Abhiroop

No red node has a red parent or a red node has only black children.
Every path from the root node to an empty node contains the same number of black nodes.
The root and leaves of the tree are black.

Abhiroop

data Color = R | B deriving Show

data Tree a = E | T Color (Tree a) a (Tree a) deriving Show

Abhiroop

{-# LANGUAGE GADTs, DataKinds  #-}
module BST where

data Nat = Zero | Succ Nat

data Tree n a where
  Branch :: T n a -> Tree (Succ n) a
  Leaf :: Tree Zero a

data T n a = NodeR (Tree n a) a (Tree (Succ n) a) -- right subtree has height + 1

Abhiroop

Timing the performance of various ways of extracting top k elements from a vector:

Here sequence size is about 10000
and k=300

Here is a randomly generated vector containing 10K maps. Each of the maps look like this
{
:id 123
:data (0 1 2 3 ....)
:more-data (0 1 2 3 ....)

Abhiroop

settings_table = {
        {
                -- Edit this table to customise your rings.
                -- You can create more rings simply by adding more elements to settings_table.
                -- "name" is the type of stat to display; you can choose from 'cpu', 'memperc', 'fs_used_perc', 'battery_used_perc'.
                name='time',
                -- "arg" is the argument to the stat type, e.g. if in Conky you would write ${cpu cpu0}, 'cpu0' would be the argument. If you would not use an argument in the Conky variable, use ''.
                arg='%I.%M',
                -- "max" is the maximum value of the ring. If the Conky variable outputs a percentage, use 100.
                max=12,

Abhiroop

board = []
board_size = -1

def initiateBoard (board_dimensions):
    global board
    global board_size
    global knights_moves
    board_size = board_dimensions
    for i in range(0, board_size):
        board.append(board_size*[0])