使用新标量更新PyVista绘图仪

Question

尝试使用新标量更新格网数据时，我无法更新图

我也已经向PyVista支持部门报告了这些问题：https://github.com/pyvista/pyvista-support/issues/501

通过使用以下示例，我可以进行图形更新：https://github.com/pyvista/pyvista-support/issues/68

不过，我的例子不起作用。

示例代码如下：

import pyvista as pv
import pyvistaqt as pvqt
import numpy as np
import time

cmap='viridis'    
nx,ny,nz = 60, 40, 42
nc = nx*ny*nz

np.random.seed(0)
inidata = np.random.randint(1, 100, nc)

# generate random data for updating
data = [np.random.randint(1, 1000, nc), 
        np.random.randint(1, 1e4, nc),
        np.random.randint(1, 1e5, nc),
        np.random.randint(1, 1e6, nc)]

gridata = np.ones((nx,ny,nz))

mesh = pv.UniformGrid()
mesh.dimensions = np.array(gridata.shape) + 1 


mesh.origin = (0, 0, 0)  # The bottom left corner of the data set
mesh.spacing = (30, 30, 2.5)  # These are the cell sizes along each axis

mesh.cell_arrays["Data"] = inidata

plotter = pvqt.BackgroundPlotter()

# Add slices
xslice = mesh.slice(normal='x')
yslice = mesh.slice(normal='y')
zslice = mesh.slice(normal='z')
rslice = mesh.slice(normal=[1,1,0])

# Plot
plotter.add_mesh(mesh.outline(), color="k")
plotter.add_mesh(xslice, cmap=cmap)
plotter.add_mesh(yslice, cmap=cmap)
plotter.add_mesh(zslice, cmap=cmap)
plotter.add_mesh(rslice, cmap=cmap)

def update():
    for dat in data:
        plotter.update_scalars(dat, mesh=mesh)
        time.sleep(1)
        plotter.update()
        
plotter.add_callback(update, interval=100)

Answer 1

PyVista允许通过为加载的网格设置新标量来更新场景。为此，应将新数据传递给绘图仪：

import numpy as np
import pyvista as pv

# Creating random data
N = 100
data = np.zeros((1, N, N))
data[:] = np.random.randint(0, 10000, data.shape)

# Creating a mesh from our data
g = pv.UniformGrid()
g.dimensions = np.array(data.shape) + 1
g.spacing = (10, 10, 10)
g.cell_data['data'] = data.flatten()
#Careful with threshold as it will turn your data into UnstructuredGrid
#g = g.threshold([0.0001, int(data.max())])

# Creating scene and loading the mesh
p = pv.Plotter()
p.add_mesh(g, opacity=0.5, name='data', cmap='gist_ncar')
p.show(interactive_update=True)

# Animation
for i in range(5, 1000):
    # Updating our data
    data[:] = np.random.randint(0, 10000, data.shape)
    # Updating scalars
    p.update_scalars(data.flatten())
    #p.mesh['data'] = data.flatten() # setting data to the specified mesh is also possible
    # Redrawing
    p.update()

但是，数据的形状(本质上是单元格或点的数量)必须保持不变。这意味着如果数据数组大小改变，或者通过阈值过滤的数据改变了它的单元格数量，加载的网格将拒绝它。

解决方法基本上是在每次更新数据时将新网格加载到绘图仪中。

将#Animation部分与此代码片段交换，平面将增加一些体积：

# Animation
for i in range(5, 1000):
    # Updating our data
    data = np.full((i, N, N),0)
    data[:] = np.random.randint(0,1000000, data.shape)
    
    # Recreating the mesh
    g = pv.UniformGrid()
    g.dimensions = np.array(data.shape) + 1
    g.spacing = (10, 10, 10)
    g.cell_data['data'] = data.flatten()

    # Reloading the mesh to the scene
    p.clear()
    p.add_mesh(g, opacity=0.5, name='data')

    # Redrawing
    p.update()

请注意，场景只有在更新时才是交互式的，因此降低更新频率会使场景变得非常滞后

Answer 2

在我看来，我们应该将#"Add Slices“和"#Plot”的部分放在函数update()中以刷新切片。

但是，如果数据范围小于scalar_bar_range，即使我们通过plotter.update_scalar_bar_range强制更新，scalar_bar_range也不会更新。

因此，我们必须手动刷新scalar_bar_range。

def update():
    for dat in data:
        # Add slices
        xslice = mesh.slice(normal='x')
        yslice = mesh.slice(normal='y')
        zslice = mesh.slice(normal='z')
        rslice = mesh.slice(normal=[1,1,0])

        # Plot
        plotter.add_mesh(mesh.outline(), color="k")
        plotter.add_mesh(xslice, cmap=cmap)
        plotter.add_mesh(yslice, cmap=cmap)
        plotter.add_mesh(zslice, cmap=cmap)
        plotter.add_mesh(rslice, cmap=cmap)
        time.sleep(1)
    plotter.scalar_bars._scalar_bar_ranges = {mesh.active_scalars_name: [0, 0]}