README.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "1a59da63",
   "metadata": {},
   "source": [
    "# pre"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "98c57a5d",
   "metadata": {},
   "outputs": [],
   "source": [
    "from __future__ import annotations\n",
    "try:\n",
    "    from mediocreatbest import auto\n",
    "except ImportError:\n",
    "    %pip install --user --upgrade pip\n",
    "    %pip install --user --upgrade --force-reinstall \\\n",
    "        mediocreatbest\n",
    "    from mediocreatbest import auto\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "43df003d",
   "metadata": {},
   "source": [
    "# lib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "69c3d521",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'mediocreatbest' from '/mnt/seenas2/data/home/thobson2/src/GraphShaders2/venv/lib/python3.9/site-packages/mediocreatbest/__init__.py'>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%mediocreatbest.module --reuse mediocreatbest\n",
    "#@title with_exit_stack\n",
    "\n",
    "def with_exit_stack(func):\n",
    "    signature = auto.inspect.signature(func)\n",
    "\n",
    "    def wrapper(*args, **kwargs):\n",
    "        with auto.contextlib.ExitStack() as stack:\n",
    "            if 'stack' in signature.parameters:\n",
    "                kwargs = kwargs | dict(stack=stack)\n",
    "            if 'enter' in signature.parameters:\n",
    "                kwargs = kwargs | dict(enter=stack.enter_context)\n",
    "            if 'defer' in signature.parameters:\n",
    "                kwargs = kwargs | dict(defer=stack.callback)\n",
    "\n",
    "            return func(*args, **kwargs)\n",
    "\n",
    "    return wrapper\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f69c4588",
   "metadata": {},
   "source": [
    "# app"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "426d311e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#@title Transpile\n",
    "def Transpile(\n",
    "    program: str,\n",
    "    *,\n",
    "    files: dict[str, auto.os.PathLike],\n",
    "    env: dict[str, str],\n",
    ") -> dict[str, str]:\n",
    "    with auto.tempfile.TemporaryDirectory() as tempdir:\n",
    "        tempdir = auto.pathlib.Path(tempdir)\n",
    "        \n",
    "        printenv0 = tempdir / 'printenv0'\n",
    "        printenv0.write_text('#!/usr/bin/env sh\\nexec printenv -0')\n",
    "        printenv0.chmod(0o500)\n",
    "        \n",
    "        inpfile = tempdir / 'inpfile'\n",
    "        inpfile.write_text(program)\n",
    "        \n",
    "        args = [\n",
    "            auto.sys.executable,\n",
    "            'src/GraphShaderTranspiler.py',\n",
    "        ] + sum([\n",
    "            ['-f', str(k), str(v)]\n",
    "            for k, v in files.items()\n",
    "        ], []) + sum([\n",
    "            ['-e', f'{k}', f'{v}']\n",
    "            for k, v in env.items()\n",
    "        ], []) + [\n",
    "            '-i', str(inpfile),\n",
    "            '-x', str(printenv0),\n",
    "        ]\n",
    "        \n",
    "        stdout = auto.subprocess.check_output(args)\n",
    "        env = {}\n",
    "        for line in stdout.split(b'\\0'):\n",
    "            line = line.decode('ascii')\n",
    "            if line == '':\n",
    "                continue\n",
    "            \n",
    "            try:\n",
    "                k, v = line.split('=', 1)\n",
    "            except ValueError:\n",
    "                print(f'{line=!r}')\n",
    "                raise\n",
    "                \n",
    "            env[k] = v\n",
    "        \n",
    "        return env\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d11d36ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "#@title GS\n",
    "@auto.functools.cache\n",
    "def GS():\n",
    "    root = auto.pathlib.Path.cwd()\n",
    "\n",
    "    path = root / 'src'\n",
    "    if str(path) not in auto.sys.path:\n",
    "        auto.sys.path.append(str(path))\n",
    "\n",
    "    path = root / 'stage' / 'lib' / 'libgraphshader.so'\n",
    "    assert path.exists(), path\n",
    "    gs = auto.graphshader.GS.load(str(path))\n",
    "    \n",
    "    return gs\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1d266a3c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#@title Graph\n",
    "@auto.dataclasses.dataclass\n",
    "class Graph:\n",
    "    files: dict[str, auto.pathlib.Path] = auto.dataclasses.field(default_factory=dict)\n",
    "    datas: dict[str, auto.np.ndarray] = auto.dataclasses.field(default_factory=dict)\n",
    "    program: str | None = auto.dataclasses.field(default=None)\n",
    "    size: tuple[\n",
    "        auto.typing.Annotated[int, 'width'],\n",
    "        auto.typing.Annotated[int, 'height'],\n",
    "    ] = auto.dataclasses.field(default=None)\n",
    "    tile: tuple[\n",
    "        auto.typing.Annotated[int, 'zoom'],\n",
    "        auto.typing.Annotated[int, 'row'],\n",
    "        auto.typing.Annotated[int, 'col'],\n",
    "    ] = auto.dataclasses.field(default=None)\n",
    "    verbose: bool | None = auto.dataclasses.field(default=None)\n",
    "    \n",
    "    @auto.mediocreatbest.with_exit_stack\n",
    "    def render(\n",
    "        self: Self,\n",
    "\n",
    "        program: str | None = None,\n",
    "\n",
    "        *,   enter,\n",
    "        verbose: bool | auto.typing.Literal[...] = ...,\n",
    "\n",
    "        size: tuple[\n",
    "            auto.typing.Annotated[int, 'width'],\n",
    "            auto.typing.Annotated[int, 'height'],\n",
    "        ] | auto.typing.Literal[...] = ...,\n",
    "        tile: tuple[\n",
    "            auto.typing.Annotated[int, 'zoom'],\n",
    "            auto.typing.Annotated[int, 'row'],\n",
    "            auto.typing.Annotated[int, 'col'],\n",
    "        ] | auto.typing.Literal[...] = ...,\n",
    "        \n",
    "        outfile: auto.pathlib.Path | auto.typing.Literal[...] = ...,\n",
    "        tempdir: auto.pathlib.Path | auto.typing.Literal[...] = ...,\n",
    "    ) -> auto.typing.Annotated[bytes, 'jpeg']:\n",
    "        if outfile is ...:\n",
    "            if tempdir is ...:\n",
    "                tempdir = enter( auto.tempfile.TemporaryDirectory() )\n",
    "                tempdir = auto.pathlib.Path(tempdir)\n",
    "            outfile = tempdir / 'outfile.jpg'\n",
    "        assert outfile is not None\n",
    "\n",
    "        if program is ...:\n",
    "            program = self.program\n",
    "        assert program is not None\n",
    "        \n",
    "        if size is ...:\n",
    "            size = self.size\n",
    "        assert size is not None\n",
    "        \n",
    "        if tile is ...:\n",
    "            tile = self.tile\n",
    "        assert tile is not None\n",
    "        \n",
    "        if verbose is ...:\n",
    "            verbose = self.verbose\n",
    "        assert verbose is not None\n",
    "\n",
    "        env = Transpile(\n",
    "            program=program,\n",
    "            files=self.files,\n",
    "            env={\n",
    "                'GS_TILE_WIDTH': size[0],\n",
    "                'GS_TILE_HEIGHT': size[1],\n",
    "                'GS_TILE_Z': tile[0],\n",
    "                'GS_TILE_Y': tile[1],\n",
    "                'GS_TILE_X': tile[2],\n",
    "                'GS_OUTPUT': str(outfile),\n",
    "            },\n",
    "        )\n",
    "        \n",
    "        root = auto.pathlib.Path.cwd()\n",
    "        path = root / 'stage' / 'bin' / 'GraphShaderEngine'\n",
    "        \n",
    "        args = [\n",
    "            str(path),\n",
    "        ]\n",
    "\n",
    "        kwargs = {}\n",
    "        if not verbose:\n",
    "            kwargs['stderr'] = auto.subprocess.DEVNULL\n",
    "            kwargs['stdout'] = auto.subprocess.DEVNULL\n",
    "        auto.subprocess.check_call(\n",
    "            args,\n",
    "            env=env,\n",
    "            **kwargs,\n",
    "        )\n",
    "        \n",
    "        return outfile.read_bytes()\n",
    "\n",
    "\n",
    "@auto.IPython.core.magic.register_cell_magic('.render')\n",
    "def render(line: str, cell: str, /):\n",
    "    def render(*, graph: Graph, program: str, verbose: bool):\n",
    "        # auto.pprint.pprint(dict(line=line, cell=cell, graph=graph, program=program))\n",
    "        image: bytes = graph.render(\n",
    "            program=program,\n",
    "            verbose=verbose,\n",
    "        )\n",
    "        auto.IPython.display.display(auto.IPython.display.Image(\n",
    "            image,\n",
    "        ))\n",
    "\n",
    "    parser = auto.argparse.ArgumentParser()\n",
    "    parser.add_argument('--name', '-n', dest='graph', default='graph')\n",
    "    parser.add_argument('--verbose', '-v', action='store_true')\n",
    "    parser.set_defaults(program=cell)\n",
    "    \n",
    "    args = auto.shlex.split(line)\n",
    "    args = vars(parser.parse_args(args))\n",
    "    \n",
    "    args['graph'] = get_ipython().ev(args.pop('graph'))\n",
    "    \n",
    "    render(**args)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d888dad1",
   "metadata": {},
   "source": [
    "# 1st"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0dd361ac",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/mnt/seenas2/data/home/thobson2/src/GraphShaders2/venv/bin/python\n",
      "3.9.5 (default, Nov 23 2021, 15:27:38) \n",
      "[GCC 9.3.0]\n"
     ]
    }
   ],
   "source": [
    "def scope():\n",
    "    import sys\n",
    "    print(sys.executable)\n",
    "    print(sys.version)\n",
    "\n",
    "/scope\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a006cbd8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "|   0  Quadro M6000 24GB              On  | 00000000:82:00.0 Off |                  Off |\n"
     ]
    }
   ],
   "source": [
    "!nvidia-smi | grep Quadro\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "89e53a58",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-- Configuring done\n",
      "-- Generating done\n",
      "-- Build files have been written to: /home/thobson2/src/GraphShaders2/build\n",
      "-- Cache values\n",
      "CMAKE_BUILD_TYPE:STRING=Debug\n",
      "CMAKE_INSTALL_PREFIX:PATH=/home/thobson2/src/GraphShaders2/stage\n"
     ]
    }
   ],
   "source": [
    "!./go.sh --Configure\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f4c45cd6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/usr/bin/cmake -S/home/thobson2/src/GraphShaders2 -B/home/thobson2/src/GraphShaders2/build --check-build-system CMakeFiles/Makefile.cmake 0\n",
      "/usr/bin/cmake -E cmake_progress_start /home/thobson2/src/GraphShaders2/build/CMakeFiles /home/thobson2/src/GraphShaders2/build/CMakeFiles/progress.marks\n",
      "/usr/bin/make -f CMakeFiles/Makefile2 all\n",
      "make[1]: Entering directory '/home/thobson2/src/GraphShaders2/build'\n",
      "/usr/bin/make -f CMakeFiles/graphshader.dir/build.make CMakeFiles/graphshader.dir/depend\n",
      "/usr/bin/make -f CMakeFiles/GraphShaderEngine.dir/build.make CMakeFiles/GraphShaderEngine.dir/depend\n",
      "make[2]: Entering directory '/home/thobson2/src/GraphShaders2/build'\n",
      "cd /home/thobson2/src/GraphShaders2/build && /usr/bin/cmake -E cmake_depends \"Unix Makefiles\" /home/thobson2/src/GraphShaders2 /home/thobson2/src/GraphShaders2 /home/thobson2/src/GraphShaders2/build /home/thobson2/src/GraphShaders2/build /home/thobson2/src/GraphShaders2/build/CMakeFiles/graphshader.dir/DependInfo.cmake --color=\n",
      "make[2]: Entering directory '/home/thobson2/src/GraphShaders2/build'\n",
      "cd /home/thobson2/src/GraphShaders2/build && /usr/bin/cmake -E cmake_depends \"Unix Makefiles\" /home/thobson2/src/GraphShaders2 /home/thobson2/src/GraphShaders2 /home/thobson2/src/GraphShaders2/build /home/thobson2/src/GraphShaders2/build /home/thobson2/src/GraphShaders2/build/CMakeFiles/GraphShaderEngine.dir/DependInfo.cmake --color=\n",
      "make[2]: Leaving directory '/home/thobson2/src/GraphShaders2/build'\n",
      "/usr/bin/make -f CMakeFiles/graphshader.dir/build.make CMakeFiles/graphshader.dir/build\n",
      "make[2]: Leaving directory '/home/thobson2/src/GraphShaders2/build'\n",
      "/usr/bin/make -f CMakeFiles/GraphShaderEngine.dir/build.make CMakeFiles/GraphShaderEngine.dir/build\n",
      "make[2]: Entering directory '/home/thobson2/src/GraphShaders2/build'\n",
      "make[2]: Nothing to be done for 'CMakeFiles/graphshader.dir/build'.\n",
      "make[2]: Leaving directory '/home/thobson2/src/GraphShaders2/build'\n",
      "make[2]: Entering directory '/home/thobson2/src/GraphShaders2/build'\n",
      "make[2]: Nothing to be done for 'CMakeFiles/GraphShaderEngine.dir/build'.\n",
      "make[2]: Leaving directory '/home/thobson2/src/GraphShaders2/build'\n",
      "[ 87%] Built target graphshader\n",
      "[ 87%] Built target GraphShaderEngine\n",
      "make[1]: Leaving directory '/home/thobson2/src/GraphShaders2/build'\n",
      "/usr/bin/cmake -E cmake_progress_start /home/thobson2/src/GraphShaders2/build/CMakeFiles 0\n"
     ]
    }
   ],
   "source": [
    "!./go.sh --Build\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "dc2a5867",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-- Install configuration: \"Debug\"\n",
      "-- Up-to-date: /home/thobson2/src/GraphShaders2/stage/bin/GraphShaderEngine\n",
      "-- Up-to-date: /home/thobson2/src/GraphShaders2/stage/lib/libgraphshader.so\n",
      "-- Up-to-date: /home/thobson2/src/GraphShaders2/stage/bin/GraphShaderTranspiler.py\n"
     ]
    }
   ],
   "source": [
    "!./go.sh --Install\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6cd1dba",
   "metadata": {},
   "source": [
    "# 2nd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0e5075b5",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "os.execlpe('/tmp/tmprag2n6ai/printenv0', '/tmp/tmprag2n6ai/printenv0 <inpfile>', env)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<textarea rows=12 style=\"width: 90%; margin-left: 5%\">{\n",
       "    &quot;GS_TILE_HEIGHT&quot;: &quot;256&quot;,\n",
       "    &quot;GS_TILE_Z&quot;: &quot;0&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_0&quot;: &quot;2E&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_1&quot;: &quot;N&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_2&quot;: &quot;N&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_3&quot;: &quot;N&quot;,\n",
       "    &quot;GS_SHADER_GEOMETRY&quot;: &quot;\\nlayout (lines) in;\\nlayout (line_strip, max_vertices=2) out;\\n\\nlayout(location=0) in uint _fg_NodeIndex[];\\n\\nlayout(location=0) out flat uint gs_SourceIndex;\\nlayout(location=1) out flat uint gs_TargetIndex;\\n\\nvoid main() {\\n    gs_SourceIndex = _fg_NodeIndex[0];\\n    gs_TargetIndex = _fg_NodeIndex[1];\\n\\n    int gs_EdgeIndex = gl_PrimitiveIDIn;\\n    vec4 gs_SourcePosition = gl_in[0].gl_Position;\\n    vec4 gs_TargetPosition = gl_in[1].gl_Position;\\n\\n\\n    #if USE_RELATIONAL\\n    uint od = 1 + atomicAdd(out_degree[gs_SourceIndex], 1);\\n    atomicCounterMax(out_degree_max, od);\\n\\n    uint id = 1 + atomicAdd(in_degree[gs_TargetIndex], 1);\\n    atomicCounterMax(in_degree_max, id);\\n    #endif /* USE_RELATIONAL */\\n\\n\\n\\n    // Apply tile transformations\\n    gs_SourcePosition.xy *= uScale;\\n    gs_SourcePosition.xy += vec2(uTranslateX, uTranslateY);\\n\\n    // Transform xy in [0, 1] to xy in [-1, 1]\\n    gs_SourcePosition.xy *= 2.;\\n    gs_SourcePosition.xy -= 1.;\\n\\n    // Apply tile transformations\\n    gs_TargetPosition.xy *= uScale;\\n    gs_TargetPosition.xy += vec2(uTranslateX, uTranslateY);\\n\\n    // Transform xy in [0, 1] to xy in [-1, 1]\\n    gs_TargetPosition.xy *= 2.;\\n    gs_TargetPosition.xy -= 1.;\\n\\n    gl_PrimitiveID = gs_EdgeIndex;\\n    gl_Position = gs_SourcePosition;\\n    EmitVertex();\\n\\n    gl_Position = gs_TargetPosition;\\n    EmitVertex();\\n\\n    EndPrimitive();\\n}\\n    &quot;,\n",
       "    &quot;GS_BUFFER_SIZE_4&quot;: &quot;N&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_5&quot;: &quot;N&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_6&quot;: &quot;N&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_0&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_7&quot;: &quot;N&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_1&quot;: &quot;GL_FLOAT&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_8&quot;: &quot;E&quot;,\n",
