@@ -51,7 +51,7 @@ def setUp(self):
5151 self .pparams = {}
5252 self .pparams ['lambda_s' ] = np .array ([- 0.1 * 1j ], dtype = 'complex' )
5353 self .pparams ['lambda_f' ] = np .array ([- 1.0 * 1j ], dtype = 'complex' )
54- self .pparams ['u0' ] = 1.0
54+ self .pparams ['u0' ] = np . random . rand ()
5555 self .swparams = {}
5656 self .swparams ['collocation_class' ] = collclass .CollGaussLobatto
5757 self .swparams ['num_nodes' ] = 2
@@ -120,7 +120,7 @@ def test_sweepequalmatrix(self):
120120 #
121121 # Make sure the implemented update formula matches the matrix update formula
122122 #
123- @unittest .skip ("Needs fix of isse #52 before passing" )
123+ @unittest .skip ("Needs fix of issue #52 before passing" )
124124 def test_updateformula (self ):
125125
126126 step , level , problem , nnodes = self .setupLevelStepProblem ()
@@ -206,7 +206,7 @@ def test_manysweepsequalmatrix(self):
206206 #
207207 # Make sure that update function for K sweeps computed from K-sweep matrix gives same result as K sweeps in node-to-node form plus compute_end_point
208208 #
209- @unittest .skip ("Needs fix of isse #52 before passing" )
209+ @unittest .skip ("Needs fix of issue #52 before passing" )
210210 def test_maysweepupdate (self ):
211211 step , level , problem , nnodes = self .setupLevelStepProblem ()
212212 step .levels [0 ].sweep .predict ()
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