimization problems myself and generate the symbolic
>> Jacobians and Hessians of the objective and constraint functions for
>> non-linear programming problems and it works great. So SymPy can likely do
>> what you want to do, but you may need to write a code printer for sympy.Sum
>> or something similar.
>>
>>
>> Jason
>> moorepants.info
>> +01 530-601-9791
>>
>> On Thu, Sep 25, 2014 at 7:03 PM, David Shin <shin....@gmail.com> wrote:
>>
>>> Thanks for the info, Jason.
>>>
>>> In my opinion, what I am trying to do is not particularly exotic.
>>> Consider for example the task of implementing logistic regression
>>> optimization via sympy and scipy. You have an n-by-k data matrix X of
>>> independent variables, a length-n output vector Y of dependent variables,
>>> and wish to approximate each Y[i] as a function of X[i], parameterized by a
>>> set of k+1 parameters, theta. This boils down to writing an objective loss
>>> function to minimize, which is a symbolic function of theta involving n
>>> summands that are individually expressions in terms Y[i], X[i], and theta.
>>> As the minimum does not have an analytic solution, you need to employ
>>> approximation algorithms, hence scipy.optimize.
>>>
>>> Of course, there are numerous packages available for vanilla logistic
>>> regression. However, if you want to customize it (for example by using an
>>> alternative loss function or regularization penalty function), then you
>>> kind of need to roll out your own implementation.
>>>
>>> From what you are saying, it sounds like sympy is not well-suited for
>>> this type of task.
>>>
>>> On Thursday, September 25, 2014 5:31:27 PM UTC-5, Jason Moore wrote:
>>>>
>>>> I'm not sure this is supported. Ideally you'd create a sympy.Sum object
>>>> representing your summation and then the code printers would print a loop
>>>> that would look something like:
>>>>
>>>> >>> sum = sympy.Sum(a, (a, 1, 5))
>>>> >>> sympy.ccode(sum, b)
>>>> double b = 0;
>>>> for (i = 0; i < 5; i++;){
>>>> b = b + a[i]
>>>> }
>>>>
>>>> I think Jim Crist is working on this functionality but it doesn't exist
>>>> now.
>>>>
>>>>
>>>> Jason
>>>> moorepants.info
>>>> +01 530-601-9791
>>>>
>>>> On Thu, Sep 25, 2014 at 5:46 PM, David Shin <shin....@gmail.com> wrote:
>>>>
>>>>> The function is a sum of thousands of summands, where each summand is
>>>>> a small function of a few of the input parameters. These small summand
>>>>> functions are composed of basic operations like multiplication, addition,
>>>>> and exp().
>>>>>
>>>>> On Thursday, September 25, 2014 4:21:32 PM UTC-5, Jason Moore wrote:
>>>>>>
>>>>>> I see. What does your function look like? Does it have summations or
>>>>>> things you want to iterate over? Or is it simply a scalar function?
>>>>>>
>>>>>>
>>>>>> Jason
>>>>>> moorepants.info
>>>>>> +01 530-601-9791
>>>>>>
>>>>>> On Thu, Sep 25, 2014 at 5:09 PM, David Shin <shin....@gmail.com>
>>>>>> wrote:
>>>>>>
>>>>>>> Also, I'd like to pass in the gradient and hessian of my function
>>>>>>> into scipy.optimize.minimize() to help it along. I don't want to do the
>>>>>>> calculus by hand, so I'm using sympy to do it for me.
>>>>>>>
>>>>>>>
>>>>>>> On Thursday, September 25, 2014 4:08:02 PM UTC-5, David Shin wrote:
>>>>>>>>
>>>>>>>> I'm looking to minimize a complicated function of hundreds of
>>>>>>>> variables. I want to ufuncify() my function so that I can pass it into
>>>>>>>> scipy.optimize.minimize(). The summation func I gave is just a toy
>>>>>>>> example,
>>>>>>>> the actual function is much more complicated.
>>>>>>>>
>>>>>>>> Please let me know if I should be doing this some other way.
>>>>>>>>
>>>>>>>> On Thursday, September 25, 2014 4:00:04 PM UTC-5, Jason Moore wrote:
>>>>>>>>>
>>>>>>>>> First, why do you need sympy to do this? Would NumPy be sufficient?
