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## All rights reserved.
##
## Redistribution and use in source and binary forms, with or without",
## modification, are permitted provided that the following conditions are met:
##
## 1 Redistributions of source code must retain the above copyright notice,
## this list of conditions and the following disclaimer.
## 2 Redistributions in binary form must reproduce the above copyright
## notice, this list of conditions and the following disclaimer in the
## documentation and/or other materials provided with the distribution.
## 3 Neither the name of the author nor the names of its contributors may be
## used to endorse or promote products derived from this software without
## specific prior written permission.
##
## THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS ''AS IS''
## AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
## IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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## DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
## SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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## OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
% function [A,REF,HMAX,H,R,EQUAL] = polyfitinf(M,N,K,X,Y,EPSH,MAXIT,REF0)
%
% Best polynomial approximation in discrete uniform norm
%
% INPUT VARIABLES:
%
% M : degree of the fitting polynomial
% N : number of data points
% X(N) : x-coordinates of data points
% Y(N) : y-coordinates of data points
% K : character of the polynomial:
% K = 0 : mixed parity polynomial
% K = 1 : odd polynomial ( X(1) must be > 0 )
% K = 2 : even polynomial ( X(1) must be >= 0 )
% EPSH : tolerance for leveling. A useful value for 24-bit
% mantissa is EPSH = 2.0E-7
% MAXIT : upper limit for number of exchange steps
% REF0(M2): initial alternating set ( N-vector ). This is an
% OPTIONAL argument. The length M2 is given by:
% M2 = M + 2 , if K = 0
% M2 = integer part of (M+3)/2 , if K = 1
% M2 = 2 + M/2 (M must be even) , if K = 2
%
% OUTPUT VARIABLES:
%
% A : polynomial coefficients of the best approximation
% in order of increasing powers:
% p*(x) = A(1) + A(2)*x + A(3)*x^2 + ...
% REF : selected alternating set of points
% HMAX : maximum deviation ( uniform norm of p* - f )
% H : pointwise approximation errors
% R : total number of iterations
% EQUAL : success of failure of algorithm
% EQUAL=1 : succesful
% EQUAL=0 : convergence not acheived
% EQUAL=-1: input error
% EQUAL=-2: algorithm failure
%
% Relies on function EXCH, provided below.
%
% Example:
% M = 5; N = 10000; K = 0; EPSH = 10^-12; MAXIT = 10;
% X = linspace(-1,1,N); % uniformly spaced nodes on [-1,1]
% k=1; Y = abs(X).^k; % the function Y to approximate
% [A,REF,HMAX,H,R,EQUAL] = polyfitinf(M,N,K,X,Y,EPSH,MAXIT);
% p = polyval(A,X); plot(X,Y,X,p) % p is the best approximation
%
% Note: using an even value of M, e.g., M=2, in the example above, makes
% the algorithm to fail with EQUAL=-2, because of collocation, which
% appears because both the appriximating function and the polynomial are
% even functions. The way aroung it is to approximate only the right half
% of the function, setting K = 2 : even polynomial. For example:
%
% N = 10000; K = 2; EPSH = 10^-12; MAXIT = 10; X = linspace(0,1,N);
% for i = 1:2
% k = 2*i-1; Y = abs(X).^k;
% for j = 1:4
% M = 2^j;
% [~,~,HMAX] = polyfitinf(M,N,K,X,Y,EPSH,MAXIT);
% approxerror(i,j) = HMAX;
% end
% end
% disp('Table 3.1 from Approximation theory and methods, M.J.D.POWELL, p. 27');
% disp(' ');
% disp(' n K=1 K=3');
% disp(' '); format short g;
% disp([(2.^(1:4))' approxerror']);
%
% ALGORITHM:
%
% Computation of the polynomial that best approximates the data (X,Y)
% in the discrete uniform norm, i.e. the polynomial with the minimum
% value of max{ | p(x_i) - y_i | , x_i in X } . That polynomial, also
% known as minimax polynomial, is obtained by the exchange algorithm,
% a finite iterative process requiring, at most,
% n
% ( ) iterations ( usually p = M + 2. See also function EXCH ).
