combi | ️ A tiny keyboard shortcut | Keyboard library

I was working on a binomial expansion in R, I came across some issues and I feel the values do not make sense. Here is my code, I used factorial and combination from "scratch" to compute. I tried x=6, y=2 and n=4 I got 2784 as an answer. If I try 1 it gives 0. If n=i I get infinity because the denominator would equal zero

I'm facing a problem with vectorizing a function so that it applies efficiently on a numpy array.

My program entries :

• A pos_part 2D Array of Nb_particles lines, 3 columns (basicaly x,y,z coordinates, only z is relevant for the part that bothers me) Nb_particles can up to several hundreds of thousands.
• An prop_part 1D array with Nb_particles values. This part I got covered, creation is made with some nice numpy functions ; I just put here a basic distribution that ressembles real values.
• A z_distances 1D Array, a simple np.arange betwwen z=0 and z=z_max.

Then come the calculation that takes time, because where I can't find a way to do things properply with only numpy operation of arrays. What i want to do is :

• For all distances z_i in z_distances, sum all values from prop_part if corresponding particle coordinate z_particle < z_i. This would return a 1D array the same length as z_distances.

My ideas so far :

• Version 0, for loop, enumerate and np.where do retrieve the index of values that I need to sum. Obviously quite long.
• Version 1, using a mask on a new array (combination of z coordinates and particle properties), and sum on the masked array. Seems better than v0
• Version 2, another mask and a np.vectorize, but i understand it's not efficient as vectorize is basicaly a for loop. Still seems better than v0
• Version 3, I'm trying to use mask on a function that can I directly apply to z_distances, but it's not working so far.

So, here I am. There is maybe something to do with a sort and a cumulative sum, but I don't know how to do this, so any help would be greatly appreciated. Please find below the code to make things clearer

Thanks in advance.

I have an array that has first rows as header:

I made a code to generate combinations based on first, second, third, fourth, fifth and sixth input. However, it is taking a long time: it usually takes 86-88 seconds.

Is there a faster and better way to do this?

I have a list of lists populated with integers. These integers represent nodes in a graph and the lists in the main list represent cycles in the graph. I want to extract a unique set of nodes - one node from each cycle - in the order of the list of lists.

Example:

I know, it's not possible to have a cycle with only two nodes, but it is the easiest non trivial example i came up with and it should make clear what I am looking for.

I have built a function which pulls in values provided by an end user and produces a graph as a result.

The user has the option to provide a site, which can be either a single value or multiple:

I need to exclude any instance of six values from a dataset that I have and wonder if there is an "all-in-one" solution to achieve this.

Aside from the usual

I have some trouble using C++17 parallel execution algorithm with Boost iterators on MSVC. Here is my code:

Hej, I´m an absolute beginner in Python (a linguist by training) and don´t know how to put the twitter-data, which I scraped with Twint (stored in a csv-file), into a DataFrame in Pandas to be able to encode nltk frequency-distributions. Actually I´m even not sure if it is important to create a test-file and a train-file, as I did (see code below). I know it´s a very basic question. However, to get some help would be great! Thank you.

This is what I have so far: