so essentially I have the task to learn matlab decently well in the next few weeks, and I want to really be able to impress the people i'm learning it for, so if you guys have advice, I would greatly appreciate it.
What I'm dealing with Throughout the course of my job I will be dealing largely in two areas.
Formatting and importing data from excel
Interpreting the data in a meaningful way.
I realize the second category is extremely broad, but essentially i'm working with arrays of pricing information to set some standard price for a commodity, so the analysis that I will be doing will be less computationally heavy and will focus more on error getting the data in correctly and accurately and making sure all of the functions that I want to perform are executed correctly. Very basic stuff.
So here's what I'm looking for:
What are the most important topics so that I can import data from excel into matlab perfectly?
What should I study just to get basic functions down that will be applied to entire matrices/arrays?
What should I study prior to studying anything else to get a firm foundation in the subject? (So I don't make stupid syntax errors, etc.)?
Your help is greatly appreciated :)
The first two things you'll want to learn about are (1) the Matlab GUI and (2) the basics of Matlab syntax. A quick visit to the Getting Started section of the Matlab documentation will do you wonders. It should take you less than a day to get through the basics. Do note that the Matlab documentation is generally excellent, and you should use it often.
Beyond that, there are a number of questions here about importing Excel into Matlab (importing from excel, exporting to excel), and there's some excellent docs on the Mathworks site as well (xlsread, xlswrite). Read them and become familiar with the details and common problems. Good luck!
Since you will be using excel it is likely the data you import could come out in cell format. Look into the differences between indexing using matrices and cells. Also, learn early on the difference between [operator] and .[operator] for vector calculations. The second one is element-wise and will most likely solve a lot of issues you'll come across if your records are meant to only relate to one row/column of data
Perhaps you have gained the MATLAB skills you need now, but hopefully this will help someone following the same path later.
The Math Works (developers of MATLAB) run a site called MATLAB Cody.
This site offers a range of problems and a web based MATLAB interpreter so you can test your solutions. When you have a correct solution, you can compare with other solutions to the same problem. Then you can look up the functions others have used in the online MATLAB documentation for more understanding.
The problems focus on regular expressions and cell manipulation which will be very relevant to importing and manipulating Excel data.
Related
I have an issue, where I need to handle a lot of figures in matlab and the code is starting to get messy. Different kinds of plot objects are added to the code in different stages and some have legends and some does not. The problem is that there is no NULL legends. As soon as an object is created, so is a legend. However, until the legend(handles,...) is called they are not shown. This means that if things are plotted and some, need a legend entry and some not, a lot of handles needs to be passed around.
Now, the file is starting to be quite long, about 1500 lines, with some globals that spans over many functions in the file and so. To prevent the "Do not use globals" comments to pour in, yes I know globals are normally unnecessary, but the code was like that when I laid my hands on it. However, now the code is getting more and more messy and I think about using Object Oriented Programming (OOP) to handle figures.
The idea is to have the custom figure objects handling themselves and thus make more readable code, split up in smaller blocks. The idea is to have a design like
class Figure
private:
MainFrame;
SubFrame;
Lines;
Legends;
Title;
X-Label;
Y-Label;
Methods:
To be defined, for example formatting plotting, edit title,…
The complete design is not really thought through completely, but the point of this questions is really about using OOP in matlab. What I have seen so far it os not really used were much. Are there a reason for this? Could anyone give pros and cons to OOP in matlab? Is OOP recommended or not in matlab?
I have added the information about my issue since I understand that OOP is more needed for large complex issues, so an answer would preferably take the drawbacks in comparison with the complexity of the problem into account. (For example, do never use OOP in matlab, do it only when you have complex problems, do it whenever you like,...)
Okay the question is about OOP in Matlab - but is it not OOP in Matlab in your organisation?
By that I mean to think who is going to use/develop and maintain the code going forward.
Background: I have used OOP for my own toolbox (because its complex/large enough to warrant it - and I develop/maintain it) - however in consultancy jobs for the majority of my clients I create functions (which in some instances call my toolbox) - because when the job is finished they get the source code and the majority are (much) more comfortable working with functions rather than classes.
In summary - I decide on whether to use OOP on the job specifics and the situation where the code will be used (developed & maintained) in the future.
So back to your topic - I would consider where you think the code is going to go and who will develop/maintain it. Will they be comfortable with classes - or will they be more comfortable with functions?
FYI: Last year I was talking to Mathworks and they said that they run multiple "Intro to Matlab" courses per week - but only 1 "Matlab Classes" per quarter!! That gives you an indication on the level of Matlab class use in industry.
I just read a fascinating paper: http://www.psy.cmu.edu/~ckemp/Papers/kempt08.pdf
In my opinion it takes the whole area of machine learning to a completely new level because it flexibly discovers the structure of data (and doesn't only try to find a best fit for an existing structure).
