如何在matplotlib中的3d条形上绘制渐变填充 [英] how to plot gradient fill on the 3d bars in matplotlib

问题描述

现在，在(x，y)的3d栏中绘制了一些统计信息.每个条形高度代表(x，y)平面方格侧面的点的密度.现在，我可以在每个栏上放置不同的颜色.但是，我想在3d栏上添加渐进式颜色，类似于cmap，因此该栏将根据密度进行渐变填充.

Right now there're some statistics plotted in 3d bar over (x, y). each bar height represents the density of the points in side the square grid of (x,y) plane. Right now, i can put different color on each bar. However, I want to put progressive color on the 3d bar, similar as the cmap, so the bar will be gradient filled depending on the density.

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

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

# height of the bars
z = np.ones((4, 4)) * np.arange(4)
# position of the bars
xpos, ypos = np.meshgrid(np.arange(4), np.arange(4))

xpos = xpos.flatten('F')

ypos = ypos.flatten('F')

zpos = np.zeros_like(xpos)


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

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

plt.show()

输出上面的代码:

推荐答案

首先让我说说，对于复杂的3D图，matplotlib可能不是首选工具.

Let me first say that matplotlib may not be the tool of choice when it comes to sophisticated 3D plots.

也就是说，没有内置的方法可以在条形图的整个范围内生成具有不同颜色的条形图.

That said, there is no built-in method to produce bar plots with differing colors over the extend of the bar.

因此，我们需要以某种方式模仿标准.可能的解决方案可以在下面找到.在这里，我们使用 plot_surface 图来创建包含以下内容的条形图渐变.

We therefore need to mimic the bar somehow. A possible solution can be found below. Here, we use a plot_surface plot to create a bar that contains a gradient.

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

fig = plt.figure()
ax = fig.add_subplot(111, projection= Axes3D.name)

def make_bar(ax, x0=0, y0=0, width = 0.5, height=1 , cmap="viridis",  
              norm=matplotlib.colors.Normalize(vmin=0, vmax=1), **kwargs ):
    # Make data
    u = np.linspace(0, 2*np.pi, 4+1)+np.pi/4.
    v_ = np.linspace(np.pi/4., 3./4*np.pi, 100)
    v = np.linspace(0, np.pi, len(v_)+2 )
    v[0] = 0 ;  v[-1] = np.pi; v[1:-1] = v_
    x = np.outer(np.cos(u), np.sin(v))
    y = np.outer(np.sin(u), np.sin(v))
    z = np.outer(np.ones(np.size(u)), np.cos(v))

    xthr = np.sin(np.pi/4.)**2 ;  zthr = np.sin(np.pi/4.)
    x[x > xthr] = xthr; x[x < -xthr] = -xthr
    y[y > xthr] = xthr; y[y < -xthr] = -xthr
    z[z > zthr] = zthr  ; z[z < -zthr] = -zthr

    x *= 1./xthr*width; y *= 1./xthr*width
    z += zthr
    z *= height/(2.*zthr)
    #translate
    x += x0; y += y0
    #plot
    ax.plot_surface(x, y, z, cmap=cmap, norm=norm, **kwargs)

def make_bars(ax, x, y, height, width=1):
    widths = np.array(width)*np.ones_like(x)
    x = np.array(x).flatten()
    y = np.array(y).flatten()

    h = np.array(height).flatten()
    w = np.array(widths).flatten()
    norm = matplotlib.colors.Normalize(vmin=0, vmax=h.max())
    for i in range(len(x.flatten())):
        make_bar(ax, x0=x[i], y0=y[i], width = w[i] , height=h[i], norm=norm)


X, Y = np.meshgrid([1,2,3], [2,3,4])
Z = np.sin(X*Y)+1.5

make_bars(ax, X,Y,Z, width=0.2, )
plt.show()

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