numpy 在绘制两个不等式的相交面积时，Delaunay三角剖分的构造不正确

kkbh8khc 于 2023-06-06 发布在其他

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在使用NumPy、Matplotlib、SymPy和SciPy库的代码中，有一个名为plot_inequalities的函数，用于使用Delaunay三角剖分绘制两个不等式的相交区域。然而，当运行代码时，Delaunay三角剖分没有正确构建。下面是代码：

import numpy as np
import matplotlib.pyplot as plt
from sympy import *
from scipy.spatial import Delaunay

def plot_inequalities(inequality1, inequality2, x_min, x_max, y_min, y_max):
x, y = symbols('x y')
try:
inequality1_expr = sympify(inequality1)
inequality2_expr = sympify(inequality2)
except:
    print("Error: Incorrect inequality format.")
    return

try:
    F1 = lambdify((x, y), inequality1_expr, 'numpy')
    F2 = lambdify((x, y), inequality2_expr, 'numpy')
except:
    print("Error: Failed to compile inequalities.")
    return

# Create grid of x and y values
x_vals = np.concatenate(([0], np.linspace(x_min, x_max, 400)))
y_vals = np.linspace(y_min, y_max, 400)
X, Y = np.meshgrid(x_vals, y_vals)
# Check inequalities at each grid point
inequality1_result = F1(X, Y)
inequality2_result = F2(X, Y)

# Find intersection points of the inequalities
intersection_points = []
for i in range(len(x_vals)):
    for j in range(len(y_vals)):
        if inequality1_result[j, i] < 0 and inequality2_result[j, i] > 0:
            intersection_points.append([x_vals[i], y_vals[j]])

intersection_points = np.array(intersection_points)

# Delaunay triangulation of intersection points
if len(intersection_points) >= 3:
    tri = Delaunay(intersection_points[:, :2])

    # Plot the graph
    plt.triplot(intersection_points[:, 0], intersection_points[:, 1], tri.simplices.copy(), color='black')

# Display the graph
plt.xlabel('x')
plt.ylabel('y')
plt.grid(False)
plt.axis('equal')
plt.xlim(x_min, x_max)
plt.ylim(y_min, y_max)
plt.show()
print("Enter the lower inequality in the format 'F(x, y) > 0':")
inequality1 = input()
print("Enter the upper inequality in the format 'F(x, y) < 0':")
inequality2 = input()
print("Enter the x interval boundaries in the format 'x_min, x_max':")
x_min, x_max = map(float, input().split(','))
print("Enter the y interval boundaries in the format 'y_min, y_max':")
y_min, y_max = map(float, input().split(','))

plot_inequalities(inequality1, inequality2, x_min, x_max, y_min, y_max)

示例区域：y-x>0且y-x**2<0

numpy

来源：https://stackoverflow.com/questions/76401637/delaunay-triangulation-is-not-correctly-constructed-when-plotting-the-intersecti

1条答案

按热度按时间

pcww981p1#

plot_inequalities函数的问题是没有正确过滤intersection_points数组以删除重复点。当intersection_points数组包含重复点时，无法正确构建Delaunay三角剖分。要解决此问题，可以在构建Delaunay三角剖分之前添加一个检查，以从intersection_points阵列中删除重复点。
下面是更新的代码：

import numpy as np
import matplotlib.pyplot as plt
from sympy import *
from scipy.spatial import Delaunay
from matplotlib.collections import PolyCollection

def plot_inequalities(inequality1, inequality2, x_min, x_max, y_min, y_max):
    x, y = symbols('x y')
    try:
        inequality1_expr = sympify(inequality1)
        inequality2_expr = sympify(inequality2)
    except:
        print("Error: Incorrect inequality format.")
        return

    try:
        F1 = lambdify((x, y), inequality1_expr, 'numpy')
        F2 = lambdify((x, y), inequality2_expr, 'numpy')
    except:
        print("Error: Failed to compile inequalities.")
        return

    # Create grid of x and y values
    x_vals, y_vals = np.meshgrid(np.linspace(x_min, x_max, 150), np.linspace(y_min, y_max, 400))
    
    # Check inequalities on grid points
    indices = np.where((F1(x_vals, y_vals) < 0) & (F2(x_vals, y_vals) > 0))
    intersection_points = np.column_stack((x_vals[indices], y_vals[indices]))

    # Remove any duplicate points
    intersection_points = np.unique(intersection_points, axis=0)

    # Delaunay triangulation of intersection points
    if len(intersection_points) >= 3:
        tri = Delaunay(intersection_points)

        # Plot the graph
        polys = PolyCollection(intersection_points[tri.simplices], facecolors='none', edgecolors='black')
        fig, ax = plt.subplots()
        ax.add_collection(polys)
        ax.autoscale()
        ax.margins(0.1)
        ax.set_xlabel('x')
        ax.set_ylabel('y')
        ax.set_aspect('equal')
        plt.show()

print("Enter the lower inequality in the format 'F(x, y) > 0':")
inequality1 = "y - x "
print("Enter the upper inequality in the format 'F(x, y) < 0':")
inequality2 = "y - x**2 "
print("Enter the x interval boundaries in the format 'x_min, x_max':")
x_min, x_max = map(float, "0,4".split(','))
print("Enter the y interval boundaries in the format 'y_min, y_max':")
y_min, y_max = map(float, "0,4".split(','))

plot_inequalities(inequality1, inequality2, x_min, x_max, y_min, y_max)

通过这种修改，intersection_points数组首先被转换为numpy数组，然后使用unique函数进行过滤以删除任何重复点。然后使用得到的intersection_points数组来构造Delaunay三角剖分，并绘制两个不等式的相交区域。

**P.S.**我在代码中硬编码了不等式。您可以通过更改np.linspace(x_min, x_max, 150)和np.linspace(y_min, y_max, 400)中的点数来更改x_vals和y_vals的数量，以查看三角剖分。

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numpy 在绘制两个不等式的相交面积时，Delaunay三角剖分的构造不正确

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