{
  "id": "palette-vp-orchid-ramp",
  "version": "1.0.0",
  "name": "Orchid ramp",
  "name_zh": "兰紫连续",
  "author": "VoltPeer maintainers",
  "license": "MIT",
  "category": "style",
  "status": "community",
  "created_at": "2026-10-03",
  "updated_at": "2026-10-03",
  "series": [
    "#FBF4FD",
    "#EEDBF5",
    "#DABCE7",
    "#C197D5",
    "#A271BC",
    "#7B4B94",
    "#512D66"
  ],
  "palette_kind": "sequential",
  "background": "#FFFFFF",
  "description": "One-direction probability or abundance",
  "description_zh": "单向概率或含量",
  "use_zh": "单向概率或含量",
  "use_en": "One-direction probability or abundance",
  "usage_mode": "heatmap",
  "cvd_level": "not_verified",
  "classic": false,
  "recommended_series_count": 6,
  "source_credit": {
    "source": "VoltPeer original / Orchid ramp",
    "url": "https://dazi.gsarrizabalaga.xyz/palettes.html#palette-vp-orchid-ramp",
    "licence": "MIT",
    "scope": "Independently authored colour values and appearance fixture. No third-party array, figure or experimental data copied."
  },
  "tags": [
    "sequential",
    "voltpeer-original",
    "heatmap"
  ],
  "scientific_review": "not_claimed",
  "template_collection": "palette-library-200",
  "saturation": "soft",
  "saturation_hsv_mean": 0.296,
  "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# Seven preview stops; the download includes the full 256-row table.\ncolours = ['#FBF4FD', '#EEDBF5', '#DABCE7', '#C197D5', '#A271BC', '#7B4B94', '#512D66']\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
  ]
}
