In principle initialization of Cube() shall accept values that are scalar or list-like. But if the input now is a masked numpy with correct number of values, we receive an AttributeError saying 'numpy.ndarrray' object has no attribute 'c_contiguous'.
By digging more into this, we also see that proper error checks on dimensions miss, e.g. the following will work (unintentionally):
c = Cube(ncol=4, nrow=2, nlay=3, xinc=1, yinc=1, zinc=1, values=np.ones((6,4)))
mferrera
commented
4 months ago
In principle initialization of
Cube()shall accept values that are scalar or list-like. But if the input now is a masked numpy with correct number of values, we receive an AttributeError saying'numpy.ndarrray' object has no attribute 'c_contiguous'.By digging more into this, we also see that proper error checks on dimensions miss, e.g. the following will work (unintentionally):
c = Cube(ncol=4, nrow=2, nlay=3, xinc=1, yinc=1, zinc=1, values=np.ones((6,4)))