Added tests

wafo/tests/test_gaussian.py

@@ -3,6 +3,7 @@ Created on 17. juli 2010
 
 @author: pab
 '''
+import unittest
 import numpy as np
 from numpy import pi, inf
 from numpy.testing import assert_array_almost_equal
@@ -165,5 +166,5 @@ def test_prbnorm2d():
     assert_array_almost_equal(prbnorm2d(a, b, r), 0.56659121)
 
 if __name__ == '__main__':
-    import doctest
+    # import sys;sys.argv = ['', 'Test.testName']
-    doctest.testmod()
+    unittest.main()

wafo/tests/test_objects.py

@@ -4,61 +4,98 @@ Created on 5. aug. 2010
 
 @author: pab
 """
+
+import unittest
+from numpy.testing import TestCase, assert_array_almost_equal
 import wafo.data  # @UnusedImport
 import numpy as np  # @UnusedImport
+import wafo.objects as wo
+import wafo.spectrum.models as sm
+import wafo.transform.models as tm
+
+
+class TestObjects(TestCase):
+    def test_timeseries(self):
+
+        x = wafo.data.sea()
+        ts = wo.mat2timeseries(x)
+        assert_array_almost_equal(ts.sampling_period(), 0.25)
+
+        S = ts.tospecdata()
+        assert_array_almost_equal(S.data[:10],
+                                  [0.00913087,  0.00881073,  0.00791944,
+                                   0.00664244,  0.00522429, 0.00389816,
+                                   0.00282753,  0.00207843,  0.00162678,
+                                   0.0013916])
+
+        rf = ts.tocovdata(lag=150)
+        assert_array_almost_equal(rf.data[:10],
+                                  [0.22368637,  0.20838473,  0.17110733,
+                                   0.12237803,  0.07024054, 0.02064859,
+                                   -0.02218831, -0.0555993, -0.07859847,
+                                   -0.09166187])
+
+    def test_timeseries_trdata(self):
+        Hs = 7.0
+        Sj = sm.Jonswap(Hm0=Hs)
+        S = Sj.tospecdata()  # Make spectrum object from numerical values
+        S.tr = tm.TrOchi(mean=0, skew=0.16, kurt=0, sigma=Hs/4, ysigma=Hs/4)
+        xs = S.sim(ns=2**20, iseed=10)
+        ts = wo.mat2timeseries(xs)
+        g0, _gemp = ts.trdata(monitor=False)  # Not Monitor the development
+
+        # Equal weight on all points
+        g1, _gemp = ts.trdata(method='mnonlinear', gvar=0.5)
+
+        # Less weight on the ends
+        g2, _gemp = ts.trdata(method='nonlinear', gvar=[3.5, 0.5, 3.5])
+        self.assert_(1.2 < S.tr.dist2gauss() < 1.6)
+        self.assert_(1.65 < g0.dist2gauss() < 2.05)
+        self.assert_(0.54 < g1.dist2gauss() < 0.95)
+        self.assert_(1.5 < g2.dist2gauss() < 1.9)
+
+    def test_cycles_and_levelcrossings(self):
+
+        x = wafo.data.sea()
+        ts = wo.mat2timeseries(x)
+
+        tp = ts.turning_points()
+        assert_array_almost_equal(tp.data[:10],
+                                  [-1.200495,  0.839505, -0.090495, -0.020495,
+                                   -0.090495, -0.040495, -0.160495,  0.259505,
+                                   -0.430495, -0.080495]
+                                  )
+
+        mm = tp.cycle_pairs()
+        assert_array_almost_equal(mm.data[:10],
+                                  [0.839505, -0.020495, -0.040495,  0.259505,
+                                   -0.080495, -0.080495, 0.349505,  0.859505,
+                                   0.009505,  0.319505])
+
+        lc = mm.level_crossings()
+
+        assert_array_almost_equal(lc.data[:10],
+                                  [0.,  1.,  2.,  2.,  3.,  4.,
+                                   5.,  6.,  7.,  9.])
+
+    def test_levelcrossings_extrapolate(self):
+        x = wafo.data.sea()
+        ts = wo.mat2timeseries(x)
+
+        tp = ts.turning_points()
+        mm = tp.cycle_pairs()
+        lc = mm.level_crossings()
+
+        s = x[:, 1].std()
+        lc_gpd = lc.extrapolate(-2 * s, 2 * s, dist='rayleigh')
+        assert_array_almost_equal(lc_gpd.data[:10],
+                                  [1.789254e-37,   2.610988e-37,
+                                   3.807130e-37,   5.546901e-37,
+                                   8.075384e-37,   1.174724e-36,
+                                   1.707531e-36,   2.480054e-36,
+                                   3.599263e-36,   5.219466e-36])
 
 
-def test_timeseries():
+if __name__ == "__main__":
-    '''
+    # import sys;sys.argv = ['', 'Test.testName']
-    >>> import wafo.data
+    unittest.main()
-    >>> import wafo.objects as wo
-    >>> x = wafo.data.sea()
-    >>> ts = wo.mat2timeseries(x)
-    >>> ts.sampling_period()
-    0.25
-
-    Estimate spectrum
-    >>> S = ts.tospecdata()
-    >>> S.data[:10]
-    array([ 0.00913087,  0.00881073,  0.00791944,  0.00664244,  0.00522429,
-            0.00389816,  0.00282753,  0.00207843,  0.00162678,  0.0013916 ])
-
-    Estimated covariance function
-    >>> rf = ts.tocovdata(lag=150)
-    >>> rf.data[:10]
-    array([ 0.22368637,  0.20838473,  0.17110733,  0.12237803,  0.07024054,
-            0.02064859, -0.02218831, -0.0555993 , -0.07859847, -0.09166187])
-    '''
-
-
-def test_timeseries_trdata():
-    '''
-    >>> import wafo.spectrum.models as sm
-    >>> import wafo.transform.models as tm
-    >>> from wafo.objects import mat2timeseries
-    >>> Hs = 7.0
-    >>> Sj = sm.Jonswap(Hm0=Hs)
-    >>> S = Sj.tospecdata()   #Make spectrum object from numerical values
-    >>> S.tr = tm.TrOchi(mean=0, skew=0.16, kurt=0, sigma=Hs/4, ysigma=Hs/4)
-    >>> xs = S.sim(ns=2**20, iseed=10)
-    >>> ts = mat2timeseries(xs)
-    >>> g0, gemp = ts.trdata(monitor=True) # Monitor the development
-
-    # Equal weight on all points
-    >>> g1, gemp = ts.trdata(method='mnonlinear', gvar=0.5 )
-
-      # Less weight on the ends
-    >>> g2, gemp = ts.trdata(method='nonlinear', gvar=[3.5, 0.5, 3.5])
-    >>> 1.2 < S.tr.dist2gauss() < 1.6
-    True
-    >>> 1.65 < g0.dist2gauss() < 2.05
-    True
-    >>> 0.54 < g1.dist2gauss() < 0.95
-    True
-    >>> 1.5 < g2.dist2gauss() < 1.9
-    True
-
-    '''
-if __name__ == '__main__':
-    import doctest
-    doctest.testmod()