text: # This code is part of Qiskit.
  #
  # (C) Copyright IBM 2017, 2019.
  #
  # This code is licensed under the Apache License, Version 2.0. You may
  # obtain a copy of this license in the LICENSE.txt file in the root directory
  # of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
  #
  # Any modifications or derivative works of this code must retain this
  # copyright notice, and modified files need to carry a notice indicating
  # that they have been altered from the originals.
  
  """
  Statevector quantum state class.
  """
  
  import copy
  import re
  from numbers import Number
  
  import numpy as np
  
  from qiskit.circuit.quantumcircuit import QuantumCircuit
  from qiskit.circuit.instruction import Instruction
  from qiskit.exceptions import QiskitError
  from qiskit.quantum_info.states.quantum_state import QuantumState
  from qiskit.quantum_info.operators.mixins.tolerances import TolerancesMixin
  from qiskit.quantum_info.operators.operator import Operator
  from qiskit.quantum_info.operators.symplectic import Pauli, SparsePauliOp
  from qiskit.quantum_info.operators.op_shape import OpShape
  from qiskit.quantum_info.operators.predicates import matrix_equal
  
  # pylint: disable=no-name-in-module
  from .cython.exp_value import expval_pauli_no_x, expval_pauli_with_x
  
  
  class Statevector(QuantumState, TolerancesMixin):
      """Statevector class"""
  
      def __init__(self, data, dims=None):
          """Initialize a statevector object.
  
          Args:
              data (np.array or list or Statevector or Operator or QuantumCircuit or
                    qiskit.circuit.Instruction):
                  Data from which the statevector can be constructed. This can be either a complex
                  vector, another statevector, a ``Operator` with only one column or a
                  ``QuantumCircuit`` or ``Instruction``.  If the data is a circuit or instruction,
                  the statevector is constructed by assuming that all qubits are initialized to the
                  zero state.
              dims (int or tuple or list): Optional. The subsystem dimension of
                                           the state (See additional information).
  
          Raises:
              QiskitError: if input data is not valid.
  
          Additional Information:
              The ``dims`` kwarg can be None, an integer, or an iterable of
              integers.
  
              * ``Iterable`` -- the subsystem dimensions are the values in the list
                with the total number of subsystems given by the length of the list.
  
              * ``Int`` or ``None`` -- the length of the input vector
                specifies the total dimension of the density matrix. If it is a
                power of two the state will be initialized as an N-qubit state.
                If it is not a power of two the state will have a single
                d-dimensional subsystem.
          """
          if isinstance(data, (list, np.ndarray)):
              # Finally we check if the input is a raw vector in either a
              # python list or numpy array format.
              self._data = np.asarray(data, dtype=complex)
          elif isinstance(data, Statevector):
              self._data = data._data
              if dims is None:
                  dims = data._op_shape._dims_l
          elif isinstance(data, Operator):
              # We allow conversion of column-vector operators to Statevectors
              input_dim, _ = data.dim
              if input_dim != 1:
                  raise QiskitError("Input Operator is not a column-vector.")
              self._data = np.ravel(data.data)
          elif isinstance(data, (QuantumCircuit, Instruction)):
              self._data = Statevector.from_instruction(data).data
          else:
              raise QiskitError("Invalid input data format for Statevector")
          # Check that the input is a numpy vector or column-vector numpy
          # matrix. If it is a column-vector matrix reshape to a vector.
          ndim = self._data.ndim
          shape = self._data.shape
          if ndim != 1:
              if ndim == 2 and shape[1] == 1:
                  self._data = np.reshape(self._data, shape[0])
                  shape = self._data.shape
              elif ndim != 2 or shape[1] != 1:
                  raise QiskitError("Invalid input: not a vector or column-vector.")
          super().__init__(op_shape=OpShape.auto(
              shape=shape, dims_l=dims, num_qubits_r=0))
  
      def __array__(self, dtype=None):
          if dtype:
              return np.asarray(self.data, dtype=dtype)
          return self.data
  
      def __eq__(self, other):
          return super().__eq__(other) and np.allclose(
              self._data, other._data, rtol=self.rtol, atol=self.atol)
  
      def __repr__(self):
          prefix = 'Statevector('
          pad = len(prefix) * ' '
          return '{}{},\n{}dims={})'.format(
              prefix, np.array2string(
                  self._data, separator=', ', prefix=prefix),
              pad, self._op_shape.dims_l())
  
      def draw(self, output=None, **drawer_args):
          """Return a visualization of the Statevector.
  
