Hdf5/ TimedeltaIndex storing not working property (table format)
#### When i save DataFrame with method to_hdf and i passed parameter format="table" I get strange behavior when I read the file, because my index is a different datatype than I recorded a file.

~~~python
import pandas as pd
import numpy as np

df = pd.DataFrame(np.random.normal(size=(10,5)))
df.index = pd.timedelta_range(start='0s',periods=10,freq='1s')

df.index  # I get this:

TimedeltaIndex(['00:00:00', '00:00:01', '00:00:02', '00:00:03', '00:00:04',
                '00:00:05', '00:00:06', '00:00:07', '00:00:08', '00:00:09'],
               dtype='timedelta64[ns]', freq='S')

df.to_hdf("a.hdf",key="proba",format="table")
r_df = pd.read_hdf("a.hdf")
r_df.index  # The read-in table gives this:

Int64Index([         0, 1000000000, 2000000000, 3000000000, 4000000000,
            5000000000, 6000000000, 7000000000, 8000000000, 9000000000],
           dtype='int64')
~~~

#### Problem description
Index datatype is changed to Int64Index i dont know why.
I tried same with format="fixed" However, in this case, the format of the index remains timedeltaindes, which in my code is not.

I do not know what the problem is, do I do the right thing, but certainly the to_hdf method behaves differently in relation to what is the parameter format sent when the "fixed" TimedeltaIndex stay TimedeltaIndex and when the "table" is passed then it is converted to Int64Index

Thanks a lot.


<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.4.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: AMD64 Family 16 Model 4 Stepping 3, AuthenticAMD
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.23.0
pytest: 3.5.1
pip: 10.0.1
setuptools: 28.8.0
Cython: None
numpy: 1.14.4
scipy: 1.0.0
pyarrow: None
xarray: None
IPython: 6.3.1
sphinx: None
patsy: None
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: None
tables: 3.4.3
numexpr: 2.6.5
feather: None
matplotlib: 2.1.1
openpyxl: 1.7.0
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>
