+
−% test_smodel_double tests the double method of the SMODEL class.
+
−%
+
−% M Hueller 02-05-2011
+
−%
+
−% $Id: test_smodel_double.m,v 1.2 2011/05/05 21:04:13 mauro Exp $
+
−%
+
−function results = test_smodel_double(varargin)
+
−  
+
−  %% List of runs
+
−  if nargin == 1
+
−    list = varargin{1};
+
−    if isa(list, 'cell')
+
−      list = list{:};
+
−    end
+
−  else
+
−    list = [];
+
−  end
+
−  
+
−  if isempty(list)
+
−    list = [10 11 20 21 30 31 40 41 50 51];
+
−  end
+
−  
+
−  %% Run tests
+
−  results = [];
+
−  
+
−  %% 10 Oscillator step, default values
+
−  test = 10;
+
−  if any(ismember(list, test))
+
−    
+
−    % Pick the model
+
−    model_def = 'oscillator_step';
+
−    
+
−    % Decide the tolerance of the test ([] or 0 for no tolerance)
+
−    TOL = 0;
+
−    
+
−    % Set parameters: duration and rate
+
−    nsecs = 100;
+
−    fs    = 1;
+
−    
+
−    % Extract the information from the ao model default plist
+
−    ao_mdl_info = eval(['ao_model_' model_def '(''info'')']);
+
−    pl = ao_mdl_info.plists;
+
−    
+
−    F0     = find(pl, 'F0');
+
−    toff   = find(pl, 'toff');
+
−    m      = find(pl, 'm');
+
−    k      = find(pl, 'k');
+
−    tau    = find(pl, 'tau');
+
−    x0     = find(pl, 'x0');
+
−    v0     = find(pl, 'v0');
+
−    
+
−    % Build the ao model
+
−    ao_mdl = ao(plist('built-in', model_def, 'nsecs', nsecs, 'fs', fs));
+
−    
+
−    % Build the smodel model
+
−    smodel_mdl = smodel(plist('built-in', model_def));
+
−    
+
−    % Set smodel parameters
+
−    smodel_mdl.setParameters({'m','k','tau','F0','x0','v0','toff'}, {m,k,tau,F0,x0,v0,toff});
+
−    
+
−    % Set smodel xvals
+
−    smodel_mdl.setXvals(ao_mdl.x);
+
−    
+
−    % Eval the smodel
+
−    d = smodel_mdl.double();
+
−    
+
−    % Compare the numbers
+
−    results = [results; test check_correctness(d, ao_mdl.y, plist('tolerance', TOL))];
+
−  end
+
−  
+
−  %% 11 Oscillator step, high fs and high nsecs
+
−  test = 11;
+
−  if any(ismember(list, test))
+
−    
+
−    % Pick the model
+
−    model_def = 'oscillator_step';
+
−    
+
−    % Decide the tolerance of the test ([] or 0 for no tolerance)
+
−    TOL = 0;
+
−    
+
−    % Set parameters: duration and rate
+
−    nsecs = 10000;
+
−    fs    = 1000;
+
−    
+
−    % Extract the information from the ao model default plist
+
−    ao_mdl_info = eval(['ao_model_' model_def '(''info'')']);
+
−    pl = ao_mdl_info.plists;
+
−    
+
−    F0     = find(pl, 'F0');
+
−    toff   = find(pl, 'toff');
+
−    m      = find(pl, 'm');
+
−    k      = find(pl, 'k');
+
−    tau    = find(pl, 'tau');
+
−    x0     = find(pl, 'x0');
+
−    v0     = find(pl, 'v0');
+
−    
+
−    % Build the ao model
+
−    ao_mdl = ao(plist('built-in', model_def, 'nsecs', nsecs, 'fs', fs));
+
−    
+
−    % Build the smodel model
+
−    smodel_mdl = smodel(plist('built-in', model_def));
+
−    
+
−    % Set smodel parameters
+
−    smodel_mdl.setParameters({'m','k','tau','F0','x0','v0','toff'}, {m,k,tau,F0,x0,v0,toff});
+
−    
+
−    % Set smodel xvals
+
−    smodel_mdl.setXvals(ao_mdl.x);
+
−    
+
−    % Eval the smodel
+
−    d = smodel_mdl.double();
+
−    
+
−    % Compare the numbers
+
−    results = [results; test check_correctness(d, ao_mdl.y, plist('tolerance', TOL))];
+
−  end
+
−  
+
−  %% 20 Oscillator sine, default values
+
−  test = 20;
+
−  if any(ismember(list, test))
+
−    
+
−    % Pick the model
+
−    model_def = 'oscillator_sine';
+
−    
+
−    % Decide the tolerance of the test ([] or 0 for no tolerance)
+
−    TOL = 0e-13;
+
−    
+
−    % Set parameters: duration and rate
