slinderman/bar_demo.ipynb

## bar_demo.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "from hips.plotting.colormaps import gradient_cmap\n",
    "from hips.plotting.layout import create_axis_at_location\n",
    "import seaborn as sns\n",
    "sns.set_style(\"white\")\n",
    "sns.set_context(\"paper\")\n",
    "color_names = [\"windows blue\",\n",
    "               \"red\",\n",
    "               \"amber\",\n",
    "               \"faded green\",\n",
    "               \"dusty purple\",\n",
    "               \"orange\",\n",
    "               \"clay\",\n",
    "               \"pink\",\n",
    "               \"greyish\",\n",
    "               \"mint\",\n",
    "               \"light cyan\",\n",
    "               \"steel blue\",\n",
    "               \"forest green\",\n",
    "               \"pastel purple\",\n",
    "               \"salmon\",\n",
    "               \"dark brown\"]\n",
    "colors = sns.xkcd_palette(color_names)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# make fake data\n",
    "N = 10\n",
    "names = [\n",
    "    \"Kermit the Frog\",\n",
    "    \"Miss Piggy\",\n",
    "    \"Fozzie Bear\",\n",
    "    \"Gonzo\",\n",
    "    \"Rowlf\",\n",
    "    \"Scooter\",\n",
    "    \"Pepe\",\n",
    "    \"Rizzo\",\n",
    "    \"Animal\",\n",
    "    \"Walter\"]\n",
    "ys = np.random.gamma(1, 1, size=N)\n",
    "yerrs = np.random.gamma(1, 0.1, size=N)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x119ae7c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Make a bar chart with errorbars\n",
    "fig = plt.figure(figsize=(2,2))\n",
    "ax = fig.add_subplot(111)\n",
    "\n",
    "# Remove spines and stuff\n",
    "ax.spines['top'].set_visible(False)\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.get_xaxis().tick_bottom()\n",
    "ax.get_yaxis().tick_left()\n",
    "\n",
    "# Make bar plot, save handles\n",
    "width = 0.8\n",
    "handles = []\n",
    "for n in range(N):\n",
    "    h = ax.bar(n, ys[n], yerr=yerrs[n],\n",
    "           width=width, color=colors[n], ecolor='k')[0]\n",
    "    handles.append(h)\n",
    "    \n",
    "# Plot the zero line\n",
    "ax.plot([-0.5, n+0.5], np.zeros(2), '-k')\n",
    "\n",
    "# Set the labels\n",
    "ax.set_xticks([])\n",
    "ax.set_xlabel(\"muppets\")\n",
    "ax.set_ylabel(\"awesomeness\")\n",
    "\n",
    "plt.tight_layout(pad=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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2mmmV5mrixImsX78ef39/ZDIZNTU1TJ06lR07dmgqGtVf3PM0Pz8/Bg8eTFxcHN26datT\nVfhfMnDgQKKjozE2NqampoalS5eSlZVFVFQUcrmcsLAwIiIiWLVqFRUVFQQFBWFqakpoaCgAvr6+\nWFpakpqaiouLywtVtOqKugry6NGjTJo0iTVr1jB27Fiio6MZMWJEnbaDgwORkZE8evSIzz77TN/h\nY21trbnIUr9+FyxYoPlUc/v2bfr27avZ3s7Ojvj4+H9dBfyqiArBZyQnJ5OVlYVSqcTe3p5hw4ax\nceNGZDIZ5eXlLFu2jEOHDpGZmUlsbKy+wxUEoRkTFYKN4OnpWec7Ap5d8GvO88yCIDQPzWrOWRAE\n4XUhkrMgCEITJJKzIAhCEySSsyAIQhNU74JgbW0tAPfu3dNZMIIgCK8TdX5V59un1Zuci4uLAXFn\ngiAIwqtWXFxc597qeu9zrq6uJjMzEwsLC6RSqU4CFARBeJ3U1tZSXFxMr169MDEx0eqrNzkLgiAI\n+iMWBAVBEJogkZwFQRCaIJGcBUEQmiCRnAVBEJqg/wNFn5e4UD8kXgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x119acff98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Make a legend in a separate figure\n",
    "fig = plt.figure(figsize=(5, .6))\n",
    "ax = create_axis_at_location(fig, 0.1, 0.1, 4.8, .4)\n",
    "ax.legend(handles, names, ncol=5, handlelength=1, loc=\"center\")\n",
    "ax.set_xticks([])\n",
    "ax.set_yticks([])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [Root]",
   "language": "python",
   "name": "Python [Root]"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
	{
	"cells": [
	{
	"cell_type": "code",
	"execution_count": 1,
	"metadata": {
	"collapsed": true
	},
	"outputs": [],
	"source": [
	"import numpy as np\n",
	"import matplotlib.pyplot as plt\n",