The code is also available: http://www.psy.cmu.edu/~ckemp/code/formdiscovery.html
I tried to do a few experiments of my own - but unfortunately I don't possess Matlab. I tried it with Octave but it only produced all kinds of error messages, which I don't understand (I am no expert on these programs).
Could anybody perhaps have a quick look if these problems can be solved easily (or at all)? Perhaps the solution will be an easy one (this is my hope after all).
This would really be a big help! I am very much looking forward to trying a few data sets of my own.
I didn't look into the source code, but if you are going to convert it, these links might help:
Porting programs from Matlab to Octave
Differences between Octave and MATLAB
I was recently looking for an answer to the same question and found this old post. Just to add my two cents for anyone else looking...
There is an Octave library called Missing Function Library that "Finds functions that are in Matlab but not in Octave". Also, there are a bunch of great packages (read "Toolboxes") for Octave as well on SourceForge. Hope this helps!
I'm trying to write a program in iPhone than can take two audio files (e.g. WAV) as inputs, compare them, and spit out a number that tells you how similar the audio files are.
If someone has done something like this, know how to go about doing it, or just have some ideas, please let me know. Anything will be greatly appreciated.
Specific questions: What language is suitable? How hard is it to do (how many
hours, roughly)? Where can I find a good source of audio library/tools?
Thanks!
I'd say it's pretty hard, not so much the implementation, but coming up with a reasonable definition of 'similar'.
That said, you're probably looking at techniques like autocorrelation and FFT, both of which are CPU-intensive tasks, so I'd say a fully-compiled language (C, C++, don't know about Objective-C) would be most suitable at least for the actual calculations. Also, you're facing a somewhat underpowered platform for such tasks (if only because uncompressed audio files are pretty large), so you're in for quite some optimization.
This book: http://www.dspguide.com/ is quite concise reading for all things DSP-related.
Sounds similar to what 'Shazam' does - awesome iPhone app by the way, check it out if you haven't already (it's free too).
A while ago there was an article on how Shazam works, read it here. It takes an acoustic fingerprint and compares it to other songs' fingerprints, returning the closest match.
I would say there is a lot of math, probably some matrices and maybe Fourier transforms involved in fingerprinting and then trying to compare the audio.
-
Probably would take a good while to program. If your math skills are up to it though, sounds like a good challenge :-)
-
EDIT: turns out there was some source code on the site I linked. It's in Java but would be well worth a look through before you start writing your own. Source code here
I am working on something similar in Java on a speech recognition app.
I would recommend using MFCC (requires calculating FFT) for feature extraction and Neural Networks or some other sort of machine learning technique for training and recognition. You train the NN with the features extracted from the reference wav file, more precisely from consecutive equal lenght slices/windows of that audio file. Then you use the NN to detect if another file, also split into slices, has the same features.
This is the basic idea upon which you can elaborate to further your own specifications, or exactly what you want your app to do.
In terms of libraries in Objective C I think you can find a few for the signal processing part (FFT and such) as for the machine learning part I have no idea about what you could find.
As for programming time it's hard to estimate because it depends on a lot of details. I would say somewhere about a week, but that's just a fair estimation.
ps: MFCC stands for Mel-Frequency Coeficients: http://en.wikipedia.org/wiki/Mel-frequency_cepstrum
I am about to start a project in visual image-processing and have no had experience with Matlab, Aforge, OpenCV and was wondering if anyone had any experiences with these different software packages.
I was also wondering which of the three packages were most efficient I assume OpenCV but has anyone had any experience?
Thanks
Jamie.
The question you need to ask yourself is which is more important - your time or the computer's time. If your task is really simple, you may be able to code it up in MATLAB and have it work right off the bat. MATLAB is by far the easiest for development - a scripted language with built-in memory management, a huge array of provided functions, and a great interface for displaying and manipulating data while debugging.
On the other hand, MATLAB is at least an order of magnitude slower than compiled openCV code for many tasks. This is especially true if you use the intel performance primitives libraries.
If you know how to code in MATLAB, I would suggest writing and debugging your algorithms in that language, then porting them to c/c++ with openCV for speed. If there are only a couple of simple functions that you need to speed up, you can call c code from MATLAB, but it's hard to get this working right the first few times you try it, so you're probably better off just rewriting your finished code entirely in c/c++
First, please elaborate about your project's needs. It has the biggest impact on the choice, in addition to other factors - your general programming knowledge (If you haven't dealt with dot net but just with C++, AForge is not a good choice, for example).
Generally,
Both AForge and OpenCV has a built-in interface to .Net, and OpenCV also with C++, python, and more. Matlab might be more efficient, but if you don't have any experience with it - you should also learn its syntax. Take it into consideration.
Matlab probably has the largest variety of functions, but it is more complicated than the other projects. OpenCV and AForge themselves have some differences - see them described in this StackOverflow question/ answers.
I worked last year in two similar projects with cars on the highway. Afaik, Matlab allows to process only one picture frame at a time (surely you could elaborate an algorithm to compute a stream) but using Simulink you can process the stream directly.
