update demo nb pandana plot to use cartopy and matplotlib directly

Author: sablanchard

demo/simple_example.ipynb

@@ -69,7 +69,7 @@
     "- Loading a network from disk\n",
     "- Visualizing the network\n",
     "- Adding average headways to network travel time\n",
-    "- Using a UrbanAccess network with Pandana"
+    "- Using an UrbanAccess network with Pandana"
    ]
   },
   {
@@ -82,6 +82,9 @@
     "matplotlib.use('agg')  # allows notebook to be tested in Travis\n",
     "\n",
     "import pandas as pd\n",
+    "import cartopy.crs as ccrs\n",
+    "import cartopy\n",
+    "import matplotlib.pyplot as plt\n",
     "import pandana as pdna\n",
     "import time\n",
     "\n",
@@ -95,20 +98,6 @@
     "%matplotlib inline"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "# Pandana currently uses depreciated parameters in matplotlib, this hides the warning until its fixed\n",
-    "import warnings\n",
-    "import matplotlib.cbook\n",
-    "warnings.filterwarnings(\"ignore\",category=matplotlib.cbook.mplDeprecation)"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -146,9 +135,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "settings.log_console = True"
@@ -166,9 +153,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "settings.log_console = False"
@@ -506,9 +491,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "urbanaccess_net = ua.network.ua_network"
@@ -1218,9 +1201,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "blocks_subset['node_id'] = transit_ped_net.get_node_ids(blocks_subset['x'], blocks_subset['y'])"
@@ -1250,9 +1231,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "transit_ped_net.set(blocks_subset.node_id, variable = blocks_subset.jobs, name='jobs')"
@@ -1320,23 +1299,31 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "scrolled": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "# s_time = time.time()\n",
-    "# transit_ped_net.plot(jobs_15, \n",
-    "#                     plot_type='scatter',\n",
-    "#                     fig_kwargs={'figsize':[20,20]},\n",
-    "#                     bmap_kwargs={'epsg':'26943','resolution':'h'},\n",
-    "#                     plot_kwargs={'cmap':'gist_heat_r','s':4,'edgecolor':'none'})\n",
-    "# print('Took {:,.2f} seconds'.format(time.time() - s_time))"
+    "s_time = time.time()\n",
+    "\n",
+    "fig = plt.subplots(figsize=(20,20))\n",
+    "\n",
+    "data_crs = ccrs.PlateCarree()\n",
+    "ax = plt.axes(projection=ccrs.epsg(26943))\n",
+    "ax.add_feature(cartopy.feature.GSHHSFeature(scale='full'), edgecolor='grey')\n",
+    "\n",
+    "plt.scatter(transit_ped_net.nodes_df.x, transit_ped_net.nodes_df.y, \n",
+    "            c=jobs_15, s=4, cmap='gist_heat_r', edgecolor='none', transform=data_crs)\n",
+    "cb = plt.colorbar()\n",
+    "\n",
+    "print('Took {:,.2f} seconds'.format(time.time() - s_time))"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
    "source": [
     "### Jobs accessible within 30 minutes"
    ]
@@ -1347,13 +1334,19 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# s_time = time.time()\n",
-    "# transit_ped_net.plot(jobs_30, \n",
-    "#                     plot_type='scatter',\n",
-    "#                     fig_kwargs={'figsize':[20,20]},\n",
-    "#                     bmap_kwargs={'epsg':'26943','resolution':'h'},\n",
-    "#                     plot_kwargs={'cmap':'gist_heat_r','s':4,'edgecolor':'none'})\n",
-    "# print('Took {:,.2f} seconds'.format(time.time() - s_time))"
+    "s_time = time.time()\n",
+    "\n",
+    "fig = plt.subplots(figsize=(20,20))\n",
+    "\n",
+    "data_crs = ccrs.PlateCarree()\n",
+    "ax = plt.axes(projection=ccrs.epsg(26943))\n",
+    "ax.add_feature(cartopy.feature.GSHHSFeature(scale='full'), edgecolor='grey')\n",
+    "\n",
+    "plt.scatter(transit_ped_net.nodes_df.x, transit_ped_net.nodes_df.y, \n",
+    "            c=jobs_30, s=4, cmap='gist_heat_r', edgecolor='none', transform=data_crs)\n",
+    "cb = plt.colorbar()\n",
+    "\n",
+    "print('Took {:,.2f} seconds'.format(time.time() - s_time))"
    ]
   },
   {
@@ -1369,50 +1362,20 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# s_time = time.time()\n",
-    "# transit_ped_net.plot(jobs_45, \n",
-    "#                     plot_type='scatter',\n",
-    "#                     fig_kwargs={'figsize':[20,20]},\n",
-    "#                     bmap_kwargs={'epsg':'26943','resolution':'h'},\n",
-    "#                     plot_kwargs={'cmap':'gist_heat_r','s':4,'edgecolor':'none'})\n",
-    "# print('Took {:,.2f} seconds'.format(time.time() - s_time))"
+    "s_time = time.time()\n",
+    "\n",
+    "fig = plt.subplots(figsize=(20,20))\n",
+    "\n",
+    "data_crs = ccrs.PlateCarree()\n",
+    "ax = plt.axes(projection=ccrs.epsg(26943))\n",
+    "ax.add_feature(cartopy.feature.GSHHSFeature(scale='full'), edgecolor='grey')\n",
+    "\n",
+    "plt.scatter(transit_ped_net.nodes_df.x, transit_ped_net.nodes_df.y, \n",
+    "            c=jobs_45, s=4, cmap='gist_heat_r', edgecolor='none', transform=data_crs)\n",
+    "cb = plt.colorbar()\n",
+    "\n",
+    "print('Took {:,.2f} seconds'.format(time.time() - s_time))"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -1436,4 +1399,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 1
-}
+}

requirements-dev.txt

@@ -4,6 +4,7 @@
 pytest
 pycodestyle
 jupyter
+cartopy
 
 # building documentation
 numpydoc