如何在python中绘制多个回归3D图

Question

我不是科学家,所以请假设我不知道有经验的程序员的行话,或者科学绘图技术的复杂性.Python是我所知道的唯一语言(初学者+,可能是中级).

任务:将多元回归的结果(z = f(x,y))绘制为3D图形上的二维平面(例如,我可以使用OSX的图形工具,或者在此处使用R 绘制回归曲面) .

经过一周搜索Stackoverflow并阅读matplotlib,seaborn和mayavi的各种文档后,我终于找到了最简单的方法来绘制3d表面给出的3d点,听起来很有希望.所以这是我的数据和代码:

首先尝试使用matplotlib:

shape: (80, 3) 
type: <type 'numpy.ndarray'> 
zmul: 

[[  0.00000000e+00   0.00000000e+00   5.52720000e+00]
 [  5.00000000e+02   5.00000000e-01   5.59220000e+00]
 [  1.00000000e+03   1.00000000e+00   5.65720000e+00]
 [  1.50000000e+03   1.50000000e+00   5.72220000e+00]
 [  2.00000000e+03   2.00000000e+00   5.78720000e+00]
 [  2.50000000e+03   2.50000000e+00   5.85220000e+00]
 ……]

import matplotlib
from matplotlib.ticker import MaxNLocator
from matplotlib import cm

from numpy.random import randn
from scipy import array, newaxis
Xs = zmul[:,0]
Ys = zmul[:,1]
Zs = zmul[:,2]


surf = ax.plot_trisurf(Xs, Ys, Zs, cmap=cm.jet, linewidth=0)
fig.colorbar(surf)

ax.xaxis.set_major_locator(MaxNLocator(5))
ax.yaxis.set_major_locator(MaxNLocator(6))
ax.zaxis.set_major_locator(MaxNLocator(5))

fig.tight_layout()

plt.show()

我得到的是一个空的3D坐标框架,其中包含以下错误消息:

RuntimeError:qhull Delaunay三角测量计算中的错误:奇异输入数据(exitcode = 2); 使用python verbose选项(-v)来查看原始的qhull错误.

我试着看看我是否可以使用绘图参数并检查这个网站http://www.qhull.org/html/qh-impre.htm#delaunay,但我真的无法理解我应该做什么.

第二次尝试使用mayavi:

相同的数据,分为3个numpy数组:

type: <type 'numpy.ndarray'> 
X: [    0   500  1000  1500  2000  2500  3000 ….]

type: <type 'numpy.ndarray'> 
Y: [  0.    0.5   1.    1.5   2.    2.5   3.  ….]

type: <type 'numpy.ndarray'> 
Z: [  5.5272   5.5922   5.6572   5.7222   5.7872   5.8522   5.9172  ….] 

码:

from mayavi import mlab
def multiple3_triple(tpl_lst):

X = xs
Y = ys
Z = zs


# Define the points in 3D space
# including color code based on Z coordinate.
pts = mlab.points3d(X, Y, Z, Z)

# Triangulate based on X, Y with Delaunay 2D algorithm.
# Save resulting triangulation.
mesh = mlab.pipeline.delaunay2d(pts)

# Remove the point representation from the plot
pts.remove()

# Draw a surface based on the triangulation
surf = mlab.pipeline.surface(mesh)

# Simple plot.
mlab.xlabel("x")
mlab.ylabel("y")
mlab.zlabel("z")
mlab.show()

我得到的就是:

如果这很重要,我在OSX 10.9.3上使用64位版本的Enthought's Canopy

对于我做错了什么的输入,将不胜感激.

编辑:发布有效的最终代码,以防有人帮助.

'''After the usual imports'''
def multiple3(tpl_lst):
    mul = []
    for tpl in tpl_lst:
        calc = (.0001*tpl[0]) + (.017*tpl[1])+ 6.166
        mul.append(calc)
    return mul

fig = plt.figure()
ax = fig.gca(projection='3d')
'''some skipped code for the scatterplot'''
X = np.arange(0, 40000, 500)
Y = np.arange(0, 40, .5)
X, Y = np.meshgrid(X, Y)
Z = multiple3(zip(X,Y))

surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1,cmap=cm.autumn,
                       linewidth=0, antialiased=False, alpha =.1)
ax.set_zlim(1.01, 11.01)
ax.set_xlabel(' x = IPP')
ax.set_ylabel('y = UNRP20')
ax.set_zlabel('z = DI')

ax.zaxis.set_major_locator(LinearLocator(10))
ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))
fig.colorbar(surf, shrink=0.5, aspect=5)
plt.show()

Answer 1

对于 matplotlib，您可以基于表面示例（缺少 plt.meshgrid）：

from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
import matplotlib.pyplot as plt
import numpy as np

fig = plt.figure()
ax = fig.gca(projection='3d')
X = np.arange(-5, 5, 0.25)
Y = np.arange(-5, 5, 0.25)
X, Y = np.meshgrid(X, Y)
R = np.sqrt(X**2 + Y**2)
Z = np.sin(R)
surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.coolwarm,
                       linewidth=0, antialiased=False)
ax.set_zlim(-1.01, 1.01)

ax.zaxis.set_major_locator(LinearLocator(10))
ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))

fig.colorbar(surf, shrink=0.5, aspect=5)

plt.show()