python - 将代码 matlab 转换为 python numpy

Question

我不懂matlab编程，我只懂python编码...

Matlab代码:

 x = ones(3,1).
con = [0.505868045540458,0.523598775598299].
series = [1,2,3] 
for j = 1:2 
   #here stuck to translate Python code#
   x = [x cos(con(j)*series)' sin(con(j)*series)'];
end

结果:

1.0000    0.8748    0.4846    0.8660    0.5000
1.0000    0.5304    0.8478    0.5000    0.8660
1.0000    0.0532    0.9986   -0.0000    1.0000

谁能帮帮我，请问如何解决这个问题...问候!

Answer 1

我在 Ipython session 中的娱乐(首先在 Octave session 中测试了您的代码):

In [649]: con = np.array([0.505868, 0.5235897])
In [650]: series = np.array([1,2,3])
In [651]: x = [np.ones((3,))]
In [652]: for j in range(2):
     ...:     x.extend([np.cos(con[j]*series), np.sin(con[j]*series)])
     ...:     
In [653]: x
Out[653]: 
[array([ 1.,  1.,  1.]),
 array([ 0.8747542 ,  0.53038982,  0.05316725]),
 array([ 0.48456691,  0.84775388,  0.99858562]),
 array([  8.66029942e-01,   5.00015719e-01,   2.72267949e-05]),
 array([ 0.49999214,  0.86601633,  1.        ])]
In [654]: np.array(x).T
Out[654]: 
array([[  1.00000000e+00,   8.74754200e-01,   4.84566909e-01,
          8.66029942e-01,   4.99992140e-01],
       [  1.00000000e+00,   5.30389821e-01,   8.47753878e-01,
          5.00015719e-01,   8.66016328e-01],
       [  1.00000000e+00,   5.31672464e-02,   9.98585622e-01,
          2.72267949e-05,   1.00000000e+00]])

在MATLAB中

x = [x cos(...) sin(...)]

更接近于

x = np.concatenate([x, cos(...), sin(...)], axis=?)

但在 numpy 列表中追加(或在本例中为扩展)更快。我只需将 x 初始化为适当的列表即可。

==================

我可以在没有循环的情况下得到相同的值

In [663]: y = con[:,None]*series
In [664]: [np.cos(y), np.sin(y)]
Out[664]: 
[array([[  8.74754200e-01,   5.30389821e-01,   5.31672464e-02],
        [  8.66029942e-01,   5.00015719e-01,   2.72267949e-05]]),
 array([[ 0.48456691,  0.84775388,  0.99858562],
        [ 0.49999214,  0.86601633,  1.        ]])]

但是将它们重新排列成迭代产生的顺序有点痛苦，[1, cos, sin, cos, sin]。