% p
% since this number can be very large , the routine may not converge
% within MAXIT iterations . The other possibility of failure occurs
% when there is insufficient floating point precision for the input
% data chosen.
%
% CREDITS: This routine was developed and modified as
% computer assignments in Approximation Theory courses by
% Prof. Andrew Knyazev, University of Colorado Denver, USA.
%
% Team Fall 98 (Revision 1.0):
% Chanchai Aniwathananon
% Crhistopher Mehl
% David A. Duran
% Saulo P. Oliveira
%
% Team Spring 11 (Revision 1.1): Manuchehr Aminian
%
% The algorithm and the comments are based on a FORTRAN code written
% by Joseph C. Simpson. The code is available on Netlib repository:
% http://www.netlib.org/toms/501
% See also: Communications of the ACM, V14, pp.355-356(1971)
%
% NOTES:
%
% 1) A may contain the collocation polynomial
% 2) If MAXIT is exceeded, REF contains a new reference set
% 3) M, EPSH and REF can be altered during the execution
% 4) To keep consistency to the original code , EPSH can be
% negative. However, the use of REF0 is *NOT* determined by
% EPSH< 0, but only by its inclusion as an input parameter.
%
% Some parts of the code can still take advantage of vectorization.
%
% Revision 1.0 from 1998 is a direct human translation of
% the FORTRAN code http://www.netlib.org/toms/501
% Revision 1.1 is a clean-up and technical update.
% Tested on MATLAB Version 7.11.0.584 (R2010b) and
% GNU Octave Version 3.2.4
% $Revision: 1.1 $ $Date: 2011/08/3 $
% ************************************ beginning of POLYFITINF
function [A,REF,HMAX,H,R,EQUAL] = polyfitinf(M,N,K,X,Y,EPSH,MAXIT,REF0)
% Preassign output variables A,REF,HMAX,H,R,EQUAL in case of error return
A = []; REF = []; HMAX = []; H = []; R = 0; EQUAL = -2;
%%%% end preassignment
% Setting M with respect to K
MOLD = M;
switch K
case 1
K0 = 0;
K1 = 1;
Q1 = 1;
Q2 = 2;
M = (M-Q1)/2;
case 2
K0 = 0;
K1 = 0;
Q1 = 0;
Q2 = 2;
% If the user has input odd M, but wants an even polynomial,
% subtract 1 from M to prevent errors later. The outputs should be
% mathematically equivalent.
if mod(M,2) == 1
M = M-1;
end
M = (M-Q1)/2;
otherwise
if (K ~= 0)
warning('polyfitinf:MixedParity','Using mixed parity polynomial...');
end
K0 = 1;
K1 = 0;
Q1 = 0;
Q2 = 1;
end
P = M + 2;
% Check input data consistency
if ( (length(X) ~= N) || (length(Y) ~= N) )
error('Input Error: check data lengths');
end
if (P > N)
error('Input Error: insufficient data points');
end
if (M < 0)
error('Input Error: insufficient degree');
end
if ( (K == 2) && (X(1) < 0) ) || ( (K == 1) && (X(1) <= 0) )
error('Input Error: X(1) inconsistent with parity');
end
if any(diff(X)<0)
error('Input Error: Abscissae out of order');
end
ITEMP = MOLD + 1;
A = zeros(1,ITEMP);
ITEMP = P + 2;
Z = zeros(1,ITEMP);
Z(1) = 0;
Z(ITEMP) = N + 1;
EPSH = abs(EPSH);
% Read initial reference set into Z, if available.
