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LeetCode medium 120. Triangle (Dynamic Programming)
Question:
Given a triangle, find the minimum path sum from top to bottom. Each step you may move to adjacent numbers on the row below.
For example, given the following triangle
[
[2],
[3,4],
[6,5,7],
[4,1,8,3]
]
//The minimum path sum from top to bottom is 11 (i.e., 2 + 3 + 5 + 1 = 11).
//Note:
//Bonus point if you are able to do this using only O(n) extra space, where n is the total number of rows in the triangle.
I always get
fatal error: Can't form Range with end < start
on "for i in (row-1)...0".
Thank you so much! Appreciate your time!
class Solution
{
func minimumTotal(triangle: [[Int]]) -> Int
{
if triangle.count == 0
{
return 0
}
if triangle.count == 1
{
return triangle[0][0]
}
var arr = [Int](count: triangle.last!.count, repeatedValue: 0)
let row = triangle.count
for i in (row-1)...0
{
let col = triangle[i].count
for j in 0...col-1
{
if i == row-1
{
arr[i] = triangle[i][j]
continue
}
arr[j] = min(arr[j], arr[j+1]) + triangle[i][j]
}
}
return arr[0]
}
}
var test1 = Solution()
//var input = [[10]]
//var input = [[1],[2,3]]
var input = [[-1],[2,3],[1,-1,-3]]
var result = test1.minimumTotal(input)
print(result)
for in (0...row-1).reverse()
Swift can't read row-1...0
It's a bad idea to create a range where the start is higher than the end: your code will compile, but it will crash at runtime, so use stride instead of ranage
for i in (row-1).stride(to: 0, by: 1) { }
With the U.S.'s large $1.5 Billion lottery this week, I wrote a function in Ruby to make Powerball picks. In Powerball, you choose 5 numbers from the range 1..69 (with no duplicates) and 1 number from the range 1..26.
This is what I came up with:
def pball
Array(1..69).shuffle[0..4].sort + [rand(1..26)]
end
It works by creating an array of integers from 1 to 69, shuffling that array, choosing the first 5 numbers, sorting those, and finally adding on a number from 1 to 26.
To do this in Swift takes a bit more work since Swift doesn't have the built-in shuffle method on Array.
This was my attempt:
func pball() -> [Int] {
let arr = Array(1...69).map{($0, drand48())}.sort{$0.1 < $1.1}.map{$0.0}[0...4].sort()
return arr + [Int(arc4random_uniform(26) + 1)]
}
Since there is no shuffle method, it works by creating an [Int] with values in the range 1...69. It then uses map to create [(Int, Double)], an array of tuple pairs that contain the numbers and a random Double in the range 0.0 ..< 1.0. It then sorts this array using the Double values and uses a second map to return to [Int] and then uses the slice [0...4] to extract the first 5 numbers and sort() to sort them.
In the second line, it appends a number in the range 1...26. I tried adding this to the first line, but Swift gave the error:
Expression was too complex to be solved in reasonable time; consider
breaking up the expression into distinct sub-expressions.
Can anyone suggest how to turn this into a 1-line function? Perhaps there is a better way to choose the 5 numbers from 1...69.
Xcode 8.3 • Swift 3.1
import GameKit
var powerballNumbers: [Int] {
return (GKRandomSource.sharedRandom().arrayByShufflingObjects(in: Array(1...69)) as! [Int])[0..<5].sorted() + [Int(arc4random_uniform(26) + 1)]
}
powerballNumbers // [5, 9, 62, 65, 69, 2]
Swift 2.x
import GameKit
var powerballNumbers: [Int] {
return (GKRandomSource.sharedRandom().arrayByShufflingObjectsInArray(Array(1...69)) as! [Int])[0...4].sort() + [Int(arc4random_uniform(26).successor())]
}
powerballNumbers // [21, 37, 39, 42, 65, 23]
I don't find the "one-liner" concept very compelling. Some languages lend themselves to it; others don't. I would suggest giving Swift a shuffle method to start with:
extension Array {
mutating func shuffle () {
for var i = self.count - 1; i != 0; i-- {
let ix1 = i
let ix2 = Int(arc4random_uniform(UInt32(i+1)))
(self[ix1], self[ix2]) = (self[ix2], self[ix1])
}
}
}
But since I made this mutating, we still need more than one line to express the entire operation because we have to have a var reference to our starting array:
var arr = Array(1...69)
(1...4).forEach {_ in arr.shuffle()}
let result = Array(arr[0..<5]) + [Int(arc4random_uniform(26)) + 1]
If you really insist on the one-liner, and you don't count the code needed to implement shuffle, then you can do it, though less efficiently, by defining shuffle more like this:
extension Array {
func shuffle () -> [Element] {
var arr = self
for var i = arr.count - 1; i != 0; i-- {
let ix1 = i
let ix2 = Int(arc4random_uniform(UInt32(i+1)))
(arr[ix1], arr[ix2]) = (arr[ix2], arr[ix1])
}
return arr
}
}
And here's your one-liner:
let result = Array(1...69).shuffle().shuffle().shuffle().shuffle()[0..<5] + [Int(arc4random_uniform(26)) + 1]
But oops, I omitted your sort. I don't see how to do that without getting the "too complex" error; to work around that, I had to split it into two lines:
var result = Array(1...69).shuffle().shuffle().shuffle().shuffle()[0..<5].sort(<)
result.append(Int(arc4random_uniform(26)) + 1)
How about this:
let winningDraw = (1...69).sort{ _ in arc4random_uniform(2) > 0}[0...4].sort() + [Int(arc4random_uniform(26)+1)]
[edit] above formula wasn't random. but this one will be
(1...69).map({Int(rand()%1000*70+$0)}).sort().map({$0%70})[0...4].sort() + [Int(rand()%26+1)]
For the fun of it, a non-GameplayKit (long) one-liner for Swift 3, using the global sequence(state:next:) function to generate random elements from the mutable state array rather than shuffling the array (although mutating the value array 5 times, so some extra copy operations here...)
