| name | ssci-plots |
|---|---|
| description | Publication-ready statistical figures for SSCI/SCI journals across psychology, economics, public health, sociology, political science, geography, methodology. Validated matplotlib styling, CVD-safe palettes (Tol, Okabe-Ito, ggsci, aesthetic sets), APA 7 formatting, 12 journal presets (APA, Elsevier, Wiley, SAGE, Psych Science, ASA, Nature, Science, NEJM, Lancet, BMJ, JAMA), 55+ chart types. Use when creating academic figures, path/SEM diagrams, heatmaps, forest plots, error-bar charts, mediation diagrams, event-study plots, RD plots, Kaplan-Meier curves, choropleths, causal DAGs, or any journal submission figure. Also use for publication-quality figures even without explicit "APA" or "SSCI" mention. Keywords: academic figure, APA figure, SSCI chart, path model, forest plot, heatmap, Kaplan-Meier, event-study, RD plot, DID, coefficient plot, choropleth, causal DAG, multi-panel, journal submission figure, 学术统计图, 论文图表, APA格式, SSCI图表, 路径模型, 森林图, 热力图, 中介模型, 事件研究, 断点回归, 生存曲线, 多面板图, 心理学可视化, 经济学图表, 公共卫生图表, 期刊投稿 |
Three design commitments guide every figure this Skill produces:
-
Data-ink ratio: Every pixel should convey data. Remove gridlines, 3D effects, and decorative elements -- they add visual noise without information value (Tufte, 1983). Use clean L-shaped axes (top and right spines off).
-
Colorblind-safe and grayscale-compatible: About 8% of male readers have red-green color vision deficiency. Categorical palettes default to validated CVD-safe sets (Tol, 2021; Wong, 2011; Okabe & Ito, 2008) and pair color with a redundant channel (line style, marker shape, or hatching) so every figure remains readable in grayscale print. Journal-anchored palettes (NPG, AAAS, NEJM, Lancet, BMJ, JAMA) are provided to match house style at submission and are flagged with their CVD grade in
list_palettes(). -
Clean figure + separate text: The saved image contains only the data visualization (axes, data, legend). Figure number, title, and Note are output as standalone Markdown text for the user to place in the manuscript. This matches APA 7th Edition requirements and most journal submission guidelines where captions are supplied separately from image files.
Initialize the style system at the start of every figure:
from scripts.ssci_style import *
apply_style() # 70+ rcParams, colormaps, fonts
apply_style(journal='nejm') # Auto-loads matching palette + sizes
apply_style(journal='psych_science', mode='slides') # Larger fonts for talksBefore writing code, identify:
- (a) Chart type from the decision table below (or its chart-family reference file)
- (b) Target journal, if the user specifies one (12 presets available)
- (c) Number of groups or conditions (determines palette size)
- (d) Error metric: SE, SD, or 95% CI
Run apply_style() to set all rcParams, register colormaps, and embed fonts.
If the user specifies a target journal, pass it as an argument and read references/journal-presets.md for details:
# Available journal keys (12):
# apa, elsevier, wiley, sage, psych_science, asa,
# nature, science, nejm, lancet, bmj, jama
apply_style(journal='lancet')apply_style(journal=...) also auto-loads the matching default palette via axes.prop_cycle (e.g. journal='nejm' activates the nejm palette). For slide / poster usage, add mode='slides' to bump font sizes without touching the underlying preset.
Open references/chart-type-guide.md first. It is the Index to the 55-chart catalog and routes you to one of the four chart-family files (chart-types-core.md, chart-types-models.md, chart-types-causal-econ.md, chart-types-applied.md) or the quick-reference file. Follow the design elements, parameters, and code patterns documented there.
