[SciPy-user] Automating Matlab
Eric Schug
I have a working version of a matlab to python translator.
It allows translation of matlab scripts into numpy constructs,
supporting most of the matlab language. The parser is nearly complete.
Most of the remaining work involves providing a robust translation. Such as
* making sure that copies on assign are done when needed.
* correct indexing a(:) becomes a.flatten(1) when on the left hand
side (lhs) of equals
and a[:] when on the right hand side
I've seen a few projects attempt to do this, but for one reason or
another have stopped it.
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Robert Kern
> Is there strong interest in automating matlab to numpy conversion?
Yes! Please post your code somewhere!
--
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
David Warde-Farley
> Is there strong interest in automating matlab to numpy conversion?
I think there is a strong interest in this. One of the main obstacles
to changing environments is inertia and familiarity. My advisor
repeatedly expresses his wish to give Python another try, and having
an easy way to show him how his existing scripts translate would be
awesome.
Of course there are caveats, corner cases where such translations will
fail, but a fairly foolproof method of converting simple scripts would
be just fantastic. I imagine if you've gotten further along than
previous attempts you'll receive a lot of street cred on this list and
probably a lot of patches to make things work better. :)
David
Young, Karl
>> Is there strong interest in automating matlab to numpy conversion?
> Yes! Please post your code somewhere!
seconded !!!!! I'm currently working on a grant that has turned out to involve porting a lot of matlab code to python; you will be gratefully acknowledged in whatever comes of the work of the grant.
-- KY
gsever
an automated tool than doing manual conversations.
Just for your information, there is a IDL-to-Python conversation tool
named i2py @ http://code.google.com/p/i2py/
> SciPy-u...@scipy.orghttp://projects.scipy.org/mailman/listinfo/scipy-user
Stef Mientki
Robert Kern wrote:
> On Sat, Jan 31, 2009 at 19:06, Eric Schug <schug...@gmail.com> wrote:
>
>> Is there strong interest in automating matlab to numpy conversion?
>>
>
> Yes! Please post your code somewhere!
>
>
+1
And this is a very good moment for the persons who are creating a Matlab
like environment,
including the Matlab-like workspace,
to show there creations.
cheers,
Stef
Alex Liberzon
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Today's Topics:
1. Automating Matlab (Eric Schug)
2. Re: Automating Matlab (Robert Kern)
3. Re: Automating Matlab (David Warde-Farley)
4. shared memory machines (Gideon Simpson)
5. Re: Automating Matlab (Young, Karl)
6. Re: Automating Matlab (gsever)
7. Re: Automating Matlab (Stef Mientki)
8. Re: shared memory machines (Gael Varoquaux)
9. Re: shared memory machines (Gideon Simpson)
10. Re: shared memory machines (Gael Varoquaux)
----------------------------------------------------------------------
Message: 1
Date: Sat, 31 Jan 2009 20:06:20 -0500
From: Eric Schug <schug...@gmail.com>
Subject: [SciPy-user] Automating Matlab
To: scipy...@scipy.org
Message-ID: <4984F58C...@gmail.com>
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
Is there strong interest in automating matlab to numpy conversion?
I have a working version of a matlab to python translator.
It allows translation of matlab scripts into numpy constructs,
supporting most of the matlab language. The parser is nearly complete.
Most of the remaining work involves providing a robust translation. Such as
* making sure that copies on assign are done when needed.
* correct indexing a(:) becomes a.flatten(1) when on the left hand
side (lhs) of equals
and a[:] when on the right hand side
I've seen a few projects attempt to do this, but for one reason or
another have stopped it.
------------------------------
Message: 2
Date: Sat, 31 Jan 2009 19:34:57 -0600
From: Robert Kern <rober...@gmail.com>
Subject: Re: [SciPy-user] Automating Matlab
To: SciPy Users List <scipy...@scipy.org>
Message-ID:
<3d375d730901311734o388...@mail.gmail.com>
Content-Type: text/plain; charset=UTF-8
On Sat, Jan 31, 2009 at 19:06, Eric Schug <schug...@gmail.com> wrote:
> Is there strong interest in automating matlab to numpy conversion?
Yes! Please post your code somewhere!
