xarray interactive plot

interactive_plot.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import cartopy.crs as ccrs\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "\n",
    "from ipywidgets import interact, IntSlider"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (lat: 25, lon: 53, time: 2920)\n",
       "Coordinates:\n",
       "  * lat      (lat) float32 75.0 72.5 70.0 67.5 65.0 62.5 60.0 57.5 55.0 52.5 ...\n",
       "  * lon      (lon) float32 200.0 202.5 205.0 207.5 210.0 212.5 215.0 217.5 ...\n",
       "  * time     (time) datetime64[ns] 2013-01-01 2013-01-01T06:00:00 ...\n",
       "Data variables:\n",
       "    air      (time, lat, lon) float32 241.2 242.5 243.5 244.0 244.1 243.89 ...\n",
       "Attributes:\n",
       "    Conventions:  COARDS\n",
       "    title:        4x daily NMC reanalysis (1948)\n",
       "    description:  Data is from NMC initialized reanalysis\\n(4x/day).  These a...\n",
       "    platform:     Model\n",
       "    references:   http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanaly..."
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = xr.tutorial.load_dataset('air_temperature')\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "dr = ds['air']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "97cf2e60189f42cf9dbb84494cc1a8a5",
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      "text/plain": [
       "interactive(children=(IntSlider(value=0, description='itime', max=2919), Output()), _dom_classes=('widget-inte…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "@interact(t=IntSlider(min=0,max=2919,step=1,value=0, \n",
    "                      continuous_update=True,description='itime'))\n",
    "def plot_layer(t):\n",
    "    plt.figure(figsize=[8, 8])\n",
    "    ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "    dr[t].plot.pcolormesh(ax=ax, vmin=230, vmax=300, cbar_kwargs={'shrink': 0.4});\n",
    "    ax.coastlines();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "dr_sub = dr.sel(lon=slice(250,300), lat=slice(60, 30))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4bbafd155297487191fa9c49e7474c58",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(IntSlider(value=0, description='itime', max=2919), Output()), _dom_classes=('widget-inte…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "@interact(t=IntSlider(min=0,max=2919,step=1,value=0, \n",
    "                      continuous_update=True,description='itime'))\n",
    "def plot_subset(t):\n",
    "    plt.figure(figsize=[8, 8])\n",
    "    ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "    dr_sub[t].plot.pcolormesh(ax=ax, vmin=230, vmax=300, cbar_kwargs={'shrink': 0.5});\n",
    "    ax.coastlines();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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