I have encountered the following problem:
N is positive non-zero integer and I have to calculate the product of : N*(N-1)^2*(N-2)^3*..*1^N.
My solution so far is as follows:
N*myFact(N-1)*fact(N-1)
The thing is I'm not allowed to use any helping functions, such as 'fact()'.
EDIT: Mathematically it can be represented as follows: N!*(N-1)! (N-2)!..*1!
This function is called the superfactorial. A recursive implementation is
long superFact(n) {
if (n < 2) return 1;
long last = superFact(n-1);
long prev = superFact(n-2);
return last * last / prev * n;
}
but this is very inefficient -- it takes about 3*F(n) recursive calls to find superFact(n), where F(n) is the n-th Fibonacci number. (The work grows exponentially.)
Try:
int myFact(int n) {
return n == 1 ? 1 : myFact(n-1)*n;
}
I assume this needs to be accomplished with 1 function i.e. you're not allowed to create a fact helper function yourself.
You can use the fact that myFact(n-1) / myFact(n-2) == (n-1)!
int myFact(int n)
{
if (n == 0 || n == 1) {
return 1
} else {
// (n - 1)!
int previousFact = myFact(n - 1) / myFact(n - 2);
return myFact(n - 1) * previousFact * n;
}
}
Related
I'm trying to write a function to find the lowest number that all integers between 1 and 20 divide. (Let's call this Condition D)
Here's my solution, which is somehow exceeding the call stack size limit.
function findSmallest(num){
var count = 2
while (count<21){
count++
if (num % count !== 0){
// exit the loop
return findSmallest(num++)
}
}
return num
}
console.log(findSmallest(20))
Somewhere my reasoning on this is faulty but here's how I see it (please correct me where I'm wrong):
Calling this function with a number N that doesn't meet Condition D will result in the function being called again with N + 1. Eventually, when it reaches a number M that should satisfy Condition D, the while loop runs all the way through and the number M is returned by the function and there are no more recursive calls.
But I get this error on running it:
function findSmallest(num){
^
RangeError: Maximum call stack size exceeded
I know errors like this are almost always due to recursive functions not reaching a base case. Is this the problem here, and if so, where's the problem?
I found two bugs.
in your while loop, the value of count is 3 to 21.
the value of num is changed in loop. num++ should be num + 1
However, even if these bugs are fixed, the error will not be solved.
The answer is 232792560.
This recursion depth is too large, so stack memory exhausted.
For example, this code causes same error.
function foo (num) {
if (num === 0) return
else foo(num - 1)
}
foo(232792560)
Coding without recursion can avoid errors.
Your problem is that you enter the recursion more than 200 million times (plus the bug spotted in the previous answer). The number you are looking for is the multiple of all prime numbers times their max occurrences in each number of the defined range. So here is your solution:
function findSmallestDivisible(n) {
if(n < 2 || n > 100) {
throw "Numbers between 2 and 100 please";
}
var arr = new Array(n), res = 2;
arr[0] = 1;
arr[1] = 2;
for(var i = 2; i < arr.length; i++) {
arr[i] = fix(i, arr);
res *= arr[i];
}
return res;
}
function fix(idx, arr) {
var res = idx + 1;
for(var i = 1; i < idx; i++) {
if((res % arr[i]) == 0) {
res /= arr[i];
}
}
return res;
}
https://jsfiddle.net/7ewkeamL/
I'm having trouble determining the worst case time complexity of this recursive function:
long f(int n) {
if(n <= 0) return 1;
else {
return f(n / 2) + f(n / 2) + f(n / 2);
}
}
I understand that if you were just returning f(n / 2) once, it would be O(log n). So I was wondering if having it three, four, five, etc times would affect the function's big O. Thanks!
Multiplying by a constant never affects the complexity. Of course, the execution time is roughly tripled, but the issue is how the time increases with respect to the value of n, not what the clock says.
Do note that this applies so easily because you're calling the same function with the same value; this could be reliably replaced by
return 3 * f(n/2)
If you had three different calls, such as
return f(n/2) + f(int(sqrt(n)) + f(n-1)
... then you'd have to compute the complexity of each and consider only the most complex. That isn't hard with this function; however, with a more complex function, such as the Collatz sequence, you'd have a more difficult time considering all of the 2nd- and 3rd-order complexities. You would also have more trouble with a call to an indirectly recursive function, such as
long f(int n);
long g(int n) {
if(n <= 2) return 1;
else {
return f(n*n mod 10) + g(n-2);
}
}
long f(int n) {
if(n <= 0) return 1;
else {
return f(n / 2) + g(n / 2);
}
}
Bottom line: your question is simple, but beware of follow-up questions.
