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ptrace.py
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ptrace.py
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# This file is part of QuTiP: Quantum Toolbox in Python.
#
# Copyright (c) 2011 and later, Paul D. Nation and Robert J. Johansson.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# 1. Redistributions of source code must retain the above copyright notice,
# this list of conditions and the following disclaimer.
#
# 2. Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
#
# 3. Neither the name of the QuTiP: Quantum Toolbox in Python nor the names
# of its contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A
# PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
# HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
###############################################################################
__all__ = []
import numpy as np
import scipy.sparse as sp
from qutip.sparse import sp_reshape
def _ptrace(rho, sel):
"""
Private function calculating the partial trace.
"""
if isinstance(sel, int):
sel = np.array([sel])
else:
sel = np.asarray(sel)
if (sel < 0).any() or (sel >= len(rho.dims[0])).any():
raise TypeError("Invalid selection index in ptrace.")
drho = rho.dims[0]
N = np.prod(drho)
M = np.prod(np.asarray(drho).take(sel))
if np.prod(rho.dims[1]) == 1:
rho = rho * rho.dag()
perm = sp.lil_matrix((M * M, N * N))
# all elements in range(len(drho)) not in sel set
rest = np.setdiff1d(np.arange(len(drho)), sel)
ilistsel = _select(sel, drho)
indsel = _list2ind(ilistsel, drho)
ilistrest = _select(rest, drho)
indrest = _list2ind(ilistrest, drho)
irest = (indrest - 1) * N + indrest - 2
# Possibly use parfor here if M > some value ?
perm.rows = np.array(
[(irest + (indsel[int(np.floor(m / M))] - 1) * N +
indsel[int(np.mod(m, M))]).T[0]
for m in range(M ** 2)])
# perm.data = np.ones_like(perm.rows,dtype=int)
perm.data = np.ones_like(perm.rows)
perm.tocsr()
rhdata = perm * sp_reshape(rho.data, [np.prod(rho.shape), 1])
rhdata = rhdata.tolil().reshape((M, M))
rho1_data = rhdata.tocsr()
dims_kept0 = np.asarray(rho.dims[0]).take(sel)
dims_kept1 = np.asarray(rho.dims[0]).take(sel)
rho1_dims = [dims_kept0.tolist(), dims_kept1.tolist()]
rho1_shape = [np.prod(dims_kept0), np.prod(dims_kept1)]
return rho1_data, rho1_dims, rho1_shape
def _list2ind(ilist, dims):
"""!
Private function returning indicies
"""
ilist = np.asarray(ilist)
dims = np.asarray(dims)
irev = np.fliplr(ilist) - 1
fact = np.append(np.array([1]), (np.cumprod(np.flipud(dims)[:-1])))
fact = fact.reshape(len(fact), 1)
return np.array(np.sort(np.dot(irev, fact) + 1, 0), dtype=int)
def _select(sel, dims):
"""
Private function finding selected components
"""
sel = np.asarray(sel) # make sure sel is np.array
dims = np.asarray(dims) # make sure dims is np.array
rlst = dims.take(sel)
rprod = np.prod(rlst)
ilist = np.ones((rprod, len(dims)), dtype=int)
counter = np.arange(rprod)
for k in range(len(sel)):
ilist[:, sel[k]] = np.remainder(
np.fix(counter / np.prod(dims[sel[k + 1:]])), dims[sel[k]]) + 1
return ilist