<reponame>grahamrow/Auspex<gh_stars>10-100
# Copyright 2016 <NAME>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0

import unittest
import os
import time
import numpy as np
import tempfile

pl = None
cl = None

import QGL.config
import auspex.config
auspex.config.auspex_dummy_mode = True

# Set temporary output directories
awg_dir = tempfile.TemporaryDirectory()
kern_dir = tempfile.TemporaryDirectory()
auspex.config.AWGDir = QGL.config.AWGDir = awg_dir.name
auspex.config.KernelDir = kern_dir.name

from QGL import *
from auspex.qubit import *
import bbndb


def simulate_rabiAmp(num_steps = 20, over_rotation_factor = 0):
    """
    Simulate the output of a RabiAmp experiment of a given number of amp points.
    amps: array of points between [-1,1]

    returns: ideal data
    """
    amps = np.hstack((np.arange(-1, 0, 2./num_steps),
                        np.arange(2./num_steps, 1+2./num_steps, 2./num_steps)))
    xpoints = amps * (1+over_rotation_factor)
    ypoints = -np.cos(2*np.pi*xpoints/1.8)
    # repeated twice for X and Y rotations
    return np.tile(ypoints, 2)

def simulate_ramsey(num_steps = 50, maxt = 50e-6, detuning = 100e3, T2 = 40e-6):
    """
    Simulate the output of a Ramsey experiment of a given number of time steps.
    maxt: longest delay (s)
    detuning: frequency detuning (Hz)
    T2: 1/e decay time (s)

    returns: ideal data
    """

    xpoints = np.linspace(0, maxt, num_steps)
    ypoints = np.cos(2*np.pi*detuning*xpoints)*np.exp(-xpoints/T2)
    return ypoints

def simulate_phase_estimation(amp, target, numPulses, ideal_amp=0.34, add_noise=False):
    """
    Simulate the output of a PhaseEstimation experiment with NumPulses.
    amp: initial pulse amplitude
    target: target angle (pi/2, etc.)

    returns: ideal data and variance
    """
    ideal_amp    = ideal_amp
    noiseScale   = 0.01
    polarization = 0.99 # residual polarization after each pulse

    # data representing over/under rotation of pi/2 pulse
    # theta = pi/2 * (amp/ideal_amp);
    theta   = target * (amp/ideal_amp)
    ks      = [ 2**k for k in range(0,numPulses+1)]

    xdata = [ polarization**x * np.sin(x*theta) for x in ks]
    xdata = np.insert(xdata,0,-1.0)
    zdata = [ polarization**x * np.cos(x*theta) for x in ks]
    zdata = np.insert(zdata,0,1.0)
    data  = np.array([zdata,xdata]).flatten('F')
    data  = np.tile(data,(2,1)).flatten('F')

    if add_noise:
        data += noiseScale * np.random.randn(len(data));

    vardata = noiseScale**2 * np.ones((len(data)))

    return data, vardata

def simulate_drag(deltas = np.linspace(-1,1,21), num_pulses = np.arange(16, 48, 4), drag = 0.6):
    """
    Simulate the output of a DRAG experiment with a set drag value

    returns: ideal data
    """
    ypoints = [t for s in [(n/2)**2*(deltas - drag)**2 for n in num_pulses] for t in s]
    ypoints = np.append(ypoints, np.repeat([max(ypoints),min(ypoints)],2))
    return ypoints

class SingleQubitCalTestCase(unittest.TestCase):
    """
    Class for unittests of single-qubit calibrations. Tested so far with a dummy X6 digitizer:
    * RabiAmpCalibration
    * RamseyCalibration
    Ideal data are generated and stored into a temporary file, whose name is set by the X6 property `ideal_data`. Calibrations which span over multiple experiments load different columns of these ideal data. The column (and experiment) number is set by an incremental counter, also a digitizer property `exp_step`. Artificial noise is added by the X6 dummy instrument.
    """
    
    @classmethod
    def setUpClass(cls):
        global cl, pl

        cl = ChannelLibrary(":memory:")
        pl = PipelineManager()

    def _setUp(self, num_averages=50):
        self.num_averages = num_averages
        cl.clear()
        q     = cl.new_qubit("q1")
        aps1  = cl.new_APS2("BBNAPS1", address="192.168.5.102")
        aps2  = cl.new_APS2("BBNAPS2", address="192.168.5.103")
        x6_1  = cl.new_X6("X6_1", address="1", record_length=512)
        holz1 = cl.new_source("Holz_1", "HolzworthHS9000", "HS9004A-009-1", power=-30)
        holz2 = cl.new_source("Holz_2", "HolzworthHS9000", "HS9004A-009-2", power=-30)
        cl.set_control(q, aps1, generator=holz1)
        cl.set_measure(q, aps2, x6_1.ch(1), generator=holz2)
        cl.set_master(aps1, aps1.ch("m2"))
        pl.create_default_pipeline()
        pl.reset_pipelines()
        pl["q1"].clear_pipeline()
        pl["q1"].stream_type = "integrated"
        pl["q1"].create_default_pipeline()
        cl.commit()