let powerballNumbers = Array(sequence(state: Array(1...69), next: {
(s: inout [Int]) -> Int? in s.remove(at: Int(arc4random_uniform(UInt32(s.count))))})
.prefix(5).sorted()) + [Int(arc4random_uniform(26) + 1)]
... broken down for readability.
(Possible in future Swift version)
If the type inference weren't broken inout closure parameters (as arguments to closures), we could reduce the above to:
let powerballNumbers = Array(sequence(state: Array(1...69), next: {
$0.remove(at: Int(arc4random_uniform(UInt32($0.count)))) })
.prefix(5).sorted()) + [Int(arc4random_uniform(26) + 1)]
If we'd also allow the following extension
extension Int {
var rand: Int { return Int(arc4random_uniform(UInt32(exactly: self) ?? 0)) }
}
Then, we could go on to reduce the one-line to:
let powerballNumbers = Array(sequence(state: Array(1...69), next: { $0.remove(at: $0.count.rand) }).prefix(5).sorted()) + [26.rand + 1]
Xcode 10 • Swift 4.2
Swift now has added shuffled() to ClosedRange and random(in:) to Int which now makes this easily accomplished in one line:
func pball() -> [Int] {
return (1...69).shuffled().prefix(5).sorted() + [Int.random(in: 1...26)]
}
Further trimmings:
Because of the return type of pball(), the Int can be inferred in the random method call. Also, .prefix(5) can be replaced with [...4]. Finally, return can be omitted from the one-line function:
func pball() -> [Int] {
(1...69).shuffled()[...4].sorted() + [.random(in: 1...26)]
}
Given a mapping:
A: 1
B: 2
C: 3
...
...
...
Z: 26
Find all possible ways a number can be represented. E.g. For an input: "121", we can represent it as:
ABA [using: 1 2 1]
LA [using: 12 1]
AU [using: 1 21]
I tried thinking about using some sort of a dynamic programming approach, but I am not sure how to proceed. I was asked this question in a technical interview.
Here is a solution I could think of, please let me know if this looks good:
A[i]: Total number of ways to represent the sub-array number[0..i-1] using the integer to alphabet mapping.
Solution [am I missing something?]:
A[0] = 1 // there is only 1 way to represent the subarray consisting of only 1 number
for(i = 1:A.size):
A[i] = A[i-1]
if(input[i-1]*10 + input[i] < 26):
A[i] += 1
end
end
print A[A.size-1]
To just get the count, the dynamic programming approach is pretty straight-forward:
A[0] = 1
for i = 1:n
A[i] = 0
if input[i-1] > 0 // avoid 0
A[i] += A[i-1];
if i > 1 && // avoid index-out-of-bounds on i = 1
10 <= (10*input[i-2] + input[i-1]) <= 26 // check that number is 10-26
A[i] += A[i-2];
If you instead want to list all representations, dynamic programming isn't particularly well-suited for this, you're better off with a simple recursive algorithm.
First off, we need to find an intuitive way to enumerate all the possibilities. My simple construction, is given below.
let us assume a simple way to represent your integer in string format.
a1 a2 a3 a4 ....an, for instance in 121 a1 -> 1 a2 -> 2, a3 -> 1
Now,
We need to find out number of possibilities of placing a + sign in between two characters. + is to mean characters concatenation here.
a1 - a2 - a3 - .... - an, - shows the places where '+' can be placed. So, number of positions is n - 1, where n is the string length.
Assume a position may or may not have a + symbol shall be represented as a bit.
So, this boils down to how many different bit strings are possible with the length of n-1, which is clearly 2^(n-1). Now in order to enumerate the possibilities go through every bit string and place right + signs in respective positions to get every representations,
For your example, 121
Four bit strings are possible 00 01 10 11
1 2 1
1 2 + 1
1 + 2 1
1 + 2 + 1
And if you see a character followed by a +, just add the next char with the current one and do it sequentially to get the representation,
x + y z a + b + c d
would be (x+y) z (a+b+c) d
Hope it helps.
And you will have to take care of edge cases where the size of some integer > 26, of course.
I think, recursive traverse through all possible combinations would do just fine:
mapping = {"1":"A", "2":"B", "3":"C", "4":"D", "5":"E", "6":"F", "7":"G",
"8":"H", "9":"I", "10":"J",
"11":"K", "12":"L", "13":"M", "14":"N", "15":"O", "16":"P",
"17":"Q", "18":"R", "19":"S", "20":"T", "21":"U", "22":"V", "23":"W",
"24":"A", "25":"Y", "26":"Z"}
def represent(A, B):
if A == B == '':
return [""]
ret = []
if A in mapping:
ret += [mapping[A] + r for r in represent(B, '')]
if len(A) > 1:
ret += represent(A[:-1], A[-1]+B)
return ret
print represent("121", "")
Assuming you only need to count the number of combinations.
Assuming 0 followed by an integer in [1,9] is not a valid concatenation, then a brute-force strategy would be:
Count(s,n)
x=0
if (s[n-1] is valid)
x=Count(s,n-1)
y=0
if (s[n-2] concat s[n-1] is valid)
y=Count(s,n-2)
return x+y
A better strategy would be to use divide-and-conquer:
Count(s,start,n)
if (len is even)
{
//split s into equal left and right part, total count is left count multiply right count
x=Count(s,start,n/2) + Count(s,start+n/2,n/2);
y=0;
if (s[start+len/2-1] concat s[start+len/2] is valid)
{
//if middle two charaters concatenation is valid
//count left of the middle two characters
//count right of the middle two characters
//multiply the two counts and add to existing count
y=Count(s,start,len/2-1)*Count(s,start+len/2+1,len/2-1);
}
return x+y;
}
else
{
//there are three cases here:
//case 1: if middle character is valid,
//then count everything to the left of the middle character,
//count everything to the right of the middle character,
//multiply the two, assign to x
x=...
//case 2: if middle character concatenates the one to the left is valid,
//then count everything to the left of these two characters
//count everything to the right of these two characters
//multiply the two, assign to y
y=...
//case 3: if middle character concatenates the one to the right is valid,
//then count everything to the left of these two characters
//count everything to the right of these two characters
//multiply the two, assign to z
z=...
return x+y+z;
}
The brute-force solution has time complexity of T(n)=T(n-1)+T(n-2)+O(1) which is exponential.
The divide-and-conquer solution has time complexity of T(n)=3T(n/2)+O(1) which is O(n**lg3).
Hope this is correct.
Something like this?
Haskell code:
import qualified Data.Map as M
import Data.Maybe (fromJust)
combs str = f str [] where
charMap = M.fromList $ zip (map show [1..]) ['A'..'Z']
f [] result = [reverse result]
f (x:xs) result
| null xs =
case M.lookup [x] charMap of
Nothing -> ["The character " ++ [x] ++ " is not in the map."]
Just a -> [reverse $ a:result]
| otherwise =
case M.lookup [x,head xs] charMap of
Just a -> f (tail xs) (a:result)
++ (f xs ((fromJust $ M.lookup [x] charMap):result))
Nothing -> case M.lookup [x] charMap of
Nothing -> ["The character " ++ [x]
++ " is not in the map."]
Just a -> f xs (a:result)
Output:
*Main> combs "121"
["LA","AU","ABA"]
Here is the solution based on my discussion here:
private static int decoder2(int[] input) {
int[] A = new int[input.length + 1];
A[0] = 1;
for(int i=1; i<input.length+1; i++) {
A[i] = 0;
if(input[i-1] > 0) {
A[i] += A[i-1];
}
if (i > 1 && (10*input[i-2] + input[i-1]) <= 26) {
A[i] += A[i-2];
}
System.out.println(A[i]);
}
return A[input.length];
}
Just us breadth-first search.
for instance 121
Start from the first integer,
consider 1 integer character first, map 1 to a, leave 21
then 2 integer character map 12 to L leave 1.
This problem can be done in o(fib(n+2)) time with a standard DP algorithm.
We have exactly n sub problems and button up we can solve each problem with size i in o(fib(i)) time.
Summing the series gives fib (n+2).
If you consider the question carefully you see that it is a Fibonacci series.
I took a standard Fibonacci code and just changed it to fit our conditions.
The space is obviously bound to the size of all solutions o(fib(n)).
