diff --git a/wafo/misc.py b/wafo/misc.py
index 966c628..e022728 100644
--- a/wafo/misc.py
+++ b/wafo/misc.py
@@ -602,8 +602,8 @@ def parse_kwargs(options, **kwargs):
     Example
     >>> opt = dict(arg1=2, arg2=3)
     >>> opt = parse_kwargs(opt,arg2=100)
-    >>> print(opt)
-    {'arg1': 2, 'arg2': 100}
+    >>> opt == {'arg1': 2, 'arg2': 100}
+    True
     >>> opt2 = dict(arg2=101)
     >>> opt = parse_kwargs(opt,**opt2)
 
@@ -1005,9 +1005,9 @@ def findrfc_astm(tp):
     # the sig_rfc was constructed too big in rainflow.rf3, so
     # reduce the sig_rfc array as done originally by a matlab mex c function
     n = len(sig_rfc)
-    sig_rfc = sig_rfc.__getslice__(0, n - cnr[0])
+    # sig_rfc = sig_rfc.__getslice__(0, n - cnr[0])
     # sig_rfc holds the actual rainflow counted cycles, not the indices
-    return sig_rfc
+    return sig_rfc[:n - cnr[0]]
 
 
 def findrfc(tp, h=0.0, method='clib'):
diff --git a/wafo/objects.py b/wafo/objects.py
index 5cb1765..1d44476 100644
--- a/wafo/objects.py
+++ b/wafo/objects.py
@@ -1505,16 +1505,24 @@ class TimeSeries(PlotData):
         >>> x = wd.sea()
         >>> ts = wo.mat2timeseries(x)
         >>> wp = ts.wave_parameters()
+        >>> true_wp = {'Ac':[ 0.25950546,  0.34950546],
+        ...            'At': [ 0.16049454,  0.43049454],
+        ...            'Hu': [ 0.69,  0.86],
+        ...            'Hd': [ 0.42,  0.78],
+        ...            'Tu': [ 6.10295202,  3.36978685],
+        ...            'Td': [ 3.84377468,  6.35707656],
+        ...            'Tcf': [ 0.42656819,  0.57361617],
+        ...            'Tcb': [ 0.93355982,  1.04063638]}
         >>> for name in ['Ac', 'At', 'Hu', 'Hd', 'Tu', 'Td', 'Tcf', 'Tcb']:
-        ...    print('%s' % name, wp[name][:2])
-        ('Ac', array([ 0.25950546,  0.34950546]))
-        ('At', array([ 0.16049454,  0.43049454]))
-        ('Hu', array([ 0.69,  0.86]))
-        ('Hd', array([ 0.42,  0.78]))
-        ('Tu', array([ 6.10295202,  3.36978685]))
-        ('Td', array([ 3.84377468,  6.35707656]))
-        ('Tcf', array([ 0.42656819,  0.57361617]))
-        ('Tcb', array([ 0.93355982,  1.04063638]))
+        ...    np.allclose(wp[name][:2], true_wp[name])
+        True
+        True
+        True
+        True
+        True
+        True
+        True
+        True
 
         import pylab as plt
         h = plt.plot(wp['Td'],wp['Hd'],'.')