I’m curious how one could solve the following physics problem with Python and Matplotlib.

In a class room a lighting meter was used to measure the illuminance E at the distance r. The data is as follows

E (lx), r (m)

663, 1

158, 2

71, 3

42, 4

19, 6

11, 8

Plot a curve that shows how the illuminance depends on the distance and the given points are made on bigger in the plot. My effort is as follows:

```
import numpy as np
from scipy.optimize import curve_fit
import matplotlib.pyplot as plt
x = np.array([1, 2, 3, 4, 6, 8])
y = np.array([660, 160, 72, 42, 20, 10])
def fit_func(x, a, b, c):
return a/(b*x**2 + c)
def connectpoints(x, y, p1, p2):
x1, x2 = x[p1], x[p2]
y1, y2 = y[p1], y[p2]
plt.plot([x1, x2], [y1, y2], 'k-')
xmin = 1
xmax = 9
params = curve_fit(fit_func, x, y)
[a, b, c] = params[0]
y = []
numpoints = 100
for i in range(numpoints):
y.append(a/(b*(i/numpoints*(xmax-xmin))**2+c))
x=[]
for i in range(numpoints):
x.append(i/numpoints*(xmax-xmin))
plt.plot(x, y, 'ro')
for i in range(0,len(x)-1):
if y[i] >0:
connectpoints(x, y, i, i+1)
plt.xlim([xmin, xmax])
plt.ylim([0, 600])
plt.show()
```

But this shows hundred data points in the plot. Is it possible to make those extra points invisible such that the plot will contain only six data points and a best-fit curve between them?