       "    &quot;GS_OUTPUT&quot;: &quot;out.jpg&quot;,\n",
       "    &quot;GS_BUFFER_BIND_0&quot;: &quot;&lt;NONE&gt;&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_2&quot;: &quot;GL_FLOAT&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_9&quot;: &quot;48&quot;,\n",
       "    &quot;GS_BUFFER_BIND_1&quot;: &quot;0&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_3&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_BUFFER_BIND_2&quot;: &quot;1&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_4&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_BUFFER_FILE_0&quot;: &quot;examples/JS-Deps/data/JS-Deps.edge.elements.2u32.bin&quot;,\n",
       "    &quot;GS_BUFFER_BIND_3&quot;: &quot;2&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_5&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_BUFFER_COUNT&quot;: &quot;10&quot;,\n",
       "    &quot;GS_BUFFER_NAME_0&quot;: &quot;_ELEMENT&quot;,\n",
       "    &quot;GS_BUFFER_FILE_1&quot;: &quot;examples/JS-Deps/data/JS-Deps.node.x.f32.bin&quot;,\n",
       "    &quot;GS_BUFFER_BIND_4&quot;: &quot;3&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_6&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_BUFFER_NAME_1&quot;: &quot;_X&quot;,\n",
       "    &quot;GS_BUFFER_FILE_2&quot;: &quot;examples/JS-Deps/data/JS-Deps.node.y.f32.bin&quot;,\n",
       "    &quot;GS_BUFFER_BIND_5&quot;: &quot;4&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_7&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_BUFFER_NAME_2&quot;: &quot;_Y&quot;,\n",
       "    &quot;GS_BUFFER_FILE_3&quot;: &quot;examples/JS-Deps/data/JS-Deps.node.date.u32.bin&quot;,\n",
       "    &quot;GS_BUFFER_BIND_6&quot;: &quot;5&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_8&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_ATOMIC_COUNT&quot;: &quot;12&quot;,\n",
       "    &quot;GS_BUFFER_NAME_3&quot;: &quot;_Date&quot;,\n",
       "    &quot;GS_BUFFER_FILE_4&quot;: &quot;examples/JS-Deps/data/JS-Deps.node.nmaintainers.u32.bin&quot;,\n",
       "    &quot;GS_BUFFER_BIND_7&quot;: &quot;6&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_0&quot;: &quot;in_degree_max&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_9&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_BUFFER_NAME_4&quot;: &quot;_Devs&quot;,\n",
       "    &quot;GS_BUFFER_FILE_5&quot;: &quot;examples/JS-Deps/data/JS-Deps.node.cve.u32.bin&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_1&quot;: &quot;out_degree_max&quot;,\n",
       "    &quot;GS_BUFFER_BIND_8&quot;: &quot;7&quot;,\n",
       "    &quot;GS_SHADER_VERTEX&quot;: &quot;\\n\\nlayout(location=0) out uint _fg_NodeIndex;\\n\\nvoid main() {\\n    const int gs_NodeIndex = gl_VertexID;\\n    vec3 gs_NodePosition = vec3(0., 0., 0.);\\n\\n    float x = X[gs_NodeIndex];\\n    float y = Y[gs_NodeIndex];\\n\\n    gs_NodePosition = vec3(x, y, 0);\\n\\n\\n\\n    gl_Position = vec4(gs_NodePosition.xyz, 1.);\\n\\n    _fg_NodeIndex = gs_NodeIndex;\\n}\\n    &quot;,\n",
       "    &quot;GS_BACKGROUND_A&quot;: &quot;1.0&quot;,\n",
       "    &quot;GS_BUFFER_KIND_0&quot;: &quot;ELEMENT&quot;,\n",
       "    &quot;GS_BUFFER_NAME_5&quot;: &quot;_Vuln&quot;,\n",
       "    &quot;GS_BUFFER_FILE_6&quot;: &quot;&lt;NONE&gt;&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_2&quot;: &quot;total&quot;,\n",
       "    &quot;GS_BUFFER_BIND_9&quot;: &quot;0&quot;,\n",
       "    &quot;GS_SHADER_FRAGMENT&quot;: &quot;\\nlayout(location=0) in flat uint gs_SourceIndex;\\nlayout(location=1) in flat uint gs_TargetIndex;\\n\\nlayout(location=0) out vec4 gs_FragColor;\\n\\nvoid main() {\\n    int gs_EdgeIndex = gl_PrimitiveID;\\n    bool first = 0 == atomicAdd(Seen[gs_EdgeIndex], 1);\\n    bool d = false;\\n\\n    if (first) atomicCounterAdd(total, 1);\\n\\n    #if FILTER_BY_DATE\\n\\n    if (Date[gs_SourceIndex] &lt; LO) {\\n        d = true;\\n        if (first) atomicCounterAdd(source_date_too_lo, 1);\\n    }\\n\\n    if (Date[gs_SourceIndex] &gt; HI) {\\n        d = true;\\n        if (first) atomicCounterAdd(source_date_too_hi, 1);\\n    }\\n\\n    if (Date[gs_TargetIndex] &lt; LO) {\\n        d = true;\\n        if (first) atomicCounterAdd(target_date_too_lo, 1);\\n    }\\n\\n    if (Date[gs_TargetIndex] &gt; HI) {\\n        d = true;\\n        if (first) atomicCounterAdd(target_date_too_hi, 1);\\n    }\\n    #endif /* FILTER_BY_DATE */\\n\\n    if (d) {\\n        if (first) atomicCounterAdd(discarded, 1);\\n        discard;\\n    } else {\\n        if (first) atomicCounterAdd(kept, 1);\\n    }\\n\\n    bool vuln = bool(Vuln[gs_SourceIndex]) || bool(Vuln[gs_TargetIndex]);\\n    bool risky = Devs[gs_SourceIndex] &gt; Devs[gs_TargetIndex];\\n\\n    #if USE_RELATIONAL\\n    const uint depends_on_source = in_degree[gs_SourceIndex];\\n    const uint depends_on_target = in_degree[gs_TargetIndex];\\n\\n    risky = depends_on_source + depends_on_target &gt; 100 * Devs[gs_TargetIndex];\\n    #endif /* USE_RELATIONAL */\\n\\n    if (risky) {\\n        if (first) atomicCounterAdd(total_risky, 1);\\n    }\\n\\n    if (risky &amp;&amp; vuln) {\\n        if (first) atomicCounterAdd(total_vuln_and_risky, 1);\\n    }\\n\\n    if (vuln) {\\n        if (first) atomicCounterAdd(total_vuln, 1);\\n    }\\n\\n    gs_FragColor = vec4(0.1);\\n    gs_FragColor.r = float(vuln);\\n    gs_FragColor.b = float(risky);\\n}\\n    &quot;,\n",
       "    &quot;GS_BACKGROUND_B&quot;: &quot;1.0&quot;,\n",
       "    &quot;GS_BUFFER_KIND_1&quot;: &quot;ATTRIBUTE&quot;,\n",
       "    &quot;GS_BUFFER_NAME_6&quot;: &quot;_in_degree&quot;,\n",
       "    &quot;GS_BUFFER_FILE_7&quot;: &quot;&lt;NONE&gt;&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_3&quot;: &quot;source_date_too_lo&quot;,\n",
       "    &quot;GS_TILE_WIDTH&quot;: &quot;256&quot;,\n",
       "    &quot;GS_BUFFER_KIND_2&quot;: &quot;ATTRIBUTE&quot;,\n",
       "    &quot;GS_BUFFER_NAME_7&quot;: &quot;_out_degree&quot;,\n",
       "    &quot;GS_BUFFER_FILE_8&quot;: &quot;&lt;NONE&gt;&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_4&quot;: &quot;source_date_too_hi&quot;,\n",
       "    &quot;GS_BUFFER_KIND_3&quot;: &quot;ATTRIBUTE&quot;,\n",
       "    &quot;GS_BUFFER_NAME_8&quot;: &quot;_Seen&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_5&quot;: &quot;target_date_too_lo&quot;,\n",
       "    &quot;GS_BUFFER_FILE_9&quot;: &quot;&lt;NONE&gt;&quot;,\n",
       "    &quot;GS_BUFFER_KIND_4&quot;: &quot;ATTRIBUTE&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_6&quot;: &quot;target_date_too_hi&quot;,\n",
       "    &quot;GS_BUFFER_NAME_9&quot;: &quot;_ATOMIC&quot;,\n",
       "    &quot;GS_BUFFER_KIND_5&quot;: &quot;ATTRIBUTE&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_7&quot;: &quot;discarded&quot;,\n",
       "    &quot;GS_BACKGROUND_G&quot;: &quot;1.0&quot;,\n",
       "    &quot;GS_BUFFER_KIND_6&quot;: &quot;SCRATCH&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_8&quot;: &quot;kept&quot;,\n",
       "    &quot;GS_BUFFER_KIND_7&quot;: &quot;SCRATCH&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_9&quot;: &quot;total_risky&quot;,\n",
       "    &quot;GS_BUFFER_KIND_8&quot;: &quot;SCRATCH&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_10&quot;: &quot;total_vuln_and_risky&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_11&quot;: &quot;total_vuln&quot;,\n",
       "    &quot;GS_BUFFER_KIND_9&quot;: &quot;ATOMIC&quot;,\n",
       "    &quot;GS_BACKGROUND_R&quot;: &quot;1.0&quot;,\n",
       "    &quot;GS_SHADER_COMMON&quot;: &quot;\\n#version 460 core\\nprecision mediump float;\\n\\nuniform float uTranslateX;\\nuniform float uTranslateY;\\nuniform float uScale;\\n// JS-Deps: Node Package Manager Dependency Graph\\n//\\n// Nodes are packages. Edges are directed from a package to its dependencies.\\n\\nlayout (std430, binding=0) buffer _X { float X[]; }; // attribute(float X[N])\\nlayout (std430, binding=1) buffer _Y { float Y[]; }; // attribute(float Y[N])\\nlayout (std430, binding=2) buffer _Date { uint Date[]; }; // attribute(uint Date[N])\\nlayout (std430, binding=3) buffer _Devs { uint Devs[]; }; // attribute(uint Devs[N])\\nlayout (std430, binding=4) buffer _Vuln { uint Vuln[]; }; // attribute(uint Vuln[N])\\n\\n#define NOV_09_2010 1289278800\\n#define MAR_22_2016 1458619200\\n\\n#define JAN_01_2011 1293858000\\n#define JAN_01_2012 1325394000\\n#define JAN_01_2013 1357016400\\n#define JAN_01_2014 1388552400\\n#define JAN_01_2015 1420088400\\n#define JAN_01_2016 1451624400\\n\\n// Some controls\\n\\n\\nlayout (std430, binding=5) buffer _in_degree { uint in_degree[]; }; // scratch(uint in_degree[N])\\nlayout (std430, binding=6) buffer _out_degree { uint out_degree[]; }; // scratch(uint out_degree[N])\\nlayout (binding=0, offset=0) uniform atomic_uint in_degree_max; // scratch(atomic_uint in_degree_max)\\nlayout (binding=0, offset=4) uniform atomic_uint out_degree_max; // scratch(atomic_uint out_degree_max)\\n#define USE_RELATIONAL 1\\nlayout (std430, binding=7) buffer _Seen { uint Seen[]; }; // scratch(uint Seen[E])\\nlayout (binding=0, offset=8) uniform atomic_uint total; // scratch(atomic_uint total)\\n#define FILTER_BY_DATE 1\\n#define LO JAN_01_2014\\n#define HI JAN_01_2015\\nlayout (binding=0, offset=12) uniform atomic_uint source_date_too_lo; // scratch(atomic_uint source_date_too_lo)\\nlayout (binding=0, offset=16) uniform atomic_uint source_date_too_hi; // scratch(atomic_uint source_date_too_hi)\\nlayout (binding=0, offset=20) uniform atomic_uint target_date_too_lo; // scratch(atomic_uint target_date_too_lo)\\nlayout (binding=0, offset=24) uniform atomic_uint target_date_too_hi; // scratch(atomic_uint target_date_too_hi)\\nlayout (binding=0, offset=28) uniform atomic_uint discarded; // scratch(atomic_uint discarded)\\nlayout (binding=0, offset=32) uniform atomic_uint kept; // scratch(atomic_uint kept)\\nlayout (binding=0, offset=36) uniform atomic_uint total_risky; // scratch(atomic_uint total_risky)\\nlayout (binding=0, offset=40) uniform atomic_uint total_vuln_and_risky; // scratch(atomic_uint total_vuln_and_risky)\\nlayout (binding=0, offset=44) uniform atomic_uint total_vuln; // scratch(atomic_uint total_vuln)\\n    &quot;,\n",
       "    &quot;GS_TILE_X&quot;: &quot;0&quot;,\n",
       "    &quot;GS_TILE_Y&quot;: &quot;0&quot;\n",
       "}\n",
       "</textarea>"
      ],
      "text/plain": [
       "<mediocreatbest._textarea.Textarea at 0x7fe7faebfc10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#@title cbf4d9cd\n",
    "def scope():\n",
    "    env = Transpile(\n",
    "        auto.pathlib.Path('examples/JS-Deps/JS-Deps.gsp').read_text(),\n",
    "        files=dict(\n",
    "            element=\"examples/JS-Deps/data/JS-Deps.edge.elements.2u32.bin\",\n",
    "            X      =\"examples/JS-Deps/data/JS-Deps.node.x.f32.bin\",\n",
    "            Y      =\"examples/JS-Deps/data/JS-Deps.node.y.f32.bin\",\n",
    "            Date   =\"examples/JS-Deps/data/JS-Deps.node.date.u32.bin\",\n",
    "            Devs   =\"examples/JS-Deps/data/JS-Deps.node.nmaintainers.u32.bin\",\n",
    "            Vuln   =\"examples/JS-Deps/data/JS-Deps.node.cve.u32.bin\",\n",
    "        ),\n",
    "    )\n",
    "\n",
    "    with auto.mediocreatbest.Textarea():\n",
    "        print(auto.json.dumps({\n",
    "            k: v\n",
    "            for k, v in env.items()\n",
    "            if k.startswith('GS_')\n",
    "        }, indent=4))\n",
    "\n",
    "/scope\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ad102104",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<textarea rows=12 style=\"width: 90%; margin-left: 5%\">from mediocreatbest import auto\n",
       "\n",
       "env = {\n",
       "    &quot;GS_TILE_HEIGHT&quot;: &quot;256&quot;,\n",
       "    &quot;GS_TILE_Z&quot;: &quot;0&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_0&quot;: &quot;2E&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_1&quot;: &quot;N&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_2&quot;: &quot;N&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_3&quot;: &quot;N&quot;,\n",
       "    &quot;GS_SHADER_GEOMETRY&quot;: &quot;\\nlayout (lines) in;\\nlayout (line_strip, max_vertices=2) out;\\n\\nlayout(location=0) in uint _fg_NodeIndex[];\\n\\nlayout(location=0) out flat uint gs_SourceIndex;\\nlayout(location=1) out flat uint gs_TargetIndex;\\n\\nvoid main() {\\n    gs_SourceIndex = _fg_NodeIndex[0];\\n    gs_TargetIndex = _fg_NodeIndex[1];\\n\\n    int gs_EdgeIndex = gl_PrimitiveIDIn;\\n    vec4 gs_SourcePosition = gl_in[0].gl_Position;\\n    vec4 gs_TargetPosition = gl_in[1].gl_Position;\\n\\n\\n    #if USE_RELATIONAL\\n    uint od = 1 + atomicAdd(out_degree[gs_SourceIndex], 1);\\n    atomicCounterMax(out_degree_max, od);\\n\\n    uint id = 1 + atomicAdd(in_degree[gs_TargetIndex], 1);\\n    atomicCounterMax(in_degree_max, id);\\n    #endif /* USE_RELATIONAL */\\n\\n\\n\\n    // Apply tile transformations\\n    gs_SourcePosition.xy *= uScale;\\n    gs_SourcePosition.xy += vec2(uTranslateX, uTranslateY);\\n\\n    // Transform xy in [0, 1] to xy in [-1, 1]\\n    gs_SourcePosition.xy *= 2.;\\n    gs_SourcePosition.xy -= 1.;\\n\\n    // Apply tile transformations\\n    gs_TargetPosition.xy *= uScale;\\n    gs_TargetPosition.xy += vec2(uTranslateX, uTranslateY);\\n\\n    // Transform xy in [0, 1] to xy in [-1, 1]\\n    gs_TargetPosition.xy *= 2.;\\n    gs_TargetPosition.xy -= 1.;\\n\\n    gl_PrimitiveID = gs_EdgeIndex;\\n    gl_Position = gs_SourcePosition;\\n    EmitVertex();\\n\\n    gl_Position = gs_TargetPosition;\\n    EmitVertex();\\n\\n    EndPrimitive();\\n}\\n    &quot;,\n",
       "    &quot;GS_BUFFER_SIZE_4&quot;: &quot;N&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_5&quot;: &quot;N&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_6&quot;: &quot;N&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_0&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_7&quot;: &quot;N&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_1&quot;: &quot;GL_FLOAT&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_8&quot;: &quot;E&quot;,\n",
       "    &quot;GS_OUTPUT&quot;: &quot;out.jpg&quot;,\n",
       "    &quot;GS_BUFFER_BIND_0&quot;: &quot;&lt;NONE&gt;&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_2&quot;: &quot;GL_FLOAT&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_9&quot;: &quot;48&quot;,\n",
       "    &quot;GS_BUFFER_BIND_1&quot;: &quot;0&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_3&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_BUFFER_BIND_2&quot;: &quot;1&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_4&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_BUFFER_FILE_0&quot;: &quot;examples/JS-Deps/data/JS-Deps.edge.elements.2u32.bin&quot;,\n",
       "    &quot;GS_BUFFER_BIND_3&quot;: &quot;2&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_5&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_BUFFER_COUNT&quot;: &quot;10&quot;,\n",
       "    &quot;GS_BUFFER_NAME_0&quot;: &quot;_ELEMENT&quot;,\n",
       "    &quot;GS_BUFFER_FILE_1&quot;: &quot;examples/JS-Deps/data/JS-Deps.node.x.f32.bin&quot;,\n",
       "    &quot;GS_BUFFER_BIND_4&quot;: &quot;3&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_6&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_BUFFER_NAME_1&quot;: &quot;_X&quot;,\n",
       "    &quot;GS_BUFFER_FILE_2&quot;: &quot;examples/JS-Deps/data/JS-Deps.node.y.f32.bin&quot;,\n",
       "    &quot;GS_BUFFER_BIND_5&quot;: &quot;4&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_7&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_BUFFER_NAME_2&quot;: &quot;_Y&quot;,\n",
       "    &quot;GS_BUFFER_FILE_3&quot;: &quot;examples/JS-Deps/data/JS-Deps.node.date.u32.bin&quot;,\n",
       "    &quot;GS_BUFFER_BIND_6&quot;: &quot;5&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_8&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_ATOMIC_COUNT&quot;: &quot;12&quot;,\n",
       "    &quot;GS_BUFFER_NAME_3&quot;: &quot;_Date&quot;,\n",
       "    &quot;GS_BUFFER_FILE_4&quot;: &quot;examples/JS-Deps/data/JS-Deps.node.nmaintainers.u32.bin&quot;,\n",
       "    &quot;GS_BUFFER_BIND_7&quot;: &quot;6&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_0&quot;: &quot;in_degree_max&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_9&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_BUFFER_NAME_4&quot;: &quot;_Devs&quot;,\n",
       "    &quot;GS_BUFFER_FILE_5&quot;: &quot;examples/JS-Deps/data/JS-Deps.node.cve.u32.bin&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_1&quot;: &quot;out_degree_max&quot;,\n",
       "    &quot;GS_BUFFER_BIND_8&quot;: &quot;7&quot;,\n",
       "    &quot;GS_SHADER_VERTEX&quot;: &quot;\\n\\nlayout(location=0) out uint _fg_NodeIndex;\\n\\nvoid main() {\\n    const int gs_NodeIndex = gl_VertexID;\\n    vec3 gs_NodePosition = vec3(0., 0., 0.);\\n\\n    float x = X[gs_NodeIndex];\\n    float y = Y[gs_NodeIndex];\\n\\n    gs_NodePosition = vec3(x, y, 0);\\n\\n\\n\\n    gl_Position = vec4(gs_NodePosition.xyz, 1.);\\n\\n    _fg_NodeIndex = gs_NodeIndex;\\n}\\n    &quot;,\n",
       "    &quot;GS_BACKGROUND_A&quot;: &quot;1.0&quot;,\n",
       "    &quot;GS_BUFFER_KIND_0&quot;: &quot;ELEMENT&quot;,\n",
       "    &quot;GS_BUFFER_NAME_5&quot;: &quot;_Vuln&quot;,\n",
       "    &quot;GS_BUFFER_FILE_6&quot;: &quot;&lt;NONE&gt;&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_2&quot;: &quot;total&quot;,\n",
       "    &quot;GS_BUFFER_BIND_9&quot;: &quot;0&quot;,\n",
       "    &quot;GS_SHADER_FRAGMENT&quot;: &quot;\\nlayout(location=0) in flat uint gs_SourceIndex;\\nlayout(location=1) in flat uint gs_TargetIndex;\\n\\nlayout(location=0) out vec4 gs_FragColor;\\n\\nvoid main() {\\n    int gs_EdgeIndex = gl_PrimitiveID;\\n    bool first = 0 == atomicAdd(Seen[gs_EdgeIndex], 1);\\n    bool d = false;\\n\\n    if (first) atomicCounterAdd(total, 1);\\n\\n    #if FILTER_BY_DATE\\n\\n    if (Date[gs_SourceIndex] &lt; LO) {\\n        d = true;\\n        if (first) atomicCounterAdd(source_date_too_lo, 1);\\n    }\\n\\n    if (Date[gs_SourceIndex] &gt; HI) {\\n        d = true;\\n        if (first) atomicCounterAdd(source_date_too_hi, 1);\\n    }\\n\\n    if (Date[gs_TargetIndex] &lt; LO) {\\n        d = true;\\n        if (first) atomicCounterAdd(target_date_too_lo, 1);\\n    }\\n\\n    if (Date[gs_TargetIndex] &gt; HI) {\\n        d = true;\\n        if (first) atomicCounterAdd(target_date_too_hi, 1);\\n    }\\n    #endif /* FILTER_BY_DATE */\\n\\n    if (d) {\\n        if (first) atomicCounterAdd(discarded, 1);\\n        discard;\\n    } else {\\n        if (first) atomicCounterAdd(kept, 1);\\n    }\\n\\n    bool vuln = bool(Vuln[gs_SourceIndex]) || bool(Vuln[gs_TargetIndex]);\\n    bool risky = Devs[gs_SourceIndex] &gt; Devs[gs_TargetIndex];\\n\\n    #if USE_RELATIONAL\\n    const uint depends_on_source = in_degree[gs_SourceIndex];\\n    const uint depends_on_target = in_degree[gs_TargetIndex];\\n\\n    risky = depends_on_source + depends_on_target &gt; 100 * Devs[gs_TargetIndex];\\n    #endif /* USE_RELATIONAL */\\n\\n    if (risky) {\\n        if (first) atomicCounterAdd(total_risky, 1);\\n    }\\n\\n    if (risky &amp;&amp; vuln) {\\n        if (first) atomicCounterAdd(total_vuln_and_risky, 1);\\n    }\\n\\n    if (vuln) {\\n        if (first) atomicCounterAdd(total_vuln, 1);\\n    }\\n\\n    gs_FragColor = vec4(0.1);\\n    gs_FragColor.r = float(vuln);\\n    gs_FragColor.b = float(risky);\\n}\\n    &quot;,\n",
       "    &quot;GS_BACKGROUND_B&quot;: &quot;1.0&quot;,\n",
       "    &quot;GS_BUFFER_KIND_1&quot;: &quot;ATTRIBUTE&quot;,\n",
       "    &quot;GS_BUFFER_NAME_6&quot;: &quot;_in_degree&quot;,\n",
       "    &quot;GS_BUFFER_FILE_7&quot;: &quot;&lt;NONE&gt;&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_3&quot;: &quot;source_date_too_lo&quot;,\n",
       "    &quot;GS_TILE_WIDTH&quot;: &quot;256&quot;,\n",
       "    &quot;GS_BUFFER_KIND_2&quot;: &quot;ATTRIBUTE&quot;,\n",
       "    &quot;GS_BUFFER_NAME_7&quot;: &quot;_out_degree&quot;,\n",
       "    &quot;GS_BUFFER_FILE_8&quot;: &quot;&lt;NONE&gt;&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_4&quot;: &quot;source_date_too_hi&quot;,\n",
       "    &quot;GS_BUFFER_KIND_3&quot;: &quot;ATTRIBUTE&quot;,\n",
       "    &quot;GS_BUFFER_NAME_8&quot;: &quot;_Seen&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_5&quot;: &quot;target_date_too_lo&quot;,\n",
       "    &quot;GS_BUFFER_FILE_9&quot;: &quot;&lt;NONE&gt;&quot;,\n",
       "    &quot;GS_BUFFER_KIND_4&quot;: &quot;ATTRIBUTE&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_6&quot;: &quot;target_date_too_hi&quot;,\n",
       "    &quot;GS_BUFFER_NAME_9&quot;: &quot;_ATOMIC&quot;,\n",
       "    &quot;GS_BUFFER_KIND_5&quot;: &quot;ATTRIBUTE&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_7&quot;: &quot;discarded&quot;,\n",
       "    &quot;GS_BACKGROUND_G&quot;: &quot;1.0&quot;,\n",
       "    &quot;GS_BUFFER_KIND_6&quot;: &quot;SCRATCH&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_8&quot;: &quot;kept&quot;,\n",
       "    &quot;GS_BUFFER_KIND_7&quot;: &quot;SCRATCH&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_9&quot;: &quot;total_risky&quot;,\n",
       "    &quot;GS_BUFFER_KIND_8&quot;: &quot;SCRATCH&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_10&quot;: &quot;total_vuln_and_risky&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_11&quot;: &quot;total_vuln&quot;,\n",
       "    &quot;GS_BUFFER_KIND_9&quot;: &quot;ATOMIC&quot;,\n",
       "    &quot;GS_BACKGROUND_R&quot;: &quot;1.0&quot;,\n",
       "    &quot;GS_SHADER_COMMON&quot;: &quot;\\n#version 460 core\\nprecision mediump float;\\n\\nuniform float uTranslateX;\\nuniform float uTranslateY;\\nuniform float uScale;\\n// JS-Deps: Node Package Manager Dependency Graph\\n//\\n// Nodes are packages. Edges are directed from a package to its dependencies.\\n\\nlayout (std430, binding=0) buffer _X { float X[]; }; // attribute(float X[N])\\nlayout (std430, binding=1) buffer _Y { float Y[]; }; // attribute(float Y[N])\\nlayout (std430, binding=2) buffer _Date { uint Date[]; }; // attribute(uint Date[N])\\nlayout (std430, binding=3) buffer _Devs { uint Devs[]; }; // attribute(uint Devs[N])\\nlayout (std430, binding=4) buffer _Vuln { uint Vuln[]; }; // attribute(uint Vuln[N])\\n\\n#define NOV_09_2010 1289278800\\n#define MAR_22_2016 1458619200\\n\\n#define JAN_01_2011 1293858000\\n#define JAN_01_2012 1325394000\\n#define JAN_01_2013 1357016400\\n#define JAN_01_2014 1388552400\\n#define JAN_01_2015 1420088400\\n#define JAN_01_2016 1451624400\\n\\n// Some controls\\n\\n\\nlayout (std430, binding=5) buffer _in_degree { uint in_degree[]; }; // scratch(uint in_degree[N])\\nlayout (std430, binding=6) buffer _out_degree { uint out_degree[]; }; // scratch(uint out_degree[N])\\nlayout (binding=0, offset=0) uniform atomic_uint in_degree_max; // scratch(atomic_uint in_degree_max)\\nlayout (binding=0, offset=4) uniform atomic_uint out_degree_max; // scratch(atomic_uint out_degree_max)\\n#define USE_RELATIONAL 1\\nlayout (std430, binding=7) buffer _Seen { uint Seen[]; }; // scratch(uint Seen[E])\\nlayout (binding=0, offset=8) uniform atomic_uint total; // scratch(atomic_uint total)\\n#define FILTER_BY_DATE 1\\n#define LO JAN_01_2014\\n#define HI JAN_01_2015\\nlayout (binding=0, offset=12) uniform atomic_uint source_date_too_lo; // scratch(atomic_uint source_date_too_lo)\\nlayout (binding=0, offset=16) uniform atomic_uint source_date_too_hi; // scratch(atomic_uint source_date_too_hi)\\nlayout (binding=0, offset=20) uniform atomic_uint target_date_too_lo; // scratch(atomic_uint target_date_too_lo)\\nlayout (binding=0, offset=24) uniform atomic_uint target_date_too_hi; // scratch(atomic_uint target_date_too_hi)\\nlayout (binding=0, offset=28) uniform atomic_uint discarded; // scratch(atomic_uint discarded)\\nlayout (binding=0, offset=32) uniform atomic_uint kept; // scratch(atomic_uint kept)\\nlayout (binding=0, offset=36) uniform atomic_uint total_risky; // scratch(atomic_uint total_risky)\\nlayout (binding=0, offset=40) uniform atomic_uint total_vuln_and_risky; // scratch(atomic_uint total_vuln_and_risky)\\nlayout (binding=0, offset=44) uniform atomic_uint total_vuln; // scratch(atomic_uint total_vuln)\\n    &quot;,\n",
       "    &quot;GS_TILE_X&quot;: &quot;0&quot;,\n",
       "    &quot;GS_TILE_Y&quot;: &quot;0&quot;,\n",
       "}\n",
       "\n",
       "@auto.functools.cache\n",
       "def GS():\n",
       "    root = auto.pathlib.Path.cwd()\n",
       "\n",
       "    path = root / &#x27;src&#x27;\n",
       "    if str(path) not in auto.sys.path:\n",
       "        auto.sys.path.append(str(path))\n",
       "\n",
       "    path = root / &#x27;stage&#x27; / &#x27;lib&#x27; / &#x27;libgraphshader.so&#x27;\n",
       "    assert path.exists(), path\n",
       "    gs = auto.graphshader.GS.load(str(path))\n",
       "\n",
       "    return gs\n",
       "\n",
       "gs = GS()\n",
       "\n",
       "enter = auto.contextlib.ExitStack().enter_context\n",
       "\n",
       "print(&#x27;gs.environment()&#x27;)\n",
       "enter( gs.environment() )\n",
       "\n",
       "for k, v in env.items():\n",
       "    gs[k] = v\n",
       "\n",
       "gs[&#x27;GS_OUTPUT&#x27;] = &#x27;&lt;MEMORY&gt;&#x27;\n",
       "\n",
       "print(&#x27;gs.egl()&#x27;)\n",
       "enter( gs.egl() )\n",
       "\n",
       "print(&#x27;gs.gl()&#x27;)\n",
       "enter( gs.gl() )\n",
       "\n",
       "print(&#x27;gs.data()&#x27;)\n",
       "enter( gs.data() )\n",
       "\n",
       "print(&#x27;gs.shader()&#x27;)\n",
       "enter( gs.shader() )\n",
       "\n",
       "print(&#x27;gs.render()&#x27;)\n",
       "image = enter( gs.render() )\n",
       "\n",
       "root = auto.pathlib.Path.cwd()\n",
       "path = root / &#x27;out.jpg&#x27;\n",
       "\n",
       "with path.open(&#x27;wb&#x27;) as f:\n",
       "    f.write(image)\n",
       "print(f&#x27;Wrote {path.stat().st_size:,d} bytes to {path}&#x27;)\n",
       "\n",
       "# auto.IPython.display.display(auto.IPython.display.Image(image))\n",
       "</textarea>"
      ],
      "text/plain": [
       "<mediocreatbest._textarea.Textarea at 0x7fe7fa94da00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "EGL_VERSION: 1.5\n",
      "EGL_VENDOR: NVIDIA\n",
      "EGL_CLIENT_APIS: OpenGL_ES OpenGL\n",
      "EGL_EXTENSIONS: EGL_EXT_buffer_age EGL_EXT_client_sync EGL_EXT_create_context_robustness EGL_EXT_image_dma_buf_import EGL_EXT_image_dma_buf_import_modifiers EGL_MESA_image_dma_buf_export EGL_EXT_output_base EGL_EXT_protected_content EGL_EXT_stream_acquire_mode EGL_EXT_sync_reuse EGL_IMG_context_priority EGL_KHR_config_attribs EGL_KHR_create_context_no_error EGL_KHR_context_flush_control EGL_KHR_create_context EGL_KHR_fence_sync EGL_KHR_get_all_proc_addresses EGL_KHR_partial_update EGL_KHR_swap_buffers_with_damage EGL_KHR_no_config_context EGL_KHR_gl_colorspace EGL_KHR_gl_renderbuffer_image EGL_KHR_gl_texture_2D_image EGL_KHR_gl_texture_3D_image EGL_KHR_gl_texture_cubemap_image EGL_KHR_image EGL_KHR_image_base EGL_KHR_reusable_sync EGL_KHR_stream EGL_KHR_stream_attrib EGL_KHR_stream_consumer_gltexture EGL_KHR_stream_cross_process_fd EGL_KHR_stream_fifo EGL_KHR_stream_producer_eglsurface EGL_KHR_surfaceless_context EGL_KHR_wait_sync EGL_NV_nvrm_fence_sync EGL_NV_quadruple_buffer EGL_NV_stream_consumer_eglimage EGL_NV_stream_cross_display EGL_NV_stream_cross_object EGL_NV_stream_cross_process EGL_NV_stream_cross_system EGL_NV_stream_dma EGL_NV_stream_flush EGL_NV_stream_metadata EGL_NV_stream_remote EGL_NV_stream_reset EGL_NV_stream_socket EGL_NV_stream_socket_inet EGL_NV_stream_socket_unix EGL_NV_stream_sync EGL_NV_stream_fifo_next EGL_NV_stream_fifo_synchronous EGL_NV_stream_consumer_gltexture_yuv EGL_NV_stream_attrib EGL_NV_stream_origin EGL_NV_system_time EGL_NV_output_drm_flip_event EGL_NV_triple_buffer EGL_NV_robustness_video_memory_purge\n",
      "GL_VENDOR: NVIDIA Corporation\n",
      "GL_VERSION: 4.6.0 NVIDIA 535.183.06\n",
      "GL_RENDERER: Quadro M6000 24GB/PCIe/SSE2\n",
      "GL_SHADING_LANGUAGE_VERSION: 4.60 NVIDIA\n",
      "buffer 0\n",
      "  name: _ELEMENT\n",
      "  kind: ELEMENT\n",
      "  file: examples/JS-Deps/data/JS-Deps.edge.elements.2u32.bin\n",
      "  size: 2E\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "Read from examples/JS-Deps/data/JS-Deps.edge.elements.2u32.bin\n",
      "buffer 1\n",
      "  name: _X\n",
      "  kind: ATTRIBUTE\n",
      "  file: examples/JS-Deps/data/JS-Deps.node.x.f32.bin\n",
      "  size: N\n",
      "  type: GL_FLOAT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "Read from examples/JS-Deps/data/JS-Deps.node.x.f32.bin\n",
      "buffer 2\n",
      "  name: _Y\n",
      "  kind: ATTRIBUTE\n",
      "  file: examples/JS-Deps/data/JS-Deps.node.y.f32.bin\n",
      "  size: N\n",
      "  type: GL_FLOAT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "Read from examples/JS-Deps/data/JS-Deps.node.y.f32.bin\n",
      "buffer 3\n",
      "  name: _Date\n",
      "  kind: ATTRIBUTE\n",
      "  file: examples/JS-Deps/data/JS-Deps.node.date.u32.bin\n",
      "  size: N\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "Read from examples/JS-Deps/data/JS-Deps.node.date.u32.bin\n",
      "buffer 4\n",
      "  name: _Devs\n",
      "  kind: ATTRIBUTE\n",
      "  file: examples/JS-Deps/data/JS-Deps.node.nmaintainers.u32.bin\n",
      "  size: N\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "Read from examples/JS-Deps/data/JS-Deps.node.nmaintainers.u32.bin\n",
      "buffer 5\n",
      "  name: _Vuln\n",
      "  kind: ATTRIBUTE\n",
      "  file: examples/JS-Deps/data/JS-Deps.node.cve.u32.bin\n",
      "  size: N\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "Read from examples/JS-Deps/data/JS-Deps.node.cve.u32.bin\n",
      "buffer 6\n",
      "  name: _in_degree\n",
      "  kind: SCRATCH\n",
      "  file: <NONE>\n",
      "  size: N\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "buffer 7\n",
      "  name: _out_degree\n",
      "  kind: SCRATCH\n",
      "  file: <NONE>\n",
      "  size: N\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "buffer 8\n",
      "  name: _Seen\n",
      "  kind: SCRATCH\n",
      "  file: <NONE>\n",
      "  size: E\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "buffer 9\n",
      "  name: _ATOMIC\n",
      "  kind: ATOMIC\n",
      "  file: <NONE>\n",
      "  size: 48\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "gs.environment()\n",
      "gs.egl()\n",
      "gs.gl()\n",
      "gs.data()\n",
      "gs.shader()\n",
      "gs.render()\n",
      "Wrote 24,379 bytes to /home/thobson2/src/GraphShaders2/out.jpg\n",
      "{\n",
      "  \"metadata\": {\n",
      "     \"nodes\": 1144424,\n",
      "     \"edges\": 6136134\n",
      "  },\n",
      "  \"atomics\": {\n",
      "    \"in_degree_max\": 79037,\n",
      "    \"out_degree_max\": 389,\n",
      "    \"total\": 6074422,\n",
      "    \"source_date_too_lo\": 727708,\n",
      "    \"source_date_too_hi\": 3929819,\n",
      "    \"target_date_too_lo\": 988494,\n",
      "    \"target_date_too_hi\": 3784427,\n",
      "    \"discarded\": 5416693,\n",
      "    \"kept\": 657729,\n",
      "    \"total_risky\": 316826,\n",
      "    \"total_vuln_and_risky\": 48344,\n",
      "    \"total_vuln\": 72566\n",
      "  }\n",
      "}\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 0, 2)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 1, 3)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 2, 4)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 3, 5)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 4, 6)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 5, 7)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 6, 8)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 7, 9)\n",
      "glDrawElements(0x1, 12272268, 0x1405, (nil))\n",
      "--- Atomics\n",
      "atomic 0 \"in_degree_max\" = 79037\n",
      "atomic 1 \"out_degree_max\" = 389\n",
      "atomic 2 \"total\" = 6074422\n",
      "atomic 3 \"source_date_too_lo\" = 727708\n",
      "atomic 4 \"source_date_too_hi\" = 3929819\n",
      "atomic 5 \"target_date_too_lo\" = 988494\n",
      "atomic 6 \"target_date_too_hi\" = 3784427\n",
      "atomic 7 \"discarded\" = 5416693\n",
      "atomic 8 \"kept\" = 657729\n",
      "atomic 9 \"total_risky\" = 316826\n",
      "atomic 10 \"total_vuln_and_risky\" = 48344\n",
      "atomic 11 \"total_vuln\" = 72566\n",
      "JPEG: 256x256\n"
     ]
    }
   ],
   "source": [
    "#@title 41c4795e\n",
    "def scope():\n",
    "    def scope():\n",
    "        from mediocreatbest import auto\n",
    "        \n",
    "        env = {\n",
    "            \"GS_TILE_HEIGHT\": \"256\",\n",
    "            \"GS_TILE_Z\": \"0\",\n",
    "            \"GS_BUFFER_SIZE_0\": \"2E\",\n",
    "            \"GS_BUFFER_SIZE_1\": \"N\",\n",
    "            \"GS_BUFFER_SIZE_2\": \"N\",\n",
    "            \"GS_BUFFER_SIZE_3\": \"N\",\n",
    "            \"GS_SHADER_GEOMETRY\": \"\\nlayout (lines) in;\\nlayout (line_strip, max_vertices=2) out;\\n\\nlayout(location=0) in uint _fg_NodeIndex[];\\n\\nlayout(location=0) out flat uint gs_SourceIndex;\\nlayout(location=1) out flat uint gs_TargetIndex;\\n\\nvoid main() {\\n    gs_SourceIndex = _fg_NodeIndex[0];\\n    gs_TargetIndex = _fg_NodeIndex[1];\\n\\n    int gs_EdgeIndex = gl_PrimitiveIDIn;\\n    vec4 gs_SourcePosition = gl_in[0].gl_Position;\\n    vec4 gs_TargetPosition = gl_in[1].gl_Position;\\n\\n\\n    #if USE_RELATIONAL\\n    uint od = 1 + atomicAdd(out_degree[gs_SourceIndex], 1);\\n    atomicCounterMax(out_degree_max, od);\\n\\n    uint id = 1 + atomicAdd(in_degree[gs_TargetIndex], 1);\\n    atomicCounterMax(in_degree_max, id);\\n    #endif /* USE_RELATIONAL */\\n\\n\\n\\n    // Apply tile transformations\\n    gs_SourcePosition.xy *= uScale;\\n    gs_SourcePosition.xy += vec2(uTranslateX, uTranslateY);\\n\\n    // Transform xy in [0, 1] to xy in [-1, 1]\\n    gs_SourcePosition.xy *= 2.;\\n    gs_SourcePosition.xy -= 1.;\\n\\n    // Apply tile transformations\\n    gs_TargetPosition.xy *= uScale;\\n    gs_TargetPosition.xy += vec2(uTranslateX, uTranslateY);\\n\\n    // Transform xy in [0, 1] to xy in [-1, 1]\\n    gs_TargetPosition.xy *= 2.;\\n    gs_TargetPosition.xy -= 1.;\\n\\n    gl_PrimitiveID = gs_EdgeIndex;\\n    gl_Position = gs_SourcePosition;\\n    EmitVertex();\\n\\n    gl_Position = gs_TargetPosition;\\n    EmitVertex();\\n\\n    EndPrimitive();\\n}\\n    \",\n",
    "            \"GS_BUFFER_SIZE_4\": \"N\",\n",
    "            \"GS_BUFFER_SIZE_5\": \"N\",\n",
    "            \"GS_BUFFER_SIZE_6\": \"N\",\n",
    "            \"GS_BUFFER_TYPE_0\": \"GL_UNSIGNED_INT\",\n",
    "            \"GS_BUFFER_SIZE_7\": \"N\",\n",
    "            \"GS_BUFFER_TYPE_1\": \"GL_FLOAT\",\n",
    "            \"GS_BUFFER_SIZE_8\": \"E\",\n",
    "            \"GS_OUTPUT\": \"out.jpg\",\n",
    "            \"GS_BUFFER_BIND_0\": \"<NONE>\",\n",
    "            \"GS_BUFFER_TYPE_2\": \"GL_FLOAT\",\n",
    "            \"GS_BUFFER_SIZE_9\": \"48\",\n",
    "            \"GS_BUFFER_BIND_1\": \"0\",\n",
    "            \"GS_BUFFER_TYPE_3\": \"GL_UNSIGNED_INT\",\n",
    "            \"GS_BUFFER_BIND_2\": \"1\",\n",
    "            \"GS_BUFFER_TYPE_4\": \"GL_UNSIGNED_INT\",\n",
    "            \"GS_BUFFER_FILE_0\": \"examples/JS-Deps/data/JS-Deps.edge.elements.2u32.bin\",\n",
    "            \"GS_BUFFER_BIND_3\": \"2\",\n",
    "            \"GS_BUFFER_TYPE_5\": \"GL_UNSIGNED_INT\",\n",
    "            \"GS_BUFFER_COUNT\": \"10\",\n",
    "            \"GS_BUFFER_NAME_0\": \"_ELEMENT\",\n",
    "            \"GS_BUFFER_FILE_1\": \"examples/JS-Deps/data/JS-Deps.node.x.f32.bin\",\n",
    "            \"GS_BUFFER_BIND_4\": \"3\",\n",
    "            \"GS_BUFFER_TYPE_6\": \"GL_UNSIGNED_INT\",\n",
    "            \"GS_BUFFER_NAME_1\": \"_X\",\n",
    "            \"GS_BUFFER_FILE_2\": \"examples/JS-Deps/data/JS-Deps.node.y.f32.bin\",\n",
    "            \"GS_BUFFER_BIND_5\": \"4\",\n",
    "            \"GS_BUFFER_TYPE_7\": \"GL_UNSIGNED_INT\",\n",
    "            \"GS_BUFFER_NAME_2\": \"_Y\",\n",
    "            \"GS_BUFFER_FILE_3\": \"examples/JS-Deps/data/JS-Deps.node.date.u32.bin\",\n",
    "            \"GS_BUFFER_BIND_6\": \"5\",\n",
    "            \"GS_BUFFER_TYPE_8\": \"GL_UNSIGNED_INT\",\n",
    "            \"GS_ATOMIC_COUNT\": \"12\",\n",
    "            \"GS_BUFFER_NAME_3\": \"_Date\",\n",
    "            \"GS_BUFFER_FILE_4\": \"examples/JS-Deps/data/JS-Deps.node.nmaintainers.u32.bin\",\n",
    "            \"GS_BUFFER_BIND_7\": \"6\",\n",
    "            \"GS_ATOMIC_NAME_0\": \"in_degree_max\",\n",
    "            \"GS_BUFFER_TYPE_9\": \"GL_UNSIGNED_INT\",\n",
    "            \"GS_BUFFER_NAME_4\": \"_Devs\",\n",
    "            \"GS_BUFFER_FILE_5\": \"examples/JS-Deps/data/JS-Deps.node.cve.u32.bin\",\n",
    "            \"GS_ATOMIC_NAME_1\": \"out_degree_max\",\n",
    "            \"GS_BUFFER_BIND_8\": \"7\",\n",
    "            \"GS_SHADER_VERTEX\": \"\\n\\nlayout(location=0) out uint _fg_NodeIndex;\\n\\nvoid main() {\\n    const int gs_NodeIndex = gl_VertexID;\\n    vec3 gs_NodePosition = vec3(0., 0., 0.);\\n\\n    float x = X[gs_NodeIndex];\\n    float y = Y[gs_NodeIndex];\\n\\n    gs_NodePosition = vec3(x, y, 0);\\n\\n\\n\\n    gl_Position = vec4(gs_NodePosition.xyz, 1.);\\n\\n    _fg_NodeIndex = gs_NodeIndex;\\n}\\n    \",\n",
    "            \"GS_BACKGROUND_A\": \"1.0\",\n",
    "            \"GS_BUFFER_KIND_0\": \"ELEMENT\",\n",
    "            \"GS_BUFFER_NAME_5\": \"_Vuln\",\n",
    "            \"GS_BUFFER_FILE_6\": \"<NONE>\",\n",
    "            \"GS_ATOMIC_NAME_2\": \"total\",\n",
    "            \"GS_BUFFER_BIND_9\": \"0\",\n",
    "            \"GS_SHADER_FRAGMENT\": \"\\nlayout(location=0) in flat uint gs_SourceIndex;\\nlayout(location=1) in flat uint gs_TargetIndex;\\n\\nlayout(location=0) out vec4 gs_FragColor;\\n\\nvoid main() {\\n    int gs_EdgeIndex = gl_PrimitiveID;\\n    bool first = 0 == atomicAdd(Seen[gs_EdgeIndex], 1);\\n    bool d = false;\\n\\n    if (first) atomicCounterAdd(total, 1);\\n\\n    #if FILTER_BY_DATE\\n\\n    if (Date[gs_SourceIndex] < LO) {\\n        d = true;\\n        if (first) atomicCounterAdd(source_date_too_lo, 1);\\n    }\\n\\n    if (Date[gs_SourceIndex] > HI) {\\n        d = true;\\n        if (first) atomicCounterAdd(source_date_too_hi, 1);\\n    }\\n\\n    if (Date[gs_TargetIndex] < LO) {\\n        d = true;\\n        if (first) atomicCounterAdd(target_date_too_lo, 1);\\n    }\\n\\n    if (Date[gs_TargetIndex] > HI) {\\n        d = true;\\n        if (first) atomicCounterAdd(target_date_too_hi, 1);\\n    }\\n    #endif /* FILTER_BY_DATE */\\n\\n    if (d) {\\n        if (first) atomicCounterAdd(discarded, 1);\\n        discard;\\n    } else {\\n        if (first) atomicCounterAdd(kept, 1);\\n    }\\n\\n    bool vuln = bool(Vuln[gs_SourceIndex]) || bool(Vuln[gs_TargetIndex]);\\n    bool risky = Devs[gs_SourceIndex] > Devs[gs_TargetIndex];\\n\\n    #if USE_RELATIONAL\\n    const uint depends_on_source = in_degree[gs_SourceIndex];\\n    const uint depends_on_target = in_degree[gs_TargetIndex];\\n\\n    risky = depends_on_source + depends_on_target > 100 * Devs[gs_TargetIndex];\\n    #endif /* USE_RELATIONAL */\\n\\n    if (risky) {\\n        if (first) atomicCounterAdd(total_risky, 1);\\n    }\\n\\n    if (risky && vuln) {\\n        if (first) atomicCounterAdd(total_vuln_and_risky, 1);\\n    }\\n\\n    if (vuln) {\\n        if (first) atomicCounterAdd(total_vuln, 1);\\n    }\\n\\n    gs_FragColor = vec4(0.1);\\n    gs_FragColor.r = float(vuln);\\n    gs_FragColor.b = float(risky);\\n}\\n    \",\n",
    "            \"GS_BACKGROUND_B\": \"1.0\",\n",
    "            \"GS_BUFFER_KIND_1\": \"ATTRIBUTE\",\n",
    "            \"GS_BUFFER_NAME_6\": \"_in_degree\",\n",
    "            \"GS_BUFFER_FILE_7\": \"<NONE>\",\n",
    "            \"GS_ATOMIC_NAME_3\": \"source_date_too_lo\",\n",
    "            \"GS_TILE_WIDTH\": \"256\",\n",
    "            \"GS_BUFFER_KIND_2\": \"ATTRIBUTE\",\n",
    "            \"GS_BUFFER_NAME_7\": \"_out_degree\",\n",
    "            \"GS_BUFFER_FILE_8\": \"<NONE>\",\n",
    "            \"GS_ATOMIC_NAME_4\": \"source_date_too_hi\",\n",
    "            \"GS_BUFFER_KIND_3\": \"ATTRIBUTE\",\n",
    "            \"GS_BUFFER_NAME_8\": \"_Seen\",\n",
    "            \"GS_ATOMIC_NAME_5\": \"target_date_too_lo\",\n",
    "            \"GS_BUFFER_FILE_9\": \"<NONE>\",\n",
    "            \"GS_BUFFER_KIND_4\": \"ATTRIBUTE\",\n",
    "            \"GS_ATOMIC_NAME_6\": \"target_date_too_hi\",\n",
    "            \"GS_BUFFER_NAME_9\": \"_ATOMIC\",\n",
    "            \"GS_BUFFER_KIND_5\": \"ATTRIBUTE\",\n",
    "            \"GS_ATOMIC_NAME_7\": \"discarded\",\n",
    "            \"GS_BACKGROUND_G\": \"1.0\",\n",
    "            \"GS_BUFFER_KIND_6\": \"SCRATCH\",\n",
    "            \"GS_ATOMIC_NAME_8\": \"kept\",\n",
    "            \"GS_BUFFER_KIND_7\": \"SCRATCH\",\n",
    "            \"GS_ATOMIC_NAME_9\": \"total_risky\",\n",
    "            \"GS_BUFFER_KIND_8\": \"SCRATCH\",\n",
    "            \"GS_ATOMIC_NAME_10\": \"total_vuln_and_risky\",\n",
    "            \"GS_ATOMIC_NAME_11\": \"total_vuln\",\n",
    "            \"GS_BUFFER_KIND_9\": \"ATOMIC\",\n",
    "            \"GS_BACKGROUND_R\": \"1.0\",\n",
    "            \"GS_SHADER_COMMON\": \"\\n#version 460 core\\nprecision mediump float;\\n\\nuniform float uTranslateX;\\nuniform float uTranslateY;\\nuniform float uScale;\\n// JS-Deps: Node Package Manager Dependency Graph\\n//\\n// Nodes are packages. Edges are directed from a package to its dependencies.\\n\\nlayout (std430, binding=0) buffer _X { float X[]; }; // attribute(float X[N])\\nlayout (std430, binding=1) buffer _Y { float Y[]; }; // attribute(float Y[N])\\nlayout (std430, binding=2) buffer _Date { uint Date[]; }; // attribute(uint Date[N])\\nlayout (std430, binding=3) buffer _Devs { uint Devs[]; }; // attribute(uint Devs[N])\\nlayout (std430, binding=4) buffer _Vuln { uint Vuln[]; }; // attribute(uint Vuln[N])\\n\\n#define NOV_09_2010 1289278800\\n#define MAR_22_2016 1458619200\\n\\n#define JAN_01_2011 1293858000\\n#define JAN_01_2012 1325394000\\n#define JAN_01_2013 1357016400\\n#define JAN_01_2014 1388552400\\n#define JAN_01_2015 1420088400\\n#define JAN_01_2016 1451624400\\n\\n// Some controls\\n\\n\\nlayout (std430, binding=5) buffer _in_degree { uint in_degree[]; }; // scratch(uint in_degree[N])\\nlayout (std430, binding=6) buffer _out_degree { uint out_degree[]; }; // scratch(uint out_degree[N])\\nlayout (binding=0, offset=0) uniform atomic_uint in_degree_max; // scratch(atomic_uint in_degree_max)\\nlayout (binding=0, offset=4) uniform atomic_uint out_degree_max; // scratch(atomic_uint out_degree_max)\\n#define USE_RELATIONAL 1\\nlayout (std430, binding=7) buffer _Seen { uint Seen[]; }; // scratch(uint Seen[E])\\nlayout (binding=0, offset=8) uniform atomic_uint total; // scratch(atomic_uint total)\\n#define FILTER_BY_DATE 1\\n#define LO JAN_01_2014\\n#define HI JAN_01_2015\\nlayout (binding=0, offset=12) uniform atomic_uint source_date_too_lo; // scratch(atomic_uint source_date_too_lo)\\nlayout (binding=0, offset=16) uniform atomic_uint source_date_too_hi; // scratch(atomic_uint source_date_too_hi)\\nlayout (binding=0, offset=20) uniform atomic_uint target_date_too_lo; // scratch(atomic_uint target_date_too_lo)\\nlayout (binding=0, offset=24) uniform atomic_uint target_date_too_hi; // scratch(atomic_uint target_date_too_hi)\\nlayout (binding=0, offset=28) uniform atomic_uint discarded; // scratch(atomic_uint discarded)\\nlayout (binding=0, offset=32) uniform atomic_uint kept; // scratch(atomic_uint kept)\\nlayout (binding=0, offset=36) uniform atomic_uint total_risky; // scratch(atomic_uint total_risky)\\nlayout (binding=0, offset=40) uniform atomic_uint total_vuln_and_risky; // scratch(atomic_uint total_vuln_and_risky)\\nlayout (binding=0, offset=44) uniform atomic_uint total_vuln; // scratch(atomic_uint total_vuln)\\n    \",\n",
    "            \"GS_TILE_X\": \"0\",\n",
    "            \"GS_TILE_Y\": \"0\",\n",
    "        }\n",
    "        \n",
    "        @auto.functools.cache\n",
    "        def GS():\n",
    "            root = auto.pathlib.Path.cwd()\n",
    "\n",
    "            path = root / 'src'\n",
    "            if str(path) not in auto.sys.path:\n",
    "                auto.sys.path.append(str(path))\n",
    "\n",
    "            path = root / 'stage' / 'lib' / 'libgraphshader.so'\n",
    "            assert path.exists(), path\n",
    "            gs = auto.graphshader.GS.load(str(path))\n",
    "            \n",
    "            return gs\n",
    "    \n",
    "        gs = GS()\n",
    "        \n",
    "        enter = auto.contextlib.ExitStack().enter_context\n",
    "\n",
    "        print('gs.environment()')\n",
    "        enter( gs.environment() )\n",
    "        \n",
    "        for k, v in env.items():\n",
    "            gs[k] = v\n",
    "        \n",
    "        gs['GS_OUTPUT'] = '<MEMORY>'\n",
    "        \n",
    "        print('gs.egl()')\n",
    "        enter( gs.egl() )\n",
    "        \n",
    "        print('gs.gl()')\n",
    "        enter( gs.gl() )\n",
    "        \n",
    "        print('gs.data()')\n",
    "        enter( gs.data() )\n",
    "        \n",
    "        print('gs.shader()')\n",
    "        enter( gs.shader() )\n",
    "        \n",
    "        print('gs.render()')\n",
    "        image = enter( gs.render() )\n",
    "        \n",
    "        root = auto.pathlib.Path.cwd()\n",
    "        path = root / 'out.jpg'\n",
    "        \n",
    "        with path.open('wb') as f:\n",
    "            f.write(image)\n",
    "        print(f'Wrote {path.stat().st_size:,d} bytes to {path}')\n",
    "        \n",
    "        # auto.IPython.display.display(auto.IPython.display.Image(image))\n",
    "\n",
    "    source = auto.inspect.getsource(scope)\n",
    "    source = auto.textwrap.dedent(source)\n",
    "    _, *source = source.splitlines()\n",
    "    source = '\\n'.join(source)\n",
    "    source = auto.textwrap.dedent(source)\n",
    "\n",
    "    with auto.mediocreatbest.Textarea():\n",
    "        print(source)\n",
    "    \n",
    "    auto.subprocess.check_call([\n",
    "        auto.sys.executable,\n",
    "        '-c', source,\n",
    "    ], cwd=auto.pathlib.Path.cwd())\n",
    "\n",
    "/scope\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ad8bb1d4",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "EGL_VERSION: 1.5\n",
      "EGL_VENDOR: NVIDIA\n",
      "EGL_CLIENT_APIS: OpenGL_ES OpenGL\n",
      "EGL_EXTENSIONS: EGL_EXT_buffer_age EGL_EXT_client_sync EGL_EXT_create_context_robustness EGL_EXT_image_dma_buf_import EGL_EXT_image_dma_buf_import_modifiers EGL_MESA_image_dma_buf_export EGL_EXT_output_base EGL_EXT_protected_content EGL_EXT_stream_acquire_mode EGL_EXT_sync_reuse EGL_IMG_context_priority EGL_KHR_config_attribs EGL_KHR_create_context_no_error EGL_KHR_context_flush_control EGL_KHR_create_context EGL_KHR_fence_sync EGL_KHR_get_all_proc_addresses EGL_KHR_partial_update EGL_KHR_swap_buffers_with_damage EGL_KHR_no_config_context EGL_KHR_gl_colorspace EGL_KHR_gl_renderbuffer_image EGL_KHR_gl_texture_2D_image EGL_KHR_gl_texture_3D_image EGL_KHR_gl_texture_cubemap_image EGL_KHR_image EGL_KHR_image_base EGL_KHR_reusable_sync EGL_KHR_stream EGL_KHR_stream_attrib EGL_KHR_stream_consumer_gltexture EGL_KHR_stream_cross_process_fd EGL_KHR_stream_fifo EGL_KHR_stream_producer_eglsurface EGL_KHR_surfaceless_context EGL_KHR_wait_sync EGL_NV_nvrm_fence_sync EGL_NV_quadruple_buffer EGL_NV_stream_consumer_eglimage EGL_NV_stream_cross_display EGL_NV_stream_cross_object EGL_NV_stream_cross_process EGL_NV_stream_cross_system EGL_NV_stream_dma EGL_NV_stream_flush EGL_NV_stream_metadata EGL_NV_stream_remote EGL_NV_stream_reset EGL_NV_stream_socket EGL_NV_stream_socket_inet EGL_NV_stream_socket_unix EGL_NV_stream_sync EGL_NV_stream_fifo_next EGL_NV_stream_fifo_synchronous EGL_NV_stream_consumer_gltexture_yuv EGL_NV_stream_attrib EGL_NV_stream_origin EGL_NV_system_time EGL_NV_output_drm_flip_event EGL_NV_triple_buffer EGL_NV_robustness_video_memory_purge\n",
      "GL_VENDOR: NVIDIA Corporation\n",
      "GL_VERSION: 4.6.0 NVIDIA 535.183.06\n",
      "GL_RENDERER: Quadro M6000 24GB/PCIe/SSE2\n",
      "GL_SHADING_LANGUAGE_VERSION: 4.60 NVIDIA\n",
      "buffer 0\n",
      "  name: _ELEMENT\n",
      "  kind: ELEMENT\n",
      "  file: examples/JS-Deps/data/JS-Deps.edge.elements.2u32.bin\n",
      "  size: 2E\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "Read from examples/JS-Deps/data/JS-Deps.edge.elements.2u32.bin\n",
      "buffer 1\n",
      "  name: _X\n",
      "  kind: ATTRIBUTE\n",
      "  file: examples/JS-Deps/data/JS-Deps.node.x.f32.bin\n",
      "  size: N\n",
      "  type: GL_FLOAT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "Read from examples/JS-Deps/data/JS-Deps.node.x.f32.bin\n",
      "buffer 2\n",
      "  name: _Y\n",
      "  kind: ATTRIBUTE\n",
      "  file: examples/JS-Deps/data/JS-Deps.node.y.f32.bin\n",
      "  size: N\n",
      "  type: GL_FLOAT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "Read from examples/JS-Deps/data/JS-Deps.node.y.f32.bin\n",
      "buffer 3\n",
      "  name: _Date\n",
      "  kind: ATTRIBUTE\n",
      "  file: examples/JS-Deps/data/JS-Deps.node.date.u32.bin\n",
      "  size: N\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "Read from examples/JS-Deps/data/JS-Deps.node.date.u32.bin\n",
      "buffer 4\n",
      "  name: _Devs\n",
      "  kind: ATTRIBUTE\n",
      "  file: examples/JS-Deps/data/JS-Deps.node.nmaintainers.u32.bin\n",
      "  size: N\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "Read from examples/JS-Deps/data/JS-Deps.node.nmaintainers.u32.bin\n",
      "buffer 5\n",
      "  name: _Vuln\n",
      "  kind: ATTRIBUTE\n",
      "  file: examples/JS-Deps/data/JS-Deps.node.cve.u32.bin\n",
      "  size: N\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "Read from examples/JS-Deps/data/JS-Deps.node.cve.u32.bin\n",
      "buffer 6\n",
      "  name: _in_degree\n",
      "  kind: SCRATCH\n",
      "  file: <NONE>\n",
      "  size: N\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "buffer 7\n",
      "  name: _out_degree\n",
      "  kind: SCRATCH\n",
      "  file: <NONE>\n",
      "  size: N\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "buffer 8\n",
      "  name: _Seen\n",
      "  kind: SCRATCH\n",
      "  file: <NONE>\n",
      "  size: E\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "buffer 9\n",
      "  name: _ATOMIC\n",
      "  kind: ATOMIC\n",
      "  file: <NONE>\n",
      "  size: 48\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 0, 2)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 1, 3)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 2, 4)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 3, 5)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 4, 6)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 5, 7)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 6, 8)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 7, 9)\n",
      "glDrawElements(0x1, 12272268, 0x1405, (nil))\n",
      "--- Atomics\n",
      "atomic 0 \"in_degree_max\" = 79037\n",
      "atomic 1 \"out_degree_max\" = 389\n",
      "atomic 2 \"total\" = 6074422\n",
      "atomic 3 \"source_date_too_lo\" = 727708\n",
      "atomic 4 \"source_date_too_hi\" = 3929819\n",
      "atomic 5 \"target_date_too_lo\" = 988494\n",
      "atomic 6 \"target_date_too_hi\" = 3784427\n",
      "atomic 7 \"discarded\" = 5416693\n",
      "atomic 8 \"kept\" = 657729\n",
      "atomic 9 \"total_risky\" = 316755\n",
      "atomic 10 \"total_vuln_and_risky\" = 48340\n",
      "atomic 11 \"total_vuln\" = 72566\n",
      "JPEG: 256x256\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#@title bd487008\n",
    "@auto.mediocreatbest.with_exit_stack\n",
    "def scope(env, /, *,   enter):\n",
    "    gs = GS()\n",
    "\n",
    "    enter( gs.environment() )\n",
    "    \n",
    "    for k, v in env.items():\n",
    "        gs[k] = v\n",
    "    \n",
    "    gs['GS_OUTPUT'] = '<MEMORY>'\n",
    "    \n",
    "    enter( gs.egl() )\n",
    "    enter( gs.gl() )\n",
    "    enter( gs.data() )\n",
    "    enter( gs.shader() )\n",
    "    image = enter( gs.render() )\n",
    "    \n",
    "    auto.IPython.display.display(auto.IPython.display.Image(image))\n",
    "\n",
    "scope({\n",
    "    \"GS_TILE_HEIGHT\": \"256\",\n",
    "    \"GS_TILE_Z\": \"0\",\n",
    "    \"GS_BUFFER_SIZE_0\": \"2E\",\n",
    "    \"GS_BUFFER_SIZE_1\": \"N\",\n",
    "    \"GS_BUFFER_SIZE_2\": \"N\",\n",
    "    \"GS_BUFFER_SIZE_3\": \"N\",\n",
    "    \"GS_SHADER_GEOMETRY\": \"\\nlayout (lines) in;\\nlayout (line_strip, max_vertices=2) out;\\n\\nlayout(location=0) in uint _fg_NodeIndex[];\\n\\nlayout(location=0) out flat uint gs_SourceIndex;\\nlayout(location=1) out flat uint gs_TargetIndex;\\n\\nvoid main() {\\n    gs_SourceIndex = _fg_NodeIndex[0];\\n    gs_TargetIndex = _fg_NodeIndex[1];\\n\\n    int gs_EdgeIndex = gl_PrimitiveIDIn;\\n    vec4 gs_SourcePosition = gl_in[0].gl_Position;\\n    vec4 gs_TargetPosition = gl_in[1].gl_Position;\\n\\n\\n    #if USE_RELATIONAL\\n    uint od = 1 + atomicAdd(out_degree[gs_SourceIndex], 1);\\n    atomicCounterMax(out_degree_max, od);\\n\\n    uint id = 1 + atomicAdd(in_degree[gs_TargetIndex], 1);\\n    atomicCounterMax(in_degree_max, id);\\n    #endif /* USE_RELATIONAL */\\n\\n\\n\\n    // Apply tile transformations\\n    gs_SourcePosition.xy *= uScale;\\n    gs_SourcePosition.xy += vec2(uTranslateX, uTranslateY);\\n\\n    // Transform xy in [0, 1] to xy in [-1, 1]\\n    gs_SourcePosition.xy *= 2.;\\n    gs_SourcePosition.xy -= 1.;\\n\\n    // Apply tile transformations\\n    gs_TargetPosition.xy *= uScale;\\n    gs_TargetPosition.xy += vec2(uTranslateX, uTranslateY);\\n\\n    // Transform xy in [0, 1] to xy in [-1, 1]\\n    gs_TargetPosition.xy *= 2.;\\n    gs_TargetPosition.xy -= 1.;\\n\\n    gl_PrimitiveID = gs_EdgeIndex;\\n    gl_Position = gs_SourcePosition;\\n    EmitVertex();\\n\\n    gl_Position = gs_TargetPosition;\\n    EmitVertex();\\n\\n    EndPrimitive();\\n}\\n    \",\n",
    "    \"GS_BUFFER_SIZE_4\": \"N\",\n",
    "    \"GS_BUFFER_SIZE_5\": \"N\",\n",
    "    \"GS_BUFFER_SIZE_6\": \"N\",\n",
    "    \"GS_BUFFER_TYPE_0\": \"GL_UNSIGNED_INT\",\n",
    "    \"GS_BUFFER_SIZE_7\": \"N\",\n",
    "    \"GS_BUFFER_TYPE_1\": \"GL_FLOAT\",\n",
    "    \"GS_BUFFER_SIZE_8\": \"E\",\n",
    "    \"GS_OUTPUT\": \"out.jpg\",\n",
    "    \"GS_BUFFER_BIND_0\": \"<NONE>\",\n",
    "    \"GS_BUFFER_TYPE_2\": \"GL_FLOAT\",\n",
    "    \"GS_BUFFER_SIZE_9\": \"48\",\n",
    "    \"GS_BUFFER_BIND_1\": \"0\",\n",
    "    \"GS_BUFFER_TYPE_3\": \"GL_UNSIGNED_INT\",\n",
    "    \"GS_BUFFER_BIND_2\": \"1\",\n",
    "    \"GS_BUFFER_TYPE_4\": \"GL_UNSIGNED_INT\",\n",
    "    \"GS_BUFFER_FILE_0\": \"examples/JS-Deps/data/JS-Deps.edge.elements.2u32.bin\",\n",
    "    \"GS_BUFFER_BIND_3\": \"2\",\n",
    "    \"GS_BUFFER_TYPE_5\": \"GL_UNSIGNED_INT\",\n",
    "    \"GS_BUFFER_COUNT\": \"10\",\n",
    "    \"GS_BUFFER_NAME_0\": \"_ELEMENT\",\n",
    "    \"GS_BUFFER_FILE_1\": \"examples/JS-Deps/data/JS-Deps.node.x.f32.bin\",\n",
    "    \"GS_BUFFER_BIND_4\": \"3\",\n",
    "    \"GS_BUFFER_TYPE_6\": \"GL_UNSIGNED_INT\",\n",
    "    \"GS_BUFFER_NAME_1\": \"_X\",\n",
    "    \"GS_BUFFER_FILE_2\": \"examples/JS-Deps/data/JS-Deps.node.y.f32.bin\",\n",
    "    \"GS_BUFFER_BIND_5\": \"4\",\n",
    "    \"GS_BUFFER_TYPE_7\": \"GL_UNSIGNED_INT\",\n",
    "    \"GS_BUFFER_NAME_2\": \"_Y\",\n",
    "    \"GS_BUFFER_FILE_3\": \"examples/JS-Deps/data/JS-Deps.node.date.u32.bin\",\n",
    "    \"GS_BUFFER_BIND_6\": \"5\",\n",
    "    \"GS_BUFFER_TYPE_8\": \"GL_UNSIGNED_INT\",\n",
    "    \"GS_ATOMIC_COUNT\": \"12\",\n",
    "    \"GS_BUFFER_NAME_3\": \"_Date\",\n",
    "    \"GS_BUFFER_FILE_4\": \"examples/JS-Deps/data/JS-Deps.node.nmaintainers.u32.bin\",\n",
    "    \"GS_BUFFER_BIND_7\": \"6\",\n",
    "    \"GS_ATOMIC_NAME_0\": \"in_degree_max\",\n",
    "    \"GS_BUFFER_TYPE_9\": \"GL_UNSIGNED_INT\",\n",
    "    \"GS_BUFFER_NAME_4\": \"_Devs\",\n",
    "    \"GS_BUFFER_FILE_5\": \"examples/JS-Deps/data/JS-Deps.node.cve.u32.bin\",\n",
    "    \"GS_ATOMIC_NAME_1\": \"out_degree_max\",\n",
    "    \"GS_BUFFER_BIND_8\": \"7\",\n",
    "    \"GS_SHADER_VERTEX\": \"\\n\\nlayout(location=0) out uint _fg_NodeIndex;\\n\\nvoid main() {\\n    const int gs_NodeIndex = gl_VertexID;\\n    vec3 gs_NodePosition = vec3(0., 0., 0.);\\n\\n    float x = X[gs_NodeIndex];\\n    float y = Y[gs_NodeIndex];\\n\\n    gs_NodePosition = vec3(x, y, 0);\\n\\n\\n\\n    gl_Position = vec4(gs_NodePosition.xyz, 1.);\\n\\n    _fg_NodeIndex = gs_NodeIndex;\\n}\\n    \",\n",
    "    \"GS_BACKGROUND_A\": \"1.0\",\n",
    "    \"GS_BUFFER_KIND_0\": \"ELEMENT\",\n",
    "    \"GS_BUFFER_NAME_5\": \"_Vuln\",\n",
    "    \"GS_BUFFER_FILE_6\": \"<NONE>\",\n",
    "    \"GS_ATOMIC_NAME_2\": \"total\",\n",
    "    \"GS_BUFFER_BIND_9\": \"0\",\n",
    "    \"GS_SHADER_FRAGMENT\": \"\\nlayout(location=0) in flat uint gs_SourceIndex;\\nlayout(location=1) in flat uint gs_TargetIndex;\\n\\nlayout(location=0) out vec4 gs_FragColor;\\n\\nvoid main() {\\n    int gs_EdgeIndex = gl_PrimitiveID;\\n    bool first = 0 == atomicAdd(Seen[gs_EdgeIndex], 1);\\n    bool d = false;\\n\\n    if (first) atomicCounterAdd(total, 1);\\n\\n    #if FILTER_BY_DATE\\n\\n    if (Date[gs_SourceIndex] < LO) {\\n        d = true;\\n        if (first) atomicCounterAdd(source_date_too_lo, 1);\\n    }\\n\\n    if (Date[gs_SourceIndex] > HI) {\\n        d = true;\\n        if (first) atomicCounterAdd(source_date_too_hi, 1);\\n    }\\n\\n    if (Date[gs_TargetIndex] < LO) {\\n        d = true;\\n        if (first) atomicCounterAdd(target_date_too_lo, 1);\\n    }\\n\\n    if (Date[gs_TargetIndex] > HI) {\\n        d = true;\\n        if (first) atomicCounterAdd(target_date_too_hi, 1);\\n    }\\n    #endif /* FILTER_BY_DATE */\\n\\n    if (d) {\\n        if (first) atomicCounterAdd(discarded, 1);\\n        discard;\\n    } else {\\n        if (first) atomicCounterAdd(kept, 1);\\n    }\\n\\n    bool vuln = bool(Vuln[gs_SourceIndex]) || bool(Vuln[gs_TargetIndex]);\\n    bool risky = Devs[gs_SourceIndex] > Devs[gs_TargetIndex];\\n\\n    #if USE_RELATIONAL\\n    const uint depends_on_source = in_degree[gs_SourceIndex];\\n    const uint depends_on_target = in_degree[gs_TargetIndex];\\n\\n    risky = depends_on_source + depends_on_target > 100 * Devs[gs_TargetIndex];\\n    #endif /* USE_RELATIONAL */\\n\\n    if (risky) {\\n        if (first) atomicCounterAdd(total_risky, 1);\\n    }\\n\\n    if (risky && vuln) {\\n        if (first) atomicCounterAdd(total_vuln_and_risky, 1);\\n    }\\n\\n    if (vuln) {\\n        if (first) atomicCounterAdd(total_vuln, 1);\\n    }\\n\\n    gs_FragColor = vec4(0.1);\\n    gs_FragColor.r = float(vuln);\\n    gs_FragColor.b = float(risky);\\n}\\n    \",\n",
    "    \"GS_BACKGROUND_B\": \"1.0\",\n",
    "    \"GS_BUFFER_KIND_1\": \"ATTRIBUTE\",\n",
    "    \"GS_BUFFER_NAME_6\": \"_in_degree\",\n",
    "    \"GS_BUFFER_FILE_7\": \"<NONE>\",\n",
    "    \"GS_ATOMIC_NAME_3\": \"source_date_too_lo\",\n",
    "    \"GS_TILE_WIDTH\": \"256\",\n",
    "    \"GS_BUFFER_KIND_2\": \"ATTRIBUTE\",\n",
    "    \"GS_BUFFER_NAME_7\": \"_out_degree\",\n",
    "    \"GS_BUFFER_FILE_8\": \"<NONE>\",\n",
    "    \"GS_ATOMIC_NAME_4\": \"source_date_too_hi\",\n",
    "    \"GS_BUFFER_KIND_3\": \"ATTRIBUTE\",\n",
    "    \"GS_BUFFER_NAME_8\": \"_Seen\",\n",
    "    \"GS_ATOMIC_NAME_5\": \"target_date_too_lo\",\n",
    "    \"GS_BUFFER_FILE_9\": \"<NONE>\",\n",
    "    \"GS_BUFFER_KIND_4\": \"ATTRIBUTE\",\n",
    "    \"GS_ATOMIC_NAME_6\": \"target_date_too_hi\",\n",
    "    \"GS_BUFFER_NAME_9\": \"_ATOMIC\",\n",
    "    \"GS_BUFFER_KIND_5\": \"ATTRIBUTE\",\n",
    "    \"GS_ATOMIC_NAME_7\": \"discarded\",\n",
    "    \"GS_BACKGROUND_G\": \"1.0\",\n",
    "    \"GS_BUFFER_KIND_6\": \"SCRATCH\",\n",
    "    \"GS_ATOMIC_NAME_8\": \"kept\",\n",
    "    \"GS_BUFFER_KIND_7\": \"SCRATCH\",\n",
    "    \"GS_ATOMIC_NAME_9\": \"total_risky\",\n",
    "    \"GS_BUFFER_KIND_8\": \"SCRATCH\",\n",
    "    \"GS_ATOMIC_NAME_10\": \"total_vuln_and_risky\",\n",
    "    \"GS_ATOMIC_NAME_11\": \"total_vuln\",\n",
    "    \"GS_BUFFER_KIND_9\": \"ATOMIC\",\n",
    "    \"GS_BACKGROUND_R\": \"1.0\",\n",
    "    \"GS_SHADER_COMMON\": \"\\n#version 460 core\\nprecision mediump float;\\n\\nuniform float uTranslateX;\\nuniform float uTranslateY;\\nuniform float uScale;\\n// JS-Deps: Node Package Manager Dependency Graph\\n//\\n// Nodes are packages. Edges are directed from a package to its dependencies.\\n\\nlayout (std430, binding=0) buffer _X { float X[]; }; // attribute(float X[N])\\nlayout (std430, binding=1) buffer _Y { float Y[]; }; // attribute(float Y[N])\\nlayout (std430, binding=2) buffer _Date { uint Date[]; }; // attribute(uint Date[N])\\nlayout (std430, binding=3) buffer _Devs { uint Devs[]; }; // attribute(uint Devs[N])\\nlayout (std430, binding=4) buffer _Vuln { uint Vuln[]; }; // attribute(uint Vuln[N])\\n\\n#define NOV_09_2010 1289278800\\n#define MAR_22_2016 1458619200\\n\\n#define JAN_01_2011 1293858000\\n#define JAN_01_2012 1325394000\\n#define JAN_01_2013 1357016400\\n#define JAN_01_2014 1388552400\\n#define JAN_01_2015 1420088400\\n#define JAN_01_2016 1451624400\\n\\n// Some controls\\n\\n\\nlayout (std430, binding=5) buffer _in_degree { uint in_degree[]; }; // scratch(uint in_degree[N])\\nlayout (std430, binding=6) buffer _out_degree { uint out_degree[]; }; // scratch(uint out_degree[N])\\nlayout (binding=0, offset=0) uniform atomic_uint in_degree_max; // scratch(atomic_uint in_degree_max)\\nlayout (binding=0, offset=4) uniform atomic_uint out_degree_max; // scratch(atomic_uint out_degree_max)\\n#define USE_RELATIONAL 1\\nlayout (std430, binding=7) buffer _Seen { uint Seen[]; }; // scratch(uint Seen[E])\\nlayout (binding=0, offset=8) uniform atomic_uint total; // scratch(atomic_uint total)\\n#define FILTER_BY_DATE 1\\n#define LO JAN_01_2014\\n#define HI JAN_01_2015\\nlayout (binding=0, offset=12) uniform atomic_uint source_date_too_lo; // scratch(atomic_uint source_date_too_lo)\\nlayout (binding=0, offset=16) uniform atomic_uint source_date_too_hi; // scratch(atomic_uint source_date_too_hi)\\nlayout (binding=0, offset=20) uniform atomic_uint target_date_too_lo; // scratch(atomic_uint target_date_too_lo)\\nlayout (binding=0, offset=24) uniform atomic_uint target_date_too_hi; // scratch(atomic_uint target_date_too_hi)\\nlayout (binding=0, offset=28) uniform atomic_uint discarded; // scratch(atomic_uint discarded)\\nlayout (binding=0, offset=32) uniform atomic_uint kept; // scratch(atomic_uint kept)\\nlayout (binding=0, offset=36) uniform atomic_uint total_risky; // scratch(atomic_uint total_risky)\\nlayout (binding=0, offset=40) uniform atomic_uint total_vuln_and_risky; // scratch(atomic_uint total_vuln_and_risky)\\nlayout (binding=0, offset=44) uniform atomic_uint total_vuln; // scratch(atomic_uint total_vuln)\\n    \",\n",
    "    \"GS_TILE_X\": \"0\",\n",
    "    \"GS_TILE_Y\": \"0\"\n",
    "})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7db884b5",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "os.execlpe('/tmp/tmpoxjw6b69/printenv0', '/tmp/tmpoxjw6b69/printenv0 <inpfile>', env)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<textarea rows=12 style=\"width: 90%; margin-left: 5%\">{\n",
       "    &quot;GS_TILE_HEIGHT&quot;: &quot;256&quot;,\n",
       "    &quot;GS_TILE_Z&quot;: &quot;0&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_0&quot;: &quot;2E&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_1&quot;: &quot;N&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_2&quot;: &quot;N&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_3&quot;: &quot;N&quot;,\n",
       "    &quot;GS_SHADER_GEOMETRY&quot;: &quot;\\nlayout (lines) in;\\nlayout (line_strip, max_vertices=2) out;\\n\\nlayout(location=0) in uint _fg_NodeIndex[];\\n\\nlayout(location=0) out flat uint gs_SourceIndex;\\nlayout(location=1) out flat uint gs_TargetIndex;\\n\\nvoid main() {\\n    gs_SourceIndex = _fg_NodeIndex[0];\\n    gs_TargetIndex = _fg_NodeIndex[1];\\n\\n    int gs_EdgeIndex = gl_PrimitiveIDIn;\\n    vec4 gs_SourcePosition = gl_in[0].gl_Position;\\n    vec4 gs_TargetPosition = gl_in[1].gl_Position;\\n\\n\\n    #if USE_RELATIONAL\\n    uint od = 1 + atomicAdd(out_degree[gs_SourceIndex], 1);\\n    atomicCounterMax(out_degree_max, od);\\n\\n    uint id = 1 + atomicAdd(in_degree[gs_TargetIndex], 1);\\n    atomicCounterMax(in_degree_max, id);\\n    #endif /* USE_RELATIONAL */\\n\\n\\n\\n    // Apply tile transformations\\n    gs_SourcePosition.xy *= uScale;\\n    gs_SourcePosition.xy += vec2(uTranslateX, uTranslateY);\\n\\n    // Transform xy in [0, 1] to xy in [-1, 1]\\n    gs_SourcePosition.xy *= 2.;\\n    gs_SourcePosition.xy -= 1.;\\n\\n    // Apply tile transformations\\n    gs_TargetPosition.xy *= uScale;\\n    gs_TargetPosition.xy += vec2(uTranslateX, uTranslateY);\\n\\n    // Transform xy in [0, 1] to xy in [-1, 1]\\n    gs_TargetPosition.xy *= 2.;\\n    gs_TargetPosition.xy -= 1.;\\n\\n    gl_PrimitiveID = gs_EdgeIndex;\\n    gl_Position = gs_SourcePosition;\\n    EmitVertex();\\n\\n    gl_Position = gs_TargetPosition;\\n    EmitVertex();\\n\\n    EndPrimitive();\\n}\\n    &quot;,\n",
       "    &quot;GS_BUFFER_SIZE_4&quot;: &quot;N&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_5&quot;: &quot;N&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_6&quot;: &quot;N&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_0&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_7&quot;: &quot;N&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_1&quot;: &quot;GL_FLOAT&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_8&quot;: &quot;E&quot;,\n",
       "    &quot;GS_OUTPUT&quot;: &quot;out.jpg&quot;,\n",
       "    &quot;GS_BUFFER_BIND_0&quot;: &quot;&lt;NONE&gt;&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_2&quot;: &quot;GL_FLOAT&quot;,\n",
       "    &quot;GS_BUFFER_SIZE_9&quot;: &quot;48&quot;,\n",
       "    &quot;GS_BUFFER_BIND_1&quot;: &quot;0&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_3&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_BUFFER_BIND_2&quot;: &quot;1&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_4&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_BUFFER_FILE_0&quot;: &quot;&lt;NONE&gt;&quot;,\n",
       "    &quot;GS_BUFFER_BIND_3&quot;: &quot;2&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_5&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_BUFFER_COUNT&quot;: &quot;10&quot;,\n",
       "    &quot;GS_BUFFER_NAME_0&quot;: &quot;_ELEMENT&quot;,\n",
       "    &quot;GS_BUFFER_FILE_1&quot;: &quot;&lt;NONE&gt;&quot;,\n",
       "    &quot;GS_BUFFER_BIND_4&quot;: &quot;3&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_6&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_BUFFER_NAME_1&quot;: &quot;_X&quot;,\n",
       "    &quot;GS_BUFFER_FILE_2&quot;: &quot;&lt;NONE&gt;&quot;,\n",
       "    &quot;GS_BUFFER_BIND_5&quot;: &quot;4&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_7&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_BUFFER_NAME_2&quot;: &quot;_Y&quot;,\n",
       "    &quot;GS_BUFFER_FILE_3&quot;: &quot;&lt;NONE&gt;&quot;,\n",
       "    &quot;GS_BUFFER_BIND_6&quot;: &quot;5&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_8&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_ATOMIC_COUNT&quot;: &quot;12&quot;,\n",
       "    &quot;GS_BUFFER_NAME_3&quot;: &quot;_Date&quot;,\n",
       "    &quot;GS_BUFFER_FILE_4&quot;: &quot;&lt;NONE&gt;&quot;,\n",
       "    &quot;GS_BUFFER_BIND_7&quot;: &quot;6&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_0&quot;: &quot;in_degree_max&quot;,\n",
       "    &quot;GS_BUFFER_TYPE_9&quot;: &quot;GL_UNSIGNED_INT&quot;,\n",
       "    &quot;GS_BUFFER_NAME_4&quot;: &quot;_Devs&quot;,\n",
       "    &quot;GS_BUFFER_FILE_5&quot;: &quot;&lt;NONE&gt;&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_1&quot;: &quot;out_degree_max&quot;,\n",
       "    &quot;GS_BUFFER_BIND_8&quot;: &quot;7&quot;,\n",
       "    &quot;GS_SHADER_VERTEX&quot;: &quot;\\n\\nlayout(location=0) out uint _fg_NodeIndex;\\n\\nvoid main() {\\n    const int gs_NodeIndex = gl_VertexID;\\n    vec3 gs_NodePosition = vec3(0., 0., 0.);\\n\\n    float x = X[gs_NodeIndex];\\n    float y = Y[gs_NodeIndex];\\n\\n    gs_NodePosition = vec3(x, y, 0);\\n\\n\\n\\n    gl_Position = vec4(gs_NodePosition.xyz, 1.);\\n\\n    _fg_NodeIndex = gs_NodeIndex;\\n}\\n    &quot;,\n",
       "    &quot;GS_BACKGROUND_A&quot;: &quot;1.0&quot;,\n",
       "    &quot;GS_BUFFER_KIND_0&quot;: &quot;ELEMENT&quot;,\n",
       "    &quot;GS_BUFFER_NAME_5&quot;: &quot;_Vuln&quot;,\n",
       "    &quot;GS_BUFFER_FILE_6&quot;: &quot;&lt;NONE&gt;&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_2&quot;: &quot;total&quot;,\n",
       "    &quot;GS_BUFFER_BIND_9&quot;: &quot;0&quot;,\n",
       "    &quot;GS_SHADER_FRAGMENT&quot;: &quot;\\nlayout(location=0) in flat uint gs_SourceIndex;\\nlayout(location=1) in flat uint gs_TargetIndex;\\n\\nlayout(location=0) out vec4 gs_FragColor;\\n\\nvoid main() {\\n    int gs_EdgeIndex = gl_PrimitiveID;\\n    bool first = 0 == atomicAdd(Seen[gs_EdgeIndex], 1);\\n    bool d = false;\\n\\n    if (first) atomicCounterAdd(total, 1);\\n\\n    #if FILTER_BY_DATE\\n\\n    if (Date[gs_SourceIndex] &lt; LO) {\\n        d = true;\\n        if (first) atomicCounterAdd(source_date_too_lo, 1);\\n    }\\n\\n    if (Date[gs_SourceIndex] &gt; HI) {\\n        d = true;\\n        if (first) atomicCounterAdd(source_date_too_hi, 1);\\n    }\\n\\n    if (Date[gs_TargetIndex] &lt; LO) {\\n        d = true;\\n        if (first) atomicCounterAdd(target_date_too_lo, 1);\\n    }\\n\\n    if (Date[gs_TargetIndex] &gt; HI) {\\n        d = true;\\n        if (first) atomicCounterAdd(target_date_too_hi, 1);\\n    }\\n    #endif /* FILTER_BY_DATE */\\n\\n    if (d) {\\n        if (first) atomicCounterAdd(discarded, 1);\\n        discard;\\n    } else {\\n        if (first) atomicCounterAdd(kept, 1);\\n    }\\n\\n    bool vuln = bool(Vuln[gs_SourceIndex]) || bool(Vuln[gs_TargetIndex]);\\n    bool risky = Devs[gs_SourceIndex] &gt; Devs[gs_TargetIndex];\\n\\n    #if USE_RELATIONAL\\n    const uint depends_on_source = in_degree[gs_SourceIndex];\\n    const uint depends_on_target = in_degree[gs_TargetIndex];\\n\\n    risky = depends_on_source + depends_on_target &gt; 100 * Devs[gs_TargetIndex];\\n    #endif /* USE_RELATIONAL */\\n\\n    if (risky) {\\n        if (first) atomicCounterAdd(total_risky, 1);\\n    }\\n\\n    if (risky &amp;&amp; vuln) {\\n        if (first) atomicCounterAdd(total_vuln_and_risky, 1);\\n    }\\n\\n    if (vuln) {\\n        if (first) atomicCounterAdd(total_vuln, 1);\\n    }\\n\\n    gs_FragColor = vec4(0.1);\\n    gs_FragColor.r = float(vuln);\\n    gs_FragColor.b = float(risky);\\n}\\n    &quot;,\n",
       "    &quot;GS_BACKGROUND_B&quot;: &quot;1.0&quot;,\n",
       "    &quot;GS_BUFFER_KIND_1&quot;: &quot;ATTRIBUTE&quot;,\n",
       "    &quot;GS_BUFFER_NAME_6&quot;: &quot;_in_degree&quot;,\n",
       "    &quot;GS_BUFFER_FILE_7&quot;: &quot;&lt;NONE&gt;&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_3&quot;: &quot;source_date_too_lo&quot;,\n",
       "    &quot;GS_TILE_WIDTH&quot;: &quot;256&quot;,\n",
       "    &quot;GS_BUFFER_KIND_2&quot;: &quot;ATTRIBUTE&quot;,\n",
       "    &quot;GS_BUFFER_NAME_7&quot;: &quot;_out_degree&quot;,\n",
       "    &quot;GS_BUFFER_FILE_8&quot;: &quot;&lt;NONE&gt;&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_4&quot;: &quot;source_date_too_hi&quot;,\n",
       "    &quot;GS_BUFFER_KIND_3&quot;: &quot;ATTRIBUTE&quot;,\n",
       "    &quot;GS_BUFFER_NAME_8&quot;: &quot;_Seen&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_5&quot;: &quot;target_date_too_lo&quot;,\n",
       "    &quot;GS_BUFFER_FILE_9&quot;: &quot;&lt;NONE&gt;&quot;,\n",
       "    &quot;GS_BUFFER_KIND_4&quot;: &quot;ATTRIBUTE&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_6&quot;: &quot;target_date_too_hi&quot;,\n",
       "    &quot;GS_BUFFER_NAME_9&quot;: &quot;_ATOMIC&quot;,\n",
       "    &quot;GS_BUFFER_KIND_5&quot;: &quot;ATTRIBUTE&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_7&quot;: &quot;discarded&quot;,\n",
       "    &quot;GS_BACKGROUND_G&quot;: &quot;1.0&quot;,\n",
       "    &quot;GS_BUFFER_KIND_6&quot;: &quot;SCRATCH&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_8&quot;: &quot;kept&quot;,\n",
       "    &quot;GS_BUFFER_KIND_7&quot;: &quot;SCRATCH&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_9&quot;: &quot;total_risky&quot;,\n",
       "    &quot;GS_BUFFER_KIND_8&quot;: &quot;SCRATCH&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_10&quot;: &quot;total_vuln_and_risky&quot;,\n",
       "    &quot;GS_ATOMIC_NAME_11&quot;: &quot;total_vuln&quot;,\n",
       "    &quot;GS_BUFFER_KIND_9&quot;: &quot;ATOMIC&quot;,\n",
       "    &quot;GS_BACKGROUND_R&quot;: &quot;1.0&quot;,\n",
       "    &quot;GS_SHADER_COMMON&quot;: &quot;\\n#version 460 core\\nprecision mediump float;\\n\\nuniform float uTranslateX;\\nuniform float uTranslateY;\\nuniform float uScale;\\n// JS-Deps: Node Package Manager Dependency Graph\\n//\\n// Nodes are packages. Edges are directed from a package to its dependencies.\\n\\nlayout (std430, binding=0) buffer _X { float X[]; }; // attribute(float X[N])\\nlayout (std430, binding=1) buffer _Y { float Y[]; }; // attribute(float Y[N])\\nlayout (std430, binding=2) buffer _Date { uint Date[]; }; // attribute(uint Date[N])\\nlayout (std430, binding=3) buffer _Devs { uint Devs[]; }; // attribute(uint Devs[N])\\nlayout (std430, binding=4) buffer _Vuln { uint Vuln[]; }; // attribute(uint Vuln[N])\\n\\n#define NOV_09_2010 1289278800\\n#define MAR_22_2016 1458619200\\n\\n#define JAN_01_2011 1293858000\\n#define JAN_01_2012 1325394000\\n#define JAN_01_2013 1357016400\\n#define JAN_01_2014 1388552400\\n#define JAN_01_2015 1420088400\\n#define JAN_01_2016 1451624400\\n\\n// Some controls\\n\\n\\nlayout (std430, binding=5) buffer _in_degree { uint in_degree[]; }; // scratch(uint in_degree[N])\\nlayout (std430, binding=6) buffer _out_degree { uint out_degree[]; }; // scratch(uint out_degree[N])\\nlayout (binding=0, offset=0) uniform atomic_uint in_degree_max; // scratch(atomic_uint in_degree_max)\\nlayout (binding=0, offset=4) uniform atomic_uint out_degree_max; // scratch(atomic_uint out_degree_max)\\n#define USE_RELATIONAL 1\\nlayout (std430, binding=7) buffer _Seen { uint Seen[]; }; // scratch(uint Seen[E])\\nlayout (binding=0, offset=8) uniform atomic_uint total; // scratch(atomic_uint total)\\n#define FILTER_BY_DATE 1\\n#define LO JAN_01_2014\\n#define HI JAN_01_2015\\nlayout (binding=0, offset=12) uniform atomic_uint source_date_too_lo; // scratch(atomic_uint source_date_too_lo)\\nlayout (binding=0, offset=16) uniform atomic_uint source_date_too_hi; // scratch(atomic_uint source_date_too_hi)\\nlayout (binding=0, offset=20) uniform atomic_uint target_date_too_lo; // scratch(atomic_uint target_date_too_lo)\\nlayout (binding=0, offset=24) uniform atomic_uint target_date_too_hi; // scratch(atomic_uint target_date_too_hi)\\nlayout (binding=0, offset=28) uniform atomic_uint discarded; // scratch(atomic_uint discarded)\\nlayout (binding=0, offset=32) uniform atomic_uint kept; // scratch(atomic_uint kept)\\nlayout (binding=0, offset=36) uniform atomic_uint total_risky; // scratch(atomic_uint total_risky)\\nlayout (binding=0, offset=40) uniform atomic_uint total_vuln_and_risky; // scratch(atomic_uint total_vuln_and_risky)\\nlayout (binding=0, offset=44) uniform atomic_uint total_vuln; // scratch(atomic_uint total_vuln)\\n    &quot;,\n",
       "    &quot;GS_TILE_X&quot;: &quot;0&quot;,\n",
       "    &quot;GS_TILE_Y&quot;: &quot;0&quot;\n",
       "}\n",
       "</textarea>"
      ],
      "text/plain": [
       "<mediocreatbest._textarea.Textarea at 0x7fe7f845bb20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#@title 6cc786d9\n",
    "def scope():\n",
    "    env = Transpile(\n",
    "        auto.pathlib.Path('examples/JS-Deps/JS-Deps.gsp').read_text(),\n",
    "        files=dict(\n",
    "        ),\n",
    "    )\n",
    "\n",
    "    with auto.mediocreatbest.Textarea():\n",
    "        print(auto.json.dumps({\n",
    "            k: v\n",
    "            for k, v in env.items()\n",
    "            if k.startswith('GS_')\n",
    "        }, indent=4))\n",
    "\n",
    "/scope\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d72155f3",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "EGL_VERSION: 1.5\n",
      "EGL_VENDOR: NVIDIA\n",
      "EGL_CLIENT_APIS: OpenGL_ES OpenGL\n",
      "EGL_EXTENSIONS: EGL_EXT_buffer_age EGL_EXT_client_sync EGL_EXT_create_context_robustness EGL_EXT_image_dma_buf_import EGL_EXT_image_dma_buf_import_modifiers EGL_MESA_image_dma_buf_export EGL_EXT_output_base EGL_EXT_protected_content EGL_EXT_stream_acquire_mode EGL_EXT_sync_reuse EGL_IMG_context_priority EGL_KHR_config_attribs EGL_KHR_create_context_no_error EGL_KHR_context_flush_control EGL_KHR_create_context EGL_KHR_fence_sync EGL_KHR_get_all_proc_addresses EGL_KHR_partial_update EGL_KHR_swap_buffers_with_damage EGL_KHR_no_config_context EGL_KHR_gl_colorspace EGL_KHR_gl_renderbuffer_image EGL_KHR_gl_texture_2D_image EGL_KHR_gl_texture_3D_image EGL_KHR_gl_texture_cubemap_image EGL_KHR_image EGL_KHR_image_base EGL_KHR_reusable_sync EGL_KHR_stream EGL_KHR_stream_attrib EGL_KHR_stream_consumer_gltexture EGL_KHR_stream_cross_process_fd EGL_KHR_stream_fifo EGL_KHR_stream_producer_eglsurface EGL_KHR_surfaceless_context EGL_KHR_wait_sync EGL_NV_nvrm_fence_sync EGL_NV_quadruple_buffer EGL_NV_stream_consumer_eglimage EGL_NV_stream_cross_display EGL_NV_stream_cross_object EGL_NV_stream_cross_process EGL_NV_stream_cross_system EGL_NV_stream_dma EGL_NV_stream_flush EGL_NV_stream_metadata EGL_NV_stream_remote EGL_NV_stream_reset EGL_NV_stream_socket EGL_NV_stream_socket_inet EGL_NV_stream_socket_unix EGL_NV_stream_sync EGL_NV_stream_fifo_next EGL_NV_stream_fifo_synchronous EGL_NV_stream_consumer_gltexture_yuv EGL_NV_stream_attrib EGL_NV_stream_origin EGL_NV_system_time EGL_NV_output_drm_flip_event EGL_NV_triple_buffer EGL_NV_robustness_video_memory_purge\n",
      "GL_VENDOR: NVIDIA Corporation\n",
      "GL_VERSION: 4.6.0 NVIDIA 535.183.06\n",
      "GL_RENDERER: Quadro M6000 24GB/PCIe/SSE2\n",
      "GL_SHADING_LANGUAGE_VERSION: 4.60 NVIDIA\n",
      "buffer 0\n",
      "  name: _ELEMENT\n",
      "  kind: ELEMENT\n",
      "  file: <NONE>\n",
      "  size: 2E\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = 0x7fe7b38ac010; app_data_buflen = 49089072\n",
      "buffer 1\n",
      "  name: _X\n",
      "  kind: ATTRIBUTE\n",
      "  file: <NONE>\n",
      "  size: N\n",
      "  type: GL_FLOAT\n",
      "app_data_buffer = 0x7fe7eb204010; app_data_buflen = 4577696\n",
      "buffer 2\n",
      "  name: _Y\n",
      "  kind: ATTRIBUTE\n",
      "  file: <NONE>\n",
      "  size: N\n",
      "  type: GL_FLOAT\n",
      "app_data_buffer = 0x7fe7e6a03010; app_data_buflen = 4577696\n",
      "buffer 3\n",
      "  name: _Date\n",
      "  kind: ATTRIBUTE\n",
      "  file: <NONE>\n",
      "  size: N\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = 0x7fe7e65a5010; app_data_buflen = 4577696\n",
      "buffer 4\n",
      "  name: _Devs\n",
      "  kind: ATTRIBUTE\n",
      "  file: <NONE>\n",
      "  size: N\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = 0x7fe7e6147010; app_data_buflen = 4577696\n",
      "buffer 5\n",
      "  name: _Vuln\n",
      "  kind: ATTRIBUTE\n",
      "  file: <NONE>\n",
      "  size: N\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = 0x7fe7e3a01010; app_data_buflen = 4577696\n",
      "buffer 6\n",
      "  name: _in_degree\n",
      "  kind: SCRATCH\n",
      "  file: <NONE>\n",
      "  size: N\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "buffer 7\n",
      "  name: _out_degree\n",
      "  kind: SCRATCH\n",
      "  file: <NONE>\n",
      "  size: N\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "buffer 8\n",
      "  name: _Seen\n",
      "  kind: SCRATCH\n",
      "  file: <NONE>\n",
      "  size: E\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "buffer 9\n",
      "  name: _ATOMIC\n",
      "  kind: ATOMIC\n",
      "  file: <NONE>\n",
      "  size: 48\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 0, 2)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 1, 3)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 2, 4)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 3, 5)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 4, 6)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 5, 7)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 6, 8)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 7, 9)\n",
      "glDrawElements(0x1, 12272268, 0x1405, (nil))\n",
      "--- Atomics\n",
      "atomic 0 \"in_degree_max\" = 79037\n",
      "atomic 1 \"out_degree_max\" = 389\n",
      "atomic 2 \"total\" = 6120214\n",
      "atomic 3 \"source_date_too_lo\" = 732599\n",
      "atomic 4 \"source_date_too_hi\" = 3960590\n",
      "atomic 5 \"target_date_too_lo\" = 994984\n",
      "atomic 6 \"target_date_too_hi\" = 3812211\n",
      "atomic 7 \"discarded\" = 5455878\n",
      "atomic 8 \"kept\" = 664336\n",
      "atomic 9 \"total_risky\" = 322790\n",
      "atomic 10 \"total_vuln_and_risky\" = 49009\n",
      "atomic 11 \"total_vuln\" = 73036\n",
      "JPEG: 512x512\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#@title 8da4103f\n",
    "@auto.mediocreatbest.with_exit_stack\n",
    "def scope(env, /, *,   enter):\n",
    "    gs = GS()\n",
    "\n",
    "    def Read(path: auto.os.PathLike, /, *, dtype: auto.np.DType) -> auto.np.ndarray:\n",
    "        return auto.np.fromfile(path, dtype)\n",
    "\n",
    "    element = Read(\"examples/JS-Deps/data/JS-Deps.edge.elements.2u32.bin\",\n",
    "        dtype=[ ('i', 'u4'), ('j', 'u4') ],\n",
    "    )\n",
    "    x = Read(\"examples/JS-Deps/data/JS-Deps.node.x.f32.bin\",\n",
    "        dtype=[ ('x', 'f4') ],\n",
    "    )\n",
    "    y = Read(\"examples/JS-Deps/data/JS-Deps.node.y.f32.bin\",\n",
    "        dtype=[ ('y', 'f4') ],\n",
    "    )\n",
    "    date = Read(\"examples/JS-Deps/data/JS-Deps.node.date.u32.bin\",\n",
    "        dtype=[ ('date', 'u4') ],\n",
    "    )\n",
    "    devs = Read(\"examples/JS-Deps/data/JS-Deps.node.nmaintainers.u32.bin\",\n",
    "        dtype=[ ('devs', 'u4') ],\n",
    "    )\n",
    "    vuln = Read(\"examples/JS-Deps/data/JS-Deps.node.cve.u32.bin\",\n",
    "        dtype=[ ('vuln', 'u4') ],\n",
    "    )\n",
    "\n",
    "    enter( gs.environment() )\n",
    "    \n",
    "    for k, v in env.items():\n",
    "        gs[k] = v\n",
    "    \n",
    "    enter( gs.egl() )\n",
    "    \n",
    "    gs['GS_TILE_WIDTH'] = '512'\n",
    "    gs['GS_TILE_HEIGHT'] = '512'\n",
    "    enter( gs.gl() )\n",
    "    \n",
    "    gs['_ELEMENT'] = element\n",
    "    gs['_X'] = x\n",
    "    gs['_Y'] = y\n",
    "    gs['_Date'] = date\n",
    "    gs['_Devs'] = devs\n",
    "    gs['_Vuln'] = vuln\n",
    "    enter( gs.data() )\n",
    "\n",
    "    enter( gs.shader() )\n",
    "    \n",
    "    gs['GS_OUTPUT'] = '<MEMORY>'\n",
    "    image = enter( gs.render() )\n",
    "    auto.IPython.display.display(auto.IPython.display.Image(image))\n",
    "\n",
    "scope({\n",
    "    \"GS_TILE_HEIGHT\": \"256\",\n",
    "    \"GS_TILE_Z\": \"0\",\n",
    "    \"GS_BUFFER_SIZE_0\": \"2E\",\n",
    "    \"GS_BUFFER_SIZE_1\": \"N\",\n",
    "    \"GS_BUFFER_SIZE_2\": \"N\",\n",
    "    \"GS_BUFFER_SIZE_3\": \"N\",\n",
    "    \"GS_SHADER_GEOMETRY\": \"\\nlayout (lines) in;\\nlayout (line_strip, max_vertices=2) out;\\n\\nlayout(location=0) in uint _fg_NodeIndex[];\\n\\nlayout(location=0) out flat uint gs_SourceIndex;\\nlayout(location=1) out flat uint gs_TargetIndex;\\n\\nvoid main() {\\n    gs_SourceIndex = _fg_NodeIndex[0];\\n    gs_TargetIndex = _fg_NodeIndex[1];\\n\\n    int gs_EdgeIndex = gl_PrimitiveIDIn;\\n    vec4 gs_SourcePosition = gl_in[0].gl_Position;\\n    vec4 gs_TargetPosition = gl_in[1].gl_Position;\\n\\n\\n    #if USE_RELATIONAL\\n    uint od = 1 + atomicAdd(out_degree[gs_SourceIndex], 1);\\n    atomicCounterMax(out_degree_max, od);\\n\\n    uint id = 1 + atomicAdd(in_degree[gs_TargetIndex], 1);\\n    atomicCounterMax(in_degree_max, id);\\n    #endif /* USE_RELATIONAL */\\n\\n\\n\\n    // Apply tile transformations\\n    gs_SourcePosition.xy *= uScale;\\n    gs_SourcePosition.xy += vec2(uTranslateX, uTranslateY);\\n\\n    // Transform xy in [0, 1] to xy in [-1, 1]\\n    gs_SourcePosition.xy *= 2.;\\n    gs_SourcePosition.xy -= 1.;\\n\\n    // Apply tile transformations\\n    gs_TargetPosition.xy *= uScale;\\n    gs_TargetPosition.xy += vec2(uTranslateX, uTranslateY);\\n\\n    // Transform xy in [0, 1] to xy in [-1, 1]\\n    gs_TargetPosition.xy *= 2.;\\n    gs_TargetPosition.xy -= 1.;\\n\\n    gl_PrimitiveID = gs_EdgeIndex;\\n    gl_Position = gs_SourcePosition;\\n    EmitVertex();\\n\\n    gl_Position = gs_TargetPosition;\\n    EmitVertex();\\n\\n    EndPrimitive();\\n}\\n    \",\n",
    "    \"GS_BUFFER_SIZE_4\": \"N\",\n",
    "    \"GS_BUFFER_SIZE_5\": \"N\",\n",
    "    \"GS_BUFFER_SIZE_6\": \"N\",\n",
    "    \"GS_BUFFER_TYPE_0\": \"GL_UNSIGNED_INT\",\n",
    "    \"GS_BUFFER_SIZE_7\": \"N\",\n",
    "    \"GS_BUFFER_TYPE_1\": \"GL_FLOAT\",\n",
    "    \"GS_BUFFER_SIZE_8\": \"E\",\n",
    "    \"GS_OUTPUT\": \"out.jpg\",\n",
    "    \"GS_BUFFER_BIND_0\": \"<NONE>\",\n",
    "    \"GS_BUFFER_TYPE_2\": \"GL_FLOAT\",\n",
    "    \"GS_BUFFER_SIZE_9\": \"48\",\n",
    "    \"GS_BUFFER_BIND_1\": \"0\",\n",
    "    \"GS_BUFFER_TYPE_3\": \"GL_UNSIGNED_INT\",\n",
    "    \"GS_BUFFER_BIND_2\": \"1\",\n",
    "    \"GS_BUFFER_TYPE_4\": \"GL_UNSIGNED_INT\",\n",
    "    \"GS_BUFFER_FILE_0\": \"<NONE>\",\n",
    "    \"GS_BUFFER_BIND_3\": \"2\",\n",
    "    \"GS_BUFFER_TYPE_5\": \"GL_UNSIGNED_INT\",\n",
    "    \"GS_BUFFER_COUNT\": \"10\",\n",
    "    \"GS_BUFFER_NAME_0\": \"_ELEMENT\",\n",
    "    \"GS_BUFFER_FILE_1\": \"<NONE>\",\n",
    "    \"GS_BUFFER_BIND_4\": \"3\",\n",
    "    \"GS_BUFFER_TYPE_6\": \"GL_UNSIGNED_INT\",\n",
    "    \"GS_BUFFER_NAME_1\": \"_X\",\n",
    "    \"GS_BUFFER_FILE_2\": \"<NONE>\",\n",
    "    \"GS_BUFFER_BIND_5\": \"4\",\n",
    "    \"GS_BUFFER_TYPE_7\": \"GL_UNSIGNED_INT\",\n",
    "    \"GS_BUFFER_NAME_2\": \"_Y\",\n",
    "    \"GS_BUFFER_FILE_3\": \"<NONE>\",\n",
    "    \"GS_BUFFER_BIND_6\": \"5\",\n",
    "    \"GS_BUFFER_TYPE_8\": \"GL_UNSIGNED_INT\",\n",
    "    \"GS_ATOMIC_COUNT\": \"12\",\n",
    "    \"GS_BUFFER_NAME_3\": \"_Date\",\n",
    "    \"GS_BUFFER_FILE_4\": \"<NONE>\",\n",
    "    \"GS_BUFFER_BIND_7\": \"6\",\n",
    "    \"GS_ATOMIC_NAME_0\": \"in_degree_max\",\n",
    "    \"GS_BUFFER_TYPE_9\": \"GL_UNSIGNED_INT\",\n",
    "    \"GS_BUFFER_NAME_4\": \"_Devs\",\n",
    "    \"GS_BUFFER_FILE_5\": \"<NONE>\",\n",
    "    \"GS_ATOMIC_NAME_1\": \"out_degree_max\",\n",
    "    \"GS_BUFFER_BIND_8\": \"7\",\n",
    "    \"GS_SHADER_VERTEX\": \"\\n\\nlayout(location=0) out uint _fg_NodeIndex;\\n\\nvoid main() {\\n    const int gs_NodeIndex = gl_VertexID;\\n    vec3 gs_NodePosition = vec3(0., 0., 0.);\\n\\n    float x = X[gs_NodeIndex];\\n    float y = Y[gs_NodeIndex];\\n\\n    gs_NodePosition = vec3(x, y, 0);\\n\\n\\n\\n    gl_Position = vec4(gs_NodePosition.xyz, 1.);\\n\\n    _fg_NodeIndex = gs_NodeIndex;\\n}\\n    \",\n",
    "    \"GS_BACKGROUND_A\": \"1.0\",\n",
    "    \"GS_BUFFER_KIND_0\": \"ELEMENT\",\n",
    "    \"GS_BUFFER_NAME_5\": \"_Vuln\",\n",
    "    \"GS_BUFFER_FILE_6\": \"<NONE>\",\n",
    "    \"GS_ATOMIC_NAME_2\": \"total\",\n",
    "    \"GS_BUFFER_BIND_9\": \"0\",\n",
    "    \"GS_SHADER_FRAGMENT\": \"\\nlayout(location=0) in flat uint gs_SourceIndex;\\nlayout(location=1) in flat uint gs_TargetIndex;\\n\\nlayout(location=0) out vec4 gs_FragColor;\\n\\nvoid main() {\\n    int gs_EdgeIndex = gl_PrimitiveID;\\n    bool first = 0 == atomicAdd(Seen[gs_EdgeIndex], 1);\\n    bool d = false;\\n\\n    if (first) atomicCounterAdd(total, 1);\\n\\n    #if FILTER_BY_DATE\\n\\n    if (Date[gs_SourceIndex] < LO) {\\n        d = true;\\n        if (first) atomicCounterAdd(source_date_too_lo, 1);\\n    }\\n\\n    if (Date[gs_SourceIndex] > HI) {\\n        d = true;\\n        if (first) atomicCounterAdd(source_date_too_hi, 1);\\n    }\\n\\n    if (Date[gs_TargetIndex] < LO) {\\n        d = true;\\n        if (first) atomicCounterAdd(target_date_too_lo, 1);\\n    }\\n\\n    if (Date[gs_TargetIndex] > HI) {\\n        d = true;\\n        if (first) atomicCounterAdd(target_date_too_hi, 1);\\n    }\\n    #endif /* FILTER_BY_DATE */\\n\\n    if (d) {\\n        if (first) atomicCounterAdd(discarded, 1);\\n        discard;\\n    } else {\\n        if (first) atomicCounterAdd(kept, 1);\\n    }\\n\\n    bool vuln = bool(Vuln[gs_SourceIndex]) || bool(Vuln[gs_TargetIndex]);\\n    bool risky = Devs[gs_SourceIndex] > Devs[gs_TargetIndex];\\n\\n    #if USE_RELATIONAL\\n    const uint depends_on_source = in_degree[gs_SourceIndex];\\n    const uint depends_on_target = in_degree[gs_TargetIndex];\\n\\n    risky = depends_on_source + depends_on_target > 100 * Devs[gs_TargetIndex];\\n    #endif /* USE_RELATIONAL */\\n\\n    if (risky) {\\n        if (first) atomicCounterAdd(total_risky, 1);\\n    }\\n\\n    if (risky && vuln) {\\n        if (first) atomicCounterAdd(total_vuln_and_risky, 1);\\n    }\\n\\n    if (vuln) {\\n        if (first) atomicCounterAdd(total_vuln, 1);\\n    }\\n\\n    gs_FragColor = vec4(0.1);\\n    gs_FragColor.r = float(vuln);\\n    gs_FragColor.b = float(risky);\\n}\\n    \",\n",
    "    \"GS_BACKGROUND_B\": \"1.0\",\n",
    "    \"GS_BUFFER_KIND_1\": \"ATTRIBUTE\",\n",
    "    \"GS_BUFFER_NAME_6\": \"_in_degree\",\n",
    "    \"GS_BUFFER_FILE_7\": \"<NONE>\",\n",
    "    \"GS_ATOMIC_NAME_3\": \"source_date_too_lo\",\n",
    "    \"GS_TILE_WIDTH\": \"256\",\n",
    "    \"GS_BUFFER_KIND_2\": \"ATTRIBUTE\",\n",
    "    \"GS_BUFFER_NAME_7\": \"_out_degree\",\n",
    "    \"GS_BUFFER_FILE_8\": \"<NONE>\",\n",
    "    \"GS_ATOMIC_NAME_4\": \"source_date_too_hi\",\n",
    "    \"GS_BUFFER_KIND_3\": \"ATTRIBUTE\",\n",
    "    \"GS_BUFFER_NAME_8\": \"_Seen\",\n",
    "    \"GS_ATOMIC_NAME_5\": \"target_date_too_lo\",\n",
    "    \"GS_BUFFER_FILE_9\": \"<NONE>\",\n",
    "    \"GS_BUFFER_KIND_4\": \"ATTRIBUTE\",\n",
    "    \"GS_ATOMIC_NAME_6\": \"target_date_too_hi\",\n",
    "    \"GS_BUFFER_NAME_9\": \"_ATOMIC\",\n",
    "    \"GS_BUFFER_KIND_5\": \"ATTRIBUTE\",\n",
    "    \"GS_ATOMIC_NAME_7\": \"discarded\",\n",
    "    \"GS_BACKGROUND_G\": \"1.0\",\n",
    "    \"GS_BUFFER_KIND_6\": \"SCRATCH\",\n",
    "    \"GS_ATOMIC_NAME_8\": \"kept\",\n",
    "    \"GS_BUFFER_KIND_7\": \"SCRATCH\",\n",
    "    \"GS_ATOMIC_NAME_9\": \"total_risky\",\n",
    "    \"GS_BUFFER_KIND_8\": \"SCRATCH\",\n",
    "    \"GS_ATOMIC_NAME_10\": \"total_vuln_and_risky\",\n",
    "    \"GS_ATOMIC_NAME_11\": \"total_vuln\",\n",
    "    \"GS_BUFFER_KIND_9\": \"ATOMIC\",\n",
    "    \"GS_BACKGROUND_R\": \"1.0\",\n",
    "    \"GS_SHADER_COMMON\": \"\\n#version 460 core\\nprecision mediump float;\\n\\nuniform float uTranslateX;\\nuniform float uTranslateY;\\nuniform float uScale;\\n// JS-Deps: Node Package Manager Dependency Graph\\n//\\n// Nodes are packages. Edges are directed from a package to its dependencies.\\n\\nlayout (std430, binding=0) buffer _X { float X[]; }; // attribute(float X[N])\\nlayout (std430, binding=1) buffer _Y { float Y[]; }; // attribute(float Y[N])\\nlayout (std430, binding=2) buffer _Date { uint Date[]; }; // attribute(uint Date[N])\\nlayout (std430, binding=3) buffer _Devs { uint Devs[]; }; // attribute(uint Devs[N])\\nlayout (std430, binding=4) buffer _Vuln { uint Vuln[]; }; // attribute(uint Vuln[N])\\n\\n#define NOV_09_2010 1289278800\\n#define MAR_22_2016 1458619200\\n\\n#define JAN_01_2011 1293858000\\n#define JAN_01_2012 1325394000\\n#define JAN_01_2013 1357016400\\n#define JAN_01_2014 1388552400\\n#define JAN_01_2015 1420088400\\n#define JAN_01_2016 1451624400\\n\\n// Some controls\\n\\n\\nlayout (std430, binding=5) buffer _in_degree { uint in_degree[]; }; // scratch(uint in_degree[N])\\nlayout (std430, binding=6) buffer _out_degree { uint out_degree[]; }; // scratch(uint out_degree[N])\\nlayout (binding=0, offset=0) uniform atomic_uint in_degree_max; // scratch(atomic_uint in_degree_max)\\nlayout (binding=0, offset=4) uniform atomic_uint out_degree_max; // scratch(atomic_uint out_degree_max)\\n#define USE_RELATIONAL 1\\nlayout (std430, binding=7) buffer _Seen { uint Seen[]; }; // scratch(uint Seen[E])\\nlayout (binding=0, offset=8) uniform atomic_uint total; // scratch(atomic_uint total)\\n#define FILTER_BY_DATE 1\\n#define LO JAN_01_2014\\n#define HI JAN_01_2015\\nlayout (binding=0, offset=12) uniform atomic_uint source_date_too_lo; // scratch(atomic_uint source_date_too_lo)\\nlayout (binding=0, offset=16) uniform atomic_uint source_date_too_hi; // scratch(atomic_uint source_date_too_hi)\\nlayout (binding=0, offset=20) uniform atomic_uint target_date_too_lo; // scratch(atomic_uint target_date_too_lo)\\nlayout (binding=0, offset=24) uniform atomic_uint target_date_too_hi; // scratch(atomic_uint target_date_too_hi)\\nlayout (binding=0, offset=28) uniform atomic_uint discarded; // scratch(atomic_uint discarded)\\nlayout (binding=0, offset=32) uniform atomic_uint kept; // scratch(atomic_uint kept)\\nlayout (binding=0, offset=36) uniform atomic_uint total_risky; // scratch(atomic_uint total_risky)\\nlayout (binding=0, offset=40) uniform atomic_uint total_vuln_and_risky; // scratch(atomic_uint total_vuln_and_risky)\\nlayout (binding=0, offset=44) uniform atomic_uint total_vuln; // scratch(atomic_uint total_vuln)\\n    \",\n",
    "    \"GS_TILE_X\": \"0\",\n",
    "    \"GS_TILE_Y\": \"0\"\n",
    "})\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c0c19dc",
   "metadata": {},
   "source": [
    "# 3rd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "53c0e061",
   "metadata": {},
   "outputs": [],
   "source": [
    "JSDeps = Graph(\n",
    "    files=dict(\n",
    "        element=\"examples/JS-Deps/data/JS-Deps.edge.elements.2u32.bin\",\n",
    "        X      =\"examples/JS-Deps/data/JS-Deps.node.x.f32.bin\",\n",
    "        Y      =\"examples/JS-Deps/data/JS-Deps.node.y.f32.bin\",\n",
    "        Date   =\"examples/JS-Deps/data/JS-Deps.node.date.u32.bin\",\n",
    "        Devs   =\"examples/JS-Deps/data/JS-Deps.node.nmaintainers.u32.bin\",\n",
    "        Vuln   =\"examples/JS-Deps/data/JS-Deps.node.cve.u32.bin\",\n",
    "    ),\n",
    "    size=(512, 512),\n",
    "    tile=(0, 0, 0),\n",
    "    verbose=True,\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "4e08afdb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%.render -n JSDeps\n",
    "#pragma gs attribute(float X[N])\n",
    "#pragma gs attribute(float Y[N])\n",
    "#pragma gs attribute(uint Date[N])\n",
    "#pragma gs attribute(uint Devs[N])\n",
    "#pragma gs attribute(uint Vuln[N])\n",
    "\n",
    "#define NOV_09_2010 1289278800\n",
    "#define MAR_22_2016 1458619200\n",
    "\n",
    "#define JAN_01_2011 1293858000\n",
    "#define JAN_01_2012 1325394000\n",
    "#define JAN_01_2013 1357016400\n",
    "#define JAN_01_2014 1388552400\n",
    "#define JAN_01_2015 1420088400\n",
    "#define JAN_01_2016 1451624400\n",
    "\n",
    "#pragma gs shader(positional)\n",
    "void main() {\n",
    "    float x = X[gs_NodeIndex];\n",
    "    float y = Y[gs_NodeIndex];\n",
    "\n",
    "    gs_NodePosition = vec3(x, y, 0);\n",
    "}\n",
    "\n",
    "#pragma gs shader(relational)\n",
    "void main() {\n",
    "}\n",
    "\n",
    "#pragma gs shader(appearance)\n",
    "void main() {\n",
    "    bool d = false;\n",
    "\n",
    "    #pragma gs define(LO JAN_01_2015)\n",
    "    #pragma gs define(HI JAN_01_2016)\n",
    "    d = d || Date[gs_SourceIndex] < LO;\n",
    "    d = d || Date[gs_SourceIndex] > HI;\n",
    "    d = d || Date[gs_TargetIndex] < LO;\n",
    "    d = d || Date[gs_TargetIndex] > HI;\n",
    "    \n",
    "    if (d) discard;\n",
    "    \n",
    "    bool vuln = bool(Vuln[gs_SourceIndex]) || bool(Vuln[gs_TargetIndex]);\n",
    "    bool risky = Devs[gs_SourceIndex] > Devs[gs_TargetIndex];\n",
    "\n",
    "    gs_FragColor = vec4(0.1);\n",
    "    gs_FragColor.r = float(vuln);\n",
    "    gs_FragColor.b = float(risky);\n",
    "}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "b4965816",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%.render -n JSDeps\n",
    "// JS-Deps: Node Package Manager Dependency Graph\n",
    "//\n",
    "// Nodes are packages. Edges are directed from a package to its dependencies.\n",
    "\n",
    "#pragma gs attribute(float X[N])\n",
    "#pragma gs attribute(float Y[N])\n",
    "#pragma gs attribute(uint Date[N])\n",
    "#pragma gs attribute(uint Devs[N])\n",
    "#pragma gs attribute(uint Vuln[N])\n",
    "\n",
    "#define NOV_09_2010 1289278800\n",
    "#define MAR_22_2016 1458619200\n",
    "\n",
    "#define JAN_01_2011 1293858000\n",
    "#define JAN_01_2012 1325394000\n",
    "#define JAN_01_2013 1357016400\n",
    "#define JAN_01_2014 1388552400\n",
    "#define JAN_01_2015 1420088400\n",
    "#define JAN_01_2016 1451624400\n",
    "\n",
    "// Some controls\n",
    "#pragma gs define(USE_COLOR)\n",
    "#pragma gs define(USE_FILTER)\n",
    "#pragma gs define(USE_RELATIONAL)\n",
    "\n",
    "\n",
    "#pragma gs shader(positional)\n",
    "void main() {\n",
    "    float x = X[gs_NodeIndex];\n",
    "    float y = Y[gs_NodeIndex];\n",
    "\n",
    "    gs_NodePosition = vec3(x, y, 0);\n",
    "}\n",
    "\n",
    "\n",
    "#pragma gs shader(relational)\n",
    "void main() {\n",
    "    #pragma gs scratch(uint in_degree[N])\n",
    "    #pragma gs scratch(uint out_degree[N])\n",
    "    #pragma gs scratch(atomic_uint in_degree_max)\n",
    "    #pragma gs scratch(atomic_uint out_degree_max)\n",
    "\n",
    "    #pragma gs define(USE_RELATIONAL 1)\n",
    "    #if USE_RELATIONAL\n",
    "    uint od = 1 + atomicAdd(out_degree[gs_SourceIndex], 1);\n",
    "    atomicCounterMax(out_degree_max, od);\n",
    "\n",
    "    uint id = 1 + atomicAdd(in_degree[gs_TargetIndex], 1);\n",
    "    atomicCounterMax(in_degree_max, id);\n",
    "    #endif /* USE_RELATIONAL */\n",
    "}\n",
    "\n",
    "\n",
    "#pragma gs shader(appearance)\n",
    "void main() {\n",
    "    #pragma gs scratch(uint Seen[E])\n",
    "    bool first = 0 == atomicAdd(Seen[gs_EdgeIndex], 1);\n",
    "    bool d = false;\n",
    "\n",
    "    #pragma gs scratch(atomic_uint total)\n",
    "    if (first) atomicCounterAdd(total, 1);\n",
    "\n",
    "    #pragma gs define(FILTER_BY_DATE 1)\n",
    "    #if FILTER_BY_DATE\n",
    "    #pragma gs define(LO JAN_01_2014)\n",
    "    #pragma gs define(HI JAN_01_2015)\n",
    "\n",
    "    if (Date[gs_SourceIndex] < LO) {\n",
    "        d = true;\n",
    "        #pragma gs scratch(atomic_uint source_date_too_lo)\n",
    "        if (first) atomicCounterAdd(source_date_too_lo, 1);\n",
    "    }\n",
    "\n",
    "    if (Date[gs_SourceIndex] > HI) {\n",
    "        d = true;\n",
    "        #pragma gs scratch(atomic_uint source_date_too_hi)\n",
    "        if (first) atomicCounterAdd(source_date_too_hi, 1);\n",
    "    }\n",
    "\n",
    "    if (Date[gs_TargetIndex] < LO) {\n",
    "        d = true;\n",
    "        #pragma gs scratch(atomic_uint target_date_too_lo)\n",
    "        if (first) atomicCounterAdd(target_date_too_lo, 1);\n",
    "    }\n",
    "\n",
    "    if (Date[gs_TargetIndex] > HI) {\n",
    "        d = true;\n",
    "        #pragma gs scratch(atomic_uint target_date_too_hi)\n",
    "        if (first) atomicCounterAdd(target_date_too_hi, 1);\n",
    "    }\n",
    "    #endif /* FILTER_BY_DATE */\n",
    "\n",
    "    if (d) {\n",
    "        #pragma gs scratch(atomic_uint discarded)\n",
    "        if (first) atomicCounterAdd(discarded, 1);\n",
    "        discard;\n",
    "    } else {\n",
    "        #pragma gs scratch(atomic_uint kept)\n",
    "        if (first) atomicCounterAdd(kept, 1);\n",
    "    }\n",
    "\n",
    "    bool vuln = bool(Vuln[gs_SourceIndex]) || bool(Vuln[gs_TargetIndex]);\n",
    "    bool risky = Devs[gs_SourceIndex] > Devs[gs_TargetIndex];\n",
    "\n",
    "    #if USE_RELATIONAL\n",
    "    const uint depends_on_source = in_degree[gs_SourceIndex];\n",
    "    const uint depends_on_target = in_degree[gs_TargetIndex];\n",
    "\n",
    "    risky = depends_on_source + depends_on_target > 100 * Devs[gs_TargetIndex];\n",
    "    #endif /* USE_RELATIONAL */\n",
    "\n",
    "    if (risky) {\n",
    "        #pragma gs scratch(atomic_uint total_risky)\n",
    "        if (first) atomicCounterAdd(total_risky, 1);\n",
    "    }\n",
    "\n",
    "    if (risky && vuln) {\n",
    "        #pragma gs scratch(atomic_uint total_vuln_and_risky)\n",
    "        if (first) atomicCounterAdd(total_vuln_and_risky, 1);\n",
    "    }\n",
    "\n",
    "    if (vuln) {\n",
    "        #pragma gs scratch(atomic_uint total_vuln)\n",
    "        if (first) atomicCounterAdd(total_vuln, 1);\n",
    "    }\n",
    "\n",
    "    gs_FragColor = vec4(0.1);\n",
    "    gs_FragColor.r = float(vuln);\n",
    "    gs_FragColor.b = float(risky);\n",
    "}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "1f2c087b",
   "metadata": {},
   "outputs": [],
   "source": [
    "SOAnswers = Graph(\n",
    "    files=dict(\n",
    "        element=\"examples/SO-Answers/data/SO-Answers.edge.element.2u32.bin\",\n",
    "        X=\"examples/SO-Answers/data/SO-Answers.node.x.f32.bin\",\n",
    "        Y=\"examples/SO-Answers/data/SO-Answers.node.y.f32.bin\",\n",
    "        When=\"examples/SO-Answers/data/SO-Answers.edge.when.u32.bin\",\n",
    "    ),\n",
    "    size=(512, 512),\n",
    "    tile=(0, 0, 0),\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "c8766471",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "EGL_VERSION: 1.5\n",
      "EGL_VENDOR: NVIDIA\n",
      "EGL_CLIENT_APIS: OpenGL_ES OpenGL\n",
      "EGL_EXTENSIONS: EGL_EXT_buffer_age EGL_EXT_client_sync EGL_EXT_create_context_robustness EGL_EXT_image_dma_buf_import EGL_EXT_image_dma_buf_import_modifiers EGL_MESA_image_dma_buf_export EGL_EXT_output_base EGL_EXT_protected_content EGL_EXT_stream_acquire_mode EGL_EXT_sync_reuse EGL_IMG_context_priority EGL_KHR_config_attribs EGL_KHR_create_context_no_error EGL_KHR_context_flush_control EGL_KHR_create_context EGL_KHR_fence_sync EGL_KHR_get_all_proc_addresses EGL_KHR_partial_update EGL_KHR_swap_buffers_with_damage EGL_KHR_no_config_context EGL_KHR_gl_colorspace EGL_KHR_gl_renderbuffer_image EGL_KHR_gl_texture_2D_image EGL_KHR_gl_texture_3D_image EGL_KHR_gl_texture_cubemap_image EGL_KHR_image EGL_KHR_image_base EGL_KHR_reusable_sync EGL_KHR_stream EGL_KHR_stream_attrib EGL_KHR_stream_consumer_gltexture EGL_KHR_stream_cross_process_fd EGL_KHR_stream_fifo EGL_KHR_stream_producer_eglsurface EGL_KHR_surfaceless_context EGL_KHR_wait_sync EGL_NV_nvrm_fence_sync EGL_NV_quadruple_buffer EGL_NV_stream_consumer_eglimage EGL_NV_stream_cross_display EGL_NV_stream_cross_object EGL_NV_stream_cross_process EGL_NV_stream_cross_system EGL_NV_stream_dma EGL_NV_stream_flush EGL_NV_stream_metadata EGL_NV_stream_remote EGL_NV_stream_reset EGL_NV_stream_socket EGL_NV_stream_socket_inet EGL_NV_stream_socket_unix EGL_NV_stream_sync EGL_NV_stream_fifo_next EGL_NV_stream_fifo_synchronous EGL_NV_stream_consumer_gltexture_yuv EGL_NV_stream_attrib EGL_NV_stream_origin EGL_NV_system_time EGL_NV_output_drm_flip_event EGL_NV_triple_buffer EGL_NV_robustness_video_memory_purge\n",
      "GL_VENDOR: NVIDIA Corporation\n",
      "GL_VERSION: 4.6.0 NVIDIA 535.183.06\n",
      "GL_RENDERER: Quadro M6000 24GB/PCIe/SSE2\n",
      "GL_SHADING_LANGUAGE_VERSION: 4.60 NVIDIA\n",
      "buffer 0\n",
      "  name: _ELEMENT\n",
      "  kind: ELEMENT\n",
      "  file: examples/SO-Answers/data/SO-Answers.edge.element.2u32.bin\n",
      "  size: 2E\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "Read from examples/SO-Answers/data/SO-Answers.edge.element.2u32.bin\n",
      "buffer 1\n",
      "  name: _X\n",
      "  kind: ATTRIBUTE\n",
      "  file: examples/SO-Answers/data/SO-Answers.node.x.f32.bin\n",
      "  size: N\n",
      "  type: GL_FLOAT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "Read from examples/SO-Answers/data/SO-Answers.node.x.f32.bin\n",
      "buffer 2\n",
      "  name: _Y\n",
      "  kind: ATTRIBUTE\n",
      "  file: examples/SO-Answers/data/SO-Answers.node.y.f32.bin\n",
      "  size: N\n",
      "  type: GL_FLOAT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "Read from examples/SO-Answers/data/SO-Answers.node.y.f32.bin\n",
      "buffer 3\n",
      "  name: _When\n",
      "  kind: ATTRIBUTE\n",
      "  file: examples/SO-Answers/data/SO-Answers.edge.when.u32.bin\n",
      "  size: E\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "Read from examples/SO-Answers/data/SO-Answers.edge.when.u32.bin\n",
      "buffer 4\n",
      "  name: _FirstContribution\n",
      "  kind: SCRATCH\n",
      "  file: <NONE>\n",
      "  size: N\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "buffer 5\n",
      "  name: _LastContribution\n",
      "  kind: SCRATCH\n",
      "  file: <NONE>\n",
      "  size: N\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "buffer 6\n",
      "  name: _CommentsReceived\n",
      "  kind: SCRATCH\n",
      "  file: <NONE>\n",
      "  size: N\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "buffer 7\n",
      "  name: _CommentsPosted\n",
      "  kind: SCRATCH\n",
      "  file: <NONE>\n",
      "  size: N\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "buffer 8\n",
      "  name: _ATOMIC\n",
      "  kind: ATOMIC\n",
      "  file: <NONE>\n",
      "  size: 8\n",
      "  type: GL_UNSIGNED_INT\n",
      "app_data_buffer = (nil); app_data_buflen = 0\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 0, 2)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 1, 3)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 2, 4)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 3, 5)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 4, 6)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 5, 7)\n",
      "X_BIND_BUFFER: glBindBufferBase(0x90d2, 6, 8)\n",
      "glDrawElements(0x1, 24299826, 0x1405, (nil))\n",
      "--- Atomics\n",
      "atomic 0 \"MaxCommentsReceived\" = 5129\n",
      "atomic 1 \"MaxCommentsPosted\" = 28799\n",
      "JPEG: 512x512\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"metadata\": {\n",
      "     \"nodes\": 1233244,\n",
      "     \"edges\": 12149913\n",
      "  },\n",
      "  \"atomics\": {\n",
      "    \"MaxCommentsReceived\": 5129,\n",
      "    \"MaxCommentsPosted\": 28799\n",
      "  }\n",
      "}\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Wrote 279009 bytes to /tmp/tmpljs4yz2y/outfile.jpg\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%.render -n SOAnswers -v\n",
    "#pragma gs attribute(float X[N])\n",
    "#pragma gs attribute(float Y[N])\n",
    "#pragma gs attribute(uint When[E])\n",
    "\n",
    "#define AUG_01_2008 1217563200\n",
    "#define MAR_07_2016 1457326800\n",
    "\n",
    "#define JAN_01_2011 1293858000\n",
    "#define JAN_01_2012 1325394000\n",
    "#define JAN_01_2013 1357016400\n",
    "#define JAN_01_2014 1388552400\n",
    "#define JAN_01_2015 1420088400\n",
    "#define JAN_01_2016 1451624400\n",
    "\n",
    "#pragma gs define(LAYOUT 1)\n",
    "\n",
    "#pragma gs shader(positional)\n",
    "void main() {\n",
    "    float x = X[gs_NodeIndex];\n",
    "    float y = Y[gs_NodeIndex];\n",
    "\n",
    "    gs_NodePosition = vec3(x, y, 0.);\n",
    "}\n",
    "\n",
    "\n",
    "#pragma gs shader(relational)\n",
    "void main() {\n",
    "    const uint when = When[gs_EdgeIndex];\n",
    "\n",
    "    #pragma gs scratch(uint FirstContribution[N])\n",
    "\n",
    "    atomicCompSwap(FirstContribution[gs_SourceIndex], 0, when);\n",
    "    atomicMin(FirstContribution[gs_SourceIndex], when);\n",
    "\n",
    "    atomicCompSwap(FirstContribution[gs_TargetIndex], 0, when);\n",
    "    atomicMin(FirstContribution[gs_TargetIndex], when);\n",
    "\n",
    "    #pragma gs scratch(uint LastContribution[N])\n",
    "\n",
    "    atomicCompSwap(LastContribution[gs_SourceIndex], 0, when);\n",
    "    atomicMax(LastContribution[gs_SourceIndex], when);\n",
    "\n",
    "    atomicCompSwap(LastContribution[gs_TargetIndex], 0, when);\n",
    "    atomicMax(LastContribution[gs_TargetIndex], when);\n",
    "\n",
    "    #pragma gs scratch(uint CommentsReceived[N])\n",
    "    #pragma gs scratch(atomic_uint MaxCommentsReceived)\n",
    "    uint cr = 1 + atomicAdd(CommentsReceived[gs_TargetIndex], 1);\n",
    "    atomicCounterMax(MaxCommentsReceived, cr);\n",
    "\n",
    "    #pragma gs scratch(uint CommentsPosted[N])\n",
    "    #pragma gs scratch(atomic_uint MaxCommentsPosted)\n",
    "    uint cp = 1 + atomicAdd(CommentsPosted[gs_SourceIndex], 1);\n",
    "    atomicCounterMax(MaxCommentsPosted, cp);\n",
    "\n",
    "    if (LAYOUT == 2) {\n",
    "        gs_SourcePosition.x = float(FirstContribution[gs_SourceIndex] - AUG_01_2008) / float(MAR_07_2016 - AUG_01_2008);\n",
    "        gs_SourcePosition.y = 1. - float(LastContribution[gs_SourceIndex] - AUG_01_2008) / float(MAR_07_2016 - AUG_01_2008);\n",
    "\n",
    "        gs_TargetPosition.x = float(FirstContribution[gs_TargetIndex] - AUG_01_2008) / float(MAR_07_2016 - AUG_01_2008);\n",
    "        gs_TargetPosition.y = 1. - float(LastContribution[gs_TargetIndex] - AUG_01_2008) / float(MAR_07_2016 - AUG_01_2008);\n",
    "    }\n",
    "}\n",
    "\n",
    "#pragma gs shader(appearance)\n",
    "void main() {\n",
    "    bool b1 = CommentsPosted[gs_SourceIndex] >= CommentsReceived[gs_SourceIndex] / 32;\n",
    "    \n",
    "    const uint sourceSpan = LastContribution[gs_SourceIndex] - FirstContribution[gs_SourceIndex];\n",
    "    const uint targetSpan = LastContribution[gs_TargetIndex] - FirstContribution[gs_TargetIndex];\n",
    "    bool b2 = targetSpan >= sourceSpan;\n",
    "\n",
    "    gs_FragColor = vec4(0.1);\n",
    "    gs_FragColor.r = float(b1 || b2);\n",
    "    gs_FragColor.g = float(b1 && b2);\n",
    "}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "d5d0774b",
   "metadata": {},
   "outputs": [],
   "source": [
    "NBERPatents = Graph(\n",
    "    files=dict(\n",
    "        element=\"examples/NBER-Patents/data/NBER-Patents.edge.element.2u32.bin\",\n",
    "        X=      \"examples/NBER-Patents/data/NBER-Patents.node.x.f32.bin\", \n",
    "        Y=      \"examples/NBER-Patents/data/NBER-Patents.node.y.f32.bin\", \n",
    "        GotYear=\"examples/NBER-Patents/data/NBER-Patents.node.gotyear.u32.bin\",\n",
    "        AppYear=\"examples/NBER-Patents/data/NBER-Patents.node.appyear.u32.bin\",\n",
    "        Cat1=   \"examples/NBER-Patents/data/NBER-Patents.node.cat1.u32.bin\", \n",
    "        Cat2=   \"examples/NBER-Patents/data/NBER-Patents.node.cat2.u32.bin\",\n",
    "    ),\n",
    "    size=(512, 512),\n",
    "    tile=(1, 0.25, 0.5),\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "812c3714",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%.render -n NBERPatents\n",
    "#pragma gs attribute(float X[N])\n",
    "#pragma gs attribute(float Y[N])\n",
    "#pragma gs attribute(uint AppYear[N])\n",
    "#pragma gs attribute(uint GotYear[N])\n",
    "#pragma gs attribute(uint Cat1[N])\n",
    "#pragma gs attribute(uint Cat2[N])\n",
    "\n",
    "#pragma gs shader(positional)\n",
    "void main() {\n",
    "    float x = X[gs_NodeIndex];\n",
    "    float y = Y[gs_NodeIndex];\n",
    "    gs_NodePosition = vec3(x, y, 0);\n",
    "}\n",
    "\n",
    "#pragma gs shader(relational)\n",
    "void main() {\n",
    "}\n",
    "\n",
    "#pragma gs shader(appearance)\n",
    "void main() {\n",
    "    #pragma gs define(SRC_CAT1 2)\n",
    "    #pragma gs define(TGT_CAT1 4)\n",
    "    #pragma gs define(LO 1980)\n",
    "    #pragma gs define(HI 1989)\n",
    "\n",
    "    #pragma gs scratch(uint Seen[E])\n",
    "    bool first = 0 == atomicAdd(Seen[gs_EdgeIndex], 1);\n",
    "\n",
    "    bool d = false;\n",
    "\n",
    "    #pragma gs scratch(atomic_uint count)\n",
    "    if (first) atomicCounterAdd(count, 1);\n",
    "\n",
    "    if (Cat1[gs_SourceIndex] != SRC_CAT1) {\n",
    "        d = true;\n",
    "        #pragma gs scratch(atomic_uint wrong_source_cat)\n",
    "        if (first) atomicCounterAdd(wrong_source_cat, 1);\n",
    "    }\n",
    "\n",
    "    if (Cat1[gs_TargetIndex] != TGT_CAT1) {\n",
    "        d = true;\n",
    "        #pragma gs scratch(atomic_uint wrong_target_cat)\n",
    "        if (first) atomicCounterAdd(wrong_target_cat, 1);\n",
    "    }\n",
    "\n",
    "    if (AppYear[gs_SourceIndex] < LO) {\n",
    "        d = true;\n",
    "        #pragma gs scratch(atomic_uint app_year_too_lo)\n",
    "        if (first) atomicCounterAdd(app_year_too_lo, 1);\n",
    "    }\n",
    "\n",
    "    if (AppYear[gs_SourceIndex] > HI) {\n",
    "        d = true;\n",
    "        #pragma gs scratch(atomic_uint app_year_too_hi)\n",
    "        if (first) atomicCounterAdd(app_year_too_hi, 1);\n",
    "    }\n",
    "\n",
    "    if (d) {\n",
    "        #pragma gs scratch(atomic_uint discarded)\n",
    "        if (first) atomicCounterAdd(discarded, 1);\n",
    "        discard;\n",
    "    }\n",
    "\n",
    "    #pragma gs scratch(atomic_uint kept)\n",
    "    if (first) atomicCounterAdd(kept, 1);\n",
    "\n",
    "    uint gotyear = GotYear[gs_SourceIndex];\n",
    "    uint appyear = AppYear[gs_SourceIndex];\n",
    "    uint lag = gotyear - appyear;\n",
    "\n",
    "    #pragma gs define(CUTOFF1 2)\n",
    "    #pragma gs define(CUTOFF2 4)\n",
    "\n",
    "    gs_FragColor = vec4(0.1);\n",
    "    gs_FragColor.r = int(lag < CUTOFF1);\n",
    "    gs_FragColor.g = int(CUTOFF1 <= lag && lag < CUTOFF2);\n",
    "    gs_FragColor.b = int(CUTOFF2 <= lag);\n",
    "}\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b062fe76",
   "metadata": {},
   "source": [
    "# end"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.5"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": false,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}