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SPARSECLEAN - Efficiently cleans a sparse matrix of small values or nan

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SPARSECLEAN - Efficiently cleans a sparse matrix of small values or nan

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14 Mar 2013 (Updated )

SPARSECLEAN cleans a double sparse matrix of small or nan values or values within a range.

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Description

SPARSECLEAN is a mex function intended to clean (remove) small values or values within a range from sparse matrices. The operation can produce a newly allocated matrix or operate on the variable inplace.

Building:

SPARSECLEAN requires that a mex routine be built (one time only). This process is typically self-building the first time you call the function as long as you have the files sparseclean.m and sparseclean.c in the same directory somewhere on the MATLAB path. If you need to manually build the mex function, here are the commands:

 >> mex -setup
   (then follow instructions to select a C or C++ compiler of your choice)
 >> mex sparseclean.c

 The usage is as follows:

 Syntax

  B = sparseclean(A [,true])
      Cleans a sparse matrix of 0's
 
  B = sparseclean(A,tol [,true])
      Cleans a sparse matrix of all abs(A(i)) <= tol
 
  B = sparseclean(A,nan [,true])
      Cleans a sparse matrix of all A(i) that are nan
 
  B = sparseclean(A,nan,value [,true])
      Replaces all A(i) that are nan with value
      If value is complex, then A must also be complex
 
  B = sparseclean(A,lower_tol,upper_tol [,true])
      Cleans a real sparse matrix of all lower_tol <= A(i) <= upper_tol
      Cleans a complex sparse matrix of all lower_tol <= abs(A(i)) <= upper_tol

  Where A = A double sparse matrix
        tol, value, lower_tol, and upper_tol = scalar numeric values
        true = Forces in-place operation even if A is shared
 
 If B is omitted, then A is cleaned in-place. If A is shared or potentially shared because it is a cell element or struct field element or class property, then an error will be thrown for this in-place case unless you add the true argument. That is, adding true at the end will force the in-place syntax to work regardless of whether A is shared or potentially shared. But doing so risks side effects of changing other variables that are sharing data memory with A!

Required Products MATLAB
MATLAB release MATLAB 7.5 (R2007b)
Other requirements Requires a C compiler, such as the built-in lcc compiler. SPARSECLEAN is a self-building mex file ... you don't have to know anything about C or mex to use it.
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Updates
14 Mar 2013

Corrects bugs in some of the nan handling cases.

14 Mar 2013

Fixed bug in complex case with real value.

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