Color selection:
- Categorical data:
get_palette(n)returns n CVD-safe hex colors (default: Tol Bright). Usecategory=/name=for discipline- or journal-anchored alternatives. - Emphasis focal + reference pair:
get_emphasis_pair(focal=..., reference=...)returns two colors for "focal series vs neutral reference" patterns (treatment vs control, event-study, simple slopes). - Heatmap:
get_diverging_cmap('BuRd')withTwoSlopeNorm(vcenter=0)for zero-centered diverging data. - Sequential data:
get_sequential_cmap('viridis')(perceptually uniform); alsocividis / plasma / inferno / magma / Blues / Oranges / tailwind_slate. - Multi-panel composition: see
references/multi-panel.mdforcompose_grid/small_multiples/add_inset/ shared legend & colorbar / marginal histogram. - Always pair color with redundant coding (
LINE_STYLES,MARKERS, orHATCHESfromssci_style).
Check every item in the Quality Checklist (Section 6 below) before saving.
If the figure includes statistical annotations (p-values, effect sizes, CI, inline statistics), read references/statistical-annotations.md for exact formatting rules. For APA figure text formatting details (number, title, Note, multi-panel conventions, mediation diagram conventions), read references/apa-figure-standards.md.
Save the figure in multiple formats using save_figure():
save_figure(fig, 'fig_1') # Default: PDF + PNG (600 DPI)
save_figure(fig, 'fig_1', formats=('pdf', 'tiff')) # Journal submission (RGB TIFF)Then output the figure description text separately as Markdown, using format_apa_figure_text():
text = format_apa_figure_text(
figure_number=1,
title="Mean Anxiety Scores by Treatment Condition and Time Point",
note_text="N = 354. PSS = perceived stress scale; SWB = subjective well-being.",
p_levels=[("*", ".05"), ("**", ".01"), ("***", ".001")],
error_bar_type="95ci", # auto-emits standard error-bar statement
)Output format:
Figure 1
Mean Anxiety Scores by Treatment Condition and Time Point
Note. N = 354. Error bars represent 95% confidence intervals. PSS = perceived stress scale; SWB = subjective well-being.
*p < .05. **p < .01. ***p < .001.
The full catalog has 55 chart types organized by family. Use this top-level table for routing; then load the chart-family file for the detailed 6-section spec.
| Family | File | Chart sections (representative) |
|---|---|---|
| Core distribution & relationship | chart-types-core.md |
§1 Grouped Bar, §2 Error Bar, §3 Line, §3.1 Annotated Time Series, §4 Scatter+Regression, §4.1 Scatter with Marginal Histogram, §5 Box, §6 Violin, §7 Correlation Heatmap |
| Statistical model output | chart-types-models.md |
§8 Forest, §8.1 Coefficient/Dot-Whisker, §9 Path/SEM, §9.1 IV Diagram, §10 Mediation (incl. §10.1 Serial, §10.2 Parallel), §11 Interaction, §11.1 Categorical Moderator, §11.2 Continuous Marginal Effect, §12 Simple Slopes, §17 Scree+Parallel Analysis, §18 Profile (LPA/LCA), §19 Growth Curve, §32 Specification Curve, §33 Causal DAG |
| Causal inference / econometrics | chart-types-causal-econ.md |
§22 Event-Study Coefficient Plot, §23 DID Parallel Trends, §24 Regression Discontinuity, §25 Binned Scatter (Binscatter), §26 Coefficient Plot multi-model, §38 IV Diagram |
| Applied / specialty | chart-types-applied.md |
§14 Raincloud, §16 Funnel, §20 Kaplan-Meier (with at-risk table), §21 Bland-Altman, §27 Ridgeline/Joy, §28 Choropleth, §29 ROC + Calibration, §30 Mobility Transition Matrix, §31 Marginal Effects |
| Quick reference (one-page each) | chart-types-quick-reference.md |
§15.1 Histogram, §15.2 Density (KDE), §15.3 Swarm/Beeswarm, §15.4 Factor Loading, §15.5 Johnson-Neyman, §15.6 CONSORT, §15.7 Lollipop, §15.8 Slope/Bump, §15.9 Dumbbell, §15.10 Population Pyramid, §15.11 Tornado/Butterfly |
| Multi-panel composition | multi-panel.md |
