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Keep all operations the same but rewrite the snippet in Scala.
import logging, logging.handlers LOG_FILENAME = "logdemo.log" FORMAT_STRING = "%(levelname)s:%(asctime)s:%(name)s:%(funcName)s:line-%(lineno)d: %(message)s" LOGLEVEL = logging.DEBUG def print_squares(number): logger.info("In print_squares") for i in range(number): print("square of {0} is {1}".format(...
fun printDebug(message: String) { val exception = RuntimeException() val stackTrace = exception.stackTrace val stackTraceElement = stackTrace[1] val fileName = stackTraceElement.fileName val className = stackTraceElement.className val methodName = stackTraceElement.methodName val lineNumber ...
Maintain the same structure and functionality when rewriting this code in Scala.
class Montgomery: BASE = 2 def __init__(self, m): self.m = m self.n = m.bit_length() self.rrm = (1 << (self.n * 2)) % m def reduce(self, t): a = t for i in xrange(self.n): if (a & 1) == 1: a = a + self.m a = a >> 1 if ...
import java.math.BigInteger val bigZero = BigInteger.ZERO val bigOne = BigInteger.ONE val bigTwo = BigInteger.valueOf(2L) class Montgomery(val m: BigInteger) { val n: Int val rrm: BigInteger init { require(m > bigZero && m.testBit(0)) n = m.bitLength() rrm = bigOne.s...
Generate a Scala translation of this Python snippet without changing its computational steps.
states = { 'ready':{ 'prompt' : 'Machine ready: (d)eposit, or (q)uit?', 'responses' : ['d','q']}, 'waiting':{ 'prompt' : 'Machine waiting: (s)elect, or (r)efund?', 'responses' : ['s','r']}, 'dispense' : { 'prompt'...
enum class State { READY, WAITING, EXIT, DISPENSE, REFUNDING } fun fsm() { println("Please enter your option when prompted") println("(any characters after the first will be ignored)") var state = State.READY var trans: String while (true) { when (state) { State.READY -> { ...
Transform the following Python implementation into Scala, maintaining the same output and logic.
from array import array from collections import deque import psyco data = [] nrows = 0 px = py = 0 sdata = "" ddata = "" def init(board): global data, nrows, sdata, ddata, px, py data = filter(None, board.splitlines()) nrows = max(len(r) for r in data) maps = {' ':' ', '.': '.', '@':' ', ' mapd =...
import java.util.LinkedList class Sokoban(board: List<String>) { val destBoard: String val currBoard: String val nCols = board[0].length var playerX = 0 var playerY = 0 init { val destBuf = StringBuilder() val currBuf = StringBuilder() for (r in 0 until board.size) { ...
Write a version of this Python function in Scala with identical behavior.
from sympy import divisors from sympy.combinatorics.subsets import Subset def isZumkeller(n): d = divisors(n) s = sum(d) if not s % 2 and max(d) <= s/2: for x in range(1, 2**len(d)): if sum(Subset.unrank_binary(x, d).subset) == s/2: return True return False def ...
import java.util.ArrayList import kotlin.math.sqrt object ZumkellerNumbers { @JvmStatic fun main(args: Array<String>) { var n = 1 println("First 220 Zumkeller numbers:") run { var count = 1 while (count <= 220) { if (isZumkeller(n)) { ...
Write the same code in Scala as shown below in Python.
import re as RegEx def Commatize( _string, _startPos=0, _periodLen=3, _separator="," ): outString = "" strPos = 0 matches = RegEx.findall( "[0-9]*", _string ) for match in matches[:-1]: if not match: outString += _string[ strPos ] strPos += 1 else: if len(match) > _periodLen: leadIn = match[:_st...
val r = Regex("""(\.[0-9]+|[1-9]([0-9]+)?(\.[0-9]+)?)""") fun String.commatize(startIndex: Int = 0, period: Int = 3, sep: String = ","): String { if ((startIndex !in 0 until this.length) || period < 1 || sep == "") return this val m = r.find(this, startIndex) if (m == null) return this val splits = m...
Rewrite this program in Scala while keeping its functionality equivalent to the Python version.
from math import floor, sqrt from datetime import datetime def main(): start = datetime.now() for i in xrange(1, 10 ** 11): if rare(i): print "found a rare:", i end = datetime.now() print "time elapsed:", end - start def is_square(n): s = floor(sqrt(n + 0.5)) return s * s == n def reverse(n): return ...
import java.time.Duration import java.time.LocalDateTime import kotlin.math.sqrt class Term(var coeff: Long, var ix1: Byte, var ix2: Byte) const val maxDigits = 16 fun toLong(digits: List<Byte>, reverse: Boolean): Long { var sum: Long = 0 if (reverse) { var i = digits.size - 1 while (i >= 0) ...
Write a version of this Python function in Scala with identical behavior.
class Node: def __init__(self, sub="", children=None): self.sub = sub self.ch = children or [] class SuffixTree: def __init__(self, str): self.nodes = [Node()] for i in range(len(str)): self.addSuffix(str[i:]) def addSuffix(self, suf): n = 0 i = ...
class Node { var sub = "" var ch = mutableListOf<Int>() } class SuffixTree(val str: String) { val nodes = mutableListOf<Node>(Node()) init { for (i in 0 until str.length) addSuffix(str.substring(i)) } private fun addSuffix(suf: String) { var n = 0 ...
Convert the following code from Python to Scala, ensuring the logic remains intact.
class Node: def __init__(self, sub="", children=None): self.sub = sub self.ch = children or [] class SuffixTree: def __init__(self, str): self.nodes = [Node()] for i in range(len(str)): self.addSuffix(str[i:]) def addSuffix(self, suf): n = 0 i = ...
class Node { var sub = "" var ch = mutableListOf<Int>() } class SuffixTree(val str: String) { val nodes = mutableListOf<Node>(Node()) init { for (i in 0 until str.length) addSuffix(str.substring(i)) } private fun addSuffix(suf: String) { var n = 0 ...
Convert this Python block to Scala, preserving its control flow and logic.
class Parent(object): __priv = 'private' def __init__(self, name): self.name = name def __repr__(self): return '%s(%s)' % (type(self).__name__, self.name) def doNothing(self): pass import re class Child(Parent): __rePrivate = re.compile('^_(Child|Parent)...
import kotlin.reflect.full.memberProperties import kotlin.reflect.jvm.isAccessible open class BaseExample(val baseProp: String) { protected val protectedProp: String = "inherited protected value" } class Example(val prop1: String, val prop2: Int, baseProp: String) : BaseExample(baseProp) { private val priva...
Can you help me rewrite this code in Scala instead of Python, keeping it the same logically?
from __future__ import print_function class Node(object): def __init__(self): self.edges = {} self.link = None self.len = 0 class Eertree(object): def __init__(self): self.nodes = [] self.rto = Node() self.rte = Node() self.rto.link = self.rte.link = self.rto; self.rto.len = -1 self.r...
class Node { val edges = mutableMapOf<Char, Node>() var link: Node? = null var len = 0 } class Eertree(str: String) { val nodes = mutableListOf<Node>() private val rto = Node() private val rte = Node() priva...
Write the same code in Scala as shown below in Python.
from __future__ import print_function class Node(object): def __init__(self): self.edges = {} self.link = None self.len = 0 class Eertree(object): def __init__(self): self.nodes = [] self.rto = Node() self.rte = Node() self.rto.link = self.rte.link = self.rto; self.rto.len = -1 self.r...
class Node { val edges = mutableMapOf<Char, Node>() var link: Node? = null var len = 0 } class Eertree(str: String) { val nodes = mutableListOf<Node>() private val rto = Node() private val rte = Node() priva...
Translate the given Python code snippet into Scala without altering its behavior.
ALPHABET = "123456789ABCDEFGHJKLMNPQRSTUVWXYZabcdefghijkmnopqrstuvwxyz" def convertToBase58(num): sb = '' while (num > 0): r = num % 58 sb = sb + ALPHABET[r] num = num // 58; return sb[::-1] s = 25420294593250030202636073700053352635053786165627414518 b = convertToBase58(s) print("...
import java.math.BigInteger const val ALPHABET = "123456789ABCDEFGHJKLMNPQRSTUVWXYZabcdefghijkmnopqrstuvwxyz" val big0 = BigInteger.ZERO val big58 = BigInteger.valueOf(58L) fun convertToBase58(hash: String, base: Int = 16): String { var x = if (base == 16 && hash.take(2) == "0x") BigInteger(hash.drop(2), 16) ...
Change the programming language of this snippet from Python to Scala without modifying what it does.
ALPHABET = "123456789ABCDEFGHJKLMNPQRSTUVWXYZabcdefghijkmnopqrstuvwxyz" def convertToBase58(num): sb = '' while (num > 0): r = num % 58 sb = sb + ALPHABET[r] num = num // 58; return sb[::-1] s = 25420294593250030202636073700053352635053786165627414518 b = convertToBase58(s) print("...
import java.math.BigInteger const val ALPHABET = "123456789ABCDEFGHJKLMNPQRSTUVWXYZabcdefghijkmnopqrstuvwxyz" val big0 = BigInteger.ZERO val big58 = BigInteger.valueOf(58L) fun convertToBase58(hash: String, base: Int = 16): String { var x = if (base == 16 && hash.take(2) == "0x") BigInteger(hash.drop(2), 16) ...
Convert the following code from Python to Scala, ensuring the logic remains intact.
def dList(n, start): start -= 1 a = range(n) a[start] = a[0] a[0] = start a[1:] = sorted(a[1:]) first = a[1] r = [] def recurse(last): if (last == first): for j,v in enumerate(a[1:]): if j + 1 == v: ...
typealias Matrix = MutableList<MutableList<Int>> fun dList(n: Int, sp: Int): Matrix { val start = sp - 1 val a = generateSequence(0) { it + 1 }.take(n).toMutableList() a[start] = a[0].also { a[0] = a[start] } a.subList(1, a.size).sort() val first = a[1] val r = mutableListOf<MutableList...
Keep all operations the same but rewrite the snippet in Scala.
def kosaraju(g): class nonlocal: pass size = len(g) vis = [False]*size l = [0]*size nonlocal.x = size t = [[]]*size def visit(u): if not vis[u]: vis[u] = True for v in g[u]: visit(v) t[v] = t[v] + [u] non...
val g = listOf( intArrayOf(1), intArrayOf(2), intArrayOf(0), intArrayOf(1, 2, 4), intArrayOf(3, 5), intArrayOf(2, 6), intArrayOf(5), intArrayOf(4, 6, 7) ) fun kosaraju(g: List<IntArray>): List<List<Int>> { val size = g.size ...
Convert this Python block to Scala, preserving its control flow and logic.
import re from random import shuffle, randint dirs = [[1, 0], [0, 1], [1, 1], [1, -1], [-1, 0], [0, -1], [-1, -1], [-1, 1]] n_rows = 10 n_cols = 10 grid_size = n_rows * n_cols min_words = 25 class Grid: def __init__(self): self.num_attempts = 0 self.cells = [['' for _ in range(n_cols)] for _ in r...
import java.util.Random import java.io.File val dirs = listOf( intArrayOf( 1, 0), intArrayOf(0, 1), intArrayOf( 1, 1), intArrayOf( 1, -1), intArrayOf(-1, 0), intArrayOf(0, -1), intArrayOf(-1, -1), intArrayOf(-1, 1) ) val nRows = 10 val nCols = 10 val gridSize = nRows * nCols val minWords = 25 val rand = ...
Convert this Python snippet to Scala and keep its semantics consistent.
import random, sys def makerule(data, context): rule = {} words = data.split(' ') index = context for word in words[index:]: key = ' '.join(words[index-context:index]) if key in rule: rule[key].append(word) else: rule[key] = [word] index...
import java.io.File fun markov(filePath: String, keySize: Int, outputSize: Int): String { require(keySize >= 1) { "Key size can't be less than 1" } val words = File(filePath).readText().trimEnd().split(' ') require(outputSize in keySize..words.size) { "Output size is out of range" } val dict = muta...
Translate the given Python code snippet into Scala without altering its behavior.
from collections import Counter def cumulative_freq(freq): cf = {} total = 0 for b in range(256): if b in freq: cf[b] = total total += freq[b] return cf def arithmethic_coding(bytes, radix): freq = Counter(bytes) cf = cumulative_freq(freq) ...
import java.math.BigInteger typealias Freq = Map<Char, Long> val bigZero = BigInteger.ZERO val bigOne = BigInteger.ONE fun cumulativeFreq(freq: Freq): Freq { var total = 0L val cf = mutableMapOf<Char, Long>() for (i in 0..255) { val c = i.toChar() val v = freq[c] if (v != null)...
Rewrite the snippet below in Scala so it works the same as the original Python code.
import copy, random def bitcount(n): return bin(n).count("1") def reoderingSign(i, j): k = i >> 1 sum = 0 while k != 0: sum += bitcount(k & j) k = k >> 1 return 1.0 if ((sum & 1) == 0) else -1.0 class Vector: def __init__(self, da): self.dims = da def dot(self, ot...
fun bitCount(i: Int): Int { var j = i j -= ((j shr 1) and 0x55555555) j = (j and 0x33333333) + ((j shr 2) and 0x33333333) j = (j + (j shr 4)) and 0x0F0F0F0F j += (j shr 8) j += (j shr 16) return j and 0x0000003F } fun reorderingSign(i: Int, j: Int): Double { var k = i shr 1 var sum ...
Change the programming language of this snippet from Python to Scala without modifying what it does.
from string import ascii_uppercase from itertools import product from re import findall def uniq(seq): seen = {} return [seen.setdefault(x, x) for x in seq if x not in seen] def partition(seq, n): return [seq[i : i + n] for i in xrange(0, len(seq), n)] def playfair(key, from_ = 'J', to = None): if ...
enum class PlayfairOption { NO_Q, I_EQUALS_J } class Playfair(keyword: String, val pfo: PlayfairOption) { private val table: Array<CharArray> = Array(5, { CharArray(5) }) init { val used = BooleanArray(26) if (pfo == PlayfairOption.NO_Q) used[16] = true ...
Preserve the algorithm and functionality while converting the code from Python to Scala.
from string import ascii_uppercase from itertools import product from re import findall def uniq(seq): seen = {} return [seen.setdefault(x, x) for x in seq if x not in seen] def partition(seq, n): return [seq[i : i + n] for i in xrange(0, len(seq), n)] def playfair(key, from_ = 'J', to = None): if ...
enum class PlayfairOption { NO_Q, I_EQUALS_J } class Playfair(keyword: String, val pfo: PlayfairOption) { private val table: Array<CharArray> = Array(5, { CharArray(5) }) init { val used = BooleanArray(26) if (pfo == PlayfairOption.NO_Q) used[16] = true ...
Change the programming language of this snippet from Python to Scala without modifying what it does.
def _notcell(c): return '0' if c == '1' else '1' def eca_infinite(cells, rule): lencells = len(cells) rulebits = '{0:08b}'.format(rule) neighbours2next = {'{0:03b}'.format(n):rulebits[::-1][n] for n in range(8)} c = cells while True: yield c c = _notcell(c[0])*2 + c + _notcell(c...
fun evolve(l: Int, rule: Int) { println(" Rule #$rule:") var cells = StringBuilder("*") for (x in 0 until l) { addNoCells(cells) val width = 40 + (cells.length shr 1) println(cells.padStart(width)) cells = step(cells, rule) } } fun step(cells: StringBuilder, rule: Int)...
Translate the given Python code snippet into Scala without altering its behavior.
from itertools import (chain) def stringParse(lexicon): return lambda s: Node(s)( tokenTrees(lexicon)(s) ) def tokenTrees(wds): def go(s): return [Node(s)([])] if s in wds else ( concatMap(nxt(s))(wds) ) def nxt(s): return lambda w: parse( ...
import java.io.File val partitions = mutableListOf<List<String>>() fun partitionString(s: String, ml: MutableList<String>, level: Int) { for (i in s.length - 1 downTo 1) { val part1 = s.substring(0, i) val part2 = s.substring(i) ml.add(part1) ml.add(part2) partitions.add(...
Convert the following code from Python to Scala, ensuring the logic remains intact.
from collections import UserDict import copy class Dict(UserDict): def __init__(self, dict=None, **kwargs): self.__init = True super().__init__(dict, **kwargs) self.default = copy.deepcopy(self.data) self.__init = False def __delitem__(self, key): if key in sel...
fun main(args: Array<String>) { val map = mapOf('A' to 65, 'B' to 66, 'C' to 67) println(map) }
Produce a functionally identical Scala code for the snippet given in Python.
from math import pi, sin, cos from collections import namedtuple from random import random, choice from copy import copy try: import psyco psyco.full() except ImportError: pass FLOAT_MAX = 1e100 class Point: __slots__ = ["x", "y", "group"] def __init__(self, x=0.0, y=0.0, group=0): self...
import java.util.Random import kotlin.math.* data class Point(var x: Double, var y: Double, var group: Int) typealias LPoint = List<Point> typealias MLPoint = MutableList<Point> val origin get() = Point(0.0, 0.0, 0) val r = Random() val hugeVal = Double.POSITIVE_INFINITY const val RAND_MAX = Int.MAX_VALUE const v...
Transform the following Python implementation into Scala, maintaining the same output and logic.
hex2bin = dict('{:x} {:04b}'.format(x,x).split() for x in range(16)) bin2hex = dict('{:b} {:x}'.format(x,x).split() for x in range(16)) def float_dec2bin(d): neg = False if d < 0: d = -d neg = True hx = float(d).hex() p = hx.index('p') bn = ''.join(hex2bin.get(char, char) for char i...
fun decToBin(d: Double): String { val whole = Math.floor(d).toLong() var binary = whole.toString(2) + "." var dd = d - whole while (dd > 0.0) { val r = dd * 2.0 if (r >= 1.0) { binary += "1" dd = r - 1 } else { binary += "0" ...
Generate a Scala translation of this Python snippet without changing its computational steps.
hex2bin = dict('{:x} {:04b}'.format(x,x).split() for x in range(16)) bin2hex = dict('{:b} {:x}'.format(x,x).split() for x in range(16)) def float_dec2bin(d): neg = False if d < 0: d = -d neg = True hx = float(d).hex() p = hx.index('p') bn = ''.join(hex2bin.get(char, char) for char i...
fun decToBin(d: Double): String { val whole = Math.floor(d).toLong() var binary = whole.toString(2) + "." var dd = d - whole while (dd > 0.0) { val r = dd * 2.0 if (r >= 1.0) { binary += "1" dd = r - 1 } else { binary += "0" ...
Write a version of this Python function in Scala with identical behavior.
from itertools import imap, imap, groupby, chain, imap from operator import itemgetter from sys import argv from array import array def concat_map(func, it): return list(chain.from_iterable(imap(func, it))) def minima(poly): return (min(pt[0] for pt in poly), min(pt[1] for pt in poly)) def translate_to_...
class Point(val x: Int, val y: Int) : Comparable<Point> { fun rotate90() = Point( this.y, -this.x) fun rotate180() = Point(-this.x, -this.y) fun rotate270() = Point(-this.y, this.x) fun reflect() = Point(-this.x, this.y) override fun equals(other: Any?): Boolean { if (other == null |...
Port the following code from Python to Scala with equivalent syntax and logic.
from itertools import groupby from unicodedata import decomposition, name from pprint import pprint as pp commonleaders = ['the'] replacements = {u'ß': 'ss', u'ſ': 's', u'ʒ': 's', } hexdigits = set('0123456789abcdef') decdigits = set('0123456789') def splitch...
val r2 = Regex("""[ ]{2,}""") val r3 = Regex("""\s""") val r5 = Regex("""\d+""") val ucAccented = arrayOf("ÀÁÂÃÄÅ", "Ç", "ÈÉÊË", "ÌÍÎÏ", "Ñ", "ÒÓÔÕÖØ", "ÙÚÛÜ", "ÝŸ") val lcAccented = arrayOf("àáâãäå", "ç", "èéêë", "ìíîï", "ñ", "òóôõöø", "ùúûü", "ýÿ") val ucNormal = "ACEINOUY" val lcNormal = "aceinouy" val ucL...
Convert this Python snippet to Scala and keep its semantics consistent.
def ownCalcPass (password, nonce, test=False) : start = True num1 = 0 num2 = 0 password = int(password) if test: print("password: %08x" % (password)) for c in nonce : if c != "0": if start: num2 = password start = False if test:...
fun ownCalcPass(password: Long, nonce: String): Long { val m1 = 0xFFFF_FFFFL val m8 = 0xFFFF_FFF8L val m16 = 0xFFFF_FFF0L val m128 = 0xFFFF_FF80L val m16777216 = 0xFF00_0000L var flag = true var num1 = 0L var num2 = 0L for (c in nonce) { num2 = nu...
Write the same code in Scala as shown below in Python.
import math import random INFINITY = 1 << 127 MAX_INT = 1 << 31 class Parameters: def __init__(self, omega, phip, phig): self.omega = omega self.phip = phip self.phig = phig class State: def __init__(self, iter, gbpos, gbval, min, max, parameters, pos, vel, bpos, bval, nParticles, nDi...
import java.util.Random typealias Func = (DoubleArray) -> Double class Parameters(val omega: Double, val phip: Double, val phig: Double) class State( val iter: Int, val gbpos: DoubleArray, val gbval: Double, val min: DoubleArray, val max: DoubleArray, val parameters: Parameters, val pos...
Produce a language-to-language conversion: from Python to Scala, same semantics.
def DrawBoard(board): peg = [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] for n in xrange(1,16): peg[n] = '.' if n in board: peg[n] = "%X" % n print " %s" % peg[1] print " %s %s" % (peg[2],peg[3]) print " %s %s %s" % (peg[4],peg[5],peg[6]) print " %s %s %s %s" % (peg[7],peg[8],peg[9],peg[10])...
data class Solution(val peg: Int, val over: Int, val land: Int) var board = BooleanArray(16) { if (it == 0) false else true } val jumpMoves = listOf( listOf(), listOf( 2 to 4, 3 to 6), listOf( 4 to 7, 5 to 9), listOf( 5 to 8, 6 to 10), listOf( 2 to 1, 5 to 6, 7 to 11, 8 to 13), ...
Convert this Python block to Scala, preserving its control flow and logic.
from __future__ import print_function from __future__ import division def extended_synthetic_division(dividend, divisor): out = list(dividend) normalizer = divisor[0] for i in xrange(len(dividend)-(len(divisor)-1)): out[i] /= normalizer coef...
fun extendedSyntheticDivision(dividend: IntArray, divisor: IntArray): Pair<IntArray, IntArray> { val out = dividend.copyOf() val normalizer = divisor[0] val separator = dividend.size - divisor.size + 1 for (i in 0 until separator) { out[i] /= normalizer val coef = out[i] if (co...
Preserve the algorithm and functionality while converting the code from Python to Scala.
from __future__ import print_function from __future__ import division def extended_synthetic_division(dividend, divisor): out = list(dividend) normalizer = divisor[0] for i in xrange(len(dividend)-(len(divisor)-1)): out[i] /= normalizer coef...
fun extendedSyntheticDivision(dividend: IntArray, divisor: IntArray): Pair<IntArray, IntArray> { val out = dividend.copyOf() val normalizer = divisor[0] val separator = dividend.size - divisor.size + 1 for (i in 0 until separator) { out[i] /= normalizer val coef = out[i] if (co...
Write the same algorithm in Scala as shown in this Python implementation.
size(300, 300) background(0) radius = min(width, height) / 2.0 cx, cy = width / 2, width / 2 for x in range(width): for y in range(height): rx = x - cx ry = y - cy s = sqrt(rx ** 2 + ry ** 2) / radius if s <= 1.0: h = ((atan2(ry, rx) / PI) + 1.0) /...
import java.awt.Color import java.awt.Graphics import java.awt.image.BufferedImage import java.io.File import javax.imageio.ImageIO import kotlin.math.* class BasicBitmapStorage(width: Int, height: Int) { val image = BufferedImage(width, height, BufferedImage.TYPE_3BYTE_BGR) fun fill(c: Color) { val...
Produce a language-to-language conversion: from Python to Scala, same semantics.
import random TRAINING_LENGTH = 2000 class Perceptron: def __init__(self,n): self.c = .01 self.weights = [random.uniform(-1.0, 1.0) for _ in range(n)] def feed_forward(self, inputs): weighted_inputs = [] for i in range(len(inputs)): weighted_inputs.append(inpu...
import java.awt.* import java.awt.event.ActionEvent import java.util.Random import javax.swing.JPanel import javax.swing.JFrame import javax.swing.Timer import javax.swing.SwingUtilities class Perceptron(n: Int) : JPanel() { class Trainer(x: Double, y: Double, val answer: Int) { val inputs = doubleArray...
Please provide an equivalent version of this Python code in Scala.
import datetime import re import urllib.request import sys def get(url): with urllib.request.urlopen(url) as response: html = response.read().decode('utf-8') if re.match(r'<!Doctype HTML[\s\S]*<Title>URL Not Found</Title>', html): return None return html def main(): template = 'http://...
import java.net.Socket import java.net.URL import java.time import java.time.format import java.time.ZoneId import java.util.Scanner import scala.collection.JavaConverters._ def get(rawUrl: String): List[String] = { val url = new URL(rawUrl) val port = if (url.getPort > -1) url.getPort else 80 val sock = n...
Maintain the same structure and functionality when rewriting this code in Scala.
from __future__ import annotations import functools import gzip import json import logging import platform import re from collections import Counter from collections import defaultdict from typing import Any from typing import Iterator from typing import Iterable from typing import List from typing import Mapping ...
import java.net.URI import java.net.http.HttpClient import java.net.http.HttpRequest import java.net.http.HttpResponse import java.util.regex.Pattern import java.util.stream.Collectors const val BASE = "http: fun main() { val client = HttpClient.newBuilder().build() val titleUri = URI.create("$BASE/mw/api.ph...
Ensure the translated Scala code behaves exactly like the original Python snippet.
from __future__ import print_function import lxml from lxml import etree if __name__=="__main__": parser = etree.XMLParser(dtd_validation=True) schema_root = etree.XML() schema = etree.XMLSchema(schema_root) parser = etree.XMLParser(schema = schema) try: root = etree.fromstring("<a>5</a>", parser) print ...
import kotlinx.cinterop.* import platform.posix.* import libxml_schemas.* fun err(ctx: COpaquePointer?, msg: CPointer<ByteVar>?, extra: CPointer<ByteVar>?) { val fp = ctx?.reinterpret<FILE>() fprintf(fp, msg?.toKString(), extra?.toKString()) } fun warn(ctx: COpaquePointer?, msg: CPointer<ByteVar>?, extra: C...
Port the following code from Python to Scala with equivalent syntax and logic.
from itertools import count, islice from _pydecimal import getcontext, Decimal def metallic_ratio(b): m, n = 1, 1 while True: yield m, n m, n = m*b + n, m def stable(b, prec): def to_decimal(b): for m,n in metallic_ratio(b): yield Decimal(m)/Decimal(n) getcontext()...
import java.math.BigDecimal import java.math.BigInteger val names = listOf("Platinum", "Golden", "Silver", "Bronze", "Copper", "Nickel", "Aluminium", "Iron", "Tin", "Lead") fun lucas(b: Long) { println("Lucas sequence for ${names[b.toInt()]} ratio, where b = $b:") print("First 15 elements: ") var x0 = 1L ...
Maintain the same structure and functionality when rewriting this code in Scala.
from itertools import count, islice from _pydecimal import getcontext, Decimal def metallic_ratio(b): m, n = 1, 1 while True: yield m, n m, n = m*b + n, m def stable(b, prec): def to_decimal(b): for m,n in metallic_ratio(b): yield Decimal(m)/Decimal(n) getcontext()...
import java.math.BigDecimal import java.math.BigInteger val names = listOf("Platinum", "Golden", "Silver", "Bronze", "Copper", "Nickel", "Aluminium", "Iron", "Tin", "Lead") fun lucas(b: Long) { println("Lucas sequence for ${names[b.toInt()]} ratio, where b = $b:") print("First 15 elements: ") var x0 = 1L ...
Write a version of this Python function in Scala with identical behavior.
class Node: def __init__(self, data=None): self.data = data self.next = None class SLinkedList: def __init__(self): self.head = None def insert_first(self, insert_this): new_node = Node(insert_this) new_node.next = self.head self.head = new_node def re...
class Node<T: Number>(var data: T, var next: Node<T>? = null) { override fun toString(): String { val sb = StringBuilder(this.data.toString()) var node = this.next while (node != null) { sb.append(" -> ", node.data.toString()) node = node.next } retu...
Port the provided Python code into Scala while preserving the original functionality.
IP = ( 58, 50, 42, 34, 26, 18, 10, 2, 60, 52, 44, 36, 28, 20, 12, 4, 62, 54, 46, 38, 30, 22, 14, 6, 64, 56, 48, 40, 32, 24, 16, 8, 57, 49, 41, 33, 25, 17, 9, 1, 59, 51, 43, 35, 27, 19, 11, 3, 61, 53, 45, 37, 29, 21, 13, 5, 63, 55, 47, 39, 31, 23, 15, 7 ) IP_INV = ( 40, 8, 48, 1...
import javax.crypto.Cipher import javax.crypto.spec.SecretKeySpec fun String.toHexByteArray(): ByteArray { val bytes = ByteArray(this.length / 2) for (i in 0 until bytes.size) { bytes[i] = this.substring(i * 2, i * 2 + 2).toInt(16).toByte() } return bytes } fun ByteArray.printHexBytes...
Rewrite the snippet below in Scala so it works the same as the original Python code.
from __future__ import annotations import functools import math import os from typing import Any from typing import Callable from typing import Generic from typing import List from typing import TypeVar from typing import Union T = TypeVar("T") class Writer(Generic[T]): def __init__(self, value: Union[T, Wri...
import kotlin.math.sqrt class Writer<T : Any> private constructor(val value: T, s: String) { var log = " ${s.padEnd(17)}: $value\n" private set fun bind(f: (T) -> Writer<T>): Writer<T> { val new = f(this.value) new.log = this.log + new.log return new } companion obj...
Generate an equivalent Scala version of this Python code.
from itertools import combinations_with_replacement as cmbr from time import time def dice_gen(n, faces, m): dice = list(cmbr(faces, n)) succ = [set(j for j, b in enumerate(dice) if sum((x>y) - (x<y) for x in a for y in b) > 0) for a in dice] def loops(seq): ...
fun fourFaceCombos(): List<Array<Int>> { val res = mutableListOf<Array<Int>>() val found = mutableSetOf<Int>() for (i in 1..4) { for (j in 1..4) { for (k in 1..4) { for (l in 1..4) { val c = arrayOf(i, j, k, l) c.sort() ...
Generate an equivalent Scala version of this Python code.
Plataanstraat 5 split as (Plataanstraat, 5) Straat 12 split as (Straat, 12) Straat 12 II split as (Straat, 12 II) Dr. J. Straat 12 split as (Dr. J. Straat , 12) Dr. J. Straat 12 a split as (Dr. J. Straat, 12 a) Dr. J. Straat 12-14 split as (Dr. J. Straat, 12...
val r = Regex("""\s+""") fun separateHouseNumber(address: String): Pair<String, String> { val street: String val house: String val len = address.length val splits = address.split(r) val size = splits.size val last = splits[size - 1] val penult = splits[size - 2] if (last[0] in...
Can you help me rewrite this code in Scala instead of Python, keeping it the same logically?
import numpy as np from numpy.linalg import inv a = np.array([[1., 2., 3.], [4., 1., 6.],[ 7., 8., 9.]]) ainv = inv(a) print(a) print(ainv)
typealias Matrix = Array<DoubleArray> fun Matrix.inverse(): Matrix { val len = this.size require(this.all { it.size == len }) { "Not a square matrix" } val aug = Array(len) { DoubleArray(2 * len) } for (i in 0 until len) { for (j in 0 until len) aug[i][j] = this[i][j] aug[i][...
Convert this Python block to Scala, preserving its control flow and logic.
import numpy as np from numpy.linalg import inv a = np.array([[1., 2., 3.], [4., 1., 6.],[ 7., 8., 9.]]) ainv = inv(a) print(a) print(ainv)
typealias Matrix = Array<DoubleArray> fun Matrix.inverse(): Matrix { val len = this.size require(this.all { it.size == len }) { "Not a square matrix" } val aug = Array(len) { DoubleArray(2 * len) } for (i in 0 until len) { for (j in 0 until len) aug[i][j] = this[i][j] aug[i][...
Convert the following code from Python to Scala, ensuring the logic remains intact.
import math import collections triple = collections.namedtuple('triple', 'm fm simp') def _quad_simpsons_mem(f: callable, a: float , fa: float, b: float, fb: float)->tuple: m = a + (b - a) / 2 fm = f(m) simp = abs(b - a) / 6 * (fa + 4*fm + fb) return triple(m, fm, simp,) def _quad_asr(f: ca...
import kotlin.math.abs import kotlin.math.sin typealias F = (Double) -> Double typealias T = Triple<Double, Double, Double> fun quadSimpsonsMem(f: F, a: Double, fa: Double, b: Double, fb: Double): T { val m = (a + b) / 2 val fm = f(m) val simp = abs(b - a) / 6 * (fa + 4 * fm + fb) return T(m, ...
Transform the following Python implementation into Scala, maintaining the same output and logic.
import math import collections triple = collections.namedtuple('triple', 'm fm simp') def _quad_simpsons_mem(f: callable, a: float , fa: float, b: float, fb: float)->tuple: m = a + (b - a) / 2 fm = f(m) simp = abs(b - a) / 6 * (fa + 4*fm + fb) return triple(m, fm, simp,) def _quad_asr(f: ca...
import kotlin.math.abs import kotlin.math.sin typealias F = (Double) -> Double typealias T = Triple<Double, Double, Double> fun quadSimpsonsMem(f: F, a: Double, fa: Double, b: Double, fb: Double): T { val m = (a + b) / 2 val fm = f(m) val simp = abs(b - a) / 6 * (fa + 4 * fm + fb) return T(m, ...
Maintain the same structure and functionality when rewriting this code in Scala.
import random board = [[" " for x in range(8)] for y in range(8)] piece_list = ["R", "N", "B", "Q", "P"] def place_kings(brd): while True: rank_white, file_white, rank_black, file_black = random.randint(0,7), random.randint(0,7), random.randint(0,7), random.randint(0,7) diff_list = [abs(rank_white - rank_black)...
import java.util.Random import kotlin.math.abs val rand = Random() val grid = List(8) { CharArray(8) } const val NUL = '\u0000' fun createFen(): String { placeKings() placePieces("PPPPPPPP", true) placePieces("pppppppp", true) placePieces("RNBQBNR", false) placePieces("rnbqbnr", false) ret...
Transform the following Python implementation into Scala, maintaining the same output and logic.
from math import prod def superFactorial(n): return prod([prod(range(1,i+1)) for i in range(1,n+1)]) def hyperFactorial(n): return prod([i**i for i in range(1,n+1)]) def alternatingFactorial(n): return sum([(-1)**(n-i)*prod(range(1,i+1)) for i in range(1,n+1)]) def exponentialFactorial(n): if n in...
import java.math.BigInteger import java.util.function.Function fun factorial(n: Int): BigInteger { val bn = BigInteger.valueOf(n.toLong()) var result = BigInteger.ONE var i = BigInteger.TWO while (i <= bn) { result *= i++ } return result } fun inverseFactorial(f: BigInteger): Int { ...
Convert this Python block to Scala, preserving its control flow and logic.
def load_ast() line = readline() line_list = tokenize the line, respecting double quotes text = line_list[0] if text == ";" return NULL node_type = text if len(line_list) > 1 return make_leaf(node_type, line_list[1]) left = load_ast() right =...
package xyz.hyperreal.rosettacodeCompiler import scala.collection.mutable import scala.io.Source object ASTInterpreter { def fromStdin = fromSource(Source.stdin) def fromString(src: String) = fromSource(Source.fromString(src)) def fromSource(s: Source) = { val lines = s.getLines def load: Node = ...
Ensure the translated Scala code behaves exactly like the original Python snippet.
def load_ast() line = readline() line_list = tokenize the line, respecting double quotes text = line_list[0] if text == ";" return NULL node_type = text if len(line_list) > 1 return make_leaf(node_type, line_list[1]) left = load_ast() right =...
package xyz.hyperreal.rosettacodeCompiler import scala.collection.mutable import scala.io.Source object ASTInterpreter { def fromStdin = fromSource(Source.stdin) def fromString(src: String) = fromSource(Source.fromString(src)) def fromSource(s: Source) = { val lines = s.getLines def load: Node = ...
Generate a Scala translation of this Python snippet without changing its computational steps.
import numpy as np import scipy as sp import scipy.stats def welch_ttest(x1, x2): n1 = x1.size n2 = x2.size m1 = np.mean(x1) m2 = np.mean(x2) v1 = np.var(x1, ddof=1) v2 = np.var(x2, ddof=1) t = (m1 - m2) / np.sqrt(v1 / n1 + v2 / n2) df = (v1 / n1 + v2 / n2)**2 / (v1**2 / (n1**2 * (n1 - ...
typealias Func = (Double) -> Double fun square(d: Double) = d * d fun sampleVar(da: DoubleArray): Double { if (da.size < 2) throw IllegalArgumentException("Array must have at least 2 elements") val m = da.average() return da.map { square(it - m) }.sum() / (da.size - 1) } fun welch(da1: DoubleArray, da2...
Change the following Python code into Scala without altering its purpose.
import numpy as np import scipy as sp import scipy.stats def welch_ttest(x1, x2): n1 = x1.size n2 = x2.size m1 = np.mean(x1) m2 = np.mean(x2) v1 = np.var(x1, ddof=1) v2 = np.var(x2, ddof=1) t = (m1 - m2) / np.sqrt(v1 / n1 + v2 / n2) df = (v1 / n1 + v2 / n2)**2 / (v1**2 / (n1**2 * (n1 - ...
typealias Func = (Double) -> Double fun square(d: Double) = d * d fun sampleVar(da: DoubleArray): Double { if (da.size < 2) throw IllegalArgumentException("Array must have at least 2 elements") val m = da.average() return da.map { square(it - m) }.sum() / (da.size - 1) } fun welch(da1: DoubleArray, da2...
Translate the given Python code snippet into Scala without altering its behavior.
import inflect def count_letters(word): count = 0 for letter in word: if letter != ',' and letter !='-' and letter !=' ': count += 1 return count def split_with_spaces(sentence): sentence_list = [] curr_word = "" for c in sentence: if...
val names = mapOf( 1 to "one", 2 to "two", 3 to "three", 4 to "four", 5 to "five", 6 to "six", 7 to "seven", 8 to "eight", 9 to "nine", 10 to "ten", 11 to "eleven", 12 to "twelve", 13 to "thirteen", 14 to "fourteen", 15 to "fifteen", 16 to "sixteen", ...
Write the same algorithm in Scala as shown in this Python implementation.
import collections def MostFreqKHashing(inputString, K): occuDict = collections.defaultdict(int) for c in inputString: occuDict[c] += 1 occuList = sorted(occuDict.items(), key = lambda x: x[1], reverse = True) outputStr = ''.join(c + str(cnt) for c, cnt in occuList[:K]) return outputStr d...
fun mostFreqKHashing(input: String, k: Int): String = input.groupBy { it }.map { Pair(it.key, it.value.size) } .sortedByDescending { it.second } .take(k) .fold("") { acc, v -> acc + "${v.first}${v.second.toChar()}" } fun mostFreqKSimilarit...
Translate this program into Scala but keep the logic exactly as in Python.
import argparse import itertools import pathlib import re import secrets import sys MAGIC = " def make_keys(n, size): return (secrets.token_hex(size) for _ in range(n)) def make_pad(name, pad_size, key_size): pad = [ MAGIC, f" f" *make_keys(pad_s...
import java.io.File import java.security.SecureRandom const val CHARS_PER_LINE = 48 const val CHUNK_SIZE = 6 const val COLS = 8 const val DEMO = true enum class FileType { OTP, ENC, DEC } fun Char.isAlpha() = this in 'A'..'Z' fun String.toAlpha() = this.filter { it.isAlpha() } fun String.isOtpRelated() = endsW...
Produce a functionally identical Scala code for the snippet given in Python.
import argparse import itertools import pathlib import re import secrets import sys MAGIC = " def make_keys(n, size): return (secrets.token_hex(size) for _ in range(n)) def make_pad(name, pad_size, key_size): pad = [ MAGIC, f" f" *make_keys(pad_s...
import java.io.File import java.security.SecureRandom const val CHARS_PER_LINE = 48 const val CHUNK_SIZE = 6 const val COLS = 8 const val DEMO = true enum class FileType { OTP, ENC, DEC } fun Char.isAlpha() = this in 'A'..'Z' fun String.toAlpha() = this.filter { it.isAlpha() } fun String.isOtpRelated() = endsW...
Can you help me rewrite this code in Scala instead of Python, keeping it the same logically?
from itertools import zip_longest fc2 = NAME, WT, COV = 0, 1, 2 def right_type(txt): try: return float(txt) except ValueError: return txt def commas_to_list(the_list, lines, start_indent=0): for n, line in lines: indent = 0 while line.startswith(' ' * (4 * indent))...
class FCNode(val name: String, val weight: Int = 1, coverage: Double = 0.0) { var coverage = coverage set(value) { if (field != value) { field = value if (parent != null) parent!!.updateCoverage() } } val children = mutabl...
Can you help me rewrite this code in Scala instead of Python, keeping it the same logically?
Python 3.2 (r32:88445, Feb 20 2011, 21:30:00) [MSC v.1500 64 bit (AMD64)] on win32 Type "copyright", "credits" or "license()" for more information. >>> import __future__ >>> __future__.all_feature_names ['nested_scopes', 'generators', 'division', 'absolute_import', 'with_statement', 'print_function', 'unicode_literals'...
@Suppress("UNUSED_VARIABLE") fun main(args: Array<String>) { val s = "To be suppressed" }
Please provide an equivalent version of this Python code in Scala.
HW = r def snusp(store, code): ds = bytearray(store) dp = 0 cs = code.splitlines() ipr, ipc = 0, 0 for r, row in enumerate(cs): try: ipc = row.index('$') ipr = r break except ValueError: pass rt, dn, l...
const val hw = """ /++++!/===========?\>++.>+.+++++++..+++\ \+++\ | /+>+++++++>/ /++++++++++<<.++>./ $+++/ | \+++++++++>\ \+++++.>.+++.-----\ \==-<<<<+>+++/ /=.>.+>.--------.-/""" fun snusp(dlen: Int, raw: String) { val ds = CharArray(dlen) var dp = 0 var s = raw s = s...
Generate an equivalent Scala version of this Python code.
try: from functools import reduce except: pass def topx(data, tops=None): 'Extract the set of top-level(s) in topological order' for k, v in data.items(): v.discard(k) if tops is None: tops = toplevels(data) return _topx(data, tops, [], set()) def _topx(data, tops, _sofar, _sofar...
import java.util.LinkedList val s = "top1, top2, ip1, ip2, ip3, ip1a, ip2a, ip2b, ip2c, ipcommon, des1, " + "des1a, des1b, des1c, des1a1, des1a2, des1c1, extra1" val deps = mutableListOf( 0 to 10, 0 to 2, 0 to 3, 1 to 10, 1 to 3, 1 to 4, 2 to 17, 2 to 5, 2 to 9, 3 to 6, 3 to 7, 3 to 8, 3 to ...
Maintain the same structure and functionality when rewriting this code in Scala.
try: from functools import reduce except: pass def topx(data, tops=None): 'Extract the set of top-level(s) in topological order' for k, v in data.items(): v.discard(k) if tops is None: tops = toplevels(data) return _topx(data, tops, [], set()) def _topx(data, tops, _sofar, _sofar...
import java.util.LinkedList val s = "top1, top2, ip1, ip2, ip3, ip1a, ip2a, ip2b, ip2c, ipcommon, des1, " + "des1a, des1b, des1c, des1a1, des1a2, des1c1, extra1" val deps = mutableListOf( 0 to 10, 0 to 2, 0 to 3, 1 to 10, 1 to 3, 1 to 4, 2 to 17, 2 to 5, 2 to 9, 3 to 6, 3 to 7, 3 to 8, 3 to ...
Rewrite this program in Scala while keeping its functionality equivalent to the Python version.
def main(): resources = int(input("Cantidad de recursos: ")) processes = int(input("Cantidad de procesos: ")) max_resources = [int(i) for i in input("Recursos máximos: ").split()] print("\n-- recursos asignados para cada proceso --") currently_allocated = [[int(i) for i in input(f"proceso {j + 1}:...
fun main(args: Array<String>) { print("Enter the number of resources: ") val r = readLine()!!.toInt() print("\nEnter the number of processes: ") val p = readLine()!!.toInt() print("\nEnter Claim Vector: ") val maxRes = readLine()!!.split(' ').map { it.toInt() } .toIntArray() println("\n...
Transform the following Python implementation into Scala, maintaining the same output and logic.
def penrose(depth): print( <g id="A{d+1}" transform="translate(100, 0) scale(0.6180339887498949)"> <use href=" <use href=" </g> <g id="B{d+1}"> <use href=" <use href=" </g> <g id="G"> <use href=" <use href=" </g> </defs> <g transform="scale(2, 2)"> <use href=" <use href=" <use href=" <use hr...
import java.awt.* import java.awt.geom.Path2D import javax.swing.* class PenroseTiling(w: Int, h: Int) : JPanel() { private enum class Type { KITE, DART } private class Tile( val type: Type, val x: Double, val y: Double, val angle: Double, val size: Do...
Change the programming language of this snippet from Python to Scala without modifying what it does.
from itertools import count, islice import numpy as np from numpy import sin, cos, pi ANGDIV = 12 ANG = 2*pi/ANGDIV def draw_all(sols): import matplotlib.pyplot as plt def draw_track(ax, s): turn, xend, yend = 0, [0], [0] for d in s: x0, y0 = xend[-1], yend[-1] a = t...
const val RIGHT = 1 const val LEFT = -1 const val STRAIGHT = 0 fun normalize(tracks: IntArray): String { val size = tracks.size val a = CharArray(size) { "abc"[tracks[it] + 1] } var norm = String(a) repeat(size) { val s = String(a) if (s < norm) norm = s val tmp = a[0] ...
Write the same algorithm in Scala as shown in this Python implementation.
import httplib connection = httplib.HTTPSConnection('www.example.com',cert_file='myCert.PEM') connection.request('GET','/index.html') response = connection.getresponse() data = response.read()
import java.security.KeyStore import javax.net.ssl.KeyManagerFactory import javax.net.ssl.SSLContext import javax.net.ssl.HttpsURLConnection import java.net.URL import java.io.FileInputStream import java.io.InputStreamReader import java.io.BufferedReader fun getSSLContext(p12Path: String, password: String): SSLConte...
Rewrite the snippet below in Scala so it works the same as the original Python code.
import mysql.connector import hashlib import sys import random DB_HOST = "localhost" DB_USER = "devel" DB_PASS = "devel" DB_NAME = "test" def connect_db(): try: return mysql.connector.connect(host=DB_HOST, user=DB_USER, passwd=DB_PASS, db=DB_NAME) except: return ...
import java.sql.Connection import java.sql.DriverManager import java.sql.ResultSet import java.security.MessageDigest import java.security.SecureRandom import java.math.BigInteger class UserManager { private lateinit var dbConnection: Connection private fun md5(message: String): String { val hexStri...
Convert the following code from Python to Scala, ensuring the logic remains intact.
from PIL import Image im = Image.open("boxes_1.ppm") im.save("boxes_1.jpg")
import java.awt.Color import java.awt.Graphics import java.awt.image.BufferedImage class BasicBitmapStorage(width: Int, height: Int) { val image = BufferedImage(width, height, BufferedImage.TYPE_3BYTE_BGR) fun fill(c: Color) { val g = image.graphics g.color = c g.fillRect(0, 0, image...
Translate this program into Scala but keep the logic exactly as in Python.
from collections import defaultdict def from_edges(edges): class Node: def __init__(self): self.root = None self.succ = [] nodes = defaultdict(Node) for v,w in edges: nodes[v].succ.append(nodes[w]) for i...
import java.util.Stack typealias Nodes = List<Node> class Node(val n: Int) { var index = -1 var lowLink = -1 var onStack = false override fun toString() = n.toString() } class DirectedGraph(val vs: Nodes, val es: Map<Node, Nodes>) fun tarjan(g: DirectedGraph): List<Nodes> { val sccs = mu...
Keep all operations the same but rewrite the snippet in Scala.
from itertools import product minos = (((197123, 7, 6), (1797, 6, 7), (1287, 6, 7), (196867, 7, 6)), ((263937, 6, 6), (197126, 6, 6), (393731, 6, 6), (67332, 6, 6)), ((16843011, 7, 5), (2063, 5, 7), (3841, 5, 7), (271, 5, 7), (3848, 5, 7), (50463234, 7, 5), (50397441, 7, 5), (33686019, 7, 5)), ...
import java.util.Random val F = arrayOf( intArrayOf(1, -1, 1, 0, 1, 1, 2, 1), intArrayOf(0, 1, 1, -1, 1, 0, 2, 0), intArrayOf(1, 0, 1, 1, 1, 2, 2, 1), intArrayOf(1, 0, 1, 1, 2, -1, 2, 0), intArrayOf(1, -2, 1, -1, 1, 0, 2, -1), intArrayOf(0, 1, 1, 1, 1, 2, 2, 1), intArrayOf(1, -1, 1, 0, 1, 1, 2, -1),...
Change the programming language of this snippet from Python to Scala without modifying what it does.
class FibonacciHeap: class Node: def __init__(self, data): self.data = data self.parent = self.child = self.left = self.right = None self.degree = 0 self.mark = False def iterate(self, head): node = stop = head f...
class Node<V : Comparable<V>>(var value: V) { var parent: Node<V>? = null var child: Node<V>? = null var prev: Node<V>? = null var next: Node<V>? = null var rank = 0 var mark = false fun meld1(node: Node<V>) { this.prev?.next = node node.prev = this.prev node....
Convert the following code from C++ to Haskell, ensuring the logic remains intact.
#include <concepts> #include <iostream> void PrintMatrix(std::predicate<int, int, int> auto f, int size) { for(int y = 0; y < size; y++) { for(int x = 0; x < size; x++) { std::cout << " " << f(x, y, size); } std::cout << "\n"; } std::cout << "\n"; } int main() { auto diagonals = [...
twoDiagonalMatrix :: Int -> [[Int]] twoDiagonalMatrix n = flip (fmap . go) xs <$> xs where xs = [1 .. n] go x y | y == x = 1 | y == succ (subtract x n) = 1 | otherwise = 0 main :: IO () main = mapM_ putStrLn $ unlines . fmap (((' ' :) . show) =<<) . twoDiagonalMatrix <$...
Rewrite this program in Haskell while keeping its functionality equivalent to the C++ version.
#include <iostream> #include <fstream> int main() { std::string word; std::ifstream file("unixdict.txt"); if (!file) { std::cerr << "Cannot open unixdict.txt" << std::endl; return -1; } while (file >> word) { if (word.length() > 11 && word.find("the") != std::string::npos)...
import System.IO (readFile) import Data.List (isInfixOf) main = do txt <- readFile "unixdict.txt" let res = [ w | w <- lines txt, isInfixOf "the" w, length w > 11 ] putStrLn $ show (length res) ++ " words were found:" mapM_ putStrLn res
Convert this C++ snippet to Haskell and keep its semantics consistent.
#include <iostream> #include <string> #include <vector> #include <algorithm> std::string lcs(const std::vector<std::string>& strs) { std::vector<std::string::const_reverse_iterator> backs; std::string s; if (strs.size() == 0) return ""; if (strs.size() == 1) return strs[0]; for (auto& str...
import Data.List (transpose) longestCommonSuffix :: [String] -> String longestCommonSuffix = foldr (flip (<>) . return . head) [] . takeWhile (all =<< (==) . head) . transpose . fmap reverse main :: IO () main = mapM_ (putStrLn . longestCommonSuffix) [ [ "Sunday" , "Monday" , "Tuesday" ...
Convert this C++ block to Haskell, preserving its control flow and logic.
#include <iostream> #include <set> #include <cmath> int main() { std::set<int> values; for (int a=2; a<=5; a++) for (int b=2; b<=5; b++) values.insert(std::pow(a, b)); for (int i : values) std::cout << i << " "; std::cout << std::endl; return 0; }
import qualified Data.Set as S distinctPowerNumbers :: Int -> Int -> [Int] distinctPowerNumbers a b = (S.elems . S.fromList) $ (fmap (^) >>= (<*>)) [a .. b] main :: IO () main = print $ distinctPowerNumbers 2 5
Maintain the same structure and functionality when rewriting this code in Haskell.
#include <iostream> #include <map> int main() { const char* strings[] = {"133252abcdeeffd", "a6789798st", "yxcdfgxcyz"}; std::map<char, int> count; for (const char* str : strings) { for (; *str; ++str) ++count[*str]; } for (const auto& p : count) { if (p.second == 1) ...
import Data.List (group, sort) uniques :: [String] -> String uniques ks = [c | (c : cs) <- (group . sort . concat) ks, null cs] main :: IO () main = putStrLn $ uniques [ "133252abcdeeffd", "a6789798st", "yxcdfgxcyz" ]
Port the following code from C++ to Haskell with equivalent syntax and logic.
#include <algorithm> #include <iostream> template <class T> class AVLnode { public: T key; int balance; AVLnode *left, *right, *parent; AVLnode(T k, AVLnode *p) : key(k), balance(0), parent(p), left(NULL), right(NULL) {} ~AVLnode() { delete left; delete ri...
data Tree a = Leaf | Node Int (Tree a) a (Tree a) deriving (Show, Eq) foldTree :: Ord a => [a] -> Tree a foldTree = foldr insert Leaf height :: Tree a -> Int height Leaf = -1 height (Node h _ _ _) = h depth :: Tree a -> Tree a -> Int depth a b = succ (max (height a) (height b)) ins...
Port the provided C++ code into Haskell while preserving the original functionality.
#include <algorithm> #include <iostream> template <class T> class AVLnode { public: T key; int balance; AVLnode *left, *right, *parent; AVLnode(T k, AVLnode *p) : key(k), balance(0), parent(p), left(NULL), right(NULL) {} ~AVLnode() { delete left; delete ri...
data Tree a = Leaf | Node Int (Tree a) a (Tree a) deriving (Show, Eq) foldTree :: Ord a => [a] -> Tree a foldTree = foldr insert Leaf height :: Tree a -> Int height Leaf = -1 height (Node h _ _ _) = h depth :: Tree a -> Tree a -> Int depth a b = succ (max (height a) (height b)) ins...
Generate a Haskell translation of this C++ snippet without changing its computational steps.
class matrixNG { private: virtual void consumeTerm(){} virtual void consumeTerm(int n){} virtual const bool needTerm(){} protected: int cfn = 0, thisTerm; bool haveTerm = false; friend class NG; }; class NG_4 : public matrixNG { private: int a1, a, b1, b, t; const bool needTerm() { if...
import Data.Ratio ((%)) real2cf frac = let (quotient, remainder) = properFraction frac in (quotient : (if remainder == 0 then [] else real2cf (1 / remainder))) apply_hfunc (a1, a, b1, b) cf = recurs (a1, a, b1, b, cf) where recurs (a1, a, b1, b, cf) = if b1 ...
Port the following code from C++ to Haskell with equivalent syntax and logic.
class matrixNG { private: virtual void consumeTerm(){} virtual void consumeTerm(int n){} virtual const bool needTerm(){} protected: int cfn = 0, thisTerm; bool haveTerm = false; friend class NG; }; class NG_4 : public matrixNG { private: int a1, a, b1, b, t; const bool needTerm() { if...
import Data.Ratio ((%)) real2cf frac = let (quotient, remainder) = properFraction frac in (quotient : (if remainder == 0 then [] else real2cf (1 / remainder))) apply_hfunc (a1, a, b1, b) cf = recurs (a1, a, b1, b, cf) where recurs (a1, a, b1, b, cf) = if b1 ...
Please provide an equivalent version of this C++ code in Haskell.
#include <iostream> int main() { std::cout << R"EOF( A raw string begins with R, then a double-quote ("), then an optional identifier (here I've used "EOF"), then an opening parenthesis ('('). If you use an identifier, it cannot be longer than 16 characters, and it cannot contain a space, either op...
main :: IO () main = do putStrLn "Hello\ \ World!\n" putStrLn $ unwords ["This", "is", "an", "example", "text!\n"] putStrLn $ unlines [ unwords ["This", "is", "the", "first" , "line."] , unwords ["This", "is", "the", "second", "line."] , unwords ["This", "is", ...
Change the following C++ code into Haskell without altering its purpose.
#include <iostream> int main() { std::cout << R"EOF( A raw string begins with R, then a double-quote ("), then an optional identifier (here I've used "EOF"), then an opening parenthesis ('('). If you use an identifier, it cannot be longer than 16 characters, and it cannot contain a space, either op...
main :: IO () main = do putStrLn "Hello\ \ World!\n" putStrLn $ unwords ["This", "is", "an", "example", "text!\n"] putStrLn $ unlines [ unwords ["This", "is", "the", "first" , "line."] , unwords ["This", "is", "the", "second", "line."] , unwords ["This", "is", ...
Write a version of this C++ function in Haskell with identical behavior.
#include <algorithm> #include <array> #include <cassert> #include <initializer_list> #include <iostream> constexpr size_t sp_rows = 3; constexpr size_t sp_columns = 3; constexpr size_t sp_cells = sp_rows * sp_columns; constexpr int sp_limit = 4; class abelian_sandpile { friend std::ostream& operator<<(std::ostrea...
import Data.List (findIndex, transpose) import Data.List.Split (chunksOf) main :: IO () main = do let s0 = [[4, 3, 3], [3, 1, 2], [0, 2, 3]] s1 = [[1, 2, 0], [2, 1, 1], [0, 1, 3]] s2 = [[2, 1, 3], [1, 0, 1], [0, 1, 0]] s3_id = [[2, 1, 2], [1, 0, 1], [2, 1, 2]] s3 = replicate 3 (replicate 3...
Transform the following C++ implementation into Haskell, maintaining the same output and logic.
#include <algorithm> #include <array> #include <cassert> #include <initializer_list> #include <iostream> constexpr size_t sp_rows = 3; constexpr size_t sp_columns = 3; constexpr size_t sp_cells = sp_rows * sp_columns; constexpr int sp_limit = 4; class abelian_sandpile { friend std::ostream& operator<<(std::ostrea...
import Data.List (findIndex, transpose) import Data.List.Split (chunksOf) main :: IO () main = do let s0 = [[4, 3, 3], [3, 1, 2], [0, 2, 3]] s1 = [[1, 2, 0], [2, 1, 1], [0, 1, 3]] s2 = [[2, 1, 3], [1, 0, 1], [0, 1, 0]] s3_id = [[2, 1, 2], [1, 0, 1], [2, 1, 2]] s3 = replicate 3 (replicate 3...
Ensure the translated Haskell code behaves exactly like the original C++ snippet.
#include <iomanip> #include <iostream> bool nondecimal(unsigned int n) { for (; n > 0; n >>= 4) { if ((n & 0xF) > 9) return true; } return false; } int main() { unsigned int count = 0; for (unsigned int n = 0; n < 501; ++n) { if (nondecimal(n)) { ++count; ...
import Data.List (intercalate, transpose) import Data.List.Split (chunksOf) import Text.Printf (printf) p :: Int -> Bool p n = 9 < n && ( 9 < rem n 16 || p (quot n 16) ) main :: IO () main = let upperLimit = 500 xs = [show x | x <- [0 .. upperLimit], p x] in mapM_ putStrL...
Port the provided C++ code into Haskell while preserving the original functionality.
#include <iomanip> #include <iostream> bool nondecimal(unsigned int n) { for (; n > 0; n >>= 4) { if ((n & 0xF) > 9) return true; } return false; } int main() { unsigned int count = 0; for (unsigned int n = 0; n < 501; ++n) { if (nondecimal(n)) { ++count; ...
import Data.List (intercalate, transpose) import Data.List.Split (chunksOf) import Text.Printf (printf) p :: Int -> Bool p n = 9 < n && ( 9 < rem n 16 || p (quot n 16) ) main :: IO () main = let upperLimit = 500 xs = [show x | x <- [0 .. upperLimit], p x] in mapM_ putStrL...
Transform the following C++ implementation into Haskell, maintaining the same output and logic.
#include <cassert> #include <iomanip> #include <iostream> #include <string> #include <gmpxx.h> using big_int = mpz_class; auto juggler(int n) { assert(n >= 1); int count = 0, max_count = 0; big_int a = n, max = n; while (a != 1) { if (a % 2 == 0) a = sqrt(a); else ...
import Text.Printf import Data.List juggler :: Integer -> [Integer] juggler = takeWhile (> 1) . iterate (\x -> if odd x then isqrt (x*x*x) else isqrt x) task :: Integer -> IO () task n = printf s n (length ns + 1) (i :: Int) (showMa...
Port the provided C++ code into Haskell while preserving the original functionality.
#include <cassert> #include <iomanip> #include <iostream> #include <string> #include <gmpxx.h> using big_int = mpz_class; auto juggler(int n) { assert(n >= 1); int count = 0, max_count = 0; big_int a = n, max = n; while (a != 1) { if (a % 2 == 0) a = sqrt(a); else ...
import Text.Printf import Data.List juggler :: Integer -> [Integer] juggler = takeWhile (> 1) . iterate (\x -> if odd x then isqrt (x*x*x) else isqrt x) task :: Integer -> IO () task n = printf s n (length ns + 1) (i :: Int) (showMa...
Rewrite the snippet below in Haskell so it works the same as the original C++ code.
#include <time.h> #include <iostream> #include <string> #include <iomanip> #include <cstdlib> typedef unsigned int uint; using namespace std; enum movDir { UP, DOWN, LEFT, RIGHT }; class tile { public: tile() : val( 0 ), blocked( false ) {} uint val; bool blocked; }; class g2048 { public: g2048() : d...
import System.IO import Data.List import Data.Maybe import Control.Monad import Data.Random import Data.Random.Distribution.Categorical import System.Console.ANSI import Control.Lens prob4 :: Double prob4 = 0.1 type Position = [[Int]] combine, shift :: [Int]->[Int] combine (x:y:l) | x==y = (2*x) : combine l combi...
Keep all operations the same but rewrite the snippet in Haskell.
#include <windows.h> #include <iostream> #include <string> using namespace std; const int PLAYERS = 4, MAX_POINTS = 100; enum Moves { ROLL, HOLD }; class player { public: player() { current_score = round_score = 0; } void addCurrScore() { current_score += round_score; } ...
module Main where import System.Random (randomRIO) import Text.Printf (printf) data PInfo = PInfo { stack :: Int , score :: Int , rolls :: Int , next :: Bool , won :: Bool , name :: String } type...
Rewrite this program in Haskell while keeping its functionality equivalent to the C++ version.
#include <windows.h> #include <iostream> #include <string> using namespace std; const int PLAYERS = 4, MAX_POINTS = 100; enum Moves { ROLL, HOLD }; class player { public: player() { current_score = round_score = 0; } void addCurrScore() { current_score += round_score; } ...
module Main where import System.Random (randomRIO) import Text.Printf (printf) data PInfo = PInfo { stack :: Int , score :: Int , rolls :: Int , next :: Bool , won :: Bool , name :: String } type...
Convert the following code from C++ to Haskell, ensuring the logic remains intact.
#include <bitset> #include <cctype> #include <cstdlib> #include <fstream> #include <iomanip> #include <iostream> #include <map> #include <string> #include <vector> size_t consonants(const std::string& word) { std::bitset<26> bits; size_t bit = 0; for (char ch : word) { ch = std::tolower(static_ca...
import Data.Bifunctor (first) import Data.Char (toUpper) import Data.Function (on) import Data.List ((\\), groupBy, intersect, nub, sortOn) import Data.Ord (Down(..)) consonants :: String consonants = cons ++ map toUpper cons where cons = ['a'..'z'] \\ "aeiou" onlyConsonants :: String -> String onlyConsonan...
Keep all operations the same but rewrite the snippet in Haskell.
#include <gmpxx.h> #include <iomanip> #include <iostream> using big_int = mpz_class; bool is_probably_prime(const big_int& n) { return mpz_probab_prime_p(n.get_mpz_t(), 30) != 0; } big_int jacobsthal_number(unsigned int n) { return ((big_int(1) << n) - (n % 2 == 0 ? 1 : -1)) / 3; } big_int jacobsthal_lucas...
jacobsthal :: [Integer] jacobsthal = 0 : 1 : zipWith (\x y -> 2 * x + y) jacobsthal (tail jacobsthal) jacobsthalLucas :: [Integer] jacobsthalLucas = 2 : 1 : zipWith (\x y -> 2 * x + y) jacobsthalLucas (tail jacobsthalLucas) jacobsthalOblong :: [Integer] jacobsthalOblong = zipWith (*) jacobsthal (tail jacobsthal) isP...
Preserve the algorithm and functionality while converting the code from C++ to Haskell.
#include <gmpxx.h> #include <iomanip> #include <iostream> using big_int = mpz_class; bool is_probably_prime(const big_int& n) { return mpz_probab_prime_p(n.get_mpz_t(), 30) != 0; } big_int jacobsthal_number(unsigned int n) { return ((big_int(1) << n) - (n % 2 == 0 ? 1 : -1)) / 3; } big_int jacobsthal_lucas...
jacobsthal :: [Integer] jacobsthal = 0 : 1 : zipWith (\x y -> 2 * x + y) jacobsthal (tail jacobsthal) jacobsthalLucas :: [Integer] jacobsthalLucas = 2 : 1 : zipWith (\x y -> 2 * x + y) jacobsthalLucas (tail jacobsthalLucas) jacobsthalOblong :: [Integer] jacobsthalOblong = zipWith (*) jacobsthal (tail jacobsthal) isP...
Rewrite this program in Haskell while keeping its functionality equivalent to the C++ version.
#include <iostream> bool is_prime(int n) { if (n < 2) { return false; } if (n % 2 == 0) { return n == 2; } if (n % 3 == 0) { return n == 3; } int i = 5; while (i * i <= n) { if (n % i == 0) { return false; } i += 2; ...
import Data.List (scanl) import Data.Numbers.Primes (isPrime, primes) indexedPrimeSums :: [(Integer, Integer, Integer)] indexedPrimeSums = filter (\(_, _, n) -> isPrime n) $ scanl (\(i, _, m) p -> (succ i, p, p + m)) (0, 0, 0) primes main :: IO () main = mapM_ print $ takeWhile (\(_, ...
Change the programming language of this snippet from C++ to Haskell without modifying what it does.
#include <iostream> bool is_prime(int n) { if (n < 2) { return false; } if (n % 2 == 0) { return n == 2; } if (n % 3 == 0) { return n == 3; } int i = 5; while (i * i <= n) { if (n % i == 0) { return false; } i += 2; ...
import Data.List (scanl) import Data.Numbers.Primes (isPrime, primes) indexedPrimeSums :: [(Integer, Integer, Integer)] indexedPrimeSums = filter (\(_, _, n) -> isPrime n) $ scanl (\(i, _, m) p -> (succ i, p, p + m)) (0, 0, 0) primes main :: IO () main = mapM_ print $ takeWhile (\(_, ...