Numpy.genfromtxt deleting square brackets in dtype.names

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小蘑菇
小蘑菇 2020-12-20 00:40

I\'m trying to read in data from files using numpy.genfromtxt. I set the names parameter to a comma-separated list of strings, such as

names = [\'a\', \'[b         


        
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  • 2020-12-20 00:55

    I've complained about this field name mangling behavior before on the numpy issue tracker and mailing list. It has also cropped up in several previous questions on SO.

    In fact, by default np.genfromtxt will mangle field names even if you specify them directly by passing a list of strings as the names= parameter:

    import numpy as np
    from io import BytesIO
    
    s = '[5],name with spaces,(x-1)!\n1,2,3\n4,5,6'
    
    x = np.genfromtxt(BytesIO(s), delimiter=',', names=True)
    print(repr(x))
    # array([(1.0, 2.0, 3.0), (4.0, 5.0, 6.0)], 
    #       dtype=[('5', '<f4'), ('name_with_spaces', '<f4'), ('x1\n1', '<f4')])
    
    names = s.split(',')[:3]
    x = np.genfromtxt(BytesIO(s), delimiter=',', skip_header=1, names=names)
    print(repr(x))
    # array([(1.0, 2.0, 3.0), (4.0, 5.0, 6.0)], 
    #       dtype=[('5', '<f4'), ('name_with_spaces', '<f4'), ('x1\n1', '<f4')])
    

    This happens despite the fact that field names containing non-alphanumeric characters are perfectly legal:

    x2 = np.empty(2, dtype=dtype)
    x2[:] = [(1.0, 2.0, 3.0), (4.0, 5.0, 6.0)]
    print(repr(x2))
    # array([(1.0, 2.0, 3.0), (4.0, 5.0, 6.0)], 
    #       dtype=[('[5]', '<f4'), ('name with spaces', '<f4'), ('(x-1)!\n1', '<f4')])
    

    The logic of this behavior escapes me.


    As you've seen, passing None as the deletechars= argument is not enough to prevent this from happening, since this argument gets initialized internally to a set of default characters within numpy._iotools.NameValidator.

    However, you can pass an empty sequence instead:

    x = np.genfromtxt(BytesIO(s), delimiter=',', names=True, deletechars='')
    print(repr(x))
    # array([(1.0, 2.0, 3.0), (4.0, 5.0, 6.0)], 
    #       dtype=[('[5]', '<f8'), ('name_with_spaces', '<f8'), ('(x-1)!', '<f8')])
    

    This could be an empty string, list, tuple etc. It doesn't matter as long as its length is zero.

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  • 2020-12-20 01:02

    In String formatting issue (parantheses vs underline) I found that dtype=None is required in addition to the deletechars parameter:

    https://stackoverflow.com/a/32540939/901925

    In [168]: np.genfromtxt([b'1,2,3'],names=['a','[b]','xcx'],delimiter=',',deletechars='',dtype=None)
    Out[168]: 
    array((1, 2, 3), 
          dtype=[('a', '<i4'), ('[b]', '<i4'), ('xcx', '<i4')])
    

    With the default dtype (float), deletechars is used, but the names pass through a second validator, easy_dtype which does not get this parameter.

    In [170]: np.genfromtxt([b'1,2,3'],names=['a','[b]','xcx'],delimiter=',',deletechars='x')
    Out[170]: 
    array((1.0, 2.0, 3.0), 
          dtype=[('a', '<f8'), ('b', '<f8'), ('c', '<f8')])
    

    https://github.com/numpy/numpy/pull/4649


    Field names can be changed after loading:

    In [205]: data=np.genfromtxt([b'1 2 3 txt'],names=['a','b','c','d'],dtype=[int,float,int,'S4'])
    
    In [206]: data.dtype.names
    Out[206]: ('a', 'b', 'c', 'd')
    
    In [207]: data.dtype.names=['a','[b]','*c*','d']
    
    In [208]: data
    Out[208]: 
    array((1, 2.0, 3, 'txt'), 
          dtype=[('a', '<i4'), ('[b]', '<f8'), ('*c*', '<i4'), ('d', 'S4')])
    

    This works for names taken from the file itself:

    In [212]: data=np.genfromtxt([b'a [b] *c* d','1 2 3 txt'],dtype=[int,float,int,'S4'],names=True)
    
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