Pyvista surface plot? - python-3.x

Question

I need a way to make a 3-dimensional surface plot using millions of datapoints, so I began checking into pyvista which is supposed to do this well.
However, pyvista is a bit difficult for me to grasp.
I have x,y,z data where x is time, y is different measurements, and z is the values for those measurements.
All I want is for pyvista to show me a surface plot with this information.
For example, if I use this array in matplotlib or other libraries with surface plots:
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
I get this output:
But if I use the same data on any of the pyvista plots, I get something like this:
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)
I managed to get "something" different using this bit of code:
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)
But it only provides a single string of data. I haven't been able to get anything else work properly.
Does anyone know why the x,y,z data is doing weird things in pyvista and how I can provide just a normal surface plot? It would be much appreciated, as I am pretty stumped.

Answer 1

Your first version is correct.
PyVista has excellent documentation, part of which is an extensive collection of examples. You need the one that's called Creating a Structured Surface. This ends up being pretty much the same code as what you originally showed:
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()
Here is the (correct!) output:
The reason why this looks different is that matplotlib isn't a 3d visualization tool (in fact its 3d tooling infamously uses a 2d renderer that leads to weird quirks). PyVista on the other hand is designed to visualize spatially referenced data. If your x goes from 1 to 9 and your z goes from 1 to 81 then why would it squash the z axis? What PyVista shows is the truth if you set a 1:1:1 aspect ratio along each coordinate axis.
If you don't want this, you can mess with scaling yourself:
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()
If you want PyVista to lie about your data, you have to tell it to do so.