FIX: cast unsupported numpy dtypes in ants.from_numpy()

[ncullen93]

If you try to create an ants image from an array with an unsupported numpy dtype, it just fails. Since we only support 4 dtypes, we really should support automatically casting unsupported dtypes to supported ones. This PR does that.

The one question I have is whether it is good to warn the user that their data is being casted or to just do it silently. Having a bunch of warnings is annoying and pollutes the console, but I can see some people being confused that their data is in a different dtype otherwise.

Below is an example that fails. The int16 type is quite common for segmentation arrays which is how I discovered the error:

import numpy as np
import ants

arr = np.random.randn(100,100).astype('int16')
img = ants.from_numpy(arr)

[coveralls]

coverage: 84.696% (+0.02%) from 84.673%
when pulling 2043781 on cast-unsupported-numpy-dtypes
into e667c28 on master.

[ntustison]

I'm fine either way although, correct me if I'm wrong, but silent conversion is the norm in core ANTs.

[cookpa]

There's also a lot of internal cloning / casting to interact with base ANTs. So even if you warn about the conversion from int16 to uint32, it's going to get cloned to float if you call apply_transforms, for example.

So I would lean towards not warning. But maybe we should allow users to set the pixel type? Clone lets you do this, but from_numpy does not.

[cookpa]

Might be nice to support conversion from numpy bool to uint8 as well, common masking pipeline

[ncullen93]

Ok, i think im convinced to not warn. And I will include bool because that's definitely used. Thanks!