Rich comparisons of Timestamps raise TypeError instead of returning NotImplemented
Hello,

#### Problem description

The problem is that pandas' ``Timestamp`` raises ``TypeError`` when compared with unsupported types (from pandas' point of view), where I think it should return ``NotImplemented`` so that comparisons are delegated to the other object (if supported). See https://github.com/pandas-dev/pandas/blob/master/pandas/_libs/tslibs/timestamps.pyx#L247

The current behaviour prevents other objects to deal with comparisons with ``Timestamp``. For instance, I developed a library that provides arithmetic operations for intervals composed of arbitrary comparable objects. In the context of this library, I defined two specific objects corresponding to negative and positive infinities (that are respectively lower and greater than "everything else"). When these objects are compared with pandas' ``Timestamp``, a ``TypeError`` is raised, preventing the comparison to be delegated to my "infinities". 

#### Code Sample

```python
# Let's define infinity, or any object whose magic methods support Timestamp
class Inf:
    def __lt__(self, o): return False
    def __le__(self, o): return isinstance(o, Inf)
    def __gt__(self, o): return not isinstance(o, Inf)
    def __ge__(self, o): return True
    def __eq__(self, o): return isinstance(o, Inf)
    def __ne__(self, o): return not self == o  # Required for Python 2
    def __repr__(self): return '+inf'

# Import pandas and create a timestamp
import pandas as pd
timestamp = pd.Timestamp('2018-11-30')

# Comparison works if compared in *that* order, because magic method is called on Inf
assert Inf() > timestamp
assert not (Inf() < timestamp)

# ... but not when magic method is called on Timestamp
assert timestamp < Inf()
```

... raises the following:

```
pandas/_libs/tslib.pyx in pandas._libs.tslib._Timestamp.__richcmp__()
TypeError: Cannot compare type 'Timestamp' with type 'Inf'
```

#### Expected Behaviour

```TypeError``` not raised, assertion holds.


#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.5.6.final.0
python-bits: 64
OS: Linux
OS-release: 4.18.17-300.fc29.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: fr_BE.UTF-8
LOCALE: fr_BE.UTF-8

pandas: 0.22.0
pytest: 3.7.4
pip: 9.0.3
setuptools: 40.2.0
Cython: None
numpy: 1.14.0
scipy: 1.0.0
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: None
patsy: None
dateutil: 2.6.1
pytz: 2017.3
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.1.2
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 1.0.1
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>


Also tested on the latest 0.23.4. 