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class_i is an m x n numpy array:

list = []
class_list=[class1,class2,class3,class4,class5,class6,class7]
for class_i in class_list:
   #data processing here
   list_1.append(class_i)

list_1 = np.array(list)

The list_1 numpy array contains the classes as in the form:

[[ 314.5513238  314.4571136  314.2739476 ...      314.6        314.6        314.6      ]
 [ 314.5890785  314.5254568  314.4539721 ...      314.6        314.6        314.6      ]
 [ 314.5886471  314.4992394  314.3350225 ...      314.6        314.6        314.6      ]
 ...

which is wrong, it does not contain every single value of the numpy classes.

Any way to fix this?

Improve this question
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  • 5
    I would avoid using list as a variable name to prevent shadowing the built-in list function. And to achieve what you want why not just a = np.array(class_list) Commented Apr 12, 2015 at 15:34
  • this is just an example, there is more processing of data in the for loop Commented Apr 12, 2015 at 15:35
  • What's the shape of list_1? I don't think there's an issue with the append. What do you get with np.array(class_list)? And regarding the ... - that's just a display feature. Commented Apr 12, 2015 at 16:36
  • class_i has shape (52L, 350L) and list_1 has shape (7L,) (wrong) Commented Apr 13, 2015 at 7:37
  • 1
    What shape do you want the output array list_1 to have? The row and column dimensions of the arrays in list do not all match. Commented Apr 16, 2015 at 12:36
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