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I've been working with JavaScript for a few days now and have got to a point where I want to overload operators for my defined objects.
After a stint on google searching for this it seems you can't officially do this, yet there are a few people out there claiming some long-winded way of performing this action.
Basically I've made a Vector2 class and want to be able to do the following:
var x = new Vector2(10,10);
var y = new Vector2(10,10);
x += y; //This does not result in x being a vector with 20,20 as its x & y values.
Instead I'm having to do this:
var x = new Vector2(10,10);
var y = new Vector2(10,10);
x = x.add(y); //This results in x being a vector with 20,20 as its x & y values.
Is there an approach I can take to overload operators in my Vector2 class? As this just looks plain ugly.
As you've found, JavaScript doesn't support operator overloading. The closest you can come is to implement toString (which will get called when the instance needs to be coerced to being a string) and valueOf (which will get called to coerce it to a number, for instance when using + for addition, or in many cases when using it for concatenation because + tries to do addition before concatenation), which is pretty limited. Neither lets you create a Vector2 object as a result. Similarly, Proxy (added in ES2015) lets you intercept various object operations (including property access), but again won't let you control the result of += on Vector instances.
For people coming to this question who want a string or number as a result (instead of a Vector2), though, here are examples of valueOf and toString. These examples do not demonstrate operator overloading, just taking advantage of JavaScript's built-in handling converting to primitives:
valueOf
This example doubles the value of an object's val property in response to being coerced to a primitive, for instance via +:
function Thing(val) {
this.val = val;
}
Thing.prototype.valueOf = function() {
// Here I'm just doubling it; you'd actually do your longAdd thing
return this.val * 2;
};
var a = new Thing(1);
var b = new Thing(2);
console.log(a + b); // 6 (1 * 2 + 2 * 2)
Or with ES2015's class:
class Thing {
constructor(val) {
this.val = val;
}
valueOf() {
return this.val * 2;
}
}
const a = new Thing(1);
const b = new Thing(2);
console.log(a + b); // 6 (1 * 2 + 2 * 2)
Or just with objects, no constructors:
var thingPrototype = {
valueOf: function() {
return this.val * 2;
}
};
var a = Object.create(thingPrototype);
a.val = 1;
var b = Object.create(thingPrototype);
b.val = 2;
console.log(a + b); // 6 (1 * 2 + 2 * 2)
toString
This example converts the value of an object's val property to upper case in response to being coerced to a primitive, for instance via +:
function Thing(val) {
this.val = val;
}
Thing.prototype.toString = function() {
return this.val.toUpperCase();
};
var a = new Thing("a");
var b = new Thing("b");
console.log(a + b); // AB
Or with ES2015's class:
class Thing {
constructor(val) {
this.val = val;
}
toString() {
return this.val.toUpperCase();
}
}
const a = new Thing("a");
const b = new Thing("b");
console.log(a + b); // AB
Or just with objects, no constructors:
var thingPrototype = {
toString: function() {
return this.val.toUpperCase();
}
};
var a = Object.create(thingPrototype);
a.val = "a";
var b = Object.create(thingPrototype);
b.val = "b";
console.log(a + b); // AB
As T.J. said, you cannot overload operators in JavaScript. However you can take advantage of the valueOf function to write a hack which looks better than using functions like add every time, but imposes the constraints on the vector that the x and y are between 0 and MAX_VALUE. Here is the code:
var MAX_VALUE = 1000000;
var Vector = function(a, b) {
var self = this;
//initialize the vector based on parameters
if (typeof(b) == "undefined") {
//if the b value is not passed in, assume a is the hash of a vector
self.y = a % MAX_VALUE;
self.x = (a - self.y) / MAX_VALUE;
} else {
//if b value is passed in, assume the x and the y coordinates are the constructors
self.x = a;
self.y = b;
}
//return a hash of the vector
this.valueOf = function() {
return self.x * MAX_VALUE + self.y;
};
};
var V = function(a, b) {
return new Vector(a, b);
};
Then you can write equations like this:
var a = V(1, 2); //a -> [1, 2]
var b = V(2, 4); //b -> [2, 4]
var c = V((2 * a + b) / 2); //c -> [2, 4]
It's possible to do vector math with two numbers packed into one. Let me first show an example before I explain how it works:
let a = vec_pack([2,4]);
let b = vec_pack([1,2]);
let c = a+b; // Vector addition
let d = c-b; // Vector subtraction
let e = d*2; // Scalar multiplication
let f = e/2; // Scalar division
console.log(vec_unpack(c)); // [3, 6]
console.log(vec_unpack(d)); // [2, 4]
console.log(vec_unpack(e)); // [4, 8]
console.log(vec_unpack(f)); // [2, 4]
if(a === f) console.log("Equality works");
if(a > b) console.log("Y value takes priority");
I am using the fact that if you bit shift two numbers X times and then add or subtract them before shifting them back, you will get the same result as if you hadn't shifted them to begin with. Similarly scalar multiplication and division works symmetrically for shifted values.
A JavaScript number has 52 bits of integer precision (64 bit floats), so I will pack one number into he higher available 26 bits, and one into the lower. The code is made a bit more messy because I wanted to support signed numbers.
function vec_pack(vec){
return vec[1] * 67108864 + (vec[0] < 0 ? 33554432 | vec[0] : vec[0]);
}
function vec_unpack(number){
switch(((number & 33554432) !== 0) * 1 + (number < 0) * 2){
case(0):
return [(number % 33554432),Math.trunc(number / 67108864)];
break;
case(1):
return [(number % 33554432)-33554432,Math.trunc(number / 67108864)+1];
break;
case(2):
return [(((number+33554432) % 33554432) + 33554432) % 33554432,Math.round(number / 67108864)];
break;
case(3):
return [(number % 33554432),Math.trunc(number / 67108864)];
break;
}
}
The only downside I can see with this is that the x and y has to be in the range +-33 million, since they have to fit within 26 bits each.
Actually, there is one variant of JavaScript that does support operator overloading. ExtendScript, the scripting language used by Adobe applications such as Photoshop and Illustrator, does have operator overloading. In it, you can write:
Vector2.prototype["+"] = function( b )
{
return new Vector2( this.x + b.x, this.y + b.y );
}
var a = new Vector2(1,1);
var b = new Vector2(2,2);
var c = a + b;
This is described in more detail in the "Adobe Extendscript JavaScript tools guide" (current link here). The syntax was apparently based on a (now long abandoned) draft of the ECMAScript standard.
FYI paper.js solves this issue by creating PaperScript, a self-contained, scoped javascript with operator overloading of vectors, which it then processing back into javascript.
But the paperscript files need to be specifically specified and processed as such.
We can use React-like Hooks to evaluate arrow function with different values from valueOf method on each iteration.
const a = Vector2(1, 2) // [1, 2]
const b = Vector2(2, 4) // [2, 4]
const c = Vector2(() => (2 * a + b) / 2) // [2, 4]
// There arrow function will iterate twice
// 1 iteration: method valueOf return X component
// 2 iteration: method valueOf return Y component
const Vector2 = (function() {
let index = -1
return function(x, y) {
if (typeof x === 'function') {
const calc = x
index = 0, x = calc()
index = 1, y = calc()
index = -1
}
return Object.assign([x, y], {
valueOf() {
return index == -1 ? this.toString() : this[index]
},
toString() {
return `[${this[0]}, ${this[1]}]`
},
len() {
return Math.sqrt(this[0] ** 2 + this[1] ** 2)
}
})
}
})()
const a = Vector2(1, 2)
const b = Vector2(2, 4)
console.log('a = ' + a) // a = [1, 2]
console.log(`b = ${b}`) // b = [2, 4]
const c = Vector2(() => (2 * a + b) / 2) // [2, 4]
a[0] = 12
const d = Vector2(() => (2 * a + b) / 2) // [13, 4]
const normalized = Vector2(() => d / d.len()) // [0.955..., 0.294...]
console.log(c, d, normalized)
Library #js-basics/vector uses the same idea for Vector3.
I wrote a library that exploits a bunch of evil hacks to do it in raw JS. It allows expressions like these.
Complex numbers:
>> Complex()({r: 2, i: 0} / {r: 1, i: 1} + {r: -3, i: 2}))
<- {r: -2, i: 1}
Automatic differentiation:
Let f(x) = x^3 - 5x:
>> var f = x => Dual()(x * x * x - {x:5, dx:0} * x);
Now map it over some values:
>> [-2,-1,0,1,2].map(a=>({x:a,dx:1})).map(f).map(a=>a.dx)
<- [ 7, -2, -5, -2, 7 ]
i.e. f'(x) = 3x^2 - 5.
Polynomials:
>> Poly()([1,-2,3,-4]*[5,-6]).map((c,p)=>''+c+'x^'+p).join(' + ')
<- "5x^0 + -16x^1 + 27x^2 + -38x^3 + 24x^4"
For your particular problem, you would define a Vector2 function (or maybe something shorter) using the library, then write x = Vector2()(x + y);
https://gist.github.com/pyrocto/5a068100abd5ff6dfbe69a73bbc510d7
Whilst not an exact answer to the question, it is possible to implement some of the python __magic__ methods using ES6 Symbols
A [Symbol.toPrimitive]() method doesn't let you imply a call Vector.add(), but will let you use syntax such as Decimal() + int.
class AnswerToLifeAndUniverseAndEverything {
[Symbol.toPrimitive](hint) {
if (hint === 'string') {
return 'Like, 42, man';
} else if (hint === 'number') {
return 42;
} else {
// when pushed, most classes (except Date)
// default to returning a number primitive
return 42;
}
}
}
https://www.keithcirkel.co.uk/metaprogramming-in-es6-symbols/
Interesting is also experimental library operator-overloading-js . It does overloading in a defined context (callback function) only.
I've been working with JavaScript for a few days now and have got to a point where I want to overload operators for my defined objects.
After a stint on google searching for this it seems you can't officially do this, yet there are a few people out there claiming some long-winded way of performing this action.
Basically I've made a Vector2 class and want to be able to do the following:
var x = new Vector2(10,10);
var y = new Vector2(10,10);
x += y; //This does not result in x being a vector with 20,20 as its x & y values.
Instead I'm having to do this:
var x = new Vector2(10,10);
var y = new Vector2(10,10);
x = x.add(y); //This results in x being a vector with 20,20 as its x & y values.
Is there an approach I can take to overload operators in my Vector2 class? As this just looks plain ugly.
As you've found, JavaScript doesn't support operator overloading. The closest you can come is to implement toString (which will get called when the instance needs to be coerced to being a string) and valueOf (which will get called to coerce it to a number, for instance when using + for addition, or in many cases when using it for concatenation because + tries to do addition before concatenation), which is pretty limited. Neither lets you create a Vector2 object as a result. Similarly, Proxy (added in ES2015) lets you intercept various object operations (including property access), but again won't let you control the result of += on Vector instances.
For people coming to this question who want a string or number as a result (instead of a Vector2), though, here are examples of valueOf and toString. These examples do not demonstrate operator overloading, just taking advantage of JavaScript's built-in handling converting to primitives:
valueOf
This example doubles the value of an object's val property in response to being coerced to a primitive, for instance via +:
function Thing(val) {
this.val = val;
}
Thing.prototype.valueOf = function() {
// Here I'm just doubling it; you'd actually do your longAdd thing
return this.val * 2;
};
var a = new Thing(1);
var b = new Thing(2);
console.log(a + b); // 6 (1 * 2 + 2 * 2)
Or with ES2015's class:
class Thing {
constructor(val) {
this.val = val;
}
valueOf() {
return this.val * 2;
}
}
const a = new Thing(1);
const b = new Thing(2);
console.log(a + b); // 6 (1 * 2 + 2 * 2)
Or just with objects, no constructors:
var thingPrototype = {
valueOf: function() {
return this.val * 2;
}
};
var a = Object.create(thingPrototype);
a.val = 1;
var b = Object.create(thingPrototype);
b.val = 2;
console.log(a + b); // 6 (1 * 2 + 2 * 2)
toString
This example converts the value of an object's val property to upper case in response to being coerced to a primitive, for instance via +:
function Thing(val) {
this.val = val;
}
Thing.prototype.toString = function() {
return this.val.toUpperCase();
};
var a = new Thing("a");
var b = new Thing("b");
console.log(a + b); // AB
Or with ES2015's class:
class Thing {
constructor(val) {
this.val = val;
}
toString() {
return this.val.toUpperCase();
}
}
const a = new Thing("a");
const b = new Thing("b");
console.log(a + b); // AB
Or just with objects, no constructors:
var thingPrototype = {
toString: function() {
return this.val.toUpperCase();
}
};
var a = Object.create(thingPrototype);
a.val = "a";
var b = Object.create(thingPrototype);
b.val = "b";
console.log(a + b); // AB
As T.J. said, you cannot overload operators in JavaScript. However you can take advantage of the valueOf function to write a hack which looks better than using functions like add every time, but imposes the constraints on the vector that the x and y are between 0 and MAX_VALUE. Here is the code:
var MAX_VALUE = 1000000;
var Vector = function(a, b) {
var self = this;
//initialize the vector based on parameters
if (typeof(b) == "undefined") {
//if the b value is not passed in, assume a is the hash of a vector
self.y = a % MAX_VALUE;
self.x = (a - self.y) / MAX_VALUE;
} else {
//if b value is passed in, assume the x and the y coordinates are the constructors
self.x = a;
self.y = b;
}
//return a hash of the vector
this.valueOf = function() {
return self.x * MAX_VALUE + self.y;
};
};
var V = function(a, b) {
return new Vector(a, b);
};
Then you can write equations like this:
var a = V(1, 2); //a -> [1, 2]
var b = V(2, 4); //b -> [2, 4]
var c = V((2 * a + b) / 2); //c -> [2, 4]
It's possible to do vector math with two numbers packed into one. Let me first show an example before I explain how it works:
let a = vec_pack([2,4]);
let b = vec_pack([1,2]);
let c = a+b; // Vector addition
let d = c-b; // Vector subtraction
let e = d*2; // Scalar multiplication
let f = e/2; // Scalar division
console.log(vec_unpack(c)); // [3, 6]
console.log(vec_unpack(d)); // [2, 4]
console.log(vec_unpack(e)); // [4, 8]
console.log(vec_unpack(f)); // [2, 4]
if(a === f) console.log("Equality works");
if(a > b) console.log("Y value takes priority");
I am using the fact that if you bit shift two numbers X times and then add or subtract them before shifting them back, you will get the same result as if you hadn't shifted them to begin with. Similarly scalar multiplication and division works symmetrically for shifted values.
A JavaScript number has 52 bits of integer precision (64 bit floats), so I will pack one number into he higher available 26 bits, and one into the lower. The code is made a bit more messy because I wanted to support signed numbers.
function vec_pack(vec){
return vec[1] * 67108864 + (vec[0] < 0 ? 33554432 | vec[0] : vec[0]);
}
function vec_unpack(number){
switch(((number & 33554432) !== 0) * 1 + (number < 0) * 2){
case(0):
return [(number % 33554432),Math.trunc(number / 67108864)];
break;
case(1):
return [(number % 33554432)-33554432,Math.trunc(number / 67108864)+1];
break;
case(2):
return [(((number+33554432) % 33554432) + 33554432) % 33554432,Math.round(number / 67108864)];
break;
case(3):
return [(number % 33554432),Math.trunc(number / 67108864)];
break;
}
}
The only downside I can see with this is that the x and y has to be in the range +-33 million, since they have to fit within 26 bits each.
Actually, there is one variant of JavaScript that does support operator overloading. ExtendScript, the scripting language used by Adobe applications such as Photoshop and Illustrator, does have operator overloading. In it, you can write:
Vector2.prototype["+"] = function( b )
{
return new Vector2( this.x + b.x, this.y + b.y );
}
var a = new Vector2(1,1);
var b = new Vector2(2,2);
var c = a + b;
This is described in more detail in the "Adobe Extendscript JavaScript tools guide" (current link here). The syntax was apparently based on a (now long abandoned) draft of the ECMAScript standard.
FYI paper.js solves this issue by creating PaperScript, a self-contained, scoped javascript with operator overloading of vectors, which it then processing back into javascript.
But the paperscript files need to be specifically specified and processed as such.
We can use React-like Hooks to evaluate arrow function with different values from valueOf method on each iteration.
const a = Vector2(1, 2) // [1, 2]
const b = Vector2(2, 4) // [2, 4]
const c = Vector2(() => (2 * a + b) / 2) // [2, 4]
// There arrow function will iterate twice
// 1 iteration: method valueOf return X component
// 2 iteration: method valueOf return Y component
const Vector2 = (function() {
let index = -1
return function(x, y) {
if (typeof x === 'function') {
const calc = x
index = 0, x = calc()
index = 1, y = calc()
index = -1
}
return Object.assign([x, y], {
valueOf() {
return index == -1 ? this.toString() : this[index]
},
toString() {
return `[${this[0]}, ${this[1]}]`
},
len() {
return Math.sqrt(this[0] ** 2 + this[1] ** 2)
}
})
}
})()
const a = Vector2(1, 2)
const b = Vector2(2, 4)
console.log('a = ' + a) // a = [1, 2]
console.log(`b = ${b}`) // b = [2, 4]
const c = Vector2(() => (2 * a + b) / 2) // [2, 4]
a[0] = 12
const d = Vector2(() => (2 * a + b) / 2) // [13, 4]
const normalized = Vector2(() => d / d.len()) // [0.955..., 0.294...]
console.log(c, d, normalized)
Library #js-basics/vector uses the same idea for Vector3.
I wrote a library that exploits a bunch of evil hacks to do it in raw JS. It allows expressions like these.
Complex numbers:
>> Complex()({r: 2, i: 0} / {r: 1, i: 1} + {r: -3, i: 2}))
<- {r: -2, i: 1}
Automatic differentiation:
Let f(x) = x^3 - 5x:
>> var f = x => Dual()(x * x * x - {x:5, dx:0} * x);
Now map it over some values:
>> [-2,-1,0,1,2].map(a=>({x:a,dx:1})).map(f).map(a=>a.dx)
<- [ 7, -2, -5, -2, 7 ]
i.e. f'(x) = 3x^2 - 5.
Polynomials:
>> Poly()([1,-2,3,-4]*[5,-6]).map((c,p)=>''+c+'x^'+p).join(' + ')
<- "5x^0 + -16x^1 + 27x^2 + -38x^3 + 24x^4"
For your particular problem, you would define a Vector2 function (or maybe something shorter) using the library, then write x = Vector2()(x + y);
https://gist.github.com/pyrocto/5a068100abd5ff6dfbe69a73bbc510d7
Whilst not an exact answer to the question, it is possible to implement some of the python __magic__ methods using ES6 Symbols
A [Symbol.toPrimitive]() method doesn't let you imply a call Vector.add(), but will let you use syntax such as Decimal() + int.
class AnswerToLifeAndUniverseAndEverything {
[Symbol.toPrimitive](hint) {
if (hint === 'string') {
return 'Like, 42, man';
} else if (hint === 'number') {
return 42;
} else {
// when pushed, most classes (except Date)
// default to returning a number primitive
return 42;
}
}
}
https://www.keithcirkel.co.uk/metaprogramming-in-es6-symbols/
Interesting is also experimental library operator-overloading-js . It does overloading in a defined context (callback function) only.
I have the following two scenarios where I want to compare a certain calculated value to float value 0.05.
In the first scenario, the value is being converted into String to get the value in two decimal place and then converting it back into a number for comparison.
var soneFunction = function(value)
{
var a = ((Math.round(value * 10) / 10) - value).toFixed(2);
if(Number(a) === 0.05)
a = -0.05;
return a;
};
In the second scenario, I am not doing any string-number conversion but using mathematical functions.
var soneFunction = function(value)
{
var roundingValue = (Math.round(value * 10) / 10) - value;
// fix the value till 2 decimal places
var a = Math.round((roundingValue) * 100) / 100;
if(a === 0.05)
a = -0.05;
return a;
};
I am curious to know which one is better?
UPDATE:
By better, I meant performance and memory consumption wise.
I think you can use
let parseFloatWithPrecision = function (value, precision){
var floatValue = parseFloat(value) || 0.0 ;
floatValue = floatValue.toFixed(precision);
return parseFloat(floatValue);
}
let compare = function(val){
if(parseFloatWithPrecision(val, 2) == 0.05)
return -0.05;
return val;
}
is there a JavaScript implementation of the Inverse Error Function?
This would implement the Gauss inverse error function. Approximations are ok.
Why yes. There is.
The following code uses built-in JavaScript functions and implments Abramowitz and Stegun's algorithm as described here:
function erfinv(x){
var z;
var a = 0.147;
var the_sign_of_x;
if(0==x) {
the_sign_of_x = 0;
} else if(x>0){
the_sign_of_x = 1;
} else {
the_sign_of_x = -1;
}
if(0 != x) {
var ln_1minus_x_sqrd = Math.log(1-x*x);
var ln_1minusxx_by_a = ln_1minus_x_sqrd / a;
var ln_1minusxx_by_2 = ln_1minus_x_sqrd / 2;
var ln_etc_by2_plus2 = ln_1minusxx_by_2 + (2/(Math.PI * a));
var first_sqrt = Math.sqrt((ln_etc_by2_plus2*ln_etc_by2_plus2)-ln_1minusxx_by_a);
var second_sqrt = Math.sqrt(first_sqrt - ln_etc_by2_plus2);
z = second_sqrt * the_sign_of_x;
} else { // x is zero
z = 0;
}
return z;
}
function provided earlier in this post did not work for me... NaN result on a 33meter circle with confidence 65% represented as 65.0 ... I wrote the following based on an equation listed here https://en.wikipedia.org/wiki/Error_function#Inverse_functions and it worked fine:
var _a = ((8*(Math.PI - 3)) / ((3*Math.PI)*(4 - Math.PI)));
function erfINV( inputX )
{
var _x = parseFloat(inputX);
var signX = ((_x < 0) ? -1.0 : 1.0 );
var oneMinusXsquared = 1.0 - (_x * _x);
var LNof1minusXsqrd = Math.log( oneMinusXsquared );
var PI_times_a = Math.PI * _a ;
var firstTerm = Math.pow(((2.0 / PI_times_a) + (LNof1minusXsqrd / 2.0)), 2);
var secondTerm = (LNof1minusXsqrd / _a);
var thirdTerm = ((2 / PI_times_a) + (LNof1minusXsqrd / 2.0));
var primaryComp = Math.sqrt( Math.sqrt( firstTerm - secondTerm ) - thirdTerm );
var scaled_R = signX * primaryComp ;
return scaled_R ;
}
Here's an alternative implementation of Abramowitz and Stegun's algorithm (equivalent to ptmalcolm's answer, but more succinct and twice as fast):
function erfinv(x) {
// maximum relative error = .00013
const a = 0.147
//if (0 == x) { return 0 }
const b = 2/(Math.PI * a) + Math.log(1-x**2)/2
const sqrt1 = Math.sqrt( b**2 - Math.log(1-x**2)/a )
const sqrt2 = Math.sqrt( sqrt1 - b )
return sqrt2 * Math.sign(x)
}
You can test the speed with console.time("erfinv"); for (let i=0; i<1000000000; i++) {erfinv(i/1000000000)}; console.timeEnd("erfinv")
The if statement optimization is commented out as it doesn't seem to make a difference - presumably the interpreter recognizes that this is all one equation.
If you need a more accurate approximation, check out Wikipedia.
I've become interested in algorithms lately, and the fibonacci sequence grabbed my attention due to its simplicity.
I've managed to put something together in javascript that calculates the nth term in the fibonacci sequence in less than 15 milliseconds after reading lots of information on the web. It goes up to 1476...1477 is infinity and 1478 is NaN (according to javascript!)
I'm quite proud of the code itself, except it's an utter monster.
So here's my question:
A) is there a faster way to calculate the sequence?
B) is there a faster/smaller way to multiply two matrices?
Here's the code:
//Fibonacci sequence generator in JS
//Cobbled together by Salty
m = [[1,0],[0,1]];
odd = [[1,1],[1,0]];
function matrix(a,b) {
/*
Matrix multiplication
Strassen Algorithm
Only works with 2x2 matrices.
*/
c=[[0,0],[0,0]];
c[0][0]=(a[0][0]*b[0][0])+(a[0][1]*b[1][0]);
c[0][1]=(a[0][0]*b[0][1])+(a[0][1]*b[1][1]);
c[1][0]=(a[1][0]*b[0][0])+(a[1][1]*b[1][0]);
c[1][1]=(a[1][0]*b[0][1])+(a[1][1]*b[1][1]);
m1=(a[0][0]+a[1][1])*(b[0][0]+b[1][1]);
m2=(a[1][0]+a[1][1])*b[0][0];
m3=a[0][0]*(b[0][1]-b[1][1]);
m4=a[1][1]*(b[1][0]-b[0][0]);
m5=(a[0][0]+a[0][1])*b[1][1];
m6=(a[1][0]-a[0][0])*(b[0][0]+b[0][1]);
m7=(a[0][1]-a[1][1])*(b[1][0]+b[1][1]);
c[0][0]=m1+m4-m5+m7;
c[0][1]=m3+m5;
c[1][0]=m2+m4;
c[1][1]=m1-m2+m3+m6;
return c;
}
function fib(n) {
mat(n-1);
return m[0][0];
}
function mat(n) {
if(n > 1) {
mat(n/2);
m = matrix(m,m);
}
m = (n%2<1) ? m : matrix(m,odd);
}
alert(fib(1476)); //Alerts 1.3069892237633993e+308
The matrix function takes two arguments: a and b, and returns a*b where a and b are 2x2 arrays.
Oh, and on a side note, a magical thing happened...I was converting the Strassen algorithm into JS array notation and it worked on my first try! Fantastic, right? :P
Thanks in advance if you manage to find an easier way to do this.
Don't speculate, benchmark:
edit: I added my own matrix implementation using the optimized multiplication functions mentioned in my other answer. This resulted in a major speedup, but even the vanilla O(n^3) implementation of matrix multiplication with loops was faster than the Strassen algorithm.
<pre><script>
var fib = {};
(function() {
var sqrt_5 = Math.sqrt(5),
phi = (1 + sqrt_5) / 2;
fib.round = function(n) {
return Math.floor(Math.pow(phi, n) / sqrt_5 + 0.5);
};
})();
(function() {
fib.loop = function(n) {
var i = 0,
j = 1;
while(n--) {
var tmp = i;
i = j;
j += tmp;
}
return i;
};
})();
(function () {
var cache = [0, 1];
fib.loop_cached = function(n) {
if(n >= cache.length) {
for(var i = cache.length; i <= n; ++i)
cache[i] = cache[i - 1] + cache[i - 2];
}
return cache[n];
};
})();
(function() {
//Fibonacci sequence generator in JS
//Cobbled together by Salty
var m;
var odd = [[1,1],[1,0]];
function matrix(a,b) {
/*
Matrix multiplication
Strassen Algorithm
Only works with 2x2 matrices.
*/
var c=[[0,0],[0,0]];
var m1=(a[0][0]+a[1][1])*(b[0][0]+b[1][1]);
var m2=(a[1][0]+a[1][1])*b[0][0];
var m3=a[0][0]*(b[0][1]-b[1][1]);
var m4=a[1][1]*(b[1][0]-b[0][0]);
var m5=(a[0][0]+a[0][1])*b[1][1];
var m6=(a[1][0]-a[0][0])*(b[0][0]+b[0][1]);
var m7=(a[0][1]-a[1][1])*(b[1][0]+b[1][1]);
c[0][0]=m1+m4-m5+m7;
c[0][1]=m3+m5;
c[1][0]=m2+m4;
c[1][1]=m1-m2+m3+m6;
return c;
}
function mat(n) {
if(n > 1) {
mat(n/2);
m = matrix(m,m);
}
m = (n%2<1) ? m : matrix(m,odd);
}
fib.matrix = function(n) {
m = [[1,0],[0,1]];
mat(n-1);
return m[0][0];
};
})();
(function() {
var a;
function square() {
var a00 = a[0][0],
a01 = a[0][1],
a10 = a[1][0],
a11 = a[1][1];
var a10_x_a01 = a10 * a01,
a00_p_a11 = a00 + a11;
a[0][0] = a10_x_a01 + a00 * a00;
a[0][1] = a00_p_a11 * a01;
a[1][0] = a00_p_a11 * a10;
a[1][1] = a10_x_a01 + a11 * a11;
}
function powPlusPlus() {
var a01 = a[0][1],
a11 = a[1][1];
a[0][1] = a[0][0];
a[1][1] = a[1][0];
a[0][0] += a01;
a[1][0] += a11;
}
function compute(n) {
if(n > 1) {
compute(n >> 1);
square();
if(n & 1)
powPlusPlus();
}
}
fib.matrix_optimised = function(n) {
if(n == 0)
return 0;
a = [[1, 1], [1, 0]];
compute(n - 1);
return a[0][0];
};
})();
(function() {
var cache = {};
cache[0] = [[1, 0], [0, 1]];
cache[1] = [[1, 1], [1, 0]];
function mult(a, b) {
return [
[a[0][0] * b[0][0] + a[0][1] * b[1][0],
a[0][0] * b[0][1] + a[0][1] * b[1][1]],
[a[1][0] * b[0][0] + a[1][1] * b[1][0],
a[1][0] * b[0][1] + a[1][1] * b[1][1]]
];
}
function compute(n) {
if(!cache[n]) {
var n_2 = n >> 1;
compute(n_2);
cache[n] = mult(cache[n_2], cache[n_2]);
if(n & 1)
cache[n] = mult(cache[1], cache[n]);
}
}
fib.matrix_cached = function(n) {
if(n == 0)
return 0;
compute(--n);
return cache[n][0][0];
};
})();
function test(name, func, n, count) {
var value;
var start = Number(new Date);
while(count--)
value = func(n);
var end = Number(new Date);
return 'fib.' + name + '(' + n + ') = ' + value + ' [' +
(end - start) + 'ms]';
}
for(var func in fib)
document.writeln(test(func, fib[func], 1450, 10000));
</script></pre>
yields
fib.round(1450) = 4.8149675025003456e+302 [20ms]
fib.loop(1450) = 4.81496750250011e+302 [4035ms]
fib.loop_cached(1450) = 4.81496750250011e+302 [8ms]
fib.matrix(1450) = 4.814967502500118e+302 [2201ms]
fib.matrix_optimised(1450) = 4.814967502500113e+302 [585ms]
fib.matrix_cached(1450) = 4.814967502500113e+302 [12ms]
Your algorithm is nearly as bad as uncached looping. Caching is your best bet, closely followed by the rounding algorithm - which yields incorrect results for big n (as does your matrix algorithm).
For smaller n, your algorithm performs even worse than everything else:
fib.round(100) = 354224848179263100000 [20ms]
fib.loop(100) = 354224848179262000000 [248ms]
fib.loop_cached(100) = 354224848179262000000 [6ms]
fib.matrix(100) = 354224848179261900000 [1911ms]
fib.matrix_optimised(100) = 354224848179261900000 [380ms]
fib.matrix_cached(100) = 354224848179261900000 [12ms]
There is a closed form (no loops) solution for the nth Fibonacci number.
See Wikipedia.
There may well be a faster way to calculate the values but I don't believe it's necessary.
Calculate them once and, in your program, output the results as the fibdata line below:
fibdata = [1,1,2,3,5,8,13, ... , 1.3069892237633993e+308]; // 1476 entries.
function fib(n) {
if ((n < 0) || (n > 1476)) {
** Do something exception-like or return INF;
}
return fibdata[n];
}
Then, that's the code you ship to your clients. That's an O(1) solution for you.
People often overlook the 'caching' solution. I once had to write trigonometry routines for an embedded system and, rather than using infinite series to calculate them on the fly, I just had a few lookup tables, 360 entries in each for each of the degrees of input.
Needless to say, it screamed along, at the cost of only about 1K of RAM. The values were stored as 1-byte entries, [actual value (0-1) * 16] so we could just do a lookup, multiply and bit shift to get the desired value.
My previous answer got a bit crowded, so I'll post a new one:
You can speed up your algorithm by using vanilla 2x2 matrix multiplication - ie replace your matrix() function with this:
function matrix(a, b) {
return [
[a[0][0] * b[0][0] + a[0][1] * b[1][0],
a[0][0] * b[0][1] + a[0][1] * b[1][1]],
[a[1][0] * b[0][0] + a[1][1] * b[1][0],
a[1][0] * b[0][1] + a[1][1] * b[1][1]]
];
}
If you care for accuracy and speed, use the caching solution. If accuracy isn't a concern, but memory consumption is, use the rounding solution. The matrix solution only makes sense if you want results for big n fast, don't care for accuracy and don't want to call the function repeatedly.
edit: You can even further speed up the computation if you use specialised multiplication functions, eliminate common subexpressions and replace the values in the existing array instead of creating a new array:
function square() {
var a00 = a[0][0],
a01 = a[0][1],
a10 = a[1][0],
a11 = a[1][1];
var a10_x_a01 = a10 * a01,
a00_p_a11 = a00 + a11;
a[0][0] = a10_x_a01 + a00 * a00;
a[0][1] = a00_p_a11 * a01;
a[1][0] = a00_p_a11 * a10;
a[1][1] = a10_x_a01 + a11 * a11;
}
function powPlusPlus() {
var a01 = a[0][1],
a11 = a[1][1];
a[0][1] = a[0][0];
a[1][1] = a[1][0];
a[0][0] += a01;
a[1][0] += a11;
}
Note: a is the name of the global matrix variable.
Closed form solution in JavaScript: O(1), accurate up for n=75
function fib(n){
var sqrt5 = Math.sqrt(5);
var a = (1 + sqrt5)/2;
var b = (1 - sqrt5)/2;
var ans = Math.round((Math.pow(a, n) - Math.pow(b, n))/sqrt5);
return ans;
}
Granted, even multiplication starts to take its expense when dealing with huge numbers, but this will give you the answer. As far as I know, because of JavaScript rounding the values, it's only accurate up to n = 75. Past that, you'll get a good estimate, but it won't be totally accurate unless you want to do something tricky like store the values as a string then parse those as BigIntegers.
How about memoizing the results that where already calculated, like such:
var IterMemoFib = function() {
var cache = [1, 1];
var fib = function(n) {
if (n >= cache.length) {
for (var i = cache.length; i <= n; i++) {
cache[i] = cache[i - 2] + cache[i - 1];
}
}
return cache[n];
}
return fib;
}();
Or if you want a more generic memoization function, extend the Function prototype:
Function.prototype.memoize = function() {
var pad = {};
var self = this;
var obj = arguments.length > 0 ? arguments[i] : null;
var memoizedFn = function() {
// Copy the arguments object into an array: allows it to be used as
// a cache key.
var args = [];
for (var i = 0; i < arguments.length; i++) {
args[i] = arguments[i];
}
// Evaluate the memoized function if it hasn't been evaluated with
// these arguments before.
if (!(args in pad)) {
pad[args] = self.apply(obj, arguments);
}
return pad[args];
}
memoizedFn.unmemoize = function() {
return self;
}
return memoizedFn;
}
//Now, you can apply the memoized function to a normal fibonacci function like such:
Fib = fib.memoize();
One note to add is that due to technical (browser security) constraints, the arguments for memoized functions can only be arrays or scalar values. No objects.
Reference: http://talideon.com/weblog/2005/07/javascript-memoization.cfm
To expand a bit on Dreas's answer:
1) cache should start as [0, 1]
2) what do you do with IterMemoFib(5.5)? (cache[5.5] == undefined)
fibonacci = (function () {
var FIB = [0, 1];
return function (x) {
if ((typeof(x) !== 'number') || (x < 0)) return;
x = Math.floor(x);
if (x >= FIB.length)
for (var i = FIB.length; i <= x; i += 1)
FIB[i] = FIB[i-1] + FIB[i-2];
return FIB[x];
}
})();
alert(fibonacci(17)); // 1597 (FIB => [0, 1, ..., 1597]) (length = 17)
alert(fibonacci(400)); // 1.760236806450138e+83 (finds 18 to 400)
alert(fibonacci(1476)); // 1.3069892237633987e+308 (length = 1476)
If you don't like silent errors:
// replace...
if ((typeof(x) !== 'number') || (x < 0)) return;
// with...
if (typeof(x) !== 'number') throw new TypeError('Not a Number.');
if (x < 0) throw new RangeError('Not a possible fibonacci index. (' + x + ')');
Here is a very fast solution of calculating the fibonacci sequence
function fib(n){
var start = Number(new Date);
var field = new Array();
field[0] = 0;
field[1] = 1;
for(var i=2; i<=n; i++)
field[i] = field[i-2] + field[i-1]
var end = Number(new Date);
return 'fib' + '(' + n + ') = ' + field[n] + ' [' +
(end - start) + 'ms]';
}
var f = fib(1450)
console.log(f)
I've just written my own little implementation using an Object to store already computed results. I've written it in Node.JS, which needed 2ms (according to my timer) to calculate the fibonacci for 1476.
Here's the code stripped down to pure Javascript:
var nums = {}; // Object that stores already computed fibonacci results
function fib(n) { //Function
var ret; //Variable that holds the return Value
if (n < 3) return 1; //Fib of 1 and 2 equal 1 => filtered here
else if (nums.hasOwnProperty(n)) ret = nums[n]; /*if the requested number is
already in the object nums, return it from the object, instead of computing */
else ret = fib( n - 2 ) + fib( n - 1 ); /* if requested number has not
yet been calculated, do so here */
nums[n] = ret; // add calculated number to nums objecti
return ret; //return the value
}
//and finally the function call:
fib(1476)
EDIT: I did not try running this in a Browser!
EDIT again: now I did. try the jsfiddle: jsfiddle fibonacci Time varies between 0 and 2ms
Much faster algorithm:
const fib = n => fib[n] || (fib[n-1] = fib(n-1)) + fib[n-2];
fib[0] = 0; // Any number you like
fib[1] = 1; // Any number you like