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ok I am lost right now by this assignment and just need some help.
The assignment is Design a program that generates the sum of numbers.
Given a number (user input) you need an application that will produce a sum of the numbers from 1 to that given number I just need some help to start because I am just having to hard of a time and i know it might seem easy but never had any experience to any of this at all.
var input = getUserInput;
var sum;
while (input > 0)
{
sum = sum + input--;
}
print sum;
You can start with something as straightforward as this:
input = getuserInput()
count = 0
sum = 0
while count < input:
count = count + 1
sum = sum + count
return sum
...then enhance it.
INPUT number
VARIABLE sum = 0
FOR VARIABLE n = 1 TO number WITH STEP 1 DO
sum += n
END FOR
PRINT sum
Translated to lua it would look like this:
number = tonumber( io.read() )
sum = 0
for n = 1, number, 1 do
sum = sum + n
end
print(sum)
Translated into python it would look like
Number = int(input("Number:"))
Sum = 0
for n in range(1,Number+1):
Sum += n
print(Sum)
Though the pythonic way would resemble:
number = int(input("Number:"))
print(sum(range(number+1)))
When applying this to any language look out for the following:
Converting the user's input to an integer, by default it will normally be a string i.e "...".
Declare a variable to hold the total (in our case sum) before you try to add a number to it i.e n.
Make sure your for loop goes from 1 to number
Actually, this question can be generalized as below:
Find all possible combinations from a given set of elements, which meets
a certain criteria.
So, any good algorithms?
There are only 16 possibilities (and one of those is to add together "none of them", which ain't gonna give you 24), so the old-fashioned "brute force" algorithm looks pretty good to me:
for (unsigned int choice = 1; choice < 16; ++choice) {
int sum = 0;
if (choice & 1) sum += elements[0];
if (choice & 2) sum += elements[1];
if (choice & 4) sum += elements[2];
if (choice & 8) sum += elements[3];
if (sum == 24) {
// we have a winner
}
}
In the completely general form of your problem, the only way to tell whether a combination meets "certain criteria" is to evaluate those criteria for every single combination. Given more information about the criteria, maybe you could work out some ways to avoid testing every combination and build an algorithm accordingly, but not without those details. So again, brute force is king.
There are two interesting explanations about the sum problem, both in Wikipedia and MathWorld.
In the case of the first question you asked, the first answer is good for a limited number of elements. You should realize that the reason Mr. Jessop used 16 as the boundary for his loop is because this is 2^4, where 4 is the number of elements in your set. If you had 100 elements, the loop limit would become 2^100 and your algorithm would literally take forever to finish.
In the case of a bounded sum, you should consider a depth first search, because when the sum of elements exceeds the sum you are looking for, you can prune your branch and backtrack.
In the case of the generic question, finding the subset of elements that satisfy certain criteria, this is known as the Knapsack problem, which is known to be NP-Complete. Given that, there is no algorithm that will solve it in less than exponential time.
Nevertheless, there are several heuristics that bring good results to the table, including (but not limited to) genetic algorithms (one I personally like, for I wrote a book on them) and dynamic programming. A simple search in Google will show many scientific papers that describe different solutions for this problem.
Find all possible combinations from a given set of elements, which
meets a certain criteria
If i understood you right, this code will helpful for you:
>>> from itertools import combinations as combi
>>> combi.__doc__
'combinations(iterable, r) --> combinations object\n\nReturn successive r-length
combinations of elements in the iterable.\n\ncombinations(range(4), 3) --> (0,1
,2), (0,1,3), (0,2,3), (1,2,3)'
>>> set = range(4)
>>> set
[0, 1, 2, 3]
>>> criteria = range(3)
>>> criteria
[0, 1, 2]
>>> for tuple in list(combi(set, len(criteria))):
... if cmp(list(tuple), criteria) == 0:
... print 'criteria exists in tuple: ', tuple
...
