day 55 - quincunx.ipynb

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    "import numpy as np\n",
    "from bokeh.plotting import figure, show, output_notebook\n",
    "from bokeh.io import push_notebook\n",
    "from time import sleep"
   ]
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   "source": [
    "## algorithm"
   ]
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   "source": [
    "def update_quincunx(n, balls, buckets):\n",
    "    x0, x1, y = balls.T\n",
    "\n",
    "    # update buckets\n",
    "    buckets[x1[y == 1] + n] += 1\n",
    "\n",
    "    # update y\n",
    "    y[:] -= 1\n",
    "    y[y <= 0] = n\n",
    "\n",
    "    # update x\n",
    "    x1[y == n] = 0\n",
    "    x0[:] = x1\n",
    "    x1[:] += np.random.choice([-1, 1], len(x1))"
   ]
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   "source": [
    "def animate_quincunx(time, balls):\n",
    "    x0, x1, y = balls.T\n",
    "\n",
    "    # animate position\n",
    "    x = x0 * (1 - time) + x1 * time\n",
    "    y = y * (1 - time) + (y - 1) * time\n",
    "    \n",
    "    return x, y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## initialization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
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   "outputs": [],
   "source": [
    "# quincunx size\n",
    "N = 30"
   ]
  },
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   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
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   "source": [
    "# row ~ ball, column ~ (current_x, next_x, current_y)\n",
    "balls = np.zeros((N - 1, 3), dtype=int)\n",
    "balls[:, 2] = np.arange(N - 1, dtype=int) + N + 1"
   ]
  },
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   "execution_count": 6,
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   "source": [
    "# bottom buckets\n",
    "buckets = np.zeros(2 * N + 1, dtype=float)\n",
    "buckets_x = np.arange(-N, N + 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## plot"
   ]
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   "cell_type": "code",
   "execution_count": 7,
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       "            var render_items = [{\"docid\":\"6be68d10-3acd-4652-9a67-0f03266b83a0\",\"elementid\":\"1a574e4b-9e98-4fbd-b5ac-b69df07a26b8\",\"modelid\":\"9fe75c1b-77e7-47a2-93fe-cbfa39fb6bff\",\"notebook_comms_target\":\"e38d5958-093b-48f7-9abe-1e0a16e78d86\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "  \n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"1a574e4b-9e98-4fbd-b5ac-b69df07a26b8\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "  \n",
       "    }\n",
       "  \n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "output_notebook()\n",
    "\n",
    "# figure\n",
    "plot = figure(plot_width=640, plot_height=420, tools='',\n",
    "              x_range=(-N, N), y_range=(0, N))\n",
    "plot.grid.visible = False\n",
    "plot.yaxis.visible = False\n",
    "\n",
    "# initial plot\n",
    "x, y = animate_quincunx(1, balls)\n",
    "\n",
    "vbar = plot.vbar(x=buckets_x, width=.8, bottom=0, top=buckets,\n",
    "                 fill_alpha=.4, fill_color='red', line_color='red')\n",
    "scatter = plot.scatter(x, y)\n",
    "\n",
    "# show\n",
    "handle = show(plot, notebook_handle=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for i in range(N * 5 * 30):\n",
    "    time = round(i / 5 % 1, 1)\n",
    "\n",
    "    # update bars\n",
    "    if time == 0:\n",
    "        update_quincunx(N, balls, buckets)\n",
    "        vbar.data_source.data['top'] = buckets * .2\n",
    "        \n",
    "    # update scatter\n",
    "    x, y = animate_quincunx(time, balls)\n",
    "    scatter.data_source.data['x'] = x\n",
    "    scatter.data_source.data['y'] = y\n",
    "\n",
    "    push_notebook()\n",
    "    sleep(.05)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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