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testAlgorithms.py
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testAlgorithms.py
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import unittest
import pygsti
from pygsti.construction import std1Q_XYI as std
import numpy as np
from scipy import polyfit
import sys
class AlgorithmTestCase(unittest.TestCase):
def setUp(self):
#Set GateSet objects to "strict" mode for testing
pygsti.objects.GateSet._strict = True
self.gs_target_noisy = std.gs_target.randomize_with_unitary(0.001, seed=1234)
def runSilent(self, callable, *args, **kwds):
orig_stdout = sys.stdout
sys.stdout = open("temp_test_files/silent.txt","w")
result = callable(*args, **kwds)
sys.stdout.close()
sys.stdout = orig_stdout
return result
class TestAlgorithmMethods(AlgorithmTestCase):
def test_strict(self):
#test strict mode, which forbids all these accesses
with self.assertRaises(KeyError):
self.gs_target_noisy['identity'] = [1,0,0,0]
with self.assertRaises(KeyError):
self.gs_target_noisy['Gx'] = np.identity(4,'d')
with self.assertRaises(KeyError):
self.gs_target_noisy['E0'] = [1,0,0,0]
with self.assertRaises(KeyError):
self.gs_target_noisy['rho0'] = [1,0,0,0]
with self.assertRaises(KeyError):
x = self.gs_target_noisy['identity']
with self.assertRaises(KeyError):
x = self.gs_target_noisy['Gx']
with self.assertRaises(KeyError):
x = self.gs_target_noisy['E0']
with self.assertRaises(KeyError):
x = self.gs_target_noisy['rho0']
def test_fiducialSelection(self):
prepFidList = pygsti.alg.optimize_integer_fiducials_slack(
std.gs_target, std.fiducials, prepOrMeas = "prep",
initialWeights=None, maxIter=100,
fixedSlack=False, slackFrac=0.1,
returnAll=False, verbosity=4)
measFidList, wts, scoredict = pygsti.alg.optimize_integer_fiducials_slack(
std.gs_target, std.fiducials, prepOrMeas = "meas",
initialWeights=np.ones( len(std.fiducials), 'i' ), maxIter=100,
fixedSlack=0.1, slackFrac=False,
returnAll=True, verbosity=4)
fiducials_to_try = pygsti.construction.list_all_gatestrings(std.gs_target.gates.keys(), 0, 2)
prepFidList2 = pygsti.alg.optimize_integer_fiducials_slack(
std.gs_target, fiducials_to_try, prepOrMeas = "prep",
initialWeights=None, scoreFunc='worst', maxIter=100,
fixedSlack=False, slackFrac=0.1,
returnAll=False, verbosity=4)
prepFidList3 = pygsti.alg.optimize_integer_fiducials_slack(
std.gs_target, fiducials_to_try, prepOrMeas = "prep",
initialWeights=None, scoreFunc='all', maxIter=100,
fixedSlack=False, slackFrac=0.1, fixedNum=4,
returnAll=False, verbosity=4)
pygsti.alg.write_fixed_hamming_weight_code(3,1)
self.runSilent(pygsti.alg.optimize_integer_fiducials_slack,
std.gs_target, fiducials_to_try, prepOrMeas = "prep",
initialWeights=None, maxIter=1,
fixedSlack=False, slackFrac=0.1,
returnAll=False, verbosity=4) #check max iterations
with self.assertRaises(ValueError):
pygsti.alg.optimize_integer_fiducials_slack(
std.gs_target, std.fiducials, prepOrMeas = "meas") #neither fixedSlack nor slackFrac given
print "prepFidList = ",prepFidList
print "measFidList = ",measFidList
print "wts = ",wts
print "scoredict = ",scoredict
self.assertTrue(pygsti.alg.test_fiducial_list(