criteria exists in tuple: (0, 1, 2)
>>> list(combi(set, len(criteria)))
[(0, 1, 2), (0, 1, 3), (0, 2, 3), (1, 2, 3)]
Generally for a problem as this you have to try all posebilities, the thing you should do have the code abort the building of combiantion if you know it will not satesfie the criteria (if you criteria is that you do not have more then two blue balls, then you have to abort calculation that has more then two). Backtracing
def perm(set,permutation):
if lenght(set) == lenght(permutation):
print permutation
else:
for element in set:
if permutation.add(element) == criteria:
perm(sett,permutation)
else:
permutation.pop() //remove the element added in the if
The set of input numbers matters, as you can tell as soon as you allow e.g. negative numbers, imaginary numbers, rational numbers etc in your start set. You could also restrict to e.g. all even numbers, all odd number inputs etc.
That means that it's hard to build something deductive. You need brute force, a.k.a. try every combination etc.
In this particular problem you could build an algoritm that recurses - e.g. find every combination of 3 Int ( 1,22) that add up to 23, then add 1, every combination that add to 22 and add 2 etc. Which can again be broken into every combination of 2 that add up to 21 etc. You need to decide if you can count same number twice.
Once you have that you have a recursive function to call -
combinations( 24 , 4 ) = combinations( 23, 3 ) + combinations( 22, 3 ) + ... combinations( 4, 3 );
combinations( 23 , 3 ) = combinations( 22, 2 ) + ... combinations( 3, 2 );
etc
This works well except you have to be careful around repeating numbers in the recursion.
private int[][] work()
{
const int target = 24;
List<int[]> combos = new List<int[]>();
for(int i = 0; i < 9; i++)
for(int x = 0; x < 9; x++)
for(int y = 0; y < 9; y++)
for (int z = 0; z < 9; z++)
{
int res = x + y + z + i;
if (res == target)
{
combos.Add(new int[] { x, y, z, i });
}
}
return combos.ToArray();
}
It works instantly, but there probably are better methods rather than 'guess and check'. All I am doing is looping through every possibility, adding them all together, and seeing if it comes out to the target value.
If i understand your question correctly, what you are asking for is called "Permutations" or the number (N) of possible ways to arrange (X) numbers taken from a set of (Y) numbers.
N = Y! / (Y - X)!
I don't know if this will help, but this is a solution I came up with for an assignment on permutations.
You have an input of : 123 (string) using the substr functions
1) put each number of the input into an array
array[N1,N2,N3,...]
2)Create a swap function
function swap(Number A, Number B)
{
temp = Number B
Number B = Number A
Number A = temp
}
3)This algorithm uses the swap function to move the numbers around until all permutations are done.
original_string= '123'
temp_string=''
While( temp_string != original_string)
{
swap(array element[i], array element[i+1])
if (i == 1)
i == 0
temp_string = array.toString
i++
}
Hopefully you can follow my pseudo code, but this works at least for 3 digit permutations
(n X n )
built up a square matrix of nxn
and print all together its corresponding crossed values
e.g.
1 2 3 4
1 11 12 13 14
2 .. .. .. ..
3 ..
4 .. ..
I've been learning Ruby, so I thought I'd try my hand at some of the project Euler puzzles. Embarrassingly, I only made it to problem 4...
Problem 4 goes as follows:
A palindromic number reads the same
both ways. The largest palindrome made
from the product of two 2-digit
numbers is 9009 = 91 × 99.
Find the largest palindrome made from
the product of two 3-digit numbers.
So I figured I would loop down from 999 to 100 in a nested for loop and do a test for the palindrome and then break out of the loops when I found the first one (which should be the largest one):
final=nil
range = 100...1000
for a in range.to_a.reverse do
for b in range.to_a.reverse do
c=a*b
final=c if c.to_s == c.to_s.reverse
break if !final.nil?
end
break if !final.nil?
end
puts final
This does output a palindrome 580085, but apparently this isn't the highest product of two three-digit numbers within the range. Strangely, the same code succeeds to return 9009, like in the example, if I change the range to 10...100.
Can someone tell me where I am going
wrong?
Also, is there a nicer way to
break out of the internal loop?
Thanks
You are testing 999* (999...100), then 998 * (999...100)
Hence you will be testing 999 * 500 before you test 997 * 996.
So, how you we find that right number?
First note the multiplication is reflective, a * b == b * a, so b need not go from 999...0 every time, just a ...0.
When you find a palindrone, add the two factors together and save the sum (save the two factors also)
Inside the loop, if (a+b) is ever less than the saved sum, abandon the inner loop and move to the next a. When a falls below sum/2, no future value you could find would be higher than the one you've already found, so you're done.
The problem is that you might find a palindrome for an a of 999 and a b of 200, but you break too soon, so you never see that there is one for 998*997 (just example numbers).
You need to either look for all palindromes or once you find the first one, set that b as your minimum bound and continue looking through the a loop.
Regarding the second question, my advice is to approach the problem in more functional, than procedural manner. So, rather than looping, you may try to "describe" your problem functionally, and let Ruby does the work:
From all the pairs of 3-digit numbers,
select only those whose product is a palindrome,
and find the one with the largest product
Although this approach may not yield the most efficient of the solutions, it may teach you couple of Ruby idioms.
Consider the digits of P – let them be x, y and z. P must be at least 6 digits long since the palindrome 111111 = 143×777 – the product of two 3-digit integers. Since P is palindromic:
P=100000x + 10000y + 1000z + 100z + 10y + x
P=100001x + 10010y + 1100z
P=11(9091x + 910y + 100z)
Since 11 is prime, at least one of the integers a or b must have a factor of 11. So if a is not divisible by 11 then we know b must be. Using this information we can determine what values of b we check depending on a.
C# Implementation :
using System;
namespace HighestPalindrome
{
class Program
{
static void Main(string[] args)
{
int i, j;
int m = 1;
bool flag = false;
while (true)
{
if (flag) j = m + 1;
else j = m;
for (i = m; i > 0; i--)
{
Console.WriteLine("{0} * {1} = {2}", 1000 - i, 1000 - j, (1000 - i) * (1000 - j));
j++;
//--- Palindrome Check ------------------------------
int number, temp, remainder, sum = 0;
number = temp = (1000 - i) * (1000 - j);
while (number > 0)
{
remainder = number % 10;
number /= 10;
sum = sum * 10 + remainder;
}
if (sum == temp)
{
Console.WriteLine("Highest Palindrome Number is - {0} * {1} = {2}", 1000 - i, 1000 - j, temp);
Console.ReadKey();
return;
}
//---------------------------------------------------
}
if (flag)
m++;
flag = !flag;
}
}
}
}
The mistake is you assume that if you find palindrom with greatest a value it will give the greatest product it isn't true. Solution is to keep max_product value and update it against solution you find.
I can answer your first question: You need to find the highest product, not the product containing the highest factor. In other words a * b could be greater than c * d even if c > a > b.
You're breaking on the first palindrome you come to, not necessarily the biggest.
Say you have A,B,C,D,E. You test E * A before you test D * C.
The main thing is to go through all the possible values. Don't try to break when you find the first answer just start with a best answer of zero then try all combinations and keep updating best. The secondary thing is to try to reduce the set of "all combinations".
One thing you can do is limit your inner loop to values less than or equal to a (since ab == ba). This puts the larger value of your equation always in a and substantially reduces the number of values you have to test.
for a in range.to_a.reverse do
for b in (100..a).to_a.reverse do
The next thing you can do is break out of the inner loop whenever the product is less than the current best value.
c = a*b
next if c < best
Next, if you're going to go through them all anyway there's no benefit to going through them in reverse. By starting at the top of the range it takes a while before you find a palindromic number and as a result it takes a while to reduce your search set. If you start at the bottom you begin to increase the lower bound quickly.
for a in range.to_a do
for b in (100..a).to_a do
My tests show that either way you try some 405K pairs however. So how about thinking of the problem a different way. What is the largest possible product of two 3 digit numbers? 999 * 999 = 998001 and the smallest is 100*100 = 10000. How about we take the idea you had of breaking on the first answer but apply it to a different range, that being 998001 to 10000 (or 999*999 to 100*100).
