import numpy
as np
from mayavi import mlab
#建立数据
x,y = np.mgrid[-
10:
10:200j,-
10:
10:200j]
z =
100*np.sin(x*y)/(x*
y)
#对数据进行可视化
mlab.figure(bgcolor=(
1,
1,
1))
surf = mlab.surf(z,colormap=
"cool") #cool使用冷色系
#更新视图并显示出来
mlab.show()
>>> x,y = np.mgrid[-
10:
10:200j,-
10:
10:200j]
>>> z =
100*np.sin(x*y)/(x*
y) #是一个二维数据
>>>
z
array([[-
0.50636564, -
1.00954046, -
0.57671118, ..., -
0.57671118,
-
1.00954046, -
0.50636564],
[-
1.00954046, -
0.58512546,
0.38643354, ...,
0.38643354,
-
0.58512546, -
1.00954046],
[-
0.57671118,
0.38643354,
1.02032807, ...,
1.02032807,
0.38643354, -
0.57671118],
...,
[-
0.57671118,
0.38643354,
1.02032807, ...,
1.02032807,
0.38643354, -
0.57671118],
[-
1.00954046, -
0.58512546,
0.38643354, ...,
0.38643354,
-
0.58512546, -
1.00954046],
[-
0.50636564, -
1.00954046, -
0.57671118, ..., -
0.57671118,
-
1.00954046, -
0.50636564]])
>>>
import numpy
as np
from mayavi import mlab
#建立数据
x,y = np.mgrid[-
10:
10:200j,-
10:
10:200j]
z =
100*np.sin(x*y)/(x*
y)
#对数据进行可视化
mlab.figure(bgcolor=(
1,
1,
1))
surf = mlab.surf(z,colormap=
"cool")
#访问surf对象的LUT
#LUT是一个255*4的数组,列向量表示RGBA,每个值的范围从0-
255
lut =
surf.module_manager.scalar_lut_manager.lut.table.to_array()
#增加透明度,修改alpha通道
lut[:,-
1] = np.linspace(
0,
255,
256) #修改列向量中A通道
surf.module_manager.scalar_lut_manager.lut.table =
lut
#更新视图并显示出来
mlab.show()
转载于:https://www.cnblogs.com/ssyfj/p/9304331.html
转载请注明原文地址: https://win8.8miu.com/read-7544.html