python - 在 matplotlib 中格式化 3d 条形图

Question

我正在使用这个代码示例

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

data = np.array([
[0,1,0,2,0],
[0,3,0,2,0],
[6,1,1,7,0],
[0,5,0,2,9],
[0,1,0,4,0],
[9,1,3,4,2],
[0,0,2,1,3],
])

column_names = ['a','b','c','d','e']
row_names = ['Mon','Tue','Wed','Thu','Fri','Sat','Sun']

fig = plt.figure()
ax = Axes3D(fig)

lx= len(data[0])            # Work out matrix dimensions
ly= len(data[:,0])
xpos = np.arange(0,lx,1)    # Set up a mesh of positions
ypos = np.arange(0,ly,1)
xpos, ypos = np.meshgrid(xpos+0.25, ypos+0.25)

xpos = xpos.flatten()   # Convert positions to 1D array
ypos = ypos.flatten()
zpos = np.zeros(lx*ly)

dx = 0.5 * np.ones_like(zpos)
dy = dx.copy()
dz = data.flatten()

ax.bar3d(xpos,ypos,zpos, dx, dy, dz, color='b')

#sh()
ax.w_xaxis.set_ticklabels(column_names)
ax.w_yaxis.set_ticklabels(row_names)
ax.set_xlabel('Letter')
ax.set_ylabel('Day')
ax.set_zlabel('Occurrence')

plt.show()

我已经成功地根据我的需要调整它，现在我需要更改每列的颜色以使我的数据更具可读性，如另一个示例所示 http://matplotlib.org/examples/mplot3d/bars3d_demo.html但由于图表是以完全不同的方式构建的，我无法弄清楚如何将一个应用到另一个

Answer 1

基本上，您只需将一组颜色传递给 color=。数组的每个元素都是您的酒吧之一。因此，根据您构建数组的方式，您可以按 列 或 行 对条形进行分组。

例如:

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline

data = np.array([
[0,1,0,2,0],
[0,3,0,2,0],
[6,1,1,7,0],
[0,5,0,2,9],
[0,1,0,4,0],
[9,1,3,4,2],
[0,0,2,1,3],
])

column_names = ['a','b','c','d','e']
row_names = ['Mon','Tue','Wed','Thu','Fri','Sat','Sun']

fig = plt.figure()
ax = Axes3D(fig)

lx= len(data[0])            # Work out matrix dimensions
ly= len(data[:,0])
xpos = np.arange(0,lx,1)    # Set up a mesh of positions
ypos = np.arange(0,ly,1)
xpos, ypos = np.meshgrid(xpos+0.25, ypos+0.25)

xpos = xpos.flatten()   # Convert positions to 1D array
ypos = ypos.flatten()
zpos = np.zeros(lx*ly)

dx = 0.5 * np.ones_like(zpos)
dy = dx.copy()
dz = data.flatten()

cs = ['r', 'g', 'b', 'y', 'c'] * ly

ax.bar3d(xpos,ypos,zpos, dx, dy, dz, color=cs)

#sh()
ax.w_xaxis.set_ticklabels(column_names)
ax.w_yaxis.set_ticklabels(row_names)
ax.set_xlabel('Letter')
ax.set_ylabel('Day')
ax.set_zlabel('Occurrence')

plt.show()