	"%matplotlib inline\n",
	"\n",
	"from hips.plotting.colormaps import gradient_cmap\n",
	"from hips.plotting.layout import create_axis_at_location\n",
	"import seaborn as sns\n",
	"sns.set_style(\"white\")\n",
	"sns.set_context(\"paper\")\n",
	"color_names = [\"windows blue\",\n",
	" \"red\",\n",
	" \"amber\",\n",
	" \"faded green\",\n",
	" \"dusty purple\",\n",
	" \"orange\",\n",
	" \"clay\",\n",
	" \"pink\",\n",
	" \"greyish\",\n",
	" \"mint\",\n",
	" \"light cyan\",\n",
	" \"steel blue\",\n",
	" \"forest green\",\n",
	" \"pastel purple\",\n",
	" \"salmon\",\n",
	" \"dark brown\"]\n",
	"colors = sns.xkcd_palette(color_names)\n"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 2,
	"metadata": {},
	"outputs": [],
	"source": [
	"# make fake data\n",
	"N = 10\n",
	"names = [\n",
	" \"Kermit the Frog\",\n",
	" \"Miss Piggy\",\n",
	" \"Fozzie Bear\",\n",
	" \"Gonzo\",\n",
	" \"Rowlf\",\n",
	" \"Scooter\",\n",
	" \"Pepe\",\n",
	" \"Rizzo\",\n",
	" \"Animal\",\n",
	" \"Walter\"]\n",
	"ys = np.random.gamma(1, 1, size=N)\n",
	"yerrs = np.random.gamma(1, 0.1, size=N)"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 3,
	"metadata": {},
	"outputs": [
	{
	"data": {
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	"text/plain": [
	"<matplotlib.figure.Figure at 0x119ae7c18>"
	]
	},
	"metadata": {},
	"output_type": "display_data"
	}
	],
	"source": [
	"# Make a bar chart with errorbars\n",
	"fig = plt.figure(figsize=(2,2))\n",
	"ax = fig.add_subplot(111)\n",
	"\n",
	"# Remove spines and stuff\n",
	"ax.spines['top'].set_visible(False)\n",
	"ax.spines['right'].set_visible(False)\n",
	"ax.get_xaxis().tick_bottom()\n",
	"ax.get_yaxis().tick_left()\n",
	"\n",
	"# Make bar plot, save handles\n",
	"width = 0.8\n",
	"handles = []\n",
	"for n in range(N):\n",
	" h = ax.bar(n, ys[n], yerr=yerrs[n],\n",
	" width=width, color=colors[n], ecolor='k')[0]\n",
	" handles.append(h)\n",
	" \n",
	"# Plot the zero line\n",
	"ax.plot([-0.5, n+0.5], np.zeros(2), '-k')\n",
	"\n",
	"# Set the labels\n",
	"ax.set_xticks([])\n",
	"ax.set_xlabel(\"muppets\")\n",
	"ax.set_ylabel(\"awesomeness\")\n",
	"\n",
	"plt.tight_layout(pad=0.1)"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 4,
	"metadata": {},
	"outputs": [
	{
	"data": {
	"text/plain": [
	"[]"
	]
	},
	"execution_count": 4,
	"metadata": {},
	"output_type": "execute_result"
	},
	{
	"data": {
	"image/png": 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2mmmV5mrixImsX78ef39/ZDIZNTU1TJ06lR07dmgqGtVf3PM0Pz8/Bg8eTFxcHN26datT\nVfhfMnDgQKKjozE2NqampoalS5eSlZVFVFQUcrmcsLAwIiIiWLVqFRUVFQQFBWFqakpoaCgAvr6+\nWFpakpqaiouLywtVtOqKugry6NGjTJo0iTVr1jB27Fiio6MZMWJEnbaDgwORkZE8evSIzz77TN/h\nY21trbnIUr9+FyxYoPlUc/v2bfr27avZ3s7Ojvj4+H9dBfyqiArBZyQnJ5OVlYVSqcTe3p5hw4ax\nceNGZDIZ5eXlLFu2jEOHDpGZmUlsbKy+wxUEoRkTFYKN4OnpWec7Ap5d8GvO88yCIDQPzWrOWRAE\n4XUhkrMgCEITJJKzIAhCEySSsyAIQhNU74JgbW0tAPfu3dNZMIIgCK8TdX5V59un1Zuci4uLAXFn\ngiAIwqtWXFxc597qeu9zrq6uJjMzEwsLC6RSqU4CFARBeJ3U1tZSXFxMr169MDEx0eqrNzkLgiAI\n+iMWBAVBEJogkZwFQRCaIJGcBUEQmiCRnAVBEJqg/wNFn5e4UD8kXgAAAABJRU5ErkJggg==\n",
	"text/plain": [
	"<matplotlib.figure.Figure at 0x119acff98>"
	]
	},
	"metadata": {},
	"output_type": "display_data"
	}
	],
	"source": [
	"# Make a legend in a separate figure\n",
	"fig = plt.figure(figsize=(5, .6))\n",
	"ax = create_axis_at_location(fig, 0.1, 0.1, 4.8, .4)\n",
	"ax.legend(handles, names, ncol=5, handlelength=1, loc=\"center\")\n",
	"ax.set_xticks([])\n",
	"ax.set_yticks([])"
	]
	}
	],
	"metadata": {
	"kernelspec": {
	"display_name": "Python [Root]",
	"language": "python",
	"name": "Python [Root]"
	},
	"language_info": {
	"codemirror_mode": {
	"name": "ipython",
	"version": 3
	},
	"file_extension": ".py",
	"mimetype": "text/x-python",
	"name": "python",
	"nbconvert_exporter": "python",
	"pygments_lexer": "ipython3",
	"version": "3.5.3"
	}
	},
	"nbformat": 4,
	"nbformat_minor": 2
	}