Can't reshape pyarray with shape of different input type about xtensor-python HOT 1 CLOSED

Hi @iamthebot

this is actually a corner-case with the initializer lists that we have. Initialization from initializer list is used to create the array, e.g. xt::pyarray<double> a({{1,2,3}, {4,5,6}}); will create a pyarray with shape {2, 3} and the values inside.
To easily use initializer lists for the shape to create xarrays etc, we have added the named constructor as follows: auto a = xt::pyarray<double>::from_shape({3, 3}); which returns the array with correct shape.
As the syntax is a little verbose, we have also added the xt::empty({3,3}); function which will come in xtensor 0.16 (however, in this case it would actually return a xtensor, as it can infer that {3, 3} has 2 dimensions at compile time.

You can also force the shape-overload by constructing a shape type in the constructor call pyarray<double> a(std::vector<std::size_t>{1,2,3,4}); should work.

And your last error ... we actually have "two" shape types in xtensor python: one "inner" which wraps the numpy shape, and one "outer" which is the std::vector<size_t>. Currently we only have a constructor from the std::vector shape type.
If you use the from_shape overload it should be fine.

It looks like we haven't added the from_shape static constructors to pyarray / pytensor yet! Sorry about that!! I'm filing a bug for that, it should land in the next release for sure!
So the current workaround is probably

xt::pyarray<double> a; a.reshape(b.shape());

from xtensor-python.