          **repr**: ASCII TextMatrix of the state's ``__repr__``.
  
          **text**: ASCII TextMatrix that can be printed in the console.
  
          **latex**: An IPython Latex object for displaying in Jupyter Notebooks.
  
          **latex_source**: Raw, uncompiled ASCII source to generate array using LaTeX.
  
          **qsphere**: Matplotlib figure, rendering of statevector using `plot_state_qsphere()`.
  
          **hinton**: Matplotlib figure, rendering of statevector using `plot_state_hinton()`.
  
          **bloch**: Matplotlib figure, rendering of statevector using `plot_bloch_multivector()`.
  
          Args:
              output (str): Select the output method to use for drawing the
                  state. Valid choices are `repr`, `text`, `latex`, `latex_source`,
                  `qsphere`, `hinton`, or `bloch`. Default is `repr`. Default can
                  be changed by adding the line ``state_drawer = <default>`` to
                  ``~/.qiskit/settings.conf`` under ``[default]``.
              drawer_args: Arguments to be passed directly to the relevant drawing
                  function or constructor (`TextMatrix()`, `array_to_latex()`,
                  `plot_state_qsphere()`, `plot_state_hinton()` or `plot_bloch_multivector()`).
                  See the relevant function under `qiskit.visualization` for that function's
                  documentation.
  
          Returns:
              :class:`matplotlib.Figure` or :class:`str` or
              :class:`TextMatrix` or :class:`IPython.display.Latex`:
              Drawing of the Statevector.
  
          Raises:
              ValueError: when an invalid output method is selected.
          """
          # pylint: disable=cyclic-import
          from qiskit.visualization.state_visualization import state_drawer
          return state_drawer(self, output=output, **drawer_args)
  
      def _ipython_display_(self):
          out = self.draw()
          if isinstance(out, str):
              print(out)
          else:
              from IPython.display import display
              display(out)
  
      @property
      def data(self):
          """Return data."""
          return self._data
  
      def is_valid(self, atol=None, rtol=None):
          """Return True if a Statevector has norm 1."""
          if atol is None:
              atol = self.atol
          if rtol is None:
              rtol = self.rtol
          norm = np.linalg.norm(self.data)
          return np.allclose(norm, 1, rtol=rtol, atol=atol)
  
      def to_operator(self):
          """Convert state to a rank-1 projector operator"""
          mat = np.outer(self.data, np.conj(self.data))
          return Operator(mat, input_dims=self.dims(), output_dims=self.dims())
  
      def conjugate(self):
          """Return the conjugate of the operator."""
          return Statevector(np.conj(self.data), dims=self.dims())
  
      def trace(self):
          """Return the trace of the quantum state as a density matrix."""
          return np.sum(np.abs(self.data) ** 2)
  
      def purity(self):
          """Return the purity of the quantum state."""
          # For a valid statevector the purity is always 1, however if we simply
          # have an arbitrary vector (not correctly normalized) then the
          # purity is equivalent to the trace squared:
          # P(|psi>) = Tr[|psi><psi|psi><psi|] = |<psi|psi>|^2
          return self.trace() ** 2
  
      def tensor(self, other):
          """Return the tensor product state self ⊗ other.
  
          Args:
              other (Statevector): a quantum state object.
  
          Returns:
              Statevector: the tensor product operator self ⊗ other.
  
          Raises:
              QiskitError: if other is not a quantum state.
          """
          if not isinstance(other, Statevector):
              other = Statevector(other)
          ret = copy.copy(self)
          ret._op_shape = self._op_shape.tensor(other._op_shape)
          ret._data = np.kron(self._data, other._data)
          return ret
  
      def expand(self, other):
          """Return the tensor product state other ⊗ self.
  
          Args:
              other (Statevector): a quantum state object.
  
          Returns:
              Statevector: the tensor product state other ⊗ self.
  
          Raises:
              QiskitError: if other is not a quantum state.
          """
          if not isinstance(other, Statevector):
              other = Statevector(other)
          ret = copy.copy(self)
          ret._op_shape = self._op_shape.expand(other._op_shape)
          ret._data = np.kron(other._data, self._data)
          return ret
  
      def _add(self, other):
          """Return the linear combination self + other.
  
          Args:
              other (Statevector): a quantum state object.
  
          Returns:
              Statevector: the linear combination self + other.
  
          Raises:
              QiskitError: if other is not a quantum state, or has
                           incompatible dimensions.
          """
          if not isinstance(other, Statevector):
              other = Statevector(other)
          self._op_shape._validate_add(other._op_shape)
          ret = copy.copy(self)
          ret._data = self.data + other.data
          return ret
  
      def _multiply(self, other):
          """Return the scalar multiplied state self * other.
  
          Args:
              other (complex): a complex number.
  
          Returns:
              Statevector: the scalar multiplied state other * self.
  
          Raises:
              QiskitError: if other is not a valid complex number.
          """
          if not isinstance(other, Number):
              raise QiskitError("other is not a number")
          ret = copy.copy(self)
          ret._data = other * self.data
          return ret
  
      def evolve(self, other, qargs=None):
          """Evolve a quantum state by the operator.
  
          Args:
              other (Operator): The operator to evolve by.
              qargs (list): a list of Statevector subsystem positions to apply
                             the operator on.
  
          Returns:
              Statevector: the output quantum state.
  
          Raises:
              QiskitError: if the operator dimension does not match the
                           specified Statevector subsystem dimensions.
          """
          if qargs is None:
              qargs = getattr(other, 'qargs', None)
  
          # Get return vector
          ret = copy.copy(self)
  
          # Evolution by a circuit or instruction
          if isinstance(other, QuantumCircuit):
              other = other.to_instruction()
          if isinstance(other, Instruction):
              if self.num_qubits is None:
                  raise QiskitError("Cannot apply QuantumCircuit to non-qubit Statevector.")
              return self._evolve_instruction(ret, other, qargs=qargs)
  
          # Evolution by an Operator
          if not isinstance(other, Operator):
              other = Operator(other)
  
          # check dimension
          if self.dims(qargs) != other.input_dims():
              raise QiskitError(
                  "Operator input dimensions are not equal to statevector subsystem dimensions."
              )
          return Statevector._evolve_operator(ret, other, qargs=qargs)
  
      def equiv(self, other, rtol=None, atol=None):
          """Return True if other is equivalent as a statevector up to global phase.
  
          .. note::
  
              If other is not a Statevector, but can be used to initialize a statevector object,
              this will check that Statevector(other) is equivalent to the current statevector up
              to global phase.
  
          Args:
              other (Statevector): an object from which a ``Statevector`` can be constructed.
              rtol (float): relative tolerance value for comparison.
              atol (float): absolute tolerance value for comparison.
  
          Returns:
              bool: True if statevectors are equivalent up to global phase.
          """
          if not isinstance(other, Statevector):
              try:
                  other = Statevector(other)
              except QiskitError:
                  return False
          if self.dim != other.dim:
              return False
          if atol is None:
              atol = self.atol
          if rtol is None:
              rtol = self.rtol
          return matrix_equal(self.data, other.data, ignore_phase=True,
                              rtol=rtol, atol=atol)
  
      def reverse_qargs(self):
          r"""Return a Statevector with reversed subsystem ordering.
  
          For a tensor product state this is equivalent to reversing the order
          of tensor product subsystems. For a statevector
          :math:`|\psi \rangle = |\psi_{n-1} \rangle \otimes ... \otimes |\psi_0 \rangle`
          the returned statevector will be
          :math:`|\psi_{0} \rangle \otimes ... \otimes |\psi_{n-1} \rangle`.
  
          Returns:
              Statevector: the Statevector with reversed subsystem order.
          """
          ret = copy.copy(self)
          axes = tuple(range(self._op_shape._num_qargs_l - 1, -1, -1))
          ret._data = np.reshape(np.transpose(
              np.reshape(self.data, self._op_shape.tensor_shape), axes),
                                 self._op_shape.shape)
          ret._op_shape = self._op_shape.reverse()
          return ret
  
      def _expectation_value_pauli(self, pauli):
          """Compute the expectation value of a Pauli.
  
              Args:
                  pauli (Pauli): a Pauli operator to evaluate expval of.
  
              Returns:
                  complex: the expectation value.
              """
          n_pauli = len(pauli)
          qubits = np.arange(n_pauli)
          x_mask = np.dot(1 << qubits, pauli.x)
          z_mask = np.dot(1 << qubits, pauli.z)
          pauli_phase = (-1j) ** pauli.phase if pauli.phase else 1
  
          if x_mask + z_mask == 0:
              return pauli_phase * np.linalg.norm(self.data)
  
          if x_mask == 0:
              return pauli_phase * expval_pauli_no_x(self.data, self.num_qubits, z_mask)
  
          x_max = qubits[pauli.x][-1]
          y_phase = (-1j) ** np.sum(pauli.x & pauli.z)
  
          return pauli_phase * expval_pauli_with_x(
              self.data, self.num_qubits, z_mask, x_mask, y_phase, x_max)
  
      def expectation_value(self, oper, qargs=None):
          """Compute the expectation value of an operator.
  
          Args:
              oper (Operator): an operator to evaluate expval of.
              qargs (None or list): subsystems to apply operator on.
  
          Returns:
              complex: the expectation value.
          """
          if isinstance(oper, Pauli):
              return self._expectation_value_pauli(oper)
  
          if isinstance(oper, SparsePauliOp):
              return sum([coeff * self._expectation_value_pauli(Pauli((z, x)))
                          for z, x, coeff in zip(oper.table.Z, oper.table.X, oper.coeffs)])
  
          val = self.evolve(oper, qargs=qargs)
          conj = self.conjugate()
          return np.dot(conj.data, val.data)
  
      def probabilities(self, qargs=None, decimals=None):
          """Return the subsystem measurement probability vector.
  
          Measurement probabilities are with respect to measurement in the
          computation (diagonal) basis.
  
          Args:
              qargs (None or list): subsystems to return probabilities for,
                  if None return for all subsystems (Default: None).
              decimals (None or int): the number of decimal places to round
                  values. If None no rounding is done (Default: None).
  
          Returns:
              np.array: The Numpy vector array of probabilities.
  
          Examples:
  
              Consider a 2-qubit product state
              :math:`|\\psi\\rangle=|+\\rangle\\otimes|0\\rangle`.
  
              .. jupyter-execute::
  
                  from qiskit.quantum_info import Statevector
  
                  psi = Statevector.from_label('+0')
  
                  # Probabilities for measuring both qubits
                  probs = psi.probabilities()
                  print('probs: {}'.format(probs))
  
                  # Probabilities for measuring only qubit-0
                  probs_qubit_0 = psi.probabilities([0])
                  print('Qubit-0 probs: {}'.format(probs_qubit_0))
  
                  # Probabilities for measuring only qubit-1
                  probs_qubit_1 = psi.probabilities([1])
                  print('Qubit-1 probs: {}'.format(probs_qubit_1))
  
              We can also permute the order of qubits in the ``qargs`` list
              to change the qubit position in the probabilities output
  
              .. jupyter-execute::
  
                  from qiskit.quantum_info import Statevector
  
                  psi = Statevector.from_label('+0')
  
                  # Probabilities for measuring both qubits
                  probs = psi.probabilities([0, 1])
                  print('probs: {}'.format(probs))
  
                  # Probabilities for measuring both qubits
                  # but swapping qubits 0 and 1 in output
                  probs_swapped = psi.probabilities([1, 0])
                  print('Swapped probs: {}'.format(probs_swapped))
          """
          probs = self._subsystem_probabilities(
              np.abs(self.data) ** 2, self._op_shape.dims_l(), qargs=qargs)
          if decimals is not None:
              probs = probs.round(decimals=decimals)
          return probs
  
      def reset(self, qargs=None):
          """Reset state or subsystems to the 0-state.
  
          Args:
              qargs (list or None): subsystems to reset, if None all
                                    subsystems will be reset to their 0-state
                                    (Default: None).
  
          Returns:
              Statevector: the reset state.
  
          Additional Information:
              If all subsystems are reset this will return the ground state
              on all subsystems. If only a some subsystems are reset this
              function will perform a measurement on those subsystems and
              evolve the subsystems so that the collapsed post-measurement
              states are rotated to the 0-state. The RNG seed for this
              sampling can be set using the :meth:`seed` method.
          """
          if qargs is None:
              # Resetting all qubits does not require sampling or RNG
              ret = copy.copy(self)
              state = np.zeros(self._op_shape.shape, dtype=complex)
              state[0] = 1
              ret._data = state
              return ret
  
          # Sample a single measurement outcome
          dims = self.dims(qargs)
          probs = self.probabilities(qargs)
          sample = self._rng.choice(len(probs), p=probs, size=1)
  
          # Convert to projector for state update
          proj = np.zeros(len(probs), dtype=complex)
          proj[sample] = 1 / np.sqrt(probs[sample])
  
          # Rotate outcome to 0
          reset = np.eye(len(probs))
          reset[0, 0] = 0
          reset[sample, sample] = 0
          reset[0, sample] = 1
  
          # compose with reset projection
          reset = np.dot(reset, np.diag(proj))
          return self.evolve(
              Operator(reset, input_dims=dims, output_dims=dims),
              qargs=qargs)
  
      @classmethod
      def from_label(cls, label):
          """Return a tensor product of Pauli X,Y,Z eigenstates.
  
          .. list-table:: Single-qubit state labels
             :header-rows: 1
  
             * - Label
               - Statevector
             * - ``"0"``
               - :math:`[1, 0]`
             * - ``"1"``
               - :math:`[0, 1]`
             * - ``"+"``
               - :math:`[1 / \\sqrt{2},  1 / \\sqrt{2}]`
             * - ``"-"``
               - :math:`[1 / \\sqrt{2},  -1 / \\sqrt{2}]`
             * - ``"r"``
               - :math:`[1 / \\sqrt{2},  i / \\sqrt{2}]`
             * - ``"l"``
               - :math:`[1 / \\sqrt{2},  -i / \\sqrt{2}]`
  
          Args:
              label (string): a eigenstate string ket label (see table for
                              allowed values).
  
          Returns:
              Statevector: The N-qubit basis state density matrix.
  
