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Victor Alencar edited this page Nov 11, 2023 · 12 revisions

Understanding the MATRIX Format

The MATRIX Format is a structured way to represent data in matrix form within a file, typically with a .matrix extension. This format is particularly useful for representing complex data in a structured, tabular form. In this tutorial, we'll explore how to read and interpret the MATRIX Format.

File Structure

A .matrix file can contain multiple matrices, each defined between BEGIN MATRIX and END MATRIX descriptors. Within these descriptors, data is organized into rows and columns, separated by tabs (TAB).

Matrix Definition

  • Begin and End: Each matrix starts with BEGIN MATRIX and ends with END MATRIX.
  • Matrix Identification: The first cell of a matrix (at position 0,0) contains the matrix name, following the format: <Matrix Identifier> (<Row Identifier>/<Column Identifier>).
  • Column Labels: The first row, starting from position 0,1 (second cell), contains column labels.
  • Row Labels: The first column, starting from position 1,0 (second row, first cell), contains row labels.
  • Data Values: The cell values of the matrix start from position 1,1 and are filled row-wise.

Example

Consider the following example of a MATRIX Format file:

BEGIN MATRIX
WGB (En/Ac) Mashing Boiling Fermentation
Water 4 2 1
Barley 2 6 3
Wort   2 4 9
Hopped_Wort 10 10 10
END MATRIX

BEGIN MATRIX
USD (Ac/En) Water Barley Wort Hopped_Wort
Mashing 4 2 2 10
Boiling 2 6 4 10
Fermentation   1 3 9 10
END MATRIX

Analysis

  • First Matrix (WGB)

    • Name: WGB (En/Ac)
    • Dimensions: 4x3
    • Row Labels: Water, Barley, Wort, Hopped_Wort
    • Column Labels: Mashing, Boiling, Fermentation
    • Data: Starts from second row and second column.

  • Second Matrix (USD)

    • Name: USD (Ac/En)
    • Dimensions: 3x4
    • Row Labels: Water, Barley, Wort, Hopped_Wort
    • Column Labels: Mashing, Boiling, Fermentation
    • Data: As above.

Conclusion

The MATRIX Format is a versatile way to represent matrices in a text file. Understanding this format is crucial for efficiently processing and analyzing complex datasets in matrix form.

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