>>>>>>>>>
>>>>>>>>> import numpy as np
>>>>>>>>> values = np.random.random(100)
>>>>>>>>> np.sum(values)
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> Jason
>>>>>>>>> moorepants.info
>>>>>>>>> +01 530-601-9791
>>>>>>>>>
>>>>>>>>> On Thu, Sep 25, 2014 at 4:52 PM, David Shin <shin....@gmail.com>
>>>>>>>>> wrote:
>>>>>>>>>
>>>>>>>>>> Would you mind showing me how to convert my demo.py to have
>>>>>>>>>> ufuncify generate code that has a single length-N array argument
>>>>>>>>>> instead of
>>>>>>>>>> N separate arguments?
>>>>>>>>>>
>>>>>>>>>> On Thursday, September 25, 2014 3:40:25 PM UTC-5, Jason Moore
>>>>>>>>>> wrote:
>>>>>>>>>>>
>>>>>>>>>>> It works for the backend='f2py' in master but fails for the
>>>>>>>>>>> default backend which is 'numpy'. I get a segmentation fault on the
>>>>>>>>>>> 'numpy'
>>>>>>>>>>> backend for values greater than 20 or so.
>>>>>>>>>>>
>>>>>>>>>>> This is an odd use of ufuncify, as summing would better be done
>>>>>>>>>>> in a loop with an array as input to the function. You can probably
>>>>>>>>>>> used the
>>>>>>>>>>> IndexBased class to set up a loop based sum. If you use the tempdir
>>>>>>>>>>> kwarg
>>>>>>>>>>> to ufuncify you can see the code it generates, and you'll basically
>>>>>>>>>>> get a
>>>>>>>>>>> Fortran function that has as many input args as your integer value
>>>>>>>>>>> which is
>>>>>>>>>>> not very efficient.
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>> Jason
>>>>>>>>>>> moorepants.info
>>>>>>>>>>> +01 530-601-9791
>>>>>>>>>>>
>>>>>>>>>>> On Thu, Sep 25, 2014 at 4:29 PM, Jason Moore <moore...@gmail.com
>>>>>>>>>>> > wrote:
>>>>>>>>>>>
>>>>>>>>>>>> David,
>>>>>>>>>>>>
>>>>>>>>>>>> This is because it wasn't wrapping lines correctly in the
>>>>>>>>>>>> generated Fortran code. If you use the development version of
>>>>>>>>>>>> SymPy it
>>>>>>>>>>>> should work.
>>>>>>>>>>>>
>>>>>>>>>>>> Here is the PR that fixed it: https://github.com/sympy/sympy
>>>>>>>>>>>> /pull/7968
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> Jason
>>>>>>>>>>>> moorepants.info
>>>>>>>>>>>> +01 530-601-9791
>>>>>>>>>>>>
>>>>>>>>>>>> On Thu, Sep 25, 2014 at 3:42 PM, David Shin <shin....@gmail.com
>>>>>>>>>>>> > wrote:
>>>>>>>>>>>>
>>>>>>>>>>>>> Hi, I recently began trying out sympy and am running into some
>>>>>>>>>>>>> difficulty.
>>>>>>>>>>>>>
>>>>>>>>>>>>> I wrote the following script, called demo.py:
>>>>>>>>>>>>>
>>>>>>>>>>>>> import sympyfrom sympy.utilities.autowrap import ufuncifyimport
>>>>>>>>>>>>> sys
>>>>>>>>>>>>>
>>>>>>>>>>>>> N = int(sys.argv[1])
>>>>>>>>>>>>> theta = []
>>>>>>>>>>>>> values = []for n in range(N):
>>>>>>>>>>>>> theta.append(sympy.symbols('x%s' % n))
>>>>>>>>>>>>> values.append(n)
>>>>>>>>>>>>>
>>>>>>>>>>>>> summation = sum(theta)
>>>>>>>>>>>>> f = ufuncify(theta, summation)print f(*values)[0]
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>> Running it for small N, it works fine:
>>>>>>>>>>>>>
>>>>>>>>>>>>> $ python demo.py 21
>>>>>>>>>>>>> 210.0
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>> But it fails for larger N. Can anyone advise? Thanks in
>>>>>>>>>>>>> advance.
>>>>>>>>>>>>>
>>>>>>>>>>>>> $ python demo.py 22
>>>>>>>>>>>>> Traceback (most recent call last):
>>>>>>>>>>>>> File "demo.py", line 13, in
>>>>>>>>>>>>> f = ufuncify(theta, summation)
>>>>>>>>>>>>> File
>>>>>>>>>>>>> "/opt/user/x86_64/Python-2.7.3/lib/python2.7/site-packages/sympy/utilities/autowrap.py",
>>>>>>>>>>>>> line 485, in ufuncify
>>>>>>>>>>>>> return autowrap(C.Equality(y[i], f(*args)), **kwargs)
>>>>>>>>>>>>> File
>>>>>>>>>>>>> "/opt/user/x86_64/Python-2.7.3/lib/python2.7/site-packages/sympy/utilities/autowrap.py",
>>>>>>>>>>>>> line 403, in autowrap
>>>>>>>>>>>>> return code_wrapper.wrap_code(routine, helpers=helps)
>>>>>>>>>>>>> File
>>>>>>>>>>>>> "/opt/user/x86_64/Python-2.7.3/lib/python2.7/site-packages/sympy/utilities/autowrap.py",
>>>>>>>>>>>>> line 139, in wrap_code
>>>>>>>>>>>>> self._process_files(routine)
>>>>>>>>>>>>> File
>>>>>>>>>>>>> "/opt/user/x86_64/Python-2.7.3/lib/python2.7/site-packages/sympy/utilities/autowrap.py",
>>>>>>>>>>>>> line 158, in _process_files
>>>>>>>>>>>>> " ".join(command), e.output))
>>>>>>>>>>>>> sympy.utilities.autowrap.CodeWrapError: Error while executing
>>>>>>>>>>>>> command: f2py -m wrapper_module_0 -c wrapped_code_0.f90. Command
>>>>>>>>>>>>> output is:
>>>>>>>>>>>>> running build
>>>>>>>>>>>>> running config_cc
>>>>>>>>>>>>> unifing config_cc, config, build_clib, build_ext, build commands
>>>>>>>>>>>>> --compiler options
>>>>>>>>>>>>> running config_fc
>>>>>>>>>>>>> unifing config_fc, config, build_clib, build_ext, build commands
>>>>>>>>>>>>> --fcompiler options
>>>>>>>>>>>>> running build_src
>>>>>>>>>>>>> build_src
>>>>>>>>>>>>> building extension "wrapper_module_0" sources
>>>>>>>>>>>>> f2py options: []
>>>>>>>>>>>>> f2py:>
>>>>>>>>>>>>> /tmp/tmpKbJQuO/src.linux-x86_64-2.7/wrapper_module_0module.c
>>>>>>>>>>>>> creating /tmp/tmpKbJQuO
>>>>>>>>>>>>> creating /tmp/tmpKbJQuO/src.linux-x86_64-2.7
>>>>>>>>>>>>> Reading fortran codes...
>>>>>>>>>>>>> Reading file 'wrapped_code_0.f90' (format:free)
>>>>>>>>>>>>> Post-processing...
>>>>>>>>>>>>> Block: wrapper_module_0
>>>>>>>>>>>>> Block: autofunc
>>>>>>>>>>>>> Post-processing (stage 2)...
>>>>>>>>>>>>> Building modules...
>>>>>>>>>>>>> Building module "wrapper_module_0"...
>>>>>>>>>>>>> Constructing wrapper function "autofunc"...
>>>>>>>>>>>>> y_15 =
>>>>>>>>>>>>> autofunc(x_16,x1,x10,x11,x12,x13,x14,x15,x16,x17,x18,x19,x2,x20,x21,x3,x4,x5,x6,x7,x8,x9,[m_17])
>>>>>>>>>>>>> Wrote C/API module "wrapper_module_0" to file
>>>>>>>>>>>>> "/tmp/tmpKbJQuO/src.linux-x86_64-2.7/wrapper_module_0module.c"
>>>>>>>>>>>>> adding '/tmp/tmpKbJQuO/src.linux-x86_64-2.7/fortranobject.c' to
>>>>>>>>>>>>> sources.
>>>>>>>>>>>>> adding '/tmp/tmpKbJQuO/src.linux-x86_64-2.7' to include_dirs.