          Raises:
              QiskitError: if the label contains invalid characters, or the
                           length of the label is larger than an explicitly
                           specified num_qubits.
          """
          # Check label is valid
          if re.match(r'^[01rl\-+]+$', label) is None:
              raise QiskitError('Label contains invalid characters.')
          # We can prepare Z-eigenstates by converting the computational
          # basis bit-string to an integer and preparing that unit vector
          # However, for X-basis states, we will prepare a Z-eigenstate first
          # then apply Hadamard gates to rotate 0 and 1s to + and -.
          z_label = label
          xy_states = False
          if re.match('^[01]+$', label) is None:
              # We have X or Y eigenstates so replace +,r with 0 and
              # -,l with 1 and prepare the corresponding Z state
              xy_states = True
              z_label = z_label.replace('+', '0')
              z_label = z_label.replace('r', '0')
              z_label = z_label.replace('-', '1')
              z_label = z_label.replace('l', '1')
          # Initialize Z eigenstate vector
          num_qubits = len(label)
          data = np.zeros(1 << num_qubits, dtype=complex)
          pos = int(z_label, 2)
          data[pos] = 1
          state = Statevector(data)
          if xy_states:
              # Apply hadamards to all qubits in X eigenstates
              x_mat = np.array([[1, 1], [1, -1]], dtype=complex) / np.sqrt(2)
              # Apply S.H to qubits in Y eigenstates
              y_mat = np.dot(np.diag([1, 1j]), x_mat)
              for qubit, char in enumerate(reversed(label)):
                  if char in ['+', '-']:
                      state = state.evolve(x_mat, qargs=[qubit])
                  elif char in ['r', 'l']:
                      state = state.evolve(y_mat, qargs=[qubit])
          return state
  
      @staticmethod
      def from_int(i, dims):
          """Return a computational basis statevector.
  
          Args:
              i (int): the basis state element.
              dims (int or tuple or list): The subsystem dimensions of the statevector
                                           (See additional information).
  
          Returns:
              Statevector: The computational basis state :math:`|i\\rangle`.
  
          Additional Information:
              The ``dims`` kwarg can be an integer or an iterable of integers.
  
              * ``Iterable`` -- the subsystem dimensions are the values in the list
                with the total number of subsystems given by the length of the list.
  
              * ``Int`` -- the integer specifies the total dimension of the
                state. If it is a power of two the state will be initialized
                as an N-qubit state. If it is not a power of  two the state
                will have a single d-dimensional subsystem.
          """
          size = np.product(dims)
          state = np.zeros(size, dtype=complex)
          state[i] = 1.0
          return Statevector(state, dims=dims)
  
      @classmethod
      def from_instruction(cls, instruction):
          """Return the output statevector of an instruction.
  
          The statevector is initialized in the state :math:`|{0,\\ldots,0}\\rangle` of the
          same number of qubits as the input instruction or circuit, evolved
          by the input instruction, and the output statevector returned.
  
          Args:
              instruction (qiskit.circuit.Instruction or QuantumCircuit): instruction or circuit
  
          Returns:
              Statevector: The final statevector.
  
          Raises:
              QiskitError: if the instruction contains invalid instructions for
                           the statevector simulation.
          """
          # Convert circuit to an instruction
          if isinstance(instruction, QuantumCircuit):
              instruction = instruction.to_instruction()
          # Initialize an the statevector in the all |0> state
          init = np.zeros(2 ** instruction.num_qubits, dtype=complex)
          init[0] = 1.0
          vec = Statevector(init, dims=instruction.num_qubits * (2,))
          return Statevector._evolve_instruction(vec, instruction)
  
      def to_dict(self, decimals=None):
          r"""Convert the statevector to dictionary form.
  
          This dictionary representation uses a Ket-like notation where the
          dictionary keys are qudit strings for the subsystem basis vectors.
          If any subsystem has a dimension greater than 10 comma delimiters are
          inserted between integers so that subsystems can be distinguished.
  
          Args:
              decimals (None or int): the number of decimal places to round
                                      values. If None no rounding is done
                                      (Default: None).
  
          Returns:
              dict: the dictionary form of the Statevector.
  
          Example:
  
              The ket-form of a 2-qubit statevector
              :math:`|\psi\rangle = |-\rangle\otimes |0\rangle`
  
              .. jupyter-execute::
  
                  from qiskit.quantum_info import Statevector
  
                  psi = Statevector.from_label('-0')
                  print(psi.to_dict())
  
              For non-qubit subsystems the integer range can go from 0 to 9. For
              example in a qutrit system
  
              .. jupyter-execute::
  
                  import numpy as np
                  from qiskit.quantum_info import Statevector
  
                  vec = np.zeros(9)
                  vec[0] = 1 / np.sqrt(2)
                  vec[-1] = 1 / np.sqrt(2)
                  psi = Statevector(vec, dims=(3, 3))
                  print(psi.to_dict())
  
              For large subsystem dimensions delimeters are required. The
              following example is for a 20-dimensional system consisting of
              a qubit and 10-dimensional qudit.
  
