将 3d 矩阵重塑为 2d 矩阵

问题描述：

我在 MATLAB 中有一个 3d 矩阵 (n-by-m-by-t) 表示一段时间内网格中的 n-by-m 测量值.我想要一个二维矩阵，其中空间信息消失了，只剩下 n*m 随时间 t 的测量值(即:n*m-by-t)

I have a 3d matrix (n-by-m-by-t) in MATLAB representing n-by-m measurements in a grid over a period of time. I would like to have a 2d matrix, where the spatial information is gone and only n*m measurements over time t are left (ie: n*m-by-t)

我该怎么做?

答

您需要命令 重塑:

You need the command reshape:

假设你的初始矩阵是(只是为了让我得到一些数据):

Say your initial matrix is (just for me to get some data):

a=rand(4,6,8);

然后，如果最后两个坐标是空间坐标(时间为 4，m 为 6，n 为 8)，则使用:

Then, if the last two coordinates are spatial (time is 4, m is 6, n is 8) you use:

a=reshape(a,[4 48]);

你最终会得到一个 4x48 的数组.

and you end up with a 4x48 array.

如果前两个是空间的，最后一个是时间(m 是 4，n 是 6，时间是 8)你使用:

If the first two are spatial and the last is time (m is 4, n is 6, time is 8) you use:

a=reshape(a,[24 8]);

你最终会得到一个 24x8 的数组.

and you end up with a 24x8 array.

这是一个快速的 O(1) 操作(它只是调整数据形状的标题).还有其他方法可以做到这一点，例如a=a(:,:) 压缩最后两个维度，但 reshape 更快.

This is a fast, O(1) operation (it just adjusts it header of what the shape of the data is). There are other ways of doing it, e.g. a=a(:,:) to condense the last two dimensions, but reshape is faster.

将 3d 矩阵重塑为 2d 矩阵

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