research-figures

A figure earns its place by making one claim visible faster than the table does. Design from the claim, not from the data: decide what the reader must see, then choose the encoding that shows it.

Rules that apply to every figure

• One claim per figure. If the caption needs "and also", split it.
• Vector output (.pdf for LaTeX, .svg or 300-dpi .png for Word) at the final printed size, so fonts are not scaled. Text width in a typical thesis is about 6 inches (15 cm); set figsize accordingly and never rescale in the document.
• Fonts match the document: same family (or the closest available) and a size between the caption size and the body size (9 to 11 pt at print size). Set once in the style file.
• Colour-blind-safe palette (Okabe-Ito or viridis for sequential data). Never encode a difference by colour alone: vary marker or line style too, and check the figure in greyscale.
• Show variance: error bars, confidence bands, or individual points. State in the caption what the bar is (SD, SEM, 95% CI) and n.
• Direct labels at line ends beat legends when there are fewer than six series.
• Axes start at zero for bar charts; for line charts, start where the data live and say so. Label with quantity and unit. Log scale when the data span orders of magnitude, stated in the label.
• No chartjunk: no 3D, no gradients, no gridlines heavier than the data, no titles inside the figure (the caption is the title).
• Consistency: the same variable has the same colour in every figure of the thesis. Keep a colors dict in the style module.
• Reproducible: every figure comes from a script in figures/src/ that reads the data file and writes the output. No hand-edited figures.

Setup

figures/src/style.py:

import matplotlib as mpl
import matplotlib.pyplot as plt

OKABE_ITO = ["#0072B2", "#E69F00", "#009E73", "#D55E00", "#CC79A7", "#56B4E9", "#F0E442", "#000000"]
COLORS = {"baseline": OKABE_ITO[0], "ours": OKABE_ITO[3]}   # one entry per named series, thesis-wide

def use_thesis_style(text_width_in=6.0, ratio=0.6):
    mpl.rcParams.update({
        "figure.figsize": (text_width_in, text_width_in * ratio),
        "font.family": "serif", "font.size": 10,
        "axes.labelsize": 10, "axes.titlesize": 10,
        "xtick.labelsize": 9, "ytick.labelsize": 9, "legend.fontsize": 9,
        "axes.prop_cycle": mpl.cycler(color=OKABE_ITO),
        "axes.spines.top": False, "axes.spines.right": False,
        "axes.grid": True, "grid.alpha": 0.3, "grid.linewidth": 0.5,
        "lines.linewidth": 1.5, "lines.markersize": 4,
        "errorbar.capsize": 2,
        "savefig.bbox": "tight", "savefig.pad_inches": 0.02,
        "pdf.fonttype": 42, "ps.fonttype": 42,        # embed TrueType, editable text
        "text.usetex": False,                          # True if the LaTeX toolchain is present
    })

A figure script:

import pandas as pd, matplotlib.pyplot as plt
from style import use_thesis_style, COLORS
use_thesis_style()
df = pd.read_csv("../../results/latency.csv")
fig, ax = plt.subplots()
for name, g in df.groupby("system"):
    m, s = g.groupby("n")["ms"].mean(), g.groupby("n")["ms"].std()
    ax.plot(m.index, m, marker="o", color=COLORS[name], label=name)
    ax.fill_between(m.index, m - s, m + s, color=COLORS[name], alpha=0.2)
    ax.annotate(name, (m.index[-1], m.iloc[-1]), xytext=(4, 0), textcoords="offset points", va="center", color=COLORS[name])
ax.set_xlabel("Input size (items)"); ax.set_ylabel("Latency (ms)"); ax.set_xscale("log")
fig.savefig("../latency.pdf")

Choosing the encoding

Captions

Caption = what is shown + conditions + what to notice. "Latency by input size for the baseline and the proposed system (mean of 10 runs, shaded band is one SD, log x-axis). The proposed system's advantage grows with input size, reaching 4x at 10^5 items." The reader should get the claim from the caption without the body text.

Diagrams

For system and method diagrams use TikZ (tikzpicture with positioning and arrows.meta libraries, one shared style block for nodes) so fonts and line weights match the document. Keep each diagram in its own .tex file under figures/, \input it, and compile standalone with the standalone class to preview. Export to PDF for Word.

Before including

Print the figure at final size in greyscale. If a series cannot be told apart, or a label is under 8 pt, fix it. Check every figure is referenced in the text before it appears.

Attribution

Palette and rcParams conventions draw on thesis-figure-skill (MIT) and the Okabe-Ito palette; the encoding table and rules are this repository's.