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That’s easy to see for this example, but how do you compute linear indices in general? MATLAB has many string array functions that return logical arrays, such as contains, startsWith, and matches. The output is always in the form of a column vector. Another indexing variation, logical indexing, is a compact and expressive notation that’s useful in many applications, including image processing. In this example, the computation is two-dimensional filtering using filter2. We hope that these examples in the article give you a feel for ways you can express algorithms compactly and efficiently. 12) extracts the matrix elements corresponding to the nonzero values of the logical array. You can use these to operate on text using logical indexing. MATLAB provides a function called sub2ind that converts from row and column subscripts to linear indices. For example, suppose you want to temporarily replace NaN values with zeros, perform some computation, and then put the NaN values back in their original locations. 5)). The logical indexing expression is faster for simple cases, but you might use find if you need the index values for something else in the computation. Logical indexing is closely related to the find function. Including these techniques and related functions in your MATLAB programming repertoire expands your ability to create concise, readable, and vectorized code. For example, you could replace all the NaN elements in an array with another value by using a combination of isnan, logical indexing, and scalar expansion with one line of code. Many MATLAB functions that start with is return logical arrays and are very useful for logical indexing. In logical indexing, you use a single, logical array for the matrix subscript.