if (nargin == 8)
J = 0;
Z(2:(P+1))= REF0(1:P);
% Check if REF is monotonically increasing
if ( any(diff(REF0) < 0) || any(REF0 > J) )
error('Input Error : Bad initial reference set');
end
else
% Loads Z with the points closest to the Chebychev abscissas
X1 = X(1);
XE = X(N);
% Setting parity-dependent parameters
if (K0 == 1)
XA = XE + X1;
XE = XE - X1;
Q = pi/(M + 1.0);
else
XA = 0.;
XE = XE + XE;
ITEMP = 2*(M+1) + Q1;
Q = pi/(ITEMP);
end
% Calculate the J-th Chebyshev abcissa and load Z(J+1)
% with the appropriate index from the data abcissas
for JJ = 1:P
J = P + 1 - JJ;
X1 = XA + XE*( cos(Q*(P-J)) );
ITEMP = J + 2;
R = Z(ITEMP);
HIGH = R - 1;
FLAG = 1;
if (HIGH >= 2)
II = 2;
while ( (II <= HIGH) && (FLAG == 1) )
I = HIGH + 2 - II;
ITEMP = I - 1;
% If the Chebyschev abscissa is bracketed by
% two input abcissas, get out of the while loop
if (X(I)+X(ITEMP) <= X1)
FLAG = 0;
end
II = II + 1;
end
end
if (FLAG == 1)
I = 1;
end
ITEMP = J + 1;
if (I < R)
Z(ITEMP) = I;
else
Z(ITEMP) = R - 1;
end
end
% If the lower Chebyshev abcissas are less than X(1),
% load the lower elements of Z with the lowest points
IND = find(Z(2:end) >= (1:(length(Z)-1)));
try TEMP = IND(1); % If IND is empty, do nothing.
catch exception % The catch will be that IND is an empty array.
if strcmpi(exception.identifier,'MATLAB:badsubscript')
% This will be the exception. Do nothing.
end
end
if TEMP~=1
Z(2:TEMP) = (1:(TEMP-1))';
end
end
% M1 entry. Initialize variables to prepare for exchange iteration
ITEMP = M + 1;
% Zero the AA array
AA = zeros(1,ITEMP);
% Load H with the ordinates and XX(I) with the abscissas if the
% polynomial is mixed . If it is even or odd , load XX with the
% squares of the abscissas.
H(1:N) = Y(1:N);
if (K0 <=0)
XX(1:N) = X(1:N).^2;
else
XX(1:N) = X(1:N);
end
B1 = 0;
B2 = 0;
B3 = 0;
R = -1;
T = 0.;
% Iteration entry. R is the iteration index
C = zeros(1,P);
D = zeros(1,P);
DAA = zeros(1,M+1);
FLAG = 1;
while ( (R < MAXIT) && (FLAG == 1) )
R = R + 1; % LABEL 350
%S = 1.;
% Computation of div. differences schemes
if (K1 > 0)
% If the polynomial is mixed or even:
%for I = 1:P
% S = -S;
% ITEMP = I + 1;
% J = Z(ITEMP);
% Q = X(J);
% C(I) = (H(J) + S*T)/Q;
% D(I) = S/Q;
%end
I = (1:P);
S = (-1).^I;
ITEMP = I+1;
J = Z(ITEMP);
C(I) = (H(J) + S*T)./X(J);
D(I) = S./Q;
clear I ITEMP S J
else
% If the polynomial is odd:
%for I = 1:P
% S = -S;
% ITEMP = I + 1;
% ITEMP = Z(ITEMP);
% C(I) = H(ITEMP) + S*T;
% D(I) = S;
%end
I = (1:P);
S = (-1).^I;
ITEMP = I+1;
C(I) = H( Z(ITEMP) ) + S.*T;
D(I) = S;
clear I ITEMP S
end
for I = 2:P
for JJ = I:P
J = P + I - JJ;
ITEMP = J + 1;
ITEMP = Z(ITEMP);
QD = XX(ITEMP);
ITEMP = 2 + J - I;
ITEMP = Z(ITEMP);
QD = QD - XX(ITEMP);
ITEMP = J - 1;
C(J) = (C(J)-C(ITEMP))/QD;
D(J) = (D(J)-D(ITEMP))/QD;
end
end
DT = -C(P)/D(P);
T = T + DT;
% Computation of polynomial coefficients
HIGH = M + 1;
for II = 1:HIGH
I = HIGH - II;
ITEMP = I + 1;
DAA(ITEMP) = C(ITEMP) + DT*D(ITEMP);
ITEMP = I + 2;
ITEMP = Z(ITEMP);
QD = XX(ITEMP);
LOW = I + 1;
if (M >= LOW)
DAA(LOW:M) = DAA(LOW:M) - QD*DAA(((LOW:M)+1));
end
end
AA(1:HIGH) = AA(1:HIGH) + DAA(1:HIGH);
% Evaluation of the polynomial to get the approximation errors
MAXX = 0.;
H = zeros(1,N);
for I = 1:N
SD = AA(HIGH);
QD = XX(I);
if (M > 0)
for J = M:-1:1
SD = SD*QD + AA(J);
end
end
if (K1 > 0)
% If the polynomial is odd, multiply SD by X(I)
SD = SD*X(I);
end
QD = Y(I) - SD;
H(I) = Y(I) - SD;
if (abs(QD) > MAXX)
% Load MAXX with the largest magnitude
% of the approximation array
MAXX = abs(QD);
end
end
% Test for alternating signs
ITEMP = Z(2);
if (H(ITEMP) == 0.)
% This represents a case where the polynomial
% exactly predicts a data point
warning('polyfitinf:Collocation','Collocation has occured.');
if (B3 > 0)
B3 = -1;
FLAG = 0;
else
B3 = 1;
if (EPSH < MAXX)
warning('polyfitinf:AnotherTry','1 more attempt with middle points');
LOW = (N+1)/2 - (P+1)/2 + 1;
HIGH = LOW + P;
Z(LOW:HIGH) = ( (LOW:HIGH) -1);
else
disp('Normal Exit.');
FLAG = 0;
end
end
else
if (H(ITEMP) > 0.)
J = -1;
else
J = 1;
end
I = 2;
FLAG2 = 1;
while ( (I <= P) && (FLAG2 == 1) )
ITEMP = I + 1;
ITEMP = Z(ITEMP);
if (H(ITEMP) == 0.)
J = 0;
warning('polyfitinf:Collocation','Collocation has occured.');
if (B3 > 0)
B3 = -1;
FLAG = 0;
else
B3 = 1;
if (EPSH < MAXX)
warning('polyfitinf:AnotherTry','1 more attempt with middle points');
LOW = (N+1)/2 - (P+1)/2 + 1;
HIGH = LOW + P;
Z(LOW:HIGH) = ( (LOW:HIGH) -1);
else
disp('Normal Exit.');
FLAG = 0;
end
end
FLAG2 = 0;
else
if (H(ITEMP) < 0)
JJ = -1;
else
JJ = 1;
end
if (J~=JJ)
% Error entry: bad accuracy for calculation
B1 = 1;
FLAG2 = 0;
FLAG = 0;
else
J = -J;
end
end
I = I + 1;
end % end of while
% Search for another reference
if (FLAG2*FLAG == 1)
[H,Z,EQUAL] = exch(N, P, EPSH, H, Z);
if (EQUAL > 0)
FLAG = 0;
else
if (R >= MAXIT)
B2 = 1;
FLAG = 0;
end
end
end
end % end of if over H(ITEMP)
end; % end of iteration loop
% M2 entry; load output variables and return
HIGH = M + 1;
% Load the coefficients into A array
A(Q1 + Q2*(((1:HIGH)-1)) + 1) = AA(1:HIGH);
% Load REF with the final reference points
REF(1:P) = Z((1:P) + 1);
HMAX = MAXX;
if (B3 < 0)
EQUAL = -2;
warning('polyfitinf:Collocation','polyfitinf terminates');
end
if (B1 > 0)
EQUAL = -2;
warning('polyfitinf:NoAlternatingSigns','Alternating signs not observed');
end
if (B2 > 0)
EQUAL = 0;
warning('polyfitinf:MaxIterationsReached','MAXIT was reached, current ref. set saved in REF.');
end
% Reverse the order of A to make it compatible with MATLAB'S polyval() function.
