{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import k3d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_plot():\n",
    "    iteration = 4\n",
    "    size = 3**iteration\n",
    "\n",
    "    voxels = np.ones((size, size, size));\n",
    "\n",
    "    def iterate(length, x, y, z):\n",
    "\n",
    "        nl = length // 3    \n",
    "\n",
    "        if nl < 1:\n",
    "            return\n",
    "\n",
    "        margin = (nl-1) // 2\n",
    "\n",
    "        voxels[z-margin:z+margin+1, y-margin:y+margin+1, :] = 0\n",
    "        voxels[z-margin:z+margin+1, :, x-margin:x+margin+1] = 0\n",
    "        voxels[:, y-margin:y+margin+1, x-margin:x+margin+1] = 0    \n",
    "\n",
    "        for ix,iy,iz in np.ndindex((3,3,3)):\n",
    "            if (1 if ix !=1 else 0) + (1 if iy != 1 else 0) + (1 if iz != 1 else 0) !=2:\n",
    "                iterate(nl, x + (ix-1) * nl, y + (iy-1) * nl , z + (iz-1) * nl)\n",
    "\n",
    "    iterate(size, size//2, size//2, size//2)\n",
    "\n",
    "    plot = k3d.plot()\n",
    "    plot += k3d.voxels(voxels.astype(np.uint8), compression_level=9)\n",
    "    \n",
    "    return plot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Create and save to *.k3d file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plot = get_plot()\n",
    "plot.display()\n",
    "data = plot.get_binary_snapshot()\n",
    "\n",
    "with open('binary_snapshot.k3d', 'wb') as f:\n",
    "    f.write(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load from *.k3d file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plot2 = k3d.plot()\n",
    "with open('binary_snapshot.k3d', 'rb') as f:\n",
    "    plot2.load_binary_snapshot(f.read())\n",
    "plot2.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Save to standalone *.html file\n",
    "\n",
    "Standalone snapshot produce HTML file that include any necessary data to draw plot with data without internet connection/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plot3 = get_plot()\n",
    "plot3.display()\n",
    "\n",
    "data = plot3.get_snapshot()\n",
    "\n",
    "with open('snapshot_standalone.html', 'w') as f:\n",
    "    f.write(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Save to online *.html file\n",
    "\n",
    "Online snapshot exclude whole js code of k3d. Produced HTML file contain a minimum code to download a K3D from NPM and display a plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plot4 = get_plot()\n",
    "plot4.snapshot_type = 'online'\n",
    "plot4.display()\n",
    "\n",
    "data = plot4.get_snapshot()\n",
    "\n",
    "with open('snapshot_online.html', 'w') as f:\n",
    "    f.write(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Save to inline *.html file\n",
    "\n",
    "Inline element can be embeded in any html document like Sphinx documentation:\n",
    "\n",
    "```\n",
    ".. raw:: html\n",
    "\t:file: inline_shapshot.html\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plot5 = get_plot()\n",
    "plot5.snapshot_type = 'inline'\n",
    "plot5.display()\n",
    "\n",
    "data = plot5.get_snapshot()\n",
    "\n",
    "with open('snapshot_inline.html', 'w') as f:\n",
    "    f.write(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "for f in ['snapshot_standalone.html', 'snapshot_online.html', 'snapshot_inline.html', 'binary_snapshot.k3d']:\n",
    "    print(f, os.stat(f).st_size, 'bytes')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.12"
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 "nbformat": 4,
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