Programmer Guide/Command Reference/EVAL/mapmind: Difference between revisions

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This function implements a non-linear alignment algorithm for two parameter sets (each defined by a vector or matrix). The method minimizes the accumulated Euclidean distance of the two sets. The result is a two column matrix containing the index map of the alignment. The function also implements a method to create a mapped-copy of the sets.
This function implements a non-linear alignment algorithm for two parameter sets (each defined by a vector or matrix). The method minimizes the accumulated Euclidean distance of the two sets. The result is a two column matrix containing the index map of the alignment. The function also implements a method to create a mapped-copy of the sets.
----
;Usage 1:<code>mapmind(0, <var>a</var>, <var>b</var>)</code>
;Usage 1:<code>mapmind(0, <var>a</var>, <var>b</var>)</code>
:;<var>a, b</var>:Are vectors are matrices containing the two parameter sets;
:;<var>a, b</var>:Are vectors are matrices containing the two parameter sets;
:::<code>nrow(''a'')>2, nrow(''b'')>2, ncol(''a'') = ncol(''b'')</code>
:::<code>nrow(''a'')>2, nrow(''b'')>2, ncol(''a'') = ncol(''b'')</code>
::Each row of ''a''/''b'' defines one parameter value or vector (e.g. for a frame).
::Each row of ''a''/''b'' defines one parameter value or vector (e.g. for a frame).
 
;Result:A matrix Nx2 defining the map of the row indices of ''a'' and ''b'' with the minimum distance matrix. The first column contains the indices for ''a'' and the second column the indices for ''b''.
=====Result:=====
:Note:To minimize the distance, individual rows of ''a'' or ''b'' are duplicated. Therefore the number of rows of the result matrix N is greater than or equal to <code>max(nrow(''a''),nrow(''b'')</code>.
 
----
An index map for vectors a and b with the minimum distance matrix with 2 columns, 1st column is index(a), 2nd column = index(b).
;Usage 2:<code>mapmind(1, <var>m</var>, <var>x</var>)</code>
 
:;<var>m</var>:A vector containing the index map for ''x'';
The number of rows is the length of the aligned path
:;<var>x</var>:A vector or matrix containing the parameter set to remap.
 
;Result 2:A vector or matrix ''r'' containing the remapped parameter set ''x''. The number of rows of ''r'' is equal to <code>nrow(''m'')</code> and the number of columns equals <code>ncol(''x'')</code>. The content of the output row <code>''r''[i,*]</code> is a copy of the input row <code>''x[''m''[i],*]</code>.
=====Usage:=====
 
<code>map := mapmind(1, <var>map</var>, <var>x</var>)</code>
 
=====Parameters:=====
 
;<var>map</var>
 
:A vector containing the index map.
 
;<var>x</var>
 
:A vector or matrix to copy or remap.


=====Result:=====
=====Result:=====


mappedX[ rows(map), columns(x) ]
mappedX[ rows(map), columns(x) ]

Revision as of 10:55, 20 April 2011

This function implements a non-linear alignment algorithm for two parameter sets (each defined by a vector or matrix). The method minimizes the accumulated Euclidean distance of the two sets. The result is a two column matrix containing the index map of the alignment. The function also implements a method to create a mapped-copy of the sets.


Usage 1
mapmind(0, a, b)
a, b
Are vectors are matrices containing the two parameter sets;
nrow(a)>2, nrow(b)>2, ncol(a) = ncol(b)
Each row of a/b defines one parameter value or vector (e.g. for a frame).
Result
A matrix Nx2 defining the map of the row indices of a and b with the minimum distance matrix. The first column contains the indices for a and the second column the indices for b.
Note:To minimize the distance, individual rows of a or b are duplicated. Therefore the number of rows of the result matrix N is greater than or equal to max(nrow(a),nrow(b).

Usage 2
mapmind(1, m, x)
m
A vector containing the index map for x;
x
A vector or matrix containing the parameter set to remap.
Result 2
A vector or matrix r containing the remapped parameter set x. The number of rows of r is equal to nrow(m) and the number of columns equals ncol(x). The content of the output row r[i,*] is a copy of the input row x[m[i],*].
Result:

mappedX[ rows(map), columns(x) ]

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