scientific-figure-assembly

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Scientific Figure Assembly (R-based)

基于R的科学图表组装

Create publication-ready multi-panel figures using R packages (patchwork, cowplot) with professional panel labels (A, B, C, D) at 300 DPI resolution.

⚠️ IMPORTANT: This workflow uses R for figure assembly. For meta-analysis projects, all figures should be generated and assembled in R.

使用R包（patchwork、cowplot）创建带有专业面板标签（A、B、C、D）、分辨率达300 DPI的可直接用于出版的多面板图表。

⚠️ 重要提示：此工作流使用R进行图表组装。对于元分析项目，所有图表都应在R中生成并组装。

When to Use

适用场景

Combining multiple plots into a single multi-panel figure for publication
Adding panel labels (A, B, C) to existing figures
Ensuring figures meet journal requirements (300 DPI minimum)
Creating consistent figure layouts for manuscripts
Preparing figures for Nature, Science, Cell, JAMA, Lancet submissions

将多个绘图组合成单个多面板图表用于发表
为现有图表添加面板标签（A、B、C）
确保图表满足期刊要求（最低300 DPI）
为手稿创建布局一致的图表
为《Nature》《Science》《Cell》《JAMA》《Lancet》等期刊投稿准备图表

Quick Start

快速开始

Tell me:

Plot objects: R plot objects (ggplot, forest plots, etc.) OR paths to PNG/JPG files
Layout: Vertical (stacked), horizontal (side-by-side), or grid (2x2, 2x3, etc.)
Output name: What to call the final figure
Labels: Which panel labels to use (default: A, B, C, D...)

I'll create an R script using patchwork or cowplot to assemble the figure with proper spacing and labels.

请告知我：

绘图对象：R绘图对象（ggplot、森林图等）或PNG/JPG文件路径
布局：垂直（堆叠）、水平（并排）或网格（2x2、2x3等）
输出名称：最终图表的命名
标签：要使用的面板标签（默认：A、B、C、D...）

我将使用patchwork或cowplot创建R脚本，以合适的间距和标签组装图表。

R Package Approach (Recommended)

Create or load individual plots

p1 <- ggplot(data1, aes(x, y)) + geom_point() + ggtitle("A. First Panel") p2 <- ggplot(data2, aes(x, y)) + geom_line() + ggtitle("B. Second Panel") p3 <- ggplot(data3, aes(x, y)) + geom_bar(stat="identity") + ggtitle("C. Third Panel")

Combine vertically

combined <- p1 / p2 / p3

Or combine horizontally

combined <- p1 | p2 | p3

Or grid layout (2 columns)

combined <- (p1 | p2) / p3

Export at 300 DPI

ggsave("figures/figure1_combined.png", plot = combined, width = 10, height = 12, dpi = 300)

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ggsave("figures/figure1_combined.png", plot = combined, width = 10, height = 12, dpi = 300)

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Method 2: cowplot (For any R plots)

方法2：cowplot（适用于所有R绘图）

More flexible, works with base R plots and ggplot2:

library(ggplot2)
library(cowplot)

灵活性更高，可用于基础R绘图和ggplot2：

library(ggplot2)
library(cowplot)

Create individual plots

p1 <- ggplot(data1, aes(x, y)) + geom_point() p2 <- ggplot(data2, aes(x, y)) + geom_line() p3 <- ggplot(data3, aes(x, y)) + geom_bar(stat="identity")

Combine with automatic panel labels

combined <- plot_grid( p1, p2, p3, labels = c("A", "B", "C"), label_size = 18, ncol = 1, # Vertical stack rel_heights = c(1, 1, 1) # Equal heights )

Export

ggsave("figures/figure1_combined.png", plot = combined, width = 10, height = 12, dpi = 300)

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ggsave("figures/figure1_combined.png", plot = combined, width = 10, height = 12, dpi = 300)

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Legacy Python Script Template (Not Recommended)

遗留Python脚本模板（不推荐）

⚠️ For meta-analysis projects, use R methods above instead.

If you absolutely need Python for existing PNG files:

python

#!/usr/bin/env python3
"""Legacy: Assemble multi-panel scientific figure from PNG files."""

from PIL import Image, ImageDraw, ImageFont
from pathlib import Path

def add_panel_label(img, label, position='top-left',
                   font_size=80, offset=(40, 40),
                   bg_color='white', text_color='black',
                   border=True):
    """
    Add panel label (A, B, C) to image.

