CODEWITHSUNDEEP
pythonnumpy
gboffi
gboffi

Reputation: 25023

I expected a `numpy.lib.polynomial.poly1d` object, I've found a sequence of integers

In [31]: print(np.poly1d((3,2)))                                                          

3 x + 2

In [32]: a = np.array(( np.poly1d((3,2)), np.poly1d((3,2)) ))

I expected that array a were a (2,) shaped array of numpy.lib.polynomial.poly1d objects, BUT

In [33]: a.shape                                                                          
Out[33]: (2, 2)

In [34]: type(a[0,0])                                                                     
Out[34]: numpy.int64

In [35]: a                                                                                
Out[35]: 
array([[2, 2],
       [2, 2]])

What's going on?

It's worth to be mentioned that

 In [36]: a = np.array(( np.poly1d((3,2,1)), np.poly1d((3,2,1)) ))

raises an error

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-38-3139075221f6> in <module>
----> 1 a = np.array(( np.poly1d((3,2,1)), np.poly1d((3,2,1)), np.poly1d((3,2,1)) ))

ValueError: cannot copy sequence with size 2 to array axis with dimension 3

Upvotes: 0

Views: 214

Answers (1)

hpaulj
hpaulj

Reputation: 231385

A poly1d object is iterable

In [1]: np.poly1d((3,2))                                                        
Out[1]: poly1d([3, 2])
In [2]: list(_)                                                                 
Out[2]: [3, 2]

np.array tries to makes a multidimensional numeric array from its inputs, iterating where possible. That's why making an array from these poly1d object ends up looking like you did np.array([[3,2],[3,2]]).

The most reliable way to create an object dtype array is to initialize a 'blank' one and fill it.

In [12]: arr = np.empty(2, object)                                              
In [13]: arr[:] = [np.poly1d((3,2)), np.poly1d((4,2))]                          
In [14]: arr                                                                    
Out[14]: array([poly1d([3, 2]), poly1d([4, 2])], dtype=object)

But do you really need an object dtype array? Why not stick with a list of the poly1d objects?

===

We've observed in other SO that attempting to create a object dtype array can go several different ways. Some times it works, sometimes you get a numeric array, and sometimes an error.

In [17]: np.array([np.poly1d((3,2)), np.poly1d((3,2,1))])                       
Out[17]: array([poly1d([3, 2]), poly1d([3, 2, 1])], dtype=object)
In [18]: np.array([np.poly1d((3,2,1)), np.poly1d((3,2,1))])                     
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-18-00b20d14a2b6> in <module>
----> 1 np.array([np.poly1d((3,2,1)), np.poly1d((3,2,1))])

ValueError: cannot copy sequence with size 2 to array axis with dimension 3

Upvotes: 1

Related Questions