Procedural Calendar Generation & Lunar Phases
Nov 30, 2017
Here we are again! This is Part 3 of a small series on how to randomly generate a physically accurate calendar starting from planet’s orbital parameters. You can find the general motivation here, part one here and part two here.
Said that, here we go with the next part: lunar phases.
Why lunar phases Lunar phases are incredibly important in a calendar. So important, that many of the early humanity calendars are, in fact, lunar calendars or lunisolar calendars.
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Seasons Generation from Orbital Parameters
Nov 14, 2017
Welcome back to part 3 of the Procedural Calendar Generation series. In the first part we looked on how to compute celestial body position in a simple two-body system. The second part, instead is crash course on ellipse geometry.
In this part, instead, we will tackle a fascinating consequence of the cosmic dance of our planet around its sun: seasons. Seasons are a strange beast because their behavior depends on a huge amount of factors.
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Not every classification error is the same
Oct 18, 2017
In this article, I would like to talk about a common mistake new people approaching Machine Learning and classification algorithm often do. In particular, when we evaluate (and thus train) a classification algorithm, people tend to consider every misclassification equally important and equally bad. We are so deep into our mathematical version of the world that we forget about the consequences of classification errors in the real world.
But let’s start from the beginning.
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Cuphead is not "hard"
Oct 16, 2017
During the last few weeks, I’ve seen over and over people saying that Cuphead is hard. That it is brutal. That is the “dark souls of the side shooter”. For this reason, before this trend goes too far, it is time to make things clear: Cuphead is not hard.
Can a game that can easily beaten in a couple of hours be hard? No. It is challenging”, yes. It requires multiple tries, for sure.
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A Dwarf Fortress calendar in PureScript + Halogen
Oct 2, 2017
My last week project involves PureScript and Halogen and the Dwarf Fortress calendar. I wanted to give a first-hand experience with some pure functional language for web front-end and, after discarding Elm, I ended with PureScript. I will not go on a comparison between PureScript and the rest of the world. If you want a comparison among the other candidates, you can look at this very detailed article. (There is ClojureScript too, if Clojure will ever came back from the graveyard).
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Crash course on basic ellipse geometry
Sep 18, 2017
Because I started a small series about astronomical algorithms and the magic of math in space, I think we need to cover an important prerequisite. In the series, I will talk a lot about ellipses (duh), I will move from the semi-axis majors, to the periapsis, to eccentricity, to ellipse’s center and ellipse’s foci. I am concerned that things can get more complicated than expected if the readers does not know many of the geometric properties of the ellipse.
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WordPress abandoning React: a Facebook horror story
Sep 15, 2017
Today, during my daily web crawling, I found this article by Matt Mullenweg. I will not dwell in details, you can read the full story in the linked post. But I try to give you the core of the announcement: WordPress just decided to abandon React. This is a big news, with many implications and a few lessons to learn. Let’s go by steps.
The Context You are probably asking yourselves: why?
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Computing planetary orbits between two celestial objects
Sep 11, 2017
As you probably know, I am working (slowly) on an astronomically accurate calendar generator. All the orbital calculations involved are quite challenging, and I am discovering a lot. It is a lot of fun (except for the all the times I need to do some trigonometric magic to make some formula work). Anyway, during this process, I am reshaping and producing many many formulas. I am sure that in six months I will forget all the motivations behind them.
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How hidden variables in statistical models affect social inequality
Sep 9, 2017
Use of machine learning is becoming ubiquitous and, even with a fancy name, it remains a tool in the statistical modeler belt. Every day, we leak billions of data from ourselves to companies ready to use it for their affair. Modeling through data get more common every day and mathematical model are the rulers of our life: they decide where we can work, if we can get a loan, how many years of jails we deserve, and more.
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Playerunknown's Battlegrounds did everything wrong. And doing so, it won.
Aug 26, 2017

This small article is born from a discussion I had with a friend of mine this week. He was writing a review on Playersunknown’s Battlegrounds (from now on, *PUBG*) and he ended up talking about the evolution of the genre and its triumph over every other competitor. The article was good but it did not enter in detail about, what I think, it is a greatly important and interesting question: **Why PUBG? Why not any of the other dozens of battle royal games we were plagued in the last years?**

PUBG is clearly a winner in this competition. It sold more than 8 million copies on Steam only, and I can see the trend going with the future release on consoles. The problem, in my opinion, is that, on paper, there is nothing in PUBG implementation that seems “right”. Nevertheless, it won.

Machiavelli once said that success is 50% luck. That’s definitely true for PUBG. But the other 50% must be researched in the PUBG qualities. Analyzing them, despite the massive “errors”, it is very important for any game designer.

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