mathc | Pure C math library for 2D and 3D programming | Math library

I have two sf datasets and I want to find the 10 closest neighbors, based not only on distance but also on mathcing another column. For example:

I want to create an Angular Material Autocomplete form control with two ways to filter the selectable options:

1. The default way, when the user types in the text input, and only the options mathcing the search term will be visible, like in the examples on the Angular Material website.
2. Above the autocomplete component there's a category select form control. When a category is chosen, I want to display only the elements in the chosen category, and allow the user to only search in these elements with the autocomplete text input.

Here is my code in the component class:

I am trying to make an offline PWA planner targeted to phones and I have no need at all for user data or interaction with my home page after installation.

Everything works fine on my PC and Lighthouse gives a clean bill of health, but on my phone (S8) the PWA does not work as expected in Chrome and Firefox when I am offline. Minimizing the app and tapping the installed icon works in Chrome as long as I am online, but occasionally gives a black screen in Firefox, especially if the app has lost focus for a while.
Going offline causes Chrome to ignore the cached files and complain about lack of connectivity if reloaded, for example after a phone restart or closing all apps. Firefox just hangs with a white or black screen.

I cache my index.html file and have a suspicion that reinstalling the service worker on reload will flush the cache if offline, but despite extensive searches I haven't been able to find a way around this - or even a mentioning.
I experience the same problem on a Samsung S5 and on an iPad.

Included below is the script in my html header:

I have two phrases:

I have a pandas dataframe where I'm using the numpy library to determine whether the values in two columns are the same. I run into problems with the values in these columns being blank/NaN and the dataframe reporting that they are differnet although they both show as NaN. What is the best way to handle NaN when doing this analysis?

I have two files that I load into dataframes and then I merge the two on a unique key into the mathced dataframe and then do the following to find differences:

I would like to find all mathces by such pattern: (one letter)(three figures)(two letter)(two or three figures).

So my python regular expression is:

build data :

I have written an integration for the AWS SDK in PHP to send the keys for files on an S3 bucket and retrieve a pre-signed url, which more or less follows this example. This worked perfectly except I need to now check if the file exists on s3 and return empty string if it does not.

I am doing this with my code below:

I have a code that generates some word using some logic and i have regex 1 (see down). But i need to generate right word such as words 1. My logic includes mathcing pattern i mentioned. I need right pattern to generate words such as in words 1 instead 2. The logic for the pattern is:

1. the word starts with the uppercase vowel or consonant
2. the length is 2 or more symbols (of the whole word)
3. there is should not be more than two vowels or consonants in a row