>>>>>>>>>>>>> copying
>>>>>>>>>>>>> /opt/user/x86_64/Python-2.7.3/lib/python2.7/site-packages/numpy/f2py/src/fortranobject.c
>>>>>>>>>>>>> -> /tmp/tmpKbJQuO/src.linux-x86_64-2.7
>>>>>>>>>>>>> copying
>>>>>>>>>>>>> /opt/user/x86_64/Python-2.7.3/lib/python2.7/site-packages/numpy/f2py/src/fortranobject.h
>>>>>>>>>>>>> -> /tmp/tmpKbJQuO/src.linux-x86_64-2.7
>>>>>>>>>>>>> build_src: building npy-pkg config files
>>>>>>>>>>>>> running build_ext
>>>>>>>>>>>>> customize UnixCCompiler
>>>>>>>>>>>>> customize UnixCCompiler using build_ext
>>>>>>>>>>>>> customize Gnu95FCompiler
>>>>>>>>>>>>> Found executable /opt/user/x86_64/gcc-4.7.2/bin/gfortran
>>>>>>>>>>>>> customize Gnu95FCompiler
>>>>>>>>>>>>> customize Gnu95FCompiler using build_ext
>>>>>>>>>>>>> building 'wrapper_module_0' extension
>>>>>>>>>>>>> compiling C sources
>>>>>>>>>>>>> C compiler: gcc -pthread -fno-strict-aliasing -g -O2 -DNDEBUG -g
>>>>>>>>>>>>> -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC
>>>>>>>>>>>>>
>>>>>>>>>>>>> creating /tmp/tmpKbJQuO/tmp
>>>>>>>>>>>>> creating /tmp/tmpKbJQuO/tmp/tmpKbJQuO
>>>>>>>>>>>>> creating /tmp/tmpKbJQuO/tmp/tmpKbJQuO/src.linux-x86_64-2.7
>>>>>>>>>>>>> compile options: '-I/tmp/tmpKbJQuO/src.linux-x86_64-2.7
>>>>>>>>>>>>> -I/opt/user/x86_64/Python-2.7.3/lib/python2.7/site-packages/numpy/core/include
>>>>>>>>>>>>> -I/opt/user/x86_64/Python-2.7.3/include/python2.7 -c'
>>>>>>>>>>>>> gcc: /tmp/tmpKbJQuO/src.linux-x86_64-2.7/wrapper_module_0module.c
>>>>>>>>>>>>> In file included from
>>>>>>>>>>>>> /opt/user/x86_64/Python-2.7.3/lib/python2.7/site-packages/numpy/core/include/numpy/ndarraytypes.h:1728:0,
>>>>>>>>>>>>> from
>>>>>>>>>>>>> /opt/user/x86_64/Python-2.7.3/lib/python2.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:17,
>>>>>>>>>>>>> from
>>>>>>>>>>>>> /opt/user/x86_64/Python-2.7.3/lib/python2.7/site-packages/numpy/core/include/numpy/arrayobject.h:15,
>>>>>>>>>>>>> from
>>>>>>>>>>>>> /tmp/tmpKbJQuO/src.linux-x86_64-2.7/fortranobject.h:13,
>>>>>>>>>>>>> from
>>>>>>>>>>>>> /tmp/tmpKbJQuO/src.linux-x86_64-2.7/wrapper_module_0module.c:18:
>>>>>>>>>>>>> /opt/user/x86_64/Python-2.7.3/lib/python2.7/site-packages/numpy/core/include/numpy/npy_deprecated_api.h:11:2:
>>>>>>>>>>>>> warning: #warning "Using deprecated NumPy API, disable it by
>>>>>>>>>>>>> #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
>>>>>>>>>>>>> /tmp/tmpKbJQuO/src.linux-x86_64-2.7/wrapper_module_0module.c:111:12:
>>>>>>>>>>>>> warning: âpy_sizeâefined but not used [-Wunused-function]
>>>>>>>>>>>>> gcc: /tmp/tmpKbJQuO/src.linux-x86_64-2.7/fortranobject.c
>>>>>>>>>>>>> In file included from
>>>>>>>>>>>>> /opt/user/x86_64/Python-2.7.3/lib/python2.7/site-packages/numpy/core/include/numpy/ndarraytypes.h:1728:0,
>>>>>>>>>>>>> from
>>>>>>>>>>>>> /opt/user/x86_64/Python-2.7.3/lib/python2.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:17,
>>>>>>>>>>>>> from
>>>>>>>>>>>>> /opt/user/x86_64/Python-2.7.3/lib/python2.7/site-packages/numpy/core/include/numpy/arrayobject.h:15,
