view m-toolbox/test/test_ao_removeVal.m @ 22:b11e88004fca database-connection-manager

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author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 16:20:06 +0100
parents f0afece42f48
children
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% Test ao/removeVal for:
% - functionality
%
% M Hueller 10-03-10
%
% $Id: test_ao_removeVal.m,v 1.1 2010/03/13 06:36:20 mauro Exp $
%

%% Start with an AO with no "bad" data in it
a_orig = ao(plist(...
  'waveform', 'sinewave', ...
  'Nsecs', 100, ...
  'fs', 1, ...
  'f', 0.02, ...
  'yunits', 'V', ...
  't0', '2010-03-10 20:00:00.000' ...
  )) + 2;
a_orig.setName('original');

%% 1) Test the case where we remove only Inf, removing data
value = Inf;
% Prepare a list of index where we add the "bad" points
N   = randi(10, 1);
bad_index   = randi(numel(a_orig.x), N, 1);

% Mix the AO with the "bad" values
y_orig = a_orig.y();
y_bad = y_orig;
y_bad(bad_index)   = value;
a_bad = a_orig.setY(y_bad);
a_bad.setName('corrupted');

% Run the ao/removeVal method
a_clean = a_bad.removeVal(plist('value', value));
a_clean.setName('cleaned');

% Compare against the original:
% units
if ~eq(a_clean.yunits, a_bad.yunits)
  disp('Warning: wrong yunits!');
end
if ~eq(a_clean.xunits, a_bad.xunits)
  disp('Warning: wrong xunits!');
end

% t0
if ~eq(a_clean.t0, a_bad.t0)
  disp('Warning: wrong t0!');
end

index   = true(size(a_bad.x));
index(bad_index) = false;

% "good" values: x
x_clean = a_clean.x;
x_bad   = a_bad.x;
if ~eq(x_bad(index), x_clean)
  disp('Warning: wrong x values!');
end

% "good" values: y
y_clean = a_clean.y;
y_bad   = a_bad.y;
if ~eq(y_bad(index), y_clean)
  disp('Warning: wrong y values!');
end

%% 2) Test the case where we remove only NaN, removing data
value = NaN;
% Prepare a list of index where we add the "bad" points
N   = randi(10, 1);
bad_index   = randi(numel(a_orig.x), N, 1);

% Mix the AO with the "bad" values
y_orig = a_orig.y();
y_bad = y_orig;
y_bad(bad_index)   = value;
a_bad = a_orig.setY(y_bad);
a_bad.setName('corrupted');

% Run the ao/removeVal method
a_clean = a_bad.removeVal(plist('value', value));
a_clean.setName('cleaned');

% Compare against the original:
% units
if ~eq(a_clean.yunits, a_bad.yunits)
  disp('Warning: wrong yunits!');
end
if ~eq(a_clean.xunits, a_bad.xunits)
  disp('Warning: wrong xunits!');
end

% t0
if ~eq(a_clean.t0, a_bad.t0)
  disp('Warning: wrong t0!');
end

index   = true(size(a_bad.x));
index(bad_index) = false;

% "good" values: x
x_clean = a_clean.x;
x_bad   = a_bad.x;
if ~eq(x_bad(index), x_clean)
  disp('Warning: wrong x values!');
end

% "good" values: y
y_clean = a_clean.y;
y_bad   = a_bad.y;
if ~eq(y_bad(index), y_clean)
  disp('Warning: wrong y values!');
end


%% 3) Test the case where we remove only 0s, removing data
value = 0;
% Prepare a list of index where we add the "bad" points
N   = randi(10, 1);
bad_index   = randi(numel(a_orig.x), N, 1);

% Mix the AO with the "bad" values
y_orig = a_orig.y();
y_bad = y_orig;
y_bad(bad_index)   = value;
a_bad = a_orig.setY(y_bad);
a_bad.setName('corrupted');

% Run the ao/removeVal method
a_clean = a_bad.removeVal(plist('value', value));
a_clean.setName('cleaned');

% Compare against the original:
% units
if ~eq(a_clean.yunits, a_bad.yunits)
  disp('Warning: wrong yunits!');
end
if ~eq(a_clean.xunits, a_bad.xunits)
  disp('Warning: wrong xunits!');
end

