![]() avoid readtable, readmatrix, et al, which are just complex wrappers around textscan ). If you want to import a large file efficiently then you need to minimize any handling of the imported file data, the optimal solution is to get all of the importing and conversion to numeric performed in one call to one reasonably low-level MATLAB command (i.e.Regardless of what method you use to import it, importing data will take some time.Create a tab-delimited file named num.txt that contains a 4 -by- 4 numeric array and display the contents of the file. Create a sample file, read the entire file, and then read a subset of the file starting at the specified location. data dlmread ('test. This example shows how to import numeric data delimited by any single character using the writematrix function. If this is not the case then you will need to use tall arrays or some other approach to processing your data. You can specify the row and column to start the import. ![]() ![]() Regardless of what method you use to import it, the entire imported file data must fit into MATLAB memory.If you click the Import button, you can also see the generated code or script. you will be able to choose what data types are imported. This is not the case with your data: your file has many small blocks, forcing you to access the file repeatedly and expand the output array many times. csv file you can use the Import Tool which will help you through the import process. Importing the file in blocks is only efficient for a relatively small number of very large data blocks.I would like to have a matrix with my data. Importing as character and then doing any kind of text manipulation before converting to numeric will be very inefficient for a large file. I tried to use csvread but from the forum, it seems that I should use textscan to read the values when there is also text in the csv file: However, I don't understand what to put in argument of the function, especially when it comes to specifiers.Notes to consider when importing a large file:
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