I'm using Octave right now, but earlier I had used MatLab. In MatLab there is a function ord2 and according to this document (http://www.obihiro.ac.jp/~suzukim/masuda/octave/html3/octave_159.html/) it should also exist in Octave. Could anyone help me with this issue, since I'm new in Octave. How can I import or in other way use 'ord2' function (second-ordered system).
The documentation you mention is for Octave 3.0 which is a very very old version. All of Control functions, together with Finance and Quaternion, were removed from core Octave with release 3.2. If you see the news for Octave 3.2 (if you have a very recent version, this may be in one of the old news file:
** The Control, Finance and Quaternion functions have been removed.
These functions are now available as separate packages from
http://octave.sourceforge.net/packages.html
and can be reinstalled using the Octave package manager (see
the pkg function).
As it is mentioned, you can download the packages from Octave Forge website but depending on your operating system, you may be better off use your package manager.
Finally, the ord2 function does not actually exist in the control package and I'm even unsure that the version you are referring to in Octave 3.0 was even Matlab compatible. However, you can still see its source online right before it was removed.
Related
I’m having a problem with printing figures in octave when the figure’s visibility is set to false. For example, the following code produces a “panic: segmentation fault” in Octave version 4.2.2:
t = 1:10;
fh = figure(“visible”, false);
plot(t,sin(t))
print(“fig.png”)
If I run the above code in Octave version 5.2.0, there is no problem. Is this a bug that was fixed in the Octave 5 update? If so, is there a workaround that I can use for Octave 4? I would prefer to use Octave 4 if possible.
Other notes:
I am running this in Ubuntu 16.04.6 LTS and I installed octave 4 using apt.
The answer to your question is, yes. Here is the relevant line from the v5.1.0 NEWS:
Dependencies:
The GUI requires Qt libraries. The minimum Qt4 version supported is Qt4.8. Qt5 of any version is preferred.
The OSMesa library is no longer used. To print invisible figures when using OpenGL graphics, the Qt QOFFSCREENSURFACE feature must be available and you must use the qt graphics toolkit.
Apparently the now deprecated OSMESA dependency and the printing of invisible figures was a long-standing pain-in-the-butt. Maybe you'll have some luck going through bug comments (e.g. someone says that if you make it visible at least once, it may be possible to print).
But as people have said in the comments, the best thing to do would be to upgrade your octave version, and recompile your mexfiles for the new version.
I would like to identify all functions needed to run a specific function in octave. I need this to deploy an application written in Octave.
While Matlab offers some tools to analyse a function on its dependencies, I could not find something similar for Octave.
Trying inmem as recommended in matlab does not produce the expected result:
> inmem
warning: the 'inmem' function is not yet implemented in Octave
Is there any other solution to this problem available?
First, let me point out that from your description, the matlab tool you're after is not inmem, but deprpt.
Secondly, while octave does not have a built-in tool for this, there is a number of ways to do so yourself. I have not tried these personally, so, ymmv.
1) Run your function while using the profiler, then inspect the functions used during the running process. As suggested in the octave archives: https://lists.gnu.org/archive/html/help-octave/2015-10/msg00135.html
2) There are some external tools on github that attempt just this, e.g. :
https://git.osuv.de/m/about
https://github.com/KaeroDot/mDepGen
3) If I had to attack this myself, I would approach the problem as follows:
Parse and tokenise the m-file in question. (possibly also use binary checks like isvarname to further filter useless tokens before moving to the next step.)
For each token x, wrap a "help(x)" call to a try / catch block
Inspect the error, this will be one of:
"Invalid input" (i.e. token was not a function)
"Not found" (i.e. not a valid identifier etc)
"Not documented" (function exists but has no help string)
No error, in which case you stumbled upon a valid function call within the file
To further check if these are builtin functions or part of a loaded package, you could further parse the first line of the "help" output, which typically tells you where this function came from.
If the context for this is that you're trying to check if a matlab script will work on octave, one complication will be that typically packages that will be required on octave are not present in matlab code. Then again, if this is your goal, you should probably be using deprpt from matlab directly instead.
Good luck.
PS. I might add that the above is for creating a general tool etc. In terms of identifying dependencies in your own code, good software engineering practices go a long way towards providing maintenable code and easily resolving dependency problems for your users. E.g: -- clearly identifying required packages (which, unlike matlab, octave does anyway by requiring such packages to be visibly loaded in code) -- similarly, for custom dependencies, consider wrapping and providing these as packages / namespaces, rather than scattered files -- if packaging dependencies isn't possible, you can create tests / checks in your file that throw errors if necessary files are missing, or at least mention such dependencies in comments in the file itself, etc.