        # Clear calibration table
        bbndb.get_cl_session().query(bbndb.calibration.Sample).delete()
        bbndb.get_cl_session().query(bbndb.calibration.Calibration).delete()

    def test_rabi_amp(self):
        self._setUp()
        """
        Test RabiAmpCalibration. Ideal data generated by simulate_rabiAmp.
        """
        pce = RabiAmpCalibration(cl["q1"], do_plotting=False, num_steps=20, sample_name="Testing123")
        pce.set_fake_data(cl["X6_1"], simulate_rabiAmp(num_steps=20))
        pce.calibrate()

        self.assertAlmostEqual(pce.pi_amp,0.9,places=2)
        self.assertAlmostEqual(pce.pi2_amp,0.45,places=2)
        self.assertAlmostEqual(pce.pi_amp, cl["q1"].pulse_params['piAmp'], places=3)
        self.assertAlmostEqual(pce.pi2_amp, cl["q1"].pulse_params['pi2Amp'], places=3)

        self.assertTrue(bbndb.get_cl_session().query(bbndb.calibration.Sample).filter_by(name="Testing123").first().name == "Testing123")
        self.assertAlmostEqual(bbndb.get_cl_session().query(bbndb.calibration.Calibration).filter_by(name="Pi2Amp").first().value, pce.pi2_amp, places=3)
        self.assertAlmostEqual(bbndb.get_cl_session().query(bbndb.calibration.Calibration).filter_by(name="PiAmp").first().value, pce.pi_amp, places=3)

        self.assertTrue(bbndb.get_cl_session().query(bbndb.calibration.Calibration).filter_by(name="Pi2Amp").first().date)

    def run_ramsey(self, set_source = True):
        """
        Simulate a RamseyCalibration run. Ideal data are generated by simulate_ramsey.
        set_source: True (False) sets the source (qubit) frequency.
        """
        ideal_data = [simulate_ramsey(num_steps = 50, detuning = 90e3),  
                      simulate_ramsey(num_steps = 50, detuning = 45e3)]
        ramsey_cal = RamseyCalibration(cl["q1"], do_plotting=False, added_detuning = 0e3, 
                        delays=np.linspace(0.0, 50.0, 50)*1e-6, set_source = set_source)
        ramsey_cal.set_fake_data(cl["X6_1"], ideal_data, increment=True)
        ramsey_cal.calibrate()
        return ramsey_cal

    @unittest.skip("Issues with Linux build.")
    def test_ramsey_set_source(self):
        self._setUp()
        """
        Test RamseyCalibration with source frequency setting.
        """
        ramsey_cal = self.run_ramsey()
        self.assertAlmostEqual(ramsey_cal.fit_freq/1e9, (self.test_settings['instruments']['Holz2']['frequency'] + 90e3)/1e9, places=3)
        #test update_settings
        # new_settings = auspex.config.load_meas_file(cfg_file)
        self.assertAlmostEqual(ramsey_cal.fit_freq/1e9, new_settings['instruments']['Holz2']['frequency']/1e9, places=3)
        #restore original settings
        # auspex.config.dump_meas_file(self.test_settings, cfg_file)

    def test_ramsey_set_qubit(self):
        self._setUp()
        """
        Test RamseyCalibration with qubit frequency setting.
        """
        ramsey_cal = self.run_ramsey(False)
        #test update_settings
        # new_settings = auspex.config.load_meas_file(cfg_file)

        print(float(round(ramsey_cal.fit_freq - ramsey_cal.orig_freq)))
        # self.assertTrue( 0.85 < ((cl["q1"].frequency+90e3)/1e6)/(new_settings['qubits'][cl["q1"].label].frequency/1e6) < 1.15)
        #restore original settings
        # auspex.config.dump_meas_file(self.test_settings, cfg_file)

    def test_phase_estimation(self):
        self._setUp()
        """
        Test generating data for phase estimation
        """
        numPulses = 9
        amp = .55
        direction = 'X'
        target = np.pi

        # Using the same simulated data as matlab
        data, vardata =  simulate_phase_estimation(amp, target, numPulses)

        # Verify output matches what was previously seen by matlab
        phase, sigma = phase_estimation(data, vardata, verbose=False)
        self.assertAlmostEqual(phase,-1.2012,places=3)

