From agent-almanac
Produces publication-ready 2D graphics with proper DPI, color profiles, typography, and export formats for academic journals, print, web, and presentations.
npx claudepluginhub pjt222/agent-almanacThis skill uses the workspace's default tool permissions.
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Creates publication-ready scientific figures with matplotlib/seaborn/plotly, including multi-panel layouts, error bars, significance annotations, colorblind-safe palettes, and journal formatting for Nature, Science, Cell.
Guides chart type selection by data structure, color palettes for accessibility/print, figure composition, and journal formatting for scientific publications. Use when preparing data visualizations for talks or submissions.
Creates journal-ready scientific plots with matplotlib, seaborn, plotly. Supports multi-panel layouts, error bars, significance markers, colorblind-safe palettes, PDF/EPS/TIFF exports.
Share bugs, ideas, or general feedback.
Produce publication-ready graphics that meet technical requirements for academic journals, books, presentations, and web publication. Covers DPI requirements, color space management, typography best practices, file format selection, and metadata embedding.
| Input | Type | Description | Example |
|---|---|---|---|
| Source graphic | File/Data | Original visualization or artwork | SVG, R ggplot, Python matplotlib, Blender render |
| Publication target | Specification | Journal, web, print, presentation | Nature journal, IEEE paper, website |
| Technical requirements | Parameters | DPI, dimensions, color space, format | 300 DPI, 180mm width, CMYK, TIFF |
| Style guide | Document | Publisher typography and formatting rules | Font families, line widths, color palette |
| Metadata | Information | Title, author, date, copyright, description | Figure caption, license info |
Identify technical specifications for target publication:
# Common publication requirements
academic_journal:
dpi: 300-600
format: TIFF, EPS, PDF
color_space: RGB or CMYK (check guidelines)
max_width: 180mm (single column) or 390mm (double column)
fonts: Embed or outline
resolution_minimums:
line_art: 1000 DPI
halftone: 300 DPI
combination: 600 DPI
web_publication:
dpi: 72-96 (retina: 144-192)
format: PNG, WebP, SVG
color_space: sRGB
max_file_size: 200KB-500KB
optimization: Compress, progressive loading
presentation:
dpi: 96-150
format: PNG, PDF, SVG
color_space: RGB
dimensions: 16:9 or 4:3 aspect ratio
contrast: High contrast for projectors
print_book:
dpi: 300-600
format: TIFF, PDF/X
color_space: CMYK
bleed: 3-5mm beyond trim
fonts: Embedded
Expected: Clear understanding of target requirements On failure: Contact publisher for specific guidelines, use conservative defaults
Configure resolution based on output medium:
from PIL import Image
def set_dpi_pillow(image_path, output_path, target_dpi=300):
"""Set DPI metadata for PNG/TIFF."""
img = Image.open(image_path)
# Save with DPI metadata
img.save(output_path, dpi=(target_dpi, target_dpi))
print(f"Saved with {target_dpi} DPI: {output_path}")
def calculate_dimensions(width_mm, height_mm, dpi=300):
"""Calculate pixel dimensions from physical size."""
# Convert mm to inches
width_inches = width_mm / 25.4
height_inches = height_mm / 25.4
# Calculate pixels
width_px = int(width_inches * dpi)
height_px = int(height_inches * dpi)
return width_px, height_px
# Example: 180mm wide figure at 300 DPI
width, height = calculate_dimensions(180, 120, dpi=300)
print(f"Required resolution: {width}x{height} pixels")
# Output: Required resolution: 2126x1417 pixels
# R ggplot2 export with proper DPI
library(ggplot2)
# Create plot
p <- ggplot(mtcars, aes(x = wt, y = mpg)) +
geom_point() +
theme_minimal(base_size = 12)
# Save for publication (300 DPI)
ggsave(
filename = "figure1.png",
plot = p,
width = 180,
height = 120,
units = "mm",
dpi = 300
)
# Save as vector for flexibility
ggsave(
filename = "figure1.pdf",
plot = p,
width = 180,
height = 120,
units = "mm",
device = cairo_pdf # Better text rendering
)
Expected: Graphics rendered at correct resolution for print quality On failure: Verify DPI metadata saved correctly, check file size appropriate
Set appropriate color profile:
from PIL import Image, ImageCms
def convert_to_cmyk(rgb_image_path, cmyk_output_path):
"""Convert RGB to CMYK for print."""
img = Image.open(rgb_image_path)
if img.mode != 'RGB':
img = img.convert('RGB')
# Convert to CMYK
cmyk_img = img.convert('CMYK')
cmyk_img.save(cmyk_output_path, format='TIFF', compression='tiff_lzw')
print(f"Converted to CMYK: {cmyk_output_path}")
def apply_srgb_profile(image_path, output_path):
"""Apply sRGB profile for web."""
img = Image.open(image_path)
# sRGB profile (embedded in Pillow)
srgb_profile = ImageCms.createProfile('sRGB')
# Convert to sRGB
img_srgb = ImageCms.profileToProfile(
img,
srgb_profile,
srgb_profile,
renderingIntent=ImageCms.Intent.PERCEPTUAL
)
img_srgb.save(output_path)
# ImageMagick for color space conversion
convert input.png -colorspace sRGB output_srgb.png
convert input.png -colorspace CMYK output_cmyk.tiff
# Check color profile
identify -verbose image.png | grep -i colorspace
Expected: Color space matches publication requirements On failure: Verify color profile embedded, test print preview
Ensure text is readable and properly formatted:
from PIL import ImageFont
def get_publication_fonts():
"""Load fonts appropriate for publication."""
# Common publication-safe fonts
fonts = {
'serif': 'Times New Roman',
'sans': 'Arial',
'mono': 'Courier New'
}
try:
# Load with proper size for DPI
# At 300 DPI, 12pt = 12 * 300/72 = 50 pixels
base_size_300dpi = 50
font_regular = ImageFont.truetype(f"{fonts['sans']}.ttf", base_size_300dpi)
font_bold = ImageFont.truetype(f"{fonts['sans']} Bold.ttf", base_size_300dpi)
return {'regular': font_regular, 'bold': font_bold}
except:
return {'regular': ImageFont.load_default(), 'bold': ImageFont.load_default()}
# Typography guidelines
typography_specs = {
'minimum_font_size': '8pt', # Readable when printed
'line_width_min': 0.5, # Points, for print clarity
'panel_labels': {
'font': 'Arial Bold',
'size': '12pt',
'position': 'top-left',
'style': 'A, B, C' # Or (a), (b), (c)
},
'axis_labels': {
'font': 'Arial',
'size': '10pt'
},
'legend': {
'font': 'Arial',
'size': '9pt',
'position': 'outside plot area'
}
}
# R publication-quality typography
library(ggplot2)
p <- ggplot(mtcars, aes(x = wt, y = mpg)) +
geom_point(size = 2) +
labs(
title = "Fuel Efficiency vs Weight",
x = "Weight (1000 lbs)",
y = "Miles per Gallon"
) +
theme_bw(base_size = 12, base_family = "Arial") +
theme(
plot.title = element_text(size = 14, face = "bold"),
axis.title = element_text(size = 12),
axis.text = element_text(size = 10),
legend.text = element_text(size = 10),
panel.grid.minor = element_blank(),
# Ensure text is black for print
text = element_text(color = "black")
)
Expected: Text readable at publication size, fonts embedded properly On failure: Increase font sizes, check font licensing, convert text to outlines
Choose format based on use case:
def export_multi_format(source_path, output_base, formats=['png', 'pdf', 'tiff']):
"""Export graphic in multiple formats."""
from PIL import Image
import cairosvg
import os
base, ext = os.path.splitext(output_base)
if ext.lower() in ['.svg']:
# SVG source - convert to rasters
for fmt in formats:
output = f"{base}.{fmt}"
if fmt == 'png':
cairosvg.svg2png(
url=source_path,
write_to=output,
output_width=2126, # 180mm @ 300 DPI
output_height=1417 # 120mm @ 300 DPI
)
elif fmt == 'pdf':
cairosvg.svg2pdf(url=source_path, write_to=output)
elif fmt == 'tiff':
# Convert via PNG intermediate
temp_png = f"{base}_temp.png"
cairosvg.svg2png(url=source_path, write_to=temp_png)
img = Image.open(temp_png)
img.save(output, format='TIFF', compression='tiff_lzw')
os.remove(temp_png)
else:
# Raster source
img = Image.open(source_path)
for fmt in formats:
output = f"{base}.{fmt}"
if fmt == 'png':
img.save(output, format='PNG', dpi=(300, 300), optimize=True)
elif fmt == 'tiff':
img.save(output, format='TIFF', compression='tiff_lzw', dpi=(300, 300))
elif fmt == 'pdf':
# Use img2pdf or similar for raster-to-PDF
img.save(output, format='PDF', resolution=300.0)
print(f"Exported in formats: {', '.join(formats)}")
# Format selection guide
format_guide = {
'TIFF': {
'use_for': 'Journal submission, archival',
'benefits': 'Lossless, supports CMYK, high quality',
'compression': 'LZW or ZIP (lossless)'
},
'PDF': {
'use_for': 'Submission, print, archival',
'benefits': 'Vector or raster, text searchable, widely accepted',
'variants': 'PDF/A (archival), PDF/X (print)'
},
'PNG': {
'use_for': 'Web, presentations, digital',
'benefits': 'Lossless, transparency, good compression',
'limitation': 'RGB only, larger than JPEG'
},
'SVG': {
'use_for': 'Web, further editing, scalable graphics',
'benefits': 'Vector, infinitely scalable, small file size',
'limitation': 'Not always accepted by journals'
},
'EPS': {
'use_for': 'Legacy journal requirements',
'benefits': 'Vector format accepted by older systems',
'limitation': 'Being phased out, use PDF instead'
}
}
Expected: Appropriate format for publication channel On failure: Check publisher requirements, provide multiple formats
Create web-optimized versions:
def optimize_for_web(input_path, output_path, max_width=1200, quality=85):
"""Optimize image for web publication."""
from PIL import Image
img = Image.open(input_path)
# Resize if too large
if img.width > max_width:
ratio = max_width / img.width
new_height = int(img.height * ratio)
img = img.resize((max_width, new_height), Image.LANCZOS)
# Convert to RGB if needed
if img.mode in ('RGBA', 'LA', 'P'):
background = Image.new('RGB', img.size, (255, 255, 255))
if img.mode == 'P':
img = img.convert('RGBA')
background.paste(img, mask=img.split()[-1] if 'A' in img.mode else None)
img = background
# Save optimized
img.save(output_path, format='JPEG', quality=quality, optimize=True, progressive=True)
# Check file size
import os
file_size_kb = os.path.getsize(output_path) / 1024
print(f"Optimized: {file_size_kb:.1f} KB")
def create_responsive_set(input_path, output_base):
"""Create multiple resolutions for responsive web."""
from PIL import Image
img = Image.open(input_path)
sizes = [
(640, '640w'),
(1024, '1024w'),
(1920, '1920w')
]
for width, suffix in sizes:
if img.width >= width:
ratio = width / img.width
height = int(img.height * ratio)
resized = img.resize((width, height), Image.LANCZOS)
output = f"{output_base}_{suffix}.jpg"
resized.save(output, format='JPEG', quality=85, optimize=True)
Expected: Web-optimized images under 500KB, responsive sizes generated On failure: Reduce quality, resize further, consider WebP format
Add descriptive metadata for archival:
from PIL import Image
from PIL.PngImagePlugin import PngInfo
def embed_metadata(image_path, output_path, metadata):
"""Embed metadata in PNG."""
img = Image.open(image_path)
# Create metadata
png_info = PngInfo()
for key, value in metadata.items():
png_info.add_text(key, str(value))
# Save with metadata
img.save(output_path, format='PNG', pnginfo=png_info)
# Example metadata
metadata = {
'Title': 'Figure 1: Relationship between weight and fuel efficiency',
'Author': 'Jane Doe',
'Description': 'Scatter plot showing negative correlation',
'Copyright': 'CC-BY 4.0',
'Software': 'R 4.3.0, ggplot2 3.4.0',
'Creation Date': '2026-02-16',
'Source': 'mtcars dataset'
}
embed_metadata('figure1.png', 'figure1_with_metadata.png', metadata)
Expected: Metadata embedded and retrievable On failure: Check format supports metadata (PNG, TIFF, PDF yes; JPEG limited)