为了推断Felix Kling的评论，你可以像这样使用.filter():

var sources = images.map(function (img) {
  if(img.src.split('.').pop() === "json") { // if extension is .json
    return null; // skip
  } else {
    return img.src;
  }
}).filter(Boolean);

这将从.map()返回的数组中删除错误值。

你可以进一步简化如下:

var sources = images.map(function (img) {
  if(img.src.split('.').pop() !== "json") { // if extension is .json
    return img.src;
  }
}).filter(Boolean);

甚至可以使用箭头函数、对象解构和&&操作符作为一行代码:

var sources = images.map(({ src }) => src.split('.').pop() !== "json" && src).filter(Boolean);

下面是@theprtk提供的代码的更新版本。这是一个小清理，以显示广义版本，同时有一个例子。

注:我想把这句话作为评论加到他的帖子里，但我还没有足够的声誉

/**
 * @see http://clojure.com/blog/2012/05/15/anatomy-of-reducer.html
 * @description functions that transform reducing functions
 */
const transduce = {
  /** a generic map() that can take a reducing() & return another reducing() */
  map: changeInput => reducing => (acc, input) =>
    reducing(acc, changeInput(input)),
  /** a generic filter() that can take a reducing() & return */
  filter: predicate => reducing => (acc, input) =>
    predicate(input) ? reducing(acc, input) : acc,
  /**
   * a composing() that can take an infinite # transducers to operate on
   *  reducing functions to compose a computed accumulator without ever creating
   *  that intermediate array
   */
  compose: (...args) => x => {
    const fns = args;
    var i = fns.length;
    while (i--) x = fns[i].call(this, x);
    return x;
  },
};

const example = {
  data: [{ src: 'file.html' }, { src: 'file.txt' }, { src: 'file.json' }],
  /** note: `[1,2,3].reduce(concat, [])` -> `[1,2,3]` */
  concat: (acc, input) => acc.concat([input]),
  getSrc: x => x.src,
  filterJson: x => x.src.split('.').pop() !== 'json',
};

/** step 1: create a reducing() that can be passed into `reduce` */
const reduceFn = example.concat;
/** step 2: transforming your reducing function by mapping */
const mapFn = transduce.map(example.getSrc);
/** step 3: create your filter() that operates on an input */
const filterFn = transduce.filter(example.filterJson);
/** step 4: aggregate your transformations */
const composeFn = transduce.compose(
  filterFn,
  mapFn,
  transduce.map(x => x.toUpperCase() + '!'), // new mapping()
);

/**
 * Expected example output
 *  Note: each is wrapped in `example.data.reduce(x, [])`
 *  1: ['file.html', 'file.txt', 'file.json']
 *  2:  ['file.html', 'file.txt']
 *  3: ['FILE.HTML!', 'FILE.TXT!']
 */
const exampleFns = {
  transducers: [
    mapFn(reduceFn),
    filterFn(mapFn(reduceFn)),
    composeFn(reduceFn),
  ],
  raw: [
    (acc, x) => acc.concat([x.src]),
    (acc, x) => acc.concat(x.src.split('.').pop() !== 'json' ? [x.src] : []),
    (acc, x) => acc.concat(x.src.split('.').pop() !== 'json' ? [x.src.toUpperCase() + '!'] : []),
  ],
};
const execExample = (currentValue, index) =>
  console.log('Example ' + index, example.data.reduce(currentValue, []));

exampleFns.raw.forEach(execExample);
exampleFns.transducers.forEach(execExample);

这里有一个有趣的解决方案:

/**
 * Filter-map. Like map, but skips undefined values.
 *
 * @param callback
 */
function fmap(callback) {
    return this.reduce((accum, ...args) => {
        const x = callback(...args);
        if(x !== undefined) {
            accum.push(x);
        }
        return accum;
    }, []);
}

与绑定操作符一起使用:

[1,2,-1,3]::fmap(x => x > 0 ? x * 2 : undefined); // [2,4,6]

const arr = [0,1， "， undefined, false, 2, undefined, null，， 3, NaN]; const filtered = arr.filter(Boolean); console.log(过滤); ／* 输出:[1,2,3] * /

你可以这样做

Var sources = []; 图像。映射(函数(img) { 如果(img.src.split (' . ') .pop () ! = = json){/ /如果扩展不是. json sources.push (img.src);//只推有效值 ｝ })；

你可以像这样使用map + filter:

   var sources = images.map(function (img) {
    if(img.src.split('.').pop() === "json"){ // if extension is .json
        return null; // skip
    }
    else{
        return img.src;
    }})?.filter(x => x !== null);