diff --git a/wafo/kdetools/kdetools.py b/wafo/kdetools/kdetools.py
index 3be3d19..56a75aa 100644
--- a/wafo/kdetools/kdetools.py
+++ b/wafo/kdetools/kdetools.py
@@ -71,6 +71,14 @@ class _KDE(object):
         self.xmax = xmax
         self.kernel = kernel if kernel else Kernel('gauss')
 
+    @property
+    def inc(self):
+        return self._inc
+
+    @inc.setter
+    def inc(self, inc):
+        self._inc = inc
+
     @property
     def dataset(self):
         return self._dataset
@@ -121,21 +129,6 @@ class _KDE(object):
     def _check_xmax(self, xmax):
         return xmax
 
-    def get_args(self, xmin=None, xmax=None):
-        sxmin = self.xmin
-        if xmin is not None:
-            sxmin = np.minimum(xmin, sxmin)
-
-        sxmax = self.xmax
-        if xmax is not None:
-            sxmax = np.maximum(xmax, sxmax)
-
-        args = []
-        inc = self.inc
-        for i in range(self.d):
-            args.append(np.linspace(sxmin[i], sxmax[i], inc))
-        return args
-
     def eval_grid_fast(self, *args, **kwds):
         """Evaluate the estimated pdf on a grid using fft.
 
@@ -205,6 +198,21 @@ class _KDE(object):
             self._add_contour_levels(wdata)
         return wdata
 
+    def get_args(self, xmin=None, xmax=None):
+        sxmin = self.xmin
+        if xmin is not None:
+            sxmin = np.minimum(xmin, sxmin)
+
+        sxmax = self.xmax
+        if xmax is not None:
+            sxmax = np.maximum(xmax, sxmax)
+
+        args = []
+        inc = self.inc
+        for i in range(self.d):
+            args.append(np.linspace(sxmin[i], sxmax[i], inc))
+        return args
+
     def eval_grid_fun(self, eval_grd, *args, **kwds):
         if len(args) == 0:
             args = self.get_args()
@@ -1355,9 +1363,9 @@ def kreg_demo1(hs=None, fast=False, fun='hisj'):
         -0.08348306, 0.00812816, -0.00908206, 0.14528945, 0.02901065])
     x = np.linspace(0, 1, N)
 
-    var_1 = 0.3 ** 2
-    var_2 = 0.7 ** 2
-    y0 = np.exp(-x ** 2 / (2 * var_1)) + 1.3*np.exp(-(x - 1) ** 2 / (2 * var_2))
+    va_1 = 0.3 ** 2
+    va_2 = 0.7 ** 2
+    y0 = np.exp(-x ** 2 / (2 * va_1)) + 1.3*np.exp(-(x - 1) ** 2 / (2 * va_2))
     y = y0 + ei
     kernel = Kernel('gauss', fun=fun)
     hopt = kernel.hisj(x)
diff --git a/wafo/kdetools/tests/data.py b/wafo/kdetools/tests/data.py
index 68ee9a3..bbf123f 100644
--- a/wafo/kdetools/tests/data.py
+++ b/wafo/kdetools/tests/data.py
@@ -3,7 +3,10 @@ Created on 29. des. 2016
 
 @author: pab
 '''
+__all__ = ['DATA1D', 'DATA2D', 'DATA3D']
+
 # N = 20
+# import numpy as np
 # DATA1D = np.random.rayleigh(1, size=(N,))
 # print(DATA1D.tolist())
 DATA1D = [0.6493244636902034, 0.6562823794215175, 1.0905183896319681,
@@ -35,6 +38,3 @@ DATA3D = [[0.932896, 0.89522635, 0.80636346, 1.32283371, 0.27125435,
            1.66888649, 0.69036947, 0.99961448, 0.30657267, 0.98798713,
            0.83298728, 1.83334948, 1.90144186, 1.25781913, 0.07122458,
            2.42340852, 2.41342037, 0.87233305, 1.17537114, 1.69505988]]
-
-if __name__ == '__main__':
-    pass