I've several confusion about tail recursion as follows:
some of the recursion functions are void functions for example,
// Prints the given number of stars on the console.
// Assumes n >= 1.
void printStars(int n) {
if (n == 1) {
// n == 1, base case
cout << "*";
} else {
// n > 1, recursive case
cout << "*"; // print one star myself
printStars(n - 1); // recursion to do the rest
}
}
and another example:
// Prints the given integer's binary representation.
// Precondition: n >= 0
void printBinary(int n) {
if (n < 2) {
// base case; same as base 10
cout << n;
} else {
// recursive case; break number apart
printBinary(n / 2);
printBinary(n % 2);
}
}
As we know by definition tail recursion should return some value from tail call. But for void functions it does not return any value. By intinction I think they are tail recursion but I am not confident about it.
another question is that, if a recursion function has several logical end, should tail recursion come at all logical ends or just one of the logical ends? I saw someone argued that only one of the logical ends is OK, but I am not sure about that. Here's my example:
// Returns base ^ exp.
// Precondition: exp >= 0
int power(int base, int exp) {
if (exp < 0) {
throw "illegal negative exponent";
} else if (exp == 0) {
// base case; any number to 0th power is 1
return 1;
} else if (exp % 2 == 0) {
// recursive case 1: x^y = (x^2)^(y/2)
return power(base * base, exp / 2);
} else {
// recursive case 2: x^y = x * x^(y-1)
return base * power(base, exp - 1);
}
}
Here we have logical end as tail recursion and another one that is not tail recursion. Do you think this function is tail recursion or not? why?
Project Euler problem 14:
The following iterative sequence is
defined for the set of positive
integers:
n → n/2 (n is even) n → 3n + 1 (n is
odd)
Using the rule above and starting with
13, we generate the following
sequence: 13 → 40 → 20 → 10 → 5 → 16 →
8 → 4 → 2 → 1
It can be seen that this sequence
(starting at 13 and finishing at 1)
contains 10 terms. Although it has not
been proved yet (Collatz Problem), it
is thought that all starting numbers
finish at 1.
Which starting number, under one
million, produces the longest chain?
My first instinct is to create a function to calculate the chains, and run it with every number between 1 and 1 million. Obviously, that takes a long time. Way longer than solving this should take, according to Project Euler's "About" page. I've found several problems on Project Euler that involve large groups of numbers that a program running for hours didn't finish. Clearly, I'm doing something wrong.
How can I handle large groups of numbers quickly?
What am I missing here?
Have a read about memoization. The key insight is that if you've got a sequence starting A that has length 1001, and then you get a sequence B that produces an A, you don't to repeat all that work again.
This is the code in Mathematica, using memoization and recursion. Just four lines :)
f[x_] := f[x] = If[x == 1, 1, 1 + f[If[EvenQ[x], x/2, (3 x + 1)]]];
Block[{$RecursionLimit = 1000, a = 0, j},
Do[If[a < f[i], a = f[i]; j = i], {i, Reverse#Range#10^6}];
Print#a; Print[j];
]
Output .... chain length´525´ and the number is ... ohhhh ... font too small ! :)
BTW, here you can see a plot of the frequency for each chain length
Starting with 1,000,000, generate the chain. Keep track of each number that was generated in the chain, as you know for sure that their chain is smaller than the chain for the starting number. Once you reach 1, store the starting number along with its chain length. Take the next biggest number that has not being generated before, and repeat the process.
This will give you the list of numbers and chain length. Take the greatest chain length, and that's your answer.
