如何将 numpy 数组 [(x1,y1),(x2,y2),(x3,y3),...(xn,yn)] 转换为 [(x1,y1,x1^2,y1^2),(x2 ,y2,x2^2,y2^2),…(xn,yn,xn^2,yn^2)]

Question

I tried this

x = np.array([
    [0,0],
    [1,0],
    [2.61,-1.28],
    [-0.59,2.1]
])

for i in X:
  X = np.append(X[i], X[i][0]**2, axis = 1)

print(X)

But i am getting this

IndexError                                Traceback (most recent call last)
<ipython-input-12-9bfd33261d84> in <module>()
      6     ])
      7 for i in X:
----> 8     X = np.append(X[i], X[i][0]**2, axis = 1)
      9 
     10 print(X)

IndexError: arrays used as indices must be of integer (or boolean) type

Someone please help!

Answer 1

How about concatenate:

np.concatenate((x,x**2))

Output:

array([[ 0.    ,  0.    ],
       [ 1.    ,  0.    ],
       [ 2.61  , -1.28  ],
       [-0.59  ,  2.1   ],
       [ 0.    ,  0.    ],
       [ 1.    ,  0.    ],
       [ 6.8121,  1.6384],
       [ 0.3481,  4.41  ]])

Answer 2

In [210]: x = np.array([ 
     ...:     [0,0], 
     ...:     [1,0], 
     ...:     [2.61,-1.28], 
     ...:     [-0.59,2.1] 
     ...: ]) 
     ...:                                                                                              
In [211]: x            # (4,2) array                                                                                            
Out[211]: 
array([[ 0.  ,  0.  ],
       [ 1.  ,  0.  ],
       [ 2.61, -1.28],
       [-0.59,  2.1 ]])
In [212]: for i in x:       # iterate on rows
     ...:     print(i)        # i is a row, not an index x[i] would be wrong 
     ...:                                                                                              
[0. 0.]
[1. 0.]
[ 2.61 -1.28]
[-0.59  2.1 ]

Look at one row:

In [214]: x[2]                                                                                         
Out[214]: array([ 2.61, -1.28])

You can join that row with its square with:

In [216]: np.concatenate((x[2], x[2]**2))                                                              
Out[216]: array([ 2.61  , -1.28  ,  6.8121,  1.6384])

And doing the same for the whole array. Where possible in numpy work with the whole array, not rows and elements. It's simpler, and faster.

In [217]: np.concatenate((x, x**2), axis=1)                                                            
Out[217]: 
array([[ 0.    ,  0.    ,  0.    ,  0.    ],
       [ 1.    ,  0.    ,  1.    ,  0.    ],
       [ 2.61  , -1.28  ,  6.8121,  1.6384],
       [-0.59  ,  2.1   ,  0.3481,  4.41  ]])