Getting started¶
journalfig encodes what Nature, APS, and Elsevier actually document about figures — column widths,
font sizes, panel-label conventions, minimum line weights, accepted file formats — so a figure can be
retargeted from one journal to another by changing a single string.
This notebook covers the parts that are not specific to any one kind of plot: picking a theme, exact sizing, saving, and checking compliance. The other notebooks in this folder each take one kind of figure:
| notebook | covers |
|---|---|
01_line_plots.ipynb |
line plots, the colour/linestyle cycle, greyscale safety |
02_scatter_plots.ipynb |
markers, the points-versus-points² trap, error bars |
03_histograms.ipynb |
distributions, outlines, shared bins, hatching |
04_heatmaps.ipynb |
imshow, pcolormesh, colormaps, colorbars |
05_multipanel_figures.ipynb |
multi-panel layouts, and how to make them look professional |
06_reading_and_fitting.ipynb |
reading a data file, fitting it, showing the uncertainty |
07_boxplots.ipynb |
the five-number summary, whisker conventions, comparing groups |
All data here is synthetic and all axis labels are deliberately generic — this notebook is about how a figure is built and styled, not about any particular measurement.
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%matplotlib inline
# Jupyter crops every inline preview with bbox_inches="tight". That defeats the exact column widths
# this package exists to guarantee, and because the themes sit the axes close to the canvas edge, the
# crop slices through the top and right spines. Turn it off so previews match the files jf.save() writes.
%config InlineBackend.print_figure_kwargs = {"bbox_inches": None}
# jf.save() reports what it wrote through the "journalfig" logger instead of printing. Raise that one
# logger -- a blanket logging.basicConfig(level="INFO") also switches on fontTools, which logs a dozen
# subsetting lines per PDF.
import logging
logging.basicConfig(format="%(message)s")
logging.getLogger("journalfig").setLevel(logging.INFO)
import numpy as np
import matplotlib.pyplot as plt
import journalfig as jf
# The themes render previews at 600 dpi, which makes every embedded image in a notebook large. This
# only touches the on-screen preview; jf.save() exports at savefig.dpi regardless.
PREVIEW_DPI = 150
def preview(journal, **kwargs):
"""Apply a theme, then drop the on-screen DPI so this notebook stays light."""
jf.use(journal, **kwargs)
plt.rcParams["figure.dpi"] = PREVIEW_DPI
rng = np.random.default_rng(0)
print("journalfig", jf.__version__, "| themes:", jf.JOURNALS)
%matplotlib inline
# Jupyter crops every inline preview with bbox_inches="tight". That defeats the exact column widths
# this package exists to guarantee, and because the themes sit the axes close to the canvas edge, the
# crop slices through the top and right spines. Turn it off so previews match the files jf.save() writes.
%config InlineBackend.print_figure_kwargs = {"bbox_inches": None}
# jf.save() reports what it wrote through the "journalfig" logger instead of printing. Raise that one
# logger -- a blanket logging.basicConfig(level="INFO") also switches on fontTools, which logs a dozen
# subsetting lines per PDF.
import logging
logging.basicConfig(format="%(message)s")
logging.getLogger("journalfig").setLevel(logging.INFO)
import numpy as np
import matplotlib.pyplot as plt
import journalfig as jf
# The themes render previews at 600 dpi, which makes every embedded image in a notebook large. This
# only touches the on-screen preview; jf.save() exports at savefig.dpi regardless.
PREVIEW_DPI = 150
def preview(journal, **kwargs):
"""Apply a theme, then drop the on-screen DPI so this notebook stays light."""
jf.use(journal, **kwargs)
plt.rcParams["figure.dpi"] = PREVIEW_DPI
rng = np.random.default_rng(0)
print("journalfig", jf.__version__, "| themes:", jf.JOURNALS)
journalfig 0.5.1 | themes: ('nature', 'aps', 'elsevier', 'iop', 'aip', 'acs', 'rsc', 'ieee', 'plos', 'wiley', 'pnas', 'science')
Pick a theme by journal name¶
jf.use() takes a theme key or any alias the package knows, so you can name the journal you are
actually submitting to.
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for name in ["Nature", "npj", "PRB", "Physical Review Letters", "Acta Materialia", "JNCS"]:
print(f"{name:28s} -> {jf.resolve(name)}")
for name in ["Nature", "npj", "PRB", "Physical Review Letters", "Acta Materialia", "JNCS"]:
print(f"{name:28s} -> {jf.resolve(name)}")
Nature -> nature npj -> nature PRB -> aps Physical Review Letters -> aps Acta Materialia -> elsevier JNCS -> elsevier
What each publisher requires¶
Every number below is read from the publisher's own document. jf.source() reports which document,
and when its numbers were last checked — a specification is only as trustworthy as that date.
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for journal in jf.JOURNALS:
spec = jf.get_spec(journal)
widths = ", ".join(f"{name} {mm:.0f} mm" for name, mm in sorted(spec.widths_mm.items()))
print(f"{spec.name}")
print(f" widths : {widths}")
faces = ", ".join(spec.font_families) or "no typeface stated"
print(f" base font : {spec.font_sizes['base']:.0f} pt, {faces}")
print(f" panel label : {spec.panel_label_fmt.format('a')} at {spec.panel_label_pt:.0f} pt")
print(f" writes : {', '.join(f.upper() for f in spec.formats)}")
print(f" accepts : {', '.join(f.upper() for f in spec.submission_formats)}")
print(f" source : {jf.source(journal)}")
for journal in jf.JOURNALS:
spec = jf.get_spec(journal)
widths = ", ".join(f"{name} {mm:.0f} mm" for name, mm in sorted(spec.widths_mm.items()))
print(f"{spec.name}")
print(f" widths : {widths}")
faces = ", ".join(spec.font_families) or "no typeface stated"
print(f" base font : {spec.font_sizes['base']:.0f} pt, {faces}")
print(f" panel label : {spec.panel_label_fmt.format('a')} at {spec.panel_label_pt:.0f} pt")
print(f" writes : {', '.join(f.upper() for f in spec.formats)}")
print(f" accepts : {', '.join(f.upper() for f in spec.submission_formats)}")
print(f" source : {jf.source(journal)}")
Nature Portfolio widths : double 183 mm, onehalf 120 mm, onehalf_wide 136 mm, single 89 mm base font : 7 pt, Arial, Helvetica, Helvetica Neue panel label : a at 8 pt writes : PDF, SVG, PNG accepts : PDF source : Nature Portfolio, Guide to Preparing Final Artwork (retrieved 2026-07-28) American Physical Society (PRB/PRL) widths : double 178 mm, onehalf 135 mm, single 86 mm base font : 9 pt, Times New Roman, Times panel label : (a) at 9 pt writes : PDF, SVG, PNG accepts : PDF, EPS source : APS Journals Style Guide for Authors, November 2024 (retrieved 2026-07-28) Elsevier widths : double 190 mm, onehalf 140 mm, single 90 mm base font : 7 pt, Arial, Times New Roman panel label : (a) at 8 pt writes : PDF, SVG, PNG accepts : PDF, EPS, TIFF, JPEG, JPG source : Elsevier, Artwork sizing (retrieved 2026-07-28) IOP Publishing widths : double 150 mm, single 85 mm base font : 8 pt, Times, Helvetica panel label : (a) at 8 pt writes : PDF, SVG, PNG accepts : PDF, EPS, TIFF, PNG, JPEG, JPG source : IOP Publishing, Figures for journal articles (retrieved 2026-08-24) AIP Publishing widths : double 170 mm, single 85 mm base font : 9 pt, no typeface stated panel label : (a) at 8 pt writes : PDF, SVG, PNG accepts : PDF, EPS, PS, TIFF, PNG, JPEG, JPG, SVG source : AIP Publishing, Author Instructions (retrieved 2026-08-24) ACS Publications widths : double 178 mm, single 85 mm base font : 8 pt, Helvetica, Arial panel label : (a) at 8 pt writes : PDF, SVG, PNG accepts : EPS, TIFF, PNG, JPEG, JPG source : ACS Publications, Author Guidelines (ACS Catalysis) (retrieved 2026-08-24) Royal Society of Chemistry widths : double 171 mm, single 83 mm base font : 7 pt, Arial, Helvetica panel label : (a) at 8 pt writes : PDF, SVG, PNG accepts : TIFF, EPS, PDF source : Royal Society of Chemistry, Author guidelines for Chemical Science (retrieved 2026-08-24) IEEE widths : double 182 mm, single 89 mm base font : 9 pt, Helvetica, Times New Roman, Arial, Cambria, Symbol panel label : (a) at 9 pt writes : PDF, SVG, PNG accepts : PS, EPS, PDF, PNG, TIFF source : IEEE Author Center, Improve Your Graphics (retrieved 2026-08-24) PLOS widths : double 190 mm, single 67 mm base font : 8 pt, Arial, Times panel label : (a) at 8 pt writes : PDF, SVG, PNG accepts : TIFF, EPS source : PLOS, Figures (retrieved 2026-08-24) Wiley widths : double 180 mm, single 80 mm base font : 8 pt, no typeface stated panel label : (a) at 8 pt writes : PDF, SVG, PNG accepts : EPS, PDF, TIFF, PNG source : Wiley, Guidelines for the Preparation of Figures, 1 September 2016 (retrieved 2026-08-24) PNAS widths : double 178 mm, onehalf 114 mm, single 87 mm base font : 8 pt, Arial, Helvetica, Times panel label : (a) at 8 pt writes : PDF, SVG, PNG accepts : TIFF, EPS, PDF source : PNAS, Digital Art Guidelines, 16 February 2022 (retrieved 2026-08-24) Science (AAAS) widths : double 183 mm, single 90 mm base font : 8 pt, Arial, Helvetica panel label : a at 10 pt writes : PDF, SVG, PNG accepts : PDF, EPS, SVG source : Science (AAAS), Guide to Preparing Figures, 2025 (retrieved 2026-08-24)
Your first figure¶
Use jf.subplots() rather than plt.subplots(figsize=...). It pins the exact size, which a plain
plt.subplots loses: interactive backends round a new figure to whole device pixels, turning a
requested 183.0 mm into 182.88 mm.
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preview("elsevier")
x = np.linspace(0, 10, 200)
fig, ax = jf.subplots("elsevier", width="single")
ax.plot(x, np.sin(x), label="Series A")
ax.plot(x, np.sin(x + 0.6), label="Series B")
ax.set_xlabel("x (a.u.)")
ax.set_ylabel("y (a.u.)")
ax.legend()
preview("elsevier")
x = np.linspace(0, 10, 200)
fig, ax = jf.subplots("elsevier", width="single")
ax.plot(x, np.sin(x), label="Series A")
ax.plot(x, np.sin(x + 0.6), label="Series B")
ax.set_xlabel("x (a.u.)")
ax.set_ylabel("y (a.u.)")
ax.legend()
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<matplotlib.legend.Legend at 0x112d6e900>
Exact widths, every time¶
width= takes a layout name from the journal's spec, or an explicit width in millimetres.
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for journal in jf.JOURNALS:
for name in sorted(jf.get_spec(journal).widths_mm):
w_in, h_in = jf.figsize(journal, name)
print(f"{journal:9s} {name:13s} {w_in * 25.4:7.2f} x {h_in * 25.4:6.2f} mm")
for journal in jf.JOURNALS:
for name in sorted(jf.get_spec(journal).widths_mm):
w_in, h_in = jf.figsize(journal, name)
print(f"{journal:9s} {name:13s} {w_in * 25.4:7.2f} x {h_in * 25.4:6.2f} mm")
nature double 183.00 x 113.10 mm nature onehalf 120.00 x 74.16 mm nature onehalf_wide 136.00 x 84.05 mm nature single 89.00 x 55.01 mm aps double 177.80 x 109.89 mm aps onehalf 134.94 x 83.40 mm aps single 85.72 x 52.98 mm elsevier double 190.00 x 117.43 mm elsevier onehalf 140.00 x 86.52 mm elsevier single 90.00 x 55.62 mm iop double 150.00 x 92.71 mm iop single 85.00 x 52.53 mm aip double 169.90 x 105.00 mm aip single 85.00 x 52.53 mm acs double 177.80 x 109.89 mm acs single 84.70 x 52.35 mm rsc double 171.00 x 105.68 mm rsc single 83.00 x 51.30 mm ieee double 181.90 x 112.42 mm ieee single 88.90 x 54.94 mm plos double 190.50 x 117.74 mm plos single 66.80 x 41.28 mm wiley double 180.00 x 111.25 mm wiley single 80.00 x 49.44 mm pnas double 178.00 x 110.01 mm pnas onehalf 114.00 x 70.46 mm pnas single 87.00 x 53.77 mm science double 183.00 x 113.10 mm science single 90.00 x 55.62 mm
Height defaults to the inverse golden ratio. Override it with ratio= or height_mm= — and for
anything with more than one row you should, because the golden ratio is far too short there.
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print("golden :", [round(v, 3) for v in jf.figsize("aps", "single")])
print("ratio=0.8 :", [round(v, 3) for v in jf.figsize("aps", "single", ratio=0.8)])
print("height_mm=40:", [round(v, 3) for v in jf.figsize("aps", "single", height_mm=40)])
print("golden :", [round(v, 3) for v in jf.figsize("aps", "single")])
print("ratio=0.8 :", [round(v, 3) for v in jf.figsize("aps", "single", ratio=0.8)])
print("height_mm=40:", [round(v, 3) for v in jf.figsize("aps", "single", height_mm=40)])
golden : [3.375, 2.086] ratio=0.8 : [3.375, 2.7] height_mm=40: [3.375, 1.575]
Saving¶
Every theme writes PDF, SVG and PNG: the file you submit, one to edit in Inkscape or Illustrator, and
one for a talk. Ask for anything else with formats=.
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import tempfile
from pathlib import Path
outdir = Path(tempfile.mkdtemp())
preview("nature")
fig, ax = jf.subplots("nature", width="single")
ax.plot(x, np.sin(x))
ax.set_xlabel("x (a.u.)")
ax.set_ylabel("y (a.u.)")
jf.save(fig, outdir / "figure_01")
print()
for path in sorted(outdir.iterdir()):
print(f" {path.name:22s} {path.stat().st_size / 1024:7.1f} kB")
import tempfile
from pathlib import Path
outdir = Path(tempfile.mkdtemp())
preview("nature")
fig, ax = jf.subplots("nature", width="single")
ax.plot(x, np.sin(x))
ax.set_xlabel("x (a.u.)")
ax.set_ylabel("y (a.u.)")
jf.save(fig, outdir / "figure_01")
print()
for path in sorted(outdir.iterdir()):
print(f" {path.name:22s} {path.stat().st_size / 1024:7.1f} kB")
Nature Portfolio: 89.0 x 55.0 mm -> figure_01.pdf, figure_01.svg, figure_01.png
figure_01.pdf 17.5 kB figure_01.png 50.2 kB figure_01.svg 38.5 kB
The declared width survives into the file — jf.save() forces bbox_inches=None, because a tight
bounding box crops an 89 mm figure to about 87.9 mm.
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import re
fig, ax = jf.subplots("nature", width="double")
ax.plot(x, np.sin(x))
(pdf_path,) = jf.save(fig, outdir / "width_check", formats=["pdf"], validate=False)
box = re.search(rb"/MediaBox\s*\[([^\]]*)\]", pdf_path.read_bytes()).group(1).split()
width_mm = (float(box[2]) - float(box[0])) / 72 * 25.4
print(f"PDF MediaBox width: {width_mm:.4f} mm (Nature double column is 183 mm)")
import re
fig, ax = jf.subplots("nature", width="double")
ax.plot(x, np.sin(x))
(pdf_path,) = jf.save(fig, outdir / "width_check", formats=["pdf"], validate=False)
box = re.search(rb"/MediaBox\s*\[([^\]]*)\]", pdf_path.read_bytes()).group(1).split()
width_mm = (float(box[2]) - float(box[0])) / 72 * 25.4
print(f"PDF MediaBox width: {width_mm:.4f} mm (Nature double column is 183 mm)")
Nature Portfolio: 183.0 x 113.1 mm -> width_check.pdf
PDF MediaBox width: 183.0000 mm (Nature double column is 183 mm)
Compliance checking¶
jf.check() reports what a publisher would object to. The most common one is invisible on screen:
matplotlib shrinks maths sub/superscripts to 0.7x, so a 7 pt Elsevier label renders a subscript at
4.9 pt against a hard 6 pt floor.
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jf.use("elsevier")
fig, ax = jf.subplots("elsevier", width="single")
ax.plot(x, np.sin(x))
ax.set_xlabel("$x_{1}$ (a.u.)")
ax.set_ylabel("$y_{2}$ (a.u.)")
for violation in jf.check(fig, warn=False):
print(violation)
plt.close(fig)
jf.use("elsevier")
fig, ax = jf.subplots("elsevier", width="single")
ax.plot(x, np.sin(x))
ax.set_xlabel("$x_{1}$ (a.u.)")
ax.set_ylabel("$y_{2}$ (a.u.)")
for violation in jf.check(fig, warn=False):
print(violation)
plt.close(fig)
[subscript] '$x_{1}$ (a.u.)' renders sub/superscripts at 4.90 pt (7.0 pt x 0.7), below the 6 pt floor
[subscript] '$y_{2}$ (a.u.)' renders sub/superscripts at 4.90 pt (7.0 pt x 0.7), below the 6 pt floor
The fix is to scale the whole theme up, which base_size= does proportionally:
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preview("elsevier", base_size=9)
fig, ax = jf.subplots("elsevier", width="single")
ax.plot(x, np.sin(x))
ax.set_xlabel("$x_{1}$ (a.u.)")
ax.set_ylabel("$y_{2}$ (a.u.)")
print("violations:", jf.check(fig, warn=False))
preview("elsevier", base_size=9)
fig, ax = jf.subplots("elsevier", width="single")
ax.plot(x, np.sin(x))
ax.set_xlabel("$x_{1}$ (a.u.)")
ax.set_ylabel("$y_{2}$ (a.u.)")
print("violations:", jf.check(fig, warn=False))
violations: []
It also catches the one failure that leaves no trace in the figure: a missing font. Ask for Arial
on a machine without it and matplotlib silently draws DejaVu Sans instead. jf.fonts() shows what
each face really resolved to — exact for a face the publisher names, substitute for a metrically
compatible stand-in (which passes), fallback for anything else.
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for journal in jf.JOURNALS:
jf.use(journal)
status = jf.fonts()["text"]
print(f"{journal:9s} {status.resolved:20s} {status.status}")
for journal in jf.JOURNALS:
jf.use(journal)
status = jf.fonts()["text"]
print(f"{journal:9s} {status.resolved:20s} {status.status}")
nature Arial exact
aps Times New Roman exact elsevier Arial exact iop Times New Roman fallback aip Times New Roman unrestricted acs Arial exact rsc Arial exact ieee Arial exact plos Arial exact wiley Arial unrestricted pnas Arial exact science Arial exact
Temporary themes¶
jf.context() restores the previous rcParams on exit, and the themes are registered with matplotlib
itself, so plain plt.style.use works too after importing the package.
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jf.use("nature")
print("outside:", plt.rcParams["font.size"])
with jf.context("aps"):
print("inside :", plt.rcParams["font.size"])
print("after :", plt.rcParams["font.size"])
print("registered styles:", [s for s in plt.style.available if s in jf.JOURNALS])
jf.use("nature")
print("outside:", plt.rcParams["font.size"])
with jf.context("aps"):
print("inside :", plt.rcParams["font.size"])
print("after :", plt.rcParams["font.size"])
print("registered styles:", [s for s in plt.style.available if s in jf.JOURNALS])
outside: 7.0 inside : 9.0 after : 7.0 registered styles: ['acs', 'aip', 'aps', 'elsevier', 'ieee', 'iop', 'nature', 'plos', 'pnas', 'rsc', 'science', 'wiley']