论文绘图复现

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论文绘图复现

前言

一位读者私信询问以上图片如何用python绘制

感觉有点意思，于是博主鼓捣鼓捣，做一期论文绘图复现

项目目标

绘制带有误差线的堆叠柱状图

项目方法

自定义函数绘制误差线，利用bar的bottom参数制作堆叠效果

第一版

代码语言：javascript代码运行次数：0运行复制

import matplotlib.pyplot as plt

# 数据
categories = ['AR5 (4)', 'CMIP5 (5)', '(10, 12) (6)', '(2)']
warming_rates = [0.35, 0.4, 0.4, 0.45]
error_bars = [0.05, 0.05, 0.05, 0.05]
# 不同柱子的底部空白
bottom_values = [0.05, 0.1, 0.15, 0.2]

# 创建图形和轴对象
fig, ax = plt.subplots()

# 绘制柱状图，设置不同的底部空白
bars = ax.bar(categories, warming_rates, yerr=error_bars, bottom=bottom_values, capsize=5)

# 设置y轴标签
ax.set_ylabel('Warming rate (W m$^{-2}$)')

# 添加数据标签
for bar, bottom in zip(bars, bottom_values):
    height = bar.get_height()
    ax.annotate(f'{height:.2f}',
                xy=(bar.get_x() + bar.get_width() / 2, height + bottom),
                xytext=(0, 3),  # 3 points vertical offset
                textcoords="offset points",
                ha='center', va='bottom')

# 设置y轴的范围，确保底部空白可见
ax.set_ylim(bottom=0)


# 显示图形
plt.show()

第二版

代码语言：javascript代码运行次数：0运行复制

import matplotlib.pyplot as plt

# 数据
categories = ['AR5 (4)', 'CMIP5 (5)', '(10, 12) (6)', '(2)']
warming_rates = [2.5, 1.6,3.2, 4.0]
error_bars = [0.05, 0.05, 0.05, 0.05]
# 不同柱子的底部空白
bottom_values = [2, 1, 2.8, 3.2]

# 创建图形和轴对象
fig, ax = plt.subplots()

# 绘制柱状图，设置不同的底部空白
bars = ax.bar(categories, warming_rates, yerr=error_bars, bottom=bottom_values, capsize=5)

# 在纵轴3的位置添加一条横虚线
ax.axhline(y=3, color='r', linestyle='--')

# 设置y轴标签
ax.set_ylabel('Warming rate (W m$^{-2}$)')

# 添加数据标签
for bar, bottom in zip(bars, bottom_values):
    height = bar.get_height()
    ax.annotate(f'{height:.2f}',
                xy=(bar.get_x() + bar.get_width() / 2, height + bottom),
                xytext=(0, 3),  # 3 points vertical offset
                textcoords="offset points",
                ha='center', va='bottom')


# 显示图形
plt.show()

最终版

代码语言：javascript代码运行次数：0运行复制

import matplotlib.pyplot as plt
import numpy as np

# 数据
categories = ['AR5 (4)', 'CMIP5 (5)', '(10, 12) (6)', '(2)']
warming_rates = [0.40, 0.45, 0.40, 0.42]
colors = ['red', 'blue', 'pink', 'yellow'] # 指定每个柱子的颜色

# 不同柱子的底部空白
bottom_values = [0.1, 0.15, 0.11, 0.12]

# 创建图形和轴对象
fig, ax = plt.subplots(figsize=(10, 8))

# 绘制柱状图，设置不同的底部空白和颜色
bars = []
for i, category in enumerate(categories):
    bar = ax.bar(i, warming_rates[i], bottom=bottom_values[i], color=colors[i], edgecolor='black', capsize=5)
    bars.append(bar)

# 在纵轴3的位置添加一条横虚线
ax.axhline(y=0.2, color='k', linestyle='--')

# 计算每个柱子的中间位置并绘制横线
for bar, bottom in zip(bars, bottom_values):
    middle_y = bar[0].get_height() / 2 + bottom
    x_start = bar[0].get_x()
    x_end = bar[0].get_x() + bar[0].get_width()
    ax.plot([x_start, x_end], [middle_y, middle_y], color='black', linewidth=1, linestyle='-')

# 设置y轴标签
ax.set_ylabel('Warming rate (W m$^{-2}$)')
# 设置y轴的范围，确保底部空白可见
ax.set_ylim(bottom=0)
# 添加数据标签
for bar, bottom in zip(bars, bottom_values):
    height = bar[0].get_height()
    ax.annotate(f'{height:.2f}',
                xy=(bar[0].get_x() + bar[0].get_width() / 2, height + bottom),
                xytext=(0, 3),  # 3 points vertical offset
                textcoords="offset points",
                ha='center', va='bottom')

# 设置x轴的刻度和标签
ax.set_xticks(np.arange(len(categories)))  # 设置刻度的位置
ax.set_xticklabels(categories)  # 设置刻度的标签

# 设置图表标题和标签
ax.set_title('Updated OHC estimates compared with AR5')
ax.set_xlabel('Category')
ax.set_ylabel('Warming rate (W m^-2)')
ax.legend()

# 显示图形
plt.show()

代码语言：javascript代码运行次数：0运行复制

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此时此刻恰如彼时彼刻

你学会了吗

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