1 | initial version |

A possibility would be to use matplotlib+numpy. For example:

```
import numpy as np
import matplotlib.pyplot as plt
def get_f( n ):
i=np.complex(0,1)
def func(t):
return np.exp(i*t*(1-n))*(1+(np.exp(np.exp(i*t))-1)/(np.exp(2*np.exp(i*t))+1))
return func
def mat_plot():
t = np.arange(0.,2*np.pi,0.01)
for i in range(20):
func = get_f(i)
ft = func(t)
plt.plot(t,np.real(ft))
plt.show()
plt.clf()
```

Takes only 0.5s at SMC (and 234ms on my laptop). Sample output:

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