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import matplotlib.pyplot as plt
import numpy as np
def calculate_area(x, y):
return np.sqrt(x**2 + y**2) + 2/3 * np.sqrt(x**2 + (5/6 - y)**2)
def generate_points(num_points):
points = np.random.rand(num_points, 2) * 2 - 1 # Generate random points in the range [-1, 1]
return points
def main():
num_points = 1000000
points = generate_points(num_points)
correct_points = points[np.where(calculate_area(points[:, 0], points[:, 1]) <= 1)]
incorrect_points = points[np.where(calculate_area(points[:, 0], points[:, 1]) > 1)]
areas = []
for i in range(1, num_points + 1):
current_correct_points = correct_points[:i]
current_area = 4 * len(current_correct_points) / i # Area estimation using the ratio of correct points
areas.append(current_area)
if i % 1000 == 0:
print("Area after {i} points: {current_area:.2f}")
# Print final result
final_area = areas[-1]
print("The area of the Twitter egg is {final_area:.2f}")
# Plot the distribution of correct and incorrect points
plt.scatter(correct_points[:, 0], correct_points[:, 1], color='blue', s=1, label='Correct Points')
plt.scatter(incorrect_points[:, 0], incorrect_points[:, 1], color='red', s=1, label='Incorrect Points')
# Display the area in the graph
plt.title('Distribution of Points\nFinal Area Estimate: {final_area:.2f}')
plt.legend()
plt.show()
if __name__ == "__main__":
main()
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