我想要符合以下数据:
x(time) y(data)
0.75; 19.33
1; 19.04
1.25; 17.21
1.5; 12.98
1.75; 11.59
2; 9.26
2.25; 7.66
2.5; 6.59
2.75; 5.68
3; 5.1
3.25; 4.36
3.5; 4.43
3.75; 3.58
4; 3.01
4.25; 3.24
4.5; 3.58
4.75; 3.13
5; 3.88
5.25; 3.19
5.5; 3.58
5.75; 3.64
使用以下代码:
#read text file
data = pd.read_table('episode_5_prova.txt', sep='\t')
#DataFrame
df = pd.DataFrame(data)
#Define your function
def func(x, a, b, c, d, e):
return a*np.exp(-b*x) + c*np.exp(-d*x) + e
#convert dataframe into numpy array
df0=df['time']
x=df0.as_matrix()
df1=df['bi']
y=df1.as_matrix()
# Using the python scipy function curve_fit with function and input variables
popt, pcov = curve_fit(func, x, y)
a, b, c, d, e= popt
fit = func(x, a, b, c, d, e)
fig, ax = plt.subplots()
ax.plot(x, fit, color='r', lw=3)
ax.plot(x, y,'g.')
observed_values=scipy.array(y)
expected_values=scipy.array(fit)
plt.xlim(0,25)
plt.ylim(0,20)
print(a,b,c,d,e)
print(scipy.stats.chisquare(observed_values, f_exp=expected_values, ddof=3))
plt.show()
我获得了以下情节:first fit但是,出于我的工作目的,我需要将我的参数b和c修复为:b = 0.000431062,d = 0.000580525但是我没有得到如下拟合:second fit
有没有人有建议?谢谢