字符串格式问题(括号与下划线)

问题描述

我得到了一个包含我所有数据的文本文件

I got a text file containing all my data

data = 'B:/tempfiles/bla.dat'

从文本文件中，我列出了列标题及其类型

from the text file I'm listing the column header and their types with

col_headers = [('VW_3_Avg','<f8'),('Lvl_Max(1)','<f8')]

然后创建一个包含选项的字典变量:

Then creating a dictionary variable holding the options:

kwargs = dict(delimiter=',',\
              deletechars=' ',\
              dtype=col_headers,\
              skip_header=4,\
              skip_footer=0,\
              filling_values='NaN',\
              missing_values={'\"NAN\"'}\
              )

现在将数据导入到变量数据文件

Now importing the data to the variable datafile

datafile = scipy.genfromtxt(datafile, **kwargs)

然后我用

VW1 = datafile['VW_3_Avg']
Lv1 = datafile['Lvl_Max(1)']

它与第一个(包含下划线)完美配合，而不是第二个(括号).我得到一个错误，不仅是这个条目，还有所有包含括号的:

It works perfectly with the first one (containing underlines), not with the second (parentheses). I get an Error, not only with this entry, but with all that contain parentheses:

ValueError: field named Lvl_Max(1) not found

当我将文本文件中的括号更改为下划线时，效果很好.但我不能说为什么它不允许我使用括号——而且我无法更改文本文件格式，因为这是在外部生成的.当然，我可以用脚本将括号更改为下划线，但我认为正确处理应该不是什么大问题.在这种情况下，我在哪里以及为什么缺少正确的格式优先级?

When I change those parentheses in the text file to underlines, it works perfectly. But I can't say why it won't let me use parentheses - and I can't change the text file formatting as this is produced externally. Of course I could change the parentheses to underlines with a script, but I think it shouldn't be a big issue to get this right. Where and why am I missing the correct formatting precedence in this case?

推荐答案

行为被记录在案，NameValidator 类在 lib/_iotools.py 中解析传入genfromtxt 的名称:

The behaviour is documented, the NameValidator class in lib/_iotools.py which parses the names passed in to genfromtxt:

class NameValidator(object):
    """
    Object to validate a list of strings to use as field names.
    The strings are stripped of any non alphanumeric character, and spaces
    are replaced by '_'. During instantiation, the user can define a list
    of names to exclude, as well as a list of invalid characters. Names in
    the exclusion list are appended a '_' character.
    Once an instance has been created, it can be called with a list of
    names, and a list of valid names will be created.  The `__call__`
    method accepts an optional keyword "default" that sets the default name
    in case of ambiguity. By default this is 'f', so that names will
    default to `f0`, `f1`, etc.

您的案例中的相关行是字符串被去除了任何非字母数字字符

您可以通过在名称中包含其他非字母数字字符的列表上调用 NameValidator.validate 来查看行为:

You can see the behaviour by calling the NameValidator.validate on a list with other non alphanumeric characters in the names:

In [17]: from numpy.lib._iotools import NameValidator

In [18]: l = ["foo(1)","bar!!!","foo bar??"]

In [19]: NameValidator().validate(l)
Out[19]: ('foo1', 'bar', 'foo_bar')

同样使用 genfromtxt:

And the same using genfromtxt:

In [24]: datafile = np.genfromtxt("foo.txt", dtype=[('foo!! bar??', '<f8'), ('foo bar bar$', '<f8')], delimiter=",",defaultfmt="%")

In [25]: datafile.dtype
Out[25]: dtype([('foo_bar', '<f8'), ('foo_bar_bar', '<f8')])

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