I'll make some code to clarify.
public static long nextInChain(long n) {
if (n==1) return 1;
if (n%2==0) {
return n/2;
} else {
return (3 * n) + 1;
}
}
public static void main(String[] args) {
long iniTime=System.currentTimeMillis();
HashSet<Long> numbers=new HashSet<Long>();
HashMap<Long,Long> lenghts=new HashMap<Long, Long>();
long currentTry=1000000l;
int i=0;
do {
doTry(currentTry,numbers, lenghts);
currentTry=findNext(currentTry,numbers);
i++;
} while (currentTry!=0);
Set<Long> longs = lenghts.keySet();
long max=0;
long key=0;
for (Long aLong : longs) {
if (max < lenghts.get(aLong)) {
key = aLong;
max = lenghts.get(aLong);
}
}
System.out.println("number = " + key);
System.out.println("chain lenght = " + max);
System.out.println("Elapsed = " + ((System.currentTimeMillis()-iniTime)/1000));
}
private static long findNext(long currentTry, HashSet<Long> numbers) {
for(currentTry=currentTry-1;currentTry>=0;currentTry--) {
if (!numbers.contains(currentTry)) return currentTry;
}
return 0;
}
private static void doTry(Long tryNumber,HashSet<Long> numbers, HashMap<Long, Long> lenghts) {
long i=1;
long n=tryNumber;
do {
numbers.add(n);
n=nextInChain(n);
i++;
} while (n!=1);
lenghts.put(tryNumber,i);
}
Suppose you have a function CalcDistance(i) that calculates the "distance" to 1. For instance, CalcDistance(1) == 0 and CalcDistance(13) == 9. Here is a naive recursive implementation of this function (in C#):
public static int CalcDistance(long i)
{
if (i == 1)
return 0;
return (i % 2 == 0) ? CalcDistance(i / 2) + 1 : CalcDistance(3 * i + 1) + 1;
}
The problem is that this function has to calculate the distance of many numbers over and over again. You can make it a little bit smarter (and a lot faster) by giving it a memory. For instance, lets create a static array that can store the distance for the first million numbers:
static int[] list = new int[1000000];
We prefill each value in the list with -1 to indicate that the value for that position is not yet calculated. After this, we can optimize the CalcDistance() function:
public static int CalcDistance(long i)
{
if (i == 1)
return 0;
if (i >= 1000000)
return (i % 2 == 0) ? CalcDistance(i / 2) + 1 : CalcDistance(3 * i + 1) + 1;
if (list[i] == -1)
list[i] = (i % 2 == 0) ? CalcDistance(i / 2) + 1: CalcDistance(3 * i + 1) + 1;
return list[i];
}
If i >= 1000000, then we cannot use our list, so we must always calculate it. If i < 1000000, then we check if the value is in the list. If not, we calculate it first and store it in the list. Otherwise we just return the value from the list. With this code, it took about ~120ms to process all million numbers.
This is a very simple example of memoization. I use a simple list to store intermediate values in this example. You can use more advanced data structures like hashtables, vectors or graphs when appropriate.
Minimize how many levels deep your loops are, and use an efficient data structure such as IList or IDictionary, that can auto-resize itself when it needs to expand. If you use plain arrays they need to be copied to larger arrays as they expand - not nearly as efficient.
This variant doesn't use an HashMap but tries only to not repeat the first 1000000 numbers. I don't use an hashmap because the biggest number found is around 56 billions, and an hash map could crash.
I have already done some premature optimization. Instead of / I use >>, instead of % I use &. Instead of * I use some +.
void Main()
{
var elements = new bool[1000000];
int longestStart = -1;
int longestRun = -1;
long biggest = 0;
for (int i = elements.Length - 1; i >= 1; i--) {
if (elements[i]) {
continue;
}
elements[i] = true;
int currentStart = i;
int currentRun = 1;
long current = i;
while (current != 1) {
if (current > biggest) {
biggest = current;
}
if ((current & 1) == 0) {
current = current >> 1;
} else {
current = current + current + current + 1;
}
currentRun++;
if (current < elements.Length) {
elements[current] = true;
}
}
if (currentRun > longestRun) {
longestStart = i;
longestRun = currentRun;
}
}
Console.WriteLine("Longest Start: {0}, Run {1}", longestStart, longestRun);
Console.WriteLine("Biggest number: {0}", biggest);
}
----------Updated ------------
codymanix and moonshadow have been a big help thus far. I was able to solve my problem using the equations and instead of using right shift I divided by 29. Because with 32bits signed 2^31 = overflows to 29. Which works!
Prototype in PHP
$r = $x - (($x - $y) & (($x - $y) / (29)));
Actual code for LEADS (you can only do one math function PER LINE!!! AHHHH!!!)