    Args:
        img: PIL Image object
        label: Label text (e.g., 'A', 'B', 'C')
        position: 'top-left', 'top-right', 'bottom-left', 'bottom-right'
        font_size: Font size in pixels (80 works well for 3000px wide images)
        offset: (x, y) offset from corner in pixels
        bg_color: Background color for label box
        text_color: Label text color
        border: Whether to draw border around label box
    """
    draw = ImageDraw.Draw(img)

    # Try system fonts (macOS, then Linux)
    try:
        font = ImageFont.truetype("/System/Library/Fonts/Helvetica.ttc", font_size)
    except:
        try:
            font = ImageFont.truetype(
                "/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf", font_size
            )
        except:
            font = ImageFont.load_default()
            print(f"Warning: Using default font for label {label}")

    # Calculate label position
    x, y = offset
    if 'right' in position:
        bbox = draw.textbbox((0, 0), label, font=font)
        text_width = bbox[2] - bbox[0]
        x = img.width - text_width - offset[0]
    if 'bottom' in position:
        bbox = draw.textbbox((0, 0), label, font=font)
        text_height = bbox[3] - bbox[1]
        y = img.height - text_height - offset[1]

    # Draw background box
    bbox = draw.textbbox((x, y), label, font=font)
    padding = 10
    draw.rectangle(
        [bbox[0] - padding, bbox[1] - padding,
         bbox[2] + padding, bbox[3] + padding],
        fill=bg_color,
        outline='black' if border else None,
        width=2 if border else 0
    )

    # Draw text
    draw.text((x, y), label, fill=text_color, font=font)

    return img


def assemble_vertical(input_files, output_file, labels=None,
                     spacing=40, dpi=300):
    """
    Stack images vertically with panel labels.

    Args:
        input_files: List of paths to input images
        output_file: Path for output image
        labels: List of labels (default: A, B, C, ...)
        spacing: Vertical spacing between panels in pixels
        dpi: Output resolution
    """
    if labels is None:
        labels = [chr(65 + i) for i in range(len(input_files))]  # A, B, C, ...

    # Load all images
    images = [Image.open(f) for f in input_files]

    # Add labels
    labeled = [add_panel_label(img, label)
               for img, label in zip(images, labels)]

    # Calculate dimensions
    max_width = max(img.width for img in labeled)
    total_height = sum(img.height for img in labeled) + spacing * (len(labeled) - 1)

    # Create combined image
    combined = Image.new('RGB', (max_width, total_height), 'white')

    # Paste images
    y_offset = 0
    for img in labeled:
        combined.paste(img, (0, y_offset))
        y_offset += img.height + spacing

    # Save with specified DPI
    combined.save(output_file, dpi=(dpi, dpi))
    print(f"✅ Created {output_file}")
    print(f"   Dimensions: {combined.width}×{combined.height} px at {dpi} DPI")

    return output_file


def assemble_horizontal(input_files, output_file, labels=None,
                       spacing=40, dpi=300):
    """Stack images horizontally with panel labels."""
    if labels is None:
        labels = [chr(65 + i) for i in range(len(input_files))]

    images = [Image.open(f) for f in input_files]
    labeled = [add_panel_label(img, label)
               for img, label in zip(images, labels)]

    max_height = max(img.height for img in labeled)
    total_width = sum(img.width for img in labeled) + spacing * (len(labeled) - 1)

    combined = Image.new('RGB', (total_width, max_height), 'white')

    x_offset = 0
    for img in labeled:
        combined.paste(img, (x_offset, 0))
        x_offset += img.width + spacing

    combined.save(output_file, dpi=(dpi, dpi))
    print(f"✅ Created {output_file}")
    print(f"   Dimensions: {combined.width}×{combined.height} px at {dpi} DPI")

    return output_file


def assemble_grid(input_files, output_file, rows, cols,
                 labels=None, spacing=40, dpi=300):
    """
    Arrange images in a grid with panel labels.

    Args:
        rows: Number of rows
        cols: Number of columns
        Other args same as assemble_vertical
    """
    if labels is None:
        labels = [chr(65 + i) for i in range(len(input_files))]

    images = [Image.open(f) for f in input_files]
    labeled = [add_panel_label(img, label)
               for img, label in zip(images, labels)]

    # Calculate cell dimensions (use max from each row/col)
    cell_width = max(img.width for img in labeled)
    cell_height = max(img.height for img in labeled)

    # Total dimensions
    total_width = cell_width * cols + spacing * (cols - 1)
    total_height = cell_height * rows + spacing * (rows - 1)

    combined = Image.new('RGB', (total_width, total_height), 'white')

