如何在python中呈现3D直方图?

2024-06-17 18:56:08 发布

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我想从Hacker's Delight制作这样的绘图:

enter image description here

在Python中有什么方法可以实现这一点?一个使交互调整图形变得容易的解决方案(改变当前正在观察的X/Y切片)将是理想的。

matplotlib和mplot3d模块都没有此功能。我找到了mayavi2,但它非常笨重(我甚至找不到调整大小的选项),只有在从ipython运行时才能正常工作。

或者gnuplot可以工作,但是我不想为了这个而学习另一种语言语法。


Tags: 模块方法功能图形绘图matplotlib选项ipython
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1楼 · 发布于 2024-06-17 18:56:08

因为TJD指出的例子看起来“难以穿透”,这里有一个修改的版本,其中有一些注释可能有助于澄清问题:

#! /usr/bin/env python
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
#
# Assuming you have "2D" dataset like the following that you need
# to plot.
#
data_2d = [ [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
            [6, 7, 8, 9, 10, 11, 12, 13, 14, 15],
            [11, 12, 13, 14, 15, 16, 17, 18 , 19, 20],
            [16, 17, 18, 19, 20, 21, 22, 23, 24, 25],
            [21, 22, 23, 24, 25, 26, 27, 28, 29, 30] ]
#
# Convert it into an numpy array.
#
data_array = np.array(data_2d)
#
# Create a figure for plotting the data as a 3D histogram.
#
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
#
# Create an X-Y mesh of the same dimension as the 2D data. You can
# think of this as the floor of the plot.
#
x_data, y_data = np.meshgrid( np.arange(data_array.shape[1]),
                              np.arange(data_array.shape[0]) )
#
# Flatten out the arrays so that they may be passed to "ax.bar3d".
# Basically, ax.bar3d expects three one-dimensional arrays:
# x_data, y_data, z_data. The following call boils down to picking
# one entry from each array and plotting a bar to from
# (x_data[i], y_data[i], 0) to (x_data[i], y_data[i], z_data[i]).
#
x_data = x_data.flatten()
y_data = y_data.flatten()
z_data = data_array.flatten()
ax.bar3d( x_data,
          y_data,
          np.zeros(len(z_data)),
          1, 1, z_data )
#
# Finally, display the plot.
#
plt.show()

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