>>>>>>>>>>>>> from
>>>>>>>>>>>>> /tmp/tmpKbJQuO/src.linux-x86_64-2.7/fortranobject.h:13,
>>>>>>>>>>>>> from
>>>>>>>>>>>>> /tmp/tmpKbJQuO/src.linux-x86_64-2.7/fortranobject.c:2:
>>>>>>>>>>>>> /opt/user/x86_64/Python-2.7.3/lib/python2.7/site-packages/numpy/core/include/numpy/npy_deprecated_api.h:11:2:
>>>>>>>>>>>>> warning: #warning "Using deprecated NumPy API, disable it by
>>>>>>>>>>>>> #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
>>>>>>>>>>>>> compiling Fortran sources
>>>>>>>>>>>>> Fortran f77 compiler: /opt/user/x86_64/gcc-4.7.2/bin/gfortran
>>>>>>>>>>>>> -Wall -ffixed-form -fno-second-underscore -fPIC -O3 -funroll-loops
>>>>>>>>>>>>> Fortran f90 compiler: /opt/user/x86_64/gcc-4.7.2/bin/gfortran
>>>>>>>>>>>>> -Wall -fno-second-underscore -fPIC -O3 -funroll-loops
>>>>>>>>>>>>> Fortran fix compiler: /opt/user/x86_64/gcc-4.7.2/bin/gfortran
>>>>>>>>>>>>> -Wall -ffixed-form -fno-second-underscore -Wall
>>>>>>>>>>>>> -fno-second-underscore -fPIC -O3 -funroll-loops
>>>>>>>>>>>>> compile options: '-I/tmp/tmpKbJQuO/src.linux-x86_64-2.7
>>>>>>>>>>>>> -I/opt/user/x86_64/Python-2.7.3/lib/python2.7/site-packages/numpy/core/include
>>>>>>>>>>>>> -I/opt/user/x86_64/Python-2.7.3/include/python2.7 -c'
>>>>>>>>>>>>> gfortran:f90: wrapped_code_0.f90
>>>>>>>>>>>>> wrapped_code_0.f90:1.133:
>>>>>>>>>>>>>
>>>>>>>>>>>>> 4, x15, x16, x17, x18, x19, x2, x20, x21, x3, x4, x5, x6, x7, x8,
>>>>>>>>>>>>> x9, y_15
>>>>>>>>>>>>>
>>>>>>>>>>>>> 1
>>>>>>>>>>>>> Warning: Line truncated at (1)
>>>>>>>>>>>>> wrapped_code_0.f90:1.132:
>>>>>>>>>>>>>
>>>>>>>>>>>>> 14, x15, x16, x17, x18, x19, x2, x20, x21, x3, x4, x5, x6, x7,
>>>>>>>>>>>>> x8, x9, y_15
>>>>>>>>>>>>>
>>>>>>>>>>>>> 1
>>>>>>>>>>>>> Error: Unexpected junk in formal argument list at (1)
>>>>>>>>>>>>> wrapped_code_0.f90:33.3:
>>>>>>>>>>>>>
>>>>>>>>>>>>> end subroutine
>>>>>>>>>>>>> 1
>>>>>>>>>>>>> Error: Expecting END PROGRAM statement at (1)
>>>>>>>>>>>>> Error: Unexpected end of file in 'wrapped_code_0.f90'
>>>>>>>>>>>>> wrapped_code_0.f90:1.133:
>>>>>>>>>>>>>
>>>>>>>>>>>>> 4, x15, x16, x17, x18, x19, x2, x20, x21, x3, x4, x5, x6, x7, x8,
>>>>>>>>>>>>> x9, y_15
>>>>>>>>>>>>>
>>>>>>>>>>>>> 1
>>>>>>>>>>>>> Warning: Line truncated at (1)
>>>>>>>>>>>>> wrapped_code_0.f90:1.132:
>>>>>>>>>>>>>
>>>>>>>>>>>>> 14, x15, x16, x17, x18, x19, x2, x20, x21, x3, x4, x5, x6, x7,
>>>>>>>>>>>>> x8, x9, y_15
>>>>>>>>>>>>>
>>>>>>>>>>>>> 1
>>>>>>>>>>>>> Error: Unexpected junk in formal argument list at (1)
>>>>>>>>>>>>> wrapped_code_0.f90:33.3:
>>>>>>>>>>>>>
>>>>>>>>>>>>> end subroutine
>>>>>>>>>>>>> 1
>>>>>>>>>>>>> Error: Expecting END PROGRAM statement at (1)
>>>>>>>>>>>>> Error: Unexpected end of file in 'wrapped_code_0.f90'
>>>>>>>>>>>>> error: Command "/opt/user/x86_64/gcc-4.7.2/bin/gfortran -Wall
>>>>>>>>>>>>> -fno-second-underscore -fPIC -O3 -funroll-loops
>>>>>>>>>>>>> -I/tmp/tmpKbJQuO/src.linux-x86_64-2.7
