mup | MUP is a markup previewer

I am trying to dispatch an action that modifies the "matrix" array in the state,the array is getting modified,but the component is updated only if I hardcode the returned array inside the MUp() function.

The Reducer:

A Meteor app created locally on a Windows 10, uses Meteor Up to deploy to a Ubuntu VPS. The app is running and accessable from the browser 185.148.129.235.

The server code reads the names of the files in a directory located in '/var/www/html/Audio' where an Apache serves its content to client browser, but please note the error below.

Also here is the mup.js file, Any help is much appricated to be able fix this error and read the names of the files in said locatioin.

I am developing a space shooter game using OpenGL. Trying to create a thruster effect for the player's spaceship using particles. I am facing a problem where the base of the thruster is not circular under some angles of the spaceship. You can see the effect in the video.

This is the code for calculating the circular base :

I am running into a file upload error with files > 10M. I have followed the advice here: http://meteor-up.com/docs.html#advanced-configuration which says how to set it in the nginx proxy by setting the clientUploadLimit: '50M'

I pushed the changes using mup proxy reconfig-shared, and it told me it had restarted the proxy. It didn't work, I still get the 413 (Request Entity Too Large) error.

I checked inside the nginx-proxy docker instance, and the file /etc/nginx/conf.d/my_proxy.conf has the correct entry client_max_body_size 50M. I restarted the EC2 box to make sure, but it's still not working.

This article https://www.tecmint.com/limit-file-upload-size-in-nginx/ suggests that the setting needs to go inside a http block, like this:

By default, Nginx has a limit of 1MB on file uploads. To set file upload size, you can use the client_max_body_size directive, which is part of Nginx’s ngx_http_core_module module. This directive can be set in the http, server or location context.

I have a simple meteor app, I want it to run on a local machine running Ubuntu in my local network with nginx so that it can be reachable from the browser with the machine's local IP address. I have tried using mup (meteor up) but it requires SSH keys and I have to use nginx so I have to deploy manually.

I would be appreciated if you can help me deploying the app, I can use and try different methods as long as it is running with nginx.

I don't need SSL at this point so I am trying to skip that step. Also, my MongoDB server is going to run on the same machine so I am trying to reach that locally too. I have tried this tutorial that is using forever to run meteor link but I couldn't figure to run it, also it does not explains how to configure my MongoDB URL and stuff.

I have Installed node, forever & meteor, created a new user, cloned my repository to my home server and I can run it with "meteor run" command locally.

I think I have problems with configuring nginx and the script that bundles the application that is explained in the tutorial I mentioned. I am not sure where to locate the env_settings.sh file. It is on my /etc/nginx/ directory.

here is my nginx config file

issues with Mutool and MuP

running this on MX-Linux: I'm trying to work with the latest release of MuPDF library.

if i a the document into pieces (A 5) then i get fancy results: the number of the pages (the pagination) does fulle get lost..

1,4,3,2,5, and so forth

btw: see the commands i run:

Im trying to deploy a project to AWS with Meteor Up plugin mup-aws-beanstalk. Instructions are pretty simple. Install plug in, get some info from your AWS account, modify a file with stuff related to your project, run the deploy command "mup deploy". Docs are here https://github.com/zodern/mup-aws-beanstalk/blob/master/docs/getting-started.md

After running the deploy command, I get this error/output

So my table(image) is :

I'm trying to repeatedly run a function that requires a few positional arguments and involves random number generation (to generate many samples of a distribution). For a MWE, I think this captures everything: