Question

我正在努力制作一个情节。在x轴上，我想看到我的FinalSigmaValues字典的键，在y轴上，我想看到同一字典的值。我希望他们创造一个平滑的曲线。同时，我有另一个字典，其密钥与FinalSigmaValues相同。所以，我也希望在同一个情节上有另一条曲线。我使用以下代码并遇到很多错误。

from scipy.interpolate import spline
import matplotlib.pyplot as plt
import numpy as np
import collections
Finalsigma = collections.OrderedDict(sorted(FinalSigmaValues.items()))
P = np.array(Finalsigma.keys())
T = np.array(Finalsigma.values())
xnew = np.linspace(T.min(),T.max(),300)
P_smooth = spline(T,P,xnew)
plt.plot(xnew,P_smooth,color='k')
plt.xlabel('w')
plt.ylabel('First Part of the Objective Function')
plt.show()

正如您在代码中所看到的，我目前只是尝试绘制FinalSigmaValues，我还要担心'FinalPhiValues'。两个词典都在len 1376.任何建议都赞赏。

---------------------------------------------------------------------------
LinAlgError                               Traceback (most recent call last)
<ipython-input-18-2d2343ec9634> in <module>()
      4 xnew = np.linspace(T.min(),T.max(),300) 
      5 
----> 6 P_smooth = spline(T,P,xnew)
      7 
      8 plt.plot(xnew,P_smooth,color='k')

C:\Users\administrater\Anaconda2\lib\site-packages\scipy\interpolate\interpolate.pyc in spline(xk, yk, xnew, order, kind, conds)
   3010 
   3011     """
-> 3012     return spleval(splmake(xk,yk,order=order,kind=kind,conds=conds),xnew)

C:\Users\administrater\Anaconda2\lib\site-packages\scipy\interpolate\interpolate.pyc in splmake(xk, yk, order, kind, conds)
   2925     # the constraint matrix
   2926     B = _fitpack._bsplmat(order, xk)
-> 2927     coefs = func(xk, yk, order, conds, B)
   2928     return xk, coefs, order
   2929 

C:\Users\administrater\Anaconda2\lib\site-packages\scipy\interpolate\interpolate.pyc in _find_smoothest(xk, yk, order, conds, B)
   2622     tmp = dot(V2.T,A)
   2623     Q = dot(tmp,V2)
-> 2624     p = scipy.linalg.solve(Q, tmp)
   2625     tmp = dot(V2,p)
   2626     tmp = np.eye(N+K) - tmp

C:\Users\administrater\Anaconda2\lib\site-packages\scipy\linalg\basic.pyc in solve(a, b, sym_pos, lower, overwrite_a, overwrite_b, debug, check_finite)
    101         return x
    102     if info > 0:
--> 103         raise LinAlgError("singular matrix")
    104     raise ValueError('illegal value in %d-th argument of internal gesv|posv' %
    105                      -info)

LinAlgError: singular matrix

或者，我试过了：

from scipy.interpolate import spline
import matplotlib.pyplot as plt
import numpy as np
import collections
Finalsigma = collections.OrderedDict(sorted(FinalSigmaValues.items()))
Finalphi = collections.OrderedDict(sorted(FinalPhiValues.items()))

from scipy.interpolate import interp1d

x = Finalsigma.keys()
y = Finalsigma.values()
f = interp1d(x, y)
f2 = interp1d(x, y, kind='cubic')

xnew = Finalphi.values()
plt.plot(x, y, 'o', xnew, f(xnew), '-', xnew, f2(xnew), '--')
plt.show()

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-37-51a1312588ca> in <module>()
     14 
     15 xnew = Finalphi.values()
---> 16 plt.plot(x, y, 'o', xnew, f(xnew), '-', xnew, f2(xnew), '--')
     17 plt.show()

C:\Users\administrater\Anaconda2\lib\site-packages\scipy\interpolate\polyint.pyc in __call__(self, x)
     77         """
     78         x, x_shape = self._prepare_x(x)
---> 79         y = self._evaluate(x)
     80         return self._finish_y(y, x_shape)
     81 

C:\Users\administrater\Anaconda2\lib\site-packages\scipy\interpolate\interpolate.pyc in _evaluate(self, x_new)
    586         y_new = self._call(self, x_new)
    587         if not self._extrapolate:
--> 588             below_bounds, above_bounds = self._check_bounds(x_new)
    589             if len(y_new) > 0:
    590                 # Note fill_value must be broadcast up to the proper size

C:\Users\administrater\Anaconda2\lib\site-packages\scipy\interpolate\interpolate.pyc in _check_bounds(self, x_new)
    618                 "range.")
    619         if self.bounds_error and above_bounds.any():
--> 620             raise ValueError("A value in x_new is above the interpolation "
    621                 "range.")
    622 

ValueError: A value in x_new is above the interpolation range.

Answer 1

为什么不尝试下面的代码（从https://docs.scipy.org/doc/scipy/reference/tutorial/interpolate.html获取的代码）

from scipy.interpolate import interp1d

x = np.linspace(0, 10, num=11, endpoint=True)
y = np.cos(-x**2/9.0)
f = interp1d(x, y)
f2 = interp1d(x, y, kind='cubic')

xnew = np.linspace(0, 10, num=41, endpoint=True)
import matplotlib.pyplot as plt
plt.plot(x, y, 'o', xnew, f(xnew), '-', xnew, f2(xnew), '--')
plt.legend(['data', 'linear', 'cubic'], loc='best')
plt.show()

在一张图上绘制两条曲线

1 个答案: