在numpy文件中存储和提取数组时出现问题

Question

Trying to store an array in numpy file however, while trying to extract it, and use it, getting an error message as trying to apply array to a sequence.

These are the two arrays, unsure which one is causing the issue.

X = [[1,2,3],[4,5,6],[7,8,9]]
y = [0,1,2,3,4,5,6....]

while trying to retrieve it and use it getting the values as:

X: array(list[1,2,3],list[4,5,6],list[7,8,9])
y = array([0,1,2,3,4,5...])

Here is the code:

vectors = np.array(X)
labels = np.array(y)

While retrieving working on t-sne

visualisations = TSNE(n_components=2).fit_transform(X,y)

I get the following error:

ValueError                                Traceback (most recent call last)
<ipython-input-11-244f99341167> in <module>()
----> 1 visualisations = TSNE(n_components=2).fit_transform(X,y)

C:\ProgramData\Anaconda3\lib\site-packages\sklearn\manifold\t_sne.py in fit_transform(self, X, y)
    856             Embedding of the training data in low-dimensional space.
    857         """
--> 858         embedding = self._fit(X)
    859         self.embedding_ = embedding
    860         return self.embedding_

C:\ProgramData\Anaconda3\lib\site-packages\sklearn\manifold\t_sne.py in _fit(self, X, skip_num_points)
    658         else:
    659             X = check_array(X, accept_sparse=['csr', 'csc', 'coo'],
--> 660                             dtype=[np.float32, np.float64])
    661         if self.method == 'barnes_hut' and self.n_components > 3:
    662             raise ValueError("'n_components' should be inferior to 4 for the "

C:\ProgramData\Anaconda3\lib\site-packages\sklearn\utils\validation.py in check_array(array, accept_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, warn_on_dtype, estimator)
    431                                       force_all_finite)
    432     else:
--> 433         array = np.array(array, dtype=dtype, order=order, copy=copy)
    434 
    435         if ensure_2d:

ValueError: setting an array element with a sequence.

Answer 1

Assuming I understand you correctly you need to package the first group in a list; something like this:

import numpy as np

#X = [[1,2,3],[4,5,6],[7,8,9]]
#y = [0,1,2,3,4,5,6, 7, 8, 9]

X = np.array([[1,2,3],[4,5,6],[7,8,9]])
y = np.array([0,1,2,3,4,5, 6, 7, 8, 9])

Answer 2

array(list[1,2,3],list[4,5,6],list[7,8,9])

is a 1d object dtype array. To get that from

[[1,2,3],[4,5,6],[7,8,9]]

requires more than np.array([[1,2,3],[4,5,6],[7,8,9]]) ; either the list elements have to vary in size, or you have to initialize an object array and copy the list values to it.

In any case fit_transform cannot handle that kind of array. It expects a 2d numeric dtype. Notice the parameters to the check_array function.

If all the list elements of X are the same size, then

X = np.stack(X)

should turn it into a 2d numeric array.

I suspect X was that 1d object array type before saving. By itself save/load should not turn a 2d numeric array into an object one.