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This module helps you plot confusion matrices or similar images where the axis labels do not have a natural order. So, the probability of confusing two phonemes is a perfect example: phonemes do not naturally fall onto a 1dimensional sequence, so one is free to put them in any order one likes. Given that, one might as well put them into an order that reveals something interesting about the probabilities.
All the functions ending in "2" work on rectangular arrays. All the functions without "2" work only on square arrays, and they assume that that both axes remain in the same order.
Classes  
diagfom A class that defines a figureofmerit for a matrix. 

diagfom2 This tries to make your matrix approximately diagonal for rectangular matrices. 

blockfom This tries to make your matrix into a block form. 
Functions  




tuple(numpy.ndarray, list(something))



tuple(numpy.ndarray, list(something))



tuple(numpy.ndarray, list(something), list(something))







tuple(numpy.ndarray, list(something), list(something))



tuple(numpy.ndarray) , list(something))






Variables  
__package__ =

Imports: numpy, die, blue_data_selector
Function Details 
Used internally. Finds an ordering of the labels that minimizes
whatever 
Used internally. Finds an ordering of the labels that minimizes
whatever 
Swap the rows and columns of a matrix to bring it closer to a diagonal matrix: i.e. entries with large absolute values on the main diagonal and small entries away from the main diagonal. Rows and columns are swapped together, so that the ordering or rows will match the ordering of columns.

Swap the rows and columns of a matrix to put the most positive values on the main diagonal. Rows and columns are swapped together, so that the ordering or rows will match the ordering of columns.

Swap the rows and columns of a matrix to make it roughly diagonal: i.e. large entries on the main diagonal and small entries away from the main diagonal. Note that this will work even if the matrix is not square.

Swap rows and columns of a matrix to bring it closer to a block form, where similar values occur together in blocks.

Swap rows and columns of a matrix to bring it closer to a block form, where similar values occur together in blocks. It minimizes the sum of changes when proceeding along a row or column.

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