+
−    nsecs = 100;
+
−    fs    = 1;
+
−    
+
−    % Extract the information from the ao model default plist
+
−    ao_mdl_info = eval(['ao_model_' model_def '(''info'')']);
+
−    pl = ao_mdl_info.plists;
+
−    
+
−    F0     = find(pl, 'F0');
+
−    toff   = find(pl, 'toff');
+
−    phi    = find(pl, 'phi');
+
−    phi = 0.0;
+
−    f      = find(pl, 'f');
+
−    m      = find(pl, 'm');
+
−    k      = find(pl, 'k');
+
−    tau    = find(pl, 'tau');
+
−    x0     = find(pl, 'x0');
+
−    x0 = 0.0;
+
−    v0     = find(pl, 'v0');
+
−    
+
−    % Build the ao model
+
−    ao_mdl = ao(plist('built-in', model_def, 'nsecs', nsecs, 'fs', fs, 'x0', x0, 'phi', phi));
+
−    
+
−    % Build the smodel model
+
−    smodel_mdl = smodel(plist('built-in', model_def));
+
−    
+
−    % Set smodel parameters
+
−    smodel_mdl.setParameters({'m','k','tau','F0','f','phi','x0','v0','toff'}, {m,k,tau,F0,f,phi,x0,v0,toff});
+
−    
+
−    % Set smodel xvals
+
−    smodel_mdl.setXvals(ao_mdl.x);
+
−    
+
−    % Eval the smodel
+
−    d = smodel_mdl.double();
+
−    
+
−    % Compare the numbers
+
−    results = [results; test check_correctness(d, ao_mdl.y, plist('tol', TOL))];
+
−  end
+
−  
+
−  %% 21 Oscillator sine, high fs and high nsecs
+
−  test = 21;
+
−  if any(ismember(list, test))
+
−    
+
−    % Pick the model
+
−    model_def = 'oscillator_sine';
+
−    
+
−    % Decide the tolerance of the test ([] or 0 for no tolerance)
+
−    TOL = 1e-12;
+
−    
+
−    % Set parameters: duration and rate
+
−    nsecs = 10000;
+
−    fs    = 1000;
+
−    
+
−    % Extract the information from the ao model default plist
+
−    ao_mdl_info = eval(['ao_model_' model_def '(''info'')']);
+
−    pl = ao_mdl_info.plists;
+
−    
+
−    F0     = find(pl, 'F0');
+
−    toff   = find(pl, 'toff');
+
−    phi    = find(pl, 'phi');
+
−    f      = find(pl, 'f');
+
−    m      = find(pl, 'm');
+
−    k      = find(pl, 'k');
+
−    tau    = find(pl, 'tau');
+
−    x0     = find(pl, 'x0');
+
−    v0     = find(pl, 'v0');
+
−    
+
−    % Build the ao model
+
−    ao_mdl = ao(plist('built-in', model_def, 'nsecs', nsecs, 'fs', fs));
+
−    
+
−    % Build the smodel model
+
−    smodel_mdl = smodel(plist('built-in', model_def));
+
−    
+
−    % Set smodel parameters
+
−    smodel_mdl.setParameters({'m','k','tau','F0','f','phi','x0','v0','toff'}, {m,k,tau,F0,f,phi,x0,v0,toff});
+
−    
+
−    % Set smodel xvals
+
−    smodel_mdl.setXvals(ao_mdl.x);
+
−    
+
−    % Eval the smodel
+
−    d = smodel_mdl.double();
+
−    
+
−    % Compare the numbers
+
−    results = [results; test check_correctness(d, ao_mdl.y, plist('tol', TOL))];
+
−  end
+
−  
+
−  %% 30 Sinewave, default values
+
−  test = 30;
+
−  if any(ismember(list, test))
+
−    
+
−    % Pick the model
+
−    model_def = 'sinewave';
+
−    
+
−    % Decide the tolerance of the test ([] or 0 for no tolerance)
+
−    TOL = 0;
+
−    
+
−    % Set parameters: duration and rate
+
−    nsecs = 100;
+
−    fs    = 1;
+
−    
+
−    % Extract the information from the ao model default plist
+
−    ao_mdl_info = eval(['ao_model_' model_def '(''info'')']);
+
−    pl = ao_mdl_info.plists;
+
−    
+
−    A      = find(pl, 'A');
+
−    phi    = find(pl, 'phi');
+
−    f      = find(pl, 'f');
+
−    
+
−    % Build the ao model
+
−    ao_mdl = ao(plist('built-in', model_def, 'nsecs', nsecs, 'fs', fs));
+
−    
+
−    % Build the smodel model
+
−    smodel_mdl = smodel(plist('built-in', model_def));
+
−    
+
−    % Set smodel parameters
+
−    smodel_mdl.setParameters({'A','f','phi'}, {A,f,phi});
+
−    
+
−    % Set smodel yunits
