ase*_*iop 7 javascript recursion accounting
我正在执行统计分析,以确定是否可以通过在特定时间范围内将其分解为较小的事务来隐藏更大的事务.我正在做的是将较大的数据集分解为较小的子集(此时为12的数组),然后在每个子集上运行一系列循环,以确定这些元素的任何组合是否在目标范围内累加.
这是我目前的代码:
amounts_matrix = [1380.54,9583.33,37993.04,3240.96...]
matrix_amounts = amounts_matrix.length
total_permutations = 0;
total_hits = 0;
target_range = 1
target = 130000
low_threshold = target - target_range
high_threshold = target + target_range
entries = []
range = 12
for(x = 0; x< matrix_amounts-(range-1); x++){
amounts = amounts_matrix.slice(x, x+range)
total_amounts = range
for(i = 0; i< total_amounts; i++){
entries.push(amounts[i])
totalcheck(entries)
entries = []
}
for(i = 0; i< total_amounts; i++){
for(j = i+1; j< total_amounts; j++){
entries.push(amounts[i])
entries.push(amounts[j])
totalcheck(entries)
entries = []
}
}
...
for(i = 0; i< total_amounts; i++){
for(j = i+1; j< total_amounts; j++){
for(k = j+1; k< total_amounts; k++){
for(l = k+1; l< total_amounts; l++){
for(m = l+1; m< total_amounts; m++){
for(n = m+1; n< total_amounts; n++){
for(o = n+1; o< total_amounts; o++){
for(p = o+1; p< total_amounts;p++){
for(q = p+1; q< total_amounts;q++){
for(r = q+1; r< total_amounts;r++){
for(s = r+1; s< total_amounts;s++){
for(t = s+1; t< total_amounts;t++){
entries.push(amounts[i])
entries.push(amounts[j])
entries.push(amounts[k])
entries.push(amounts[l])
entries.push(amounts[m])
entries.push(amounts[n])
entries.push(amounts[o])
entries.push(amounts[p])
entries.push(amounts[q])
entries.push(amounts[r])
entries.push(amounts[s])
entries.push(amounts[t])
totalcheck(entries)
entries = []
}
}
}
}
}
}
}
}
}
}
}
}
}
function totalcheck(array){
total_permutations += 1;
sum_amount = 0
for(z = 0; z < array.length; z++){
sum_amount += array[z]
}
if(sum_amount > low_threshold && sum_amount < high_threshold){
total_hits += 1
console.log(array)
console.log(sum_amount.toFixed(2))
console.log("---------------")
}
}
console.log("overall total hits = " + total_hits)
console.log("overall total permutations = " + total_permutations)
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我对这些for循环有多广泛感到尴尬,我想用一个函数来概括它,我可以告诉它运行X循环,而不是像这样构建它们.我发现的排列函数对我来说并不可行,因为它们都构建了充满可能性的数组; 我想要检查目标,因为我要避免使用巨大的阵列并遇到内存问题.如何构建一个递归循环来执行此操作?
for(i = 0; i< total_amounts; i++){
for(j = i+1; j< total_amounts; j++){
for(k = j+1; k< total_amounts; k++){
for(l = k+1; l< total_amounts; l++){
for(m = l+1; m< total_amounts; m++){
for(n = m+1; n< total_amounts; n++){
for(o = n+1; o< total_amounts; o++){
for(p = o+1; p< total_amounts;p++){
for(q = p+1; q< total_amounts;q++){
for(r = q+1; r< total_amounts;r++){
for(s = r+1; s< total_amounts;s++){
for(t = s+1; t< total_amounts;t++){
entries.push(amounts[i])
entries.push(amounts[j])
entries.push(amounts[k])
entries.push(amounts[l])
entries.push(amounts[m])
entries.push(amounts[n])
entries.push(amounts[o])
entries.push(amounts[p])
entries.push(amounts[q])
entries.push(amounts[r])
entries.push(amounts[s])
entries.push(amounts[t])
totalcheck(entries)
entries = []
}
}
}
}
}
}
}
}
}
}
}
}
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可以变成这样
function loopinator(){
for(i=0; i<total_amounts; i++){
for(j=0; j<11; j++){//You had 11 loops plus root loop
entries.push(amounts[( i+j )]);//Will increase with each iteration of j loop, simulating loop branching
}
//Will run at same time as it did before, after all nested roots, but before next iteration of i loop
totalcheck(entries);
entries = [];
}
}
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