In general, the simplest (and quite optimal) algorithm is checking on which side of the half-plane created by the edges the point is. Here’s some high quality info in this topic on GameDev, including performance issues. And here’s some code to get you started: float sign (fPoint p1, fPoint p2, fPoint p3) { return (p1.x … Read more
One way of thinking about it is this: O(N^2) means for every element, you’re doing something with every other element, such as comparing them. Bubble sort is an example of this. O(N log N) means for every element, you’re doing something that only needs to look at log N of the elements. This is usually … Read more
You could average the RGB values of random colors with those of a constant color: (example in Java) public Color generateRandomColor(Color mix) { Random random = new Random(); int red = random.nextInt(256); int green = random.nextInt(256); int blue = random.nextInt(256); // mix the color if (mix != null) { red = (red + mix.getRed()) / … Read more
Do you know about “vanishing” and “exploding” gradients in backpropagation? I’m not too familiar with Haskell so I can’t easily see what exactly your backprop is doing, but it does look like you are using a logistic curve as your activation function. If you look at the plot of this function you’ll see that the … Read more
I’ll try to answer your question, but I’ll start with something that may look strange at first: if you are not interested in Redis internals you should not care about how data types are implemented internally. This is for a simple reason: for every Redis operation you’ll find the time complexity in the documentation and, … Read more
O(n^2) time and O(1) space algorithm ( without any workarounds and hanky-panky stuff! ) Rotate by +90: Transpose Reverse each row Rotate by -90: Method 1 : Transpose Reverse each column Method 2 : Reverse each row Transpose Rotate by +180: Method 1: Rotate by +90 twice Method 2: Reverse each row and then reverse … Read more
Robust peak detection algorithm (using z-scores) I came up with an algorithm that works very well for these types of datasets. It is based on the principle of dispersion: if a new datapoint is a given x number of standard deviations away from some moving mean, the algorithm signals (also called z-score). The algorithm is … Read more
In general, x and y must satisfy (x – center_x)² + (y – center_y)² < radius². Please note that points that satisfy the above equation with < replaced by == are considered the points on the circle, and the points that satisfy the above equation with < replaced by > are considered the outside the … Read more
I learned that depth and height are properties of a node: The depth of a node is the number of edges from the node to the tree’s root node.A root node will have a depth of 0. The height of a node is the number of edges on the longest path from the node to … Read more
My answer works like the others here, but I’ll post it because it looks a bit faster than the other Python solutions, from setting up the dictionary faster. (I checked this against John Fouhy’s solution.) After setup, the time to solve is down in the noise. grid = “fxie amlo ewbx astu”.split() nrows, ncols = … Read more