在python中拟合变量Sinc函数 [英] Fitting a variable Sinc function in python

问题描述

我想将sinc函数适合一堆数据线。
使用高斯拟合本身确实可以工作，但数据似乎不够高斯，因此我认为我可以切换到正弦。

I would like to fit a sinc function to a bunch of datalines. Using a gauss the fit itself does work but the data does not seem to be sufficiently gaussian, so I figured I could just switch to sinc..

I只是试图将一小段自运行的代码放在一起，但意识到，我可能不太了解，如果将数组移交给函数将如何处理数组，这可能是原因之一，为什么我会收到调用程序的错误消息

I just tried to put together a short piece of self running code but realized, that I probably do not fully understand, how arrays are handled if handed over to a function, which could be part of the reason, why I get error messages calling my program

所以我的代码当前如下所示：

So my code currently looks as follows:

from numpy import exp
from scipy.optimize import curve_fit
from math import sin, pi

def gauss(x,*p):
    print(p)
    A, mu, sigma = p
    return A*exp(-1*(x[:]-mu)*(x[:]-mu)/sigma/sigma)

def sincSquare_mod(x,*p):
    A, mu, sigma = p
    return A * (sin(pi*(x[:]-mu)*sigma) / (pi*(x[:]-mu)*sigma))**2


p0 = [1., 30., 5.]
xpos = range(100)
fitdata = gauss(xpos,p0)
p1, var_matrix = curve_fit(sincSquare_mod, xpos, fitdata, p0)

我得到的是：

Traceback (most recent call last):
File "orthogonal_fit_test.py", line 18, in <module>
fitdata = gauss(xpos,p0)
File "orthogonal_fit_test.py", line 7, in gauss
A, mu, sigma = p
ValueError: need more than 1 value to unpack

据我了解，p没有正确交出，这很奇怪，因为它在我手中实际代码。安装后，我会从sincSquare函数获得类似的消息，可能是同一类型的错误。我对这家星级经营者还算陌生，所以可能隐藏了一个小故障...

From my understanding p is not handed over correctly, which is odd, because it is in my actual code. I then get a similar message from the sincSquare function, when fitted, which could probably be the same type of error. I am fairly new to the star operator, so there might be a glitch hidden...

有人有什么想法吗？ ：）

Anybody some ideas? :)

谢谢！

推荐答案

您需要进行三处更改，

def gauss(x, A, mu, sigma):
    return A*exp(-1*(x[:]-mu)*(x[:]-mu)/sigma/sigma)

def sincSquare_mod(x, A, mu, sigma):
    x=np.array(x)
    return A * (np.sin(pi*(x[:]-mu)*sigma) / (pi*(x[:]-mu)*sigma))**2

fitdata = gauss(xpos,*p0)

1，请参见文档

2，将 sin 替换为 array的 numpy 版本 code>广播

2, replace sin by the numpy version for array broadcasting

3，直截了当吧？ ：P

3, straight forward right? :P

注意，我想您正在寻找的是 p1，var_matrix = curve_fit（gauss，... 而不是比OP中的那个没有解决方案。

Note, i think you are looking for p1, var_matrix = curve_fit(gauss,... rather than the one in the OP, which appears do not have a solution.

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