如何使现有的numpy数组成为结构化数组？

Question

I would like to give an existing numpy array named columns. I've tried to name the columns in the following way:

X = np.random.normal(0,1,(3,3))
names = ['a','b','c']
types = ['f4']*len(names)
t = list(zip(names,types))

Y= np.array(X, dtype=t)

However, when I call Y['a'] , I am given a 3x3 array rather than the first column of X, which is 3x1.

How can I give an existing array named columns? What is my error in my example?

Answer 1

You're looking for .view , which reinterprets existing memory in a new way.

names = ['a','b','c']
types = [X.dtype]*len(names)
t = list(zip(names,types))
Y = X.view(t)

For this to work, you need to match the dtype of X - f4 is probably not correct.

Your code is equivalent to X.astype(t) . When converting to a struct array, that tries to set every field to the same value.