    # Place images
    for idx, img in enumerate(labeled):
        if idx >= rows * cols:
            break
        row = idx // cols
        col = idx % cols
        x = col * (cell_width + spacing)
        y = row * (cell_height + spacing)
        combined.paste(img, (x, y))

    combined.save(output_file, dpi=(dpi, dpi))
    print(f"✅ Created {output_file}")
    print(f"   Dimensions: {combined.width}×{combined.height} px at {dpi} DPI")

    return output_file


if __name__ == '__main__':
    import sys

    # Example usage
    if len(sys.argv) < 3:
        print("Usage: python assemble_figures.py <output> <layout> <input1> <input2> ...")
        print("  layout: vertical, horizontal, or grid:RxC (e.g., grid:2x2)")
        sys.exit(1)

    output = sys.argv[1]
    layout = sys.argv[2]
    inputs = sys.argv[3:]

    if layout == 'vertical':
        assemble_vertical(inputs, output)
    elif layout == 'horizontal':
        assemble_horizontal(inputs, output)
    elif layout.startswith('grid:'):
        rows, cols = map(int, layout.split(':')[1].split('x'))
        assemble_grid(inputs, output, rows, cols)
    else:
        print(f"Unknown layout: {layout}")
        sys.exit(1)

⚠️ 对于元分析项目，请使用上述R方法。

如果因现有PNG文件确实需要使用Python：

python

#!/usr/bin/env python3
"""Legacy: Assemble multi-panel scientific figure from PNG files."""

from PIL import Image, ImageDraw, ImageFont
from pathlib import Path

def add_panel_label(img, label, position='top-left',
                   font_size=80, offset=(40, 40),
                   bg_color='white', text_color='black',
                   border=True):
    """
    Add panel label (A, B, C) to image.

    Args:
        img: PIL Image object
        label: Label text (e.g., 'A', 'B', 'C')
        position: 'top-left', 'top-right', 'bottom-left', 'bottom-right'
        font_size: Font size in pixels (80 works well for 3000px wide images)
        offset: (x, y) offset from corner in pixels
        bg_color: Background color for label box
        text_color: Label text color
        border: Whether to draw border around label box
    """
    draw = ImageDraw.Draw(img)

    # Try system fonts (macOS, then Linux)
    try:
        font = ImageFont.truetype("/System/Library/Fonts/Helvetica.ttc", font_size)
    except:
        try:
            font = ImageFont.truetype(
                "/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf", font_size
            )
        except:
            font = ImageFont.load_default()
            print(f"Warning: Using default font for label {label}")

    # Calculate label position
    x, y = offset
    if 'right' in position:
        bbox = draw.textbbox((0, 0), label, font=font)
        text_width = bbox[2] - bbox[0]
        x = img.width - text_width - offset[0]
    if 'bottom' in position:
        bbox = draw.textbbox((0, 0), label, font=font)
        text_height = bbox[3] - bbox[1]
        y = img.height - text_height - offset[1]

    # Draw background box
    bbox = draw.textbbox((x, y), label, font=font)
    padding = 10
    draw.rectangle(
        [bbox[0] - padding, bbox[1] - padding,
         bbox[2] + padding, bbox[3] + padding],
        fill=bg_color,
        outline='black' if border else None,
        width=2 if border else 0
    )

    # Draw text
    draw.text((x, y), label, fill=text_color, font=font)

    return img


def assemble_vertical(input_files, output_file, labels=None,
                     spacing=40, dpi=300):
    """
    Stack images vertically with panel labels.

    Args:
        input_files: List of paths to input images
        output_file: Path for output image
        labels: List of labels (default: A, B, C, ...)
        spacing: Vertical spacing between panels in pixels
        dpi: Output resolution
    """
    if labels is None:
        labels = [chr(65 + i) for i in range(len(input_files))]  # A, B, C, ...

    # Load all images
    images = [Image.open(f) for f in input_files]

    # Add labels
    labeled = [add_panel_label(img, label)
               for img, label in zip(images, labels)]

    # Calculate dimensions
    max_width = max(img.width for img in labeled)
    total_height = sum(img.height for img in labeled) + spacing * (len(labeled) - 1)

    # Create combined image
    combined = Image.new('RGB', (max_width, total_height), 'white')

    # Paste images
    y_offset = 0
    for img in labeled:
        combined.paste(img, (0, y_offset))
        y_offset += img.height + spacing

