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I am using version 1.5.1 of numpy and Python 2.6.6.
I am reading a binary file into a numpy array:
>>> dt = np.dtype('<u4,<i2,<i2,<i2,<i2,<i2,<i2,<i2,<i2,u1,u1,u1,u1')
>>> file_data = np.fromfile(os.path.join(folder,f), dtype=dt)
This works just fine. Examining the result:
>>> type(file_data)
<type 'numpy.ndarray'>
>>> file_data
array([(3571121L, -54, 103, 1, 50, 48, 469, 588, -10, 0, 102, 0, 0),
(3571122L, -78, 20, 25, 45, 44, 495, 397, -211, 0, 102, 0, 0),
(3571123L, -69, -48, 23, 60, 19, 317, -26, -151, 0, 102, 0, 0), ...,
(3691138L, -53, 52, -2, -11, 76, 988, 288, -101, 1, 102, 0, 0),
(3691139L, -11, 21, -27, 25, 47, 986, 253, 176, 1, 102, 0, 0),
(3691140L, -30, -19, -63, 59, 12, 729, 23, 302, 1, 102, 0, 0)],
dtype=[('f0', '<u4'), ('f1', '<i2'), ('f2', '<i2'), ... , ('f12', '|u1')])
>>> file_data[0]
(3571121L, -54, 103, 1, 50, 48, 469, 588, -10, 0, 102, 0, 0)
>>> file_data[0][0]
3571121
>>> len(file_data)
120020
When I try to slice the first column:
>>> file_data[:,0]
I get:
IndexError: invalid index.
I have looked at simple examples and was able to do the slicing:
>>> a = np.array([(1,2,3),(4,5,6)])
>>> a[:,0]
array([1, 4])
The only difference I can see between my case and the simple example is that I am using the dtype. What I am doing wrong?
687
The Python "IndexError: invalid index to scalar variable" occurs when we try to access a numpy scalar like an integer or a float at a specific index. To solve the error, make sure the value you are trying to index is an array or another sequence with the right dimensions.
To slice elements from two-dimensional arrays, you need to specify both a row index and a column index as [row_index, column_index] . For example, you can use the index [1,2] to query the element at the second row, third column in precip_2002_2013 .
Solution of the invalid index to scalar variable Error You can access directly using the variable name only. And if it is an array of single-dimensional then don't use the square bracket two times to access the element. Just use the single square bracket with the index inside it.
Negative indices are interpreted as counting from the end of the array (i.e., if i < 0, it means n_i + i). All arrays generated by basic slicing are always views of the original array. The standard rules of sequence slicing apply to basic slicing on a per-dimension basis (including using a step index).
When you set the dtype like that, you are creating a Record Array. Numpy treats that like a 1D array of elements of your dtype. There's a fundamental difference between
file_data[0][0]
and
file_data[0,0]
In the first, you are asking for the first element of a 1D array and then retrieving the first element of that returned element. In the second, you are asking for the element in the first row of the first column of a 2D array. That's why you are getting the IndexError.
If you want to access an individual element using 2D notation, you can create a view and work with that. Unfortunately, AFAIK if you want to treat your object like a 2D array, all elements have to have the same dtype.
96
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