{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "1abfc7de-3ced-4407-b38e-3fc276b6a133",
"metadata": {},
"outputs": [],
"source": [
"import math\n",
"import json\n",
"from pathlib import Path\n",
"\n",
"import plotly.io as pio\n",
"import plotly.graph_objects as go\n",
"from coloraide import Color\n",
"\n",
"import gamut_3d_plotly as diagrams\n",
"\n",
"pio.renderers\n",
"pio.renderers.default = \"notebook_connected\"\n",
"\n",
"\n",
"def face_radial_plane(fig, theta_deg, r=2.5, tilt_deg=0):\n",
" # normal in xy\n",
" nx = -math.sin(math.radians(theta_deg))\n",
" ny = math.cos(math.radians(theta_deg))\n",
"\n",
" # allow optional tilt up/down so it's not perfectly horizontal\n",
" tilt = math.radians(tilt_deg) # 0 => horizontal view, positive looks slightly downward\n",
" ex = r * nx * math.cos(tilt)\n",
" ey = r * ny * math.cos(tilt)\n",
" ez = r * math.sin(tilt)\n",
"\n",
" fig.update_layout(\n",
" scene_camera=dict(\n",
" eye=dict(x=ex, y=ey, z=ez),\n",
" center=dict(x=0, y=0, z=0),\n",
" up=dict(x=0, y=0, z=1)\n",
" )\n",
" )\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "642b3763-f250-4e24-bd4c-2a080772467d",
"metadata": {},
"outputs": [],
"source": [
"PALETTE_DIR = \"palettes\"\n",
"\n",
"with Path(PALETTE_DIR, \"monobiome-v111-oklch.json\").open(\"rb\") as f:\n",
" mb_v111_dict = json.load(f)\n",
"with Path(PALETTE_DIR, \"monobiome-vUCC-oklch.json\").open(\"rb\") as f:\n",
" mb_vUCC_dict = json.load(f)\n",
"with Path(PALETTE_DIR, \"monobiome-vMCL-oklch.json\").open(\"rb\") as f:\n",
" mb_vMCL_dict = json.load(f)\n",
"with Path(PALETTE_DIR, \"monobiome-vQBR-oklch.json\").open(\"rb\") as f:\n",
" mb_vQBR_dict = json.load(f)\n",
"with Path(PALETTE_DIR, \"monobiome-vQBRsn-oklch.json\").open(\"rb\") as f:\n",
" mb_vQBRsn_dict = json.load(f)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "0e778a92-78fa-40eb-8b4f-51fbbbc9eb0a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"===> Generating oklch model...\n"
]
},
{
"data": {
"text/html": [
" \n",
" \n",
" "
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"metadata": {},
"output_type": "display_data"
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""
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"metadata": {},
"output_type": "display_data"
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],
"source": [
"name = 'oklch'\n",
"gamut = 'srgb'\n",
"title = f'{name} color space'\n",
"\n",
"# elev=45\n",
"# azim=-60.0\n",
"elev=45\n",
"azim=29.0\n",
"width = 600\n",
"height = 400\n",
"\n",
"print(f'===> Generating {name} model...')\n",
"fig = diagrams.plot_gamut_in_space(\n",
" name,\n",
" gamuts={\n",
" gamut: {\n",
" 'opacity': 0.2,\n",
" # 'edges': 'black',\n",
" # 'faces': True,\n",
" }\n",
" },\n",
" # dark=True,\n",
" gmap={'method': 'raytrace'},\n",
" title=title,\n",
" size=(width, height),\n",
" camera={'a': azim, 'e': elev, 'r': 2.5},\n",
" projection='orthographic',\n",
")\n",
"\n",
"fig.update_layout(\n",
" margin=dict(l=0, r=0, t=0, b=0)\n",
")\n",
"\n",
"fig.show()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "ed02f2b8-ea4e-43f1-bec6-914b1b3ccccf",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# trajectory = [Color(c_str) for c_str in mb_dict[\"badlands\"].values()]\n",
"trajectories = [ [Color(c_str) for c_str in c_str_dict.values()] for c_str_dict in mb_v111_dict.values()] \n",
"\n",
"tmp_fig = go.Figure(fig)\n",
"\n",
"for trajectory in trajectories:\n",
" diagrams.plot_trajectory(\n",
" tmp_fig,\n",
" space=\"oklab\",\n",
" trajectory_colors=trajectory,\n",
" gmap={'method': 'raytrace'},\n",
" filters=(),\n",
" connect_line=True,\n",
" marker_size=2,\n",
" line_width=2,\n",
" # simulate_alpha=False\n",
" )\n",
"\n",
"face_radial_plane(tmp_fig, 29)\n",
"tmp_fig.show()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "e2c781cc-f8a9-49f0-9488-e380897f5c9a",
"metadata": {},
"outputs": [
{
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"