小编ana*_*nar的帖子

我试图用Python取代复杂矩阵并遇到麻烦.我正在使用该scipy.linalg.expm函数,当我尝试以下代码时,我有一个相当奇怪的错误消息:

import numpy as np
from scipy import linalg

hamiltonian = np.mat('[1,0,0,0;0,-1,0,0;0,0,-1,0;0,0,0,1]')

# This works
t_list = np.linspace(0,1,10)
unitary = [linalg.expm(-(1j)*t*hamiltonian) for t in t_list]

# This doesn't
t_list = np.linspace(0,10,100)
unitary = [linalg.expm(-(1j)*t*hamiltonian) for t in t_list]

第二个实验运行时的错误是:

This works!
Traceback (most recent call last):
  File "matrix_exp.py", line 11, in <module>
    unitary_t = [linalg.expm(-1*t*(1j)*hamiltonian) for t in t_list]
  File "/usr/lib/python2.7/dist-packages/scipy/linalg/matfuncs.py",     line 105, in expm
    return scipy.sparse.linalg.expm(A)
  File "/usr/lib/python2.7/dist- packages/scipy/sparse/linalg/matfuncs.py", line 344, in expm
    X = _fragment_2_1(X, A, …

我正在尝试解决puLP（Python）中的MILP，并且不断收到以下错误：

Traceback (most recent call last):
  File "main_lp.py", line 63, in <module>
    ans = solve_lp(C)
  File "/home/ashwin/Documents/Williams/f2014/math317_or/project/solve_lp.py", line 36, in solve_lp
    prob.solve()
  File "/usr/local/lib/python2.7/dist-packages/PuLP-1.5.6-py2.7.egg/pulp/pulp.py", line 1619, in solve
    status = solver.actualSolve(self, **kwargs)
  File "/usr/local/lib/python2.7/dist-packages/PuLP-1.5.6-py2.7.egg/pulp/solvers.py", line 1283, in actualSolve
    return self.solve_CBC(lp, **kwargs)
  File "/usr/local/lib/python2.7/dist-packages/PuLP-1.5.6-py2.7.egg/pulp/solvers.py", line 1346, in solve_CBC
    raise PulpSolverError("Pulp: Error while executing "+self.path)
pulp.solvers.PulpSolverError: Pulp: Error while executing /usr/local/lib/python2.7/dist-packages/PuLP-1.5.6-py2.7.egg/pulp/solverdir/cbc-32

对于我的线性编程问题，我试图将不同向量的总和作为约束，并且我认为我一定做错了这个问题，因为一个更简单的问题可以解决。我已经附上了代码（C是一个N×N numpy数组）。

def solve_lp(C):
    N = len(C)
    prob=LpProblem('Scheduling',LpMinimize)

    X = [[LpVariable('X' + str(i+1) + str(j+1), 0, C[i,j],LpBinary)
          for …