dom-walk | Iteratively walk any DOM node | Runtime Evironment library

I'm working on a Data Science dashboard project and am having trouble fine-tuning some of the container spacing. I've turned most of the page features off to reduce the scope of the problem. I'm trying to achieve 4 evenly spaced div containers in the 960x600 main container, however, the lower right div with subcontainers keeps throwing off the alignment. I'm sure there is a way to do this elegantly with HTML and CSS but coming from a background in Python I haven't been able to narrow down the root cause. Now after struggling all yesterday on it feel it's time to put up my hand and ask for help.

I am trying to init a new react native project via the React Native CLI. I am on the most recent version (2.0.1)

Then, I run the standard React Native Init command and the new project builds with all of these unmet peer dependency warnings:

I always use to develop my projects natively for Android and iOS, but after many people talking to me about react-native, I decided to give it a try.

However, I got very frustrated at the very first initial step: create my first project.

This is my environment:

• macOS Mojave 10.14
• Xcode 10.0
• node v10.12.0
• watchman 4.9.0
• react-native-cli: 2.0.1

When I run the command react-native init AwesomeProject, I see many warnings like this:

Let me first clarify that I'm not trying to generate random walk lines like in this and many other questions. I'm trying to make a random walk heat map that changes color as points are revisted, like this.

I've been able to create still-lifes like this: but I want to see the process.

I can get the figure to show up, and if I print the array at each step I can see that the walk is working. But the figure itself doesn't animate. My code:

I am currently reading Sutton's Reinforcement Learning: An introduction book. After reading chapter 6.1 I wanted to implement a TD(0) RL algorithm for this setting:

To do this, I tried to implement the pseudo-code presented here:

Doing this I wondered how to do this step A <- action given by π for S: I can I choose the optimal action A for my current state S? As the value function V(S) is just depending on the state and not on the action I do not really know, how this can be done.

I found this question (where I got the images from) which deals with the same exercise - but here the action is just picked randomly and not choosen by an action policy π.

Edit: Or this is pseudo-code not complete, so that I have to approximate the action-value function Q(s, a) in another way, too?

I have two procedures (Levy Walk and Correlated Random Walk movement strategies, each with their own buttons for debugging purposes, as well as their own parameter sets on the netlogo interface), but I have also embedded both the aforementioned procedures in a single "Go" procedure for batch simulation processing in the following code implementation:

I've managed to implement a continuous axis google chart on my page and got it formatted the way I want it. Now my requirements have changed and I'm trying to load this chart from a CSV as opposed to hard coded and randomly generated data.

I've confused myself and gotten in over my head on how to convert my working chart into pulling from a CSV. I'm going to post a few things here,

1. One of my other charts that utilizes a CSV, this is what I was trying to recreate
2. My working continuous axis chart running off hard coded data
3. My current state of the chart now that I've tried to implement the change.

Here is #1:

In this matlab post, one can find solution of "Loop erasing random walk" vector problem. This problem consists in "erasing loops" which means: removing integers between any integer repetition.

Example: