介绍
Mayavi是一款3D科学数据可视化Python库,其简单易用,可视化功能非常强大,能够满足我们对各种数据的可视化需求。
学习资源
官网:https://docs.enthought.com/mayavi/mayavi/
mlab模块参考手册:https://docs.enthought.com/mayavi/mayavi/auto/mlab_reference.html#mlab-reference
https://wizardforcel.gitbooks.io/hyry-studio-scipy/content/9.html
安装
可以使用pip直接进行安装:
pip install PyQt5 vtk
pip install mayavi
我曾经成功的版本:
pip install PyQt5==5.15.2 vtk==8.1.0
pip install mayavi==4.7.1
这种安装讲道理是官方推荐的安装方法,但是容易出现以下问题:
Building wheel for mayavi (setup.py) ... error
Running setup.py install for mayavi ... error
此时可以采用源码安装方案:
git clone https://github.com/enthought/mayavi.git
cd mayavi
pip install -r requirements.txt
pip install PyQt5
python setup.py install
验证安装:
终端直接执行mayavi2
,出现如下界面则说明安装成功:
mayavi.mlab为脚本中绘图包:
https://docs.enthought.com/mayavi/mayavi/mlab.html#simple-scripting-with-mlab
所有函数索引为:
https://docs.enthought.com/mayavi/mayavi/auto/mlab_reference.html#mlab-reference
import numpy as np
import mayavi.mlab as mlab
try:
raw_input # Python 2
except NameError:
raw_input = input # Python 3
fig = mlab.figure(
figure=None, bgcolor=(0, 0, 0), fgcolor=None, engine=None, size=(1000, 500))
fov = np.array(
[[20.0, 20.0, 0.0, 0.0], [20.0, -20.0, 0.0, 0.0]], dtype=np.float64 # 45 degree
)
def load_velo_scan(velo_filename, dtype=np.float32, n_vec=4):
scan = np.fromfile(velo_filename, dtype=dtype)
scan = scan.reshape((-1, n_vec))
return scan
pc = load_velo_scan('/media/zhanghm/Data/Datasets/KITTI/tracking/training/velodyne/0019/000000.bin')
print(pc.shape)
s = np.full((pc.shape[0], ), 2)
mlab.points3d(
pc[:, 0],
pc[:, 1],
pc[:, 2],
mode='point',
color=(1,0,1),
#colormap="gnuplot",
colormap="copper",
scale_factor=10,
figure=fig)
input_str = raw_input()
mlab.points3d(
pc[:, 0],
pc[:, 1],
pc[:, 2],
color=(1,0,1),
colormap="gnuplot",
scale_factor=0.01,
figure=fig)
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