Flatten tuple containing numpy array to numpy array

Question

So I used operator.attrgetter to try to rip an array class into a numpy array by tupleList=map(attrgetter(*inNames),inClass) and ended up with something like this for tupleList[0]

(1, array([0.0, 0.0, 0.0, 0.0], 'f'), 1)

I'd like to turn that into a numpy array (specifically a structured array, but I can work that out) that looks like this

array([1, 0.0, 0.0, 0.0, 0.0, 1], dtype=(('id', 'i8'), . . . .)])

Unfortunately, np.asArray(tupleList[0]) and np.asAnyArray(tupleList[0]) don't work and I get

ValueError: setting an array element with a sequence

Is there a way around this? Currently fighting my IT division to get pandas, but don't have it right now. I assume that would that help?

Daniel F · Accepted Answer · 2017-08-29 07:38:43Z

2

Use np.hstack in order to integrate your tuple :

In [106]: foo = (1, np.array([0.0, 0.0, 0.0, 0.0], 'f'), 1)

In [107]: np.hstack(foo)
Out[107]: array([ 1.,  0.,  0.,  0.,  0.,  1.])

edited Aug 29, 2017 at 7:38

Daniel F

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answered Nov 3, 2016 at 10:45

Kasravnd

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3 Comments

Daniel F Over a year ago

That works 1d, is there a way to do this for the whole tupleList?

Moses Koledoye Over a year ago

@DanielForsman But your question relates to 1D and not the entire tupleList. Changing the requirements of your question after an answer has been provided is not very fair.

Daniel F Over a year ago

Understood. In any case it seems np.array([np.hstack(t) for t in tupleList]) works.

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