A = A(end:-1:1);
endfunction
% ****************************************** end of POLYFITINF
function [H,Z,EQUAL] = exch(N, P, EPSH, H, Z)
% function [H,Z,EQUAL] = exch(N, P, EPSH, H, Z)
%
% EXCH: exchange algorithm
%
% INPUT VARIABLES:
% N : number of data points
% P : number of reference points
% EPSH : tolerance for leveling.
% Z : old reference indices
%
% OUTPUT VARIABLES:
% H : pointwise approximation errors
% Z : new reference indices
% EQUAL : EQUAL=1 : normal exchange
% EQUAL=0 : old and new references are equal
%
% CREDITS: This routine was developed and modified as
% computer assignments in Approximation Theory courses by
% Prof. Andrew Knyazev, University of Colorado Denver, USA.
%
% Team Fall 98 (Revision 1.0):
% Chanchai Aniwathananon
% Crhistopher Mehl
% David A. Duran
% Saulo P. Oliveira
%
% Team Spring 11 (Revision 1.1): Manuchehr Aminian
%
% The algorithm and the comments are based on a FORTRAN code written
% by Joseph C. Simpson. The code is available on Netlib repository:
% http://www.netlib.org/toms/501
% See also: Communications of the ACM, V14, pp.355-356(1971)
%
% Revision 1.0 from 1998 is a direct human translation of
% the FORTRAN code http://www.netlib.org/toms/501
% Revision 1.1 is a clean-up and technical update.
% Tested on MATLAB Version 7.11.0.584 (R2010b) and
% GNU Octave Version 3.2.4
% License: BSD
% Copyright 1998-2011 Andrew V. Knyazev
% $Revision: 1.1 $ $Date: 2011/05/17 $
% ************************************ beginning of exch
EQUAL = 0;
L = 0;
ITEMP = Z(2);
% SIG is arbitrarily chosen equal to the sign of the input
% point. This will be adjusted later if necessary.
if (H(ITEMP) <= 0)
SIG = 1.;
else
SIG = -1.;
end
% The next loop prescans Z to insure it is a proper choice, i.e
% resets Z if necessary so that maximum error points are chosen,
% given the sign convention mentioned above. In order to work
% properly, this section requires Z(1) = 0 and Z(P+2) = N + 1 .
for I = 1:P
MAXX = 0.;
SIG = -SIG;
ITEMP = I + 2;
ZE = Z(ITEMP) - 1;
LOW = Z(I) + 1;
% Scan the open point interval containing only the 1th initial
% reference point. In the interval pick the point with largest
% magnitude and correct sign. Most of the sorting occurs in
% this section. SIG contains the sign assumed for H(I).
for J = LOW:ZE
if (SIG*(H(J)-MAXX) > 0)
MAXX = H(J);
INDEX = J;
end
end
ITEMP = I + 1;
ITEMP = Z(ITEMP);
MAXL = abs(MAXX);
% If the MAX error is significantly greater than the
% input point, switch to this point.
if (abs( MAXX - H(ITEMP) )/MAXL > EPSH)
ITEMP = I + 1;
Z(ITEMP) = INDEX;
L = 1;
end
end
%
MAXL = 0.;
MAXR = 0.;
ITEMP = P + 1;
LOW = Z(ITEMP) + 1;
%
if (LOW <= N)
% Find the error with largest abs value and proper sign
% from among the points above the last reference point.
% This section is necessary because the set of points
% chosen may begin with the wrong sign alternation.
for J = LOW:N
if (SIG*(MAXR-H(J)) > 0)
MAXR = H(J);
INDR = J;
end
end
end
% Find the error with largest abs value and proper sign
% from among the points below the 1st reference point.
