patrick - 2 years ago 107
Python Question

# Why does the numpy function `take` change the shape of my array?

I am trying to calculate which points in my data set (in the shape of a numpy array called "matrix") are closest to a vector (array called "vector") in ndimensional space. Then, I want to extract these same vectors from a data set which is identical to "matrix" but includes additional labels (="matrix_with_labels").

``````vector=([1,2,3,...])
matrix=[[1,2,3,...], [2,4,6,...], ...]]
matrix_with_labels=[[a,1,2,3,...], [b,2,4,6,...], ...]]
``````

Thus, I compute the distances between the vector and each item in the matrix:

``````dist=scipy.spatial.distance.cdist(matrix,vector,'euclidean')
``````

Then I sort these distances to identify the closest neighbors:

``````sorted_index=np.argsort(dist, axis=0)
``````

Then I try to sort the "matrix_with_labels" by "sorted_index", using
`numpy.take`
as explained in this post on SO.

``````result= matrix_with_labels.take(sorted_index, 0)
``````

The outcome looks just fine until I try to process it further - it seems to have changed shape:

``````print result.shape
(20, 1, 11)
``````

When I look at the shape of the initial "matrix_with_labels", however:

``````matrix_with_labels.shape
(20, 11)
``````

The documentation on take says:

subarray : ndarray
The returned array has the same type as a.

What am I doing wrong? Any help is appreciated!

If you're starting with a `(20, 11)` shape, I think the only way to get a `(20, 1, 11)` shape is if `x` has shape `(1, 11)`.
Try `result = matrix_with_labels.take(x.reshape(-1), 0)`.