我知道有与之相关的线程,但我很困惑,我想把自己的数据调整到合适的位置。
我的数据已导入并按此绘制。
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,我不确定如何计算数据集中的参数值。
如果可能的话,我希望将拟合衰减方程的等式与图一起显示。但如果能够产生合身,那么这很容易应用。
修改 --------------------------------------- ----------------------
所以当使用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
我带着此错误消息返回
TypeError: ufunc 'multiply' did not contain a loop with signature matching types dtype('S32') dtype('S32') dtype('S32')
有关如何解决这个问题的想法吗?
答案 0 :(得分:4)
您必须使用scipy.optimize中的curve_fit
: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()
答案 1 :(得分:1)
"我已收到此错误消息
TypeError: ufunc 'multiply' did not contain a loop with signature matching types dtype('S32') dtype('S32') dtype('S32')
关于如何解决此问题的任何想法?"
您读取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)
使用:
FreqTime1, DecayCount1 = np.loadtxt('Half_Life.csv', delimiter=',', usecols=(0, 3), unpack=True)