+
−    smodel_mdl.setYunits(ao_mdl.yunits);
+
−    
+
−    % Set smodel xvals
+
−    smodel_mdl.setXvals(ao_mdl.x);
+
−    
+
−    % Eval the smodel
+
−    d = smodel_mdl.double();
+
−    
+
−    % Compare the numbers
+
−    results = [results; test check_correctness(d, ao_mdl.y, plist('tol', TOL))];
+
−  end
+
−  
+
−  %% 31 Sinewave, high fs and high nsecs
+
−  test = 31;
+
−  if any(ismember(list, test))
+
−    
+
−    % Pick the model
+
−    model_def = 'sinewave';
+
−    
+
−    % Decide the tolerance of the test ([] or 0 for no tolerance)
+
−    TOL = 0;
+
−    
+
−    % Set parameters: duration and rate
+
−    nsecs = 10000;
+
−    fs    = 1000;
+
−    
+
−    % Extract the information from the ao model default plist
+
−    ao_mdl_info = eval(['ao_model_' model_def '(''info'')']);
+
−    pl = ao_mdl_info.plists;
+
−    
+
−    A      = find(pl, 'A');
+
−    phi    = find(pl, 'phi');
+
−    f      = find(pl, 'f');
+
−    
+
−    % Build the ao model
+
−    ao_mdl = ao(plist('built-in', model_def, 'nsecs', nsecs, 'fs', fs));
+
−    
+
−    % Build the smodel model
+
−    smodel_mdl = smodel(plist('built-in', model_def));
+
−    
+
−    % Set smodel parameters
+
−    smodel_mdl.setParameters({'A','f','phi'}, {A,f,phi});
+
−    
+
−    % Set smodel yunits
+
−    smodel_mdl.setYunits(ao_mdl.yunits);
+
−    
+
−    % Set smodel xvals
+
−    smodel_mdl.setXvals(ao_mdl.x);
+
−    
+
−    % Eval the smodel
+
−    d = smodel_mdl.double();
+
−    
+
−    % Compare the numbers
+
−    results = [results; test check_correctness(d, ao_mdl.y, plist('tol', TOL))];
+
−  end
+
−  
+
−  %% 40 Squarewave, default values
+
−  test = 40;
+
−  if any(ismember(list, test))
+
−    
+
−    % Pick the model
+
−    model_def = 'squarewave';
+
−    
+
−    % Decide the tolerance of the test ([] or 0 for no tolerance)
+
−    TOL = 0;
+
−    
+
−    % Set parameters: duration and rate
+
−    nsecs = 100;
+
−    fs    = 1;
+
−    
+
−    % Extract the information from the ao model default plist
+
−    ao_mdl_info = eval(['ao_model_' model_def '(''info'')']);
+
−    pl = ao_mdl_info.plists;
+
−    
+
−    phi    = find(pl, 'phi');
+
−    f      = find(pl, 'f');
+
−    
+
−    % Build the ao model
+
−    ao_mdl = ao(plist('built-in', model_def, 'nsecs', nsecs, 'fs', fs));
+
−    
+
−    % Build the smodel model
+
−    smodel_mdl = smodel(plist('built-in', model_def));
+
−    
+
−    % Set smodel parameters
+
−    smodel_mdl.setParameters({'f','phi'}, {f,phi});
+
−    
+
−    % Set smodel yunits
+
−    smodel_mdl.setYunits(ao_mdl.yunits);
+
−    
+
−    % Set smodel xvals
+
−    smodel_mdl.setXvals(ao_mdl.x);
+
−    
+
−    % Eval the smodel
+
−    d = smodel_mdl.double();
+
−    
+
−    % Compare the numbers
+
−    results = [results; test check_correctness(d, ao_mdl.y, plist('tol', TOL))];
+
−  end
+
−  
+
−  %% 41 Squarewave, high fs and high nsecs
+
−  test = 41;
+
−  if any(ismember(list, test))
+
−    
+
−    % Pick the model
+
−    model_def = 'squarewave';
+
−    
+
−    % Decide the tolerance of the test ([] or 0 for no tolerance)
+
−    TOL = 0;
+
−    
+
−    % Set parameters: duration and rate
+
−    nsecs = 10000;
+
−    fs    = 1000;
+
−    
+
−    % Extract the information from the ao model default plist
+
−    ao_mdl_info = eval(['ao_model_' model_def '(''info'')']);
+
−    pl = ao_mdl_info.plists;
+
−    
+
−    phi    = find(pl, 'phi');
+
−    f      = find(pl, 'f');
+
−    
+
−    % Build the ao model
+
−    ao_mdl = ao(plist('built-in', model_def, 'nsecs', nsecs, 'fs', fs));
+
−    
+
−    % Build the smodel model
+
