NoRaincheck

Important: Background information

Overview

This page will look up trainer battle AI procedures for the Generation IV Pokémon games – Pokémon Diamond, Pearl, Platinum, HeartGold, and SoulSilver. Trainer AI between each of these games is nearly identical, with only Diamond and Pearl having a single small difference from Platinum, HeartGold, and SoulSilver (in Icy Wind / Mud Shot / Rock Tomb!).

I recommend you read over this whole article at least once to be made aware of all the strange quirks and edge cases that affect the AI procedures.

The Battle AI uses a scoring system to determine which move to use (and which target to use it on, if applicable). Each move starts with a score of 100 (but this starting point is arbitrary), which is then added or subtracted to by the different parts of the scoring procedure.

	"""
	Diamond-Square Terrain Generator

	A Python implementation of the Diamond-Square algorithm for procedural fractal
	terrain generation, with extensions for constrained generation, seamless tile
	stitching, and water ratio control.

	THE DIAMOND-SQUARE ALGORITHM
	============================

	"""
	FFT Terrain Generator

	Generates 2D fractal noise terrain using Fast Fourier Transforms.
	Based on Paul Bourke's "Frequency Synthesis of Landscapes (and clouds)" (1997).
	"""

	import argparse
	import numpy as np
	from PIL import Image

	import random
	from typing import Any, Dict, Hashable, List, Tuple, Union

	import numpy as np
	from coba.primitives import Learner
	from scipy.special import softmax
	from sklearn.base import BaseEstimator, clone


	class BaseOnline(Learner):

	#!/bin/bash

	PATH=/usr/local/bin:/opt/homebrew/bin/:$PATH

	# Check if an argument is provided
	if [ -z "$1" ]; then
	echo "Usage: $0 <input-image-file>"
	exit 1
	fi

	/*
	@title Strudeldudel
	@by Lennard Voogdt
	@license CC BY-NC-SA
	*/

	// let cpm = 77
	setcps(78/60)

	register('withAsdr', x => x.attack(saw.range(0, 0.05).fast(6)).decay(rand.range(0.1, 0.3)).sustain(0))

	import math
	from collections import Counter

	# primes chosen to be the 4, 6, 8, 12, 20, 100 primes to match the dice roll
	# with this it is at least possible to get a reproducible sequence, for each one
	# with length desired

	DICE = [4, 6, 8, 12, 20, 100]
	PRIME_NUMBERS = [11, 13, 19, 29, 41, 211]

	{
	"description": "Remap mouse keys",
	"manipulators": [
	{
	"from": {
	"key_code": "spacebar",
	"modifiers": { "mandatory": ["right_control"] }
	},
	"to": [
	{

	[
	{
	"isrc": "USUAN1100001",
	"title": "C-Funk",
	"instruments": [
	"Bass",
	"Kit",
	"Guitar",
	"Bari Sax",
	"Tenor Sax",

	from itertools import cycle
	# the colors cycle in 3 different "rates"


	def linspace(start, stop, num):
	"""Generate num evenly spaced numbers over the interval [start, stop]."""
	if num < 2:
	return [start]
	step = (stop - start) / (num - 1)
	return [start + step * i for i in range(num)]