Sylvain Notes: Process to convert(Linux):
pip3 install numpy
pip3 install networkx==1.11
python3 setup.py install --user
~/.local/bin/smop generateMultiratePitchFilterbank.m
- Change import in new Pythonfile from
from libsmop import *
tofrom smop.libsmop import *
- Fix indentation
- Run look for errors
SMOP stands for Small Matlab/Octave to Python compiler. It is supposed to help those who attempt migration from Matlab to Python. Despite the similarities between the two languages, there are enough differences to make manual translation too time consuming.
SMOP is not a polished product, nor a replacement to Octave and Matlab. Taking into account its size (less than 3000 lines), this is not surprizing. There are no toolboxes. Small everyday functions (max, length, etc.) are recognized and supported, but that's all.
SMOP is written in Python, using PLY -- Python Lex/Yacc for lexical analysis and parsing, and numpy for runtime environment. SMOP is platform-independent, but is tested only on Linux. It is a command-line utility.
It is possible to run an example without installing smop. Just unzip
it somewhere, and cd
there. In your current directory you will find
a bunch of .py files and a file named fastsolver.m. It is taken from
the winning submission to Matlab programming competition in 2004
(Moving Furniture
http://www.mathworks.cn/matlabcentral/contest/contests/12/submissions/29989).
Now type python main.py fastsolver.m -o fastsolver.py
. If you don't
specify the output file with -o option, it is written to a.py
.
Each time a function is translated, its name is written.
.. code:: sh
lei@fuji:~/smop/smop$ python main.py fastsolver.m
fastsolver.m
solver
cbest
mainsolver
imoves
easysolver
localfiddler
findoverlaps
dijkstra
improve
TLL79
solverA
solver1
movefrompos
onemove
solver2
SearchPath
Faster10IntReps2
matrixsolver
outoftheway
ismember1
ismember2
setdiff
unique
sub2ind
randperm
perms
itTakesAThief
movefurniture
findshortestpath
dealWall1
lei@fuji:~/smop/smop$
The entire submission contains 2093 lines, and it is automatically translated to Python by smop. These are the good news. The bad news are that generating the code is not enough to run the program, so there are no performance numbers yet.
#. While the submission itself --- the solver program --- does not use graphics, the envelope code that is responsible to run the submission, collect and display the results, does. So about 100 lines of the envelope must be rewritten by hand.
#. Many standard functions are not yet implemented --- rand, find, and others. They are on the issues list.
#. Some matlab constructs, especially creating arrays by out of bound assignment, are used in the submission, but not yet supported by smop. Meanwhile, these lines should be rewritten in the Matlab code.
.. code:: matlab
01 function moves=solver(A,B,w0)
02 [moves,optmove,optscore]=cbest(A,B,w0);
03 curscore=sum(w0(moves(:,1)));
04 lots=1;
05 if length(moves)-optmove<20||curscore/optscore<1.05
06 lots=2; return
07 else
08 lenw=length(w0);
09 [xx,nseq]=sort(rand(1,lenw));
10 A1=A;
11 B1=B;
12 w01=w0;
13 for i=1:lenw
14 A1(A==i)=nseq(i);
15 B1(B==i)=nseq(i);
16 w01(nseq(i))=w0(i);
17 end;
18 [moves2,optmove,optscore]=cbest(A1,B1,w01);
becomes
.. code:: python
01 def solver(A,B,w0):
02 moves,optmove,optscore = cbest(A,B,w0)
03 curscore=np.sum(w0[(moves[:,0]-1)])
04 lots=1
05 if max(moves.shape) - optmove < 20 or curscore / optscore < 1.05:
06 lots=2
07 return moves
08 else:
09 lenw=max(w0.shape)
10 xx,nseq=sort(rand(1,lenw))
11 A1=A
12 B1=B
13 w01=w0
14 for i in range(1,(lenw+1)):
15 A1[A == i]=nseq[(i-1)]
16 B1[B == i]=nseq[(i-1)]
17 w01[(nseq[(i-1)]-1)]=w0[(i-1)]
18 moves2,optmove,optscore = cbest(A1,B1,w01)
Now some random notes.
#. Line 03. Functions vs. arrays ambiguity is correctly resolved:
for example, sum
is a function, but w0
and moves
are
arrays.
#. Line 09, Matlab function length
is correctly inlined as
max(w0.shape)
--- that is the maximum of the array dimensions.
#. For some functions, such as abs
, max
, and others, there are
both a builtin version and a different numpy version, and it is
important to use the right one. In line 03 np.sum
is used, but
in line 09 builtin max
. This is correct.
#. Line 10. Functions rand and sort are not yet implemented.
#. Lines 15-16. There is some support to boolean indexing.
#. Lines 15-17. Array subscripts are modified to start with zero index. Note that if all subscripts were decremented, it would break boolean indexing.
#. Line 13. Range specification in Matlab includes the upper bound.
In Python, it doesn't. So for i=1:lenw
becomes for i in range(1,(lenw+1))
. Extra parentheses are known as issue #1.
The table below tries to summarize various features.
+------------------------+----------------------------------+ | Implemented features | | +========================+==================================+ | Lexical and syntactical| Mostly complete, including | | analysis | some weird Matlab features | +------------------------+----------------------------------+ | Name resolution | For each occurrence of a | | | variable, find a set of its | | | possible definitions | +------------------------+----------------------------------+ | Inlining of small | | | functions | | +------------------------+----------------------------------+ | Array subscripts | Also, end subscript implemented | | translated from 1-based| | | (Matlab and Fortran | | | style) to 0-based (C | | | and Python style) | | +------------------------+----------------------------------+ | from:step:to | | | translated to | | | from:to:step | | +------------------------+----------------------------------+ | Upper bound is n+1 | | +------------------------+----------------------------------+
+------------------------+----------------------------------+
| Unimplemented features | |
| | |
+========================+==================================+
| Structs | |
| | To be implemented as soon as cc |
| | possible. |
+------------------------+----------------------------------+
| Arrays silently become | In some cases it may break the |
| C=style (rows first). | code. Not detected. |
+------------------------+----------------------------------+
| Function handles and | Handles break the heuristic that |
| lambda expressions | tells between function calls and |
| | array references. |
+------------------------+----------------------------------+
| Graphics, | Never |
+------------------------+----------------------------------+
| Auto-expanding arrays | Unlike other languages, matlab |
| | allows out-of-bounds assignment. |
| | As MathWorks tries to phase out |
| | this feature, there is a lot of |
| | legacy code depending on it. |
+------------------------+----------------------------------+
| Sparse matrices | Have good chances of being |
| | implemented, especially taking |
| | into account that scipy have |
| | several implementations to choose|
| | from. |
+------------------------+----------------------------------+
| Full support for | For example, x(x>0.5) = 1 |
| boolean indexing. | works, but y=x>0.5; x(y)=1 |
| Currently, some | does not work. |
| expressions don't work | |
| | |
+------------------------+----------------------------------+
| Command syntax | Too complex to support |
+------------------------+----------------------------------+
| Type, rank and shape | |
| inference | |
+------------------------+----------------------------------+
| Strings | |
+------------------------+----------------------------------+