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Merged
merged 4 commits into from
May 7, 2019
Merged

ENH: Poisson exponential window #26243

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99f498b
Exponential window can be used
rbenes Apr 29, 2019
1b3d957
Whats new added
rbenes Apr 29, 2019
d867ad4
Simplify
rbenes May 4, 2019
af96493
computation.rst updated
rbenes May 7, 2019
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3 changes: 2 additions & 1 deletion doc/source/user_guide/computation.rst
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Expand Up @@ -365,7 +365,8 @@ The list of recognized types are the `scipy.signal window functions
* ``kaiser`` (needs beta)
* ``gaussian`` (needs std)
* ``general_gaussian`` (needs power, width)
* ``slepian`` (needs width).
* ``slepian`` (needs width)
* ``exponential`` (needs tau).

.. ipython:: python

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1 change: 1 addition & 0 deletions doc/source/whatsnew/v0.25.0.rst
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Expand Up @@ -39,6 +39,7 @@ Other Enhancements
- :class:`datetime.timezone` objects are now supported as arguments to timezone methods and constructors (:issue:`25065`)
- :meth:`DataFrame.query` and :meth:`DataFrame.eval` now supports quoting column names with backticks to refer to names with spaces (:issue:`6508`)
- :func:`merge_asof` now gives a more clear error message when merge keys are categoricals that are not equal (:issue:`26136`)
- :meth:`pandas.core.window.Rolling` supports exponential (or Poisson) window type (:issue:`21303`)

.. _whatsnew_0250.api_breaking:

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19 changes: 14 additions & 5 deletions pandas/core/window.py
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Expand Up @@ -504,7 +504,8 @@ class Window(_Window):
* ``kaiser`` (needs beta)
* ``gaussian`` (needs std)
* ``general_gaussian`` (needs power, width)
* ``slepian`` (needs width).
* ``slepian`` (needs width)
* ``exponential`` (needs tau), center is set to None.

If ``win_type=None`` all points are evenly weighted. To learn more about
different window types see `scipy.signal window functions
Expand Down Expand Up @@ -623,11 +624,19 @@ def _validate_win_type(win_type, kwargs):
arg_map = {'kaiser': ['beta'],
'gaussian': ['std'],
'general_gaussian': ['power', 'width'],
'slepian': ['width']}
'slepian': ['width'],
'exponential': ['tau'],
}

if win_type in arg_map:
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why are you changing the structure of passing args here? was there some reason the existing would not just work?

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For exponential window kwargs contains {tau: 10} but I need to get back tuple (None, 10) (first None is the center parameter required for exponential window). So I pass the immutable_args to _pop_args function that is the second source of params (another than kwargs).

Another possible option can be add {"center": None} to kwargs for exponential window and let _pop_args without change.
More info about exponential window is in comments above.

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yes pls do this instead

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The code is now without immutable_args. As I wrote in another comment, I simplyfied my code even more because other window (that would be possibly implemented in future) in scipy will not need such handling like the exponential one. So please check the last code version.
Thanks.

return tuple([win_type] + _pop_args(win_type,
arg_map[win_type],
kwargs))
win_args = _pop_args(win_type, arg_map[win_type], kwargs)
if win_type == 'exponential':
# exponential window requires the first arg (center)
# to be set to None (necessary for symmetric window)
win_args.insert(0, None)

return tuple([win_type] + win_args)

return win_type

def _pop_args(win_type, arg_names, kwargs):
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13 changes: 9 additions & 4 deletions pandas/tests/test_window.py
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Expand Up @@ -42,7 +42,8 @@ def win_types(request):
return request.param


@pytest.fixture(params=['kaiser', 'gaussian', 'general_gaussian'])
@pytest.fixture(params=['kaiser', 'gaussian', 'general_gaussian',
'exponential'])
def win_types_special(request):
return request.param

Expand Down Expand Up @@ -1260,7 +1261,8 @@ def test_cmov_window_special(self, win_types_special):
kwds = {
'kaiser': {'beta': 1.},
'gaussian': {'std': 1.},
'general_gaussian': {'power': 2., 'width': 2.}}
'general_gaussian': {'power': 2., 'width': 2.},
'exponential': {'tau': 10}}

vals = np.array([6.95, 15.21, 4.72, 9.12, 13.81, 13.49, 16.68, 9.48,
10.63, 14.48])
Expand All @@ -1271,7 +1273,9 @@ def test_cmov_window_special(self, win_types_special):
'general_gaussian': [np.nan, np.nan, 9.85011, 10.71589, 11.73161,
13.08516, 12.95111, 12.74577, np.nan, np.nan],
'kaiser': [np.nan, np.nan, 9.86851, 11.02969, 11.65161, 12.75129,
12.90702, 12.83757, np.nan, np.nan]
12.90702, 12.83757, np.nan, np.nan],
'exponential': [np.nan, np.nan, 9.83364, 11.10472, 11.64551,
12.66138, 12.92379, 12.83770, np.nan, np.nan],
}

xp = Series(xps[win_types_special])
Expand All @@ -1287,7 +1291,8 @@ def test_cmov_window_special_linear_range(self, win_types_special):
'kaiser': {'beta': 1.},
'gaussian': {'std': 1.},
'general_gaussian': {'power': 2., 'width': 2.},
'slepian': {'width': 0.5}}
'slepian': {'width': 0.5},
'exponential': {'tau': 10}}

vals = np.array(range(10), dtype=np.float)
xp = vals.copy()
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