Merge pull request #46 from cehbrecht/added-demo-notebooks

added demo notebooks

docs/source/_static/README.rst

@@ -0,0 +1,4 @@
+Readme
+======
+
+placeholder for _static folder.

docs/source/examples.rst

@@ -4,7 +4,7 @@
 Examples
 ########
 
-You can try this notebook examples online using Binder, or view the notebooks on NBViewer.
+You can try these notebook online using Binder, or view the notebooks on NBViewer.
 
 .. image:: https://mybinder.org/badge_logo.svg
    :target: https://mybinder.org/v2/gh/ESGF/esgf-pyclient.git/master?filepath=notebooks
@@ -16,9 +16,21 @@ You can try this notebook examples online using Binder, or view the notebooks on
    :alt: NBViewer
    :height: 20
 
+Basic Usage
+===========
+
 .. toctree::
    :maxdepth: 1
 
    notebooks/examples/search
    notebooks/examples/logon
    notebooks/examples/download
+
+Demo
+====
+
+.. toctree::
+   :maxdepth: 1
+
+   notebooks/demo/subset-cmip5
+   notebooks/demo/subset-cmip6

notebooks/demo/subset-cmip5.ipynb

@@ -0,0 +1,180 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Subset CMIP5 Datasets with xarray\n",
+    "\n",
+    "xarray: http://xarray.pydata.org/en/stable/index.html"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Search CMIP5 Dataset with ESGF pyclient\n",
+    "\n",
+    "using: https://esgf-pyclient.readthedocs.io/en/latest/index.html"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pyesgf.search import SearchConnection\n",
+    "conn = SearchConnection('https://esgf-data.dkrz.de/esg-search', distrib=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ctx = conn.new_context(\n",
+    "    project='CMIP5', \n",
+    "    experiment='rcp45',\n",
+    "    model='HadCM3',\n",
+    "    ensemble='r1i1p1',\n",
+    "    time_frequency='mon',\n",
+    "    realm='atmos',\n",
+    "    data_node='esgf-data1.ceda.ac.uk',\n",
+    "    )\n",
+    "ctx.hit_count"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "result = ctx.search()[0]\n",
+    "result.dataset_id"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "files = result.file_context().search()\n",
+    "for file in files:\n",
+    "    if 'tasmax' in file.opendap_url:\n",
+    "        tasmax_url = file.opendap_url\n",
+    "        print(tasmax_url)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## ESGF Logon"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pyesgf.logon import LogonManager\n",
+    "lm = LogonManager()\n",
+    "lm.logoff()\n",
+    "lm.is_logged_on()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lm.logon(hostname='esgf-data.dkrz.de', interactive=True, bootstrap=True)\n",
+    "lm.is_logged_on()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Subset single dataset with xarray\n",
+    "\n",
+    "Using OpenDAP: http://xarray.pydata.org/en/stable/io.html?highlight=opendap#opendap"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import xarray as xr\n",
+    "ds = xr.open_dataset(tasmax_url, chunks={'time': 120})\n",
+    "print(ds)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "da = ds['tasmax']\n",
+    "da = da.isel(time=slice(0, 1))\n",
+    "da = da.sel(lat=slice(-50, 50), lon=slice(0, 50))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "da.plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Download to NetCDF"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "da.to_netcdf('tasmax.nc')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}