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📄 blended_spectrum_fast.m

📁 《模式分析的核方法》一书中的源代码
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function [result, K_p] = blended_spectrum_fast(s,t,p,lambda)%BLENDED_SPECTRUM_FAST%        -Finds the contiguous subsequence match count between strings s and t%         by using a dynamic programming implementation,%         for all substrings of length <= p, and with  penalties lambda.%         *(There is also a brute force implementation of this algorithm.%           Type help blended_spectrum_fast_bf for info.)%        -Is faster than blended_spectrum b/c this program only tries to fill in the last%         index of the matrix, rather than the whole structure.%%        -Simply prompting the function will return the value K(s,t), however%         using the function as [result,K] = K(s,t) will also return the matrix K.%%        -The following algorithm is used:%         K[p](sa,t) = K[p](s,t) + [Summation of j from 1 to |t|] ( lambda^2 * K'[p](sa,t(1:j)) )%           K[p](s,t) = 0 if |s| == 0 or |t| == 0%         K'[p](sa,tb) = (1 + lambda^2 * K'[p-1](s,t)) [a == b]%           K'[0](s,t) = 0 for all s,t%           K'[p](s,t) = 0 if |s| == 0 or |t| == 0%%        -Example: blended_spectrum_fast_bf('abccc','abc', 2, 1) returns a value of 7.%            (Note that blended_spectrum_fast_bf('abccc','abc',2, 1)=%                       blended_spectrum_fast_bf('abc','abccc',2, 1) %             since K(s,t,p) = K(t,s,p) ).%        -Example: blended_spectrum_fast_bf('a','a', 1, 1) returns a value of 1.%        -Example: blended_spectrum_fast_bf('a','b', 1, 1) returns a value of 0.%        -Example: blended_spectrum_fast_bf('ab','ab', 1, 1) returns a value of 2.%         %%%USAGE:   scalar = blended_spectrum_fast('string1','string2', p, lambda);    (where p is the length of the subsequence)%%         [scalar, matrix] = blended_spectrum_fast('string1,'string2', p, lambda);%%%For more information, visit http://www.kernel-methods.net/%Written and tested in Matlab 6.0, Release 12.%Copyright 2003, Manju M. Pai 4/2003%manju@kernel-methods.net%------------------------------------------------------------------------------------------%Obtain lengths of strings[num_rows_s, n] = size(s);[num_rows_t, m] = size(t);%Initially set every matrix index to -1 to show value has not yet been foundK_p = repmat(-1, [n, m]);                %The main kernelK_s_p = repmat(-1, [n, m, p]);           %The suffix kernel%Error checking statements:  %Make sure input vectors are horizontal.  if (num_rows_s ~= 1 | num_rows_t ~= 1)       error('Error: s and t must be horizontal vectors.');  end;    %If p is less than zero or not a number, program should quit due to faulty variable input.  if p <= 0 | ischar(p)      error('Error: p needs to be a number greater than 0.');  end;    %If lambda is less than zero or not a number, program should quit due to faulty variable input.  if lambda <= 0 | ischar(lambda)      error('Error: lambda needs to be a number greater than 0.');  end;%End of error checking%Fill in the rest of the matrix using the function blended_spectrum_fast(s,t)[K_p(n,m), K_s_p] = blended_spectrum_fast_kernel(s, t, K_p, K_s_p, p, lambda);result = K_p(n,m);%------------------------------------------------------------------------------------------function [ans, K_s_p] = blended_spectrum_fast_kernel(sa, t, K_p, K_s_p, p, lambda)%This function is called by blended_spectrum_fast().%Type 'help blended_spectrum_fast' for a description of the program.%%------------------------------------------------------------------------------------------%Obtain lengths of both stringsn = length(sa);m = length(t);%truncate last character of strings = sa(1:n-1);%Start algorithm:  % 1) Split main algorithm into two parts:    % a) K_p(s,t)       if (length(s) == 0) | (length(t) == 0)         %This is a base case where 0 is returned if either string has length 0         ans = 0;       elseif( K_p( length(s), length(t) ) == -1 )         % Value has not yet been calculated         ans = blended_spectrum_fast_kernel(s, t, K_p, K_s_p, p, lambda);       else         % Value has already been calculated         ans = K_p( length(s), length(t) );       end;    % b) Summation of (lambda^2)*K_s_p(sa,t(1:j))      %We need this 'for' loop as a cursor that iterates through the t string.      for i = 1:m          t_length = length(t(1:i));          if ( K_s_p( n, t_length, p) == -1 )            % Value has not yet been calculated            [result, K_s_p] = suffix_kernel(sa, t(1:i), K_s_p, (p-1), lambda);            K_s_p( length(sa), t_length, p) = result;  %Store this newly calculated result into suffix kernel          else            % Value has already been calculated            result = K_s_p( n, t_length, p);          end;          ans = ans + (lambda * lambda * result);      end;                  return% End of algorithm%------------------------------------------------------------------------------------------function [ans, K_s_p] = suffix_kernel(sa, tb, K_s_p, p, lambda)%This function is called by blended_spectrum_fast().%Type 'help blended_spectrum_fast' for a description of the program.%%------------------------------------------------------------------------------------------%Obtain lengths of both stringsn = length(sa);m = length(tb);%if last characters of both strings do not match, return 0if ~(strcmpi( sa(n), tb(m) ) )    ans = 0;    returnend;%truncate last character of strings = sa(1:n-1);t = tb(1:m-1);%Obtain lengths of truncated stringslength_s = length(s);length_t = length(t);%Start algorithm: K_s_p(sa,tb) = (1 + lambda^2)*K_s_p-1(s,t)[a==b]if (p == 0)    result = 0;elseif (length_s == 0) | (length_t == 0)    %This is a base case where 0 is returned if either string has length 0    result = 0;elseif( K_s_p( length_s, length_t, p ) == -1 )    % Value has not yet been calculated    [result, K_s_p] = suffix_kernel(s, t, K_s_p, (p-1), lambda);    K_s_p( length_s, length_t, p) = result;else    % Value has already been calculated    result = K_s_p( length_s, length_t, p );end;ans = 1 + (lambda * lambda * result);return

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