python 拟合logistics曲线
时间: 2023-10-21 07:06:54 浏览: 56
要拟合logistics曲线,可以使用Python中的scipy.optimize.curve_fit函数。首先,需要导入必要的库:
```python
import numpy as np
from scipy.optimize import curve_fit
import matplotlib.pyplot as plt
```
然后,定义logistics函数:
```python
def logistics(x, a, b, c):
return c / (1 + np.exp(-a * (x - b)))
```
其中,a、b、c是需要拟合的参数。
接下来,准备数据并调用curve_fit函数进行拟合:
```python
# 准备数据
xdata = np.array([1, 2, 3, 4, 5])
ydata = np.array([0.1, 0.5, 0.9, 0.95, 0.99])
# 调用curve_fit函数进行拟合
popt, pcov = curve_fit(logistics, xdata, ydata)
```
最后,绘制拟合曲线:
```python
# 绘制原始数据
plt.plot(xdata, ydata, 'ko', label='Original Data')
# 绘制拟合曲线
x = np.linspace(0, 6, 100)
y = logistics(x, *popt)
plt.plot(x, y, 'r-', label='Fitted Curve')
plt.legend()
plt.show()
```