wehub-resource-sync
418 lines
9.7 KiB
Markdown
418 lines
9.7 KiB
Markdown
# Python数据图表模块
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本模块指导使用Python生成科研论文级别的数据图表。
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---
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## 一、环境要求
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### 1.1 conda环境
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**默认环境名**：`research`
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**激活命令**：
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```bash
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conda activate research
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```
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**必需库**：
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```bash
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pip install matplotlib seaborn numpy pandas scikit-learn
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```
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**可选库**：
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```bash
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pip install plotly scipy statsmodels
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```
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### 1.2 环境配置
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详见 `modules/environment-setup.md` 获取完整的环境配置指南。
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---
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## 二、图表规范
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### 2.1 分辨率要求
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| 用途 | DPI | 说明 |
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|------|-----|------|
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| 期刊投稿 | 300-600 | 大多数期刊要求 |
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| 顶刊投稿 | 450+ | Nature/Science等 |
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| 屏幕展示 | 150 | PPT/网页 |
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| 打印海报 | 300 | A0/A1海报 |
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**本模块默认使用 450 DPI**
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### 2.2 输出格式
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每张图同时输出两种格式：
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- **PNG**：位图，适合网页和PPT
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- **SVG**：矢量图，适合期刊投稿和后期编辑
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### 2.3 图表尺寸
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| 类型 | 宽度（英寸） | 适用场景 |
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|------|-------------|----------|
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| 单栏图 | 3.5 | 期刊单栏 |
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| 双栏图 | 7.0 | 期刊双栏/全宽 |
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| PPT图 | 10.0 | 演示文稿 |
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---
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## 三、顶刊配色方案
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### 3.1 Nature/Science 风格
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```python
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NATURE_COLORS = ['#2E86AB', '#A23B72', '#F18F01', '#C73E1D', '#95C623']
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```
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| 颜色 | 色值 | 用途 |
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|------|------|------|
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| 深蓝 | #2E86AB | 主色调 |
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| 玫红 | #A23B72 | 对比色 |
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| 橙色 | #F18F01 | 强调色 |
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| 砖红 | #C73E1D | 警示色 |
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| 黄绿 | #95C623 | 辅助色 |
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### 3.2 Cell 风格
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```python
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CELL_COLORS = ['#4E79A7', '#F28E2B', '#E15759', '#76B7B2', '#59A14F', '#EDC948']
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```
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### 3.3 渐变色系
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```python
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# 蓝色渐变（适合热力图）
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BLUE_GRADIENT = ['#A8DADC', '#6DAEDB', '#457B9D', '#2C5F7C', '#1D3557']
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# 红蓝对比（适合正负值）
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DIVERGING_COLORS = {
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'cold': ['#2166AC', '#4393C3', '#92C5DE', '#D1E5F0'],
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'neutral': '#F7F7F7',
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'warm': ['#FDDBC7', '#F4A582', '#D6604D', '#B2182B'],
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}
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```
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### 3.4 色盲友好配色
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```python
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COLORBLIND_SAFE = ['#0077BB', '#33BBEE', '#009988', '#EE7733', '#CC3311', '#EE3377']
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```
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### 3.5 配色原则
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- ❌ 禁止使用matplotlib默认颜色
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- ❌ 禁止使用纯红、纯蓝、纯绿等基础色
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- ✅ 同一图中颜色数量控制在5种以内
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- ✅ 确保色盲友好（避免红绿直接对比）
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- ✅ 使用渐变色表示连续变量
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---
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## 四、代码模板
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### 4.1 基础模板
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```python
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"""
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Figure X: [图表标题]
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论文章节: [所属章节]
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描述: [图表内容描述]
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"""
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import numpy as np
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import pandas as pd
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import matplotlib.pyplot as plt
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import matplotlib.font_manager as fm
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from pathlib import Path
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# ============================================================
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# 中文字体配置（macOS系统）
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# ============================================================
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CHINESE_FONT = None
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font_candidates = [
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'/System/Library/Fonts/STHeiti Light.ttc',
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'/System/Library/Fonts/Supplemental/Songti.ttc',
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'/Library/Fonts/Songti.ttc',
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'/System/Library/Fonts/PingFang.ttc',
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]
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for fp in font_candidates:
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if Path(fp).exists():
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CHINESE_FONT = fm.FontProperties(fname=fp)
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break
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if CHINESE_FONT is None:
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plt.rcParams['font.sans-serif'] = ['Heiti TC', 'STHeiti', 'Arial Unicode MS']
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plt.rcParams['axes.unicode_minus'] = False
