nature-figure-guide

Nature Figure Preparation Guide

Overview

This guide provides the complete specifications for preparing figures for submission to Nature and Nature Research journals. Following these guidelines ensures smooth processing and high-quality reproduction of your figures in both print and online formats.

Official reference: https://www.nature.com/nature/for-authors/formatting-guide

Resolution Requirements

| Image Type | Minimum Resolution | Notes | |---|---|---| | All figures | 300 DPI | At maximum print size | | Optimal quality | 450 DPI+ | Recommended for best online display | | Online submission | 300 PPI max | To keep file sizes manageable |

CRITICAL: Do NOT artificially increase resolution (upsampling) in image editing software. This does not improve quality and may introduce artifacts.

Verify Resolution with Python

from PIL import Image

def check_nature_resolution(image_path):
    """Check if image meets Nature's resolution requirements."""
    img = Image.open(image_path)
    width_px, height_px = img.size
    dpi = img.info.get('dpi', (72, 72))

    print(f"Image: {image_path}")
    print(f"Dimensions: {width_px} x {height_px} px")
    print(f"DPI: {dpi[0]} x {dpi[1]}")

    if dpi[0] < 300 or dpi[1] < 300:
        print("WARNING: Resolution below 300 DPI minimum")
        print(f"  Need at least 300 DPI for Nature submission")
    elif dpi[0] >= 450:
        print("PASS: Meets optimal resolution (450+ DPI)")
    else:
        print("PASS: Meets minimum resolution (300+ DPI)")

    # Check file size
    import os
    size_mb = os.path.getsize(image_path) / (1024 * 1024)
    print(f"File size: {size_mb:.1f} MB")
    if size_mb > 10:
        print("WARNING: File exceeds 10 MB limit")

    return dpi[0] >= 300 and dpi[1] >= 300

File Format

Preferred Formats by Figure Type

| Figure Type | Preferred Format | Alternative | |---|---|---| | Line drawings, graphs, schematics | Adobe Illustrator (AI), EPS, PDF | Vector formats preserve editability | | Photographs, micrographs | Photoshop (PSD), TIFF | High-quality raster | | General purpose | JPEG (300-600 DPI) | Acceptable for most figures | | Extended Data figures | JPEG (preferred), TIFF, EPS | |

Also Accepted

• CorelDraw (up to version 8)
• Microsoft Word, Excel, PowerPoint

File Size

• Maximum: 10 MB per figure file
• Most files should be well under this limit

Important Rules

• Multi-panel figures must be assembled into a single image file
• Individual panels must NOT be uploaded separately
• Each complete figure must be a separate file upload

Figure Size and Dimensions

Nature does not specify fixed column widths for initial submission, but figures should be:

• Composed as a single image for multi-panel figures
• Sized appropriately for the intended display
• Not uploaded as individual panels

Python: Set Figure Dimensions

import matplotlib.pyplot as plt

def create_nature_figure(n_panels=1, fig_type='single_column'):
    """Create a Matplotlib figure sized for Nature."""
    if fig_type == 'single_column':
        fig_width = 3.5  # inches (approx 89 mm)
    elif fig_type == 'double_column':
        fig_width = 7.0  # inches (approx 178 mm)
    else:
        fig_width = 5.0  # 1.5 column

    fig_height = fig_width * 0.75  # default aspect ratio

    fig, axes = plt.subplots(1, n_panels, figsize=(fig_width, fig_height))
    fig.set_dpi(450)

    return fig, axes

Color Mode

• RGB recommended (wider color gamut; faithful reproduction of fluorescent colors online)
• CMYK also accepted (converted for print automatically)
• Accessibility: Use colorblind-friendly palettes

Recommended Colorblind-Safe Palette

# Nature-friendly colorblind-safe colors
NATURE_COLORS = {
    'blue':   '#0072B2',
    'orange': '#E69F00',
    'green':  '#009E73',
    'red':    '#D55E00',
    'purple': '#CC79A7',
    'cyan':   '#56B4E9',
    'yellow': '#F0E442',
    'black':  '#000000',
}

Font Requirements

| Element | Font | Size | Style | |---|---|---|---| | Body text in figures | Helvetica or Arial | 5-7 pt | Regular | | Panel labels | Helvetica or Arial | 8 pt | Bold, lowercase (a, b, c) | | Amino acid sequences | Courier | — | Monospace | | Greek characters | Symbol | — | — |

Critical Rules

• Use sans-serif fonts only (Helvetica or Arial)
• Do NOT outline text — text must remain editable
• Embed fonts as TrueType 2 or 42 (NOT TrueType 3)
• Panel labels: lowercase bold letters (a, b, c — not A, B, C)

Python: Apply Nature Font Settings

import matplotlib.pyplot as plt

def set_nature_fonts():
    """Configure Matplotlib for Nature figure fonts."""
    plt.rcParams.update({
        'font.family': 'sans-serif',
        'font.sans-serif': ['Helvetica', 'Arial'],
        'font.size': 7,
        'axes.labelsize': 7,
        'axes.titlesize': 7,
        'xtick.labelsize': 6,
        'ytick.labelsize': 6,
        'legend.fontsize': 6,
        'figure.titlesize': 8,
    })

Labeling Conventions

Figure Numbering

• Sequential: Figure 1, Figure 2, Figure 3, etc.
• All figures must be cited in the text in order

Panel Labels

• Lowercase bold letters: a, b, c, d, ...
• Font size: 8 pt bold
• Position: top-left corner of each panel

Axes and Legends

• Include units in parentheses on all axes
• Scale bars must be on separate layers (not flattened into the image)
• Figure legends placed on a separate manuscript page after References

Example Panel Labeling

import matplotlib.pyplot as plt
import string

def add_nature_panel_labels(fig, axes):
    """Add Nature-style lowercase bold panel labels."""
    if not hasattr(axes, '__iter__'):
        axes = [axes]

    for i, ax in enumerate(axes):
        label = string.ascii_lowercase[i]
        ax.text(-0.1, 1.1, label,
                transform=ax.transAxes,
                fontsize=8,
                fontweight='bold',
                va='top',
                ha='right',
                fontfamily='Arial')

Image Integrity and Manipulation Policy

Prohibited

• Flattening scale bars into the image layer
• Outlining text (must remain editable)
• Adding gridlines, patterns, or drop shadows
• Using colored text in graphs
• Publishing copyrighted images without permission

Permitted (with transparency)

• Linear brightness/contrast adjustments applied uniformly to the entire image
• Color balance corrections applied to the whole image

Best Practices

• Keep scale bars on separate layers for editability
• Avoid busy backgrounds behind text
• Remove superfluous decorative elements
• Obtain permissions for all copyrighted figures

Python Quick Start: Full Validation

from PIL import Image
import os

def validate_nature_figure(image_path):
    """Full validation of a figure against Nature requirements."""
    img = Image.open(image_path)
    issues = []

    # 1. Resolution check
    dpi = img.info.get('dpi', (72, 72))
    if dpi[0] < 300 or dpi[1] < 300:
        issues.append(f"Resolution too low: {dpi[0]}x{dpi[1]} DPI (need 300+)")

    # 2. Color mode check
    if img.mode == 'CMYK':
        issues.append("Color mode is CMYK; RGB is recommended for Nature")
    elif img.mode not in ('RGB', 'RGBA'):
        issues.append(f"Unexpected color mode: {img.mode}; use RGB")

    # 3. File size check
    size_mb = os.path.getsize(image_path) / (1024 * 1024)
    if size_mb > 10:
        issues.append(f"File size {size_mb:.1f} MB exceeds 10 MB limit")

    # 4. Format check
    fmt = img.format
    accepted = ['TIFF', 'JPEG', 'PNG', 'EPS', 'PDF']
    if fmt and fmt.upper() not in accepted:
        issues.append(f"Format '{fmt}' may not be accepted; prefer TIFF or JPEG")

    # Report
    print(f"=== Nature Figure Validation: {os.path.basename(image_path)} ===")
    print(f"Dimensions: {img.size[0]} x {img.