compose_grid, small_multiples, add_inset, shared legend/colorbar, marginal histogram, subfigures |
| Discipline | Primary chart-family file |
|---|---|
| Psychology — descriptive | chart-types-core.md |
| Psychology — modeling (SEM, mediation, forest, simple slopes, growth) | chart-types-models.md |
| Economics — causal (event-study, DID, RD, IV, binscatter) | chart-types-causal-econ.md |
| Public health & medicine (KM, ROC, funnel, Bland-Altman) | chart-types-applied.md |
| Sociology (mobility matrix, ridgeline) | chart-types-applied.md |
| Political science (annotated time series, ideological scaling, choropleth) | chart-types-applied.md + chart-types-core.md §3.1 |
| Geography (choropleth, spatial overlays) | chart-types-applied.md |
| Methodology / robustness (specification curve, DAG) | chart-types-models.md |
| Data / Analysis | Recommended chart | Section anchor |
|---|---|---|
| Group mean comparison (t-test, ANOVA) | Grouped bar + error bars | core §1 |
| Group means with uncertainty (cleaner than bars) | Error bar / dot-and-whisker | core §2 |
| Trend over time / repeated measures | Line chart with CI bands | core §3 |
| Time series with event markers (policy, intervention) | Annotated time series | core §3.1 |
| Two continuous variables (r, regression) | Scatter + regression line | core §4 |
| Distribution shape comparison | Box plot | core §5 |
| Distribution with density | Violin plot | core §6 |
| Multi-variable correlation matrix | Lower-triangle heatmap | core §7 |
| Meta-analysis effect sizes | Forest plot | models §8 |
| Multi-model coefficients side-by-side | Coefficient / dot-whisker plot | models §8.1, econ §26 |
| SEM / CFA path structure | Path diagram | models §9 |
| Instrumental variable identification | IV diagram | models §9.1 / econ §38 |
| Mediation pathway (a, b, c') | Mediation diagram | models §10 |
| Moderation / interaction | Interaction / simple slopes | models §11, §12 |
| Continuous moderator marginal effect | Marginal effects plot | applied §31 |
| Factor structure (EFA/PCA) | Scree + parallel analysis | models §17 |
| Latent profile / class structure | Profile plot (LPA/LCA) | models §18 |
| Individual trajectories | Growth curve | models §19 |
| Robustness across specifications | Specification curve | models §32 |
| Causal assumptions diagram | DAG | models §33 |
| Difference-in-differences design | Event-study or DID parallel trends | econ §22, §23 |
| Sharp cutoff design | Regression discontinuity plot | econ §24 |
| Large-N continuous-X relationship | Binned scatter (binscatter) | econ §25 |
| Full distribution + mean + density | Raincloud plot | applied §14 |
| Publication bias / small-study effects | Funnel plot | applied §16 |
| Time-to-event analysis | Kaplan-Meier survival curve | applied §20 |
| Method comparison agreement | Bland-Altman plot | applied §21 |
| Multi-group distribution stack | Ridgeline / joy plot | applied §27 |
| Geographic distribution | Choropleth map | applied §28 |
| Diagnostic / prediction performance | ROC + calibration | applied §29 |
| Categorical transition / mobility | Mobility transition matrix | applied §30 |
| Multi-panel composite | Multi-panel composition | multi-panel.md |
When NOT to use:
- Bar chart for continuous distributions -- use violin, box, or raincloud instead (Weissgerber et al., 2015)
- Rainbow / jet colormap -- use viridis, cividis, or Tol diverging schemes
- Pie chart -- use grouped bar chart (APA does not define pie chart standards)
- 3D charts -- use 2D with faceting or color encoding
- Sankey -- use mobility transition matrix (zero new deps; sociology-standard alternative)
Set automatically by apply_style(). Override via plt.rcParams[...] after the call. All numeric defaults live in scripts/ssci_style.py; never copy them across docs (SSOT).
| Parameter | Rationale |
|---|---|
font.family (sans-serif) |
APA 7th recommends sans-serif for figures |
font.size (8 pt body) |
APA range 8--14 pt; 8 pt is legible at print column width |
axes.spines.top / right = False |
L-shaped axes maximize data-ink ratio |
axes.linewidth |
Exceeds APA minimum 0.5 pt; clear at print |
savefig.dpi |
Meets APA, Wiley, OUP, ASA line-art requirements |
pdf.fonttype = 42 |
TrueType embedding; journals reject Type 3 fonts |
mathtext.fontset = 'custom' (Arial italic) |
Render r, t, F, p in body font (P0 fix) |
errorbar.capsize |
Visible cap without visual clutter |
constrained_layout enabled |
Prevents label clipping in multi-panel figures |
Full parameter set: scripts/ssci.mplstyle (loaded by apply_style()).
21 categorical palettes are registered (_PALETTE_REGISTRY in scripts/ssci_style.py). HEX values live exclusively in the SSOT; the table below references palettes by name only. Discover at runtime via list_palettes(category=..., publication_grade=...).
| Category | Palettes |
|---|---|
| General CVD-safe (default) | tol_bright (default), okabe_ito, high_contrast, ibm, tol_vibrant |
| Journal-anchored (ggsci R, GPL-3 credit) | nature_npg, science_aaas, nejm, lancet, jama, bmj |
| Discipline-anchored | economics (Stata s2color), tailwind_slate (modern slate scale) |
| Aesthetic publication-grade | tol_muted, tol_light, tol_medium_contrast, metbrewer_hiroshige, metbrewer_cassatt2, uk_gov_af, economist_chart, bbc_bbplot |
| Aesthetic supplement (deferred, opt-in) | 17 candidates in AESTHETIC_PALETTES; opt-in via register_aesthetic_palette(name) which emits a warning that they are not publication-grade |
| Colormap | Use | API |
|---|---|---|
ssci_BuRd |
Correlation heatmap (blue-white-red, zero-anchored) | get_diverging_cmap('BuRd') |
ssci_PRGn |
CVD-safer diverging alternative | get_diverging_cmap('PRGn') |
ssci_sunset |
Tol Sunset diverging | get_diverging_cmap('sunset') |
viridis / cividis / plasma / inferno / magma |
Sequential (perceptually uniform) | get_sequential_cmap('viridis') etc. |
ssci_Blues / ssci_Oranges / ssci_tailwind_slate |
Single-hue sequential | get_sequential_cmap('Blues') etc. |
| Grayscale | B&W-only output | get_grayscale(n) (n ∈ {2,3,4,5}) |
Pair every color encoding with a redundant channel: line style (LINE_STYLES), marker shape (MARKERS), or hatching (HATCHES).
Full palette catalog, academic citations, license credits, decision tree, and journal/discipline anchoring: references/color-system.md.
FIGURE_SIZES in scripts/ssci_style.py registers 30 named sizes: 3 generic layouts (single_column, one_half_column, full_width) + 27 chart-type-specific keys. Use the key, not the literal inches:
fig, ax = plt.subplots(figsize=FIGURE_SIZES['event_study'])
fig, ax = plt.subplots(figsize=FIGURE_SIZES['km_plot'])
compose_grid("ABCD", figsize='full_width')For one-off dimensions, fig_size(width_cm, height_cm) converts to inches.
Journal-specific column widths differ across the 12 presets; calling apply_style(journal=...) selects the right dimensions automatically (see JOURNAL_PRESETS in ssci_style.py for exact mm / DPI per preset). Full table: references/journal-presets.md.
All 27 public helpers defined in scripts/ssci_style.py. Full NumPy-style docstrings (Parameters / Returns / Raises / Examples) live with each function.
| Function | Purpose |
|---|---|
apply_style(journal=None, *, mode='paper') |
Apply 70+ rcParams, register colormaps, set font embedding. journal ∈ 12 keys (auto-loads matching palette + sizes); mode='slides' bumps fonts for talks. |
fig_size(width_cm, height_cm) |
Convert centimetres to inches for matplotlib figsize |
save_figure(fig, name, output_dir='.', dpi=600, formats=('pdf','png')) |
Save in multiple formats; TIFF support via Pillow (RGB on white background) |
| Function | Purpose |
|---|---|
get_palette(n, name='tol_bright', *, category=None, return_emphasis=False) |
Return n CVD-safe categorical hex colors; optional category filter; return_emphasis=True returns (focal, reference) pair |
get_grayscale(n) |
Return n grayscale hex values (n ∈ {2..5}) |
get_diverging_cmap(name='BuRd', N=256) |
Diverging colormap object: `'BuRd' |
get_sequential_cmap(name='viridis', N=256) |
Sequential colormap: built-ins or single-hue (Blues / Oranges / tailwind_slate) |
list_palettes(category=None, publication_grade=None) |
Introspect registered palettes; returns list of dicts with name / category / publication_grade / cvd_grade / max_colors / source |
get_emphasis_pair(focal=None, *, reference=...) |
Return (focal, reference) pair for "treatment vs control" patterns; default reference is neutral gray (see SSOT); named focals: blue / red / green / orange / purple / navy / maroon |
register_aesthetic_palette(name, hex_list=None, *, acknowledge_non_publication_grade=True) |
Opt-in registration of aesthetic / mood palettes; emits warning that they are not publication-grade |
| Function | Purpose |
|---|---|
format_p_value(p, style='apa') |
APA p-value string: `'apa' |
p_to_stars(p) |
Convert p to '***' / '**' / '*' / 'n.s.' |
format_apa_figure_text(figure_number, title, note_text=..., specific_notes=..., p_levels=..., *, error_bar_type=None, model_fit=None, zwsp=True) |
Generate APA figure description as Markdown; error_bar_type ∈ {'se','sd','95ci','within_subject_ci'}; model_fit for SEM stats |
| Function | Purpose |
|---|---|
add_significance_bracket(ax, x1, x2, y, p_value, height=0.02, ...) |
Draw significance bracket with auto p-to-stars (emits 'n.s.' for non-significant) |
annotate_effect_size(ax, d, ci=None, x=0.95, y=0.95, label='d', ...) |
Annotate effect size (Cohen's d/g/r) with optional CI on axes |
add_inline_stats(ax, items, position='top_left', *, fontsize=None, bbox=False, italic_latin=True) |
Position-preset inline statistic block (dict or list of (key, value) / (key, value, ci)); auto-italicises Latin symbols (r, t, F, p, d) |
add_reference_line(ax, value, orientation='horizontal', *, color=None, linestyle='--', label=None, label_position='right_top', zorder=0.5) |
Add zero-line / threshold reference; default color from NEUTRAL['reference']; label positions right_top / right_bottom / left_top / left_bottom / center |
| Function | Purpose |
|---|---|
remove_spines(ax, keep=('bottom','left')) |
Remove spines except those listed (L-shaped axes by default) |
setup_legend(ax, loc='best', ncol=1, frameon=False, title=None, ...) |
Clean legend following APA conventions |
add_panel_labels(axes, labels=None, style=None, fontsize=None, *, journal=None, prefix='', suffix='', overlay_bg=None) |
Add A, B, C panel labels; auto-styled per _ACTIVE_PRESET (e.g. Nature uses lowercase a/b/c, Science uses uppercase A/B/C); prefix='(' + suffix=')' add parentheses for any journal that requires them; journal= overrides for one-off mixing |
compose_grid(layout, figsize='full_width', *, width_ratios=None, height_ratios=None, share=False, panel_labels='auto', ...) |
Asymmetric mosaic via subplot_mosaic; pre-validates rectangular layout (raises SSCIPlotsMosaicError on L-shape) |
small_multiples(n_rows, n_cols, figsize='full_width', *, share='all', panel_labels='auto', ...) |
Isomorphic grid for repeated comparisons |
add_inset(ax, bbox=(0.55,0.55,0.4,0.4), *, xlim=None, ylim=None, zoom_indicator=False, hide_ticks=False) |
Inset axes with optional zoom indicator (NEJM-style) |
add_marginal_hist(ax, x, y, *, bins=30, size='20%', kind='hist', hide_inner=True) |
Top + right marginal axes for scatter (kde requires scipy) |
add_shared_colorbar(fig, mappable, axes=None, *, label=None, location='right', shrink=0.7, extend='neither') |
Single colorbar spanning multiple panels |
add_shared_legend(fig, handles_or_axes, labels=None, *, loc='lower center', ncol=None, region=None, deduplicate=True) |
Single figure-level legend with deduplicated handles |
compose_subfigures(n_rows, n_cols, figsize='full_width', *, per_subfig_suptitle=None, ...) |
Wrap Figure.subfigures for Nature-style grouped panels |
(Count check: 3 style/save + 7 palette + 3 APA + 4 annotation + 10 layout = 27 public helpers. See _ssot_signature_lock.md for the exact accounting.)
Before saving any figure, verify every item:
- Top and right spines removed (L-shaped axes)
- Font is sans-serif (Arial / Helvetica), all text 8--14 pt at final print size
- Colors are from a validated CVD-safe palette (not custom RGB guesses)
- Redundant coding present (line styles / markers / hatching supplement color)
- Error bars included where applicable; type (SE, SD, or 95% CI) stated in planned Note text
- Axis labels use Title Case, parallel to their axis
- Legend inside figure area or below; Title Case entries;
frameon=False - No gridlines, no 3D effects, no decorative elements
- Multi-panel labels bold, top-left of each panel; case (A/B/C vs a/b/c) and font size follow the active journal preset's
panel_label_case/panel_label_size(APA default: uppercase 12 pt; Nature: lowercase 9 pt; seejournal-presets.md) - Figure saved as both PDF (vector) and PNG or TIFF (600 DPI raster)
-
pdf.fonttype = 42confirmed (TrueType embedding) - Figure text (number, title, Note) output as separate Markdown, not embedded in the image
- Figure Note 未嵌入图片本体：
*Note.*、*p < .05.*、解释性 caption 等应作为 Markdown 文本通过format_apa_figure_text()输出，不要用fig.text(...)/ax.text(...)嵌入 PNG。inline stats 簇（如 "r = .45, p < .001"）是允许的，但完整的"Note. ..."段落违反 APA §7.28 + Skill §9 输出原则。
For APA formatting details: references/apa-figure-standards.md.
For statistical annotation rules: references/statistical-annotations.md.
| Issue | Cause | Fix |
|---|---|---|
| Fonts show as boxes or wrong glyphs | Arial not installed | DejaVu Sans is configured as fallback in apply_style() |
| Text cut off when saving | tight_layout failure with complex layouts | constrained_layout is enabled by default; do not mix with tight_layout |
| Colors look different in print | RGB-to-CMYK gamut shift | Stick to Tol / Okabe-Ito palettes (mid-saturation, CMYK-safe) |
| PDF rejected ("Type 3 fonts") | pdf.fonttype not 42 |
Ensure apply_style() was called before any plotting |
| Heatmap zero-point not white | Missing TwoSlopeNorm | Use TwoSlopeNorm(vmin=-1, vcenter=0, vmax=1) |
| Error bars invisible on bar chart | Error bar color same as fill | Use NEUTRAL['error_bar'] (black) with capsize=3 |
| Figure text too small after resize | Font < 8 pt at final column width | Design at target width (85 mm); text at 8 pt stays legible |
| TIFF output needed | matplotlib lacks native TIFF | save_figure(fig, name, formats=('tiff',)) handles conversion via Pillow |
| Italic r / t renders as DejaVu Sans Oblique | mathtext fontset mismatch | Already fixed: apply_style() sets mathtext.fontset='custom' with Arial |
compose_grid rejects L-shape |
subplot_mosaic only supports rectangular | Restructure layout or split into two figures (SSCIPlotsMosaicError is informative) |
| Aesthetic palette unavailable | Deferred / opt-in by design | register_aesthetic_palette('studio_ghibli') (emits warning that palette is not publication-grade) |
| Note 段落嵌在图片里 | fig.text(0.5, 0.02, "*Note.* ...") 嵌图违反 APA §7.28 |
删除该调用；用 format_apa_figure_text(note_text="...") 生成 Markdown 文本同步输出 |
Load each file only when needed (progressive disclosure). The chart catalog is split across 5 files; load the family file matching the requested chart type, not the whole catalog.
| File | Content | Load when... |
|---|---|---|
references/chart-type-guide.md |
Index: TOC across 4 chart families + quick reference + cross-cutting Y-axis baseline rule + old-anchor redirects | Step 3: looking up which chart-family file to open |
references/chart-types-core.md |
Core distribution & relationship: §1-§7 + §3.1 + §4.1 + §16 Histogram | Building any §1-§7 figure or the new annotated time series / marginal-histogram subsections |
references/chart-types-models.md |
Statistical model output: §8-§12, §17-§19, §32, §33 | Forest, SEM, mediation, interaction, simple slopes, scree, profile, growth, specification curve, DAG |
references/chart-types-causal-econ.md |
Causal inference / econometrics: §22-§26, §38 | Event-study, DID parallel trends, RD, binscatter, multi-model coefficient plot, IV diagram |
references/chart-types-applied.md |
Applied / specialty: §14, §16, §20, §21, §27-§31 | Raincloud, funnel, Kaplan-Meier, Bland-Altman, ridgeline, choropleth, ROC+calibration, mobility matrix, marginal effects |
references/chart-types-quick-reference.md |
11 one-page references (§15.1-§15.11) + per-discipline decision matrix | Quick lookups for histogram, density, swarm, factor loading, Johnson-Neyman, CONSORT, lollipop, slope/bump, dumbbell, population pyramid, tornado |
references/multi-panel.md |
Multi-panel composition: compose_grid / small_multiples / add_inset / shared legend & colorbar / marginal histogram / subfigures + cross-panel consistency checklist |
Step 3 for any A/B/C or N×M figure, inset zooms, shared colorbar across panels |
references/color-system.md |
Full 21-palette catalog (general / journal-anchored / discipline-anchored / aesthetic publication-grade / deferred aesthetic), license credits, decision tree, redundant coding, semantic conventions | Choosing non-default colors, needing > 7 groups, journal-anchoring, or aesthetic palettes |
references/apa-figure-standards.md |
APA 7th Figure number / title / Note format, font and italic rules, multi-panel specs, accessibility, §11 Mediation Diagram Conventions (SEM notation rules) | Step 4: validating APA compliance; writing Figure text output; mediation diagram setup |
references/journal-presets.md |
Size / DPI / format requirements per publisher (APA, Elsevier, Wiley, SAGE, Psych Science, OUP/ASA, Nature, Science, NEJM, Lancet, BMJ, JAMA) | Step 2: when user specifies a target journal |
references/statistical-annotations.md |
p-value, effect size, CI formatting; statistical symbol italic rules; decimal place conventions; add_inline_stats / add_reference_line usage |
Step 4: when figure includes statistical annotations |
references/complexity-elements-catalog.md |
Catalog of "publication-quality complexity elements" (white-halo lines, inset zooms, descriptor matrices, at-risk tables, CI ribbons, etc.) and which chart types use which elements | Stepping up an existing figure from "course assignment" feel to "top-SSCI" feel; choosing which complexity elements to layer onto a base chart |
references/multi-figure-gallery-pitfalls.md |
11 high-frequency cross-figure pitfalls + 60-second self-check sweep + 3 cognitive traps. Non-binding companion distilled from Phase 7 polish (88 P0 fixes on an 18-figure gallery) | Strongly recommended when generating ≥ 3 figures for the same surface (README gallery, paper figures, slide deck). Single-figure use can skip |