1D->二维阵列W /法线曲线子阵列长度 [英] 1D -> 2D Array W/Normal Curve Sub-Array Lengths

问题描述

我正在尝试将1D数组分解为2D数组，其中子数组的长度不同。这种变化应遵循高斯曲线（或丘形）。因此，假设我们制作的2D数组变量名为gaussianCurve。 gaussianCurve [0]&中的数组gaussianCurve [n]的长度为1，而gaussianCurve [n / 2]的长度为参数 maxArrayLength提供的最大值。这迫使gaussianCurve索引的数量变为变量。

I am trying to break a 1D array into a 2D array where the sub-arrays are of varying lengths. This variance should follow the gaussian curve [or a mound shape]. So, say the 2D array variable we make is named gaussianCurve. The array within gaussianCurve[0] & gaussianCurve[n] would be of length 1, and gaussianCurve[n/2] would be a maximum provided by a parameter "maxArrayLength". This forces the number of gaussianCurve indexes to become variable.

说我有以下伪代码：

function (oneDimentionalArray, maxArrayLength) {
// oneDimentionalArray is ["A","B","C","D","E","F","G","H","I","J","K"]
// maxArrayLength is 5
// Currently working like this (i.e. "batches"):
// return [["A","B","C","D","E"],["F","G","H","I","J"],["K"]]
// would LIKE it to work like this
    gaussianCurve = []
    gaussianCurve.push(["A"])
    gaussianCurve.push(["B", "C"])
    gaussianCurve.push(["D", "E", "F", "G", "H"])
    gaussianCurve.push(["I", "J"])
    gaussianCurve.push(["K"])

    return  gaussianCurve
}

我为什么要这样的东西？进度条。

Why would I want such a thing? Progress bars.

1. 他们没有显示我正在立即取得进步
   
   

1. They don’t show I am making progress immediately

1. 这是因为必须先完成第一项工作，酒吧才能移动

它们放慢速度达到95％以上，有时甚至会保持100％

They slow down at 95%+ and sometimes even stick at 100%

1. 只是烦人

欢迎提出任何建议。我只是在脑海中看不到答案。

Any suggestions are welcome. I am just not seeing the answer in my minds eye.

编辑：我觉得它的措词很差，所以我在改写它。

I feel it was worded poorly, so I am rewording it.

... gaussianCurve [0] .length& gaussianCurve [gaussianCurve.length-1] .length将为1，而gaussianCurve [gaussianCurve.length / 2] .length将为 maxArrayLength。

...gaussianCurve[0].length & gaussianCurve[gaussianCurve.length - 1].length would be 1, and gaussianCurve[gaussianCurve.length/2].length would be up to "maxArrayLength".

输入：

function gaussianRefactor(["A","B","C","D","E","F","G","H","I","J","K"], 1)
function gaussianRefactor(["A","B","C","D","E","F","G","H","I","J","K"], 2)
function gaussianRefactor(["A","B","C","D","E","F","G","H","I","J","K"], 4)
function gaussianRefactor(["A","B","C","D","E","F","G","H","I","J","K"], 8)
function gaussianRefactor(["A","B","C","D","E","F","G","H","I","J","K"], 16)

输出：

[["A"],["B"],["C"],["D"],["E"],["F"],["G"],["H"],["I"],["J"],["K"]]
[["A"],["B","C"],["D","E"],["F","G"],["H","I"],["J"],["K"]]
[["A"],["B","C","D"],["E","F","G","H"],["I","J","K"]]
[["A"],["B","C","D","E","F","G","H","I"],["J","K"]]
[["A","B","C","D","E","F","G","H","I","J","K"]]

N内部数组可能超出maxArrayLength的长度

No inner array may exceed the length of maxArrayLength

推荐答案

我给了它一个快速镜头，它似乎可以正常工作。一些潜在的改进：

I gave it a quick shot and it seems to work. Some potential improvements:

• 输入检查功能


• 它将所有可能的剩余值放入中间垃圾箱。对于偶数总数的箱，它将受益于一些平衡。之后，尝试根据输入数据中的原始索引对每个bin进行排序可能是一件好事，因为现在事情可能最终会乱序。但是，如果只是在进度条上使用非线性分布的作业，则顺序可能无关紧要。

function probability(s, m, x) {
	var eExp = -Math.pow(x - m, 2) /
		(2 * Math.pow(s, 2));
	return 1/(Math.sqrt(2*Math.PI) * s) *
		Math.pow(Math.E, eExp);
}

function gassianArray(input, nBins) {
	// first try to determine a reasonable value of s so that the outer bins have a value
	var s = 0.1;
	var sMax = 10;
	var m = (nBins - 1) / 2.0;
	var outerBinMinimum = 1 / input.length;
	var p = 0;
	while (true && s <= sMax) {
		p = probability(s, m, 0);
		if (p >= outerBinMinimum) {
			break;
		} else {
			s += 0.1;
		}
	}

	// holds arrays
	var output = [];
	// holds desired array sizes
	var outputLengths = [];
	// fill these based on probability density
	for (var b=0; b<nBins; b++) {
		var n = Math.floor(probability(s, m, b) * input.length);
		output.push([]);
		outputLengths.push(n);
	}

	// fill arrays from outside, leaving extra values for the middle
	var midIndex = Math.floor(m);
	// left side
	for (var i=0; i<midIndex; i++) {
		for (var j=0; j<outputLengths[i]; j++) {
			output[i].push(input.shift());
		}
	}
	// right side
	for (var i=nBins-1; i>=midIndex; i--) {
		for (var j=0; j<outputLengths[i]; j++) {
			output[i].push(input.pop());
		}
		output[i].reverse();
	}
	// whatever remains goes in the "middle"
	while (input.length !== 0) {
		output[midIndex].unshift(input.pop());
	}

	return output;
}

var input = ["A","B","C","D","E","F","G","H","I","J","K"];
var n = 5;
console.log(gassianArray(input, n));
/*
[ [ 'A' ],
  [ 'B', 'C' ],
  [ 'E', 'D', 'F', 'G', 'H' ],
  [ 'I', 'J' ],
  [ 'K' ] ]
*/


var input = ["A","B","C","D","E","F","G","H","I","J","K","L","M","N","O","P","Q","R","S","T","U","V","W","X","Y","Z"];
var n = 6;
console.log(gassianArray(input, n));
/*
[ [ 'A' ],
  [ 'B', 'C', 'D', 'E' ],
  [ 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N' ],
  [ 'O', 'P', 'Q', 'R', 'S', 'T', 'U' ],
  [ 'V', 'W', 'X', 'Y' ],
  [ 'Z' ] ]
*/

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