agcmem.m

具有特色的地震数据处理源码

function [dataout]=agcmem(datain,window,type)

%[dataout]=agcmem(datain,window,type)
%
%This function will do automatic gain control with a running window equation
%on the traces in datain.
%The size of the sliding window is specified by the parameter 'window' in 
%seconds.
%'type' = 1 use absolute values for normalizing
%'type' = 2 use energy values (x^2) for normalizing
%
%Rewritten to conserve memory!
%Is much slower than agc but conserves memory
%Use only when memory restrictions make agc unuseable!
%
%Based on module by Kristen Beaty Dec. 1997
%Written by Marko Mah February 1999

%$Id: agcmem.m,v 3.0 2000/06/13 19:19:38 gilles Exp $
%$Log: agcmem.m,v $
%Revision 3.0  2000/06/13 19:19:38  gilles
%Release 3
%
%Revision 2.0  1999/05/21 18:45:04  mah
%Release 2
%
%Revision 1.1  1999/02/10 19:09:29  mah
%Initial revision
%
%
%
%Copyright (C) 1998 Seismology and Electromagnetic Section/
%Continental Geosciences Division/Geological Survey of Canada
%
%This library is free software; you can redistribute it and/or
%modify it under the terms of the GNU Library General Public
%License as published by the Free Software Foundation; either
%version 2 of the License, or (at your option) any later version.
%
%This library is distributed in the hope that it will be useful,
%but WITHOUT ANY WARRANTY; without even the implied warranty of
%MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
%Library General Public License for more details.
%
%You should have received a copy of the GNU Library General Public
%License along with this library; if not, write to the
%Free Software Foundation, Inc., 59 Temple Place - Suite 330,
%Boston, MA  02111-1307, USA.
%
%DSI Consortium
%Continental Geosciences Division
%Geological Survey of Canada
%615 Booth St.
%Ottawa, Ontario
%K1A 0E9
%
%email: [e-mail]

disp('[dataout]=agcmem(datain,window,type)')

dataout=datain;

tstart=datain.fh{9}; %start time in seconds
int=datain.fh{8}; %sampling interval in seconds
samples=datain.fh{7}; %number of points per trace
nrec=datain.fh{12}; %number of records in datain
w=round(window/int)+1; %convert 'window' from seconds to indexes
pt=round(w/2); %index of point in the centre of the window

% the following checks to see if the window chosen is too large
if w>=samples %error check
   w = samples-1;
   pt=round(w/2);
   ntime = (samples - 1)*int;
   text = sprintf('WARNING! Window has been reset to %8.5f s',ntime);
   disp(text)
end %if

% the following checks to see if the either type 1 or 2 has been chosen

if((type ~=1) & (type ~=2))
   type=1;
   text = sprintf('WARNING! Type has been reset to 1');
   disp(text)
end %if

% the following for loop applies the agc to each record
for COUNT1=1:nrec
 % the following applies the method of agc specified by type
 switch type

  case 1 %absolute values
   % first determine how many traces there are
   [a,ntraces]=size(datain.dat{COUNT1}); %ntraces is the number of traces in the record

   trccor=zeros(samples,1); %initializes the trace correction

   for COUNT2=1:ntraces

    % first take the absolute value of the data and divide by w to make it faster
    temp=abs(datain.dat{COUNT1}(:,COUNT2))/w;
    % first determine the average in the window
    fact=sum(temp(1:w));
    % now apply this to the first half of the window
    trccor(1:pt)=fact;

    % now apply the agc to the centre portion of the trace using a for loop
    for k=1:samples-w
     % the correction factor fact is being recalculated after each position moved
     fact=fact-temp(k)+temp(k+w);
     trccor(k+pt)=fact;
    end %for k
   
    % now apply this correction factor to the last half of the window
    i=(k+pt+1):samples; %i are the positions that still need to be corrected
    trccor(i)=fact;

    % now apply the trace correction to the data
    trccoreps=trccor+eps; %eps is added in to prevent divide by zero problem
    dataout.dat{COUNT1}(:,COUNT2)=datain.dat{COUNT1}(:,COUNT2)./trccoreps;

   end %for COUNT2

  case 2 %squared values
   % first determine how many traces there are
   [a,ntraces]=size(datain.dat{COUNT1}); %ntraces is the number of traces in the record

   trccor=zeros(samples,1); %initializes the trace correction

   for COUNT2=1:ntraces

    % first square the data and divide by w squared to make it faster
    temp=datain.dat{COUNT1}(:,COUNT2).*datain.dat{COUNT1}(:,COUNT2)/w/w;
    % first determine the average in the window
    fact=sum(temp(1:w));
    % now apply this to the first half of the window
    trccor(1:pt)=fact;

    % now apply the agc to the centre portion of the trace using a for loop
    for k=1:samples-w
     % the correction factor fact is being recalculated after each position moved
     fact=fact-temp(k)+temp(k+w);
     trccor(k+pt)=fact;
    end %for k

    % now apply this correction factor to the last half of the window
    i=(k+pt+1):samples; %i are the positions that still need to be corrected
    trccor(i)=fact;

    % now apply the trace correction to the data
    trccoreps=sqrt(trccor+eps); %eps is added in to prevent divide by zero problem
    dataout.dat{COUNT1}(:,COUNT2)=datain.dat{COUNT1}(:,COUNT2)./trccoreps;

    % the following balances the energy from trace to trace
    temp=dataout.dat{COUNT1}(:,COUNT2).*dataout.dat{COUNT1}(:,COUNT2);
    fact=sum(temp);
    fact=sqrt(fact);
    if fact==0
     fact=1; %avoid divide by zero error for dead traces
    end %if
    dataout.dat{COUNT1}(:,COUNT2)=dataout.dat{COUNT1}(:,COUNT2)/fact; %applies the correction

   end %for COUNT2

  end %type

end %loop over records