Bits & Flames bitsandflames/fyron

Colors And Styles

Fyron plotting uses a small scientific color system for publication figures. The default categorical palette is colorblind-safe, while Bits & Flames colors remain available for branded figures.

Use this page when choosing palettes, figure styles, or grayscale-safe outputs. For full plotting workflows, see Clinical Plotting.

Public APIs

python
from fyron import plotting as fp

fp.list_palettes()
fp.get_palette("okabe_ito")
fp.get_colormap("fyron_diverging_blue_red")
fp.set_plot_style(style="paper", palette="okabe_ito")
fp.preview_palette("okabe_ito")
fp.palette_luminance_table("okabe_ito")
fp.palette_grayscale_contrast("okabe_ito")

Palette Families

FamilyUse
qualitativecategories such as treatment arm, risk group, sex, scanner, or cohort
sequentialordered magnitude such as risk score, density, or intensity
divergingcentered quantities such as correlations, residuals, and difference maps

Built-In Names

NameTypeRecommended useColorblind-safe
okabe_itoqualitativedefault categorical palette for treatment arms, risk groups, and cohortsyes
wongqualitativecompact categorical palette for up to seven groupsyes
muted_scientificqualitativesofter manuscript palette for journals and slidesno
nature_coolqualitativerestrained two-to-three group comparison paletteno
bfqualitativeBits & Flames / BOARISK continuityno
bf_corequalitativebalanced Bits & Flames palette for branded clinical dashboards and slide figuresno
bf_flamesqualitativewarm Bits & Flames palette for highlights, emphasis, and presentation figuresno
bf_embersqualitativecool ember-inspired Bits & Flames palette for quiet analytics figuresno
bf_vibrantqualitativehigh-contrast Bits & Flames palette for vibrant branded figures and presentation highlightsno
bf_vibrant_mutedqualitativemuted Bits & Flames vibrant palette for branded figures that need less saturationno
fyron_sequential_bluesequentialordered magnitude maps, density, risk scores, intensity summariesyes
fyron_sequential_tealsequentialordered magnitude maps with a cooler visual toneyes
fyron_diverging_blue_reddivergingcorrelations, residuals, and zero-centered difference mapsno
fyron_diverging_teal_orangedivergingcentered clinical quantities and signed changesno

Palette Overview

All Fyron scientific palettes

Reproducible Palette Audit

Use the API to generate the exact same previews in a notebook or paper-figure script:

python
from fyron import plotting as fp

palettes = fp.list_palettes()
fig, ax = fp.preview_palette("okabe_ito")

luminance = fp.palette_luminance_table("okabe_ito")
contrast = fp.palette_grayscale_contrast("okabe_ito")

list_palettes() returns the palette name, family, number of colors, maximum recommended categorical colors, colorblind-safe flag, source note, and explicit hex values.

Figure Style

python
fp.set_plot_style("paper", palette="okabe_ito")

Use palette="bf", palette="bf_core", palette="bf_flames", palette="bf_embers", palette="bf_vibrant", or palette="bf_vibrant_muted" when brand continuity matters. For manuscripts, prefer okabe_ito plus hatches, markers, direct labels, and small multiples when there are many groups.

Checks Before Publication

  • Preview the palette in the expected number of groups.
  • Audit luminance when figures may be printed in grayscale.
  • Use diverging colormaps only when zero or a midpoint has meaning.
  • Avoid rainbow and jet palettes for scientific interpretation.
  • Verify final exported figures in the target medium: PDF, SVG, slides, or grayscale print.