Block passing in MATLAB refers to the process of passing an entire block of data, such as an array or matrix, to a function or subroutine, rather than passing individual elements one at a time. Block passing is a more efficient way of passing multiple elements of data to a function and can greatly improve the performance of your MATLAB code.
Here's an example of how to use block passing in MATLAB:
Let's say you want to calculate the mean, median, and maximum value of a 2D array of data using MATLAB's built-in functions. You could do it like this:
data = [1 2 3; 4 5 6; 7 8 9];
% Calculate the mean of the entire array
mean_value = mean(data(:));
% Calculate the median of each row
median_values = median(data, 2);
% Calculate the maximum value of each column
max_values = max(data);
This code works fine for small arrays, but for large arrays, it can be slow because it involves passing each individual element of the array to the functions. A faster way is to use block passing. Here's how you can do it:
data = [1 2 3; 4 5 6; 7 8 9];
% Calculate the mean of the entire array using block passing
mean_value = mean(data(:));
% Calculate the median and maximum values using block passing
[median_values, max_values] = blockproc(data, [1 size(data, 2)], @(b) [median(b.data, 2); max(b.data)]);
In the above example, we used the blockproc function to pass the entire array to the functions. The second argument to blockproc specifies the block size: [1 size(data, 2)] means we want to process one row at a time. The third argument is a function handle that specifies what to do with each block of data. In this case, we want to calculate the median and maximum values for each row of the input array, so we used the functions median and max inside the function handle. The output of the function handle is a column vector of the median values and a row vector of the maximum values for each block.
By using block passing, we can process large arrays more efficiently, resulting in faster code execution.