Member Avatar for Alex9385

Hi,

I would like to select rows from a 2D numpy array according to a condition. I would like to get a 2D results array directly without the need of the costly np.reshape statement.

Does anybody know how to assemble array b more efficiently?

Thanks,
Alexander

>>> a = np.array([[0, 0.01, 1], [1, 0.02, 1], [2, 0.03, 2], [3, 0.04, 2], [4, 0.05, 3], [5, 0.06, 3]])

>>> a
array([[ 0.  ,  0.01,  1.  ],
       [ 1.  ,  0.02,  1.  ],
       [ 2.  ,  0.03,  2.  ],
       [ 3.  ,  0.04,  2.  ],
       [ 4.  ,  0.05,  3.  ],
       [ 5.  ,  0.06,  3.  ]])

>>> b = np.empty(0)
>>> for i in range(a.shape[0]):
...     if a[i,2] == 1.0:
...         b = np.append(b, a[i], axis=0)
>>> b = b.reshape(b.shape[0]/a.shape[1], a.shape[1])

>>> b
array([[ 0.  ,  0.01,  1.  ],
       [ 1.  ,  0.02,  1.  ]])
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  • Latest Post Latest Post by TrustyTony
Member Avatar for TrustyTony 
>>> b = a[a[:,2]==1]
>>> b
array([[ 0.  ,  0.01,  1.  ],
       [ 1.  ,  0.02,  1.  ]])
>>>
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