for c in (10000...998001).to_a.reverse do
We get to a palindrome after only 202 tests... the problem is it isn't a product of two 3-digit numbers. So now we have to check whether the palindrome we've found is a product of 2 3-digit numbers. As soon as we find a value in the range that is a palindrome and a product of two 3-digit numbers we're done. My tests show we find the highest palindrome that meets the requirement after less than 93K tests. But since we have the overhead of checking that all palindromes to that point were products of two 3-digit numbers it may not be more efficient than the previous solution.
So lets go back to the original improvement.
for a in range.to_a.reverse do
for b in (100..a).to_a.reverse do
We're looping rows then columns and trying to be efficient by detecting a point where we can go to the next row because any additional trys on the current row could not possibly be better than our current best. What if, instead of going down the rows, we go across the diagonals?
Since the products get smaller diagonal by diagonal you can stop as soon as you find a palindome number. This is a really efficient solution but with a more complex implementation. It turns out this method finds the highest palindrome after slightly more than 2200 trys.
ar=[]
limit = 100..999
for a in limit.to_a.reverse do
for b in (100..a).to_a.reverse do
c=a*b
if c.to_s == c.to_s.reverse
palndrm=c
ar << palndrm
end
end
end
print ar
print"\n"
puts ar.max
puts ar.min
an implementation:
max = 100.upto(999).inject([-1,0,0]) do |m, a|
a.upto(999) do |b|
prod = a * b
m = [prod, a, b] if prod.to_s == prod.to_s.reverse and prod > m[0]
end
m
end
puts "%d = %d * %d" % max
prints 906609 = 913 * 993
Here's what I came up with in Ruby:
def largest_palindrome_product(digits)
largest, upper, lower = 0, 10**digits - 1, 10**(digits - 1)
for i in upper.downto(lower) do
for j in i.downto(lower) do
product = i * j
largest = product if product > largest && palindrome?(product)
end
end
largest
end
And here's the function to check if the number is a palindrome:
def palindrome?(input)
chars = input.to_s.chars
for i in 0..(chars.size - 1) do
return false if chars[i] != chars[chars.size - i - 1]
end
true
end
I guess there's probably a more efficient solution out there, though.
For this problem, as we are looking for the highest palindrom, i assumed it would start with a 9. Thus ending with a 9 (palindrom).
if you pay attention, to get a number finishing by 9, you can only get it with numbers finishing by 9 and 1, 3 and 3, 7 and 7.
Then it is useless to check the other values (for instance 999*998 as it will not end with a 9).
Starting from 999 and 991, you can then substract 10 to 991, trying 999 and 981 etc...
You do the same with 993 and 993 ... 993 * 983
same with 997 * 997 then 997 * 987 etc
You don't need to go further than 900 or 10^4 - 10^3 as you can be sure the highest will be before.
int PB4_firstTry(int size)
{
int nb1 = (int)pow(10.0,size+1.0) - 1, nb2 = (int)pow(10.0,size+1.0) - 1;
int pal91 = getFirstPalindrome(size,9,1);
int pal33 = getFirstPalindrome(size,3,3);
int pal77 = getFirstPalindrome(size,7,7);
int bigger1 = (pal91 > pal33) ? pal91 : pal33;
return (bigger1 > pal77) ? bigger1 : pal77;
}
int getFirstPalindrome(int size,int ending1,int ending2)
{
int st1 = (int)pow(10.0,size+1.0) - 10 + ending1;
int comp = st1 - pow(10.0,size);
int st2 = (int)pow(10.0,size+1.0) - 10 + ending2;
int answer = -1;
while (st1 > comp)
{
for (int i = st2; i > comp && st1*i > answer; i-=10)
{
if (PB4_isPalindrome(st1*i))
answer = st1*i;
}
st1 -= 10;
}
return answer;
}
bool PB4_isPalindrome(int number)
{
std::string str = intToString(number);
for (int i = 0; i < (int)(str.length() / 2); i++)
{
if (str[i] != str[str.length() - 1 - i])
return false;
}
return true;
}
std::string intToString(int number)
{
std::ostringstream convert;
convert << number;
return convert.str();
}
Of course, this works for 4 size digits factors etc.
I'm trying to figure out a way to create random numbers that "feel" random over short sequences. This is for a quiz game, where there are four possible choices, and the software needs to pick one of the four spots in which to put the correct answer before filling in the other three with distractors.
Obviously, arc4random % 4 will create more than sufficiently random results over a long sequence, but in a short sequence its entirely possible (and a frequent occurrence!) to have five or six of the same number come back in a row. This is what I'm aiming to avoid.
I also don't want to simply say "never pick the same square twice," because that results in only three possible answers for every question but the first. Currently I'm doing something like this:
bool acceptable = NO;
do {
currentAnswer = arc4random() % 4;
if (currentAnswer == lastAnswer) {
if (arc4random() % 4 == 0) {
acceptable = YES;
}
} else {
acceptable = YES;
}
} while (!acceptable);
Is there a better solution to this that I'm overlooking?
If your question was how to compute currentAnswer using your example's probabilities non-iteratively, Guffa has your answer.
If the question is how to avoid random-clustering without violating equiprobability and you know the upper bound of the length of the list, then consider the following algorithm which is kind of like un-sorting:
from random import randrange
# randrange(a, b) yields a <= N < b
def decluster():
for i in range(seq_len):
j = (i + 1) % seq_len
if seq[i] == seq[j]:
i_swap = randrange(i, seq_len) # is best lower bound 0, i, j?
if seq[j] != seq[i_swap]:
print 'swap', j, i_swap, (seq[j], seq[i_swap])
seq[j], seq[i_swap] = seq[i_swap], seq[j]
seq_len = 20
seq = [randrange(1, 5) for _ in range(seq_len)]; print seq
decluster(); print seq
decluster(); print seq
where any relation to actual working Python code is purely coincidental. I'm pretty sure the prior-probabilities are maintained, and it does seem break clusters (and occasionally adds some). But I'm pretty sleepy so this is for amusement purposes only.
You populate an array of outcomes, then shuffle it, then assign them in that order.
So for just 8 questions:
answer_slots = [0,0,1,1,2,2,3,3]
shuffle(answer_slots)
print answer_slots
[1,3,2,1,0,2,3,0]
To reduce the probability for a repeated number by 25%, you can pick a random number between 0 and 3.75, and then rotate it so that the 0.75 ends up at the previous answer.
To avoid using floating point values, you can multiply the factors by four:
Pseudo code (where / is an integer division):
currentAnswer = ((random(0..14) + lastAnswer * 4) % 16) / 4
Set up a weighted array. Lets say the last value was a 2. Make an array like this:
array = [0,0,0,0,1,1,1,1,2,3,3,3,3];
Then pick a number in the array.
newValue = array[arc4random() % 13];
Now switch to using math instead of an array.
newValue = ( ( ( arc4random() % 13 ) / 4 ) + 1 + oldValue ) % 4;
For P possibilities and a weight 0<W<=1 use:
newValue = ( ( ( arc4random() % (P/W-P(1-W)) ) * W ) + 1 + oldValue ) % P;
For P=4 and W=1/4, (P/W-P(1-W)) = 13. This says the last value will be 1/4 as likely as other values.
If you completely eliminate the most recent answer it will be just as noticeable as the most recent answer showing up too often. I do not know what weight will feel right to you, but 1/4 is a good starting point.
I'm trying to write a piece of code that will do the following:
Take the numbers 0 to 9 and assign one or more letters to this number. For example:
0 = N,
1 = L,
2 = T,
3 = D,
4 = R,
5 = V or F,
6 = B or P,
7 = Z,
8 = H or CH or J,
9 = G
When I have a code like 0123, it's an easy job to encode it. It will obviously make up the code NLTD. When a number like 5,6 or 8 is introduced, things get different. A number like 051 would result in more than one possibility:
NVL and NFL
It should be obvious that this gets even "worse" with longer numbers that include several digits like 5,6 or 8.
Being pretty bad at mathematics, I have not yet been able to come up with a decent solution that will allow me to feed the program a bunch of numbers and have it spit out all the possible letter combinations. So I'd love some help with it, 'cause I can't seem to figure it out. Dug up some information about permutations and combinations, but no luck.
Thanks for any suggestions/clues. The language I need to write the code in is PHP, but any general hints would be highly appreciated.
Update:
Some more background: (and thanks a lot for the quick responses!)
The idea behind my question is to build a script that will help people to easily convert numbers they want to remember to words that are far more easily remembered. This is sometimes referred to as "pseudo-numerology".
I want the script to give me all the possible combinations that are then held against a database of stripped words. These stripped words just come from a dictionary and have all the letters I mentioned in my question stripped out of them. That way, the number to be encoded can usually easily be related to a one or more database records. And when that happens, you end up with a list of words that you can use to remember the number you wanted to remember.
It can be done easily recursively.
The idea is that to handle the whole code of size n, you must handle first the n - 1 digits.
Once you have all answers for n-1 digits, the answers for the whole are deduced by appending to them the correct(s) char(s) for the last one.
There's actually a much better solution than enumerating all the possible translations of a number and looking them up: Simply do the reverse computation on every word in your dictionary, and store the string of digits in another field. So if your mapping is:
0 = N,
1 = L,
2 = T,
3 = D,
4 = R,
5 = V or F,
6 = B or P,
7 = Z,
8 = H or CH or J,
9 = G
your reverse mapping is:
N = 0,
L = 1,
T = 2,
D = 3,
R = 4,
V = 5,
F = 5,
B = 6,
P = 6,
Z = 7,
H = 8,
J = 8,
G = 9
Note there's no mapping for 'ch', because the 'c' will be dropped, and the 'h' will be converted to 8 anyway.
Then, all you have to do is iterate through each letter in the dictionary word, output the appropriate digit if there's a match, and do nothing if there isn't.
Store all the generated digit strings as another field in the database. When you want to look something up, just perform a simple query for the number entered, instead of having to do tens (or hundreds, or thousands) of lookups of potential words.
The general structure you want to hold your number -> letter assignments is an array or arrays, similar to:
// 0 = N, 1 = L, 2 = T, 3 = D, 4 = R, 5 = V or F, 6 = B or P, 7 = Z,
// 8 = H or CH or J, 9 = G
$numberMap = new Array (
0 => new Array("N"),
1 => new Array("L"),
2 => new Array("T"),
3 => new Array("D"),
4 => new Array("R"),
5 => new Array("V", "F"),
6 => new Array("B", "P"),
7 => new Array("Z"),
8 => new Array("H", "CH", "J"),
9 => new Array("G"),
);
Then, a bit of recursive logic gives us a function similar to:
function GetEncoding($number) {
$ret = new Array();
for ($i = 0; $i < strlen($number); $i++) {
// We're just translating here, nothing special.
// $var + 0 is a cheap way of forcing a variable to be numeric
$ret[] = $numberMap[$number[$i]+0];
}
}
function PrintEncoding($enc, $string = "") {
// If we're at the end of the line, then print!
if (count($enc) === 0) {
print $string."\n";
return;
}
// Otherwise, soldier on through the possible values.
// Grab the next 'letter' and cycle through the possibilities for it.
foreach ($enc[0] as $letter) {
// And call this function again with it!
PrintEncoding(array_slice($enc, 1), $string.$letter);
}
}
Three cheers for recursion! This would be used via:
PrintEncoding(GetEncoding("052384"));
And if you really want it as an array, play with output buffering and explode using "\n" as your split string.
This kind of problem are usually resolved with recursion. In ruby, one (quick and dirty) solution would be
#values = Hash.new([])
#values["0"] = ["N"]
#values["1"] = ["L"]
#values["2"] = ["T"]
#values["3"] = ["D"]
#values["4"] = ["R"]
#values["5"] = ["V","F"]
#values["6"] = ["B","P"]
#values["7"] = ["Z"]
#values["8"] = ["H","CH","J"]
#values["9"] = ["G"]
def find_valid_combinations(buffer,number)
first_char = number.shift
#values[first_char].each do |key|
if(number.length == 0) then
puts buffer + key
else
find_valid_combinations(buffer + key,number.dup)
end
end
end
find_valid_combinations("",ARGV[0].split(""))
And if you run this from the command line you will get:
$ ruby r.rb 051
NVL
NFL
This is related to brute-force search and backtracking
Here is a recursive solution in Python.
#!/usr/bin/env/python
import sys
ENCODING = {'0':['N'],
'1':['L'],
'2':['T'],
'3':['D'],
'4':['R'],
'5':['V', 'F'],
'6':['B', 'P'],
'7':['Z'],
'8':['H', 'CH', 'J'],
'9':['G']
}
def decode(str):
if len(str) == 0:
return ''
elif len(str) == 1:
return ENCODING[str]
else:
result = []
for prefix in ENCODING[str[0]]:
result.extend([prefix + suffix for suffix in decode(str[1:])])
return result
if __name__ == '__main__':
print decode(sys.argv[1])
Example output:
$ ./demo 1
['L']
$ ./demo 051
['NVL', 'NFL']
$ ./demo 0518
['NVLH', 'NVLCH', 'NVLJ', 'NFLH', 'NFLCH', 'NFLJ']
Could you do the following:
Create a results array.
Create an item in the array with value ""
Loop through the numbers, say 051 analyzing each one individually.
Each time a 1 to 1 match between a number is found add the correct value to all items in the results array.
So "" becomes N.
Each time a 1 to many match is found, add new rows to the results array with one option, and update the existing results with the other option.
So N becomes NV and a new item is created NF
Then the last number is a 1 to 1 match so the items in the results array become
NVL and NFL
To produce the results loop through the results array, printing them, or whatever.
Let pn be a list of all possible letter combinations of a given number string s up to the nth digit.
Then, the following algorithm will generate pn+1:
digit = s[n+1];
foreach(letter l that digit maps to)
{
foreach(entry e in p(n))
{
newEntry = append l to e;
add newEntry to p(n+1);
}
}
The first iteration is somewhat of a special case, since p-1 is undefined. You can simply initialize p0 as the list of all possible characters for the first character.
So, your 051 example:
Iteration 0:
p(0) = {N}
Iteration 1:
digit = 5
foreach({V, F})
{
foreach(p(0) = {N})
{
newEntry = N + V or N + F
p(1) = {NV, NF}
}
}
Iteration 2:
digit = 1
foreach({L})
{
foreach(p(1) = {NV, NF})
{
newEntry = NV + L or NF + L
p(2) = {NVL, NFL}
}
}
The form you want is probably something like:
function combinations( $str ){
$l = len( $str );
$results = array( );
if ($l == 0) { return $results; }
if ($l == 1)
{
foreach( $codes[ $str[0] ] as $code )
{
$results[] = $code;
}
return $results;
}
$cur = $str[0];
$combs = combinations( substr( $str, 1, $l ) );
foreach ($codes[ $cur ] as $code)
{
foreach ($combs as $comb)
{
$results[] = $code.$comb;
}
}
return $results;}
This is ugly, pidgin-php so please verify it first. The basic idea is to generate every combination of the string from [1..n] and then prepend to the front of all those combinations each possible code for str[0]. Bear in mind that in the worst case this will have performance exponential in the length of your string, because that much ambiguity is actually present in your coding scheme.
The trick is not only to generate all possible letter combinations that match a given number, but to select the letter sequence that is most easy to remember. A suggestion would be to run the soundex algorithm on each of the sequence and try to match against an English language dictionary such as Wordnet to find the most 'real-word-sounding' sequences.