              .. jupyter-execute::
  
                  import numpy as np
                  from qiskit.quantum_info import Statevector
  
                  vec = np.zeros(2 * 10)
                  vec[0] = 1 / np.sqrt(2)
                  vec[-1] = 1 / np.sqrt(2)
                  psi = Statevector(vec, dims=(2, 10))
                  print(psi.to_dict())
          """
          return self._vector_to_dict(self.data,
                                      self._op_shape.dims_l(),
                                      decimals=decimals,
                                      string_labels=True)
  
      @staticmethod
      def _evolve_operator(statevec, oper, qargs=None):
          """Evolve a qudit statevector"""
          new_shape = statevec._op_shape.compose(oper._op_shape, qargs=qargs)
          if qargs is None:
              # Full system evolution
              statevec._data = np.dot(oper._data, statevec._data)
              statevec._op_shape = new_shape
              return statevec
  
          # Get transpose axes
          num_qargs = statevec._op_shape.num_qargs[0]
          indices = [num_qargs - 1 - i for i in reversed(qargs)]
          axes = indices + [i for i in range(num_qargs) if i not in indices]
          axes_inv = np.argsort(axes).tolist()
  
          # Calculate contraction dimensions
          contract_dim = oper._op_shape.shape[1]
          contract_shape = (contract_dim, statevec._op_shape.shape[0] // contract_dim)
  
          # Reshape input for contraction
          statevec._data = np.reshape(
              np.transpose(np.reshape(statevec.data, statevec._op_shape.tensor_shape),
                           axes), contract_shape)
          # Contract and reshape output
          statevec._data = np.reshape(np.dot(oper.data, statevec._data),
                                      new_shape.tensor_shape)
          statevec._data = np.reshape(np.transpose(statevec._data, axes_inv),
                                      new_shape.shape[0])
  
          # Update dimension
          statevec._op_shape = new_shape
          return statevec
  
      @staticmethod
      def _evolve_instruction(statevec, obj, qargs=None):
          """Update the current Statevector by applying an instruction."""
          from qiskit.circuit.reset import Reset
          from qiskit.circuit.barrier import Barrier
  
          mat = Operator._instruction_to_matrix(obj)
          if mat is not None:
              # Perform the composition and inplace update the current state
              # of the operator
              return Statevector._evolve_operator(statevec, Operator(mat), qargs=qargs)
  
          # Special instruction types
          if isinstance(obj, Reset):
              statevec._data = statevec.reset(qargs)._data
              return statevec
          if isinstance(obj, Barrier):
              return statevec
  
          # If the instruction doesn't have a matrix defined we use its
          # circuit decomposition definition if it exists, otherwise we
          # cannot compose this gate and raise an error.
          if obj.definition is None:
              raise QiskitError('Cannot apply Instruction: {}'.format(obj.name))
          if not isinstance(obj.definition, QuantumCircuit):
              raise QiskitError('{} instruction definition is {}; expected QuantumCircuit'.format(
                  obj.name, type(obj.definition)))
          if obj.definition.global_phase:
              statevec._data *= np.exp(1j * float(obj.definition.global_phase))
          qubits = {qubit: i for i, qubit in enumerate(obj.definition.qubits)}
          for instr, qregs, cregs in obj.definition:
              if cregs:
                  raise QiskitError(
                      'Cannot apply instruction with classical registers: {}'.format(
                          instr.name))
              # Get the integer position of the flat register
              if qargs is None:
                  new_qargs = [qubits[tup] for tup in qregs]
              else:
                  new_qargs = [qargs[qubits[tup]] for tup in qregs]
              Statevector._evolve_instruction(statevec, instr, qargs=new_qargs)
          return statevec
  