TST: Set seed for deterministic random test

also fixed some PEP8 issues

1 files changed, 6 insertions, 103 deletions

diff --git a/numpy/lib/tests/test_polynomial.py b/numpy/lib/tests/test_polynomial.py
index d412504fa..6d2e330ec 100644
--- a/numpy/lib/tests/test_polynomial.py
+++ b/numpy/lib/tests/test_polynomial.py
@@ -92,122 +92,25 @@ class TestDocs(TestCase):
     def test_poly(self):
         assert_array_almost_equal(np.poly([3, -np.sqrt(2), np.sqrt(2)]),
                                   [1, -3, -2, 6])
-        
+
         # From matlab docs
         A = [[1, 2, 3], [4, 5, 6], [7, 8, 0]]
         assert_array_almost_equal(np.poly(A), [1, -6, -72, -27])
 
         # Should produce real output for perfect conjugates
         assert_(np.isrealobj(np.poly([+1.082j, +2.613j, -2.613j, -1.082j])))
-        assert_(np.isrealobj(np.poly([0+1j, -0+-1j, 1+2j, 1-2j, 1.+3.5j, 1-3.5j])))
+        assert_(np.isrealobj(np.poly([0+1j, -0+-1j, 1+2j,
+                                      1-2j, 1.+3.5j, 1-3.5j])))
         assert_(np.isrealobj(np.poly([1j, -1j, 1+2j, 1-2j, 1+3j, 1-3.j])))
         assert_(np.isrealobj(np.poly([1j, -1j, 1+2j, 1-2j])))
         assert_(np.isrealobj(np.poly([1j, -1j, 2j, -2j])))
         assert_(np.isrealobj(np.poly([1j, -1j])))
         assert_(np.isrealobj(np.poly([1, -1])))
-        
+
         assert_(np.iscomplexobj(np.poly([1j, -1.0000001j])))
 
-        a = np.array([ 0.156954782163288+0.984270709753367j,
-        0.622215082237431+0.815403412551784j,
-        0.192767508171407+0.025782783400578j,
-        0.185259804856739+0.062797902506984j,
-        0.642062232914462+0.258301456097768j,
-        0.554216030989744+0.563355351870913j,
-        0.257546073507044+0.525462181113635j,
-        0.069480950067410+0.929049150512649j,
-        0.096319535923967+0.157777020606244j,
-        0.708090004255965+0.844669553809902j,
-        0.425935775597273+0.125078838218321j,
-        0.970152325957828+0.851990066251973j,
-        0.704876672261560+0.193300382687057j,
-        0.973090791069053+0.373260711231715j,
-        0.858196147177131+0.05834145118111j ,
-        0.219200867770377+0.841215110962817j,
-        0.262803798327004+0.350643402581111j,
-        0.695129112984574+0.838433416963582j,
-        0.492312071206577+0.568692426000207j,
-        0.461596720878441+0.939374973294176j,
-        0.875862628133633+0.387188834096265j,
-        0.510155097370032+0.086507519082896j,
-        0.416241737182592+0.997111268069588j,
-        0.437687604607545+0.338506697660151j,
-        0.521443013907779+0.867476314513278j,
-        0.430452365593011+0.37031608091577j ,
-        0.345316632952483+0.548675748644057j,
-        0.149523073174576+0.928825871510194j,
-        0.923082836345975+0.437036121992853j,
-        0.833612375039695+0.683069897188595j,
-        0.139074221945298+0.833315145348817j,
-        0.653499684833185+0.351573042621427j,
-        0.461341447535269+0.925980448573019j,
-        0.055277550126714+0.533775159709293j,
-        0.270768043029381+0.010703056622904j,
-        0.482823304062645+0.08952461265093j ,
-        0.385633251633276+0.471519033804927j,
-        0.720444297565953+0.115168361978791j,
-        0.901325096506279+0.573680608616877j,
-        0.959391049112433+0.693872340885839j,
-        0.875681825163325+0.568590792955772j,
-        0.342690505279819+0.157893904699271j,
-        0.464525179914033+0.29171018650294j ,
-        0.009793808914706+0.561574572890755j,
-        0.728374526873344+0.766958583319351j,
-        0.236256527104613+0.398956198854611j,
-        0.005192803665847+0.6582409070444j  ,
-        0.500947297517811+0.986725666390376j,
-        0.122809093777905+0.718680008979424j,
-        0.526136583175024+0.623303763302004j,
-        0.330389021549133+0.453395938203371j,
-        0.077737539510244+0.247246328523751j,
-        0.975408285543645+0.107323424042245j,
-        0.003108270882599+0.887002919906503j,
-        0.705369913247720+0.727872932569583j,
-        0.633198660668698+0.638479991067479j,
-        0.549251188569645+0.805780727887373j,
-        0.265913392155735+0.780589896981667j,
-        0.886221583652843+0.354483251386333j,
-        0.075962413516947+0.74149612838474j ,
-        0.387765278689023+0.261920931194769j,
-        0.948020419648345+0.962386254625887j,
-        0.171825523058385+0.627697322385636j,
-        0.773639395361929+0.560492952470529j,
-        0.939715690837345+0.905583974484841j,
-        0.435045495931129+0.094656944697808j,
-        0.762649213991775+0.449112026839121j,
-        0.213651264630881+0.811270873115497j,
-        0.570908734237865+0.658844605819891j,
-        0.219391840755125+0.495267594812611j,
-        0.262407487010337+0.040859801611494j,
-        0.442188925584075+0.152902944310853j,
-        0.461651269744638+0.656796707213587j,
-        0.664031310363019+0.109070794733818j,
-        0.771690766165916+0.30133668510443j ,
-        0.920953990465468+0.805475073423507j,
-        0.573345189066715+0.150257996561483j,
-        0.188075887121730+0.949400965438739j,
-        0.657412049911476+0.671647766047969j,
-        0.457617239769180+0.524527009214878j,
-        0.171132581309313+0.863116500343149j,
-        0.684223873158406+0.020730339332808j,
-        0.689288538461901+0.853005338506492j,
-        0.655100897151547+0.738842295189445j,
-        0.469288725720117+0.169269913506413j,
-        0.727009355656050+0.143819575672136j,
-        0.629418760068722+0.903341905093775j,
-        0.721343748466731+0.530360235423122j,
-        0.175701721256605+0.116376710227018j,
-        0.525170376501935+0.296511653195648j,
-        0.964998457578896+0.329699663252158j,
-        0.640601603201311+0.462798516244823j,
-        0.877865654950912+0.654173127841309j,
-        0.729729383013391+0.56291800466453j ,
-        0.018630332051044+0.821498382381245j,
-        0.131727707997140+0.530713631823519j,
-        0.187791574003037+0.626722638953091j,
-        0.399902516540311+0.950780374305921j,
-        0.526632360878467+0.467303482757566j,
-        0.296258070015251+0.977206756817445j])
+        np.random.seed(42)
+        a = np.random.randn(100) + 1j*np.random.randn(100)
         assert_(np.isrealobj(np.poly(np.concatenate((a, np.conjugate(a))))))
 
     def test_roots(self):