Yes. The next release should be soon. We're just finishing up the last
couple of milestones. Can't but a date on it yet for sure though. If you
want to try it now though, you can pull the latest master off of github.
-Jim
On Wednesday, October 1, 2014 2:11:10 PM UTC-5, David Shin wrote:
>
> Just to confirm, the latest official release is 0.7.5 and does not work
> with your code. Is that right? Do you know when the next release will be?
>
> On Friday, September 26, 2014 10:12:23 AM UTC-5, James Crist wrote:
>>
>> @david:
>>
>> This is all in sympy master. The codegen stuff has had major work done to
>> it in the last development cycle.
>>
>> On Fri, Sep 26, 2014 at 10:10 AM, David Shin <shin....@gmail.com> wrote:
>>
>>> 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
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> --
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>>>>>>>>>>>>>>>> To unsubscribe from this group and stop receiving emails
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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
>>>>>>>>>>>>>>>> https://groups.google.com/d/msgid/sympy/68af9759-5988-4e85-
>>>>>>>>>>>>>>>> 81ec-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.
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>> --
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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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>>>>>>>>>> https://groups.google.com/d/msgid/sympy/6728544e-2ef8-45b5-8
>>>>>>>>>> e42-01b0f57dbe1a%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.
>>>>>>>>>>
>>>>>>>>>
>>>>>>>>> --
>>>>>>>> You received this message because you are subscribed to the Google
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>>>>>>>> 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/54f695f9-70c6-4eed-
>>>>>>>> 9761-fd39b4a18b8b%40googlegroups.com
>>>>>>>> <https://groups.google.com/d/msgid/sympy/54f695f9-70c6-4eed-9761-fd39b4a18b8b%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
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>>>>>> 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/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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>>> https://groups.google.com/d/msgid/sympy/f5809096-38c1-44ef-993e-2f3d3a732948%40googlegroups.com
>>>
>>> <https://groups.google.com/d/msgid/sympy/f5809096-38c1-44ef-993e-2f3d3a732948%40googlegroups.com?utm_medium=email&utm_source=footer>
>>> .
>>>
>>> For more options, visit https://groups.google.com/d/optout.
>>>
>>
>>
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