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authorendolith <endolith@gmail.com>2015-01-25 12:33:15 -0500
committerendolith <endolith@gmail.com>2015-01-25 12:33:15 -0500
commit7d9789f06d305e438425d98e0ce779fb012e6296 (patch)
tree0ffe3bc385a028fba8f67ab964491515a9928f5c /numpy/lib
parent6a88cb9cced64ba2e0079c5df48b9734ec0f05bc (diff)
downloadnumpy-7d9789f06d305e438425d98e0ce779fb012e6296.tar.gz
TST: Fix missing imports, undeterministic test
Change to a deterministic test instead of using rand
Diffstat (limited to 'numpy/lib')
-rw-r--r--numpy/lib/tests/test_polynomial.py103
1 files changed, 101 insertions, 2 deletions
diff --git a/numpy/lib/tests/test_polynomial.py b/numpy/lib/tests/test_polynomial.py
index 8574fd813..d412504fa 100644
--- a/numpy/lib/tests/test_polynomial.py
+++ b/numpy/lib/tests/test_polynomial.py
@@ -81,7 +81,7 @@ poly1d([ 2.])
import numpy as np
from numpy.testing import (
run_module_suite, TestCase, assert_, assert_equal, assert_array_equal,
- assert_almost_equal, rundocs
+ assert_almost_equal, assert_array_almost_equal, rundocs
)
@@ -108,7 +108,106 @@ class TestDocs(TestCase):
assert_(np.iscomplexobj(np.poly([1j, -1.0000001j])))
- a = rand(100) + 1j* rand(100)
+ 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])
assert_(np.isrealobj(np.poly(np.concatenate((a, np.conjugate(a))))))
def test_roots(self):