fix gkernel

pyleoclim/core/series.py

@@ -3976,17 +3976,20 @@ def interp(self, method='linear', keep_log= False, **kwargs):
 
         return new
 
-    def gkernel(self, step_type='median', keep_log = False, **kwargs):
+    def gkernel(self, step_style='max', keep_log = False, step_type=None, **kwargs):
         ''' Coarse-grain a Series object via a Gaussian kernel.
 
         Like .bin() this technique is conservative and uses the max space between points
         as the default spacing. Unlike .bin(), gkernel() uses a gaussian kernel to
         calculate the weighted average of the time series over these intervals.
 
+        Note that if the series being examined has very low resolution sections with few points,
+        you may need to tune the parameter for the kernel e-folding scale (h).
+
         Parameters
         ----------
 
-        step_type : str
+        step_style : str
 
             type of timestep: 'mean', 'median', or 'max' of the time increments
 
@@ -4009,10 +4012,12 @@ def gkernel(self, step_type='median', keep_log = False, **kwargs):
 
         pyleoclim.utils.tsutils.gkernel : application of a Gaussian kernel
         '''
-
+        if step_type is not None:
+            warnings.warn("step_type is deprecated. Please use step_style instead",
+                          DeprecationWarning, stacklevel=2)
+
         new=self.copy()
-
-        ti, vi = tsutils.gkernel(self.time, self.value, **kwargs) # apply kernel
+        ti, vi = tsutils.gkernel(self.time, self.value, step_style=step_style, **kwargs) # apply kernel
         new.time = ti
         new.value = vi
 

pyleoclim/tests/test_core_Series.py

@@ -799,7 +799,19 @@ def test_gkernel_t2(self):
 
         ts2 = pyleo.Series(time=t_unevenly, value=v_unevenly)
         ts_interp=ts2.gkernel(h=15)
+
+    def test_gkernel_t3(self):
+        ''' Test the gkernel function with specified step_style'''
 
+        ts = gen_ts(nt=550, alpha=1.0)
+        # randomly remove some data pts
+        n_del = 50
+        deleted_idx = np.random.choice(range(np.size(ts.time)), n_del, replace=False)
+        t_unevenly =  np.delete(ts.time, deleted_idx)
+        v_unevenly =  np.delete(ts.value, deleted_idx)
+
+        ts2 = pyleo.Series(time=t_unevenly, value=v_unevenly)
+        ts_interp=ts2.gkernel(step_style='median')
 
 class TestUISeriesInterp():
     ''' Unit tests for the interpolation function

pyleoclim/utils/tsutils.py

@@ -474,8 +474,7 @@ def gkernel(t,y, h = 3.0, step=None,start=None,stop=None, step_style = None, eve
         if len(xslice)>0:
             d      = xslice-time_axis[i]
             weight = kernel(d,h)
-            yc[i]  = sum(weight*yslice)
-            yc    /= sum(weight) # normalize by the sum of weights
+            yc[i]  = sum(weight*yslice)/sum(weight) # normalize by the sum of weights
         else:
             yc[i] = np.nan