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Categories
- ►Learning Matlab
- ►Making interfaces
- ▼Optimizing your code
- Choose your variables wisely...
- Code is poetry
- Columns and Rows are not the same
- Copy on Write
- Copy on Write in subfunctions
- How to load Tiff stacks fast, really fast!
- Inline your lines
- Look for the loop
- Mathworks has listened to our TIFF prays!
- Matlab is no longer slow at for loops
- On fractal graphics
- Preallocation is not an option
- Some places, some rules
- The art of vectorizing - Part 1
- The art of vectorizing - Part 2
- The art of vectorizing - Part 3
- The secret rule for good Matlab code
- Using pointers in Matlab
- Waiting for the waitbar
- What happen at my place, stays at my place
- What's the difference between AND and AND AND?
- ►Annoyances
- ►Various
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Category Archives: Optimizing your code
Using pointers in Matlab
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
Posted in Advanced, Optimizing your code
3 Comments
Mathworks has listened to our TIFF prays!
I just want to leave a short note : Mathworks just released a new version of their Tiff libraries to improve performance on all Matlab since 2009b with Tiffs! Continue reading
Posted in Annoyances, Optimizing your code
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The art of vectorizing – Part 3
Following the last post on using repmat to avoid unnecessary for loops, I introduce bsxfun which is a faster alternative to repmat. Continue reading
Posted in Intermediate, Optimizing your code
6 Comments
The art of vectorizing – Part 2
In a previous post, I introduced you how to vectorize your code. Here I show how to use repmat to process series of elements all at once. Continue reading
Posted in Intermediate, Optimizing your code
6 Comments
The art of vectorizing – Part 1
Vectorizing is the art of transforming a calculation done element by element into an operation on vectors. Here I start a serie of posts on how to vectorize your code. Continue reading
Posted in Beginners, Optimizing your code
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Preallocation is not an option
As any activity, programming does require that you follow some rules of good practice. In this post, I introduce you to the joy of memory preallocation. Continue reading
Posted in Beginners, Optimizing your code
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Matlab is no longer slow at for loops
Here, I discuss the most widespread piece of knowledge on Matlab : its inherent slowness with for loop. I demonstrate that it is no longer the case, explain why, and discuss some of the consequences of this fact. Continue reading
Posted in Intermediate, Optimizing your code
4 Comments
