fli | Just like you can use Git | Continuous Backup library

With those changes, I'm able to acheive 3 to 4 stable delay ;)

LINE 79 of

https://github.com/OpenVidu/openvidu/blob/master/openvidu-server/docker/openvidu-recording/scripts/composed.sh

I REPLACED

You are creating axes on each iteration of the loop with this line

A segmentation fault happens when the code try to access a memory region that is not available.

Accessing an array out of bounds doesn't means that the memory before or after the area occupied by the array is not available: The compiler or the runtime usually put all varibales or data in general in a given block of memory. If your array is the last item of such a memory block, the accessing it with a to big index will produce a Segmentaion Fault but is the array is in the middle of the memory block, you will just access memory used for other data, giving unexpected result and undefined behavior.

If the array (In may example, but valid for anything) is written, accessing available memory will not produce a segmentation fault but will overwrite something else. It may produce unexpected results or crash or segmentation fault later! This kind of bug is frequently very difficult to find because the unexpected result/behavior looks completely independent of the root cause.

This is probably due to the step size control being also influenced by the rapidly growing v vector. Either by regulating step sizes rapidly down due to stiffness, or more likely, due to increasing the step size to match the dominant components, thus becoming unsuitable for an exact integration of the original trajectory. This rapid growth is the reason that Lyapunov exponents were introduced, as they capture this growth in nicely bounded numbers.

What you can do is to split up the integration into smaller chunks and normalize the v vector at the start of each chunk. One would have to experiment on how long it takes until the v component unduly dominates the step size control. As the coupling is purely multiplicative, the dynamic theoretically is linear. So it could also help if you scale the initial v to have norm 1e-100.

First however check what error tolerances you use. Setting them narrower also tends to stabilize the computation. You might also get some progress be setting the maximal step size hmax to half or so of the external step.

Or you could do the Lyapunov exponent computation like I explored in https://scicomp.stackexchange.com/questions/36013/numerical-computation-of-lyapunov-exponent. This approach however increases a system of dimension n by the n x n matrix of eigen/singular vectors and the n products of exponents times time.

You need to make the blocks list a property of the room class, and then draw them in draw. Notice how in draw, I call

The DWARF file in the dSYM only has symbol information & debug information in it, it does not contain a complete copy of the binary's TEXT & DATA segments. If there is a copy of the binary next to the dSYM on the file system lldb will load that when it loads the dSYM. Or you can use the target modules add command to tell lldb to load the binary into the current session.

In ToDoList.svelte you are calling deleteTodo(todo) but deleteTodo is undefined. Svelte should really throw a better error message here...

Edit:

Also, if you assign an event handler, you want to pass in a reference to a function like on:deleteTodo = {() => deleteTodo(todo)} or on:deleteTodo = {deleteTodo} and not call the function directly.