% This section is necessary by the same reason as above.
ITEMP = Z(2);
HZ1 = H(ITEMP);
HIGH = ITEMP -1;
if (HIGH > 0)
if (HZ1 < 0)
SIG = -1.;
elseif (HZ1 == 0)
SIG = 0.;
else
SIG = 1.;
end
for J = 1:HIGH
if (SIG*(MAXL-H(J)) > 0)
MAXL = H(J);
INDL = J;
end
end
end
% MAXL and MAXR contain the magnitude of the significant
% errors outside the reference point set. If either is
% zero, the reference point set extends to the end point
% on that side of the interval.
MAXL = abs(MAXL);
MAXR = abs(MAXR);
HZ1 = abs(HZ1);
ITEMP = P + 1;
ITEMP = Z(ITEMP);
HZP = abs(H(ITEMP));
% L = 0 implies that the previous prescan did not change
% any points. If L = 0 and MAXL, MAXR are not significant
% if compared with upper and lower reference point errors,
% respectively, use the EQUAL exit.
FLAG1 = 1;
if (L == 0)
if ( (MAXL == 0) || (EPSH >= (MAXL-HZP)/MAXL) )
if ( (MAXR == 0) || (EPSH >= (MAXR-HZ1)/MAXR) )
FLAG1 = 0;
EQUAL = 1;
end
end
end
if ( (MAXL == 0) && (MAXR == 0) )
FLAG1 = 0;
end
if ( (MAXL > MAXR) && (MAXL <= HZP) && (MAXR < HZ1) )
FLAG1 = 0;
end
if ( (MAXL <= MAXR) && (MAXR <= HZ1) && (MAXL < HZP) )
FLAG1 = 0;
end
% If a point outside the present reference set must be
% included, (i.e. the sign of the 1st point previously
% assumed is wrong) shift to the side of largest
% relative error first.
if (FLAG1 == 1)
FLAG2 = 1;
if ( (MAXL > MAXR) && (MAXL > HZP) )
FLAG2 = 0;
end
if ( (MAXL <= MAXR) && (MAXR <= HZ1) )
FLAG2 = 0;
end
if (FLAG2 == 1)
% SHR entry. This section inserts a point from
% above the prescan point set
INDEX = Z(2);
% shift point set down, dropping the lowest point
Z(2:P) = Z((2:P)+1);
ITEMP = P + 1;
% add the next high point
Z(ITEMP)=INDR;
% if MAXL > 0 replace reference points from the left,
% stopping the 1st time the candidate for replacement
% is greater than in magnitude than the prospective
% replacee. Alternation of signs is preserved because
% non-replacement immediately terminates the process.
if (MAXL > 0)
I = 2;
FLAG3 = 1;
while ( (I <= P) && (FLAG3 == 1) )
ITEMP = Z(I);
if ( abs(H(INDL)) >= abs(H(ITEMP)) )
J = Z(I);
Z(I) = INDL;
INDL = INDEX;
INDEX = J;
else
FLAG3 = 0;
end
I = I + 1;
end
end
else
% SHL entry. This section inserts a point from below the
% prescan point set.
ITEMP = P + 1 ;
INDEX = Z(ITEMP);
Z((2:P)+1) = Z(2:P);
% store lowest point in Z(2)
Z(2) = INDL;
% if MAXR > 0 replace reference points from the right,
% stopping the 1st time the candidate for replacement
% is greater than in magnitude than the prospective
% replacee.
if (MAXR > 0)
II = 2;
FLAG3 = 1;
while ( (II <= P) && (FLAG3 == 1) )
I = P + 2 - II;
ITEMP = I + 1;
HIGH = Z(ITEMP);
if ( abs(H(INDR)) >= abs(H(HIGH)) )
J = Z(ITEMP);
Z(ITEMP) = INDR;
INDR = INDEX;
INDEX = J;
else
FLAG3 = 0;
end
II = II + 1;
end
end
end
end
endfunction
% ****************************************** end of exch
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