The data type supported by “dim” is a positive integer scalar. The data type for this input is the same as for “a.”ĭim: This input sets the dimension on which the max() function will operate. In cases where max() is sent with an additional array, it must have dimensions compatible with “a”. The type of data supported by this input is scalar, vector, matrix, or multidimensional array.ī: Additional input matrix. We will show you the different modes this function has to get the maximum values in the following examples.īelow we will detail each of the arguments and input flags of the max() function:Ī: This input specifies the input scalar, vector, or matrix. The data types supported by max() are single, double, int8, int16, int32, int64, uint8, uint16, uint32, uint64, logical, categorical, datetime, and duration. The types of input arguments accepted by this function are scalars, vectors, matrices, and multidimensional arrays. When the function is called, these modes are selected by flags, size and dimension vectors. Max() has different modes for processing input and output data.

This function can also return the index of the maximum values sent in “a” and returned in “r”.

The max() function returns in “r” the maximum value among all elements of the array “a”. The same procedure is applied for the number of columns, c, by empty-indexing in the first dimension and summing along that dimension.=max (a,, _, ‘linear’ ) MATLAB max() description and examples Negating and summing this vector gives r. Summing that r × 0 vector along its second dimension ( sum(m(:,),2)) produces a vector of r × 1 zeros. In addition, this empty indexing automatically provides insensitivity to NaN, inf or complex values in m (and probably accounts for the small computation time as well).

Let r and c be the (possibly zero) numbers of rows and columns of m. the fact that summing along an empty dimension gives zeros.empty indexing (that is, indexing with ).The keys to handling empty matrices in a unified way are: It is also very fast: for a 1000 × 1000 matrix it takes about 22 microseconds in my old laptop (a for loop with 1e5 repetitions takes 2.2 seconds, measured with tic, toc). It accepts empty matrices (with 0 columns, 0 rows, or both), as well as complex, NaN or inf values.

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