使用Scipy将字典从Python保存到Matlab [英] Saving dictionaries from Python to Matlab with Scipy
问题描述
我发现了一些问题，无法将生成的整洁数据保存到.mat文件中.我以为使用Scipy会更简单，但是看来我出了点问题.
I'm finding some problems to save my neat generated data into .mat files. I thought it was more straightforward with Scipy, but it seems I'm getting something wrong.
这是我要保存的数据的示例:
This is an example of data I want to save:
out = {'features': array([[ 5.00088905e+01, 1.51847522e+01, 4.93513862e+01,
3.76548415e+00, -3.96946513e+01, -2.11885850e+01,
9.85304035e+00, -6.30005764e+00, 1.19987435e+01,
3.89762536e+00, -1.31554755e+00, -1.66890836e+01,
4.75289017e-02, 3.65829480e-01, -4.77872832e-01,
1.13641908e+00, -1.08742775e-01, -2.42751445e-01,
-1.13054913e-01, 3.39011561e-01, 1.37158960e-01,
-2.80760116e-01, -4.15187861e-01, 9.85433526e-02,
-8.66144928e-02, 9.18260870e-03, -7.38139130e-01,
8.04136232e-01, 2.31623188e-02, -7.88927536e-02,
-2.17779710e-01, 2.85428986e-01, -8.16231884e-02,
1.79710145e-03, -3.47710145e-01, -9.84115942e-02,
3.96077031e+00, 3.29914828e+01, 2.60086805e+01,
2.44418378e+01, 2.01712577e+01, 1.56827627e+01,
1.59131122e+01, 1.84134126e+01, 1.63149310e+01,
1.35579058e+01, 1.15772911e+01, 1.82263123e+01,
3.96077031e+00, 3.29914828e+01, 2.60086805e+01,
2.44418378e+01, 2.01712577e+01, 1.56827627e+01,
1.59131122e+01, 1.84134126e+01, 1.63149310e+01,
1.35579058e+01, 1.15772911e+01, 1.82263123e+01,
3.96077031e+00, 3.29914828e+01, 2.60086805e+01,
2.44418378e+01, 2.01712577e+01, 1.56827627e+01,
1.59131122e+01, 1.84134126e+01, 1.63149310e+01,
1.35579058e+01, 1.15772911e+01, 1.82263123e+01]]), 'tags': [['rock', 'metal']]}
它是矩阵的单行，可以与标签列表(长度可变)相关联.
It's a single row of a matrix that can be associated with a list of tags (variable in lengths).
这个想法是要创建一个.mat文件，其中包含矩阵和列表的单元格数组.当我这样做时:
The idea was to have a .mat file with the matrix and a cell array of lists. When I go for this:
scipy.io.savemat('./test.mat',out)
在Matlab中获取标签的结果各不相同.对于上面的示例，我有一个1x2x5的字符矩阵
results in Matlab for tags vary. For the example above I have a 1x2x5 char matrix
val(:,:,1) = rm
val(:,:,2) = oe
val(:,:,3) = ct
val(:,:,4) = ka
val(:,:,5) = l
如果我尝试使用矩阵而不是单行向量，则会得到一个单元格数组，其中每行都有一个单元格，但是列表被合并，特定行的单元格为: rmoectkal .
If I try for matrix instead than single row vectors, I get a cell array with a cell for every row, but the list is merged and the cell for the specific row would be: rmoectkal.
我尝试举一个例子来解释:
Il try to explain with an example:
>>> genre_tags_matrix = np.array(genre_tags, dtype=np.object)
>>> print(genre_tags_matrix)
[['classical', 'pop'] ['classical'] ['classical'] ['classical']]
>>> out = {'tags' : genre_tags_matrix}
>>> scipy.io.savemat('./test.mat',out)
这是我在Matlab中看到的:
This is what I see in Matlab:
到底是怎么回事?有解决方法吗?
What exactly is going on? Is there a workaround for this?
推荐答案
问题是MATLAB和Octave中的字符串实际上只是一个字符数组，因此以下语句实际上是3D图像.数组
The issue is that a string in MATLAB and Octave is really just an array of characters, so the following statement is actually a 3D array
[['rock', 'metal']]
如果我们将字符替换为数字，以便更清楚地知道它是3D数组，我们会得到类似的东西
If we replace the characters with numbers to make it a little clearer that it's a 3D array we get something like this
[[[1,2,3], [4,5,6]]]
当您使用 savemat 将其中任何一个保存到 .mat 文件时，它将被视为3D数组.
When you save either of these to a .mat file with savemat it's going to be treated as a 3D array.
如果您想要一个单元格数组，则必须手动创建一个numpy对象的numpy数组 .
If you instead want a cell array, you have to manually create a numpy array of numpy objects.
import scipy
import numpy as np
out = {'tags': np.array(['rock', 'metal'], dtype=np.object)}
scipy.io.savemat('test.mat', out)
然后在MATLAB或Octave中
Then within MATLAB or Octave
data = load('test.mat')
% tags =
% {
% [1,1] = rock
% [1,2] = metal
% }
更新
对于嵌套单元格数组，要成为单元格数组的每个级别也必须也是numpy对象的numpy数组
In the case of a nested cell array, each level that you would like to be a cell array must also be a numpy array of numpy objects
out = {'tags': np.array([
np.array(['classical', 'pop'], dtype=np.object), # A nested cell array
'classical', 'classical', 'classical'], dtype=np.object)}
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