[英]How to get rid of NaturalNameWarning?
My script is doing following things:我的脚本正在做以下事情:
trc
file (UHF Measurement)trc
文件中读取时间序列(UHF 测量)pd.DataFrame
pd.DataFrame
DataFrames
into one hdf5
fileDataFrames
保存到一个hdf5
文件中This works fine but the tables
module seems to throw a NaturalNameWarning
for every single DataFrame
.这工作正常,但
tables
模块似乎为每个DataFrame
NaturalNameWarning
This is where the DataFrames
are saved to the hdf5
:这是
DataFrames
保存到hdf5
的位置:
num = 0
for idx, row in df_oszi.iloc[peaks].iterrows():
start_peak = idx - 1*1e-3
end_peak = idx + 10*1e-3 #tges=11us
df_pos = df_oszi[start_peak:end_peak]
df_pos.to_hdf('pos.h5', key=str(num))
num += 1
Output: Output:
Warning (from warnings module):
File "C:\Users\Artur\AppData\Local\Programs\Python\Python37\lib\site-packages\tables\path.py", line 157
check_attribute_name(name)
NaturalNameWarning: object name is not a valid Python identifier: '185'; it does not match the pattern ``^[a-zA-Z_][a-zA-Z0-9_]*$``; you will not be able to use natural naming to access this object; using ``getattr()`` will still work, though
You can always do this as long as you are not really going to use the table accessing.只要您不真的要使用表访问,您就可以随时执行此操作。
import warnings
from tables import NaturalNameWarning
warnings.filterwarnings('ignore', category=NaturalNameWarning)
This is a warning.这是一个警告。 It means you can't use PyTables natural naming convention to access a dataset named
185
.这意味着您不能使用 PyTables 自然命名约定来访问名为
185
的数据集。 It's not a problem if you don't plan to use PyTables.如果您不打算使用 PyTables,这不是问题。 If you want to use PyTables, you have to use
File.get_node(where)
to access this group name.如果你想使用 PyTables,你必须使用
File.get_node(where)
来访问这个组名。
Comparison of the 2 methods (where h5f is my HDF5 file object):两种方法的比较(其中 h5f 是我的 HDF5 文件对象):
h5f.get_node('/185') # works
tb1nn = h5f.root.185 # gives Python invalid syntax error
Change the group name to t185
and you can use natural naming.将组名更改为
t185
即可使用自然命名。 See example PyTables code below to show the difference:请参阅下面的示例 PyTables 代码以显示差异:
import tables as tb
import numpy as np
arr = np.arange(10.)
ds_dt = ds_dt= ( [ ('f1', float) ] )
rec_arr = np.rec.array(arr,dtype=ds_dt)
with tb.File('natname.h5','w') as h5f:
tb1 = h5f.create_table('/','t185',obj=rec_arr)
tb1nn = h5f.root.t185
print (tb1nn.nrows)
tb2 = h5f.create_table('/','185',obj=rec_arr)
# tb2nn = h5f.root.185 # will give Python syntax error
tb2un = h5f.get_node('/185')
print (tb2un.nrows)
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