classAndrew

# Andrew's Discord color utils https://gist.github.com/classAndrew/2f151a12c49a9e4a105fd1dfa338daba 
# See https://gist.github.com/kkrypt0nn/a02506f3712ff2d1c8ca7c9e0aed7c06 for details

'''
example:
from discord_ansicolor import green bold, bg_light_gray
colored = green(bold(bg_light_gray("hello!")))
'''

from typing import Union, Callable

classAndrew

import os
import logging
import time
import requests
import json

__version__ = "1.0.0"
__author__ = "Andrew Lin"

logging.basicConfig(level=logging.INFO, format="[%(name)s] %(levelname)s %(asctime)s :: %(message)s")

classAndrew

#define BOOST_LOG_DYN_LINK 1

#include <iostream>
#include <boost/log/trivial.hpp>
#include <SDL2/SDL.h>
#include <sys/time.h>
#include <cmath>

using namespace std;

classAndrew

"""
@classAndrew
Nonlinear regression with a single layer perceptron.
Forgot when this was written
"""

import numpy as np
import statistics
import matplotlib.pyplot as plt

classAndrew

/**
 * @classAndrew
 * Shunting-Yard logical expression truth table generator
 * 9 September 2021
 */

interface BoolRefJSON {
    [name: string]: boolean;
};

classAndrew

from collections import Counter

# for K, M-length dictionary words, and an N-tile hand, you can expect a complexity of
# O(KM * lg M) Assuming letter counting and comparing is done in O(n) time (it isn't but
# it can be with the cost of lots of memory) There's a pretty large coefficient of 2^26 since 
# there's 26 characters.

# tiles our hand!
hand = "buncheesefoodragon"
# you can realize right away that there's "bun", "cheese", "food", "dragon", "on"