Calling np.sqrt on a pint quantity has a side effect on the pint quantity

[abrahamneben]

Strange numpy/pint interaction. When I call np.sqrt on a pint quantity, it has the side effect of changing the type of the object in the pint quantity. When I use **(1/2) instead of np.sqrt, this doesn't happen.

>>> import numpy as np
>>> import pint
>>> units = pint.UnitRegistry()

>>> a = 1*units.m
>>> print(type(a.m))
<class 'int'>

>>> np.sqrt(a) # has the side effect of changing the type of a.m

print(type(a.m))
<class 'numpy.ndarray'>

>>> import numpy as np
>>> import pint
>>> units = pint.UnitRegistry()

>>> a = 1*units.m
>>> print(type(a.m))
<class 'int'>

>>> a**(1/2) # no side effects

print(type(a.m))
<class 'int'>

[hgrecco]

Yes. This is true not only for Pint but for everything:

>>> import numpy as np
>>> type(np.sqrt(4))
<class 'numpy.float64'>

While it looks unexpected, it is actually what numpy does

[dopplershift]

The issue isn't changing data type between source and result. The issue is that a**(1/2) returns a new result, but for some reason the original a is modified in-place. I've found that weird as well.

[raphaeltimbo]

This is also described in issue #509.

I believe it could be something related to this part of the code:

pint/pint/quantity.py

Lines 1341 to 1345 in 0c4a950

	else:
	# If an `__array_` attributes is requested but the magnitude is not an ndarray,
	# we convert the magnitude to a numpy ndarray.
	self._magnitude = _to_magnitude(self._magnitude, force_ndarray=True)
	return getattr(self._magnitude, item)

Maybe this conversion could be done only when the magnitude is iterable?
Or maybe the magnitude could be an np.array right from the beggining (when the quantity is instantiated)?

[hgrecco]

I am closing this as it is taken care by #925