DERIVDE1 = IMAGE1 - IMAGE2;
DERIVED2 = DERIVED1 / 29;
DERIVED3 = DERIVED1 AND DERIVED2;
MAX = IMAGE1 - DERIVED3;
----------Original Question-----------
I don't think this is quite possible with my application's limitations but I figured it's worth a shot to ask.
I'll try to make this simple. I need to find the max values between two numbers without being able to use a IF or any conditional statement.
In order to find the the MAX values I can only perform the following functions
Divide, Multiply, Subtract, Add, NOT, AND ,OR
Let's say I have two numbers
A = 60;
B = 50;
Now if A is always greater than B it would be simple to find the max value
MAX = (A - B) + B;
ex.
10 = (60 - 50)
10 + 50 = 60 = MAX
Problem is A is not always greater than B. I cannot perform ABS, MAX, MIN or conditional checks with the scripting applicaiton I am using.
Is there any way possible using the limited operation above to find a value VERY close to the max?
finding the maximum of 2 variables:
max = a-((a-b)&((a-b)>>31))
where >> is bitwise right-shift (also called SHR or ASR depeding on signedness).
Instead of 31 you use the number of bits your numbers have minus one.
I guess this one would be the most simplest if we manage to find difference between two numbers (only the magnitude not sign)
max = ((a+b)+|a-b|)/2;
where |a-b| is a magnitude of difference between a and b.
If you can't trust your environment to generate the appropriate branchless operations when they are available, see this page for how to proceed. Note the restriction on input range; use a larger integer type for the operation if you cannot guarantee your inputs will fit.
Solution without conditionals. Cast to uint then back to int to get abs.
int abs (a) { return (int)((unsigned int)a); }
int max (a, b) { return (a + b + abs(a - b)) / 2; }
int max3 (a, b, c) { return (max(max(a,b),c); }
Using logical operations only, short circuit evaluation and assuming the C convention of rounding towards zero, it is possible to express this as:
int lt0(int x) {
return x && (!!((x-1)/x));
}
int mymax(int a, int b) {
return lt0(a-b)*b+lt0(b-a)*a;
}
The basic idea is to implement a comparison operator that will return 0 or 1. It's possible to do a similar trick if your scripting language follows the convention of rounding toward the floor value like python does.
function Min(x,y:integer):integer;
Var
d:integer;
abs:integer;
begin
d:=x-y;
abs:=d*(1-2*((3*d) div (3*d+1)));
Result:=(x+y-abs) div 2;
end;
Hmmm. I assume NOT, AND, and OR are bitwise? If so, there's going to be a bitwise expression to solve this. Note that A | B will give a number >= A and >= B. Perhaps there's a pruning method for selecting the number with the most bits.
To extend, we need the following to determine whether A (0) or B (1) is greater.
truth table:
0|0 = 0
0|1 = 1
1|0 = 0
1|1 = 0
!A and B
therefore, will give the index of the greater bit. Ergo, compare each bit in both numbers, and when they are different, use the above expression (Not A And B) to determine which number was greater. Start from the most significant bit and proceed down both bytes. If you have no looping construct, manually compare each bit.
Implementing "when they are different":
(A != B) AND (my logic here)
try this, (but be aware for overflows)
(Code in C#)
public static Int32 Maximum(params Int32[] values)
{
Int32 retVal = Int32.MinValue;
foreach (Int32 i in values)
retVal += (((i - retVal) >> 31) & (i - retVal));
return retVal;
}
You can express this as a series of arithmetic and bitwise operations, e.g.:
int myabs(const int& in) {
const int tmp = in >> ((sizeof(int) * CHAR_BIT) - 1);
return tmp - (in ^ tmp(;
}
int mymax(int a, int b) {
return ((a+b) + myabs(b-a)) / 2;
}
//Assuming 32 bit integers
int is_diff_positive(int num)
{
((num & 0x80000000) >> 31) ^ 1; // if diff positive ret 1 else 0
}
int sign(int x)
{
return ((num & 0x80000000) >> 31);
}
int flip(int x)
{
return x ^ 1;
}
int max(int a, int b)
{
int diff = a - b;