--
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
------------------------------
Message: 3
Date: Sat, 31 Jan 2009 20:49:32 -0500
From: David Warde-Farley <d...@cs.toronto.edu>
Subject: Re: [SciPy-user] Automating Matlab
To: SciPy Users List <scipy...@scipy.org>
Message-ID: <5BC40EFF-8964-45CB...@cs.toronto.edu>
Content-Type: text/plain; charset=US-ASCII; format=flowed; delsp=yes
On 31-Jan-09, at 8:06 PM, Eric Schug wrote:
> Is there strong interest in automating matlab to numpy conversion?
I think there is a strong interest in this. One of the main obstacles
to changing environments is inertia and familiarity. My advisor
repeatedly expresses his wish to give Python another try, and having
an easy way to show him how his existing scripts translate would be
awesome.
Of course there are caveats, corner cases where such translations will
fail, but a fairly foolproof method of converting simple scripts would
be just fantastic. I imagine if you've gotten further along than
previous attempts you'll receive a lot of street cred on this list and
probably a lot of patches to make things work better. :)
David
------------------------------
Message: 4
Date: Sun, 1 Feb 2009 00:37:48 -0500
From: Gideon Simpson <sim...@math.toronto.edu>
Subject: [SciPy-user] shared memory machines
To: SciPy Users List <scipy...@scipy.org>
Message-ID: <2AE6D153-799C-450E...@math.toronto.edu>
Content-Type: text/plain; charset=US-ASCII; format=flowed; delsp=yes
Has anyone been able to take advantage of shared memory machines with
scipy? How did you do it?
-gideon
------------------------------
Message: 5
Date: Sat, 31 Jan 2009 21:45:59 -0800
From: "Young, Karl" <karl....@ucsf.edu>
Subject: Re: [SciPy-user] Automating Matlab
To: "SciPy Users List" <scipy...@scipy.org>
Message-ID:
<9D202D4E86A4BF47BA69...@EXVS06.net.ucsf.edu>
Content-Type: text/plain; charset=iso-8859-1
>> Is there strong interest in automating matlab to numpy conversion?
> Yes! Please post your code somewhere!
seconded !!!!! I'm currently working on a grant that has turned out to involve porting a lot of matlab code to python; you will be gratefully acknowledged in whatever comes of the work of the grant.
-- KY
------------------------------
Message: 6
Date: Sat, 31 Jan 2009 23:49:32 -0800 (PST)
From: gsever <gokha...@gmail.com>
Subject: Re: [SciPy-user] Automating Matlab
To: scipy...@scipy.org
Message-ID:
<27b4bf7a-bb75-457d...@t13g2000yqc.googlegroups.com>
Content-Type: text/plain; charset=ISO-8859-1
I am interested with this project, too. Would be much better to have
an automated tool than doing manual conversations.
Just for your information, there is a IDL-to-Python conversation tool
named i2py @ http://code.google.com/p/i2py/
On Jan 31, 7:06?pm, Eric Schug <schugsc...@gmail.com> wrote:
> Is there strong interest in automating matlab to numpy conversion?
>
> I have a working version of a matlab to python translator.
> It allows translation of matlab scripts into numpy constructs,
> supporting most of the matlab language. ?The parser is nearly complete. ?
> Most of the remaining work involves providing a robust translation. Such as
> ? ? * making sure that copies on assign are done when needed.
> ? ? * correct indexing a(:) becomes a.flatten(1) when on the left hand
> side (lhs) of equals
> ? ? ? ?and a[:] when on the right hand side
>
> I've seen a few projects attempt to do this, but for one reason or
> another have stopped it.
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-u...@scipy.orghttp://projects.scipy.org/mailman/listinfo/scipy-user
------------------------------
Message: 7
Date: Sun, 01 Feb 2009 10:27:11 +0100
From: Stef Mientki <s.mi...@ru.nl>
Subject: Re: [SciPy-user] Automating Matlab
To: scipy...@scipy.org
Message-ID: <49856AEF...@ru.nl>
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
Robert Kern wrote:
> On Sat, Jan 31, 2009 at 19:06, Eric Schug <schug...@gmail.com> wrote:
>
>> Is there strong interest in automating matlab to numpy conversion?
>>
>
> Yes! Please post your code somewhere!