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# ============================================================
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# 顶刊配色
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# ============================================================
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COLORS = ['#4E79A7', '#F28E2B', '#E15759', '#76B7B2', '#59A14F', '#EDC948']
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# ============================================================
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# 全局样式设置
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# ============================================================
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def setup_plot_style():
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"""配置全局绑定样式"""
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plt.rcParams.update({
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'font.family': 'sans-serif',
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'font.size': 10,
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'axes.titlesize': 12,
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'axes.labelsize': 10,
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'xtick.labelsize': 9,
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'ytick.labelsize': 9,
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'legend.fontsize': 9,
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'lines.linewidth': 1.5,
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'lines.markersize': 6,
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'axes.linewidth': 1.0,
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'axes.spines.top': False,
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'axes.spines.right': False,
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'axes.grid': True,
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'grid.alpha': 0.3,
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'grid.linewidth': 0.5,
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'legend.frameon': False,
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'savefig.dpi': 450,
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'savefig.bbox': 'tight',
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'savefig.pad_inches': 0.1,
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'figure.facecolor': 'white',
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'axes.facecolor': 'white',
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})
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# ============================================================
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# 主绑定代码
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# ============================================================
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def main():
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setup_plot_style()
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# === 在此处编写具体绑定代码 ===
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fig, ax = plt.subplots(figsize=(7, 5))
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# 示例数据
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x = np.linspace(0, 10, 100)
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ax.plot(x, np.sin(x), color=COLORS[0], label='Model A')
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ax.plot(x, np.cos(x), color=COLORS[1], label='Model B')
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# 标签设置（中文使用FontProperties）
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if CHINESE_FONT:
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ax.set_xlabel('时间 (s)', fontproperties=CHINESE_FONT)
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ax.set_ylabel('幅值', fontproperties=CHINESE_FONT)
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ax.set_title('模型对比', fontproperties=CHINESE_FONT)
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ax.legend(prop=CHINESE_FONT)
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else:
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ax.set_xlabel('Time (s)')
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ax.set_ylabel('Amplitude')
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ax.set_title('Model Comparison')
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ax.legend()
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# === 绑定代码结束 ===
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# 保存图片
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output_dir = Path(__file__).parent
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fig_name = Path(__file__).stem
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plt.savefig(output_dir / f'{fig_name}.png', dpi=450, format='png')
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plt.savefig(output_dir / f'{fig_name}.svg', format='svg')
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plt.show()
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print(f"图片已保存至: {output_dir}")
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if __name__ == '__main__':
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main()
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```
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### 4.2 常用图表类型
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#### 折线图
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```python
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fig, ax = plt.subplots(figsize=(7, 5))
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for i, (label, data) in enumerate(datasets.items()):
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ax.plot(x, data, color=COLORS[i], label=label, linewidth=1.5, marker='o', markersize=4)
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ax.set_xlabel('Epoch')
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ax.set_ylabel('Accuracy (%)')
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ax.legend()
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```
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#### 柱状图
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```python
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fig, ax = plt.subplots(figsize=(7, 5))
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x_pos = np.arange(len(categories))
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bars = ax.bar(x_pos, values, color=COLORS[:len(categories)], edgecolor='white', linewidth=0.5)
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ax.set_xticks(x_pos)
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ax.set_xticklabels(categories)
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ax.set_ylabel('Performance')
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```
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#### 分组柱状图
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```python
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fig, ax = plt.subplots(figsize=(8, 5))
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x = np.arange(len(categories))
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width = 0.25
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for i, (label, values) in enumerate(groups.items()):
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ax.bar(x + i * width, values, width, label=label, color=COLORS[i])
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ax.set_xticks(x + width)
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ax.set_xticklabels(categories)
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ax.legend()
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```
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#### 热力图
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```python
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fig, ax = plt.subplots(figsize=(8, 6))
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im = ax.imshow(matrix, cmap='RdBu_r', aspect='auto', vmin=-1, vmax=1)
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plt.colorbar(im, ax=ax, label='Correlation')
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ax.set_xticks(range(len(labels)))
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ax.set_xticklabels(labels, rotation=45, ha='right')
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ax.set_yticks(range(len(labels)))
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ax.set_yticklabels(labels)
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```
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#### 箱线图
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```python
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fig, ax = plt.subplots(figsize=(7, 5))
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bp = ax.boxplot(data_list, labels=labels, patch_artist=True)
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for patch, color in zip(bp['boxes'], COLORS):
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patch.set_facecolor(color)
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patch.set_alpha(0.7)
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```
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#### 散点图
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```python
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fig, ax = plt.subplots(figsize=(7, 5))
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scatter = ax.scatter(x, y, c=colors, s=sizes, alpha=0.6, cmap='viridis')
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plt.colorbar(scatter, ax=ax, label='Value')
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ax.set_xlabel('X Label')
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ax.set_ylabel('Y Label')
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```
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---
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## 五、文件管理
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### 5.1 目录结构
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```
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项目目录/
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├── figures/
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│ ├── chapter1_introduction/
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│ │ ├── fig1_overview.py
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│ │ ├── fig1_overview.png
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│ │ └── fig1_overview.svg
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│ ├── chapter2_method/
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│ │ └── ...
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│ ├── chapter3_results/
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│ │ └── ...
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│ └── chapter4_discussion/
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│ └── ...
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```
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### 5.2 命名规范
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- 文件名格式：`fig{序号}_{描述}.py`
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- 示例：`fig1_model_architecture.py`, `fig5_accuracy_comparison.py`
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- 输出图片与代码同名，仅扩展名不同
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---
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## 六、执行流程
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### 6.1 标准流程
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1. **确认conda环境已激活**
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```bash
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conda activate research
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```
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2. **创建/编辑Python脚本**
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- 使用上述模板
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- 修改数据和绑定代码
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3. **运行脚本**
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```bash
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python figures/chapter1/fig1_xxx.py
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```
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4. **检查输出**
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- 确认PNG和SVG都已生成
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- 检查图表质量
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5. **如有错误，修复后重新运行**
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### 6.2 缺失库处理
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```bash
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# 使用pip安装
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pip install [package_name]
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# 或使用conda安装
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conda install [package_name]
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```
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---
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## 七、质量检查清单
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### 图表内容
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- [ ] 数据准确无误
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- [ ] 坐标轴标签完整（含单位）
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- [ ] 图例清晰可读
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- [ ] 标题简洁明了
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### 视觉效果
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- [ ] 使用顶刊配色方案
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- [ ] 分辨率达到450 DPI
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- [ ] 字体大小适中（可读）
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- [ ] 无多余的网格线或边框
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### 文件输出
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- [ ] PNG格式已生成
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- [ ] SVG格式已生成
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- [ ] 文件命名规范
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- [ ] 存放在正确目录
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---
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## 八、常见问题
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### Q1：中文显示为方块
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**解决方案**：
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```python
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# 方法1：指定字体文件
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from matplotlib.font_manager import FontProperties
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font = FontProperties(fname='/System/Library/Fonts/STHeiti Light.ttc')
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ax.set_xlabel('中文标签', fontproperties=font)
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# 方法2：全局设置
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plt.rcParams['font.sans-serif'] = ['SimHei', 'Heiti TC', 'STHeiti']
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plt.rcParams['axes.unicode_minus'] = False
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```
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### Q2：图片模糊
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**解决方案**：
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```python
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plt.savefig('figure.png', dpi=450, bbox_inches='tight')
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```
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### Q3：颜色不够用
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**解决方案**：
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```python
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# 使用colormap生成更多颜色
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import matplotlib.cm as cm
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colors = cm.viridis(np.linspace(0, 1, n_colors))
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```
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### Q4：图例遮挡数据
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**解决方案**：
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```python
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ax.legend(loc='upper left', bbox_to_anchor=(1.02, 1))
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plt.tight_layout()
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```
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