使用 Hist 函数在 Python 3d 图中构建一系列一维直方图

发布于 2024-11-07 19:20:18 字数 413 浏览 0 评论 0原文

我正在使用 python 的 hist 函数生成一维直方图，每个直方图都链接到给定的实验。现在我明白了 Hist 函数允许在同一 x 轴上绘制多个直方图以进行比较。为此，我通常使用类似于以下内容的内容，结果是一个非常好的图，其中 x1、x2 和 x3 定义如下 x1 = 长度 expt1 x2 = 长度 exp2 x3 = lengths expt3

P.figure()
n, bins, patches = P.hist( [x0,x1,x2], 10, weights=[w0, w1, w2], histtype='bar')
P.show()

然而，我希望尝试实现 3d 效果，因此我问有人知道是否可以让每个唯一的直方图在 y 平面上与另一个直方图偏移给定的单位，从而生成 3d 效果。

我将不胜感激任何帮助。

原文

I am using pythons hist function to generate 1d histograms each linked to a given experiment.
Now I understand that the Hist function allows one to plot multiple histograms on the same x axis for comparison. I normally use something akin to the following for this purpose and the result is a very nice plot where x1,x2 and x3 are defined as follows
x1 = lengths expt1
x2 = lengths expt2
x3 = lengths expt3

P.figure()
n, bins, patches = P.hist( [x0,x1,x2], 10, weights=[w0, w1, w2], histtype='bar')
P.show()

I was hoping to try achieve a 3d effect however and therefore I ask dose anyone know if it is it possible to have each unique histogram offset from the other in the y plane by a given unit thus generating a 3d effect.

I would appreciate any help on this .

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绝不服输 2024-11-14 19:20:18

我相信你只想要matplotlib.pyplot.bar3d。

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

x0, x1, x2 = [np.random.normal(loc=loc, size=100) for loc in [1, 2, 3]]

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

yspacing = 1
for i, measurement in enumerate([x0, x1, x2]):
    hist, bin_edges = np.histogram(measurement, bins=10)
    dx = np.diff(bin_edges)
    dy = np.ones_like(hist)
    y = i * (1 + yspacing) * np.ones_like(hist)
    z = np.zeros_like(hist)
    ax.bar3d(bin_edges[:-1], y, z, dx, dy, hist, color='b', 
            zsort='average', alpha=0.5)

plt.show()

在此处输入图像描述

I believe you just want matplotlib.pyplot.bar3d.

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

x0, x1, x2 = [np.random.normal(loc=loc, size=100) for loc in [1, 2, 3]]

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

yspacing = 1
for i, measurement in enumerate([x0, x1, x2]):
    hist, bin_edges = np.histogram(measurement, bins=10)
    dx = np.diff(bin_edges)
    dy = np.ones_like(hist)
    y = i * (1 + yspacing) * np.ones_like(hist)
    z = np.zeros_like(hist)
    ax.bar3d(bin_edges[:-1], y, z, dx, dy, hist, color='b', 
            zsort='average', alpha=0.5)

plt.show()

enter image description here

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