{
  "id": "palette-tol-iridescent",
  "version": "1.0.0",
  "name": "Paul Tol · Iridescent",
  "name_zh": "Paul Tol · Iridescent",
  "author": "Paul Tol / Bokeh 3.5.2",
  "license": "BSD-3-Clause",
  "category": "style",
  "status": "community",
  "created_at": "2026-10-03",
  "updated_at": "2026-10-03",
  "series": [
    "#FEFBE9",
    "#FCF7D5",
    "#F5F3C1",
    "#EAF0B5",
    "#DDECBF",
    "#D0E7CA",
    "#C2E3D2",
    "#B5DDD8",
    "#A8D8DC",
    "#9BD2E1",
    "#8DCBE4",
    "#81C4E7",
    "#7BBCE7",
    "#7EB2E4",
    "#88A5DD",
    "#9398D2",
    "#9B8AC4",
    "#9D7DB2",
    "#9A709E",
    "#906388",
    "#805770",
    "#684957",
    "#46353A"
  ],
  "palette_kind": "sequential",
  "background": "#FFFFFF",
  "description": "Low-to-high quantities with explicit colourbar range and units.",
  "description_zh": "表示从低到高的量；保留色标范围和单位。",
  "use_zh": "表示从低到高的量；保留色标范围和单位。",
  "use_en": "Low-to-high quantities with explicit colourbar range and units.",
  "usage_mode": "heatmap",
  "cvd_level": "not_verified",
  "cvd_evidence_url": null,
  "source_credit": {
    "source": "Paul Tol / Bokeh 3.5.2",
    "url": "https://github.com/bokeh/bokeh/blob/3.5.2/src/bokeh/palettes.py",
    "licence": "BSD-3-Clause",
    "upstream_table": "Iridescent23",
    "direction": "native",
    "scope": "Licensed colour data only; VoltPeer appearance fixture and renderer are original MIT work."
  },
  "tags": [
    "sequential",
    "tol",
    "scientific-palette"
  ],
  "classic": false,
  "scientific_review": "not_claimed",
  "template_collection": "palette-library-200",
  "recommended_series_count": 6,
  "warning": null,
  "warning_zh": null,
  "discrete": false,
  "permissions": {
    "public_display": true,
    "registry": true,
    "automated_testing": true,
    "model_training": false
  },
  "saturation": "soft",
  "saturation_hsv_mean": 0.277,
  "colorblind_status": "not_certified",
  "intended_background": "#FFFFFF",
  "dark_background_support": false,
  "palette_categories": [
    "sequential",
    "soft"
  ],
  "plot_code": "import matplotlib.pyplot as plt\nfrom matplotlib.colors import LinearSegmentedColormap\n\n# Complete labelled colour stops; inspect the supplied table and usage notes.\ncolours = ['#FEFBE9', '#FCF7D5', '#F5F3C1', '#EAF0B5', '#DDECBF', '#D0E7CA', '#C2E3D2', '#B5DDD8', '#A8D8DC', '#9BD2E1', '#8DCBE4', '#81C4E7', '#7BBCE7', '#7EB2E4', '#88A5DD', '#9398D2', '#9B8AC4', '#9D7DB2', '#9A709E', '#906388', '#805770', '#684957', '#46353A']\ncmap = LinearSegmentedColormap.from_list('selected', colours)\nfig, ax = plt.subplots()\nimage = ax.imshow(values, cmap=cmap, vmin=minimum, vmax=maximum)\nfig.colorbar(image, ax=ax, label=unit)\nfor spine in ax.spines.values():\n    spine.set_visible(True)\nfig.savefig('new-figure.svg')\n",
  "preview_series_indices": [
    0,
    1,
    2,
    3,
    4,
    5
  ]
}