std.gs_target,prepFidList,"prep",
scoreFunc='all',returnAll=False))
self.assertTrue(pygsti.alg.test_fiducial_list(
std.gs_target,measFidList,"meas",
scoreFunc='worst',returnAll=False))
bResult, spectrum, score = pygsti.alg.test_fiducial_list(
std.gs_target,measFidList,"meas",
scoreFunc='all',returnAll=True)
with self.assertRaises(Exception):
pygsti.alg.test_fiducial_list(
std.gs_target,measFidList,"foobar",
scoreFunc='all',returnAll=False)
def test_fiducialPairReduction(self):
self.runSilent(pygsti.alg.find_sufficient_fiducial_pairs,
std.gs_target, std.fiducials, std.fiducials,
std.germs, testPairList=[(0,0),(0,1),(1,0)], verbosity=4)
suffPairs = self.runSilent(pygsti.alg.find_sufficient_fiducial_pairs,
std.gs_target, std.fiducials, std.fiducials, std.germs, verbosity=4)
small_fiducials = pygsti.construction.gatestring_list([('Gx',)])
small_germs = pygsti.construction.gatestring_list([('Gx',),('Gy',)])
self.runSilent(pygsti.alg.find_sufficient_fiducial_pairs,
std.gs_target, small_fiducials, small_fiducials,
small_germs, searchMode="sequential", verbosity=2)
self.runSilent(pygsti.alg.find_sufficient_fiducial_pairs,
std.gs_target, std.fiducials, std.fiducials,
std.germs, searchMode="random", nRandom=3,
seed=1234, verbosity=2)
self.runSilent(pygsti.alg.find_sufficient_fiducial_pairs,
std.gs_target, std.fiducials, std.fiducials,
std.germs, searchMode="random", nRandom=300,
seed=1234, verbosity=2)
self.assertEqual(suffPairs, [(0, 0), (0, 1), (1, 0)])
def test_germSelection(self):
germsToTest = pygsti.construction.list_all_gatestrings_without_powers_and_cycles(
std.gs_target.gates.keys(), 2)
bSuccess, eigvals_finiteL = pygsti.alg.test_germ_list_finitel(
self.gs_target_noisy, germsToTest, L=16, returnSpectrum=True, tol=1e-3)
self.assertFalse(bSuccess)
bSuccess,eigvals_infiniteL = pygsti.alg.test_germ_list_infl(
self.gs_target_noisy, germsToTest, returnSpectrum=True, check=True)
self.assertFalse(bSuccess)
germsToTest = pygsti.construction.list_all_gatestrings_without_powers_and_cycles(
std.gs_target.gates.keys(), 3)
germsToTest2 = pygsti.construction.list_all_gatestrings_without_powers_and_cycles(
std.gs_target.gates.keys(), 4)
finalGerms = pygsti.alg.optimize_integer_germs_slack(
self.gs_target_noisy, germsToTest, initialWeights=None,
fixedSlack=0.1, slackFrac=False, returnAll=False, tol=1e-6, verbosity=4)
finalGerms, wts, scoreDict = pygsti.alg.optimize_integer_germs_slack(
self.gs_target_noisy, germsToTest2, initialWeights=np.ones( len(germsToTest2), 'd' ),
fixedSlack=False, slackFrac=0.1, returnAll=True, tol=1e-6, verbosity=4)
self.runSilent(pygsti.alg.optimize_integer_germs_slack,
self.gs_target_noisy, germsToTest,
initialWeights=np.ones( len(germsToTest), 'd' ),
fixedSlack=False, slackFrac=0.1,
returnAll=True, tol=1e-6, verbosity=4, maxIter=1)
# test hitting max iterations
with self.assertRaises(ValueError):
pygsti.alg.optimize_integer_germs_slack(
self.gs_target_noisy, germsToTest,
initialWeights=np.ones( len(germsToTest), 'd' ),
returnAll=True, tol=1e-6, verbosity=4)
# must specify either fixedSlack or slackFrac
if __name__ == "__main__":
unittest.main(verbosity=2)