本文整理汇总了Python中qutip.solver.Result.expect[jj]方法的典型用法代码示例。如果您正苦于以下问题：Python Result.expect[jj]方法的具体用法？Python Result.expect[jj]怎么用？Python Result.expect[jj]使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类qutip.solver.Result的用法示例。
在下文中一共展示了Result.expect[jj]方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: _gather
# 需要导入模块: from qutip.solver import Result [as 别名]
# 或者: from qutip.solver.Result import expect[jj] [as 别名]
def _gather(sols):
# gather list of Result objects, sols, into one.
sol = Result()
# sol = sols[0]
ntraj = sum([a.ntraj for a in sols])
sol.col_times = np.zeros((ntraj), dtype=np.ndarray)
sol.col_which = np.zeros((ntraj), dtype=np.ndarray)
sol.col_times[0:sols[0].ntraj] = sols[0].col_times
sol.col_which[0:sols[0].ntraj] = sols[0].col_which
sol.states = np.array(sols[0].states)
sol.expect = np.array(sols[0].expect)
if (hasattr(sols[0], 'entropy')):
sol.entropy = np.array(sols[0].entropy)
sofar = 0
for j in range(1, len(sols)):
sofar = sofar + sols[j - 1].ntraj
sol.col_times[sofar:sofar + sols[j].ntraj] = (
sols[j].col_times)
sol.col_which[sofar:sofar + sols[j].ntraj] = (
sols[j].col_which)
if (config.e_num == 0):
if (config.options.average_states):
# collect states, averaged over trajectories
sol.states += np.array(sols[j].states)
else:
# collect states, all trajectories
sol.states = np.vstack((sol.states,
np.array(sols[j].states)))
else:
if (config.options.average_expect):
# collect expectation values, averaged
for i in range(config.e_num):
sol.expect[i] += np.array(sols[j].expect[i])
else:
# collect expectation values, all trajectories
sol.expect = np.vstack((sol.expect,
np.array(sols[j].expect)))
if (hasattr(sols[j], 'entropy')):
if (config.options.average_states or
config.options.average_expect):
# collect entropy values, averaged
sol.entropy += np.array(sols[j].entropy)
else:
# collect entropy values, all trajectories
sol.entropy = np.vstack((sol.entropy,
np.array(sols[j].entropy)))
if (config.options.average_states or config.options.average_expect):
if (config.e_num == 0):
sol.states = sol.states / len(sols)
else:
sol.expect = list(sol.expect / len(sols))
inds = np.where(config.e_ops_isherm)[0]
for jj in inds:
sol.expect[jj] = np.real(sol.expect[jj])
if (hasattr(sols[0], 'entropy')):
sol.entropy = sol.entropy / len(sols)
# convert sol.expect array to list and fix dtypes of arrays
if (not config.options.average_expect) and config.e_num != 0:
temp = [list(sol.expect[ii]) for ii in range(ntraj)]
for ii in range(ntraj):
for jj in np.where(config.e_ops_isherm)[0]:
temp[ii][jj] = np.real(temp[ii][jj])
sol.expect = temp
# convert to list/array to be consistent with qutip mcsolve
sol.states = list(sol.states)
return sol