Hello everyone, I’m using a 2-D numpy array and I’m trying to do SVD on that. Along the way I’m centering the initial array by calculating a new array with the mean value per column and subtracting that from the initial array. For some reason when I calculate the per-column-mean array and the ‘VT’ array (array with right eigen-vectors) using scidb I get completely different results than when I am using numpy or scipy and their corresponding functions. Am I missing something here?

The following sample specifies the point where the problem occurs when calculating the per-column-mean array.

```
# X is the afore-mentioned numpy array
X_sci = sdb.from_array(X)
# This returns the correct array
X_sci.toarray()
# This returns the wrong mean array
X_sci.mean(0).toarray()
# The following two functions return the correct array
np.mean(X_sci.toarray(), axis=0)
np.mean(X, axis=0)
```