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我已经计算了散点图的最佳拟合曲线,并且我想将结果绘制为平滑曲线,类似于SAS的样条。使用scipy.interplote.interp1d和matplotlib绘制平滑曲线Python 2.7 32位(Enthought Canopy)
经过一番谷歌搜索后,发现我应该先在我的数据上使用interpolate.interp1d,然后再绘制线条。但是,当我尝试基于documentation中的教程来执行此操作时,出现错误。提前感谢任何帮助或资源!
from scipy import interpolate
j = np.arange(0, 29, 1) # new x values
k = (model(xdata, g_fit, a_fit, b_fit)) # y values
l = interpolate.interp1d(j, k)
plt.scatter(xdata, ydata, c='g', marker='x')
plt.plot(xdata, model(xdata, g_fit, a_fit, b_fit), color='red')
plt.plot(j, l(k))
plt.axis([-1, 31, 0.5, 1.2]) # xmin, xmax, ymin, ymax
plt.show()
print p
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-56-0db707080a49> in <module>()
2 j = np.arange(0, 29, 1)
3 k = (model(xdata, g_fit, a_fit, b_fit))
----> 4 l = interpolate.interp1d(j, k)
5
6 plt.scatter(xdata, ydata, c='g', marker='x')
C:\Enthought\Canopy32\User\lib\sitepackages\scipy\interpolate\
interpolate.py in __init__
(self, x, y, kind, axis, copy, bounds_error, fill_value)
331 copy=True, bounds_error=True, fill_value=np.nan):
332 """ Initialize a 1D linear interpolation class."""
--> 333 _Interpolator1D.__init__(self, x, y, axis=axis)
334
335 self.copy = copy
C:\Enthought\Canopy32\User\lib\site-packages\scipy\interpolate\
polyint.py in __init__(self, xi, yi, axis)
33 self.dtype = None
34 if yi is not None:
---> 35 self._set_yi(yi, xi=xi, axis=axis)
36
37 def __call__(self, x):
C:\Enthought\Canopy32\User\lib\site-packages\scipy\interpolate\
polyint.py in _set_yi(self, yi, xi, axis)
92 shape = (1,)
93 if xi is not None and shape[axis] != len(xi):
---> 94 raise ValueError("x and y arrays must be equal in length along "
95 "interpolation axis.")
96
ValueError: x and y arrays must be equal in length along interpolation axis.
我想,我也许已经做了一些错误,当我试图interpolate.interp1d和np.arange,我不知道每一步应该做什么。每个y值都有一个x值,你问的是什么? – Bprodz
错误_ValueError:x和y数组沿着插值axis_的长度必须相等。说我和j的形状不一样。但是我有广告poblems与特定功能之前进行三次插值。对于你的情况不应该如此。 – ssm