pierre-haessig/Marker disappear bug.ipynb

## Marker disappear bug.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Matplotlib markers disappear bug\n",
    "\n",
    "\n",
    "when using `seaborn-notebook` style\n",
    "\n",
    "\n",
    "PH May 2016"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1.5.1'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mpl.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mpl.style.use(['seaborn-deep', 'seaborn-whitegrid'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{u'lines.antialiased': True,\n",
       " u'lines.color': u'b',\n",
       " u'lines.dash_capstyle': u'butt',\n",
       " u'lines.dash_joinstyle': u'round',\n",
       " u'lines.linestyle': u'-',\n",
       " u'lines.linewidth': 1.0,\n",
       " u'lines.marker': u'None',\n",
       " u'lines.markeredgewidth': 0.5,\n",
       " u'lines.markersize': 6.0,\n",
       " u'lines.solid_capstyle': u'round',\n",
       " u'lines.solid_joinstyle': u'round'}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "{k:mpl.rcParams[k] for k in mpl.rcParams \n",
    " if k.startswith('lines') }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mpl.rcParams['lines.markeredgewidth']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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qWrm963749CWjxzGEfdf6Ku5aHxbVSxYOHTqEPXv2oLCwsM/t6enpWLBgAYKCgpCWloaD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\nYbATEXkYBjsRkYdhsBMReZj/B8m17ScKwzMaAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f4f4ca1e5d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = [1,2,3,2,4]\n",
    "plt.plot(x, '+-');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mpl.style.use(['seaborn-notebook'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{u'lines.antialiased': True,\n",
       " u'lines.color': u'b',\n",
       " u'lines.dash_capstyle': u'butt',\n",
       " u'lines.dash_joinstyle': u'round',\n",
       " u'lines.linestyle': u'-',\n",
       " u'lines.linewidth': 1.75,\n",
       " u'lines.marker': u'None',\n",
       " u'lines.markeredgewidth': 0.0,\n",
       " u'lines.markersize': 7.0,\n",
       " u'lines.solid_capstyle': u'round',\n",
       " u'lines.solid_joinstyle': u'round'}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "{k:mpl.rcParams[k] for k in mpl.rcParams \n",
    " if k.startswith('lines') }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mpl.rcParams['lines.markeredgewidth']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Oq5EGRT2SnqHFQAMREs50p9VIg0L6Nuk5nqRnSDDQQJhFMt1pNdKg3nV+0nMiSc+QYKCB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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f4f4c4568d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = [1,2,3,2,4]\n",
    "plt.plot(x, '+-');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "in the code: [seaborn-notebook.mplstyle](https://github.com/matplotlib/matplotlib/blob/v1.5.1/lib/matplotlib/mpl-data/stylelib/seaborn-notebook.mplstyle#L13) v1.5.1\n",
    "\n",
    "> l13: `lines.markeredgewidth: 0`"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}