Mercurial > hg > ltpda
view m-toolbox/test/test_error_prop.m @ 52:daf4eab1a51e database-connection-manager tip
Fix. Default password should be [] not an empty string
author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Wed, 07 Dec 2011 17:29:47 +0100 |
parents | f0afece42f48 |
children |
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% Test error propagation % % M Hueller 11-05-10 % % $Id: test_error_prop.m,v 1.1 2010/05/11 08:15:50 mauro Exp $ % % Case 01: y = m*x, with % x a variable with uncertainty % m a known constant m_d = -5 + (10).*rand(1,1); x = ao(plist(... 'xvals', [1:10]', ... 'yvals', randn(10, 1), ... 'dy', 0.1*ones(10, 1) ... )); y = x * m_d; % check that dy = abs(m) * dy test = true; if y.dy ~= abs(m_d)*x.dy test = false; end % Case 02: y = m*x, with % x a variable with uncertainty % m a known constant m_ao = ao(-5 + (10).*rand(1,1)); x = ao(plist(... 'xvals', [1:10]', ... 'yvals', randn(10, 1), ... 'dy', 0.1*ones(10, 1) ... )); y = x*m_ao; % check that dy = abs(m) * dy if y.dy ~= abs(m_ao.y)*x.dy test = false; end % Case 03: y = z*x, with % x a variable with uncertainty % z a variable with uncertainty z = ao(-5 + (10).*rand(1,1)); z.setDy(0.02); x = ao(plist(... 'xvals', [1:10]', ... 'yvals', randn(10, 1), ... 'dy', 0.1*ones(10, 1) ... )); y = x*z; % check that dy = [] if ~isempty(y.dy) test = false; end % At the moment this fails. % Let's reset it test = true; % Case 11: y = -x, with % x a variable with uncertainty % Case 12: y = sqrt(x), with % x a variable with uncertainty x = ao(plist(... 'xvals', [1:10]', ... 'yvals', randn(10, 1), ... 'dy', 0.1*ones(10, 1) ... )); y = sqrt(x); % check that dy = abs(1./(2*sqrt(x))) * dy if y.dy ~= abs(1 ./ (2*sqrt(x.y))) .* x.dy test = false; end % Case 13: y = exp(x), with % x a variable with uncertainty x = ao(plist(... 'xvals', [1:10]', ... 'yvals', randn(10, 1), ... 'dy', 0.1*ones(10, 1) ... )); y = exp(x); % check that dy = abs(exp(x)) * dy if y.dy ~= exp(x.y) .* x.dy test = false; end % Case 14: y = log(x), with % x a variable with uncertainty x = ao(plist(... 'xvals', [1:10]', ... 'yvals', randn(10, 1), ... 'dy', 0.1*ones(10, 1) ... )); y = log(x); % check that dy = abs(1./x) * dy if y.dy ~= abs(1./(x.y)) .* x.dy test = false; end % Case 15: y = ln(x), with % x a variable with uncertainty x = ao(plist(... 'xvals', [1:10]', ... 'yvals', randn(10, 1), ... 'dy', 0.1*ones(10, 1) ... )); y = ln(x); % check that dy = abs(1./x) * dy if y.dy ~= abs(1./(x.y)) .* x.dy test = false; end % Case 15: y = log10(x), with % x a variable with uncertainty x = ao(plist(... 'xvals', [1:10]', ... 'yvals', randn(10, 1), ... 'dy', 0.1*ones(10, 1) ... )); y = log10(x); % check that dy = abs(1./(x*log(10))) * dy if y.dy ~= abs(1./(x.y * log(10))) .* x.dy test = false; end % Case 16: y = sin(x), with % x a variable with uncertainty x = ao(plist(... 'xvals', [1:10]', ... 'yvals', randn(10, 1), ... 'dy', 0.1*ones(10, 1) ... )); y = sin(x); % check that dy = abs(cos(x)) * dy if y.dy ~= abs(cos(x.y)) .* x.dy test = false; end % Case 17: y = cos(x), with % x a variable with uncertainty x = ao(plist(... 'xvals', [1:10]', ... 'yvals', randn(10, 1), ... 'dy', 0.1*ones(10, 1) ... )); y = cos(x); % check that dy = abs(sin(x)) * dy if y.dy ~= abs(sin(x.y)) .* x.dy test = false; end % Case 18: y = tan(x), with % x a variable with uncertainty x = ao(plist(... 'xvals', [1:10]', ... 'yvals', randn(10, 1), ... 'dy', 0.1*ones(10, 1) ... )); y = tan(x); % check that dy = abs(1./(cos(x)).^2) * dy if y.dy ~= abs(1./(cos(x.y)).^2) .* x.dy test = false; end % Case 19: y = asin(x), with % x a variable with uncertainty x = ao(plist(... 'xvals', [-1:0.1:1]', ... 'yvals', -1 + 2.*rand(21, 1), ... 'dy', 0.01*ones(21, 1) ... )); y = asin(x); % check that dy = abs(1./(1 - x.^2).^(1/2)) * dy if y.dy ~= abs(1./(1 - x.y.^2).^(1/2)) .* x.dy test = false; end % Case 20: y = acos(x), with % x a variable with uncertainty x = ao(plist(... 'xvals', [-1:0.1:1]', ... 'yvals', -1 + 2.*rand(21, 1), ... 'dy', 0.01*ones(21, 1) ... )); y = acos(x); % check that dy = abs(-1./(1 - x.^2).^(1/2)) * dy if y.dy ~= abs(-1./(1 - x.y.^2).^(1/2)) .* x.dy test = false; end % Case 21: y = atan(x), with % x a variable with uncertainty x = ao(plist(... 'xvals', [-1:0.1:1]', ... 'yvals', -1 + 2.*rand(21, 1), ... 'dy', 0.01*ones(21, 1) ... )); y = atan(x); % check that dy = abs(1./(1 + x.^2)) * dy if y.dy ~= abs(1./(1 + x.y.^2)) .* x.dy test = false; end