problem with adding to numpy.float64, ufunc issue? about clifford HOT 6 CLOSED

The left operand gets the first shot at implementing the operation. Only if it fails does the right operand attempt with its __radd__ method. Because MultiVector implements the Sequence interface, np.asarray() knows how to convert it to a numpy array via np.asarray(). The numpy scalar types will attempt to convert the other operand to a numpy array via np.asarray(). Since this succeeds, np.float64.__add__() succeeds, and MultiVector.__radd__() does not get a chance to run.

I don't have a good idea offhand how to get around this.

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thanks very much for the info.

is it clear to you that the operator change would cause this? the exp() function operating on a MultiVector now fails also, which i suspect is related.

a similar question is raised in this SO post. after looking at their suggestions the __array_priority__ does not work, but __array_wrap__ does. however this hook seems to be after the numpy __add__ has happened...

they also suggest to subclassing ndarray. however, i am not sure that i have the time/ability to make this change to the whole class, or to decide whether it is a good idea.

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so if the left hand operator fails, the right operand attempt with its __radd__ method, then would it be possible to make the ufunc 'fail' by doing something in __array_prepare__

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arsenovic@bd3bb72 . . . embarrasing

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@arsenovic is this now fixed or still a problem?

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i think we can close

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