Consider this pseudo code:
Map<Integer, String> mapping = new HashMap<Integer, String>();
List<String > iterative_fib_sequence(string input) {
int length = input.length;
if (length <= 1)
{
if (length==0)
{
return "";
}
else//input is a-j
{
return mapping.get(input);
}
}
List<String> b = new List<String>();
List<String> a = new List<String>(mapping.get(input.substring(0,0));
List<String> c = new List<String>();
for (int i = 1; i < length; ++i)
{
int dig2Prefix = input.substring(i-1, i); //Get a letter with 2 digit (k-z)
if (mapping.contains(dig2Prefix))
{
String word2Prefix = mapping.get(dig2Prefix);
foreach (String s in b)
{
c.Add(s.append(word2Prefix));
}
}
int dig1Prefix = input.substring(i, i); //Get a letter with 1 digit (a-j)
String word1Prefix = mapping.get(dig1Prefix);
foreach (String s in a)
{
c.Add(s.append(word1Prefix));
}
b = a;
a = c;
c = new List<String>();
}
return a;
}
old question but adding an answer so that one can find help
It took me some time to understand the solution to this problem – I refer accepted answer and #Karthikeyan's answer and the solution from geeksforgeeks and written my own code as below:
To understand my code first understand below examples:
we know, decodings([1, 2]) are "AB" or "L" and so decoding_counts([1, 2]) == 2
And, decodings([1, 2, 1]) are "ABA", "AU", "LA" and so decoding_counts([1, 2, 1]) == 3
using the above two examples let's evaluate decodings([1, 2, 1, 4]):
case:- "taking next digit as single digit"
taking 4 as single digit to decode to letter 'D', we get decodings([1, 2, 1, 4]) == decoding_counts([1, 2, 1]) because [1, 2, 1, 4] will be decode as "ABAD", "AUD", "LAD"
case:- "combining next digit with the previous digit"
combining 4 with previous 1 as 14 as a single to decode to letter N, we get decodings([1, 2, 1, 4]) == decoding_counts([1, 2]) because [1, 2, 1, 4] will be decode as "ABN" or "LN"
Below is my Python code, read comments
def decoding_counts(digits):
# defininig count as, counts[i] -> decoding_counts(digits[: i+1])
counts = [0] * len(digits)
counts[0] = 1
for i in xrange(1, len(digits)):
# case:- "taking next digit as single digit"
if digits[i] != 0: # `0` do not have mapping to any letter
counts[i] = counts[i -1]
# case:- "combining next digit with the previous digit"
combine = 10 * digits[i - 1] + digits[i]
if 10 <= combine <= 26: # two digits mappings
counts[i] += (1 if i < 2 else counts[i-2])
return counts[-1]
for digits in "13", "121", "1214", "1234121":
print digits, "-->", decoding_counts(map(int, digits))
outputs:
13 --> 2
121 --> 3
1214 --> 5
1234121 --> 9
note: I assumed that input digits do not start with 0 and only consists of 0-9 and have a sufficent length
For Swift, this is what I came up with. Basically, I converted the string into an array and goes through it, adding a space into different positions of this array, then appending them to another array for the second part, which should be easy after this is done.
//test case
let input = [1,2,2,1]
func combination(_ input: String) {
var arr = Array(input)
var possible = [String]()
//... means inclusive range
for i in 2...arr.count {
var temp = arr
//basically goes through it backwards so
// adding the space doesn't mess up the index
for j in (1..<i).reversed() {
temp.insert(" ", at: j)
possible.append(String(temp))
}
}
print(possible)
}
combination(input)
//prints:
//["1 221", "12 21", "1 2 21", "122 1", "12 2 1", "1 2 2 1"]
def stringCombinations(digits, i=0, s=''):
if i == len(digits):
print(s)
return
alphabet = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
total = 0
for j in range(i, min(i + 1, len(digits) - 1) + 1):
total = (total * 10) + digits[j]
if 0 < total <= 26:
stringCombinations(digits, j + 1, s + alphabet[total - 1])
if __name__ == '__main__':
digits = list()
n = input()
n.split()
d = list(n)
for i in d:
i = int(i)
digits.append(i)
print(digits)
stringCombinations(digits)
This is an interview question: "How to build a distributed algorithm to compute the balance of the parentheses ?"
Usually he balance algorithm scans a string form left to right and uses a stack to make sure that the number of open parentheses always >= the number of close parentheses and finally the number of open parentheses == the number of close parentheses.
How would you make it distributed ?
You can break the string into chunks and process each separately, assuming you can read and send to the other machines in parallel. You need two numbers for each string.
The minimum nesting depth achieved relative to the start of the string.
The total gain or loss in nesting depth across the whole string.
With these values, you can compute the values for the concatenation of many chunks as follows:
minNest = 0
totGain = 0
for p in chunkResults
minNest = min(minNest, totGain + p.minNest)
totGain += p.totGain
return new ChunkResult(minNest, totGain)
The parentheses are matched if the final values of totGain and minNest are zero.
I would apply the map-reduce algorithm in which the map function would compute a part of the string return either an empty string if parentheses are balanced or a string with the last parenthesis remaining.
Then the reduce function would concatenate the result of two returned strings by map function and compute it again returning the same result than map. At the end of all computations, you'd either obtain an empty string or a string containing the un-balanced parenthesis.
I'll try to have a more detailed explain on #jonderry's answer. Code first, in Scala
def parBalance(chars: Array[Char], chunkSize: Int): Boolean = {
require(chunkSize > 0, "chunkSize must be greater than 0")
def traverse(from: Int, until: Int): (Int, Int) = {
var count = 0
var stack = 0
var nest = 0
for (n <- from until until) {
val cur = chars(c)
if (cur == '(') {
count += 1
stack += 1
}
else if (cur == ')') {
count -= 1
if (stack > 0) stack -= 1
else nest -= 1
}
}
(nest, count)
}
def reduce(from: Int, until: Int): (Int, Int) = {
val m = (until + from) / 2
if (until - from <= chunkSize) {
traverse(from, until)
} else {
parallel(reduce(from, m), reduce(m, until)) match {
case ((minNestL, totGainL), (minNestR, totGainR)) => {
((minNestL min (minNestR + totGainL)), (totGainL + totGainR))
}
}
}
}
reduce(0, chars.length) == (0,0)
}
Given a string, if we remove balanced parentheses, what's left will be in a form )))(((, give n for number of ) and m for number of (, then m >= 0, n <= 0(for easier calculation). Here n is minNest and m+n is totGain. To make a true balanced string, we need m+n == 0 && n == 0.
In a parallel operation, how to we derive those for node from it's left and right? For totGain we just needs to add them up. When calculating n for node, it can just be n(left) if n(right) not contribute or n(right) + left.totGain whichever is smaller.
I would like to generate a random string (or a series of random strings, repetitions allowed) of length between 1 and n characters from some (finite) alphabet. Each string should be equally likely (in other words, the strings should be uniformly distributed).
The uniformity requirement means that an algorithm like this doesn't work:
alphabet = "abcdefghijklmnopqrstuvwxyz"
len = rand(1, n)
s = ""
for(i = 0; i < len; ++i)
s = s + alphabet[rand(0, 25)]
(pseudo code, rand(a, b) returns a integer between a and b, inclusively, each integer equally likely)
This algorithm generates strings with uniformly distributed lengths, but the actual distribution should be weighted toward longer strings (there are 26 times as many strings with length 2 as there are with length 1, and so on.) How can I achieve this?
What you need to do is generate your length and then your string as two distinct steps. You will need to first chose the length using a weighted approach. You can calculate the number of strings of a given length l for an alphabet of k symbols as k^l. Sum those up and then you have the total number of strings of any length, your first step is to generate a random number between 1 and that value and then bin it accordingly. Modulo off by one errors you would break at 26, 26^2, 26^3, 26^4 and so on. The logarithm based on the number of symbols would be useful for this task.
Once you have you length then you can generate the string as you have above.
Okay, there are 26 possibilities for a 1-character string, 262 for a 2-character string, and so on up to 2626 possibilities for a 26-character string.
That means there are 26 times as many possibilities for an (N)-character string than there are for an (N-1)-character string. You can use that fact to select your length:
def getlen(maxlen):
sz = maxlen
while sz != 1:
if rnd(27) != 1:
return sz
sz--;
return 1
I use 27 in the above code since the total sample space for selecting strings from "ab" is the 26 1-character possibilities and the 262 2-character possibilities. In other words, the ratio is 1:26 so 1-character has a probability of 1/27 (rather than 1/26 as I first answered).
This solution isn't perfect since you're calling rnd multiple times and it would be better to call it once with an possible range of 26N+26N-1+261 and select the length based on where your returned number falls within there but it may be difficult to find a random number generator that'll work on numbers that large (10 characters gives you a possible range of 2610+...+261 which, unless I've done the math wrong, is 146,813,779,479,510).
If you can limit the maximum size so that your rnd function will work in the range, something like this should be workable:
def getlen(chars,maxlen):
assert maxlen >= 1
range = chars
sampspace = 0
for i in 1 .. maxlen:
sampspace = sampspace + range
range = range * chars
range = range / chars
val = rnd(sampspace)
sz = maxlen
while val < sampspace - range:
sampspace = sampspace - range
range = range / chars
sz = sz - 1
return sz
Once you have the length, I would then use your current algorithm to choose the actual characters to populate the string.
Explaining it further:
Let's say our alphabet only consists of "ab". The possible sets up to length 3 are [ab] (2), [ab][ab] (4) and [ab][ab][ab] (8). So there is a 8/14 chance of getting a length of 3, 4/14 of length 2 and 2/14 of length 1.
The 14 is the magic figure: it's the sum of all 2n for n = 1 to the maximum length. So, testing that pseudo-code above with chars = 2 and maxlen = 3:
assert maxlen >= 1 [okay]
range = chars [2]
sampspace = 0
for i in 1 .. 3:
i = 1:
sampspace = sampspace + range [0 + 2 = 2]
range = range * chars [2 * 2 = 4]
i = 2:
sampspace = sampspace + range [2 + 4 = 6]
range = range * chars [4 * 2 = 8]
i = 3:
sampspace = sampspace + range [6 + 8 = 14]
range = range * chars [8 * 2 = 16]
range = range / chars [16 / 2 = 8]
val = rnd(sampspace) [number from 0 to 13 inclusive]
sz = maxlen [3]
while val < sampspace - range: [see below]
sampspace = sampspace - range
range = range / chars
sz = sz - 1
return sz
So, from that code, the first iteration of the final loop will exit with sz = 3 if val is greater than or equal to sampspace - range [14 - 8 = 6]. In other words, for the values 6 through 13 inclusive, 8 of the 14 possibilities.
Otherwise, sampspace becomes sampspace - range [14 - 8 = 6] and range becomes range / chars [8 / 2 = 4].
Then the second iteration of the final loop will exit with sz = 2 if val is greater than or equal to sampspace - range [6 - 4 = 2]. In other words, for the values 2 through 5 inclusive, 4 of the 14 possibilities.
Otherwise, sampspace becomes sampspace - range [6 - 4 = 2] and range becomes range / chars [4 / 2 = 2].
Then the third iteration of the final loop will exit with sz = 1 if val is greater than or equal to sampspace - range [2 - 2 = 0]. In other words, for the values 0 through 1 inclusive, 2 of the 14 possibilities (this iteration will always exit since the value must be greater than or equal to zero.
In retrospect, that second solution is a bit of a nightmare. In my personal opinion, I'd go for the first solution for its simplicity and to avoid the possibility of rather large numbers.
Building on my comment posted as a reply to the OP:
I'd consider it an exercise in base
conversion. You're simply generating a
"random number" in "base 26", where
a=0 and z=25. For a random string of
length n, generate a number between 1
and 26^n. Convert from base 10 to base
26, using symbols from your chosen
alphabet.
Here's a PHP implementation. I won't guaranty that there isn't an off-by-one error or two in here, but any such error should be minor:
<?php
$n = 5;
var_dump(randstr($n));
function randstr($maxlen) {
$dict = 'abcdefghijklmnopqrstuvwxyz';
$rand = rand(0, pow(strlen($dict), $maxlen));
$str = base_convert($rand, 10, 26);
//base convert returns base 26 using 0-9 and 15 letters a-p(?)
//we must convert those to our own set of symbols
return strtr($str, '1234567890abcdefghijklmnopqrstuvwxyz', $dict);
}
Instead of picking a length with uniform distribution, weight it according to how many strings are a given length. If your alphabet is size m, there are mx strings of size x, and (1-mn+1)/(1-m) strings of length n or less. The probability of choosing a string of length x should be mx*(1-m)/(1-mn+1).
Edit:
Regarding overflow - using floating point instead of integers will expand the range, so for a 26-character alphabet and single-precision floats, direct weight calculation shouldn't overflow for n<26.
A more robust approach is to deal with it iteratively. This should also minimize the effects of underflow:
int randomLength() {
for(int i = n; i > 0; i--) {
double d = Math.random();
if(d > (m - 1) / (m - Math.pow(m, -i))) {
return i;
}
}
return 0;
}
To make this more efficient by calculating fewer random numbers, we can reuse them by splitting intervals in more than one place:
int randomLength() {
for(int i = n; i > 0; i -= 5) {
double d = Math.random();
double c = (m - 1) / (m - Math.pow(m, -i))
for(int j = 0; j < 5; j++) {
if(d > c) {
return i - j;
}
c /= m;
}
}
for(int i = n % 0; i > 0; i--) {
double d = Math.random();
if(d > (m - 1) / (m - Math.pow(m, -i))) {
return i;
}
}
return 0;
}
Edit: This answer isn't quite right. See the bottom for a disproof. I'll leave it up for now in the hope someone can come up with a variant that fixes it.
It's possible to do this without calculating the length separately - which, as others have pointed out, requires raising a number to a large power, and generally seems like a messy solution to me.
Proving that this is correct is a little tough, and I'm not sure I trust my expository powers to make it clear, but bear with me. For the purposes of the explanation, we're generating strings of length at most n from an alphabet a of |a| characters.