>
>
+1
And this is a very good moment for the persons who are creating a Matlab
like environment,
including the Matlab-like workspace,
to show there creations.
cheers,
Stef
------------------------------
Message: 8
Date: Sun, 1 Feb 2009 10:57:46 +0100
From: Gael Varoquaux <gael.va...@normalesup.org>
Subject: Re: [SciPy-user] shared memory machines
To: SciPy Users List <scipy...@scipy.org>
Message-ID: <2009020109...@phare.normalesup.org>
Content-Type: text/plain; charset=iso-8859-1
On Sun, Feb 01, 2009 at 12:37:48AM -0500, Gideon Simpson wrote:
> Has anyone been able to take advantage of shared memory machines with
> scipy? How did you do it?
I am not sure I understand your question. You want to do parallel
computing and share the arrays between processes, is that it?
Ga?l
------------------------------
Message: 9
Date: Sun, 1 Feb 2009 10:03:30 -0500
From: Gideon Simpson <sim...@math.toronto.edu>
Subject: Re: [SciPy-user] shared memory machines
To: SciPy Users List <scipy...@scipy.org>
Message-ID: <FDC4C5E2-3740-44BB...@math.toronto.edu>
Content-Type: text/plain; charset=ISO-8859-1; format=flowed; delsp=yes
Yes, but I'm talking about when you have a multiprocessor/multicore
system, not a commodity cluster. In these shared memory
configurations, were I using compiled code, I'd be able to use OpenMP
to take advantage of the additional cores/processors. I'm wondering
if anyone has looked at ways to take advantage of such configurations
with scipy.
-gideon
On Feb 1, 2009, at 4:57 AM, Gael Varoquaux wrote:
> On Sun, Feb 01, 2009 at 12:37:48AM -0500, Gideon Simpson wrote:
>> Has anyone been able to take advantage of shared memory machines with
>> scipy? How did you do it?
>
> I am not sure I understand your question. You want to do parallel
> computing and share the arrays between processes, is that it?
>
> Ga?l
> _______________________________________________
> SciPy-user mailing list
> SciPy...@scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
------------------------------
Message: 10
Date: Sun, 1 Feb 2009 16:29:40 +0100
From: Gael Varoquaux <gael.va...@normalesup.org>
Subject: Re: [SciPy-user] shared memory machines
To: SciPy Users List <scipy...@scipy.org>
Message-ID: <2009020115...@phare.normalesup.org>
Content-Type: text/plain; charset="iso-8859-1"
On Sun, Feb 01, 2009 at 10:03:30AM -0500, Gideon Simpson wrote:
> Yes, but I'm talking about when you have a multiprocessor/multicore
> system, not a commodity cluster. In these shared memory
> configurations, were I using compiled code, I'd be able to use OpenMP
> to take advantage of the additional cores/processors. I'm wondering
> if anyone has looked at ways to take advantage of such configurations
> with scipy.
I use the multiprocessing module:
http://docs.python.org/library/multiprocessing.html
I also have some code to share arrays between processes. I'd love to
submit it for integration with numpy, but first I'd like it to get more
exposure so that the eventual flaws in the APIs are found. I am attaching
it.
Actually I wrote this code a few months ago, and now that I am looking at
it, I realise that the SharedMemArray should probably be a subclass of
numpy.ndarray, and implement the full array signature. I am not sure if
this is possible or not (ie if it will still be easy to have
multiprocessing share the data between processes or not). I don't really
have time for polishing this right, anybody wants to have a go?
Ga?l
> On Feb 1, 2009, at 4:57 AM, Gael Varoquaux wrote:
> > On Sun, Feb 01, 2009 at 12:37:48AM -0500, Gideon Simpson wrote:
> >> Has anyone been able to take advantage of shared memory machines with
> >> scipy? How did you do it?
> > I am not sure I understand your question. You want to do parallel
> > computing and share the arrays between processes, is that it?
-------------- next part --------------
"""
Small helper module to share arrays between processes without copying
data.
Numpy arrays can be converted to shared memory arrays, which implement
the array protocole, but are allocated in memory that can be
share transparently by the multiprocessing module.
