ここでは、Pythonのmatplotlibライブラリを使ってベジェ曲線を視覚化する基本的なスクリプトを紹介する：

```python
import numpy as np
import matplotlib.pyplot as plt

def bezier_curve(control_points, num_points=100):
    t = np.linspace(0, 1, num_points)
    curve = np.zeros((num_points, 2))
    for i in range(num_points):
        curve[i] = (1-t[i])**3 * control_points[0] + 3*(1-t[i])**2 * t[i] * control_points[1] + 3*(1-t[i]) * t[i]**2 * control_points[2] + t[i]**3 * control_points[3]
    return curve

control_points = np.array([[0, 0], [0, 1], [1, 1], [1, 0]])
curve = bezier_curve(control_points)
plt.plot(curve[:, 0], curve[:, 1], '-')
plt.plot(control_points[:, 0], control_points[:, 1], 'ro')
plt.show()
```

このスクリプトでは、bezier_curve関数が制御点のセットと曲線を評価する点の数を受け取ります。曲線は、制御点の加重和であるベジェ曲線公式を用いて生成される。そして、曲線点と制御点がmatplotlibライブラリを使ってプロットされる。
Here is a basic script for visualizing a Bezier curve using the matplotlib library in Python:

```python
import numpy as np
import matplotlib.pyplot as plt

def bezier_curve(control_points, num_points=100):
    t = np.linspace(0, 1, num_points)
    curve = np.zeros((num_points, 2))
    for i in range(num_points):
        curve[i] = (1-t[i])**3 * control_points[0] + 3*(1-t[i])**2 * t[i] * control_points[1] + 3*(1-t[i]) * t[i]**2 * control_points[2] + t[i]**3 * control_points[3]
    return curve

control_points = np.array([[0, 0], [0, 1], [1, 1], [1, 0]])
curve = bezier_curve(control_points)
plt.plot(curve[:, 0], curve[:, 1], '-')
plt.plot(control_points[:, 0], control_points[:, 1], 'ro')
plt.show()
```

In this script, the bezier_curve function takes a set of control points and the number of points to evaluate the curve at. The curve is generated using the Bezier curve formula, which is a weighted sum of the control points. The curve points and the control points are then plotted using the matplotlib library.