First, imagine you have a maximum length of n, and you've already decided you're generating a string of at least length n-1. It should be obvious that there are |a|+1 equally likely possibilities: we can generate any of the |a| characters from the alphabet, or we can choose to terminate with n-1 characters. To decide, we simply pick a random number x between 0 and |a| (inclusive); if x is |a|, we terminate at n-1 characters; otherwise, we append the xth character of a to the string. Here's a simple implementation of this procedure in Python:
def pick_character(alphabet):
x = random.randrange(len(alphabet) + 1)
if x == len(alphabet):
return ''
else:
return alphabet[x]
Now, we can apply this recursively. To generate the kth character of the string, we first attempt to generate the characters after k. If our recursive invocation returns anything, then we know the string should be at least length k, and we generate a character of our own from the alphabet and return it. If, however, the recursive invocation returns nothing, we know the string is no longer than k, and we use the above routine to select either the final character or no character. Here's an implementation of this in Python:
def uniform_random_string(alphabet, max_len):
if max_len == 1:
return pick_character(alphabet)
suffix = uniform_random_string(alphabet, max_len - 1)
if suffix:
# String contains characters after ours
return random.choice(alphabet) + suffix
else:
# String contains no characters after our own
return pick_character(alphabet)
If you doubt the uniformity of this function, you can attempt to disprove it: suggest a string for which there are two distinct ways to generate it, or none. If there are no such strings - and alas, I do not have a robust proof of this fact, though I'm fairly certain it's true - and given that the individual selections are uniform, then the result must also select any string with uniform probability.
As promised, and unlike every other solution posted thus far, no raising of numbers to large powers is required; no arbitrary length integers or floating point numbers are needed to store the result, and the validity, at least to my eyes, is fairly easy to demonstrate. It's also shorter than any fully-specified solution thus far. ;)
If anyone wants to chip in with a robust proof of the function's uniformity, I'd be extremely grateful.
Edit: Disproof, provided by a friend:
dato: so imagine alphabet = 'abc' and n = 2
dato: you have 9 strings of length 2, 3 of length 1, 1 of length 0
dato: that's 13 in total
dato: so probability of getting a length 2 string should be 9/13
dato: and probability of getting a length 1 or a length 0 should be 4/13
dato: now if you call uniform_random_string('abc', 2)
dato: that transforms itself into a call to uniform_random_string('abc', 1)
dato: which is an uniform distribution over ['a', 'b', 'c', '']
dato: the first three of those yield all the 2 length strings
dato: and the latter produce all the 1 length strings and the empty strings
dato: but 0.75 > 9/13
dato: and 0.25 < 4/13
// Note space as an available char
alphabet = "abcdefghijklmnopqrstuvwxyz "
result_string = ""
for( ;; )
{
s = ""
for( i = 0; i < n; i++ )
s += alphabet[rand(0, 26)]
first_space = n;
for( i = 0; i < n; i++ )
if( s[ i ] == ' ' )
{
first_space = i;
break;
}
ok = true;
// Reject "duplicate" shorter strings
for( i = first_space + 1; i < n; i++ )
if( s[ i ] != ' ' )
{
ok = false;
break;
}
if( !ok )
continue;
// Extract the short version of the string
for( i = 0; i < first_space; i++ )
result_string += s[ i ];
break;
}
Edit: I forgot to disallow 0-length strings, that will take a bit more code which I don't have time to add now.
Edit: After considering how my answer doesn't scale to large n (takes too long to get lucky and find an accepted string), I like paxdiablo's answer much better. Less code too.
Personally I'd do it like this:
Let's say your alphabet has Z characters. Then the number of possible strings for each length L is:
L | Z
--------------------------
1 | 26
2 | 676 (= 26 * 26)
3 | 17576 (= 26 * 26 * 26)
...and so on.
Now let's say your maximum desired length is N. Then the total number of possible strings from length 1 to N that your function could generate would be the sum of a geometric sequence:
(1 - (Z ^ (N + 1))) / (1 - Z)
Let's call this value S. Then the probability of generating a string of any length L should be:
(Z ^ L) / S
OK, fine. This is all well and good; but how do we generate a random number given a non-uniform probability distribution?
The short answer is: you don't. Get a library to do that for you. I develop mainly in .NET, so one I might turn to would be Math.NET.
That said, it's really not so hard to come up with a rudimentary approach to doing this on your own.
Here's one way: take a generator that gives you a random value within a known uniform distribution, and assign ranges within that distribution of sizes dependent on your desired distribution. Then interpret the random value provided by the generator by determining which range it falls into.
Here's an example in C# of one way you could implement this idea (scroll to the bottom for example output):
RandomStringGenerator class
public class RandomStringGenerator
{
private readonly Random _random;
private readonly char[] _alphabet;
public RandomStringGenerator(string alphabet)
{
if (string.IsNullOrEmpty(alphabet))
throw new ArgumentException("alphabet");
_random = new Random();
_alphabet = alphabet.Distinct().ToArray();
}
public string NextString(int maxLength)
{
// Get a value randomly distributed between 0.0 and 1.0 --
// this is approximately what the System.Random class provides.
double value = _random.NextDouble();
// This is where the magic happens: we "translate" the above number
// to a length based on our computed probability distribution for the given
// alphabet and the desired maximum string length.
int length = GetLengthFromRandomValue(value, _alphabet.Length, maxLength);
// The rest is easy: allocate a char array of the length determined above...
char[] chars = new char[length];
// ...populate it with a bunch of random values from the alphabet...
for (int i = 0; i < length; ++i)
{
chars[i] = _alphabet[_random.Next(0, _alphabet.Length)];
}
// ...and return a newly constructed string.
return new string(chars);
}
static int GetLengthFromRandomValue(double value, int alphabetSize, int maxLength)
{
// Looping really might not be the smartest way to do this,
// but it's the most obvious way that immediately springs to my mind.
for (int length = 1; length <= maxLength; ++length)
{
Range r = GetRangeForLength(length, alphabetSize, maxLength);
if (r.Contains(value))
return length;
}
return maxLength;
}
static Range GetRangeForLength(int length, int alphabetSize, int maxLength)
{
int L = length;
int Z = alphabetSize;
int N = maxLength;
double possibleStrings = (1 - (Math.Pow(Z, N + 1)) / (1 - Z));
double stringsOfGivenLength = Math.Pow(Z, L);
double possibleSmallerStrings = (1 - Math.Pow(Z, L)) / (1 - Z);
double probabilityOfGivenLength = ((double)stringsOfGivenLength / possibleStrings);
double probabilityOfShorterLength = ((double)possibleSmallerStrings / possibleStrings);
double startPoint = probabilityOfShorterLength;
double endPoint = probabilityOfShorterLength + probabilityOfGivenLength;
return new Range(startPoint, endPoint);
}
}
Range struct
public struct Range
{
public readonly double StartPoint;
public readonly double EndPoint;
public Range(double startPoint, double endPoint)
: this()
{
this.StartPoint = startPoint;
this.EndPoint = endPoint;
}
public bool Contains(double value)
{
return this.StartPoint <= value && value <= this.EndPoint;
}
}
Test
static void Main(string[] args)
{
const int N = 5;
const string alphabet = "acegikmoqstvwy";
int Z = alphabet.Length;
var rand = new RandomStringGenerator(alphabet);
var strings = new List<string>();
for (int i = 0; i < 100000; ++i)
{
strings.Add(rand.NextString(N));
}
Console.WriteLine("First 10 results:");
for (int i = 0; i < 10; ++i)
{
Console.WriteLine(strings[i]);
}
// sanity check
double sumOfProbabilities = 0.0;
for (int i = 1; i <= N; ++i)
{
double probability = Math.Pow(Z, i) / ((1 - (Math.Pow(Z, N + 1))) / (1 - Z));
int numStrings = strings.Count(str => str.Length == i);
Console.WriteLine("# strings of length {0}: {1} (probability = {2:0.00%})", i, numStrings, probability);
sumOfProbabilities += probability;
}
Console.WriteLine("Probabilities sum to {0:0.00%}.", sumOfProbabilities);
Console.ReadLine();
}
Output:
First 10 results:
wmkyw
qqowc
ackai
tokmo
eeiyw
cakgg
vceec
qwqyq
aiomt
qkyav
# strings of length 1: 1 (probability = 0.00%)
# strings of length 2: 38 (probability = 0.03%)
# strings of length 3: 475 (probability = 0.47%)
# strings of length 4: 6633 (probability = 6.63%)
# strings of length 5: 92853 (probability = 92.86%)
Probabilities sum to 100.00%.
My idea regarding this is like:
you have 1-n length string.there 26 possible 1 length string,26*26 2 length string and so on.
you can find out the percentage of each length string of the total possible strings.for example percentage of single length string is like
((26/(TOTAL_POSSIBLE_STRINGS_OF_ALL_LENGTH))*100).
similarly you can find out the percentage of other length strings.
Mark them on a number line between 1 to 100.ie suppose percentage of single length string is 3 and double length string is 6 then number line single length string lies between 0-3 while double length string lies between 3-9 and so on.
Now take a random number between 1 to 100.find out the range in which this number lies.I mean suppose for examplethe number you have randomly chosen is 2.Now this number lies between 0-3 so go 1 length string or if the random number chosen is 7 then go for double length string.
In this fashion you can see that length of each string choosen will be proportional to the percentage of the total number of that length string contribute to the all possible strings.
Hope I am clear.
Disclaimer: I have not gone through above solution except one or two.So if it matches with some one solution it will be purely a chance.
Also,I will welcome all the advice and positive criticism and correct me if I am wrong.
Thanks and regard
Mawia
Matthieu: Your idea doesn't work because strings with blanks are still more likely to be generated. In your case, with n=4, you could have the string 'ab' generated as 'a' + 'b' + '' + '' or '' + 'a' + 'b' + '', or other combinations. Thus not all the strings have the same chance of appearing.