    # Save with specified DPI
    combined.save(output_file, dpi=(dpi, dpi))
    print(f"✅ Created {output_file}")
    print(f"   Dimensions: {combined.width}×{combined.height} px at {dpi} DPI")

    return output_file


def assemble_horizontal(input_files, output_file, labels=None,
                       spacing=40, dpi=300):
    """Stack images horizontally with panel labels."""
    if labels is None:
        labels = [chr(65 + i) for i in range(len(input_files))]

    images = [Image.open(f) for f in input_files]
    labeled = [add_panel_label(img, label)
               for img, label in zip(images, labels)]

    max_height = max(img.height for img in labeled)
    total_width = sum(img.width for img in labeled) + spacing * (len(labeled) - 1)

    combined = Image.new('RGB', (total_width, max_height), 'white')

    x_offset = 0
    for img in labeled:
        combined.paste(img, (x_offset, 0))
        x_offset += img.width + spacing

    combined.save(output_file, dpi=(dpi, dpi))
    print(f"✅ Created {output_file}")
    print(f"   Dimensions: {combined.width}×{combined.height} px at {dpi} DPI")

    return output_file


def assemble_grid(input_files, output_file, rows, cols,
                 labels=None, spacing=40, dpi=300):
    """
    Arrange images in a grid with panel labels.

    Args:
        rows: Number of rows
        cols: Number of columns
        Other args same as assemble_vertical
    """
    if labels is None:
        labels = [chr(65 + i) for i in range(len(input_files))]

    images = [Image.open(f) for f in input_files]
    labeled = [add_panel_label(img, label)
               for img, label in zip(images, labels)]

    # Calculate cell dimensions (use max from each row/col)
    cell_width = max(img.width for img in labeled)
    cell_height = max(img.height for img in labeled)

    # Total dimensions
    total_width = cell_width * cols + spacing * (cols - 1)
    total_height = cell_height * rows + spacing * (rows - 1)

    combined = Image.new('RGB', (total_width, total_height), 'white')

    # Place images
    for idx, img in enumerate(labeled):
        if idx >= rows * cols:
            break
        row = idx // cols
        col = idx % cols
        x = col * (cell_width + spacing)
        y = row * (cell_height + spacing)
        combined.paste(img, (x, y))

    combined.save(output_file, dpi=(dpi, dpi))
    print(f"✅ Created {output_file}")
    print(f"   Dimensions: {combined.width}×{combined.height} px at {dpi} DPI")

    return output_file


if __name__ == '__main__':
    import sys

    # Example usage
    if len(sys.argv) < 3:
        print("Usage: python assemble_figures.py <output> <layout> <input1> <input2> ...")
        print("  layout: vertical, horizontal, or grid:RxC (e.g., grid:2x2)")
        sys.exit(1)

    output = sys.argv[1]
    layout = sys.argv[2]
    inputs = sys.argv[3:]

    if layout == 'vertical':
        assemble_vertical(inputs, output)
    elif layout == 'horizontal':
        assemble_horizontal(inputs, output)
    elif layout.startswith('grid:'):
        rows, cols = map(int, layout.split(':')[1].split('x'))
        assemble_grid(inputs, output, rows, cols)
    else:
        print(f"Unknown layout: {layout}")
        sys.exit(1)

Common Layouts

常见布局

Vertical (Most Common)

垂直布局（最常用）

Stack plots on top of each other - good for showing progression or related outcomes.

Example: Three forest plots (pCR, EFS, OS) stacked vertically

Panel A: pCR forest plot
Panel B: EFS forest plot
Panel C: OS forest plot

将绘图上下堆叠 - 适合展示过程或相关结果。

示例：三个森林图（pCR、EFS、OS）垂直堆叠

面板A：pCR森林图
面板B：EFS森林图
面板C：OS森林图

Horizontal

水平布局

Place plots side-by-side - good for comparisons.

Example: Two funnel plots showing publication bias

Panel A: pCR funnel plot
Panel B: EFS funnel plot

将绘图并排摆放 - 适合对比展示。

示例：两个展示发表偏倚的漏斗图

面板A：pCR漏斗图
面板B：EFS漏斗图

Grid (2x2, 2x3, etc.)

网格布局（2x2、2x3等）

Arrange in rows and columns - good for systematic comparisons.

Example: 2x2 grid of subgroup analyses

Panel A: Age subgroup
Panel B: Sex subgroup
Panel C: Stage subgroup
Panel D: Histology subgroup

按行和列排列 - 适合系统性对比。

示例：2x2网格的亚组分析

面板A：年龄亚组
面板B：性别亚组
面板C：分期亚组
面板D：组织学亚组

R Workflow (Recommended)

assemble_forest_plots.R

Combine multiple forest plots into a single figure

library(meta) library(metafor) library(patchwork)

Set working directory

setwd("/Users/htlin/meta-pipe/06_analysis")

Load extraction data

data <- read.csv("../05_extraction/extraction.csv")

--- Create individual forest plots ---

Plot 1: Pathologic complete response

res_pcr <- metabin( event.e = events_pcr_ici, n.e = total_ici, event.c = events_pcr_control, n.c = total_control, data = data, studlab = study_id, sm = "RR", method = "MH" )

Save as ggplot-compatible object

p1 <- forest(res_pcr, layout = "RevMan5") + ggtitle("A. Pathologic Complete Response")

Plot 2: Event-free survival

res_efs <- metagen( TE = log_hr_efs, seTE = se_log_hr_efs, data = data, studlab = study_id, sm = "HR" )

p2 <- forest(res_efs) + ggtitle("B. Event-Free Survival")

res_efs <- metagen( TE = log_hr_efs, seTE = se_log_hr_efs, data = data, studlab = study_id, sm = "HR" )

p2 <- forest(res_efs) + ggtitle("B. Event-Free Survival")

Plot 3: Overall survival

res_os <- metagen( TE = log_hr_os, seTE = se_log_hr_os, data = data, studlab = study_id, sm = "HR" )

p3 <- forest(res_os) + ggtitle("C. Overall Survival")

res_os <- metagen( TE = log_hr_os, seTE = se_log_hr_os, data = data, studlab = study_id, sm = "HR" )

p3 <- forest(res_os) + ggtitle("C. Overall Survival")

--- Combine with patchwork ---

combined <- p1 / p2 / p3 + plot_annotation( title = "Figure 1. Efficacy Outcomes with ICI vs Control", theme = theme(plot.title = element_text(size = 16, face = "bold")) )

Export at 300 DPI

ggsave("../07_manuscript/figures/figure1_efficacy.png", plot = combined, width = 10, height = 14, dpi = 300, bg = "white")

cat("✅ Created figure1_efficacy.png\n") cat(" Dimensions: 3000×4200 px at 300 DPI\n")

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ggsave("../07_manuscript/figures/figure1_efficacy.png", plot = combined, width = 10, height = 14, dpi = 300, bg = "white")

cat("✅ Created figure1_efficacy.png\n") cat(" Dimensions: 3000×4200 px at 300 DPI\n")

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Using cowplot for More Control

使用cowplot实现更多控制

library(cowplot)

library(cowplot)

Combine with explicit panel labels and alignment

combined <- plot_grid( p1, p2, p3, labels = c("A", "B", "C"), label_size = 18, label_fontface = "bold", ncol = 1, align = "v", # Vertical alignment axis = "l", # Align left axis rel_heights = c(1, 1, 1) )

Add overall title

title <- ggdraw() + draw_label( "Figure 1. Efficacy Outcomes with ICI vs Control", fontface = "bold", size = 16, x = 0.5, hjust = 0.5 )

Combine title and plots

final <- plot_grid( title, combined, ncol = 1, rel_heights = c(0.1, 1) )

Export

ggsave("../07_manuscript/figures/figure1_efficacy.png", plot = final, width = 10, height = 14, dpi = 300, bg = "white")

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ggsave("../07_manuscript/figures/figure1_efficacy.png", plot = final, width = 10, height = 14, dpi = 300, bg = "white")

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Grid Layout (2x2 or 2x3)

网格布局（2x2或2x3）

library(patchwork)

library(patchwork)

2x2 grid

combined <- (p1 | p2) / (p3 | p4) + plot_annotation(tag_levels = "A")

2x3 grid

combined <- (p1 | p2 | p3) / (p4 | p5 | p6) + plot_annotation(tag_levels = "A")

ggsave("figure_grid.png", width = 14, height = 10, dpi = 300)

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combined <- (p1 | p2 | p3) / (p4 | p5 | p6) + plot_annotation(tag_levels = "A")

ggsave("figure_grid.png", width = 14, height = 10, dpi = 300)

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Python Workflow (Legacy - For PNG Files Only)

Python工作流（遗留 - 仅适用于PNG文件）

⚠️ Only use if you have existing PNG files and cannot regenerate in R.

⚠️ 仅当你有现有PNG文件且无法在R中重新生成时使用。

Step 1: Verify Input Files

步骤1：验证输入文件

bash

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bash

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Check that all files exist and are PNG/JPG

ls -lh path/to/plots/*.png

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ls -lh path/to/plots/*.png

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Step 2: Create Assembly Script

步骤2：创建组装脚本

Use the Python template provided in this skill.

使用本技能中提供的Python模板。

Step 3: Run Assembly

步骤3：运行组装

bash

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bash

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Using uv (recommended for dependency management)

使用uv（推荐用于依赖管理）

uv run python assemble_figures.py Figure1_Efficacy.png vertical
forest_plot_pCR.png
forest_plot_EFS.png
forest_plot_OS.png

Or with system Python (requires PIL/Pillow)

或使用系统Python（需要安装PIL/Pillow）

python assemble_figures.py Figure1.png grid:2x2
plot1.png plot2.png plot3.png plot4.png

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python assemble_figures.py Figure1.png grid:2x2
plot1.png plot2.png plot3.png plot4.png

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Step 4: Verify Output

步骤4：验证输出

bash

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bash

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Check dimensions and file size

检查尺寸和文件大小

ls -lh Figure1_Efficacy.png

Verify DPI (should show 300x300)

验证DPI（应显示300x300）

file Figure1_Efficacy.png

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file Figure1_Efficacy.png

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Customization Options

自定义选项

Font Size Adjustment

字体大小调整

For different image sizes:

3000px wide images:
```
font_size=80
```
(default)
1500px wide images:
```
font_size=40
```
6000px wide images:
```
font_size=160
```

针对不同图像尺寸：

3000px宽图像：
```
font_size=80
```
（默认）
1500px宽图像：
```
font_size=40
```
6000px宽图像：
```
font_size=160
```

Label Position

标签位置

```
position='top-left'
```
(default)
```
position='top-right'
```
```
position='bottom-left'
```
```
position='bottom-right'
```

```
position='top-left'
```
（默认）
```
position='top-right'
```
```
position='bottom-left'
```
```
position='bottom-right'
```

Spacing Between Panels

面板间距

Default:
```
spacing=40
```
pixels
Tight spacing:
```
spacing=20
```
Loose spacing:
```
spacing=80
```

默认：
```
spacing=40
```
像素
紧凑间距：
```
spacing=20
```
宽松间距：
```
spacing=80
```

Label Style

标签样式

White background with black border (default, best visibility)
Transparent background:
```
bg_color=None, border=False
```

Custom colors:

bg_color='#f0f0f0', text_color='#333333'

白色背景带黑色边框（默认，可见性最佳）
透明背景：
```
bg_color=None, border=False
```

自定义颜色：

bg_color='#f0f0f0', text_color='#333333'

Journal Requirements

期刊要求

Nature, Science, Cell

《Nature》《Science》《Cell》

Resolution: 300-600 DPI
Format: TIFF or high-quality PDF preferred, PNG acceptable
Width: 89mm (single column) or 183mm (double column) at final size
Font: Arial, Helvetica, or similar sans-serif
Labels: Bold, 8-10pt at final size

分辨率：300-600 DPI
格式：优先使用TIFF或高质量PDF，PNG也可接受
宽度：最终尺寸下单栏89mm或双栏183mm
字体：Arial、Helvetica或类似无衬线字体
标签：加粗，最终尺寸下8-10pt

Lancet, JAMA, NEJM

《Lancet》《JAMA》《NEJM》

Resolution: 300 DPI minimum
Format: TIFF, EPS, or PNG
Width: Fit within column width (typically 3-4 inches)
Labels: Clear, high contrast
Grayscale: Must be readable in B&W

分辨率：最低300 DPI
格式：TIFF、EPS或PNG
宽度：适配栏宽（通常3-4英寸）
标签：清晰、高对比度
灰度：在黑白模式下必须可读

Quality Checklist

质量检查清单

Common Issues & Solutions

常见问题与解决方案

Problem: Labels too small Solution: Increase

font_size

parameter (try doubling it)

Problem: Labels obscure data Solution: Change

position

to different corner or adjust

offset

Problem: DPI too low Solution: Regenerate input plots at higher resolution first, then reassemble

Problem: Uneven spacing Solution: Crop input images to remove excess white space before assembly

Problem: File too large Solution: Use PNG compression or convert to JPEG (may lose quality)

问题：标签过小 解决方案：增大

font_size

参数（尝试翻倍）

问题：标签遮挡数据 解决方案：将

position

改为其他角落或调整

offset

问题：DPI过低 解决方案：先以更高分辨率重新生成输入绘图，再进行组装

问题：间距不均 解决方案：组装前裁剪输入图像以去除多余空白

问题：文件过大 解决方案：使用PNG压缩或转换为JPEG（可能会损失质量）

Example Use Cases

示例用例

Meta-Analysis Figures (R)

元分析图表（R）

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Figure 1: Efficacy outcomes (3 vertical panels)

library(patchwork)

combined <- p_pcr / p_efs / p_os + plot_annotation( title = "Figure 1. Efficacy Outcomes", tag_levels = "A" )

ggsave("07_manuscript/figures/figure1_efficacy.png", width = 10, height = 14, dpi = 300)

library(patchwork)

combined <- p_pcr / p_efs / p_os + plot_annotation( title = "Figure 1. Efficacy Outcomes", tag_levels = "A" )

ggsave("07_manuscript/figures/figure1_efficacy.png", width = 10, height = 14, dpi = 300)

Figure 2: Safety + Bias (2 vertical panels)

combined <- p_safety / p_funnel + plot_annotation(tag_levels = "A")

ggsave("07_manuscript/figures/figure2_safety.png", width = 10, height = 10, dpi = 300)

combined <- p_safety / p_funnel + plot_annotation(tag_levels = "A")

ggsave("07_manuscript/figures/figure2_safety.png", width = 10, height = 10, dpi = 300)

Figure 3: Subgroup analysis (2x2 grid)

combined <- (p_age | p_sex) / (p_stage | p_histology) + plot_annotation( title = "Figure 3. Subgroup Analyses", tag_levels = "A" )

ggsave("07_manuscript/figures/figure3_subgroups.png", width = 14, height = 12, dpi = 300)

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combined <- (p_age | p_sex) / (p_stage | p_histology) + plot_annotation( title = "Figure 3. Subgroup Analyses", tag_levels = "A" )

ggsave("07_manuscript/figures/figure3_subgroups.png", width = 14, height = 12, dpi = 300)

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Legacy Python Examples (Not Recommended)

遗留Python示例（不推荐）

bash

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bash

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Figure 1: Efficacy outcomes (3 vertical panels)

uv run python assemble.py Figure1_Efficacy.png vertical
forest_plot_pCR.png
forest_plot_EFS.png
forest_plot_OS.png

Figure 2: Safety + Bias (2 vertical panels)

uv run python assemble.py Figure2_Safety.png vertical
forest_plot_SAE.png
funnel_plot_pCR.png

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uv run python assemble.py Figure2_Safety.png vertical
forest_plot_SAE.png
funnel_plot_pCR.png

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Dependencies

依赖项

R Packages (Recommended)

Install from CRAN

install.packages(c("patchwork", "cowplot", "ggplot2"))

For meta-analysis plots

install.packages(c("meta", "metafor"))

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install.packages(c("meta", "metafor"))

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Python (Legacy - Only for PNG Assembly)

Python（遗留 - 仅用于PNG组装）

bash

undefined

bash

undefined

Install using uv (if needed for legacy workflows)

使用uv安装（如果遗留工作流需要）

uv add Pillow

Or using pip

或使用pip

pip install Pillow

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pip install Pillow

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Output Example

输出示例

R Output

R输出

✅ Created figure1_efficacy.png
   Dimensions: 3000×4200 px at 300 DPI
   Size: 2.3 MB

The output file will have:

Professional panel labels (A, B, C) automatically added by patchwork/cowplot
Consistent spacing between panels
300 DPI resolution suitable for publication
Aligned axes for easy comparison
Publication-ready theme

✅ Created figure1_efficacy.png
   Dimensions: 3000×4200 px at 300 DPI
   Size: 2.3 MB

输出文件将包含：

由patchwork/cowplot自动添加的专业面板标签（A、B、C）
面板间一致的间距
适合发表的300 DPI分辨率
对齐的坐标轴便于对比
可直接用于发表的主题样式

Python Output (Legacy)

Python输出（遗留）

✅ Created Figure1_Efficacy.png
   Dimensions: 3000×6080 px at 300 DPI

The output file will have:

Professional panel labels (A, B, C) in top-left corners
Consistent spacing between panels
300 DPI resolution suitable for publication
White background with black border around labels for maximum visibility

✅ Created Figure1_Efficacy.png
   Dimensions: 3000×6080 px at 300 DPI

输出文件将包含：

位于左上角的专业面板标签（A、B、C）
面板间一致的间距
适合发表的300 DPI分辨率
标签带有白色背景和黑色边框以保证最高可见性

Related Skills

Pro Tips

专业技巧

R Workflow Tips

R工作流技巧

Work in R throughout: Generate plots AND assemble in R for best results
Use patchwork for ggplot2: Simplest syntax (
```
p1 / p2
```
for vertical)
Use cowplot for mixed plots: Works with base R and ggplot2
Set theme globally: Use
```
theme_set(theme_minimal())
```
for consistency
Export once at end: Create all plots, combine, then export (faster)
Check alignment: Use
```
align = "v"
```
and
```
axis = "l"
```
in cowplot
Consistent sizes: Set
```
base_size
```
in theme for readable text

全程使用R：在R中生成并组装绘图以获得最佳效果
ggplot2绘图使用patchwork：语法最简单（
```
p1 / p2
```
表示垂直堆叠）
混合绘图使用cowplot：适用于基础R绘图和ggplot2
全局设置主题：使用
```
theme_set(theme_minimal())
```
保证一致性
最后统一导出：创建所有绘图后再组合导出（速度更快）
检查对齐：在cowplot中使用
```
align = "v"
```
和
```
axis = "l"
```
统一尺寸：在主题中设置
```
base_size
```
以保证文本可读性

General Tips

通用技巧

Generate high-quality inputs first: Assembly won't improve low-quality source plots
Label systematically: A-B-C top-to-bottom or left-to-right
Check in print preview: Ensure labels readable at final print size
Keep R scripts: Save R code for reproducibility
Version control figures: Commit both R scripts and final PNG files
Test on different screens: Check readability on laptop and printed page

先生成高质量输入：组装无法提升低质量源绘图的品质
系统地添加标签：按从上到下或从左到右的顺序使用A-B-C标签
打印预览检查：确保标签在最终印刷尺寸下可读
保留R脚本：保存R代码以保证可重复性
版本控制图表：同时提交R脚本和最终PNG文件
多屏幕测试：在笔记本电脑和打印页面上检查可读性

R Package Resources

R包资源

When you need help with R packages:

CRAN: https://cran.r-project.org/ (patchwork, cowplot documentation)
Tidyverse: https://www.tidyverse.org/ (ggplot2 reference)
R-universe: https://r-universe.dev/search/ (search all R packages)
patchwork guide: https://patchwork.data-imaginist.com/
cowplot guide: https://wilkelab.org/cowplot/

当你需要R包帮助时：

CRAN：https://cran.r-project.org/（patchwork、cowplot文档）
Tidyverse：https://www.tidyverse.org/（ggplot2参考）
R-universe：https://r-universe.dev/search/（搜索所有R包）
patchwork指南：https://patchwork.data-imaginist.com/
cowplot指南：https://wilkelab.org/cowplot/

scientific-figure-assembly

Original

Translation

Scientific Figure Assembly (R-based)

基于R的科学图表组装

When to Use

适用场景

Quick Start

快速开始

R Package Approach (Recommended)

推荐的R包方法

Method 1: patchwork (For ggplot2 objects)

方法1：patchwork（适用于ggplot2对象）

Create or load individual plots

Create or load individual plots

Combine vertically

Combine vertically

Or combine horizontally

Or combine horizontally

Or grid layout (2 columns)

Or grid layout (2 columns)

Export at 300 DPI

Export at 300 DPI

Method 2: cowplot (For any R plots)

方法2：cowplot（适用于所有R绘图）

Create individual plots

Create individual plots

Combine with automatic panel labels

Combine with automatic panel labels

Export

Export

Legacy Python Script Template (Not Recommended)

遗留Python脚本模板（不推荐）

Common Layouts

常见布局

Vertical (Most Common)

垂直布局（最常用）

Horizontal

水平布局

Grid (2x2, 2x3, etc.)

网格布局（2x2、2x3等）

R Workflow (Recommended)

推荐的R工作流

Complete Example: Meta-Analysis Forest Plots

完整示例：元分析森林图

assemble_forest_plots.R

assemble_forest_plots.R

Combine multiple forest plots into a single figure

Combine multiple forest plots into a single figure

Set working directory

Set working directory

Load extraction data

Load extraction data

--- Create individual forest plots ---

--- Create individual forest plots ---

Plot 1: Pathologic complete response

Plot 1: Pathologic complete response

Save as ggplot-compatible object

Save as ggplot-compatible object

Plot 2: Event-free survival

Plot 2: Event-free survival

Plot 3: Overall survival

Plot 3: Overall survival

--- Combine with patchwork ---

--- Combine with patchwork ---

Export at 300 DPI

Export at 300 DPI

Using cowplot for More Control

使用cowplot实现更多控制

Combine with explicit panel labels and alignment

Combine with explicit panel labels and alignment

Add overall title

Add overall title

Combine title and plots

Combine title and plots

Export

Export

Grid Layout (2x2 or 2x3)

网格布局（2x2或2x3）

2x2 grid