        # TODO: fix me
        # self.assertAlmostEqual(sigma,0.0245,places=3)

    def test_pi_phase_estimation(self):
        self._setUp()
        """
        Test PiCalibration with phase estimation
        """

        numPulses = 9
        cl["q1"].pulse_params['piAmp'] = 0.4
        cl["q1"].pulse_params['pi2Amp'] = 0.2

        amp = 0.4
        direction = 'X'
        target = np.pi

        ideal_data, vardata         = simulate_phase_estimation(amp, target, numPulses, ideal_amp=0.399)
        phase, sigma                = phase_estimation(ideal_data, vardata, verbose=False)
        amp, done_flag, phase_error = phase_to_amplitude(phase, sigma, amp, target)

        for quad in ['real']: # TODO: fix this for other quadratures
            pi_cal = PiCalibration(cl["q1"], do_plotting=False, num_pulses=numPulses, quad=quad, sample_name="TestingPi")
            pi_cal.set_fake_data(cl["X6_1"], ideal_data)
            pi_cal.calibrate()
            self.assertAlmostEqual(pi_cal.amplitude, amp, places=2)

        picals = list(bbndb.get_cl_session().query(bbndb.calibration.Calibration).filter_by(name="PiAmp", category="PhaseEstimation").all())
        self.assertTrue(len(picals)>0)
        for pical in picals:
            if pical.sample.name == "TestingPi":
                self.assertAlmostEqual(pical.value, 0.399, places=2)

    def test_drag(self):
        self._setUp()
        """
        Test DRAGCalibration. Ideal data generated by simulate_drag.
        """
        ideal_drag   = 0.0 # arbitrary choice for testing
        deltas_0     = np.linspace(-0.3,0.3,21)
        pulses_0     = np.arange(4, 20, 4)
        drag_step_1  = 0.25*(max(deltas_0) - min(deltas_0))
        deltas_1     = np.linspace(ideal_drag - drag_step_1, ideal_drag + drag_step_1, len(deltas_0))
        pulse_step_1 = 2*(max(pulses_0) - min(pulses_0))/len(pulses_0)
        pulses_1     = np.arange(max(pulses_0) - pulse_step_1, max(pulses_0) + pulse_step_1*(len(pulses_0)-1))

        ideal_data = [np.tile(simulate_drag(deltas_0, pulses_0, ideal_drag), self.num_averages), np.tile(simulate_drag(deltas_1, pulses_1, ideal_drag), self.num_averages)]

        drag_cal = DRAGCalibration(cl["q1"], do_plotting=False, deltas = deltas_0, num_pulses = pulses_0, sample_name="TestingDrag")
        drag_cal.set_fake_data(cl["X6_1"], ideal_data)
        drag_cal.calibrate()

        self.assertAlmostEqual(drag_cal.opt_drag, ideal_drag, places=2)
        self.assertAlmostEqual(drag_cal.opt_drag, cl["q1"].pulse_params['drag_scaling'], places=2)
 
        dragcalss = list(bbndb.get_cl_session().query(bbndb.calibration.Calibration).filter_by(name="drag_scaling").all())
        self.assertTrue(len(dragcalss)>0)
        for dragcals in dragcalss:
            if dragcals.sample.name == "TestingPi":
                self.assertAlmostEqual(dragcals.value, 0.399, places=2)

class TwoQubitCalTestCase(unittest.TestCase):
    """
    Class for unittests of single-qubit calibrations. Tested so far with a dummy X6 digitizer:
    * RabiAmpCalibration
    * RamseyCalibration
    Ideal data are generated and stored into a temporary file, whose name is set by the X6 property `ideal_data`. Calibrations which span over multiple experiments load different columns of these ideal data. The column (and experiment) number is set by an incremental counter, also a digitizer property `exp_step`. Artificial noise is added by the X6 dummy instrument.
    """
    
    @classmethod
    def setUpClass(cls):
        global cl, pl

        cl = ChannelLibrary(":memory:")
        pl = PipelineManager()

    def _setUp(self, num_averages=50):
        self.num_averages = num_averages
        cl.clear()
        q1    = cl.new_qubit("q1") # Source
        q2    = cl.new_qubit("q2") # Target
        e     = cl.new_edge(q1, q2)
        aps1  = cl.new_APS2("BBNAPS1", address="192.168.5.102")
        aps2  = cl.new_APS2("BBNAPS2", address="192.168.5.103")
        aps3  = cl.new_APS2("BBNAPS3", address="192.168.5.104")
        aps4  = cl.new_APS2("BBNAPS4", address="192.168.5.105")
        aps5  = cl.new_APS2("BBNAPS5", address="192.168.5.106")
        x6_1  = cl.new_X6("X6_1", address="1", record_length=512)
        x6_2  = cl.new_X6("X6_2", address="2", record_length=512)
        holz1 = cl.new_source("Holz_1", "HolzworthHS9000", "HS9004A-009-1", power=-30)
        holz2 = cl.new_source("Holz_2", "HolzworthHS9000", "HS9004A-009-2", power=-30)
        holz3 = cl.new_source("Holz_3", "HolzworthHS9000", "HS9004A-009-3", power=-30)
        holz4 = cl.new_source("Holz_4", "HolzworthHS9000", "HS9004A-009-4", power=-30)
        holz5 = cl.new_source("Holz_5", "HolzworthHS9000", "HS9004A-009-5", power=-30)
        cl.set_control(q1, aps1, generator=holz1)
        cl.set_measure(q1, aps2, x6_1.ch(1), generator=holz2)
        cl.set_control(q2, aps3, generator=holz3)
        cl.set_measure(q2, aps4, x6_2.ch(1), generator=holz4)
        cl.set_control(e,  aps5, generator=holz5)
        cl.set_master(aps1, aps1.ch("m2"))
        pl.create_default_pipeline()
        pl.reset_pipelines()
        pl["q1"].clear_pipeline()
        pl["q1"].stream_type = "integrated"
        pl["q1"].create_default_pipeline()
        pl["q2"].clear_pipeline()
        pl["q2"].stream_type = "integrated"
        pl["q2"].create_default_pipeline()
        from bbndb.auspex import Display
        pl['q2'].add(Display(label="q2"))
        pl['q1'].add(Display(label="q1"))
        cl.commit()

        # Clear calibration table
        bbndb.get_cl_session().query(bbndb.calibration.Sample).delete()
        bbndb.get_cl_session().query(bbndb.calibration.Calibration).delete()

    def test_setup(self):
        self._setUp()

    def test_CRLen(self):
        """
        Test RabiAmpCalibration. Ideal data generated by simulate_rabiAmp.
        """
        self._setUp()
        lengths = np.linspace(20, 1020, 21)*1e-9
        pce = CRLenCalibration(cl["q1->q2"], lengths=lengths, phase = 0, amp = 0.8, rise_fall = 40e-9,
            do_plotting=False, sample_name="Testing123", averages=10)
        A = 0.45
        f = 1.20e6
        f_pi = 1.10e6
        phi = np.pi/2+0.02
        y0 = 0.005

        vals    = A*np.sin(2*np.pi*f*lengths + phi) + y0
        vals_pi = A*np.sin(2*np.pi*f_pi*lengths + phi) + y0
        vals = np.r_[vals,vals_pi].flatten() # Double each element... No prizes for this code...
        # vals = np.r_[vals,vals].reshape(2,-1).T.flatten() # Double each element... No prizes for this code...

        vals1 = np.append(vals, [-A,-A,-A,-A, A, A, A, A])
        vals2 = np.append(vals, [-A,-A, A, A, -A, -A, A, A])
        pce.set_fake_data(cl["X6_2"], vals2)
        pce.set_fake_data(cl["X6_1"], vals1)
        pce.calibrate()

        self.assertAlmostEqual(pce.opt_par, 220e-9, places=1)

    def test_CRPhase(self):
        """
        Test RabiAmpCalibration. Ideal data generated by simulate_rabiAmp.
        """
        self._setUp()
        phases = np.linspace(0, 2*np.pi, 21)
        pce = CRPhaseCalibration(cl["q1->q2"], length=220.0e-9, phases = phases, amp = 0.8, rise_fall = 40e-9,
            do_plotting=False, sample_name="Testing123", averages=10)
        A = 0.45
        y0 = 0.005

        vals    = A*np.sin(phases + 0.04) + y0
        vals_pi = A*np.sin(phases*1.01 + 0.02 + np.pi) + y0
        vals = np.r_[vals,vals_pi].flatten() # Double each element... No prizes for this code...
        # vals = np.r_[vals,vals].reshape(2,-1).T.flatten() # Double each element... No prizes for this code...

        vals1 = np.append(vals, [-A,-A,-A,-A, A, A, A, A])
        vals2 = np.append(vals, [-A,-A, A, A, -A, -A, A, A])
        pce.set_fake_data(cl["X6_2"], vals2)
        pce.set_fake_data(cl["X6_1"], vals1)
        pce.calibrate()

        self.assertAlmostEqual(pce.opt_par, 1.52, places=1)

if __name__ == '__main__':
    unittest.main()

# Copyright 2016 <NAME>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0

import unittest
import os
import time
import numpy as np
import tempfile

pl = None
cl = None

import QGL.config
import auspex.config
auspex.config.auspex_dummy_mode = True

# Set temporary output directories
awg_dir = tempfile.TemporaryDirectory()
kern_dir = tempfile.TemporaryDirectory()
auspex.config.AWGDir = QGL.config.AWGDir = awg_dir.name
auspex.config.KernelDir = kern_dir.name

from QGL import *
from auspex.qubit import *
import bbndb


def simulate_rabiAmp(num_steps = 20, over_rotation_factor = 0):
    """
    Simulate the output of a RabiAmp experiment of a given number of amp points.
    amps: array of points between [-1,1]

    returns: ideal data
    """
    amps = np.hstack((np.arange(-1, 0, 2./num_steps),
                        np.arange(2./num_steps, 1+2./num_steps, 2./num_steps)))
    xpoints = amps * (1+over_rotation_factor)
    ypoints = -np.cos(2*np.pi*xpoints/1.8)
    # repeated twice for X and Y rotations
    return np.tile(ypoints, 2)

def simulate_ramsey(num_steps = 50, maxt = 50e-6, detuning = 100e3, T2 = 40e-6):
    """
    Simulate the output of a Ramsey experiment of a given number of time steps.
    maxt: longest delay (s)
    detuning: frequency detuning (Hz)
    T2: 1/e decay time (s)

    returns: ideal data
    """

    xpoints = np.linspace(0, maxt, num_steps)
    ypoints = np.cos(2*np.pi*detuning*xpoints)*np.exp(-xpoints/T2)
    return ypoints

def simulate_phase_estimation(amp, target, numPulses, ideal_amp=0.34, add_noise=False):
    """
    Simulate the output of a PhaseEstimation experiment with NumPulses.
    amp: initial pulse amplitude
    target: target angle (pi/2, etc.)

    returns: ideal data and variance
    """
    ideal_amp    = ideal_amp
    noiseScale   = 0.01
    polarization = 0.99 # residual polarization after each pulse

    # data representing over/under rotation of pi/2 pulse
    # theta = pi/2 * (amp/ideal_amp);
    theta   = target * (amp/ideal_amp)
    ks      = [ 2**k for k in range(0,numPulses+1)]

    xdata = [ polarization**x * np.sin(x*theta) for x in ks]
    xdata = np.insert(xdata,0,-1.0)
    zdata = [ polarization**x * np.cos(x*theta) for x in ks]
    zdata = np.insert(zdata,0,1.0)
    data  = np.array([zdata,xdata]).flatten('F')
    data  = np.tile(data,(2,1)).flatten('F')

    if add_noise:
        data += noiseScale * np.random.randn(len(data));

    vardata = noiseScale**2 * np.ones((len(data)))

    return data, vardata

def simulate_drag(deltas = np.linspace(-1,1,21), num_pulses = np.arange(16, 48, 4), drag = 0.6):
    """
    Simulate the output of a DRAG experiment with a set drag value

    returns: ideal data
    """
    ypoints = [t for s in [(n/2)**2*(deltas - drag)**2 for n in num_pulses] for t in s]
    ypoints = np.append(ypoints, np.repeat([max(ypoints),min(ypoints)],2))
    return ypoints

class SingleQubitCalTestCase(unittest.TestCase):
    """
    Class for unittests of single-qubit calibrations. Tested so far with a dummy X6 digitizer:
    * RabiAmpCalibration
    * RamseyCalibration
    Ideal data are generated and stored into a temporary file, whose name is set by the X6 property `ideal_data`. Calibrations which span over multiple experiments load different columns of these ideal data. The column (and experiment) number is set by an incremental counter, also a digitizer property `exp_step`. Artificial noise is added by the X6 dummy instrument.
    """
    
    @classmethod
    def setUpClass(cls):
        global cl, pl

        cl = ChannelLibrary(":memory:")
        pl = PipelineManager()

    def _setUp(self, num_averages=50):
        self.num_averages = num_averages
        cl.clear()
        q     = cl.new_qubit("q1")
        aps1  = cl.new_APS2("BBNAPS1", address="192.168.5.102")
        aps2  = cl.new_APS2("BBNAPS2", address="192.168.5.103")
        x6_1  = cl.new_X6("X6_1", address="1", record_length=512)
        holz1 = cl.new_source("Holz_1", "HolzworthHS9000", "HS9004A-009-1", power=-30)
        holz2 = cl.new_source("Holz_2", "HolzworthHS9000", "HS9004A-009-2", power=-30)
        cl.set_control(q, aps1, generator=holz1)
        cl.set_measure(q, aps2, x6_1.ch(1), generator=holz2)
        cl.set_master(aps1, aps1.ch("m2"))
        pl.create_default_pipeline()
        pl.reset_pipelines()
        pl["q1"].clear_pipeline()
        pl["q1"].stream_type = "integrated"
        pl["q1"].create_default_pipeline()
        cl.commit()

        # Clear calibration table
        bbndb.get_cl_session().query(bbndb.calibration.Sample).delete()
        bbndb.get_cl_session().query(bbndb.calibration.Calibration).delete()

    def test_rabi_amp(self):
        self._setUp()
        """
        Test RabiAmpCalibration. Ideal data generated by simulate_rabiAmp.
        """
        pce = RabiAmpCalibration(cl["q1"], do_plotting=False, num_steps=20, sample_name="Testing123")
        pce.set_fake_data(cl["X6_1"], simulate_rabiAmp(num_steps=20))
        pce.calibrate()

        self.assertAlmostEqual(pce.pi_amp,0.9,places=2)
        self.assertAlmostEqual(pce.pi2_amp,0.45,places=2)
        self.assertAlmostEqual(pce.pi_amp, cl["q1"].pulse_params['piAmp'], places=3)
        self.assertAlmostEqual(pce.pi2_amp, cl["q1"].pulse_params['pi2Amp'], places=3)

        self.assertTrue(bbndb.get_cl_session().query(bbndb.calibration.Sample).filter_by(name="Testing123").first().name == "Testing123")
        self.assertAlmostEqual(bbndb.get_cl_session().query(bbndb.calibration.Calibration).filter_by(name="Pi2Amp").first().value, pce.pi2_amp, places=3)
        self.assertAlmostEqual(bbndb.get_cl_session().query(bbndb.calibration.Calibration).filter_by(name="PiAmp").first().value, pce.pi_amp, places=3)

        self.assertTrue(bbndb.get_cl_session().query(bbndb.calibration.Calibration).filter_by(name="Pi2Amp").first().date)

    def run_ramsey(self, set_source = True):
        """
        Simulate a RamseyCalibration run. Ideal data are generated by simulate_ramsey.
        set_source: True (False) sets the source (qubit) frequency.
        """
        ideal_data = [simulate_ramsey(num_steps = 50, detuning = 90e3),  
                      simulate_ramsey(num_steps = 50, detuning = 45e3)]
        ramsey_cal = RamseyCalibration(cl["q1"], do_plotting=False, added_detuning = 0e3, 
                        delays=np.linspace(0.0, 50.0, 50)*1e-6, set_source = set_source)
        ramsey_cal.set_fake_data(cl["X6_1"], ideal_data, increment=True)
        ramsey_cal.calibrate()
        return ramsey_cal

    @unittest.skip("Issues with Linux build.")
    def test_ramsey_set_source(self):
        self._setUp()
        """
        Test RamseyCalibration with source frequency setting.
        """
        ramsey_cal = self.run_ramsey()
        self.assertAlmostEqual(ramsey_cal.fit_freq/1e9, (self.test_settings['instruments']['Holz2']['frequency'] + 90e3)/1e9, places=3)
        #test update_settings
        # new_settings = auspex.config.load_meas_file(cfg_file)
        self.assertAlmostEqual(ramsey_cal.fit_freq/1e9, new_settings['instruments']['Holz2']['frequency']/1e9, places=3)
        #restore original settings
        # auspex.config.dump_meas_file(self.test_settings, cfg_file)

    def test_ramsey_set_qubit(self):
        self._setUp()
        """
        Test RamseyCalibration with qubit frequency setting.
        """
        ramsey_cal = self.run_ramsey(False)
        #test update_settings
        # new_settings = auspex.config.load_meas_file(cfg_file)

        print(float(round(ramsey_cal.fit_freq - ramsey_cal.orig_freq)))
        # self.assertTrue( 0.85 < ((cl["q1"].frequency+90e3)/1e6)/(new_settings['qubits'][cl["q1"].label].frequency/1e6) < 1.15)
        #restore original settings
        # auspex.config.dump_meas_file(self.test_settings, cfg_file)

    def test_phase_estimation(self):
        self._setUp()
        """
        Test generating data for phase estimation
        """
        numPulses = 9
        amp = .55
        direction = 'X'
        target = np.pi

        # Using the same simulated data as matlab
        data, vardata =  simulate_phase_estimation(amp, target, numPulses)

        # Verify output matches what was previously seen by matlab
        phase, sigma = phase_estimation(data, vardata, verbose=False)
        self.assertAlmostEqual(phase,-1.2012,places=3)

        # TODO: fix me
        # self.assertAlmostEqual(sigma,0.0245,places=3)

    def test_pi_phase_estimation(self):
        self._setUp()
        """
        Test PiCalibration with phase estimation
        """

        numPulses = 9
        cl["q1"].pulse_params['piAmp'] = 0.4
        cl["q1"].pulse_params['pi2Amp'] = 0.2

        amp = 0.4
        direction = 'X'
        target = np.pi

        ideal_data, vardata         = simulate_phase_estimation(amp, target, numPulses, ideal_amp=0.399)
        phase, sigma                = phase_estimation(ideal_data, vardata, verbose=False)
        amp, done_flag, phase_error = phase_to_amplitude(phase, sigma, amp, target)

        for quad in ['real']: # TODO: fix this for other quadratures
            pi_cal = PiCalibration(cl["q1"], do_plotting=False, num_pulses=numPulses, quad=quad, sample_name="TestingPi")
            pi_cal.set_fake_data(cl["X6_1"], ideal_data)
            pi_cal.calibrate()
            self.assertAlmostEqual(pi_cal.amplitude, amp, places=2)

        picals = list(bbndb.get_cl_session().query(bbndb.calibration.Calibration).filter_by(name="PiAmp", category="PhaseEstimation").all())
        self.assertTrue(len(picals)>0)
        for pical in picals:
            if pical.sample.name == "TestingPi":
                self.assertAlmostEqual(pical.value, 0.399, places=2)

    def test_drag(self):
        self._setUp()
        """
        Test DRAGCalibration. Ideal data generated by simulate_drag.
        """
        ideal_drag   = 0.0 # arbitrary choice for testing
        deltas_0     = np.linspace(-0.3,0.3,21)
        pulses_0     = np.arange(4, 20, 4)
        drag_step_1  = 0.25*(max(deltas_0) - min(deltas_0))
        deltas_1     = np.linspace(ideal_drag - drag_step_1, ideal_drag + drag_step_1, len(deltas_0))
        pulse_step_1 = 2*(max(pulses_0) - min(pulses_0))/len(pulses_0)
        pulses_1     = np.arange(max(pulses_0) - pulse_step_1, max(pulses_0) + pulse_step_1*(len(pulses_0)-1))

        ideal_data = [np.tile(simulate_drag(deltas_0, pulses_0, ideal_drag), self.num_averages), np.tile(simulate_drag(deltas_1, pulses_1, ideal_drag), self.num_averages)]

        drag_cal = DRAGCalibration(cl["q1"], do_plotting=False, deltas = deltas_0, num_pulses = pulses_0, sample_name="TestingDrag")
        drag_cal.set_fake_data(cl["X6_1"], ideal_data)
        drag_cal.calibrate()

        self.assertAlmostEqual(drag_cal.opt_drag, ideal_drag, places=2)
        self.assertAlmostEqual(drag_cal.opt_drag, cl["q1"].pulse_params['drag_scaling'], places=2)
 
        dragcalss = list(bbndb.get_cl_session().query(bbndb.calibration.Calibration).filter_by(name="drag_scaling").all())
        self.assertTrue(len(dragcalss)>0)
        for dragcals in dragcalss:
            if dragcals.sample.name == "TestingPi":
                self.assertAlmostEqual(dragcals.value, 0.399, places=2)

class TwoQubitCalTestCase(unittest.TestCase):
    """
    Class for unittests of single-qubit calibrations. Tested so far with a dummy X6 digitizer:
    * RabiAmpCalibration
    * RamseyCalibration
    Ideal data are generated and stored into a temporary file, whose name is set by the X6 property `ideal_data`. Calibrations which span over multiple experiments load different columns of these ideal data. The column (and experiment) number is set by an incremental counter, also a digitizer property `exp_step`. Artificial noise is added by the X6 dummy instrument.
    """
    
    @classmethod
    def setUpClass(cls):
        global cl, pl

        cl = ChannelLibrary(":memory:")
        pl = PipelineManager()

    def _setUp(self, num_averages=50):
        self.num_averages = num_averages
        cl.clear()
        q1    = cl.new_qubit("q1") # Source
        q2    = cl.new_qubit("q2") # Target
        e     = cl.new_edge(q1, q2)
        aps1  = cl.new_APS2("BBNAPS1", address="192.168.5.102")
        aps2  = cl.new_APS2("BBNAPS2", address="192.168.5.103")
        aps3  = cl.new_APS2("BBNAPS3", address="192.168.5.104")
        aps4  = cl.new_APS2("BBNAPS4", address="192.168.5.105")
        aps5  = cl.new_APS2("BBNAPS5", address="192.168.5.106")
        x6_1  = cl.new_X6("X6_1", address="1", record_length=512)
        x6_2  = cl.new_X6("X6_2", address="2", record_length=512)
        holz1 = cl.new_source("Holz_1", "HolzworthHS9000", "HS9004A-009-1", power=-30)
        holz2 = cl.new_source("Holz_2", "HolzworthHS9000", "HS9004A-009-2", power=-30)
        holz3 = cl.new_source("Holz_3", "HolzworthHS9000", "HS9004A-009-3", power=-30)
        holz4 = cl.new_source("Holz_4", "HolzworthHS9000", "HS9004A-009-4", power=-30)
        holz5 = cl.new_source("Holz_5", "HolzworthHS9000", "HS9004A-009-5", power=-30)
        cl.set_control(q1, aps1, generator=holz1)
        cl.set_measure(q1, aps2, x6_1.ch(1), generator=holz2)
        cl.set_control(q2, aps3, generator=holz3)
        cl.set_measure(q2, aps4, x6_2.ch(1), generator=holz4)
        cl.set_control(e,  aps5, generator=holz5)
        cl.set_master(aps1, aps1.ch("m2"))
        pl.create_default_pipeline()
        pl.reset_pipelines()
        pl["q1"].clear_pipeline()
        pl["q1"].stream_type = "integrated"
        pl["q1"].create_default_pipeline()
        pl["q2"].clear_pipeline()
        pl["q2"].stream_type = "integrated"
        pl["q2"].create_default_pipeline()
        from bbndb.auspex import Display
        pl['q2'].add(Display(label="q2"))
        pl['q1'].add(Display(label="q1"))
        cl.commit()

        # Clear calibration table
        bbndb.get_cl_session().query(bbndb.calibration.Sample).delete()
        bbndb.get_cl_session().query(bbndb.calibration.Calibration).delete()

    def test_setup(self):
        self._setUp()

    def test_CRLen(self):
        """
        Test RabiAmpCalibration. Ideal data generated by simulate_rabiAmp.
        """
        self._setUp()
        lengths = np.linspace(20, 1020, 21)*1e-9
        pce = CRLenCalibration(cl["q1->q2"], lengths=lengths, phase = 0, amp = 0.8, rise_fall = 40e-9,
            do_plotting=False, sample_name="Testing123", averages=10)
        A = 0.45
        f = 1.20e6
        f_pi = 1.10e6
        phi = np.pi/2+0.02
        y0 = 0.005

        vals    = A*np.sin(2*np.pi*f*lengths + phi) + y0
        vals_pi = A*np.sin(2*np.pi*f_pi*lengths + phi) + y0
        vals = np.r_[vals,vals_pi].flatten() # Double each element... No prizes for this code...
        # vals = np.r_[vals,vals].reshape(2,-1).T.flatten() # Double each element... No prizes for this code...

