Exponential window can be used

Author: rbenes

pandas/core/window.py

@@ -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
@@ -623,20 +624,30 @@ def _validate_win_type(win_type, kwargs):
                 arg_map = {'kaiser': ['beta'],
                            'gaussian': ['std'],
                            'general_gaussian': ['power', 'width'],
-                           'slepian': ['width']}
+                           'slepian': ['width'],
+                           'exponential': ['center', 'tau']}
+                immutable_args_map = {'exponential': {'center': None}}
+
                 if win_type in arg_map:
+                    immutable_args = immutable_args_map.get(win_type, {})
                     return tuple([win_type] + _pop_args(win_type,
                                                         arg_map[win_type],
+                                                        immutable_args,
                                                         kwargs))
+
                 return win_type
 
-            def _pop_args(win_type, arg_names, kwargs):
+            def _pop_args(win_type, arg_names, immutable_args, kwargs):
                 msg = '%s window requires %%s' % win_type
                 all_args = []
                 for n in arg_names:
-                    if n not in kwargs:
+                    if n in immutable_args:
+                        value = immutable_args[n]
+                    elif n in kwargs:
+                        value = kwargs.pop(n)
+                    else:
                         raise ValueError(msg % n)
-                    all_args.append(kwargs.pop(n))
+                    all_args.append(value)
                 return all_args
 
             win_type = _validate_win_type(self.win_type, kwargs)

pandas/tests/test_window.py

@@ -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
 
@@ -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])
@@ -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])
@@ -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()