When data from a Simulink simulation is imported into the MATLAB workspace, it often comes in the form of a Simulink.SimulationData.Dataset or a cell array, especially if you're logging signals with the "To Workspace" block or using signal logging.
Here are a few approaches:
Convert to a Matrix or Array: If the data in each cell is numeric and of the same size and type, you can concatenate them into a matrix:
% Concatenate all numeric data from the cell array into a matrix
matrixData = cat(1, simData{:});
Convert to a Table: If the data represents different variables, a table might be a good way to store the data:
% Convert the cell array to a table
tableData = cell2table(simData);
Convert to a Structured Array: If the data in each cell is a struct with the same fields, you can convert the cell array of structs to a structured array:
% Assuming each cell contains a struct with the same fields
structuredArray = [simData{:}];
Convert to a Time Series Object: If the data is time-series data, you might want to convert it to a timeseries object or an array of timeseries objects.
% Create an array of timeseries objects if each cell contains one timeseries
timeSeriesArray = cell2mat(simData);
Extract Specific Fields: If each cell contains a complex object (like a Simulink.SimulationData.Dataset), and you're only interested in specific fields, you could extract those:
% For example, if you only want the 'signals' field from a Dataset
extractedData = cellfun(@(c) c.signals, simData, 'UniformOutput', false);
% Now extractedData is a cell array of 'signals' fields
% You can further process this to extract exactly what you need
Deal with Varying Sizes: If the sizes of the data in each cell vary, you might need to deal with them on a case-by-case basis or use cell arrays of varying sizes.
To convert the data from a cell array to individual variables in the MATLAB workspace, you can iterate over the cell array and assign each cell's contents to a unique variable. Here's an example of how to do this:
% Assuming 'simData' is your cell array from Simulink
for k = 1:length(simData)
% Create a variable name based on the cell index
varName = sprintf('simData%d', k);
% Assign the cell's contents to a variable in the base workspace
assignin('base', varName, simData{k});
end
This script will create variables named simData1, simData2, and so on, each containing the data from the corresponding cell of simData.
If the cell array contains timeseries or Simulink.SimulationData.Dataset objects, and you want to extract just the numerical data, you would need to handle each case appropriately. For instance, if simData{k} is a timeseries object:
for k = 1:length(simData)
if isa(simData{k}, 'timeseries')
% Extract the data and time from the timeseries object
data = simData{k}.Data;
time = simData{k}.Time;
% Create variable names
dataVarName = sprintf('simData%d_Data', k);
timeVarName = sprintf('simData%d_Time', k);
% Assign to variables in the base workspace
assignin('base', dataVarName, data);
assignin('base', timeVarName, time);
elseif isa(simData{k}, 'Simulink.SimulationData.Dataset')
% Handle Dataset case
% ...
else
% Handle other cases or throw an error
error('Unsupported data type in cell array.');
end
end
This will create pairs of variables for each timeseries object: one for the data and one for the time values.
Note that using assignin is generally discouraged because it can lead to code that is hard to debug and maintain. It's usually better to work with structured data types like structures, tables, or classes that encapsulate the related data. However, if you really need separate variables in the workspace, assignin is one way to accomplish that.
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