>>>>>>>>>>>>> -I/opt/user/x86_64/Python-2.7.3/lib/python2.7/site-packages/numpy/core/include
>>>>>>>>>>>>> -I/opt/user/x86_64/Python-2.7.3/include/python2.7 -c -c
>>>>>>>>>>>>> wrapped_code_0.f90 -o /tmp/tmpKbJQuO/wrapped_code_0.o" failed
>>>>>>>>>>>>> with exit status 1
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>> --
>>>>>>>>>>>>> You received this message because you are subscribed to the
>>>>>>>>>>>>> Google Groups "sympy" group.
>>>>>>>>>>>>> To unsubscribe from this group and stop receiving emails from
>>>>>>>>>>>>> it, send an email to sympy+un...@googlegroups.com.
>>>>>>>>>>>>> To post to this group, send email to sy...@googlegroups.com.
>>>>>>>>>>>>> Visit this group at http://groups.google.com/group/sympy.
>>>>>>>>>>>>> To view this discussion on the web visit
>>>>>>>>>>>>> https://groups.google.com/d/msgid/sympy/68af9759-5988-4e85-8
>>>>>>>>>>>>> 1ec-7cc303022e46%40googlegroups.com
>>>>>>>>>>>>> <https://groups.google.com/d/msgid/sympy/68af9759-5988-4e85-81ec-7cc303022e46%40googlegroups.com?utm_medium=email&utm_source=footer>
>>>>>>>>>>>>> .
>>>>>>>>>>>>> For more options, visit https://groups.google.com/d/optout.
>>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>> --
>>>>>>>>>> You received this message because you are subscribed to the
>>>>>>>>>> Google Groups "sympy" group.
>>>>>>>>>> To unsubscribe from this group and stop receiving emails from it,
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>>>>>>>>>> To post to this group, send email to sy...@googlegroups.com.
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>>>>>>>>>> To view this discussion on the web visit
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>>>>>>>>>> a9c-959f77ef6811%40googlegroups.com
>>>>>>>>>> <https://groups.google.com/d/msgid/sympy/191c2f57-99c2-44eb-9a9c-959f77ef6811%40googlegroups.com?utm_medium=email&utm_source=footer>
>>>>>>>>>> .
>>>>>>>>>>
>>>>>>>>>> For more options, visit https://groups.google.com/d/optout.
>>>>>>>>>>
>>>>>>>>>
>>>>>>>>> --
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>>>>>>> 8e42-01b0f57dbe1a%40googlegroups.com
>>>>>>> <https://groups.google.com/d/msgid/sympy/6728544e-2ef8-45b5-8e42-01b0f57dbe1a%40googlegroups.com?utm_medium=email&utm_source=footer>
>>>>>>> .
>>>>>>>
>>>>>>> For more options, visit https://groups.google.com/d/optout.
>>>>>>>
>>>>>>
>>>>>> --
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>>>>> .
>>>>>
>>>>> For more options, visit https://groups.google.com/d/optout.
>>>>>
>>>>
>>>> --
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>>> https://groups.google.com/d/msgid/sympy/8e86a644-69c5-49dd-9a9c-450522899fa2%40googlegroups.com
>>>
>>> <https://groups.google.com/d/msgid/sympy/8e86a644-69c5-49dd-9a9c-450522899fa2%40googlegroups.com?utm_medium=email&utm_source=footer>
>>> .
>>>
>>> For more options, visit https://groups.google.com/d/optout.
>>>
>>
>>
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