According to Octave Compatibility FAQ here,
Q. inmem
A. who -functions
You can use who -function. (Note: I have not tried yet.)
I have a Cython extension which I've compiled on Ubuntu 14 and uploaded as an Anaconda package. I'm trying to install the package on another machine which is running Scientific Linux (6?) which ships with an older version of glibc. When I try to import the module I get an error that looks (something like) this:
./myprogram: /lib/libc.so.6: version `GLIBC_2.14' not found (required by ./myprogram)
When I say "something like" - the "myprogram" is actually the .so name of the extension.
From what I understand this error is because I have a newer version of glibc on the build system which has an updated version of the memcpy function.
This page has a good description of the problem, and some rather impractical solutions: http://www.lightofdawn.org/wiki/wiki.cgi/NewAppsOnOldGlibc
There is also a much simpler answer proposed here: How can I link to a specific glibc version?
My question is: how to I apply this solution to my Cython extension? Assuming the __asm__ solution works (as given in the second link) what's the best way to get it into the C generated by Cython?
Also, more generally, how to other modules avoid this issue in the first place? For example, I installed and ran a pre-built copy of numpy without any issues.
This turned out to be quite simple.
Create the following header, glibc_fix.h:
__asm__(".symver memcpy,memcpy#GLIBC_2.2.5")
Then include it by using CFLAGS="-include glibc_fix.h". This can be set as an environment variable, or defined in setup.py.
Additionally, it turns out numpy doesn't do anything special in this regard. if I compile it myself it links with the newer version on my system.
I've just started using IPython for interactive development and exploratory research, which I've found really exciting with all the cool features and possibilities. I am using the Anaconda package manager to manage dependencies, which includes IPython.
From what I've read, one goal of the IPython team is to eventually integrate Sage Math (CAS) into IPython, as a cell magic. Does anyone know if this is still under development? Or rather, if I wanted to use Sage now, is writing an extension the only way to do this [1]?
[1] https://github.com/ipython/ipython/wiki/Extensions-Index
Also, if I install additional packages for scientific development, not included in the Anaconda distribution, is that as easy as just pip or do I have to go through a Anaconda package build to handle dependencies and such? If I were only using IPython, I could understand just doing easy_install or pip as recommended in the docs, but I believe that overwrites existing dependencies within Anaconda. If I use pip, how does that affect Anaconda dependencies if I do not install in an Anaconda environment, which I take is the equivalent as virtualenv.py, and is this the way to also set up revision control (i.e. Mercurial)?
To clarify, I do not want to run IPython from within Sage, I want to run Sage, as a CAS, from within IPython. I'd rather go the Sage approach of integrating domain specific languages. Or in contrast, will IPython extensions replace Sage?
I'm a self taught programmer, not a professional software developer. As an engineer, I am used to Matlab, Mathematica, and commercial solutions, that allow me to abstract away the plumbing. I'm trying to wrap my mind around getting everything glued together, but it's like a mix of spaghetti soup and a dynamic link library, due to lack of knowledge. I'm probably using the wrong approach.
What I want is Anaconda/Enthought package management (IPython, pandas, etc..), custom rolled Sage through hooks/extensions or magics, extensions to packages not included in Anaconda (i.e. Matlab see [1] above), and revision control with Git and Mercurial. How would professional developers set this up on a Mac or Linux box?
Answering the first question:
Sage is a huge collection of mathematical software, including IPython. There's no way we'd integrate all of that into IPython.
Possibly what you've heard is that we're going to integrate Sage-style 'interacts' into IPython. That's where you have a slider to control the value of some input variable, and the output updates as you move it around, based on a calculation written in Python. That is still on our roadmap to add to IPython.
Another possibility is that you're thinking of SymPy, a Python-based CAS. SymPy works well within IPython, especially if you call sympy.init_printing() to get the fancy representations of expressions.
I wrote an IPython extension to load Sage customizations into the IPython notebook---in fact, that's how many of the customizations to IPython are done for the normal Sage interface. It basically turns the IPython notebook into an interface to Sage (e.g., preparsing is done, etc.).
