euler.m #158
euler.m #158
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june128
added
the
Implementation
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Welcome to the team @vasilisk075, thank you for submitting code :)
| % Loop over time | ||
| while succes==0 | ||
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| t(i+1) = t(i) + dt; % Calculate next time |
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Dynamically growing vector sizes is bad practice, they should always be predefined. For t is is very easy to do since you already know the bounds and the time difference.
| y(i+1) = y(i) + f( y(i) )*dt; % Update solution | ||
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| % Calculate differce between 2 time steps | ||
| error=abs(( y(i+1) - y(i) )/dt); |
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I wouldn't call this error, it's not an error, it's a slope. I also wouldn't use that as an indication that the computation is over. I would simply predefine the time vector, calculate the function for all time steps and plot that.
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I understand your idea but ODEs usually reach a SteadyState, and this particular surely does, so why waste time computing something that practically stays the same?
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What if your function was actually a sinusoidal function? It would stop at the first extremum. In general you don't have prior knowledge of the function, and computational time is dirt cheap nowadays.
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It is dirt cheap, if you talk about small problems like that! Generally when i run a big simulation based on some differential equation, i need a creteria indicating that Steady State is reached and thus terminating the simulation. Normaly a don't know the amount of time steps needed for that.
But either way, i think that it is a long discussion, so i am going to update the code according to your suggestions.
Thank you!
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Well, yeah, real world is more complex of course. Let's keep it simple here :)
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Also if you want your code to be included in the website, you should include the code in the chapter |
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I'll do the EditorConfig once this is merged. |
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#166 adds Matlab to book.json. Let's just merge that one first and we don't have to deal with it here. |
Implementation of Forward Euler method on Matlab
Matlab implementation of the Forward_Euler method