"""
# Author: Gael Varoquaux <gael dot varoquaux at normalesup dot org>
# Copyright: Gael Varoquaux
# License: BSD
import numpy as np
import multiprocessing
import ctypes
_ctypes_to_numpy = {
ctypes.c_char : np.int8,
ctypes.c_wchar : np.int16,
ctypes.c_byte : np.int8,
ctypes.c_ubyte : np.uint8,
ctypes.c_short : np.int16,
ctypes.c_ushort : np.uint16,
ctypes.c_int : np.int32,
ctypes.c_uint : np.int32,
ctypes.c_long : np.int32,
ctypes.c_ulong : np.int32,
ctypes.c_float : np.float32,
ctypes.c_double : np.float64
}
_numpy_to_ctypes = dict((value, key) for key, value in
_ctypes_to_numpy.iteritems())
def shmem_as_ndarray(data, dtype=float):
""" Given a multiprocessing.Array object, as created by
ndarray_to_shmem, returns an ndarray view on the data.
"""
dtype = np.dtype(dtype)
size = data._wrapper.get_size()/dtype.itemsize
arr = np.frombuffer(buffer=data, dtype=dtype, count=size)
return arr
def ndarray_to_shmem(arr):
""" Converts a numpy.ndarray to a multiprocessing.Array object.
The memory is copied, and the array is flattened.
"""
arr = arr.reshape((-1, ))
data = multiprocessing.RawArray(_numpy_to_ctypes[arr.dtype.type],
arr.size)
ctypes.memmove(data, arr.data[:], len(arr.data))
return data
def test_ndarray_conversion():
""" Check that the conversion to multiprocessing.Array and back works.
"""
a = np.random.random((100, ))
a_sh = ndarray_to_shmem(a)
b = shmem_as_ndarray(a_sh)
np.testing.assert_almost_equal(a, b)
def test_conversion_non_flat():
""" Check that the conversion also works with non-flat arrays.
"""
a = np.random.random((100, 2))
a_flat = a.flatten()
a_sh = ndarray_to_shmem(a)
b = shmem_as_ndarray(a_sh)
np.testing.assert_almost_equal(a_flat, b)
def test_conversion_non_contiguous():
""" Check that the conversion also works with non-contiguous arrays.
"""
a = np.indices((3, 3, 3))
a = a.T
a_flat = a.flatten()
a_sh = ndarray_to_shmem(a)
b = shmem_as_ndarray(a_sh, dtype=a.dtype)
np.testing.assert_almost_equal(a_flat, b)
def test_no_copy():
""" Check that the data is not copied from the multiprocessing.Array.
"""
a = np.random.random((100, ))
a_sh = ndarray_to_shmem(a)
a = shmem_as_ndarray(a_sh)
b = shmem_as_ndarray(a_sh)
a[0] = 1
np.testing.assert_equal(a[0], b[0])
a[0] = 0
np.testing.assert_equal(a[0], b[0])
################################################################################
# A class to carry around the relevant information
################################################################################
class SharedMemArray(object):
""" Wrapper around multiprocessing.Array to share an array accross
processes.
"""
def __init__(self, arr):
""" Initialize a shared array from a numpy array.
The data is copied.
"""
self.data = ndarray_to_shmem(arr)
self.dtype = arr.dtype
self.shape = arr.shape
def __array__(self):
""" Implement the array protocole.
"""
arr = shmem_as_ndarray(self.data, dtype=self.dtype)
arr.shape = self.shape
return arr
def asarray(self):
return self.__array__()
def test_sharing_array():
""" Check that a SharedMemArray shared between processes is indeed
modified in place.
"""
# Our worker function
def f(arr):
a = arr.asarray()
a *= -1
a = np.random.random((10, 3, 1))
arr = SharedMemArray(a)
# b is a copy of a
b = arr.asarray()
np.testing.assert_array_equal(a, b)
multiprocessing.Process(target=f, args=(arr,)).run()
np.testing.assert_equal(-b, a)
if __name__ == '__main__':
import nose
nose.runmodule()
------------------------------
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Alex Liberzon
Turbulence Structure Laboratory (http://www.eng.tau.ac.il/efdl)
School of Mechanical Engineering
Tel Aviv University
Tel: +972-3-640-8928 (office)
Tel: +972-3-640-6860 (lab)
E-mail: ale...@eng.tau.ac.il
Sturla Molden
>> Is there strong interest in automating matlab to numpy conversion?
>
> Yes! Please post your code somewhere!
For those who are interested, there are two ways of doing this:
The most portable is to call the 'Matlab engine', which is a C and Fortran
library for automating Matlab. This can be done using f2py or ctypes (wrap
libeng.dll and libmx.dll).
The other option (Windows only) is to use Matlab as an outproc COM server.
This will require pywin32.
S.M.
David Cournapeau
>
> For those who are interested, there are two ways of doing this:
>
I think Eric talked about source code translation, that is .m to .py.
> The most portable is to call the 'Matlab engine', which is a C and Fortran
> library for automating Matlab. This can be done using f2py or ctypes (wrap
> libeng.dll and libmx.dll).
>
If you are not aware of it, there is already code for it:
http://svn.scipy.org/svn/scikits/trunk/mlabwrap/
cheers,
David
Andrew Straw
http://frontiersin.org/neuroinformatics/paper/10.3389/neuro.11/005.2009/
Eric Schug
> Is there strong interest in automating matlab to numpy conversion?
>
> I have a working version of a matlab to python translator.
> It allows translation of matlab scripts into numpy constructs,
> supporting most of the matlab language. The parser is nearly
> complete. Most of the remaining work involves providing a robust
> translation. Such as
> * making sure that copies on assign are done when needed.
> * correct indexing a(:) becomes a.flatten(1) when on the left hand
> side (lhs) of equals
> and a[:] when on the right hand side
>
>
> I've seen a few projects attempt to do this, but for one reason or
> another have stopped it.
>
>
http://sourceforge.net/projects/libermate/
Latest version now supports simple command expressions (e.g hold on)
Dmitrey
it's very interesting,
certainly it should be mentioned in scipy.org topical software section,
also, I guess, it's worth mention in such mail lists as
http://groups.google.com/group/comp.soft-sys.matlab,
http://groups.google.com/group/comp.lang.python.announce,
http://groups.google.com/group/sci.op-research,
http://groups.google.com/group/sci.math.num-analysis
Regards, Dmitrey
Eric Schug wrote:
Nils Wagner
Hi Eric,
You might be interested in some tests.
Different Matlab Toolboxes are available through
http://www.maths.manchester.ac.uk/~higham/mg/
Cheers,
Nils
Tiziano Zito
Dmitrey
I'm trying to use your soft on a file from matlab fileexchage area (BTW
you could place a link to your soft there), so it prints
The following appear to be variables:
status, A, b, lb, val, f, M, bound, options, Aeq, val0, x, x0, beq, e, ub
The following appear to be functions:
rec, inf, IP1, linprog, optimset
So I would say "inf" is certainly not a function, it's equivalent to
numpy.inf (I guess you know).
BTW I think it would be a good idea to mention your software in
http://www.scipy.org/NumPy_for_Matlab_Users
as well as in Octave, SAGE mail lists.
Regards, D.
josef...@gmail.com
>> For those interested, my new project has been uploaded sourceforge at,
>> http://sourceforge.net/projects/libermate/
>>
>> Latest version now supports simple command expressions (e.g hold on)
>>
I tried it out on some simple matlab files. I didn't try to run the
translated files yet, but two translations make the code less readable
* translation of integers to floats, e.g. for array indices or for arange
* multiplication of scalar with array is translated with dot, eg
m: randn(n,k-1)*10 -> py: = dot(randn(n, k-1.), 10.)
string array in matlab came out as empty numpy array
m:
vnames=['yvar',
'iota',
'x1 ',
'x2 '];
-> py:
vnames = array(r_[])
Importing everything is a source of possible errors (e.g. pylab
overwrites numpy names)
from numpy import *
import scipy
# if available import pylab (from matlibplot)
try:
from pylab import *
except ImportError:
pass
I would prefer the current standard
import numpy as np
import matplotlib.pylab as plt
and keep the name space as part of the name, e.g. np.dot, np.exp, ...
But it looks like it will save a lot of typing and editing, even
though it will need careful proof reading.
Thanks,
Josef
Dmitrey
>> Eric Schug wrote:
>>
>>> For those interested, my new project has been uploaded sourceforge at,
>>> http://sourceforge.net/projects/libermate/
>>>
>>> Latest version now supports simple command expressions (e.g hold on)
>>>
>>>
>
>
> import scipy
>
> I would prefer the current standard
> import numpy as np
>
Let me add some more cents:
instead of round(arr) it should be used arr.round() (because Python's
round doesn't work for numpy arrays)
zeros(m,n) should be zeros((m,n))
ones(m,n) should be ones((m,n))
"end" should go to "-1" (now "xend-1")
variables of index type (for example, obtained from ind=find(...)
replaced by ind=nonzero() or ind=where()) should not be decreased in the
following lines with indexing, eg arr[ind] should be used instead of
arr[ind-1]
for A=[B C ...] and A=[B;C] using A=hstack((B, C,...)) and A=vstack((B,
C,...)) is more readable and natural than current
array(r_[c_[B], c_[C]])
Regards, D.
Eric Schug
I will try to address them.
> * translation of integers to floats, e.g. for array indices or for arange
>
Rational for cast if int to float.
Matlab always uses float data type, for most expressions
e.g. try
format long e
a=1
This is mostly a problem for division, integer division would be used in some cases
yielding the wrong results. e.g.
a=1/2
would give 0 and not 0.5 as it does in Matlab. An alternative method would be
to use
from __future__ import division
I think the best would be to have this be a command line option, so that various translation rules could be enabled or disabled.
> * multiplication of scalar with array is translated with dot, eg
> m: randn(n,k-1)*10 -> py: = dot(randn(n, k-1.), 10.)
Matrix multiplication in matlab is * -> dot in Numpy but with scalars should use more readable *
> string array in matlab came out as empty numpy array
>
> m:
> vnames=['yvar',
> 'iota',
> 'x1 ',
> 'x2 '];
> -> py:
> vnames = array(r_[])
> Importing everything is a source of possible errors (e.g. pylab
> overwrites numpy names)
>
> from numpy import *
> import scipy
> # if available import pylab (from matlibplot)
> try:
> from pylab import *
> except ImportError:
> pass
need to cross reference numpy functions.
I've added the rest to tracker at SourceForge. Although, still learning to use Source forge tools.
Eric.
Stef Mientki
Eric Schug wrote:
> Eric Schug wrote:
>
>> Is there strong interest in automating matlab to numpy conversion?
>>
>> I have a working version of a matlab to python translator.
>> It allows translation of matlab scripts into numpy constructs,
>> supporting most of the matlab language. The parser is nearly
>> complete. Most of the remaining work involves providing a robust
>> translation. Such as
>> * making sure that copies on assign are done when needed.
>> * correct indexing a(:) becomes a.flatten(1) when on the left hand
>> side (lhs) of equals
>> and a[:] when on the right hand side
>>
>>
>> I've seen a few projects attempt to do this, but for one reason or
>> another have stopped it.
>>
>>
>>
>
>
Such a translator would be very welcome.
We just tried the translator with a simple script,
attached the m-file and the hand-corrected py-file (where you can
changes the corrections).
These are our findings
* show() command is not needed in Matlab.
* Case-Senitive function calls are automatically translated in Matlab
* Complex number i is transformed in a function 1j()
* product of 2 numbers is changed in a (ugly) dot-product.
* can't handle unicode e.g. "reëel"
* matdiv is not found
* graphs are nicer, but axis are uglier
* subplot needs integer values
the resulting graphs from both Matlab and Python, can be seen here
(we might not have used the latest MatPlotLib).
good luck and cheers,
Stef
Stef Mientki
>
>
> the resulting graphs from both Matlab and Python, can be seen here
> (we might not have used the latest MatPlotLib).
>
David Warde-Farley
On 26-Feb-09, at 6:33 AM, Stef Mientki wrote:
> * graphs are nicer, but axis are uglier
It looks like the problem is mostly font size and perhaps margins.
There's not a lot that can be done about this, since it will depend on
your window size as well. You could try some heuristic to decrease the
font size for subplots, I suppose.
David
Gunten
help me with this conversion?
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alex
> I have my matlabcodes but i could not convert them into matlabcodes can you
> help me with this conversion?
Sounds easy. But maybe you mean something like this:
http://www.scipy.org/NumPy_for_Matlab_Users
Alex
alex
> I have my matlabcodes but i could not convert them into matlabcodes can you
> help me with this conversion?
Sup dawg, I heard you like idempotence so we converted your matlabcodes
into matlabcodes so that they still run in matlab.
Scott Sinclair
> Gunten wrote:
>> I have my matlabcodes but i could not convert them into matlabcodes can you
>> help me with this conversion?
>
Hi Gunten,
Glad to hear that you're keen to start using NumPy and SciPy.
I suggest reading through the web page suggested by Alex and starting
to convert your code. Once you hit issues that you are unable to
solve, you should post detailed questions here. It will be easier for
someone to give you a helpful response to a detailed query instead of
a general request to convert all of your code.
Cheers,
Scott