python-3.x - Pyvista 曲面图？

Question

我需要一种使用数百万个数据点制作 3 维曲面图的方法，因此我开始检查 pyvista，它应该可以很好地完成这项工作。不过pyvista对我来说有点难掌握。

我有 x,y,z 数据，其中 x 是时间，y 是不同的测量值，z 是这些测量值。我只想让 pyvista 向我展示包含这些信息的曲面图。

例如，如果我在 matplotlib 或其他带有曲面图的库中使用此数组:

X = np.array([1,2,3,4,5,6,7,8,9])
Y = np.array([1,2,3,4,5,6,7,8,9])
X, Y = np.meshgrid(X, Y)
Z = X*Y

我得到这个输出:

但是如果我在任何 pyvista 图上使用相同的数据，我会得到这样的结果:

import sys

# Setting the Qt bindings for QtPy
import os
os.environ["QT_API"] = "pyqt5"

from qtpy import QtWidgets
from qtpy.QtWidgets import QMainWindow

import numpy as np

import pyvista as pv
from pyvistaqt import QtInteractor

import pandas as pd

class MainWindow(QMainWindow):

    def __init__(self, parent=None, show=True):
        QtWidgets.QMainWindow.__init__(self, parent)

        # create the frame
        self.frame = QtWidgets.QFrame()
        vlayout = QtWidgets.QVBoxLayout()

        # add the pyvista interactor object
        self.plotter = QtInteractor(self.frame)
        vlayout.addWidget(self.plotter.interactor)

        self.frame.setLayout(vlayout)
        self.setCentralWidget(self.frame)

        # simple menu to demo functions
        mainMenu = self.menuBar()
        fileMenu = mainMenu.addMenu('File')
        exitButton = QtWidgets.QAction('Exit', self)
        exitButton.setShortcut('Ctrl+Q')
        exitButton.triggered.connect(self.close)
        fileMenu.addAction(exitButton)

        # allow adding a sphere
        meshMenu = mainMenu.addMenu('Mesh')
        self.add_sphere_action = QtWidgets.QAction('Add Sphere', self)
        self.add_sphere_action.triggered.connect(self.add_sphere)
        meshMenu.addAction(self.add_sphere_action)

        x = np.array([9,8,7,6,5,4,3,2,1])
        y = np.array([9,8,7,6,5,4,3,2,1])
        x, y = np.meshgrid(x, y)
        z = x*y
    
        # z[z < -10] = np.nan  # get rid of missing data. pyvista needs you to do this

        i_res = 2  # display every nth point
        j_res = 2  # display every nth point
        self.grid = pv.StructuredGrid(x[::i_res, ::j_res], y[::i_res, ::j_res], z[::i_res, ::j_res])

        self.z = z
        self.x = x
        self.y = y

        self.plotter.add_mesh(self.grid, scalars=self.grid.points[:, 2], lighting=True, specular=0.5, smooth_shading=True,
                              show_scalar_bar=True)

        if show:
            self.show()

    def add_sphere(self): #changing resolution, not adding a sphere
        i_res = 5  # display every nth point
        j_res = 5  # display every nth point
        self.grid = pv.StructuredGrid(self.x[::i_res, ::j_res], self.y[::i_res, ::j_res], self.z[::i_res, ::j_res])
        self.plotter.update()

    
if __name__ == '__main__':
    app = QtWidgets.QApplication(sys.argv)
    window = MainWindow()
    sys.exit(app.exec())

import pyvista as pv
import numpy as np

# Define a simple Gaussian surface
x = np.array([1,2,3,4,5,6,7,8,9])
y = np.array([1,2,3,4,5,6,7,8,9])
x, y = np.meshgrid(x, y)
z = x*y

# Get the points as a 2D NumPy array (N by 3)
points = np.c_[x.reshape(-1), y.reshape(-1), z.reshape(-1)]
points[0:5, :]

# simply pass the numpy points to the PolyData constructor
cloud = pv.PolyData(points)
cloud.plot(point_size=15)

我设法使用这段代码得到了一些不同的东西:

import pandas as pd
import pyvista as pv
import numpy as np

# Load Excel sheet using Pandas
# Note - you may need to `pip install xlrd`
# x = np.array([1,2,3,4,5,6,7,8,9])
# y = np.array([1,2,3,4,5,6,7,8,9])

x = np.array([[1],[2],[3],[4],[5],[6],[7],[8],[9]])
y = np.array([[1],[2],[3],[4],[5],[6],[7],[8],[9]])
# # x, y = np.meshgrid(x, y)
z = x*y

coords = np.hstack((x,y,z))

# Make the structured surface manually
structured = pv.StructuredGrid()
# Set coordinates
structured.points = coords
# Set the dimensions of the structured grid
structured.dimensions = [1, 1, 9]

# Apply an Elevation filter
elevation = structured.elevation()
elevation.plot(show_edges=True, show_grid=True, notebook=False)

但它只提供单串数据。我无法让其他任何东西正常工作。

有谁知道为什么 x、y、z 数据在 pyvista 中做奇怪的事情以及我如何只提供一个正常的曲面图？非常感谢，因为我很困惑。

Answer 1

您的第一个版本是正确的。

PyVista 拥有出色的文档，其中一部分是大量示例。你需要一个叫做 Creating a Structured Surface 的.这最终与您最初展示的代码几乎相同:

import pyvista as pv
import numpy as np

# Define a simple linear surface
x = np.array([1,2,3,4,5,6,7,8,9])
y = np.array([1,2,3,4,5,6,7,8,9])
x, y = np.meshgrid(x, y)
z = x*y

# Create and plot structured grid
grid = pv.StructuredGrid(x, y, z)
plotter = pv.Plotter()
plotter.add_mesh(grid, scalars=grid.points[:, -1], show_edges=True,
                 scalar_bar_args={'vertical': True})
plotter.show_grid()
plotter.show()

这是(正确的!)输出:

这看起来不同的原因是 matplotlib 不是 3d 可视化工具(事实上，它的 3d 工具臭名昭著地使用 2d 渲染器，这会导致奇怪的怪癖)。另一方面，PyVista 旨在可视化空间引用数据。如果您的 x 从 1 变为 9 而您的 z 从 1 变为 81 那么为什么它会挤压 z 轴？如果沿每个坐标轴设置 1:1:1 的纵横比，PyVista 显示的就是事实。

如果您不想要这个，您可以自行扩展:

import pyvista as pv
import numpy as np

# Define a simple linear surface
x = np.array([1,2,3,4,5,6,7,8,9])
y = np.array([1,2,3,4,5,6,7,8,9])
x, y = np.meshgrid(x, y)
z = x*y

# Create and plot structured grid
grid = pv.StructuredGrid(x, y, z)
plotter = pv.Plotter()
plotter.add_mesh(grid, scalars=grid.points[:, -1], show_edges=True,
                 scalar_bar_args={'vertical': True})
plotter.show_grid()
# scale plot to enforce 1:1:1 aspect ratio
plotter.set_scale(xscale=1, yscale=x.ptp()/y.ptp(), zscale=x.ptp()/z.ptp())
plotter.show()

如果您希望 PyVista 对您的数据撒谎，您必须告诉它这样做。