I run some function which require "optimoptions" function. I run pkg load optim. But when I use the function I get the error
warning: the 'optimoptions' function belongs to the optim package from Octave
Forge but has not yet been implemented.
Please read https://www.octave.org/missing.html to learn how you can
contribute missing functionality.
Related
In the c++ environment, I can use the cvEigenVV command, but I import the opencv module in python, corresponding to which API ?
the error in python: module 'cv2' has no attribute 'cvEigenVV'
I am working with matlab packages and I want to make a package available to all methods in same .m file. I am trying to import the package in main method of .m file and it seems to me that other functions in .m file are unable to access the package. I do not want to import package in all functions and want to avoid this situation. Is there a way to tackle this issue.
In short: no. Unfortunately, in MATLAB you must always use the fully qualified name of a function, even if you're in the same packaged (or else use import statements).
Note that adding the +mypackage directory to the MATLAB path doesn't work - you'll get the warning:
>> addpath +mypackage
Warning: Package directories not allowed in MATLAB path: +mypackage
> In path (line 109)
In addpath (line 88)
When I write this line in Octave:
[b,a] = butter (5,0.2);
I get the error:
error: `butter' undefined near line 1 column 10
How can I get rid of it? Thanks.
Seems that you forgot to load the signal package. You have to install and load it in order to use the butter function:
pkg install -forge signal
pkg load signal
[b,a] = butter (5,0.2);
Please take a look in the Octave documentation. It explains how to install and how to load packages.
The butter function is part of the signal package. You need to download, install and load the package before you can use its functions:
>> pkg install -forge signal
>> pkg load signal
I have a script in matlab that calls other libraries. I use matlab version 2012a on linux . I get below error and I don't know how to fix it.
The error is :
Invalid MEX-file '/home/XXX/nearest_neighbors.mexa64':
libflann.so.1.8: cannot open shared object file: No such file or
directory
Error in flann_search (line 82)
[indices,dists] = nearest_neighbors('find_nn', data, testset, n, params);
Error in MyScript (line 73)
[nresult, ndists] = flann_search(Ntraindata', Ntraindata', resu.KNN, struct('algorithm','composite',...
That library you are referring to - https://github.com/mariusmuja/flann/ - has the nearest_neighbors function written in MEX code. MEX code is C code that is used to interface with MATLAB. People usually write heavily computationally burdening code over in MEX as it is known to handle loops and other things faster. The inputs come from MATLAB and are sent to this MEX function, and the outputs come from the MEX function and are piped back to MATLAB. It's basically a nice black box where you can use it just like any other MATLAB function. In fact, a lot of the functions that come shipped with MATLAB have MEX wrappers written to promote acceleration.
You are getting that error because you need to compile the nearest_neighbors function so that there is a MEX wrapper that can be called in MATLAB. That wrapper is missing because you haven't compiled the code.
First, you need to set up MEX. Make sure you have a compiler that is compatible with your version of MATLAB. You can do that by visiting this link:
http://www.mathworks.com/support/compilers/R20xxy/index.html
xx is the version number that belongs to your MATLAB and y is the character code that comes after it. For example, if you are using R2013a, you would visit:
http://www.mathworks.com/support/compilers/R2013a/index.html
Once you're there, go to your Operating System and ensure you have one of those supported compilers installed. Once you have that installed, go into MATLAB, and in the command prompt, type in:
mex -setup
This will allow you to set up MEX and choose the compiler you want. Given your error, you're using Linux 64-bit, so it should be very easy for you to get GCC. Just make sure that you choose a version of GCC that is compatible with your version of MATLAB. Once you choose the compiler, you can compile the code by doing this in the command prompt:
>> mex -v -O nearest_neighbors.cpp
This should generate the nearest_neighbors MEX file for you. Once that's done, you can now run the code.
For more detailed instructions, check out FLANN's user manual - http://people.cs.ubc.ca/~mariusm/uploads/FLANN/flann_manual-1.8.4.pdf - It tells you how to build and compile it for MATLAB use.
Good luck!
I've inherited a Fortran 77 code which implements several subroutines which are run through a program block which requires a significant amount of user-input via an interactive command prompt every time the program is run. Since I'd like to automate running the code, I moved all the subroutines into a module and wrote a wrapper code through F2PY. Everything works fine after a 2-step compilation:
gfortran -c my_module.f90 -o my_module.o -ffixed-form
f2py -c my_module.o -m my_wrapper my_wrapper.f90
This ultimately creates three files: my_module.o, my_wrapper.o, my_module.mod, and my_wrapper.so. The my_wrapper.so is the module which I import into Python to access the legacy Fortran code.
My goal is to include this code to use in a larger package of scientific codes, which already has a setup.py using distutils to build a Cython module. Totally ignoring the Cython code for the moment, how am I supposed to translate the 2-step build into an extension in the setup.py? The closes I've been able to figure out looks like:
from numpy.distutils.core import setup, Extension
wrapper = Extension('my_wrapper', ['my_wrapper.f90', ])
setup(
libraries = [('my_module', dict(sources=['my_module.f90']],
extra_f90_compile_args=["-ffixed-form", ])))],
ext_modules = [wrapper, ]
)
This doesn't work, though. My compiler throws many warnings on the my_module.f90, but it still compiles (it throws no warnings if I use the compiler invocation above). When it tries to compile the wrapper though, it fails to find the my_module.mod, even though it is successfully created.
Any thoughts? I have a feeling I'm missing something trivial, but the documentation just doesn't seem fleshed out enough to indicate what it might be.
It might be a little late, but your problem is that you are not linking in my_module when building my_wrapper:
wrapper = Extension('my_wrapper', sources=['my_wrapper.f90'], libraries=['my_module'])
setup(
libraries = [('my_module', dict(sources=['my_module.f90'],
extra_f90_compile_args=["-ffixed-form"]))],
ext_modules = [wrapper]
)
If your only use of my_module is for my_wrapper, you could simply add it to the sources of my_wrapper:
wrapper = Extension('my_wrapper', sources=['my_wrapper.f90', 'my_module.f90'],
extra_f90_compile_args=["-ffixed-form"])
setup(
ext_modules = [wrapper]
)
Note that this will also export everything in my_module to Python, which you probably don't want.
I am dealing with such a two-layer library structure outside of Python, using cmake as the top level build system. I have it setup so that make python calls distutils to build the Python wrappers. The setup.pys can safely assume that all external libraries are already built and installed. This strategy is advantageous if one wants to have general-purpose libraries that are installed system-wide, and then wrapped for different applications such as Python, Matlab, Octave, IDL,..., which all have different ways to build extensions.