Say you have a 100 element vector representing 10 time steps of 10 sensor measurements. Reshaping Vectors to MatricesĬonverting a long vector to a matrix is a common task. Now let‘s walk through some practical examples. This sets dimension 1 to length 3, and dimension 2 to an automatically calculated size that retains all elements. You can also set a dimension to for automatic size calculation: B = reshape(A, ]) sz1… szN define sizes for each dimension.The reshape() function uses this syntax: B = reshape(A,sz)

Let‘s get reshaping! The Syntax for Reshape() This totals transforms an array while retaining the underlying data buffer.Īlright, enough background. The main unique capability of reshape() is directly specifying a new size and dimension count. Shiftdim() – Shifts dimensions position without changing data Squeeze() – Removes singleton dimensions from arrays Compare Reshape() to Similar Functionsīefore going further, it‘s useful to understand how reshape() differs from related MATLAB functions: The reshape() function handles these jobs quickly while preserving all the element values.įortunately, MATLAB makes inspection and manipulation of array internals easy. Flattening then expanding classification training data for neural networks.Combining image color channels into depth x width x channels cubes.Rearranging a time-series from a long vector into a matrix matching time steps x features.Here are some common scenarios where reshaping facilitates the next steps: It‘s a similar story for image processing, plotting geospatial data, generating 3D meshes… the list goes on.

For example, machine learning models typically want feature data formatted as a 2D matrix. The short answer – your analysis and algorithms will often expect specific input shapes and orientations.

Why Reshaping Data Structures Mattersīefore diving into syntax details, let‘s talk about why you‘d want to reshape data. In this comprehensive, beginner-friendly guide, we‘ll explore how the powerful reshape() function gives you flexibility to transform MATLAB matrices and vectors to suit your needs. So reshaping arrays with MATLAB is an essential skill. But data doesn‘t always come in the exact structure we need. Working with matrices and vectors is crucial for data analysis and machine learning applications.

Reshape vector to matrix matlab