This is a draft cheat sheet. It is a work in progress and is not finished yet.
Naming conventions
Variable names in camel case |
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Functions & methods in camel case |
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Acronyms follow camel case |
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Use meaningful names |
wage = hourlyRate * nHours
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n prefix for amounts |
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No suffix for specific numbers |
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Cnt suffix for iterator variables |
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Constant uppercase + underscore |
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Classes & stuctures capitalized |
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Non-default units in variable name |
BOTTLE_CAPACITY_CL = 50
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Layout
Split lines if needed |
longMethodName(...
long, list, of, params)
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Align for better readability |
value = (10 * nDimes) + ...
(5 * nNickels) + ...
(1 * nPennies);
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Commas are followed by spaces |
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Brackets are NOT surrounded by spaces |
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Separate logical groups of code by a blank line |
Separate functional groups of code by using %%
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Best practices
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Write code as functions when possible The main role of scripts is in development because they provide direct visibility of variables. Functions modularize computation by using internal variables, and tend to be cleaner and more flexible. It is also much easier to manage changes if code appears in only one file.
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Don't (always) use clear all
Whenever Matlab meets new code it pre-compiles it, making re-runs faster. Make sure you don't use clear all
when you meant to use clear
- the former not only clears variables but also the pre-compiled code. |
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Helper functions A single .m file can contain multiple functions. Although only the first function is exposed, this allows for better structuring and reuse of the code.
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Subfunctions It's possible to nest functions, allowing for better structuring while strongly associating the subfunction with it parent.
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Comments
Write comments only when needed |
For comments after code, prefix '␣␣%␣' |
SAMPLE_FREQ = 3e9 % Hz
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Align for better readability |
var = 1; % Comment
otherVar = 2; % Other comment
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Documentation
Class header gives a description of the class and a summary of all its functions |
Function headers give information about the inputs & outputs |
Include a demo file for non-trivial classes and functions |
Speed-ups
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Preallocation Allocate empty matrices to store incremental results generated by loops. If the number of results is unknown, you can allocate the for maximum amount and prune afterward (if possible).
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Vectorization Placing a period (.) before the operators *, /, and ^, transforms them into array operators. Some functions also accept vectors/matrices as input and perform their computations on element/row-wise. Example t = 0:.01:10;
y = sin(t);
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Indexing Use vector or boolean indexing instead of loops where possible Example someNumbers(someNumbers < 0) = 0;
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Profiler To determine which parts of your code are the most time consuming use the tic toc
, timeit
, or profile
commands. |
Workflow
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Create a new branch for your feature git checkout -b featurename
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Use git as you normally would git add file1.m file2.m
git commit -m "message"
git pull origin featurename
git push origin featurename
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Regularly merge the master branch into the feature branch (git checkout featurename)
git fetch origin
git merge origin/master
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One the feature is completed, file a merge request on GitLab. If your request if rejected.
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Sources
Guidelines for writing clean and fast code in MATLAB - Nico Schlömer |
MATLAB Style Guidelines 2.0 - Richard Johnson |
The Elements of MATLAB Style - Richard Johnson |
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