% t0
if ~eq(a_clean.t0, a_bad.t0)
  disp('Warning: wrong t0!');
end

index   = true(size(a_bad.x));
index(bad_index) = false;

% "good" values: x
x_clean = a_clean.x;
x_bad   = a_bad.x;
if ~eq(x_bad(index), x_clean)
  disp('Warning: wrong x values!');
end

% "good" values: y
y_clean = a_clean.y;
y_bad   = a_bad.y;
if ~eq(y_bad(index), y_clean)
  disp('Warning: wrong y values!');
end


%% 4) Test the case where we remove Inf AND NaN AND 0s, removing data
% Prepare a list of index where we add the "bad" points
N_nan   = randi(10, 1);
N_inf   = randi(10, 1);
N_zeros = randi(10, 1);
nan_index   = randi(numel(a_orig.x), N_nan, 1);
inf_index   = randi(numel(a_orig.x), N_inf, 1);
zeros_index = randi(numel(a_orig.x), N_zeros, 1);

% Mix the AO with NaN, Inf, and 0s inside
y_orig = a_orig.y();
y_bad = y_orig;
y_bad(nan_index)   = NaN;
y_bad(inf_index)   = Inf;
y_bad(zeros_index) = 0;
a_bad = a_orig.setY(y_bad);
a_bad.setName('corrupted');

% Run the ao/removeVal method
value = [Inf NaN 0];
a_clean = a_bad.removeVal(plist('value', value));
a_clean.setName('cleaned');

% Compare against the original
% units
if ~eq(a_clean.yunits, a_bad.yunits)
  disp('Warning: wrong yunits!');
end
if ~eq(a_clean.xunits, a_bad.xunits)
  disp('Warning: wrong xunits!');
end

% t0
if ~eq(a_clean.t0, a_bad.t0)
  disp('Warning: wrong t0!');
end

index   = true(size(a_bad.x));
index(nan_index) = false;
index(inf_index) = false;
index(zeros_index) = false;

% "good" values: x
x_clean = a_clean.x;
x_bad   = a_bad.x;
if ~eq(x_bad(index), x_clean)
  disp('Warning: wrong x values!');
end

% "good" values: y
y_clean = a_clean.y;
y_bad   = a_bad.y;
if ~eq(y_bad(index), y_clean)
  disp('Warning: wrong y values!');
end

% plots the original, "bad", and "clean" data
iplot(a_orig, a_bad, a_clean, plist('LineStyles', {'-', '-', 'None'}, 'Markers', {'.', '.', 'o'}));

%% 5) Test the case where we remove Inf AND NaN AND 0s, interpolating data
% Prepare a list of index where we add the "bad" points
N_nan   = randi(10, 1);
N_inf   = randi(10, 1);
N_zeros = randi(10, 1);
nan_index   = randi(numel(a_orig.x), N_nan, 1);
inf_index   = randi(numel(a_orig.x), N_inf, 1);
zeros_index = randi(numel(a_orig.x), N_zeros, 1);

% Mix the AO with NaN, Inf, and 0s inside
y_orig = a_orig.y();
y_bad = y_orig;
y_bad(nan_index)   = NaN;
y_bad(inf_index)   = Inf;
y_bad(zeros_index) = 0;
a_bad = a_orig.setY(y_bad);
a_bad.setName('corrupted');

% Run the ao/removeVal method
value = [Inf NaN 0];
a_clean = a_bad.removeVal(plist('value', value, 'method', 'interp'));
a_clean.setName('cleaned');

% Compare against the original
% units
if ~eq(a_clean.yunits, a_bad.yunits)
  disp('Warning: wrong yunits!');
end
if ~eq(a_clean.xunits, a_bad.xunits)
  disp('Warning: wrong xunits!');
end

% t0
if ~eq(a_clean.t0, a_bad.t0)
  disp('Warning: wrong t0!');
end

% plots the original, "bad", and "clean" data
iplot(a_orig, a_bad, a_clean, plist('LineStyles', {'-', '-', 'None'}, 'Markers', {'.', '.', 'o'}));