Original blog illustration by Cali Rossi
Before we move back to Matlab, I am very happy to announce, for the new year, that Matlabtips.com got itself a professional illustrator. We are now well equipped to fulfill our mission : Make learning Matlab easy and entertaining. Among my resolutions for new year, there is one to make tons of new posts (illustrated this time with original drawings!).
As I discussed already several times, Matlab has supposedly no real equivalent to the C pointer available to you. This is so due to a design choice from Mathworks. The entire language is organized to avoid pointers. Even so, there are occasions where a pointer is really what we need, like when you are dealing with very large datasets that take nearly the entire memory. In this post, I first introduce you to the world of pointer and then shows you how to use them in Matlab for real. Continue reading
Today I am going to present a technique that I have used extensively to deal with figures. I have never seen it named before or even presented anywhere on the web so I decided to call it “Child Swapping” (edit : Yair from Undocumentedmatlab rightfully pointed out that this technique is often called re-parenting. I like my own name too though so I kept the post title). I believe this technique is very useful when you have to manipulate figure windows, reuse them in a different context or concatenate them together. So if I managed to tickle your curiosity, read on. Continue reading
In this post, I talk about the two heterogenous containers that are available to you in Matlab, the structure and the cell. I explain when you probably want to use one or the other and when you probably should not. As often, I end with some ideas for little more advanced programmers on how to combine cell and structures together.
I want to thank all that attended our Poster in New Orleans. It was fantastic to feel that our enthusiast for SpikeE was shared among so many labs. I set up a mailing list to keep anyone update on the development of SpikeE. It is a google group. Anyone is free to join. I am looking forward to see how SpikeE performs and realize this vision of a plateform to easily share code between programmers and non-expert users in many labs.
This is a post for all Neurosciences folks that are attending the Society for Neuroscience 2012 meeting at New Orleans. I (along with some of my lab colleagues) will be presenting SpikeE (SpikeExtractor) over there. SpikeE is a general Matlab framework to perform data analysis on imaging data. But it is also a complete developing environment for Matlab programmers to develop elementary pieces of computations that can be batch process on large datasets. It provides all the tools to only focus on your particular computational task and forget about developing all time consuming steps (like data loading, saving or visualization).
Matlab was designed for dealing with numbers, not strings. As opposed to Python, which is an expert at string, Matlab could look sort of limited in this domain. Still you can do many things to manipulate this element. The goal of this post is to introduce you to the usage of strings in Matlab and to help you loosen the knot…
In this post, I talk about how to store very very large datasets on hard drive. I also talk about some semi-documented features of Matlab storage file, the MAT file and discuss the usage of HDF5 files that can store TeraBytes of data (and more) in a single file.