I'm trying to fill an array with missing intermediate data
My data input is like this
var data = [[5.23,7],[5.28,7],[5.32,8],[5.35,8]];
I wanna fill the array with missing value but I need to respect this rule:
The 1st value on 2d array must be the next sequence number, so 5.23
... 5.24 ... 5.25 ...
The 2nd value on 2d array must be the same element from the i+1
value
So the results in this case would be
var data = [[5.23,7],[5.24,7],[5.25,7],[5.26,7],[5.27,7],[5.28,7],[5.29,8],[5.30,8],[5.31,8],[5.32,8],[5.33,8],[5.34,8],[5.35,8]];
This little piece of code works, but I don't know
how to put in loop
and how to write a while loop that pass every time the new length of the array
var data = [[5.23,7],[5.28,7],[5.32,8],[5.35,8]];
if (data[1][0]-data[0][0] > 0.01) {
data.push([data[0][0]+0.01,data[1][1]]);
data.sort(function (a, b) { return a[0] - b[0]; });
} else {
check the next element
}
console.log(data);
Any idea?
Here's another idea... I thought it might feel more natural to loop through the sequence numbers directly.
Your final array will range (in this example) from 5.23 to 5.35 incrementing by 0.01. This approach uses a for loop starting going from 5.23 to 5.35 incrementing by 0.01.
key points
Rounding: Work in x100 then divide back down to avoid floating point rounding issues. I round to the neared hundredth using toFixed(2) and then converting back to a number (with leading + operator).
Indexing: Recognizing 5.23 is the zero index with each index incrementing 1/100, you can calculate index from numerical values, ex. 100*(5.31-5.23) equals 8 (so 5.31 belongs in output[8]).
2nd values: given a numerical value (ex. 5.31), just find the first element in the data array with a higher 1st value and use its 2nd value - this is a corollary of your requirement. Because 5.31 <= 5.28 is false, don't use 7 (from [5.28,7]). Because 5.31 <= 5.32 is true, use 8 (from [5.32,8]).
EDIT
I improved the performance a bit - (1) initialize output instead of modifying array size, (2) work in multiples of 100 instead of continuously rounding from floating point to hundredths.
I ran 5000 iterations on a longer example and, on average, these modifications make this approach 3x faster than Redu's (where the original was 2x slower).
var data = [[5.23,7],[5.28,7],[5.32,8],[5.35,8]];
var output = Array((data[data.length-1][0]-data[0][0]).toFixed(2)*100+1)
function getIndex(value){
return (value-data[0][0]*100)
}
for( var i = 100*data[0][0]; i <= 100*data[data.length-1][0]; i++ ){
output[getIndex(i)] = [i/100, data.find( d => i <= 100*d[0] )[1]]
}
//console.log(output)
// Performance comparison
function option1(data){
let t = performance.now()
var output = Array((data[data.length-1][0]-data[0][0]).toFixed(2)*100+1)
function getIndex(value){
return (value-data[0][0]*100)
}
for( var i = 100*data[0][0]; i <= 100*data[data.length-1][0]; i++ ){
output[getIndex(i)] = [i/100, data.find( d => i <= 100*d[0] )[1]]
}
return performance.now()-t
}
function option2(data){
let t = performance.now()
newData = data.reduce((p,c,i,a) => i ? p.concat(Array(Math.round(c[0]*100 - a[i-1][0]*100)).fill()
.map((_,j) => [Number((a[i-1][0]+(j+1)/100).toFixed(2)),c[1]]))
: [c],[]);
return performance.now()-t
}
var testdata = [[1.13,4],[2.05,6],[5.23,7],[5.28,7],[5.32,8],[5.35,8],[8.91,9],[10.31,9]];
var nTrials = 10000;
for(var trial=0, t1=0; trial<=nTrials; trial++) t1 += option1(testdata)
for(var trial=0, t2=0; trial<=nTrials; trial++) t2 += option2(testdata)
console.log(t1/nTrials) // ~0.4 ms
console.log(t2/nTrials) // ~0.55 ms
Array.prototype.reduce() is sometimes handy to extend the array. May be you can do as follows;
var data = [[5.23,7],[5.28,7],[5.32,8],[5.35,8]],
newData = data.reduce((p,c,i,a) => i ? p.concat(Array(Math.round(c[0]*100 - a[i-1][0]*100)).fill()
.map((_,j) => [Number((a[i-1][0]+(j+1)/100).toFixed(2)),c[1]]))
: [c],[]);
console.log(newData);
var data = [[1.01,3],[1.04,4],[1.09,5],[1.10,6],[1.15,7]],
newData = data.reduce((p,c,i,a) => i ? p.concat(Array(Math.round(c[0]*100 - a[i-1][0]*100)).fill()
.map((_,j) => [Number((a[i-1][0]+(j+1)/100).toFixed(2)),c[1]]))
: [c],[]);
console.log(newData);
I propose this solution :
var data = [[5.23,7],[5.28,7],[5.32,8],[5.35,8]];
var res = [];
data.forEach((item, index, arr) => {
res.push(item);
var temp = item[0];
while (arr[index+1] && arr[index+1][0]-temp > 0.01){
temp += 0.01;
res.push([temp, arr[index+1][1]]);
}
});
console.log(res);
Related
After having a long difficult coding challenge, there was a problem that bugged me. I thought about it for an adequate time but couldn't find the way to solve it. Here, I am providing a problem and example below.
Input
v : an array of numbers.
q : 2 dimensional array with 3 elements in nested array.
Description
v is an array and q is a commands that does different thing according to its nested element.
if first element of nested array is 1 => second and third element of the nested array becomes the index and it returns sum[second:third+1] (As you can see, it is inclusive)
if first element of nested array is 2 => element of second index becomes the third. same as v[second] = third
Input example
v : [1,2,3,4,5]
q : [[1,2,4], [2,3,8], [1,2,4]]
Example
With a provided example, it goes like
command is [1,2,4] => first element is 1. it should return sum from v[2] to v[4] (inclusive) => 12.
command is [2,3,8] => first element is 2. it switches v[3] to 8. (now v is [1,2,3,8,5])
command is [1,2,4] => first element is 1. it should return sum from v[2] to v[4] (inclusive) => 16, as the third index has been changed from the previous command.
So the final answer is [12, 16]
Question.
The code below is how I solved, however, this is O(n**2) complexity. I wonder how I can reduce the time complexity in this case.
I tried making a hash object, but it didn't work. I can't think of a good way to make a cache in this case.
function solution(v, q) {
let answer = [];
for (let i = 0; i < q.length; i++) {
let [a, b, c] = q[i];
if (a === 1) {
let sum = 0;
for (let i = b; i <= c; i++) {
sum += v[i];
}
answer.push(sum);
} else if (a === 2) {
v[b] = c;
}
}
return answer;
}
This type of problem can typically be solved more efficiently with a Fenwick tree
Here is an implementation:
class BinaryIndexedTree extends Array {
constructor(length) {
super(length + 1);
this.fill(0);
}
add(i, delta) {
i++; // make index 1-based
while (i < this.length) {
this[i] += delta;
i += i & -i; // add least significant bit
}
}
sumUntil(i) {
i++; // make index 1-based
let sum = 0;
while (i) {
sum += this[i];
i -= i & -i;
}
return sum;
}
}
function solution(values, queries) {
const tree = new BinaryIndexedTree(values.length);
values.forEach((value, i) => tree.add(i, value));
const answer = [];
for (const [a, b, c] of queries) {
if (a === 1) {
answer.push(tree.sumUntil(c) - tree.sumUntil(b - 1));
} else {
tree.add(b, c - values[b]);
values[b] = c;
}
}
return answer;
}
let answer = solution([1,2,3,4,5], [[1,2,4], [2,3,8], [1,2,4]]);
console.log(answer);
Time Complexity
The time complexity of running tree.add or tree.sumUntil once is O(log𝑛), where 𝑛 is the size of the input values (values.length). So this is also the time complexity of running one query.
The creation of the tree costs O(𝑛), as this is the size of the tree
The initialisation of the tree with values costs O(𝑛log𝑛), as really each value in the input acts as a query that updates a value from 0 to the actual value.
Executing the queries costs O(𝑚log𝑛) where 𝑚 is the number of queries (queries.length)
So in total, we have a time complexity of O(𝑛 + 𝑛log𝑛 + 𝑚log𝑛) = O((𝑚+𝑛)log𝑛)
Further reading
For more information on Fenwick trees, see BIT: What is the intuition behind a binary indexed tree and how was it thought about?
I just took a coding test online and this one question really bothered me. My solution was correct but was rejected for being unoptimized. The question is as following:
Write a function combineTheGivenNumber taking two arguments:
numArray: number[]
num: a number
The function should check all the concatenation pairs that can result in making a number equal to num and return their count.
E.g. if numArray = [1, 212, 12, 12] & num = 1212 then we will have return value of 3 from combineTheGivenNumber
The pairs are as following:
numArray[0]+numArray[1]
numArray[2]+numArray[3]
numArray[3]+numArray[2]
The function I wrote for this purpose is as following:
function combineTheGivenNumber(numArray, num) {
//convert all numbers to strings for easy concatenation
numArray = numArray.map(e => e+'');
//also convert the `hay` to string for easy comparison
num = num+'';
let pairCounts = 0;
// itereate over the array to get pairs
numArray.forEach((e,i) => {
numArray.forEach((f,j) => {
if(i!==j && num === (e+f)) {
pairCounts++;
}
});
});
return pairCounts;
}
console.log('Test 1: ', combineTheGivenNumber([1,212,12,12],1212));
console.log('Test 2: ', combineTheGivenNumber([4,21,42,1],421));
From my experience, I know conversion of number to string is slow in JS, but I am not sure whether my approach is wrong/lack of knowledge or does the tester is ignorant of this fact. Can anyone suggest further optimization of the code snipped?
Elimination of string to number to string will be a significant speed boost but I am not sure how to check for concatenated numbers otherwise.
Elimination of string to number to string will be a significant speed boost
No, it won't.
Firstly, you're not converting strings to numbers anywhere, but more importantly the exercise asks for concatenation so working with strings is exactly what you should do. No idea why they're even passing numbers. You're doing fine already by doing the conversion only once for each number input, not every time your form a pair. And last but not least, avoiding the conversion will not be a significant improvement.
To get a significant improvement, you should use a better algorithm. #derpirscher is correct in his comment: "[It's] the nested loop checking every possible combination which hits the time limit. For instance for your example, when the outer loop points at 212 you don't need to do any checks, because regardless, whatever you concatenate to 212, it can never result in 1212".
So use
let pairCounts = 0;
numArray.forEach((e,i) => {
if (num.startsWith(e)) {
//^^^^^^^^^^^^^^^^^^^^^^
numArray.forEach((f,j) => {
if (i !== j && num === e+f) {
pairCounts++;
}
});
}
});
You might do the same with suffixes, but it becomes more complicated to rule out concatenation to oneself there.
Optimising further, you can even achieve a linear complexity solution by putting the strings in a lookup structure, then when finding a viable prefix just checking whether the missing part is an available suffix:
function combineTheGivenNumber(numArray, num) {
const strings = new Map();
for (const num of numArray) {
const str = String(num);
strings.set(str, 1 + (strings.get(str) ?? 0));
}
const whole = String(num);
let pairCounts = 0;
for (const [prefix, pCount] of strings) {
if (!whole.startsWith(prefix))
continue;
const suffix = whole.slice(prefix.length);
if (strings.has(suffix)) {
let sCount = strings.get(suffix);
if (suffix == prefix) sCount--; // no self-concatenation
pairCounts += pCount*sCount;
}
}
return pairCounts;
}
(the proper handling of duplicates is a bit difficile)
I like your approach of going to strings early. I can suggest a couple of simple optimizations.
You only need the numbers that are valid "first parts" and those that are valid "second parts"
You can use the javascript .startsWith and .endsWith to test for those conditions. All other strings can be thrown away.
The lengths of the strings must add up to the length of the desired answer
Suppose your target string is 8 digits long. If you have 2 valid 3-digit "first parts", then you only need to know how many valid 5-digit "second parts" you have. Suppose you have 9 of them. Those first parts can only combine with those second parts, and give you 2 * 9 = 18 valid pairs.
You don't actually need to keep the strings!
It struck me that if you know you have 2 valid 3-digit "first parts", you don't need to keep those actual strings. Knowing that they are valid 2-digit first parts is all you need to know.
So let's build an array containing:
How many valid 1-digit first parts do we have?,
How many valid 2-digit first parts do we have?,
How many valid 3-digit first parts do we have?,
etc.
And similarly an array containing the number of valid 1-digit second parts, etc.
X first parts and Y second parts can be combined in X * Y ways
Except if the parts are the same length, in which case we are reusing the same list, and so it is just X * (Y-1).
So not only do we not need to keep the strings, but we only need to do the multiplication of the appropriate elements of the arrays.
5 1-char first parts & 7 3-char second parts = 5 * 7 = 35 pairs
6 2-char first part & 4 2-char second parts = 6 * (4-1) = 18 pairs
etc
So this becomes extremely easy. One pass over the strings, tallying the "first part" and "second part" matches of each length. This can be done with an if and a ++ of the relevant array element.
Then one pass over the lengths, which will be very quick as the array of lengths will be very much shorter than the array of actual strings.
function combineTheGivenNumber(numArray, num) {
const sElements = numArray.map(e => "" + e);
const sTarget = "" + num;
const targetLength = sTarget.length
const startsByLen = (new Array(targetLength)).fill(0);
const endsByLen = (new Array(targetLength)).fill(0);
sElements.forEach(sElement => {
if (sTarget.startsWith(sElement)) {
startsByLen[sElement.length]++
}
if (sTarget.endsWith(sElement)) {
endsByLen[sElement.length]++
}
})
// We can now throw away the strings. We have two separate arrays:
// startsByLen[1] is the count of strings (without attempting to remove duplicates) which are the first character of the required answer
// startsByLen[2] similarly the count of strings which are the first 2 characters of the required answer
// etc.
// and endsByLen[1] is the count of strings which are the last character ...
// and endsByLen[2] is the count of strings which are the last 2 characters, etc.
let pairCounts = 0;
for (let firstElementLength = 1; firstElementLength < targetLength; firstElementLength++) {
const secondElementLength = targetLength - firstElementLength;
if (firstElementLength === secondElementLength) {
pairCounts += startsByLen[firstElementLength] * (endsByLen[secondElementLength] - 1)
} else {
pairCounts += startsByLen[firstElementLength] * endsByLen[secondElementLength]
}
}
return pairCounts;
}
console.log('Test 1: ', combineTheGivenNumber([1, 212, 12, 12], 1212));
console.log('Test 2: ', combineTheGivenNumber([4, 21, 42, 1], 421));
Depending on a setup, the integer slicing can be marginally faster
Although in the end it falls short
Also, when tested on higher N values, the previous answer exploded in jsfiddle. Possibly a memory error.
As far as I have tested with both random and hand-crafted values, my solution holds. It is based on an observation, that if X, Y concantenated == Z, then following must be true:
Z - Y == X * 10^(floor(log10(Y)) + 1)
an example of this:
1212 - 12 = 1200
12 * 10^(floor((log10(12)) + 1) = 12 * 10^(1+1) = 12 * 100 = 1200
Now in theory, this should be faster then manipulating strings. And in many other languages it most likely would be. However in Javascript as I just learned, the situation is a bit more complicated. Javascript does some weird things with casting that I haven't figured out yet. In short - when I tried storing the numbers(and their counts) in a map, the code got significantly slower making any possible gains from this logarithm shenanigans evaporate. Furthermore, storing them in a custom-crafted data structure isn't guaranteed to be faster since you have to build it etc. Also it would be quite a lot of work.
As it stands this log comparison is ~ 8 times faster in a case without(or with just a few) matches since the quadratic factor is yet to kick in. As long as the possible postfix count isn't too high, it will outperform the linear solution. Unfortunately it is still quadratic in nature with the breaking point depending on a total number of strings as well as their length.
So if you are searching for a needle in a haystack - for example you are looking for a few pairs in a huge heap of numbers, this can help. In the other case of searching for many matches, this won't help. Similarly, if the input array was sorted, you could use binary search to push the breaking point further up.
In the end, unless you manage to figure out how to store ints in a map(or some custom implementation of it) in a way that doesn't completely kill the performance, the linear solution of the previous answer will be faster. It can still be useful even with the performance hit if your computation is going to be memory heavy. Storing numbers takes less space then storing strings.
var log10 = Math.log(10)
function log10floored(num) {
return Math.floor(Math.log(num) / log10)
}
function combineTheGivenNumber(numArray, num) {
count = 0
for (var i=0; i!=numArray.length; i++) {
let portion = num - numArray[i]
let removedPart = Math.pow(10, log10floored(numArray[i]))
if (portion % (removedPart * 10) == 0) {
for (var j=0; j!=numArray.length; j++) {
if (j != i && portion / (removedPart * 10) == numArray[j] ) {
count += 1
}
}
}
}
return count
}
//The previous solution, that I used for timing, comparison and check purposes
function combineTheGivenNumber2(numArray, num) {
const strings = new Map();
for (const num of numArray) {
const str = String(num);
strings.set(str, 1 + (strings.get(str) ?? 0));
}
const whole = String(num);
let pairCounts = 0;
for (const [prefix, pCount] of strings) {
if (!whole.startsWith(prefix))
continue;
const suffix = whole.slice(prefix.length);
if (strings.has(suffix)) {
let sCount = strings.get(suffix);
if (suffix == prefix) sCount--; // no self-concatenation
pairCounts += pCount*sCount;
}
}
return pairCounts;
}
var myArray = []
for (let i =0; i!= 10000000; i++) {
myArray.push(Math.floor(Math.random() * 1000000))
}
var a = new Date()
t1 = a.getTime()
console.log('Test 1: ', combineTheGivenNumber(myArray,15285656));
var b = new Date()
t2 = b.getTime()
console.log('Test 2: ', combineTheGivenNumber2(myArray,15285656));
var c = new Date()
t3 = c.getTime()
console.log('Test1 time: ', t2 - t1)
console.log('test2 time: ', t3 - t2)
Small update
As long as you are willing to take a performance hit with the setup and settle for the ~2 times performance, using a simple "hashing" table can help.(Hashing tables are nice and tidy, this is a simple modulo lookup table. The principle is similar though.)
Technically this isn't linear, practicaly it is enough for the most cases - unless you are extremely unlucky and all your numbers fall in the same bucket.
function combineTheGivenNumber(numArray, num) {
count = 0
let size = 1000000
numTable = new Array(size)
for (var i=0; i!=numArray.length; i++) {
let idx = numArray[i] % size
if (numTable[idx] == undefined) {
numTable[idx] = [numArray[i]]
} else {
numTable[idx].push(numArray[i])
}
}
for (var i=0; i!=numArray.length; i++) {
let portion = num - numArray[i]
let removedPart = Math.pow(10, log10floored(numArray[i]))
if (portion % (removedPart * 10) == 0) {
if (numTable[portion / (removedPart * 10) % size] != undefined) {
let a = numTable[portion / (removedPart * 10) % size]
for (var j=0; j!=a.length; j++) {
if (j != i && portion / (removedPart * 10) == a[j] ) {
count += 1
}
}
}
}
}
return count
}
Here's a simplified, and partially optimised approach with 2 loops:
// let's optimise 'combineTheGivenNumber', where
// a=array of numbers AND n=number to match
const ctgn = (a, n) => {
// convert our given number to a string using `toString` for clarity
// this isn't entirely necessary but means we can use strict equality later
const ns = n.toString();
// reduce is an efficient mechanism to return a value based on an array, giving us
// _=[accumulator], na=[array number] and i=[index]
return a.reduce((_, na, i) => {
// convert our 'array number' to an 'array number string' for later concatenation
const nas = na.toString();
// iterate back over our array of numbers ... we're using an optimised/reverse loop
for (let ii = a.length - 1; ii >= 0; ii--) {
// skip the current array number
if (i === ii) continue;
// string + number === string, which lets us strictly compare our 'number to match'
// if there's a match we increment the accumulator
if (a[ii] + nas === ns) ++_;
}
// we're done
return _;
}, 0);
}
Using ES6's Set, given two arrays we can get the intersection like so:
let a = new Set([1,2,3])
let b = new Set([1,2,4])
let intersect = new Set([...a].filter(i => b.has(i)));
How can we get the intersection of n arrays?
Update:
I'm trying to wrap my head around this for the following use case. I have a two dimensional array with at least one element.
parts.forEach(part => {
intersection = new Set()
})
How would you get the intersection of each element (array) in parts?
Assuming you have some function function intersect(set1, set2) {...} that can intersect two sets, you can get the intersection of an array of sets using reduce:
function intersect(a, b) {
return new Set(a.filter(i => b.has(i)));
}
var sets = [new Set([1,2,3]), ...];
var intersection = sets.reduce(intersect);
You can create an intersect helper function using a combination of Array methods like .filter(), .map(), and .every().
This answer is inspired by the comment above from Xufox, who mentioned using Array#every in a filter predicate.
function intersect (first = [], ...rest) {
rest = rest.map(array => new Set(array))
return first.filter(e => rest.every(set => set.has(e)))
}
let parts = [
[1, 2, 3],
[1, 2, 4],
[1, 5, 2]
]
console.log(
intersect(...parts)
)
ES6 still has a while
This is the type of function that can easily cause long lags due to excessive amounts of processing. This is more true with the unquestioning and even preferential use of ES6 and array methods like reduce, filter etc, over simple old fashioned loops like while and for.
When calculating the intersection of many sets the amount of work done per iteration should go down if an item has been found not to be part of the intersection. Because forEach can not break you are forced to still iterate all elements. Adding some code to avoid doing the search if the current item has been found to not belong can improve the performance, but it is a real kludge.
The is also the tendency to just create whole new datasets just to remove a single item from an array, set, or map. This is a very bad habit that i see more and more of as people adopt the ES5 way.
Get the intersection of n sets.
So to the problem at hand. Find the intersection of many sets.
Solution B
A typical ES6 solution
function intersectB(firstSet, ...sets) {
// function to intercept two sets
var intersect = (a,b) => {
return new Set([...a].filter(item => b.has(item)))
};
// iterate all sets comparing the first set to each.
sets.forEach(sItem => firstSet = intersect(firstSet, sItem));
// return the result.
return firstSet;
}
var sets = [new Set([1,2,3,4]), new Set([1,2,4,6,8]), new Set([1,3,4,6,8])];
var inter = intersectB(...sets);
console.log([...inter]);
Works well and for the simple test case execution time is under a millisecond. But in my book it is a memory hogging knot of inefficiency, creating arrays, and sets at every line almost and iterating whole sets when the outcome is already known.
Let's give it some more work. 100 sets, with up to 10000 items over 10 tests each with differing amount of matching items. Most of the intercepts will return empty sets.
Warning will cause page to hang up to one whole second... :(
// Create a set of numbers from 0 and < count
// With a odds for any number occurring to be odds
// return as a new set;
function createLargeSet(count,odds){
var numbers = new Set();
while(count-- > 0){
if(Math.random() < odds){
numbers.add(count);
}
}
return numbers;
}
// create a array of large sets
function bigArrayOfSets(setCount,setMaxSize,odds){
var bigSets = [];
for(var i = 0; i < setCount; i ++){
bigSets.push(createLargeSet(setMaxSize,odds));
}
return bigSets;
}
function intersectB(firstSet, ...sets) {
var intersect = (a,b) => {
return new Set([...a].filter(item => b.has(item)))
};
sets.forEach(sItem => firstSet = intersect(firstSet, sItem));
return firstSet;
}
var testSets = [];
for(var i = 0.1; i <= 1; i += 0.1){
testSets.push(bigArrayOfSets(100,10000,i));
}
var now = performance.now();
testSets.forEach(testDat => intersectB(...testDat));
var time = performance.now() - now;
console.log("Execution time : " + time);
Solution A
A better way, not as fancy but much more efficient.
function intersectA(firstSet,...sets) {
var count = sets.length;
var result = new Set(firstSet); // Only create one copy of the set
firstSet.forEach(item => {
var i = count;
var allHave = true;
while(i--){
allHave = sets[i].has(item)
if(!allHave) { break } // loop only until item fails test
}
if(!allHave){
result.delete(item); // remove item from set rather than
// create a whole new set
}
})
return result;
}
Compare
So now let's compare both, if you are feeling lucky try and guess the performance difference, it's a good way to gage your understanding of Javascript execution.
// Create a set of numbers from 0 and < count
// With a odds for any number occurring to be odds
// return as a new set;
function createLargeSet(count,odds){
var numbers = new Set();
while(count-- > 0){
if(Math.random() < odds){
numbers.add(count);
}
}
return numbers;
}
// create a array of large sets
function bigArrayOfSets(setCount,setMaxSize,odds){
var bigSets = [];
for(var i = 0; i < setCount; i ++){
bigSets.push(createLargeSet(setMaxSize,odds));
}
return bigSets;
}
function intersectA(firstSet,...sets) {
var count = sets.length;
var result = new Set(firstSet); // Only create one copy of the set
firstSet.forEach(item => {
var i = count;
var allHave = true;
while(i--){
allHave = sets[i].has(item)
if(!allHave) { break } // loop only until item fails test
}
if(!allHave){
result.delete(item); // remove item from set rather than
// create a whole new set
}
})
return result;
}
function intersectB(firstSet, ...sets) {
var intersect = (a,b) => {
return new Set([...a].filter(item => b.has(item)))
};
sets.forEach(sItem => firstSet = intersect(firstSet, sItem));
return firstSet;
}
var testSets = [];
for(var i = 0.1; i <= 1; i += 0.1){
testSets.push(bigArrayOfSets(100,10000,i));
}
var now = performance.now();
testSets.forEach(testDat => intersectB(...testDat));
var time = performance.now() - now;
console.log("Execution time 'intersectB' : " + time);
var now = performance.now();
testSets.forEach(testDat => intersectA(...testDat));
var time = performance.now() - now;
console.log("Execution time 'intersectA' : " + time);
As you can see using a simple while loop may not be a cool as using filter but the performance benefit is huge, and something to keep in mind next time you are writing that perfect 3 line ES6 array manipulation function. Dont forget about for and while.
The most efficient algorithm for intersecting n arrays is the one implemented in fast_array_intersect. It runs in O(n), where n is the total number of elements in all the arrays.
The base principle is simple: iterate over all the arrays, storing the number of times you see each element in a map. Then filter the smallest array, to return only the elements that have been seen in all the arrays. (source code).
You can use the library with a simple :
import intersect from 'fast_array_intersect'
intersect([[1,2,3], [1,2,6]]) // --> [1,2]
OK i guess the most efficient way of performing the Array intersection is by utilizing a Map or Hash object. Here I test 1000 arrays each with ~1000 random integer items among 1..175 for an intersection. The result is obtained in less than 100msec.
function setIntersection(a){
var m = new Map(),
r = new Set(),
l = a.length;
a.forEach(sa => new Set(sa).forEach(n => m.has(n) ? m.set(n,m.get(n)+1)
: m.set(n,1)));
m.forEach((v,k) => v === l && r.add(k));
return r;
}
var testSets = Array(1000).fill().map(_ => Array(1000).fill().map(_ => ~~(Math.random()*175+1)));
console.time("int");
result = setIntersection(testSets);
console.timeEnd("int");
console.log(JSON.stringify([...result]));
I know it is a noob question, but still thought of asking out of curiosity.
I have a byte array of 3 bytes for example [00,00,00]. everytime I iterate a method I have increment the last by by 0x02 times. Now once the last byte reaches the threshold value FF I need to increment the last but one byte to +1 along with incrementing last byte. For example for byte array values [00,00,FF] incrementing it with 0x02 should become [00,01,02] and finally it should reach [FF,FF,FF] what should be the ideal way of doing it rather than using the normal if conditions.
Did you try with a for loop and a if condition ?
You cycle through your elements. If the element is smaller than 0xFF, you increment it, and you return. Otherwise you set it to 0x00 and you let the for loop cycle further.
Pseudo-code:
for element in array (in reverse order):
if(element == 0xFF):
element = 0
else:
element += 0x02
return array
you should work with only one variable
var i=0; // from 0 to 4096
//every time you can increment i++;
where you want result just convert i to array like :
function convert_array(val){
var val2 = parseInt(val/4096, 16);
var val1 = parseInt(val2/256, 16);
var val0 = parseInt(val2%256, 16);
return [val2 , val1, val0];
}
var result = convert_array(i);
the advanges :
to increment number no problem just i++;
you have no loops (for) :)
EDIT (dumped the nested loops)
For a more generic approach (obviously not with colors), you should try a cascading increment like this:
// non-destructive increment of the arr
// [0xFF, 0x00] -> [0x00, 0x02]
function incremented(arr) {
var value,
index = 0,
increment = 0x02,
threshold = 0xFF,
re = [],
flip = true;
for (var i = 0; i < arr.length; i++) {
value = arr[i];
if (flip === false) {
// don't touch, just add it
re.push(value);
} else if (value + increment > threshold) {
// add zero value, but keep on flipping
re.push(0);
} else {
// add incremented value
re.push(value + increment);
}
}
if (flip) {
// if even the last number did not stop flipping add another
re.push(increment);
}
return re;
}
So, I have successfully written the Fibonacci sequence to create an array with the sequence of numbers, but I need to know the length (how many digits) the 500th number has.
I've tried the below code, but its finding the length of the scientific notation (22 digits), not the proper 105 it should be returning.
Any ideas how to convert a scientific notation number into an actual integer?
var fiblength = function fiblength(nth) {
var temparr = [0,1];
for(var i = 2; i<=nth; i++){
var prev = temparr[temparr.length-2],
cur = temparr[temparr.length-1],
next = prev + cur;
temparr.push(next);
}
var final = temparr[temparr.length-1].toString().length;
console.log(temparr[temparr.length-1]);
return final;
};
a = fiblength(500);
console.log(a);
Why not use the simple procedure of dividing the number by 10 until the number is less than 1.
Something as simple as this should work (a recursive def obv works as well)
function getDigits(n) {
var digits = 0;
while(n >= 1) {
n/=10;
digits += 1;
}
return digits;
}
getDigits(200);//3
getDigits(3.2 * 10e20);//=>22
Here's a solution in constant time:
function fiblength(n) {
return Math.floor((n>1)?n*.2089+.65051:1);
}
Let's explain how I arrived to it.
All previous solutions will probably not work for N>300 unless you have a BigNumber library in place. Also they're pretty inneficient.
There is a formula to get any Fibonacci number, which uses PHI (golden ratio number), it's very simple:
F(n) = ABS((PHI^n)/sqrt(5))
Where PHI=1.61803399 (golden ratio, found all over the fibonacci sequence)
If you want to know how many digits a number has, you calculate the log base 10 and add 1 to that. Let's call that function D(n) = log10(n) + 1
So what you want fiblength to be is in just the following function
fiblength(n) = D(F(n)) // number of digits of a fibonacci number...
Let's work it out, so you see what the one liner code will be like once you use math.
Substitute F(n)
fiblength(n) = D(ABS((PHI^n)/sqrt(5)))
Now apply D(n) on that:
fiblength(n) = log10(ABS((PHI^n)/sqrt(5))) + 1
So, since log(a/b) = log(a) - log(b)
fiblength(n) = log10(ABS((PHI^n))) - log10(sqrt(5))) + 1
and since log(a^n) = n * log(a)
fiblength(n) = n*log10(PHI) - log10(sqrt(5))) + 1
Then we evaluate those logarithms since they're all on constants
and add the special cases of n=0 and n=1 to return 1
function fiblength(n) {
return Math.floor((n>1)?n*.2089+.65051:1);
}
Enjoy :)
fiblength(500) => 105 //no iterations necessary.
Most of the javascript implementations, internally use 64 bit numbers. So, if the number we are trying to represent is very big, it uses scientific notation to represent those numbers. So, there is no pure "javascript numbers" based solution for this. You may have to look for other BigNum libraries.
As far as your code is concerned, you want only the 500th number, so you don't have to store the entire array of numbers in memory, just previous and current numbers are enough.
function fiblength(nth) {
var previous = 0, current = 1, temp;
for(var i = 2; i<=nth; i++){
temp = current;
current = previous + current;
previous = temp;
}
return current;
};
My Final Solution
function fiblength(nth) {
var a = 0, b = 1, c;
for(var i=2;i<=nth;i++){
c=b;
b=a+b;
a=c;
}
return Math.floor(Math.log(b)/Math.log(10))+1;
}
console.log(fiblength(500));
Thanks for the help!!!
The problem is because the resulting number was converted into a string before any meaningful calculations could be made. Here's how it could have been solved in the original code:
var fiblength = function fiblength(nth) {
var temparr = [0,1];
for(var i = 2; i<=nth; i++){
var prev = temparr[temparr.length-2],
cur = temparr[temparr.length-1],
next = prev + cur;
temparr.push(next);
}
var x = temparr[temparr.length-1];
console.log(x);
var length = 1;
while (x > 1) {
length = length + 1;
x = x/10;
}
return length;
};
console.log ( fiblength(500) );