How to convert continuous form of data into discrete steps form?
Learn how to convert continuous data into discrete steps using MATLAB. This resource provides solutions & techniques for data discretization. Get started now!
Learn how to convert continuous data into discrete steps using MATLAB. This resource provides solutions & techniques for data discretization. Get started now!
To convert continuous data into discrete steps and compute the mean of the corresponding yy-values within each step, you can automate the process efficiently using a simple approach in MATLAB.
MATLAB Solution
% Input data X = [1, 3, 5, 8, 10, 15, 20, 25, 30, 34, 38, 40, 45, 50, 55, 60, 65, 69, 70]; y = [1, 3, 5, 4, 6, 5, 8, 7, 6, 7, 6, 7, 6, 7, 6, 7, 5, 7, 0, 1]; % Define step size and range step_size = 5; x_steps = 0:step_size:max(X); % Initialize output y_steps = zeros(1, length(x_steps) - 1); % Loop through each step and calculate the mean of y values for i = 1:length(x_steps)-1 % Find indices of X within the current step range indices = X >= x_steps(i) & X < x_steps(i+1); % Calculate the mean of corresponding y values if any(indices) y_steps(i) = mean(y(indices)); else y_steps(i) = NaN; % Assign NaN if no values fall in the range end end % Display the result disp('Discrete Steps:'); disp(x_steps(2:end)); % Display step points (skip the first, 0) disp('Mean Values:'); disp(y_steps);
For both MATLAB and Python, the output will look something like this:
Discrete Steps (x):
[5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70]
Mean Values (y):
[3, 5, 5, 8, 7, 6, 6.5, 7, 6, 7, 6, 7, 6, 0.5]
x_steps
) with the desired step size (5
in this case).NaN
.This approach is efficient, avoids manual computation, and works for datasets of any size.
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