I am going to store char's in some container, then take char's from a string and look up index for char from string in said container.
I also need to do the opposite, take an index and find out what char is there.
So it be more like:
container<char> c;
int index = c.indexOf('a');
char letter = c[12];
I don't care about insert or remove operations.
I suppose the best solution would be to just use a string or char table.
Then do:
int index = 'a'-myString[0]; //for lookup
char c = myString[index]; //for index
The generic data structure that has the ability to look up in two directions is the bidirectional map. If implemented with hash tables, it should have constant complexity for lookup.
Now, if we can make the assumption that char is 8 bits wide, and that your indices are contiguous, then we can use a greatly simpler data structure: Simply store the characters in an array. Use another array of size 1 << CHAR_BIT to store the index of each character.
I need suggestion to use STL containers in the best possible way to sort 3 sets of data
1. A ID (Integer)
2. First Value (String)
3. Second Value (String)
An example of the data structure is as below:
I want to use map as it is sorted at the time of insert and no need to execute a sorting algorithm separately. Since the ID can repeat it must be a multimap, and each data of a column is linked to each other so the rows will change in order to sort keeping the same values attached to a ID.
Sorting the ID and value is ok, but how do I sort 2 values as multimap can take only one value. From my thinking it will be multimap of a multimap or a struct of the data structure and then STL containers. But I want to make it as simple as possible. I need suggestion on how this can be achieved.
Thanks!
Having a map or a set makes sense if and only if you are going to do many insert/erase operations it. If the data structure is static, storing a vector and sorting it once is way more effective. That said, if I understand your question correctly, I think you don't need a map, but a multiset.
typedef pair<int, pair<string, string>> myDataType;
set<myDataType> mySet;
here, the operator < of pair will take care of the ordering.
If you don't want to refer to the id as elem.first, and to the strings as elem.second.first, and elem.second.second, then you can use a struct and overload operator < for it.
struct myType
{
int id;
string s1;
string s2;
};
bool operator < (const myType& t1, const myType& t2)
{
return make_tuple(t1.id, t1.s1, t1.s2) < make_tuple(t2.id, t2.s1, t2.s2);
}
You could just use a std::set<std::tuple<int, std::string, std::string>>. Tuples are lexicographically compared thus you would get the effect you want for free.
Live Demo
Elements in a multimap are sorted by the Key. You cannot 'sort' multimap. What you can do is to create vector of pairs<Key, Map<Key>::Interator> with elements fulfilling some logical condition and sort vector.
so I'm just learning (or trying to) a bit about hashing. I'm attempting to make a hashing function, however I'm confused where I save the data to. I'm trying to calculate the number of collisions and print that out. I have made 3 different files, one with 10,000 words, 20,000 words and 30,000 words. Each word is just 10 random numbers/letters.
long hash(char* s]){
long h;
for(int i = 0; i < 10; i++){
h = h + (int)s[i];
}
//A lot of examples then mod h by the table size
//I'm a bit confused what this table is... Is it an array of
//10,000 (or however many words)?
//h % TABLE_SIZE
return h
}
int main (int argc, char* argv[]){
fstream input(argv[1]);
char* nextWord;
while(!input.eof()){
input >> nextWord;
hash(nextWord);
}
}
So that's what I currently have, but I can't figure out what the table is exactly, as I said in the comments above... Is it a predefined array in my main with the number of words in it? For example, if I have a file of 10 words, do I make an array a of size 10 in my main? Then if/when I return h, lets say the order goes: 3, 7, 2, 3
The 4th word is a collision, correct? When that happens, I add 1 to collision and then add 1 to then check if slot 4 is also full?
Thanks for the help!
The point of hashing is to have a constant time access to every element you store. I'll try to explain on simple example bellow.
First, you need to know how much data you'd have to store. If for example you want to store numbers and you know, that you won't store numbers greater than 10. Simpliest solution is to create an array with 10 elements. That array is your "table", where you store your numbers. So how do I achieve that amazing constant time access? Hashing function! It's point is to return you an index to your array. Let's create a simple one: If you'd like to store 7, you just save it to array on position 7. Every time, you'd like to look, for element 7, you just pass it to your hasning funcion and bzaah! You got an position to your element in constant time! But what if you'd like to store more elements with value 7? Your simple hashing function is returning 7 for every element and now its position i already occupied! How to solve that? Well, there is not many solution, the simpliest are:
1: Chaining - you simply save element on first free position. This has significant draw back. Imagine, you want to delete some element ... (this is the method, you describing in question)
2: Linked list - if you create an array of pointers on some linked lists, you can easilly add your new element at the end of linked list, that is on position 7!
Both of this simple solutions has its drawbacks and cons. I guess you can see them. As #rwols has said, you don't have to use array. You can also use a tree or be a real C++ master and use unordered_map and unordered_set with custom hash function, which is quite cool. Also there is structure named trie, which is usefull, when you'd like to create some sort of dictionary (where is really hard to know, how many words you will need to store)
To sum it up. You has to know, how many things, you wan't to store and then, create ideal hashing function, that covers up array of apropriate size and in perfect world, it has to have uniform index distribution, with no colisions. (Achiving this is pretty hard and in the real world, I guess, this is impossible, so the less colisions, the better.)
Your hash function, is pretty bad. It will have lot of colisions (like strings "ab" and "ba") and also, you need to mod m it with m being the size of you array (aka. table), so you can save it to some array and you can profit of it. The modus is a way of simplyfiing the has function, because has function has to "fit" in table, that you specified in beginning, because you can't save element on position 11, 12, ... if you have array of 10.
How should good hashing function look like? Well, there is better sources than me. Some example (Alert! It's in Java)
To your example: You simply can't save 10k or even more words into table of size 10. That'll create a lot of collisions and you loose the main benefit of hashing function - constant access to elements you saved.
And how would your code look? Something like this:
int main (int argc, char* argv[]){
fstream input(argv[1]);
char* nextWord;
TypeOfElement table[size_of_table];
while(!input.eof()){
input >> nextWord;
table[hash(nextWord)] = // desired element which you want to save
}
}
But I guess, your goal isn't to save something somewhere, but to count number of colisions. Also note that code above doesn't solve colisions. If you'd like to count colisions, create array table of ints and initialize it to zero. Than, just increment the value, which is stored on index, which is returned by your hash funcion, like this:
table[hash(nextWord)]++;
I hope I helped. Please specify, what else you want to know.
If a hash table is required then as others have stated std::unordered_map will work in most cases. Now if you need something more powerful because of a large entry base, then I would suggest looking into tries. Tries combine the concepts of (Vector-Array) insertion, (Hashing) & Linked Lists. The run time is close to O(M) where M is the amount of characters in a string if you are hashing a string. It helps to remove the chance of collisions. And the more you add to a trie structure the less work has to be done as certain nodes are opened and created. The one draw back is that tries require more memory. Here is a diagram
Now your trie may vary on the size of the array due to what you are storing, but the overall concept and construction of one is the same. If you was doing a word - definition look up then you may want an array of 26 or a few more for each possible hashing character.
To count a number of words which have same hash, we should know hashes of all previous words. When you count a hash of some word, you should write it down, for example in some array. So you need an array with size equal to the number of words.
Then you should compare the new hash with all previous ones. Method of counting depends on what you need - number of pair of collisions or number off same elements.
Hash function should not be responsible for storing data. Normally you would have a container that uses hash function internally.
From what you wrote I understood that you want to create hashtable. One way you could do that (probably not the most efficient one, but should give you an idea):
#include <fstream>
#include <vector>
#include <string>
#include <map>
#include <memory>
using namespace std;
namespace example {
long hash(char* s){
long h;
for(int i = 0; i < 10; i++){
h = h + (int)s[i];
}
return h;
}
}
int main (int argc, char* argv[]){
fstream input(argv[1]);
char* nextWord;
std::map<long, std::unique_ptr<std::vector<std::string>>> hashtable;
while(!input.eof()){
input >> nextWord;
long newHash = example::hash(nextWord);
auto it = hashtable.find(newHash);
// Collision detected?
if (it == hashtable.end()) {
hashtable.insert(std::make_pair(newHash, std::unique_ptr<std::vector<std::string>>(new std::vector<std::string> { nextWord } )));
}
else {
it->second->push_back(nextWord);
}
}
}
I used some C++ 11 features to write an example faster.
I am not sure that I understand what you do not understand. The explanations below might help you.
A hash table is a kind of associative array. It is used to map keys to values in a similar manner an array is used to map indexes (keys) to values. For instance, an array of three numbers, { 11, -22, 33 }, associates index 0 to 11, index 1 to -22 and index 2 to 33.
Now, let us assume that we would like to associate 1 to 11, 2 to -22 and 3 to 33. The solution is simple: we keep the same array, only we transform the key by subtracting one from it, thus obtaining the original index
This is fine until we realize that this is just a particular case. What if the keys are not so “predictable”? A solution would be to put the associations in a list of {key, value} pairs and when someone is asking for a key, just search the list: { 123, 11}, {3, -22}, {0, 33} If the value associated to 3 is asked, we simply search the keys in list for a match and find -22. That’s fine, but if the list is large we’re in trouble. We could speed the search if we sort the array by keys and use binary search, but still the search may take some time if the list is large.
The search speed may be further enhanced if we break the list in sub-lists (or buckets) made of related pairs. This is what a hash function does: puts together pairs by related keys (an ideal hash function would associate one key to one value).
A hash table is a two columns table (an array):
The first column is the hash key (the index computed by a hash function). The size of the hash table is given by the maximum value of the hash function. If, for instance, the last step in computing the hash function is modulo 10, the size of the table will be 10; the pairs list will be broken into 10 sub-lists.
The second column is a list (bucket) of key/values pairs (the sub-list I was taking about).
I need a way in Which I can take the Input in a 2d array and sort it row wise in one of the fastest way . I tried taking Input and Sort it simultaneously using Insertion Sort. The Second thing I used is i took a multimap individually for a row and inserted with key value as the value i want and mapped value relates to that key as some Dummy value . Since map sorts key while Inserting It could be the one way I thought .
The below code is for making sure that 1 row in my 2D has its element sorted in
multimap. Basically you can say that I dont want to use a 2D structure at all as I
will use these rows individually one by one and hence can be considered as 1D array.
I also want they they gets rearranged While reading the Input , so i dont have to
extra opeartions for doing them.
for(long int j=1;j<=number_in_group;j++)
{
cin >> arrival_time;
arrival_map.insert(pair<long int, long int>(arrival_time,1));
}
Try an STL std::priority_queue? The output is guaranteed to be sorted, and if you polarize the inputs to be 2-D objects (that contain a row number for example) you're queue will build literally perfectly. At that point simply slurp the number off the queue in batches of 'n' where 'n' is your row size and each one will be sorted correctly. You will need a element type that encodes both the value AND the row in your priority queue, and sorts biased to the row # first, then then value. Your example uses long int as the data type for your values. Assuming your rows are no larger than the size of a system unsigned int:
class Element
{
public:
Element(unsigned int row, long int val)
: myrow(row), myval(val)
{};
bool operator <(const Element& elem)
{
return (myrow < elem.myrow ||
(myrow == elem.myrow && myval < elem.myvel);
}
unsigned int myrow;
long int myval;
};
typedef std::priority_queue<Element> MyQueue;
Note: this takes advantage of the priority queue's default comparison operator invoking std::less<>, which simply compares the items using the item-defined operator <(). Once you have this simply push your matrix into the queue, incrementing the row index as you switch to the next row.
MyQueue mq;
mq.push_back(Element(1,100));
mq.push_back(Element(1,99));
mq.push_back(Element(2,100));
mq.push_back(Element(2,101));
Popping the queue when finished will result in the following sequence:
99
100
100
101
Which I hope is what you want. Finally, please forgive the syntax errors and/or missing junk, as I just blasted this on the fly and have no compiler to check it against. Gotta love web cafes.
I need a data structure with the following properties:
Access to elements must be very fast
Elements, that are not added, shouldn't take memory (as ideal, size of empty structure near to zero)
Each element has two integer coordinates (x,y) (access to elements only by them)
Max count of elements known at creation time (over 10^3)
Element contains few float values
It would be good if you also directed to an implementation of this structure in C or C++.
Are you looking for a sparse matrix ?
Check this out - you could alter the element type to float if this does everything you want.
Concise Sparse Matrix Package in C
For C++ you could use Boost.uBLAS - sparse_matrix details here.
If your X and Y are relatively small then a two dimensional array of pointers would work. 10000 pointers would be 40K in 32 bit code.
typdef ElementAccessor std::pair<int, int>;
struct Element
{
float f1;
float f2;
//etc.
};
std::map< ElementAccessor, Element > myElementMap;
You can now use this map as a matrix. ElementAccessor refers to x,y. Just make sure to see if the element exists in the map before you try to access it, or one is created by default.
http://www.cplusplus.com/reference/std/utility/pair/
http://www.cplusplus.com/reference/stl/map/find/
edit: the template brackets are showing up for the map. the map key type is ElementAccessor, the value is Element. Also, for the pair, the templating is int, int.