Example.py

from __future__ import print_function
import numpy as np
import matplotlib.pyplot as plt
import QuantumTomography as qKLib

"""
Copyright 2020 University of Illinois Board of Trustees.
Licensed under the terms of an MIT license
"""


"""CHECK OUT THE REFERENCE PAGE ON OUR WEBSITE :
https://quantumtomo.web.illinois.edu/Doc/"""


# Step 1. Initialize Tomography Object
t = qKLib.Tomography()

# Step 2. Set up Configurations
# import conf file
t.importConf('ExampleFiles/conf.txt')
# or set the conf settings directly or with the helper
t.setConfSetting('DoAccidentalCorrection', 1)

# Step 3. Run Tomography on The data
# import data file
[rho, intensity, fval] = t.importData('ExampleFiles/data.txt')
# or call the object's tomography function
tomo_input = np.array([[1, 0, 500, 1, 0], [1, 0, 0, 0, 1], [1, 0, 250, 0.7071, 0.7071], [1, 0, 250, 0.7071, -0.7071], [1, 0, 250, 0.7071, 0.7071j], [1, 0, 250, 0.7071, -0.7071j]])
intensity = np.array([1, 1, 1, 1, 1, 1])
[rho, intens, fval] = t.state_tomography(tomo_input, intensity)
# or import the eval file to import both the config and data
[rho, intensity, fval] = t.importEval('ExampleFiles/pythoneval.txt')

# Step 4. Optional Methods
# The library also include useful functions you may use included in TomoFunctions.py.
# See https://quantumtomo.web.illinois.edu/Doc/ for a full reference guide of all the functions.
qKLib.printLastOutput(t)

expectedState = np.array([[1.0, 0.0], [0.0, 0.0]])
print("Fidelity: " + str(qKLib.fidelity(rho, expectedState)))
rho = np.kron(rho, rho)
qKLib.makeRhoImages(rho, plt, True)
plt.show()