#!/usr/bin/env python3

# Copyright 2017 IBM RESEARCH. All Rights Reserved.
#
# 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
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# =============================================================================

"""
Quantum teleportation example based on an OpenQASM example.

## Running this script using the "lightweight" CK infrastructure to import QISKit library...

# 1) on local simulator:
    ck virtual env --tags=lib,qiskit --shell_cmd=teleport.py

# 2) on remote simulator (need the API Token from IBM QuantumExperience) :
      CK_IBM_BACKEND=ibmq_qasm_simulator ck virtual `ck search env:* --tags=qiskit,lib`  `ck search env:* --tags=ibmqx,login` --shell_cmd=teleport.py
"""

import sys
import os

# We don't know from where the user is running the example,
# so we need a relative position from this file path.
# TODO: Relative imports for intra-package imports are highly discouraged.
# http://stackoverflow.com/a/7506006
sys.path.append(os.path.join(os.path.dirname(__file__), '../..'))

from qiskit import QuantumProgram, available_backends, register
from qiskit.mapper._coupling import coupling_dict2list

try:
    import Qconfig
    register(Qconfig.APItoken, Qconfig.config["url"], verify=False,
                      hub=Qconfig.config["hub"],
                      group=Qconfig.config["group"],
                      project=Qconfig.config["project"])
except:
    print("""
            WARNING: There's no connection with IBMQuantumExperience servers.
            cannot test I/O intesive tasks, will only test CPU intensive tasks
            running the jobs in the local simulator
            """)

###############################################################
# Set the backend name
###############################################################
print("The backends available for use are: {}\n".format(available_backends()))
#backend = os.environ.get('CK_IBM_BACKEND', 'ibmq_qasm_simulator')
backend = os.environ.get('CK_IBM_BACKEND', 'local_qasm_simulator')

###############################################################
# Set the coupling map
###############################################################
coupling_map = coupling_dict2list( {0: [1, 2],
                                    1: [2],
                                    2: [],
                                    3: [2, 4],
                                    4: [2],
})

###############################################################
# Make a quantum program for quantum teleportation.
###############################################################
QPS_SPECS = {
    "circuits": [{
        "name": "teleport",
        "quantum_registers": [{
            "name": "q",
            "size": 3
        }],
        "classical_registers": [
            {"name": "c0",
             "size": 1},
            {"name": "c1",
             "size": 1},
            {"name": "c2",
             "size": 1},
        ]}]
}

qp = QuantumProgram(specs=QPS_SPECS)
qc = qp.get_circuit("teleport")
q = qp.get_quantum_register("q")
c0 = qp.get_classical_register("c0")
c1 = qp.get_classical_register("c1")
c2 = qp.get_classical_register("c2")

# Prepare an initial state
qc.u3(0.3, 0.2, 0.1, q[0])

# Prepare a Bell pair
qc.h(q[1])
qc.cx(q[1], q[2])

# Barrier following state preparation
qc.barrier(q)

# Measure in the Bell basis
qc.cx(q[0], q[1])
qc.h(q[0])
qc.measure(q[0], c0[0])
qc.measure(q[1], c1[0])

# Apply a correction
qc.z(q[2]).c_if(c0, 1)
qc.x(q[2]).c_if(c1, 1)
qc.measure(q[2], c2[0])

###############################################################
# Execute the program.
###############################################################


# Experiment does not support feedback, so we use the simulator

# First version: not mapped
result = qp.execute(["teleport"], backend=backend,
                    coupling_map=None, shots=1024)
print(result)
print(result.get_counts("teleport"))

# Second version: mapped to qx2 coupling graph
result = qp.execute(["teleport"], backend=backend,
                    coupling_map=coupling_map, shots=1024)
print(result)
print(result.get_counts("teleport"))

if backend != 'local_qasm_simulator':
    print(result.get_ran_qasm("teleport"))

# Both versions should give the same distribution