```python
import numpy as np
import matplotlib.pyplot as plt
from scipy import integrate
import sympy as sm
```


```python
def dxdt(x,t):
    return np.sin(x)

u = np.linspace(-10, 10,25)

soln=integrate.odeint(dxdt,y0=[1],t=u)
soln2=integrate.odeint(dxdt,y0=[np.pi],t=u)
plt.plot(soln)
plt.plot(soln2)
```


```python
#Find stable fixed points and classify their stability
x = sm.symbols("x")

# differential equations
B = x**2-1
# use sympy's way of setting equations to zero
BEqual = sm.Eq(B, 0)

# compute equilibria (fixed points, extrema)
fp = sm.solve(BEqual,x)
print('The equilibria of this system are %s' %fp)
```

    The equilibria of this system are [-1, 1]


73970e1a3e63bf22fcf04026117727c6199219cc
ipynb
Jupyter Notebook
StrogatzBook/Chapter1.ipynb
mariakesa/ComputationalCalculus
9e6c1e636878171b613156b094e557c01814ebea
MIT
StrogatzBook/Chapter1.ipynb
mariakesa/ComputationalCalculus
9e6c1e636878171b613156b094e557c01814ebea
MIT
StrogatzBook/Chapter1.ipynb
mariakesa/ComputationalCalculus
9e6c1e636878171b613156b094e557c01814ebea
MIT
Qwen/Qwen-72B
1. YES
2. YES