You do need to run it from Sage's copy of IPython, though. Just start the IPython notebook:
sage -ipython notebook
and then load the sage extension in a cell:
%load_ext sage.misc.sage_extension
Pretty soon we'll upgrade to IPython 1.0 (I've made the changes necessary, and it needs to be reviewed). If you want to run IPython 1.0 already, email the sage-support mailing list and I'll post instructions.
To answer your other question, Sage includes many packages that are not available in Anaconda. Sage depends on these packages heavily for many features. I suppose there is a possibility getting Sage and its dependencies distributed with something like Anaconda, but no one is working on that as far as I know. There is some work on packaging Sage up for different linux distributions and replacing the package manager for Sage.
To clarify, I do not want to run Ipython from within Sage, I want to run Sage, as a CAS, from within Ipython. I'd rather go the Sage approach of integrating domain specific languages. Or in contrast, will Ipython extensions replace Sage?
If you want to run Sage within Ipython, the easiest thing to do is to use Sage's copy of Ipython:
$ sage -ipython
Python 2.7.5 (default, Aug 1 2013, 18:11:00)
Type "copyright", "credits" or "license" for more information.
IPython 0.13.1 -- An enhanced Interactive Python.
? -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help -> Python's own help system.
object? -> Details about 'object', use 'object??' for extra details.
In [1]: from sage.all import *
In [2]: integrate(x^2,x)
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
<ipython-input-2-006357f5d9c0> in <module>()
----> 1 integrate(x^2,x)
NameError: name 'x' is not defined
In [3]: var('x')
Out[3]: x
In [4]: integrate(x^2,x)
---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
<ipython-input-4-006357f5d9c0> in <module>()
----> 1 integrate(x^2,x)
/Users/.../sage-5.11.rc0/local/lib/python2.7/site-packages/sage/structure/element.so in sage.structure.element.Element.__xor__ (sage/structure/element.c:6754)()
RuntimeError: Use ** for exponentiation, not '^', which means xor
in Python, and has the wrong precedence.
In [5]: integrate(x**2,x)
Out[5]: 1/3*x^3
Note that there are some differences between this and Sage - for instance, there is no preparsing of the syntax. Presumably if you had Sage someplace your own installation of Ipython can find it, you could do this there too (though there is no easy_install and the Python versions might not match correctly!).
Please observe that Sage, as it currently is and should be in the near future, is a huge package that runs in POSIX (Linux-like) OSes only. If you intend it to run in Windows you must use VirtualBox with Sage running under a VM.
If you want a simple CAS that is simple to install and runs everywhere that Python does, you should consider taking a look at Sympy. It doesn't interact with all the software that Sage does, but is simple to use, lightweight (no external libraries needed) and is already included in the base Anaconda distribution.
Besides, it can be easily used inside other Python programs, since it's just like any other module and doesn't make changes to the Python syntax.
In order to distribute a function I've written that depends on other functions I've written that have their own dependencies and so on without distributing every m-file I have ever written, I need to figure out what the full list of dependencies is for a given m-file. Is there a built-in/freely downloadable way to do this?
Specifically I am interested in solutions for MATLAB 7.4.0 (R2007a), but if there is a different way to do it in older versions, by all means please add them here.
For newer releases of Matlab (eg 2007 or 2008) you could use the built in functions:
mlint
dependency report and
coverage report
Another option is to use Matlab's profiler. The command is profile, it can also be used to track dependencies. To use profile, you could do
>> profile on % turn profiling on
>> foo; % entry point to your matlab function or script
>> profile off % turn profiling off
>> profview % view the report
If profiler is not available, then perhaps the following two functions are (for pre-MATLAB 2015a):
depfun
depdir
For example,
>> deps = depfun('foo');
gives a structure, deps, that contains all the dependencies of foo.m.
From answers 2, and 3, newer versions of MATLAB (post 2015a) use matlab.codetools.requiredFilesAndProducts instead.
See answers
EDIT:
Caveats thanks to #Mike Katz comments
Remember that the Profiler will only
show you files that were actually used
in those runs, so if you don't go
through every branch, you may have
additional dependencies. The
dependency report is a good tool, but
only resolves static dependencies on
the path and just for the files in a
single directory.
Depfun is more reliable but gives you
every possible thing it can think of,
and still misses LOAD's and EVAL's.
For MATLAB 2015a and later you should preferably look at matlab.codetools.requiredFilesAndProducts
or doc matlab.codetools.requiredFilesAndProducts
because depfun is marked to be removed in a future release.