小编Tim*_*sto的帖子

我正在尝试将2D数据绘制到3D轴上.我使用了3D形状,ax.plot_surface但是我无法使2D数据与轴墙齐平ax.plot.

这是一个精简的示例代码,显示了我对2D数据的问题:

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

# Generate Example Data
x = [0.04,0,-0.04]
y = [0.04,0,-0.04]
z = [0.04,0,-0.04]

# Start plotting environment
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

# Plot 3 lines positioned against the axes "walls"
ax.plot(x,y,-0.08,zdir='z',c='r')
ax.plot(x,z, 0.08,zdir='y',c='g')
ax.plot(y,z,-0.08,zdir='x',c='b')

# Label each axis
ax.set_xlabel('x')
ax.set_ylabel('y')
ax.set_zlabel('z')

# Set each axis limits
ax.set_xlim([-0.08,0.08])
ax.set_ylim([-0.08,0.08]) 
ax.set_zlim([-0.08,0.08]) 

# Equally stretch all axes
ax.set_aspect("equal")

# Set plot size for saving to disk …

我正在尝试在python中使用joblib来加快某些数据处理的速度，但是在尝试确定如何将输出分配为所需格式时遇到了问题。我试图生成一个也许过于简单的代码来显示我所遇到的问题：

from joblib import Parallel, delayed
import numpy as np

def main():
    print "Nested loop array assignment:"
    regular()
    print "Parallel nested loop assignment using a single process:"
    par2(1)
    print "Parallel nested loop assignment using multiple process:"
    par2(2)

def regular():
    # Define variables
    a = [0,1,2,3,4]
    b = [0,1,2,3,4]
    # Set array variable to global and define size and shape
    global ab
    ab = np.zeros((2,np.size(a),np.size(b)))

    # Iterate to populate array
    for i in range(0,np.size(a)):
        for j in range(0,np.size(b)):
            func(i,j,a,b)

    # Show …