        vals1 = np.append(vals, [-A,-A,-A,-A, A, A, A, A])
        vals2 = np.append(vals, [-A,-A, A, A, -A, -A, A, A])
        pce.set_fake_data(cl["X6_2"], vals2)
        pce.set_fake_data(cl["X6_1"], vals1)
        pce.calibrate()

        self.assertAlmostEqual(pce.opt_par, 220e-9, places=1)

    def test_CRPhase(self):
        """
        Test RabiAmpCalibration. Ideal data generated by simulate_rabiAmp.
        """
        self._setUp()
        phases = np.linspace(0, 2*np.pi, 21)
        pce = CRPhaseCalibration(cl["q1->q2"], length=220.0e-9, phases = phases, amp = 0.8, rise_fall = 40e-9,
            do_plotting=False, sample_name="Testing123", averages=10)
        A = 0.45
        y0 = 0.005

        vals    = A*np.sin(phases + 0.04) + y0
        vals_pi = A*np.sin(phases*1.01 + 0.02 + np.pi) + y0
        vals = np.r_[vals,vals_pi].flatten() # Double each element... No prizes for this code...
        # vals = np.r_[vals,vals].reshape(2,-1).T.flatten() # Double each element... No prizes for this code...

        vals1 = np.append(vals, [-A,-A,-A,-A, A, A, A, A])
        vals2 = np.append(vals, [-A,-A, A, A, -A, -A, A, A])
        pce.set_fake_data(cl["X6_2"], vals2)
        pce.set_fake_data(cl["X6_1"], vals1)
        pce.calibrate()

        self.assertAlmostEqual(pce.opt_par, 1.52, places=1)

if __name__ == '__main__':
    unittest.main()
# Copyright 2016 <NAME> # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # #    http://www.apache.org/licenses/LICENSE-2.0 # Set temporary output directories Simulate the output of a RabiAmp experiment of a given number of amp points.     amps: array of points between [-1,1]      returns: ideal data # repeated twice for X and Y rotations Simulate the output of a Ramsey experiment of a given number of time steps.     maxt: longest delay (s)     detuning: frequency detuning (Hz)     T2: 1/e decay time (s)      returns: ideal data Simulate the output of a PhaseEstimation experiment with NumPulses.     amp: initial pulse amplitude     target: target angle (pi/2, etc.)      returns: ideal data and variance # residual polarization after each pulse # data representing over/under rotation of pi/2 pulse # theta = pi/2 * (amp/ideal_amp); Simulate the output of a DRAG experiment with a set drag value      returns: ideal data Class for unittests of single-qubit calibrations. Tested so far with a dummy X6 digitizer:     * RabiAmpCalibration     * RamseyCalibration     Ideal data are generated and stored into a temporary file, whose name is set by the X6 property `ideal_data`. Calibrations which span over multiple experiments load different columns of these ideal data. The column (and experiment) number is set by an incremental counter, also a digitizer property `exp_step`. Artificial noise is added by the X6 dummy instrument. # Clear calibration table Test RabiAmpCalibration. Ideal data generated by simulate_rabiAmp. Simulate a RamseyCalibration run. Ideal data are generated by simulate_ramsey.         set_source: True (False) sets the source (qubit) frequency. Test RamseyCalibration with source frequency setting. #test update_settings # new_settings = auspex.config.load_meas_file(cfg_file) #restore original settings # auspex.config.dump_meas_file(self.test_settings, cfg_file) Test RamseyCalibration with qubit frequency setting. #test update_settings # new_settings = auspex.config.load_meas_file(cfg_file) # self.assertTrue( 0.85 < ((cl["q1"].frequency+90e3)/1e6)/(new_settings['qubits'][cl["q1"].label].frequency/1e6) < 1.15) #restore original settings # auspex.config.dump_meas_file(self.test_settings, cfg_file) Test generating data for phase estimation # Using the same simulated data as matlab # Verify output matches what was previously seen by matlab # TODO: fix me # self.assertAlmostEqual(sigma,0.0245,places=3) Test PiCalibration with phase estimation # TODO: fix this for other quadratures Test DRAGCalibration. Ideal data generated by simulate_drag. # arbitrary choice for testing Class for unittests of single-qubit calibrations. Tested so far with a dummy X6 digitizer:     * RabiAmpCalibration     * RamseyCalibration     Ideal data are generated and stored into a temporary file, whose name is set by the X6 property `ideal_data`. Calibrations which span over multiple experiments load different columns of these ideal data. The column (and experiment) number is set by an incremental counter, also a digitizer property `exp_step`. Artificial noise is added by the X6 dummy instrument. # Source # Target # Clear calibration table Test RabiAmpCalibration. Ideal data generated by simulate_rabiAmp. # Double each element... No prizes for this code... # vals = np.r_[vals,vals].reshape(2,-1).T.flatten() # Double each element... No prizes for this code... Test RabiAmpCalibration. Ideal data generated by simulate_rabiAmp. # Double each element... No prizes for this code... # vals = np.r_[vals,vals].reshape(2,-1).T.flatten() # Double each element... No prizes for this code...