PyVista NaN 不透明度错误？

Question

以下代码：

import pyvista as pv
import numpy as np

def test_pyvista_layers():
    """Test how PyVista handles multiple mesh layers with NaN values and opacity settings"""
    
    # Create a simple sphere
    sphere = pv.Sphere(radius=1.0)
    total_points = sphere.n_points
    
    # Create three meshes with known patterns
    mesh1 = sphere.copy()
    mesh2 = sphere.copy()
    mesh3 = sphere.copy()
    
    # Test 1: Basic overlap with different values and NaN
    values1 = np.full(total_points, np.nan)  # Initialize with NaN
    values1[:total_points//3] = 1  # Set first third to 1
    
    values2 = np.full(total_points, np.nan)  # Initialize with NaN
    values2[total_points//3:2*total_points//3] = 2  # Set middle third to 2
    
    values3 = np.full(total_points, np.nan)  # Initialize with NaN
    values3[2*total_points//3:] = 3  # Set final third to 3
    
    # Validate NaN counts and non-overlap
    nan_count1 = np.sum(np.isnan(values1))
    nan_count2 = np.sum(np.isnan(values2))
    nan_count3 = np.sum(np.isnan(values3))
    
    print(f"\nNaN Counts:")
    print(f"Layer 1: {nan_count1} NaN values ({(nan_count1/total_points)*100:.1f}% of points)")
    print(f"Layer 2: {nan_count2} NaN values ({(nan_count2/total_points)*100:.1f}% of points)")
    print(f"Layer 3: {nan_count3} NaN values ({(nan_count3/total_points)*100:.1f}% of points)")
    
    # Check for overlap between non-NaN regions
    overlap_12 = np.sum(~np.isnan(values1) & ~np.isnan(values2))
    overlap_23 = np.sum(~np.isnan(values2) & ~np.isnan(values3))
    overlap_13 = np.sum(~np.isnan(values1) & ~np.isnan(values3))
    
    print("\nOverlap Check:")
    print(f"Overlap between layers 1-2: {overlap_12} points")
    print(f"Overlap between layers 2-3: {overlap_23} points")
    print(f"Overlap between layers 1-3: {overlap_13} points")
    
    # Validate complete coverage
    total_coverage = np.sum(~np.isnan(values1) | ~np.isnan(values2) | ~np.isnan(values3))
    print(f"\nTotal Coverage: {total_coverage} points ({(total_coverage/total_points)*100:.1f}% of surface)")
    
    plotter = pv.Plotter()
    
    # Add meshes with point data and NaN handling
    mesh1.point_data['values'] = values1
    mesh2.point_data['values'] = values2
    mesh3.point_data['values'] = values3
    
    # Add meshes with nan_opacity=0 to make NaN values completely transparent
    plotter.add_mesh(mesh1, color='red', opacity=1.0, label='Layer 1', nan_opacity=0.0)
    plotter.add_mesh(mesh2, color='blue', opacity=1.0, label='Layer 2', nan_opacity=0.0)
    plotter.add_mesh(mesh3, color='green', opacity=1.0, label='Layer 3', nan_opacity=0.0)
    
    return plotter

test_plotter = test_pyvista_layers()
test_plotter.show()

生成附加图像（绿色球体）而不是预期的三部分球体。我的理解是 nan_opacity=0.0 应该使球体的其余部分透明??

图形输出

它还会打印以下输出，确认这些点确实是 NaN。

NaN 计数： 第 1 层：562 个 NaN 值（66.7% 的点） 第 2 层：561 个 NaN 值（占点的 66.6%） 第 3 层：561 个 NaN 值（66.6% 的点）

重叠检查： 第 1-2 层之间的重叠：0 分 第 2-3 层之间的重叠：0 分 第 1-3 层之间的重叠：0 分

总覆盖范围：842 点（表面的 100.0%）

我尝试了许多不同的方法来呈现它，并浏览了文档，但没有任何效果。有关如何处理此问题的建议表示赞赏！

Answer 1

问题是您为网格请求特定的颜色，这会覆盖每个网格上的任何标量，这反过来会影响映射（有效地禁用任何依赖于标量的内容）。您可以尝试将

show_scalar_bar=True

传递给

add_mesh()

并看到它没有执行任何操作。

最简单的解决方案是使用 颜色图 与您想要作为分类数据的颜色相匹配：

cmap = ['red', 'blue', 'green']                                     
plotter.add_mesh(mesh1, label='Layer 1', nan_opacity=0.0, cmap=cmap)
plotter.add_mesh(mesh2, label='Layer 2', nan_opacity=0.0, cmap=cmap)
plotter.add_mesh(mesh3, label='Layer 3', nan_opacity=0.0, cmap=cmap)

请注意，我删除了默认的

opacity=1.0

和

color=...

，它允许每个网格上的标量显现。

结果如下：

唯一奇怪的是这些碎片现在是半透明的。我不知道为什么会发生这种情况。这似乎是纳米不透明度的副作用，因为将其更改为 1.0 也会使网格的其余部分变得不透明。也许这是一个错误。