Python - 根据记录值拟合指数衰减曲线

Posted 2021-04-26

我知道有关于此的线程，但我很困惑我想要的地方我的数据适合。

我的数据是导入的，并按此绘制。

import matplotlib.pyplot as plt
%matplotlib inline
import pylab as plb
import numpy as np
import scipy as sp
import csv

FreqTime1 = []
DecayCount1 = []
with open('Half_Life.csv', 'r') as f:
    reader = csv.reader(f, delimiter=',')
    for row in reader:
        FreqTime1.append(row[0])
        DecayCount1.append(row[3])

FreqTime1 = np.array(FreqTime1) 
DecayCount1 = np.array(DecayCount1)

fig1 = plt.figure(figsize=(15,6))
ax1 = fig1.add_subplot(111)
ax1.plot(FreqTime1,DecayCount1, ".", label = 'Run 1')
ax1.set_xlabel('Time (sec)')
ax1.set_ylabel('Count')
plt.legend()

问题是，我在设置一般指数衰减时遇到困难，我不知道如何计算数据集中的参数值。

如果可能的话，我想要将拟合衰减方程的方程与图一起显示。但是，如果能够生产合身，则可以很容易地应用。

编辑------------------------------------------------- ------------

因此，当使用Stanely R提到的拟合函数时

def model_func(x, a, k, b):
    return a * np.exp(-k*x) + b

x = FreqTime1
y = DecayCount1


p0 = (1.,1.e-5,1.) 
opt, pcov = curve_fit(model_func, x, y, p0)
a, k, b = opt

我收到此错误消息

TypeError: ufunc 'multiply' did not contain a loop with signature matching types dtype('S32') dtype('S32') dtype('S32')

有关如何解决此问题的任何想法？

答案

你必须使用scipy.optimize：curve_fit中的http://docs.scipy.org/doc/scipy-0.16.1/reference/generated/scipy.optimize.curve_fit.html

from scipy.optimize import curve_fit
import numpy as np
# define type of function to search
def model_func(x, a, k, b):
    return a * np.exp(-k*x) + b

# sample data
x = np.array([399.75, 989.25, 1578.75, 2168.25, 2757.75, 3347.25, 3936.75, 4526.25, 5115.75, 5705.25])
y = np.array([109,62,39,13,10,4,2,0,1,2])

# curve fit
p0 = (1.,1.e-5,1.) # starting search koefs
opt, pcov = curve_fit(model_func, x, y, p0)
a, k, b = opt
# test result
x2 = np.linspace(250, 6000, 250)
y2 = model_func(x2, a, k, b)
fig, ax = plt.subplots()
ax.plot(x2, y2, color='r', label='Fit. func: $f(x) = %.3f e^{%.3f x} %+.3f$' % (a,k,b))
ax.plot(x, y, 'bo', label='data with noise')
ax.legend(loc='best')
plt.show()

另一答案

“我收到此错误消息

TypeError: ufunc 'multiply' did not contain a loop with signature matching types dtype('S32') dtype('S32') dtype('S32')

关于如何解决这个问题的任何想法？“

读取CSV文件以创建FreqTime1和DelayCount1的代码正在创建字符串数组。你可以按照@StanleyR在评论中提出的建议来解决这个问题。更好的想法是替换此代码：

FreqTime1 = []
DecayCount1 = []
with open('Half_Life.csv', 'r') as f:
    reader = csv.reader(f, delimiter=',')
    for row in reader:
        FreqTime1.append(row[0])
        DecayCount1.append(row[3])

FreqTime1 = np.array(FreqTime1) 
DecayCount1 = np.array(DecayCount1)

有：

FreqTime1, DecayCount1 = np.loadtxt('Half_Life.csv', delimiter=',', usecols=(0, 3), unpack=True)