> For the complete documentation index, see [llms.txt](https://kuckelkorn.gitbook.io/filter-bubble-machine-product-biografie/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://kuckelkorn.gitbook.io/filter-bubble-machine-product-biografie/product-biography/week-2.md).

# Week 2

### Notes from logbook

> I started this week with remembering the little knowledge of D3 I still had left. I was able to plot all the nodes on a plane. After that, I was going to focus on making the links between nodes. On Tuesday I moved my sandbox code to the project and made some changes to the code, I also started watching some tutorials on D3 links, with no prevail. Because I couldn't figure out how to make links between nodes, I decided to shift the focus to restructuring the code for the rest of the day. Wednesday I had a code review and further worked on the network graph, still wasn't able to create links between nodes. On Thursday, I left the links alone for a minute and made some progress on the autoplay function. There are some limitations regarding the API, for now it is hard for me to tell if there are too many API call's or there is a different issue, but it stops at around 25 steps for the first run, then takes 5 steps on the second run, and it scales further down. For the next day, the goal is to solve this problem and add the possibility of adding a pause option.

[Logbook](https://github.com/Kuckelkorn/bubble-machine/wiki/Logbook)

### Deep dive of this week's work

So earlier in the year I already had the opportunity to learn the d3 client, so I started looking at the code I wrote previously and implemented it on the current API. Previous project. This made the choice to use D3 a lot easier because it is the most complete library when it comes to reading data with the added bonus of the "simplicity" of making a chart. From the API we received nodes and links. I had a look at the Force directed graph. However, this wouldn't be a good representation of the graph we are trying to represent. So I made a scatter plot with the intent to show the links. However, I wasn't able to progress much on the links part. So, having only the plot with a circle on every node, I went further with a different function of the application.    &#x20;

![First visualisation of the scatterplot](https://user-images.githubusercontent.com/49679168/174834252-2c3b01de-fa7e-4a4c-a430-6946bcaebf75.png)

[Earlier project with D3](https://github.com/Kuckelkorn/frontend-data)

The auto run function, was the next step in the process. The client would have liked to implement websockets within the application. However, the API wasn't ready for it and in the demo of the clients' application there was an auto run function. That function wasn't build in the API, so we had to come up with a workaround. I came up with a workaround by making a loop that went through all the steps with a delay, otherwise the API couldn't keep up with all the requests. The delay also made it possible that the graph got more readable when on the auto run function.&#x20;


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