Matlab：优化这个？

发布于 2024-12-07 03:33:05 字数 427 浏览 1 评论 0原文

我是 matlab 新手。已承担加快程序速度的任务。我确信有更好的方法来执行以下语句：

for i = 2:length(WallId)
     if WallId(i) ~= WallId(i-1)
        ReducedWallId = [ReducedWallId;WallId(i)];
        ReducedWallTime = [ReducedWallTime;WallTime(i)];
        GroupCount = [GroupCount;tempCount];
        tempCount = 1;
    else
        tempCount = tempCount +1;
    end
end

我可以将各种变量预先分配给“length(WallId)”，但是完成后我该如何处理额外的变量呢？我在乎吗？

原文

Im v new to matlab. Have been tasked with speeding up a procedure. Im sure there is a better way to do the following statements:

for i = 2:length(WallId)
     if WallId(i) ~= WallId(i-1)
        ReducedWallId = [ReducedWallId;WallId(i)];
        ReducedWallTime = [ReducedWallTime;WallTime(i)];
        GroupCount = [GroupCount;tempCount];
        tempCount = 1;
    else
        tempCount = tempCount +1;
    end
end

I can preallocate the various vars to 'length(WallId)' but what do I do with the extra after its done? Do I care?

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亚希 2024-12-14 03:33:05

idx = find([true diff(WallId) ~= 0]);
ReducedWallId = WallId(idx);
ReducedWallTime = WallTime(idx);
GroupCount = diff([idx numel(WallId)+1]);

假设您想要的是 WallId 和 WallTime 中唯一数据的摘要，那么您应该
确保 WallId 首先排序。您可以重新组织 WallTime 进行匹配，如下所示：

[WallId, ind] = sort(WallId);
WallTime = WallTime(ind);

此外，只有当 WallTime 与 WallId 匹配时，您才会获得正确的答案。

idx = find([true diff(WallId) ~= 0]);
ReducedWallId = WallId(idx);
ReducedWallTime = WallTime(idx);
GroupCount = diff([idx numel(WallId)+1]);

Assuming what you want is a summary of the unique data in WallId and WallTime, then you should
make sure that WallId is sorted first. You can re-organise WallTime to match, as follows:

[WallId, ind] = sort(WallId);
WallTime = WallTime(ind);

Also, you'll only get the right answer if WallTime matches whenever WallId does.

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我不咬妳我踢妳 2024-12-14 03:33:05

使用矢量化。

ReducedWallId=WallId(find(diff(WallId)~=0));

对于ReducedWallTime 也类似。

显式的 for 循环非常慢。使用矢量运算可以大大加快速度。这是优化 MATLAB 代码的一般主题，网络上的各种文档对此进行了详细介绍。

Use vectorization.

ReducedWallId=WallId(find(diff(WallId)~=0));

and similarly for ReducedWallTime.

The explicit for-loops are extremely slow. Using vector-operations speeds everything up considerably. This is a general theme in optimizing MATLAB code and is covered in detail in various documents found in the web.

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