−    smodel_mdl = smodel(plist('built-in', model_def));
+
−    
+
−    % Set smodel parameters
+
−    smodel_mdl.setParameters({'f','phi'}, {f,phi});
+
−    
+
−    % Set smodel yunits
+
−    smodel_mdl.setYunits(ao_mdl.yunits);
+
−    
+
−    % Set smodel xvals
+
−    smodel_mdl.setXvals(ao_mdl.x);
+
−    
+
−    % Eval the smodel
+
−    d = smodel_mdl.double();
+
−    
+
−    % Compare the numbers
+
−    results = [results; test check_correctness(d, ao_mdl.y, plist('tol', TOL))];
+
−  end
+
−  
+
−  %% 50 Step, default values
+
−  test = 50;
+
−  if any(ismember(list, test))
+
−    
+
−    % Pick the model
+
−    model_def = 'step';
+
−    
+
−    % Decide the tolerance of the test ([] or 0 for no tolerance)
+
−    TOL = 0;
+
−    
+
−    % Set parameters: duration and rate
+
−    nsecs = 100;
+
−    fs    = 1;
+
−    
+
−    % Extract the information from the ao model default plist
+
−    ao_mdl_info = eval(['ao_model_' model_def '(''info'')']);
+
−    pl = ao_mdl_info.plists;
+
−    
+
−    A    = find(pl, 'A');
+
−    toff = find(pl, 'toff');
+
−    
+
−    % Build the ao model
+
−    ao_mdl = ao(plist('built-in', model_def, 'nsecs', nsecs, 'fs', fs));
+
−    
+
−    % Build the smodel model
+
−    smodel_mdl = smodel(plist('built-in', model_def));
+
−    
+
−    % Set smodel parameters
+
−    smodel_mdl.setParameters({'A','toff'}, {A,toff});
+
−    
+
−    % Set smodel yunits
+
−    smodel_mdl.setYunits(ao_mdl.yunits);
+
−    
+
−    % Set smodel xvals
+
−    smodel_mdl.setXvals(ao_mdl.x);
+
−    
+
−    % Eval the smodel
+
−    d = smodel_mdl.double();
+
−    
+
−    % Compare the numbers
+
−    results = [results; test check_correctness(d, ao_mdl.y, plist('tol', TOL))];
+
−  end
+
−  
+
−  %% 51 Step, high fs and high nsecs
+
−  test = 51;
+
−  if any(ismember(list, test))
+
−    
+
−    % Pick the model
+
−    model_def = 'step';
+
−    
+
−    % Decide the tolerance of the test ([] or 0 for no tolerance)
+
−    TOL = 0;
+
−    
+
−    % Set parameters: duration and rate
+
−    nsecs = 10000;
+
−    fs    = 1000;
+
−    
+
−    % Extract the information from the ao model default plist
+
−    ao_mdl_info = eval(['ao_model_' model_def '(''info'')']);
+
−    pl = ao_mdl_info.plists;
+
−    
+
−    A    = find(pl, 'A');
+
−    toff = find(pl, 'toff');
+
−    
+
−    % Build the ao model
+
−    ao_mdl = ao(plist('built-in', model_def, 'nsecs', nsecs, 'fs', fs));
+
−    
+
−    % Build the smodel model
+
−    smodel_mdl = smodel(plist('built-in', model_def));
+
−    
+
−    % Set smodel parameters
+
−    smodel_mdl.setParameters({'A','toff'}, {A,toff});
+
−    
+
−    % Set smodel yunits
+
−    smodel_mdl.setYunits(ao_mdl.yunits);
+
−    
+
−    % Set smodel xvals
+
−    smodel_mdl.setXvals(ao_mdl.x);
+
−    
+
−    % Eval the smodel
+
−    d = smodel_mdl.double();
+
−    
+
−    % Compare the numbers
+
−    results = [results; test check_correctness(d, ao_mdl.y, plist('tol', TOL))];
+
−  end
+
−  
+
−end
+
−
+
−function atest = check_correctness(smodel_y, ao_y, pl)
+
−  
+
−  % Exceptions plist for ao/eq
+
−  ple = plist('Exceptions', ...
+
−    {'created', 'proctime', 'UUID', 'param/desc', 'name', 'methodInvars', 'version'});
+
−  
+
−  % Start testing
+
−  atest = true;
+
−  
+
−  % Strict check or with tolerance?
+
−  tol = mfind(pl, 'tolerance', 'tol');
+
−  if ~isempty(tol) && tol > 0
+
−    % Check within tolerance
+
−    if any(abs(smodel_y - ao_y) ./ max(abs(smodel_y)) >= tol)
+
−      atest = false;
+
−    end
+
−  else
+
−    % Strict check on the values
+
−    if ~isequal(smodel_y, ao_y)
+
−      atest = false;
+
−    end
+
−  end
+
−  
+
−end