On the other hand, i found AForge a lot friendlier and easier to use since you can easily adjust the processing parameters from a GUI (not so fast/easy) to do in Matlab/simulink.
I'd go for Aforge.Net. It's also fast enough if you're worrying about processing speed. (using 640x480)
If you are asking about using one of these in .net,easily you can get info by this:
1-matlab mostly used in simulation of projects not the End-prototype project; my numer : 30;
2-aforge (as I'v used in many project) if you do not need the circular process like capturing image, or recognition of something in images or ... you'll find it very good, cause it is easy to use but useful for single processes; my number : 50
3-opencv very good at speed and useful for circular processes, for example you can capture images from a webcam and Instantly cartoonize it without any delay, But not easy-to-use as aforge. I like it anyway cause of its speed and MANY functions it gives us mostly anything we need in programming; my number : 80
Dr.Taha - Tahasoft.net
I've been using F# for a while now to model algorithms before coding them in C++, and also using it afterwards to check the results of the C++ code, and also against real-world recorded data.
For the modeling side of things, it's very handy, but for the 'data mashup' kind of stuff, pulling in data from CSV and other sources, generating statistics, drawing charts etc., my colleague teases me no end ("why are you coding that yourself? It's built in to MatLab").
And I have another colleague who swears by R, which also has charting stuff 'built-in'.
I know that MatLab, R and F# are not strictly comparable, so I'm not asking for a 'feature comparison shoot out'. I just wondered what other people are using for these kind of pre- and post-analysis scenarios, and how happy they are with it.
(If there's anyone out there working on wrapping Microsoft Charts into something F#-friendly, let me know, I'd be happy to participate...)
(Note: answers to this question will be subjective, but based on experience, please)
I have very little experience with F#, but regarding C++/Matlab/R: If the speed of your program's execution is the most important, use C++. If speed of implementation is the most important, use Matlab or R. This is true for a number of reasons, not the least of which is their massive libraries of math/stats packages.
Both Matlab and R can be sped up through parallelism: so generally, I think that speed and quality of implementation should be a bigger concern. That's where the real "value" of programming is taking place, in the design of the application. It's not a minor proposition if you can write 3 or 4 good R programs in the same time it takes you to write 1 good C++ program.
Regarding F#: so far as it is part of Microsoft's framework, it must have a lot to offer. If you're developing in Visual Studio or working on a big .Net project (for instance), it might make sense to use F#. On the other hand, you can call both Matlab and R from .Net applications, so I would probably argue that their libraries should be a bigger concern. For instance, see this article as an example for R and the Matlab Builder.
Long story short: comparing F# and Matlab/R isn't a good comparison. F# is a general purpose programming language, while Matlab/R can be viewed as massive mathematical/data analysis toolkits. Some people call Matlab or R from F# in order to take advantage of each language's benefits (e.g. see this discussion, this article on Matlab/F#, or this article on R/F#).
So far as charting is concerned: R is extremely strong on this front. Have a look at the graphics view on CRAN and this series of posts on the LearnR blog about Lattice and ggplot2.
I've worked a bit with matlab and python/pylab for these purposes. What these tools have 'built-in' is a programming environment, a shell, and gui tools designed for quickly looking at data from a variety of sources.
In a few commands, you can go from having a csv file to interactive plots on the screen, then to an image export in just about any format. It takes a minute or two to go from data to visualization once you have the hang of it. I would imagine this is uncommon in the C++ world (although I have seen some professors with pretty impressive work-flows).
I've tried R, but I can't say much useful about it. It seems to offer about the same set of features, but it may be troublesome to Google for support.
If you are spending more than a couple minutes getting from data to plot using your current method, it's definitely worth learning one of these environments. The best choice depends on your colleagues, your work environment, experience, and your budget.
This is a reasonable close double to the previous question on suitable functional language for scientific/statistical computing so you may want to peruse the long and detailed answers there.
Answers depends, as so often, on your experience and prior language training. I very much prefer R for data munging / modeling / visualization.
I use R because on the one hand it has everything built in and on the other hand you can still manipulate almost everything or start from scratch. Nevertheless, R is rather slow for heavy calculations (although I do all my Monte Carlo simulations in it).
I would say that Matlab is best for the availability of mathematical functionalities in general, R is best for data input/manipulation/visualisation/analysis/etc., and C++ for high-speed subroutines. You can by the way easily integrate C++ (or C, fortran, ...) code in R. Why not read and manipulate input data in R, apply the models in C++, and analyse/visualize output back in R?
I always prototype my models in MATLAB. If my prototype is fast enough, I refactor and it's done. If not, I go back and implement certain functions in C to be called by MATLAB. This requires knowledge of a low level language, which I think is always going to be the case if you are doing anything that is technically challenging.
I'm intrigued with this Lisp flavor if it ever gets off the ground.