spaced | web app to help you memorize anything

I am trying to obtain the upper convex hull, in R, of a set of points relating to productivity data. I expect it to be a function with decreasing returns to scale, with the input being worker hours and output being a measure of work done. I would like the upper convex hull because this would allow me to get the efficiency frontier.

I have searched and found the method chull in R, but this gives the set of points in the whole envelope and not just the upper hull points. Is there a way to automatically select the upper hull points in R?

As an example, we can find the upper hull of a points generated in a circle

For practice I've implemented the qoi specification in rust. In it there is a small hash function to store recently used pixels:

index_position = (r * 3 + g * 5 + b * 7 + a * 11) % 64

where r, g, b, and a are the red, green, blue and alpha channels respectively.

I assume this works as a hash because it creates a unique prime factorization for the numbers with the mod to limit the number of bytes. Anyways I implemented it naively in my code.

While looking at other implementations I came across this bit hack to optimize the hash calculation:

Below you will find my python code for a class assignment I was given a couple weeks ago which I have been unable to successfully debug. The problem is about finding the value at risk (i.e., the p% quantile) for an aggregate loss random variable, using FFT. We are given a clear mathematical procedure by which we can gain an estimation of the discretized CDF of the aggregate loss random variable. My results are, however, seriously off and I am making some kind of mistake which I have been unable to find even after hours of debugging my code.

The aggregate loss random variable S is given such that S=sum(X_i for i in range(N)), where N is negative binomially distributed with r=5, beta=.2, and X_i is exponentially distributed with theta=1. The probability generating function for this parametrization is P(z)=[1-\beta(z-1)]^{-r}.

We were asked to approximate the distribution of S by

1. choosing a grid width h and an integer n such that r=2^n is the number of elements to discretize X on,
2. discretizing X and calculating the probabilities of being in equally spaced intervals of width h,
3. applying the FFT to the discretized X,
4. applying the PGF of N to the elements of the Fourier-transformed X,
5. applying the inverse FFT to this vector.

The resulting vector should be an approximation for the probability masses of each such interval for S. I know from previous methods that the 95% VaR ought to be ~4 and the 99.9% VaR ought to be ~10. But my code returns nonsensical results. Generally speaking, my index where the ECDF reaches levels >0.95 is way too late, and even after hours of debugging I have not managed to find where I am going wrong.

I have also asked this question on the math stackexchange, since this question is very much on the intersection of programming and math and I have no idea at this moment whether the issue is on the implementation side of things or whether I am applying the mathematical ideas wrong.

I'm having an issue with the linting for my Vue SPA. I'm using the defineEmits function from the script setup syntactic sugar (https://v3.vuejs.org/api/sfc-script-setup.html). The errors just do not make any sense, does anyone know how to fix this (without disabling these rules for the affected files, because it happens to every usage of defineEmits). The weird thing is that the defineProps function works without errors, which follows the same syntax. Can anyone help me out here?

My linter complains about these errors:

I am new to using tkinter and am struggling to get my buttons to render at the very bottom of the screen, evenly spaced out, filling the entire bottom row.

I have been using grid() to try to do this but no luck. I want these three buttons to render without impacting other components of the page(such as the text at the top). I am trying to accomplish a window that has three buttons, each button rendering a different page that you can interact with.

Here is my full code below, I appreciate any insight at all more than you know.

I am working on a p2p application and to make testing simple, I am currently using udp broadcast for the peer discovery in my local network. Each peer binds one udp socket to port 29292 of the ip address of each local network interface (discovered via GetAdaptersInfo) and each socket periodically sends a packet to the broadcast address of its network interface/local address. The sockets are set to allow port reuse (via setsockopt SO_REUSEADDR), which enables me to run multiple peers on the same local machine without any conflicts. In this case there is only a single peer on the entire network though.

This all works perfectly fine (tested with 2 peers on 1 machine and 2 peers on 2 machines) UNTIL a network interface is disconnected. When deactivacting the network adapter of either my wifi or an USB-to-LAN adapter in the windows dialog, or just plugging the usb cable of the adapter, the next call to sendto will fail with return code 10049. It doesn't matter if the other adapter is still connected, or was at the beginning, it will fail. The only thing that doesn't make it fail is deactivating wifi through the fancy win10 dialog through the taskbar, but that isn't really a surprise because that doesn't deactivate or remove the adapter itself.

I initially thought that this makes sense because when the nic is gone, how should the system route the packet. But: The fact that the packet can't reach its target has absolutely nothing to do with the address itsself being invalid (which is what the error means), so I suspect I am missing something here. I was looking for any information I could use to detect this case and distinguish it from simply trying to sendto INADDR_ANY, but I couldn't find anything. I started to log every bit of information which I suspected could have changed, but its all the same on a successfull sendto and the one that crashes (retrieved via getsockopt):

in my program I defined a data type called Lyapunov_orbit that contains 8 fields, then I used it to read data from external .txt file (see below where I report only a few lines for convenience because the file has about 4000 lines). I need to perform some operations by using such structure (as to find minimum and maximum value of an array) but to handle it I had to declare an "auxiliary" variable called vec_J_cst because if I try to directly use my data strucutre, I get some errors (the structure-name is invalid or missing).

Here is the .txt file:

I would like to know if there is a Python functionality in either Numpy or SciPy that allows to shift arrays over non-uniform grids. I have created a minimal example to illustrate the procedure, but this does not seem to work in this minimal example:

Is it possible to combine Arrangement.spacedBy(16.dp) and Arrangement.Center in a Row.horizontalArrangement?

What I would like to do is to center the content horizontally and also set a default spacing of 16.dp.

I know that I can combine the Row and a Box to achieve the same result but I was wondering if can be done with just he Row's properties.