Week 4 – Data Viz Wind Turbines

Concept:
During class on Wednesday, one of the example datasets that was brought up in class was wind data as the professor played with the globe data visualization. When I saw the wind data, I immediately thought of drawing wind turbines that matched the wind speed data, and that’s what I ended up doing for this project.

Sketch:

While in the planning phase, I thought that this project would be just fun to look at and not a data-focused piece, but this had the unexpected result of being surprisingly insightful about wind speeds during the day. The wind is strongest during the day at about 14:00-17:00, and weakest around midnight to late morning.

Code: 
I was proud of my day/ night cycle code, as I thought it was clever. I drew a black box over the entire screen, and the opacity changes depending on the time of day so it is able to give off a feeling of ‘darkness’ during midnight hours, and it is fully transparent during the daytime.

// opacity of black screen over the screen to give illusion of day/night cycle
const darknessLevel = mapOfHourToDarkness[curHour - 1]
push()
fill(0, 0, 0, darknessLevel * 5)
square(0, 0, 400)
pop()

// complex math -- basically calculates the curSkyColor as an average of darkSky and brightSky, weighted towards darkSky based on the current darknessLevel
curSkyColor = p5.Vector.add(p5.Vector.mult(darkSkyColor, darknessLevel), p5.Vector.mult(brightSkyColor, 10 - darknessLevel)).div(10)

Improvements
There was more data in my .CSV file including wind direction, but I couldn’t think of a good way to implement but it would’ve been nice. I was also not able to find a free API for UAE wind data, and I had to manually scrape the data for a certain day. It would have been fun to be able to visualize the wind speeds of the current/previous day instead of being stuck on 27 Sept 2023.