In the previous part of this tutorial, Improving the Rainbow – Part 1, we have seen different techniques to reproduce the colours of the rainbow procedurally. Solving this problem efficiently will allow us to simulate physically based reflections with a much higher fidelity.
The purpose of this post is to introduce a novel approach that yields better results than any of the previous solutions, without using any branching.
You can find the complete series here:
A link to download the Unity project used in this series is also provided at the end of the page.
This post shows how it is possible to find the position of an object in space, using a technique called trilateration. The traditional approach to this problem relies on three measurements only. This tutorial addresses how to it is possible to take into account more measurements to improve the precision of the final result. This algorithm is robust and can work even with inaccurate measurements.
If you are unfamiliar with the concepts of latitude and longitude, I suggest you read the first post in this series: Understanding Geographical Coordinates.
This series introduces the concept of trilateration. This technique can be applied to a wide range of problems, from indoor localisation to earthquake detection. This first post provides a general introduction to the concept of geographical coordinates, and how they can be effectively manipulated. The second post in the series, Positioning and Trilateration, will cover the actual techniques used to identify the position of an object given independent distance readings. Most trilateration tutorials require the measures from the sensors to be precise and consistent. The approach here presented, instead, is highly robust and can tolerate inaccurate readings.
The previous post in this series, Understanding Deep Dreams, explained what deep dreams are, and what they can be used for. In this second post you’ll learn how to create them, with a step by step guide.
Despite being a very serious language, Python is full of Easter eggs and hidden references. This post shows the top 5:
- Hello World…
- The Zen of Python
- C-Style braces instead of indentation
- Monthy Python references
I have covered the 5 most interesting features of Python in this post. Continue reading
Python aims to be an elegant and expressive language; this post includes its top 5 hidden features:
- List slicing
- For…else syntax
- Yield statement
- Multiple assignments
- Argument unpacking
The term hidden is loosely used to indicate features which are generally unique to Python, or not very well known. I covered the most interesting Easter eggs which are really hidden in Python in this post. Continue reading
This tutorial shows how to download videos from YouTube and to process their frames with Python; I have used this technique to create game barcode, an image created by sorting the colours in each frame of a particular video. You can see some of most intriguing here:
This tutorial is divided in four parts:
You can find a high resolution version of the melancoil tree (2000x2000px, first 1000 numbers) here: PNG, SVG, HTML. Continue reading
This post is for all the developers and mathematicians out there that are curious to explore and visualize the bizarre properties of numbers. Although Maths plays an important role in today’s technology, many people likes to
abuse it for recreational purposes. Part of the appeal of Recreational Maths lies in the challenge to discover something new. Despite what many believe, finding mathematical patterns is very easy; it’s discovering something useful that is incredibly challenging. If you’re up for such a challenge, this tutorial will teach you how to use Python to calculate some of the most infamous numerical sequences.
Let’s start with something trivial: sorting numbers. Regardless of the algorithm you’ll use, real numbers are naturally ordered. Mathematically speaking, they have a total order, in the sense that you can always decide if a number is greater than another one. There is no ambiguity in this, meaning you can actually sort them, and (excluding duplicates) this sort is unique. There are other fields which are not that lucky: colour, for instance, are very unlucky. Supposing you’re representing colours with their RGB values, there is no standard way to order triples in a line, since they are naturally not organised in a line fashion. The problem is even more complicated since colours have a meaning in the real world. How can we sort colours so that they look as continuous as possible? Which parameters affects the sorting order? Is azure closer to blue (similar hue) or to cyan (similar luminosity)? I can stop you all here and say that there is no solution to this problem. You can sort colours, but the overall result depends on what you are trying to achieve. This post will explore how colours can be sorted, and how this can lead to very different results.