int is_pos_a = sign(a);
int is_pos_b = sign(b);
int is_diff_positive = diff_positive(diff);
int is_diff_neg = flip(is_diff_positive);
// diff (a - b) will overflow / underflow if signs are opposite
// ex: a = INT_MAX , b = -3 then a - b => INT_MAX - (-3) => INT_MAX + 3
int can_overflow = is_pos_a ^ is_pos_b;
int cannot_overflow = flip(can_overflow);
int res = (cannot_overflow * ( (a * is_diff_positive) + (b *
is_diff_negative)) + (can_overflow * ( (a * is_pos_a) + (b *
is_pos_b)));
return res;
}
This is my implementation using only +, -, *, %, / operators
using static System.Console;
int Max(int a, int b) => (a + b + Abs(a - b)) / 2;
int Abs(int x) => x * ((2 * x + 1) % 2);
WriteLine(Max(-100, -2) == -2); // true
WriteLine(Max(2, -100) == 2); // true
I just came up with an expression:
(( (a-b)-|a-b| ) / (2(a-b)) )*b + (( (b-a)-|b-a| )/(2(b-a)) )*a
which is equal to a if a>b and is equal to b if b>a
when a>b:
a-b>0, a-b = |a-b|, (a-b)-|a-b| = 0 so the coeficcient for b is 0
b-a<0, b-a = -|b-a|, (b-a)-|b-a| = 2(b-a)
so the coeficcient for a is 2(b-a)/2(b-a) which is 1
so it would ultimately return 0*b+1*a if a is bigger and vice versa
Find MAX between n & m
MAX = ( (n/2) + (m/2) + ( ((n/2) - (m/2)) * ( (2*((n/2) - (m/2)) + 1) % 2) ) )
Using #define in c:
#define MAX(n, m) ( (n/2) + (m/2) + ( ((n/2) - (m/2)) * ( (2*((n/2) - (m/2)) + 1) % 2) ) )
or
#define ABS(n) ( n * ( (2*n + 1) % 2) ) // Calculates abs value of n
#define MAX(n, m) ( (n/2) + (m/2) + ABS((n/2) - (m/2)) ) // Finds max between n & m
#define MIN(n, m) ( (n/2) + (m/2) - ABS((n/2) - (m/2)) ) // Finds min between n & m
please look at this program.. this might be the best answer till date on this page...
#include <stdio.h>
int main()
{
int a,b;
a=3;
b=5;
printf("%d %d\n",a,b);
b = (a+b)-(a=b); // this line is doing the reversal
printf("%d %d\n",a,b);
return 0;
}
If A is always greater than B .. [ we can use] .. MAX = (A - B) + B;
No need. Just use: int maxA(int A, int B){ return A;}
(1) If conditionals are allowed you do max = a>b ? a : b.
(2) Any other method either use a defined set of numbers or rely on the implicit conditional checks.
(2a) max = a-((a-b)&((a-b)>>31)) this is neat, but it only works if you use 32 bit numbers. You can expand it arbitrary large number N, but the method will fail if you try to find max(N-1, N+1). This algorithm works for finite state automata, but not a Turing machine.
(2b) Magnitude |a-b| is a condition |a-b| = a-b>0 a-b : b-a
What about:
Square root is also a condition. Whenever c>0 and c^2 = d we have second solution -c, because (-c)^2 = (-1)^2*c^2 = 1*c^2 = d. Square root returns the greatest in the pair. I comes with a build in int max(int c1, int c2){return max(c1, c2);}
Without comparison operator math is very symmetric as well as limited in power. Positive and negative numbers cannot be distinguished without if of some sort.
It depends which language you're using, but the Ternary Operator might be useful.
But then, if you can't perform conditional checks in your 'scripting application', you probably don't have the ternary operator.
using System;
namespace ConsoleApp2
{
class Program
{
static void Main(string[] args)
{
float a = 101, b = 15;
float max = (a + b) / 2 + ((a > b) ? a - b : b - a) / 2;
}
}
}
#region GetMaximumNumber
/// <summary>
/// Provides method to get maximum values.
/// </summary>
/// <param name="values">Integer array for getting maximum values.</param>
/// <returns>Maximum number from an array.</returns>
private int GetMaximumNumber(params int[] values)
{
// Declare to store the maximum number.
int maximumNumber = 0;
try
{
// Check that array is not null and array has an elements.
if (values != null &&
values.Length > 0)
{
// Sort the array in ascending order for getting maximum value.
Array.Sort(values);
// Get the last value from an array which is always maximum.
maximumNumber = values[values.Length - 1];
}
}
catch (Exception ex)
{
throw ex;
}
return maximumNumber;
}
#endregion