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const arr1 = [4, 23, 7, 6, 3, 6, 4, 3, 56, 4]; const arr2 = [4, 56, 23]; We are required to write a JavaScript function that takes in these two arrays and filters the first to contain only those elements that are not present in the second array.
Filter an array containing objects based on another array containing objects in JavaScript. const arr1 = [{id:'1',name:'A'},{id:'2',name:'B'},{id:'3',name:'C'},{id:'4',name:'D'}]; const arr2 = [{id:'1',name:'A',state:'healthy'},{id:'3',name:'C',state:'healthy'}];
ES6 | Array filter() Method Callback: The function is a predicate, to test each element of the array. Return true to keep the element, false otherwise. It accepts three arguments: element: The current element being processed in the array.
I would do as follows;
var arr1 = [1,2,3,4],
arr2 = [2,4],
res = arr1.filter(item => !arr2.includes(item));
console.log(res);You can use the this parameter of the filter() function to avoid to store your filter array in a global variable.
var filtered = [1, 2, 3, 4].filter(
function(e) {
return this.indexOf(e) < 0;
},
[2, 4]
);
console.log(filtered);var array = [1,2,3,4];
var anotherOne = [2,4];
var filteredArray = array.filter(myCallBack);
function myCallBack(el){
return anotherOne.indexOf(el) < 0;
}
In the callback, you check if each value of array is in anotherOne
https://jsfiddle.net/0tsyc1sx/
If you are using lodash.js, use _.difference
filteredArray = _.difference(array, anotherOne);
Demo
If you have an array of objects :
var array = [{id :1, name :"test1"},{id :2, name :"test2"},{id :3, name :"test3"},{id :4, name :"test4"}];
var anotherOne = [{id :2, name :"test2"}, {id :4, name :"test4"}];
var filteredArray = array.filter(function(array_el){
return anotherOne.filter(function(anotherOne_el){
return anotherOne_el.id == array_el.id;
}).length == 0
});
Demo array of objects
Demo diff array of objects with lodash
/* Here's an example that uses (some) ES6 Javascript semantics to filter an object array by another object array. */
// x = full dataset
// y = filter dataset
let x = [
{"val": 1, "text": "a"},
{"val": 2, "text": "b"},
{"val": 3, "text": "c"},
{"val": 4, "text": "d"},
{"val": 5, "text": "e"}
],
y = [
{"val": 1, "text": "a"},
{"val": 4, "text": "d"}
];
// Use map to get a simple array of "val" values. Ex: [1,4]
let yFilter = y.map(itemY => { return itemY.val; });
// Use filter and "not" includes to filter the full dataset by the filter dataset's val.
let filteredX = x.filter(itemX => !yFilter.includes(itemX.val));
// Print the result.
console.log(filteredX);The code below is the simplest way to filter an array with respect to another array. Both arrays can have objects inside them instead of values.
let array1 = [1, 3, 47, 1, 6, 7];
let array2 = [3, 6];
let filteredArray1 = array1.filter(el => array2.includes(el));
console.log(filteredArray1); Output: [3, 6]
All the above solutions "work", but are less than optimal for performance and are all approach the problem in the same way which is linearly searching all entries at each point using Array.prototype.indexOf or Array.prototype.includes. A far faster solution (far faster even than a binary search for most cases) would be to sort the arrays and skip ahead as you go along as seen below. However, one downside is that this requires all entries in the array to be numbers or strings. Also however, binary search may in some rare cases be faster than the progressive linear search. These cases arise from the fact that my progressive linear search has a complexity of O(2n1+n2) (only O(n1+n2) in the faster C/C++ version) (where n1 is the searched array and n2 is the filter array), whereas the binary search has a complexity of O(n1ceil(log2n2)) (ceil = round up -- to the ceiling), and, lastly, the indexOf search has a highly variable complexity between O(n1) and O(n1n2), averaging out to O(n1ceil(n2÷2)). Thus, indexOf will only be the fastest, on average, in the cases of (n1,n2) equaling {1,2}, {1,3}, or {x,1|x∈N}. However, this is still not a perfect representation of modern hardware. IndexOf is natively optimized to the fullest extent imaginable in most modern browsers, making it very subject to the laws of branch prediction. Thus, if we make the same assumption on indexOf as we do with progressive linear and binary search -- that the array is presorted -- then, according to the stats listed in the link, we can expect roughly a 6x speed up for IndexOf, shifting its complexity to between O(n1÷6) and O(n1n2), averaging out to O(n1ceil(n27÷12)). Finally, take note that the below solution will never work with objects because objects in JavaScript cannot be compared by pointers in JavaScript.
function sortAnyArray(a,b) { return a>b ? 1 : (a===b ? 0 : -1); }
function sortIntArray(a,b) { return (a|0) - (b|0) |0; }
function fastFilter(array, handle) {
var out=[], value=0;
for (var i=0, len=array.length|0; i < len; i=i+1|0)
if (handle(value = array[i]))
out.push( value );
return out;
}
const Math_clz32 = Math.clz32 || (function(log, LN2){
return function(x) {
return 31 - log(x >>> 0) / LN2 | 0; // the "| 0" acts like math.floor
};
})(Math.log, Math.LN2);
/* USAGE:
filterArrayByAnotherArray(
[1,3,5],
[2,3,4]
) yields [1, 5], and it can work with strings too
*/
function filterArrayByAnotherArray(searchArray, filterArray) {
if (
// NOTE: This does not check the whole array. But, if you know
// that there are only strings or numbers (not a mix of
// both) in the array, then this is a safe assumption.
// Always use `==` with `typeof` because browsers can optimize
// the `==` into `===` (ONLY IN THIS CIRCUMSTANCE)
typeof searchArray[0] == "number" &&
typeof filterArray[0] == "number" &&
(searchArray[0]|0) === searchArray[0] &&
(filterArray[0]|0) === filterArray[0]
) {filterArray
// if all entries in both arrays are integers
searchArray.sort(sortIntArray);
filterArray.sort(sortIntArray);
} else {
searchArray.sort(sortAnyArray);
filterArray.sort(sortAnyArray);
}
var searchArrayLen = searchArray.length, filterArrayLen = filterArray.length;
var progressiveLinearComplexity = ((searchArrayLen<<1) + filterArrayLen)>>>0
var binarySearchComplexity= (searchArrayLen * (32-Math_clz32(filterArrayLen-1)))>>>0;
// After computing the complexity, we can predict which algorithm will be the fastest
var i = 0;
if (progressiveLinearComplexity < binarySearchComplexity) {
// Progressive Linear Search
return fastFilter(searchArray, function(currentValue){
while (filterArray[i] < currentValue) i=i+1|0;
// +undefined = NaN, which is always false for <, avoiding an infinite loop
return filterArray[i] !== currentValue;
});
} else {
// Binary Search
return fastFilter(
searchArray,
fastestBinarySearch(filterArray)
);
}
}
// see https://stackoverflow.com/a/44981570/5601591 for implementation
// details about this binary search algorithm
function fastestBinarySearch(array){
var initLen = (array.length|0) - 1 |0;
const compGoto = Math_clz32(initLen) & 31;
return function(sValue) {
var len = initLen |0;
switch (compGoto) {
case 0:
if (len & 0x80000000) {
const nCB = len & 0x80000000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 1:
if (len & 0x40000000) {
const nCB = len & 0xc0000000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 2:
if (len & 0x20000000) {
const nCB = len & 0xe0000000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 3:
if (len & 0x10000000) {
const nCB = len & 0xf0000000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 4:
if (len & 0x8000000) {
const nCB = len & 0xf8000000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 5:
if (len & 0x4000000) {
const nCB = len & 0xfc000000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 6:
if (len & 0x2000000) {
const nCB = len & 0xfe000000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 7:
if (len & 0x1000000) {
const nCB = len & 0xff000000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 8:
if (len & 0x800000) {
const nCB = len & 0xff800000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 9:
if (len & 0x400000) {
const nCB = len & 0xffc00000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 10:
if (len & 0x200000) {
const nCB = len & 0xffe00000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 11:
if (len & 0x100000) {
const nCB = len & 0xfff00000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 12:
if (len & 0x80000) {
const nCB = len & 0xfff80000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 13:
if (len & 0x40000) {
const nCB = len & 0xfffc0000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 14:
if (len & 0x20000) {
const nCB = len & 0xfffe0000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 15:
if (len & 0x10000) {
const nCB = len & 0xffff0000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 16:
if (len & 0x8000) {
const nCB = len & 0xffff8000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 17:
if (len & 0x4000) {
const nCB = len & 0xffffc000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 18:
if (len & 0x2000) {
const nCB = len & 0xffffe000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 19:
if (len & 0x1000) {
const nCB = len & 0xfffff000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 20:
if (len & 0x800) {
const nCB = len & 0xfffff800;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 21:
if (len & 0x400) {
const nCB = len & 0xfffffc00;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 22:
if (len & 0x200) {
const nCB = len & 0xfffffe00;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 23:
if (len & 0x100) {
const nCB = len & 0xffffff00;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 24:
if (len & 0x80) {
const nCB = len & 0xffffff80;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 25:
if (len & 0x40) {
const nCB = len & 0xffffffc0;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 26:
if (len & 0x20) {
const nCB = len & 0xffffffe0;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 27:
if (len & 0x10) {
const nCB = len & 0xfffffff0;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 28:
if (len & 0x8) {
const nCB = len & 0xfffffff8;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 29:
if (len & 0x4) {
const nCB = len & 0xfffffffc;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 30:
if (len & 0x2) {
const nCB = len & 0xfffffffe;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 31:
if (len & 0x1) {
const nCB = len & 0xffffffff;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
}
// MODIFICATION: Instead of returning the index, this binary search
// instead returns whether something was found or not.
if (array[len|0] !== sValue) {
return true; // preserve the value at this index
} else {
return false; // eliminate the value at this index
}
};
}
Please see my other post here for more details on the binary search algorithm used
If you are squeamish about file size (which I respect), then you can sacrifice a little performance in order to greatly reduce the file size and increase maintainability.
function sortAnyArray(a,b) { return a>b ? 1 : (a===b ? 0 : -1); }
function sortIntArray(a,b) { return (a|0) - (b|0) |0; }
function fastFilter(array, handle) {
var out=[], value=0;
for (var i=0, len=array.length|0; i < len; i=i+1|0)
if (handle(value = array[i]))
out.push( value );
return out;
}
/* USAGE:
filterArrayByAnotherArray(
[1,3,5],
[2,3,4]
) yields [1, 5], and it can work with strings too
*/
function filterArrayByAnotherArray(searchArray, filterArray) {
if (
// NOTE: This does not check the whole array. But, if you know
// that there are only strings or numbers (not a mix of
// both) in the array, then this is a safe assumption.
typeof searchArray[0] == "number" &&
typeof filterArray[0] == "number" &&
(searchArray[0]|0) === searchArray[0] &&
(filterArray[0]|0) === filterArray[0]
) {
// if all entries in both arrays are integers
searchArray.sort(sortIntArray);
filterArray.sort(sortIntArray);
} else {
searchArray.sort(sortAnyArray);
filterArray.sort(sortAnyArray);
}
// Progressive Linear Search
var i = 0;
return fastFilter(searchArray, function(currentValue){
while (filterArray[i] < currentValue) i=i+1|0;
// +undefined = NaN, which is always false for <, avoiding an infinite loop
return filterArray[i] !== currentValue;
});
}
To prove the difference in speed, let us examine some JSPerfs. For filtering an array of 16 elements, binary search is roughly 17% faster than indexOf while filterArrayByAnotherArray is roughly 93% faster than indexOf. For filtering an array of 256 elements, binary search is roughly 291% faster than indexOf while filterArrayByAnotherArray is roughly 353% faster than indexOf. For filtering an array of 4096 elements, binary search is roughly 2655% faster than indexOf while filterArrayByAnotherArray is roughly 4627% faster than indexOf.
The previous section provided code to take array A and array B, and remove all elements from A that exist in B:
filterArrayByAnotherArray(
[1,3,5],
[2,3,4]
);
// yields [1, 5]
This next section will provide code for reverse-filtering, where we remove all elements from A that DO NOT exist in B. This process is functionally equivalent to only retaining the elements common to both A and B, like an AND gate:
reverseFilterArrayByAnotherArray(
[1,3,5],
[2,3,4]
);
// yields [3]
Here is the code for reverse filtering:
function sortAnyArray(a,b) { return a>b ? 1 : (a===b ? 0 : -1); }
function sortIntArray(a,b) { return (a|0) - (b|0) |0; }
function fastFilter(array, handle) {
var out=[], value=0;
for (var i=0, len=array.length|0; i < len; i=i+1|0)
if (handle(value = array[i]))
out.push( value );
return out;
}
const Math_clz32 = Math.clz32 || (function(log, LN2){
return function(x) {
return 31 - log(x >>> 0) / LN2 | 0; // the "| 0" acts like math.floor
};
})(Math.log, Math.LN2);
/* USAGE:
reverseFilterArrayByAnotherArray(
[1,3,5],
[2,3,4]
) yields [3], and it can work with strings too
*/
function reverseFilterArrayByAnotherArray(searchArray, filterArray) {
if (
// NOTE: This does not check the whole array. But, if you know
// that there are only strings or numbers (not a mix of
// both) in the array, then this is a safe assumption.
// Always use `==` with `typeof` because browsers can optimize
// the `==` into `===` (ONLY IN THIS CIRCUMSTANCE)
typeof searchArray[0] == "number" &&
typeof filterArray[0] == "number" &&
(searchArray[0]|0) === searchArray[0] &&
(filterArray[0]|0) === filterArray[0]
) {
// if all entries in both arrays are integers
searchArray.sort(sortIntArray);
filterArray.sort(sortIntArray);
} else {
searchArray.sort(sortAnyArray);
filterArray.sort(sortAnyArray);
}
var searchArrayLen = searchArray.length, filterArrayLen = filterArray.length;
var progressiveLinearComplexity = ((searchArrayLen<<1) + filterArrayLen)>>>0
var binarySearchComplexity= (searchArrayLen * (32-Math_clz32(filterArrayLen-1)))>>>0;
// After computing the complexity, we can predict which algorithm will be the fastest
var i = 0;
if (progressiveLinearComplexity < binarySearchComplexity) {
// Progressive Linear Search
return fastFilter(searchArray, function(currentValue){
while (filterArray[i] < currentValue) i=i+1|0;
// +undefined = NaN, which is always false for <, avoiding an infinite loop
// For reverse filterning, I changed !== to ===
return filterArray[i] === currentValue;
});
} else {
// Binary Search
return fastFilter(
searchArray,
inverseFastestBinarySearch(filterArray)
);
}
}
// see https://stackoverflow.com/a/44981570/5601591 for implementation
// details about this binary search algorithim
function inverseFastestBinarySearch(array){
var initLen = (array.length|0) - 1 |0;
const compGoto = Math_clz32(initLen) & 31;
return function(sValue) {
var len = initLen |0;
switch (compGoto) {
case 0:
if (len & 0x80000000) {
const nCB = len & 0x80000000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 1:
if (len & 0x40000000) {
const nCB = len & 0xc0000000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 2:
if (len & 0x20000000) {
const nCB = len & 0xe0000000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 3:
if (len & 0x10000000) {
const nCB = len & 0xf0000000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 4:
if (len & 0x8000000) {
const nCB = len & 0xf8000000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 5:
if (len & 0x4000000) {
const nCB = len & 0xfc000000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 6:
if (len & 0x2000000) {
const nCB = len & 0xfe000000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 7:
if (len & 0x1000000) {
const nCB = len & 0xff000000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 8:
if (len & 0x800000) {
const nCB = len & 0xff800000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 9:
if (len & 0x400000) {
const nCB = len & 0xffc00000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 10:
if (len & 0x200000) {
const nCB = len & 0xffe00000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 11:
if (len & 0x100000) {
const nCB = len & 0xfff00000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 12:
if (len & 0x80000) {
const nCB = len & 0xfff80000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 13:
if (len & 0x40000) {
const nCB = len & 0xfffc0000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 14:
if (len & 0x20000) {
const nCB = len & 0xfffe0000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 15:
if (len & 0x10000) {
const nCB = len & 0xffff0000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 16:
if (len & 0x8000) {
const nCB = len & 0xffff8000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 17:
if (len & 0x4000) {
const nCB = len & 0xffffc000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 18:
if (len & 0x2000) {
const nCB = len & 0xffffe000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 19:
if (len & 0x1000) {
const nCB = len & 0xfffff000;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 20:
if (len & 0x800) {
const nCB = len & 0xfffff800;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 21:
if (len & 0x400) {
const nCB = len & 0xfffffc00;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 22:
if (len & 0x200) {
const nCB = len & 0xfffffe00;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 23:
if (len & 0x100) {
const nCB = len & 0xffffff00;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 24:
if (len & 0x80) {
const nCB = len & 0xffffff80;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 25:
if (len & 0x40) {
const nCB = len & 0xffffffc0;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 26:
if (len & 0x20) {
const nCB = len & 0xffffffe0;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 27:
if (len & 0x10) {
const nCB = len & 0xfffffff0;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 28:
if (len & 0x8) {
const nCB = len & 0xfffffff8;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 29:
if (len & 0x4) {
const nCB = len & 0xfffffffc;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 30:
if (len & 0x2) {
const nCB = len & 0xfffffffe;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
case 31:
if (len & 0x1) {
const nCB = len & 0xffffffff;
len ^= (len ^ (nCB-1)) & ((array[nCB] <= sValue |0) - 1 >>>0);
}
}
// MODIFICATION: Instead of returning the index, this binary search
// instead returns whether something was found or not.
// For reverse filterning, I swapped true with false and vice-versa
if (array[len|0] !== sValue) {
return false; // preserve the value at this index
} else {
return true; // eliminate the value at this index
}
};
}
For the slower smaller version of the reverse filtering code, see below.
function sortAnyArray(a,b) { return a>b ? 1 : (a===b ? 0 : -1); }
function sortIntArray(a,b) { return (a|0) - (b|0) |0; }
function fastFilter(array, handle) {
var out=[], value=0;
for (var i=0, len=array.length|0; i < len; i=i+1|0)
if (handle(value = array[i]))
out.push( value );
return out;
}
/* USAGE:
reverseFilterArrayByAnotherArray(
[1,3,5],
[2,3,4]
) yields [3], and it can work with strings too
*/
function reverseFilterArrayByAnotherArray(searchArray, filterArray) {
if (
// NOTE: This does not check the whole array. But, if you know
// that there are only strings or numbers (not a mix of
// both) in the array, then this is a safe assumption.
typeof searchArray[0] == "number" &&
typeof filterArray[0] == "number" &&
(searchArray[0]|0) === searchArray[0] &&
(filterArray[0]|0) === filterArray[0]
) {
// if all entries in both arrays are integers
searchArray.sort(sortIntArray);
filterArray.sort(sortIntArray);
} else {
searchArray.sort(sortAnyArray);
filterArray.sort(sortAnyArray);
}
// Progressive Linear Search
var i = 0;
return fastFilter(searchArray, function(currentValue){
while (filterArray[i] < currentValue) i=i+1|0;
// +undefined = NaN, which is always false for <, avoiding an infinite loop
// For reverse filter, I changed !== to ===
return filterArray[i] === currentValue;
});
}
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