diagnostic.m

function diagnostic(t,s,d,m)
%DIAGNOSTIC Creates a diagnostic plot of the data
%  
% Syntax: diagnostic(t,s[[,d],m])     
%
%   d = optional argument allowing to adjust the
%       number of points used in the Spline by default
%       or the distance between points depending on the option below
%
%   m = optional argument allowing to select
%       different methods of computation of the derivative
%
%   's' for spline resampling
%       in that case d is the number of points for the spline
%
%   'd' for direct derivation
%       in that case the value provided in the variable d is not used
%
%   'b' for the Bourdet et al. formula 
%       in that case d is the lag distance used to compute the derivative       
%
% Description:
%     This function allows to create rapidly a diagnostic plot (i.e. a 
%     log-log plot of the drawdown as a function of time together with
%     its logarithmic derivative) of the data.
%
% Example:
%     diagnostic(t,s)
%     diagnostic(t,s,30)
%     diagnostic(t,s,20,'d')   - in that case the number 20 is not used
%
% See also: trial, ldf, ldiff, ldiffs, fit
%

if(nargin==2) % Default value for d if not given by user
  d=20;
  m='s';
end

if(nargin==3) % Default value for d if not given by user
  m='s';
end

ispositive=find(t>0);
t=t(ispositive);
s=s(ispositive);

switch m
  case 's'
     [td,sd]=ldiffs(t,s,d);  % Numerical estimation of the derivative with spline sampling
  case 'd'
     [td,sd]=ldiff(t,s);    % Standard estimation of the derivative
  case 'b'
     [td,sd]=ldiffb(t,s,d);    % Standard estimation of the derivative
  otherwise
     disp('ERROR: diagnostic(t,s,d,m)');
     disp('  The method selected for log-derivative calculation is unknown');
     td=NaN;
     sd=NaN;
end

isd=find(sd>0);
clf
loglog(t,s,'o',td(isd),sd(isd),'+') 
xlabel('Time')
ylabel('Drawdown and log derivative')
legend('Drawdown','Derivative','Location','Northwest')