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testRPE.py
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testRPE.py
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from __future__ import print_function
from ..testutils import BaseTestCase, temp_files, compare_files
import unittest
import pygsti as gst
import numpy as np
import pygsti.construction.std1Q_XY as Std1Q_XY
from pygsti.extras import rpe
RPE = rpe
RPEConstr = rpe.rpeconstruction
rpeconfig_GxPi2_GyPi2_00 = rpe.rpeconfig_GxPi2_GyPi2_00
class TestRPEMethods(BaseTestCase):
def test_rpe_demo(self):
#Declare the particular RPE instance we are interested in
#(X and Y pi/2 rotations)
rpeconfig_inst = rpeconfig_GxPi2_GyPi2_00
#Declare a variety of relevant parameters
target_model = Std1Q_XY.target_model()
target_model.set_all_parameterizations('TP')
maxLengths_1024 = [1,2,4,8,16,32,64,128,256,512,1024]
stringListsRPE = RPEConstr.make_rpe_angle_string_list_dict(10,rpeconfig_inst)
angleList = ['alpha','epsilon','theta']
numStrsD = {}
numStrsD['RPE'] = [6*i for i in np.arange(1,12)]
#Create noisy model
mdl_real = target_model.rotate(rotate=[0.01,0.01,0])
#Extract noisy model angles
true_alpha = RPE.extract_alpha(mdl_real,rpeconfig_inst)
true_epsilon = RPE.extract_epsilon(mdl_real,rpeconfig_inst)
true_theta = RPE.extract_theta(mdl_real,rpeconfig_inst)
#Load pre-simulated dataset
# N=100
# DS = gst.construction.generate_fake_data(mdl_real,stringListsRPE['totalStrList'],N,sampleError='binomial',seed=1)
DS = gst.io.load_dataset(compare_files + '/rpe_test_ds.txt')
#Analyze dataset
resultsRPE = RPE.analyze_rpe_data(DS,mdl_real,stringListsRPE,rpeconfig_inst)
PhiFunErrorListCorrect = np.array([1.4647120176458639e-08, 5.466086847039087e-09, 2.811838817340373e-09, 9.295340015064157e-09, 1.4896280285670027e-08, 1.4897848815698111e-08, 4.269122493016919e-09, 1.4897576120637135e-08, 1.4897610849801124e-08, 6.193216574995608e-09, 1.4469989279702888e-08])
alphaErrorListCorrect= np.array([0.05000352128724339, 0.09825031832409103, 0.02500687294425541, 0.012575500499770742, 0.012523502109159201, 0.0044641536173215535, 0.0007474956215971496, 0.00018069665046693828, 0.00027322234186732963, 0.00020451259672338296, 3.198565800954789e-05])
epsilonErrorListCorrect = np.array([0.18811777239515082, 0.009964509397691668, 0.004957204616348632, 0.007362158521305728, 0.00010888027730326932, 0.0015920480408759818, 0.001403238695757869, 0.0004870373015233298, 0.0001929699810709895, 3.411170328226909e-05, 2.723356656519904e-05])
thetaErrorListCorrect= np.array([0.018281791956737087, 0.015230174647994477, 0.0018336710008779447, 0.004525418577473875, 0.0047631900047339125, 0.002627347622582976, 0.0030228260649800788, 0.002591470061459089, 0.0027097752869584, 0.002733081374122569, 0.0027947590038843876])
PhiFunErrorList = resultsRPE['PhiFunErrorList']
alphaErrorList = resultsRPE['alphaErrorList']
epsilonErrorList = resultsRPE['epsilonErrorList']
thetaErrorList = resultsRPE['thetaErrorList']
assert np.linalg.norm(PhiFunErrorListCorrect-PhiFunErrorList) < 1e-8
assert np.linalg.norm(alphaErrorListCorrect-alphaErrorList) < 1e-8
assert np.linalg.norm(epsilonErrorListCorrect-epsilonErrorList) < 1e-8
assert np.linalg.norm(thetaErrorListCorrect-thetaErrorList) < 1e-8
# again, with consistency checks
# We are currently not testing the consistency check. -KMR 2/26/18
# dummy_k_list = [ 1 ] #EGN: not sure what this should really be...
# resultsRPE_2 = RPE.analyze_rpe_data(DS,mdl_real,stringListsRPE,rpeconfig_inst,
# do_consistency_check=True, k_list=dummy_k_list)
# with self.assertRaises(ValueError):
# RPE.analyze_rpe_data(DS,mdl_real,stringListsRPE,rpeconfig_inst,
# do_consistency_check=True) #no k_list given
#Print results
print('alpha_true - pi/2 =',true_alpha-np.pi/2)
print('epsilon_true - pi/2 =',true_epsilon-np.pi/2)
print('theta_true =',true_theta)
print()
print('alpha_true - alpha_est_final =',resultsRPE['alphaErrorList'][-1])
print('epsilon_true - epsilon_est_final =',resultsRPE['epsilonErrorList'][-1])
print('theta_true - theta_est_final =',resultsRPE['thetaErrorList'][-1])