diff --git a/wafo/gaussian.py b/wafo/gaussian.py
index e77d260..c961a80 100644
--- a/wafo/gaussian.py
+++ b/wafo/gaussian.py
@@ -91,8 +91,9 @@ class Rind(object):
             Cov(Xi,Xj) = 0.3 for i~=j and
             Cov(Xi,Xi) = 1   otherwise
     >>> import wafo.gaussian as wg
+    >>> import numpy as np
     >>> n = 5
-    >>> Blo =-np.inf; Bup=-1.2; indI=[-1, n-1]  # Barriers
+    >>> Blo =-np.inf; Bup=-1.2; indI=np.array([-1, n-1], dtype=int)  # Barriers
     >>> m = np.zeros(n); rho = 0.3;
     >>> Sc =(np.ones((n,n))-np.eye(n))*rho+np.eye(n)
     >>> rind = wg.Rind()
diff --git a/wafo/sg_filter/_core.py b/wafo/sg_filter/_core.py
index aa4c942..454a404 100644
--- a/wafo/sg_filter/_core.py
+++ b/wafo/sg_filter/_core.py
@@ -248,7 +248,7 @@ def evar(y):
     sh0 = y.shape
 
     S = np.zeros(sh0)
-    sh1 = np.ones((d,))
+    sh1 = np.ones((d,), dtype=np.int64)
     cos = np.cos
     for i in range(d):
         ni = sh0[i]
diff --git a/wafo/spectrum/core.py b/wafo/spectrum/core.py
index d4909cf..16e111b 100644
--- a/wafo/spectrum/core.py
+++ b/wafo/spectrum/core.py
@@ -758,16 +758,16 @@ class SpecData1D(PlotData):
             raise ValueError(txt)
 
         if rate is None:
-            rate = 1  # %interpolation rate
+            rate = 1  # interpolation rate
         elif rate > 16:
             rate = 16
         else:  # make sure rate is a power of 2
             rate = 2 ** nextpow2(rate)
 
         if nt is None:
-            nt = rate * (n_f - 1)
+            nt = int(rate * (n_f - 1))
         else:  # check if Nt is ok
-            nt = minimum(nt, rate * (n_f - 1))
+            nt = int(minimum(nt, rate * (n_f - 1)))
 
         spec = self.copy()
 
diff --git a/wafo/tests/test_gaussian.py b/wafo/tests/test_gaussian.py
index 066e150..e043a5f 100644
--- a/wafo/tests/test_gaussian.py
+++ b/wafo/tests/test_gaussian.py
@@ -17,7 +17,7 @@ def test_rind():
     n = 5
     Blo = -np.inf
     Bup = -1.2
-    indI = [-1, n - 1]  # Barriers
+    indI = np.array([-1, n - 1], dtype=int)  # Barriers
     m = np.zeros(n)
     rho = 0.3
     Sc = (np.ones((n, n)) - np.eye(n)) * rho + np.eye(n)