ΟĨΝΟΨ ΠÓΝΤΟΣ

or, actually

Computer simulating of color perception's evolution in linguistics.

What?

I've been asking myself this question for all the time I've been doing this project, mostly because there has been no clear and strict formulating not only of its purposes - but of its actual meaning without all those cranky "ummmmm" and "well, its kinda serious problem".

But back to the question.

As any single word in any language - whether it's Spanish, Sanskrit or Mandarin - the terms (in linguistics and formal logic definition) to describe colors evolved, as languages became more complex and developed.

Why?

1. It's a complicated question in linguistics and cognitive linguistics and psycholinguistics, that is a possible key to prove the concept of Linguistics Relativity - or eliminate it.
2. As many natural processes, linguistics' ones could not be performed in an experimental way - the possibly ten-thousand-years-lasting processes unrepeatable due to obvious reasons, - so the only way to study them is by studying their models.
3. This is an interesting case of connecting fields of science that seem to be unrelated - linguistics, biology, and data science.
4. And its ambitious, hilarious and complex project - why not implement it?

How?

• Dataset - generated colourSet.csv of different variables representing RGB.
• Clustering method - AgglomerativeClustering from sklearn.cluster
• Visualization - tkinter

Aim?

Reproduce the sequence of basic color acquiring by Berlin and Kay:

1. Dark-cool and light-warm (this covers a larger set of colors than English "black" and "white".)
2. Red
3. Either green or yellow
4. Both green and yellow
5. Blue
6. Brown
7. Purple, pink, orange, or gray

Results?

Kinda interesting...