Merge pull request #49 from wwieder/land-example

point to shared directory, no dask

README.md

@@ -62,3 +62,11 @@ $ cupid-build config.yml # Will build HTML from Jupyter Book
 After the last step is finished, you can use Jupyter to view generated notebooks in `${CUPID_ROOT}/examples/coupled-model/computed_notebooks/quick-run`
 or you can copy the entire `${CUPID_ROOT}/examples/coupled-model/computed_notebooks/quick-run/_build/html`
 directory to your local machine and look at `index.html` in a web browser.
+
+For users running on the NCAR super computers (derecho or casper), you can visualize the web page in a browser with the following steps:
+1. open a new browser window that points to https://fastx.ucar.edu:3300/session/
+1. open a default desktop icon
+1. select the browser client
+1. type `xterm` and hit enter to open a terminal
+1. In the terminal, run `cd ${CUPID_ROOT}/examples/coupled_model/computed_notebooks/quick-run/_build/html` to enter the `html` directory
+1. From the updated directory, run `firefox index.html &` to open a web browser pointed at the generated web page

examples/nblibrary/land_comparision.ipynb

@@ -20,11 +20,10 @@
    "metadata": {},
    "source": [
     "## Simple example comparing land variables from two simulations\n",
-    "- Created by [email protected]\n",
-    "- Jan 2024\n",
+    "Created by [email protected], Jan 2024\n",
     "\n",
     "- paths are harded coded for now\n",
-    "- quickly (and inaccurately) calcultes 20 year mean from raw, .h0., files \n",
+    "- quickly (and inaccurately) calculates 5 year mean from raw, .h0., files.\n",
     "- plots global means and differences which  also not very nice to look at, especially since this points to a 4x5 grid."
    ]
   },
@@ -64,55 +63,6 @@
     "%matplotlib inline"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e0d67916-85c5-4590-b03f-c00753e88df4",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Updated for PBS scheduler\n",
-    "# this could go into utils.\n",
-    "# By default gets 1 core w/ 25 GB memory\n",
-    "def get_ClusterClient(ncores=1, nmem='25GB'):\n",
-    "    import dask\n",
-    "    from dask_jobqueue import PBSCluster\n",
-    "    from dask.distributed import Client\n",
-    "    ncores=ncores\n",
-    "    nmem = nmem\n",
-    "\n",
-    "    cluster = PBSCluster(\n",
-    "        cores=ncores, # The number of cores you want\n",
-    "        memory=nmem, # Amount of memory\n",
-    "        processes=ncores, # How many processes\n",
-    "        queue='casper', # The type of queue to utilize (/glade/u/apps/dav/opt/usr/bin/execcasper)\n",
-    "        resource_spec='select=1:ncpus='+str(ncores)+':mem='+nmem, # Specify resources\n",
-    "        project='P93300641', # Input your project ID here\n",
-    "        walltime='2:00:00', # Amount of wall time\n",
-    "        interface='ext', # Interface to use  'lo' provided a cluster window, below.\n",
-    "    )\n",
-    "\n",
-    "    dask.config.set({\n",
-    "        'distributed.dashboard.link':\n",
-    "        'https://jupyterhub.hpc.ucar.edu/stable/user/{USER}/proxy/{port}/status'\n",
-    "    })\n",
-    "\n",
-    "    client = Client(cluster)\n",
-    "    return cluster, client"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "590d68d1-7bf3-4164-911c-c6593d010246",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "cluster, client = get_ClusterClient(nmem='1GB')\n",
-    "cluster.scale(10) \n",
-    "cluster"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -123,8 +73,8 @@
     "# -- read only these variables from the whole netcdf files\n",
     "# average over time\n",
     "def preprocess (ds):\n",
-    "    variables = ['GPP', 'TOTECOSYSC', 'TOTVEGC','ELAI','TOTSOMC',\n",
-    "                 'SOM_PAS_C_vr','SOM_SLO_C_vr','ALT']\n",
+    "    variables = ['TOTECOSYSC', 'TOTVEGC','TOTSOMC',\n",
+    "                 'SOM_PAS_C_vr']\n",
     "\n",
     "    ds_new= ds[variables]\n",
     "    return ds_new\n",
@@ -154,10 +104,11 @@
     "for c in range(len(cases)):\n",
     "\n",
     "    sim_files =[]\n",
-    "    sim_path = \"/glade/derecho/scratch/slevis/archive/\"+cases[c]+\"/lnd/hist/\"\n",
+    "    sim_path = \"/glade/campaign/cesm/development/cross-wg/diagnostic_framework/CESM_output_for_testing/\"\n",
+    "    sim_path = sim_path+cases[c]+\"/lnd/hist/\"\n",
     "    sim_files.extend(sorted(glob(join(sim_path+cases[c]+\".clm2.h0.*.nc\"))))\n",
-    "    # subset last 20 years of data \n",
-    "    sim_files = sim_files[-240:None]\n",
+    "    # subset last 5 years of data \n",
+    "    sim_files = sim_files[-60:None]\n",
     "    print(\"All simulation files for \"+cases[c]+\": [\", len(sim_files), \"files]\")\n",
     "\n",
     "    temp = xr.open_mfdataset(sim_files, decode_times=True, combine='by_coords',\n",
@@ -261,22 +212,6 @@
     "plt.ylabel(None)\n",
     "#plt.ylim(6,0)"
    ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "b3f729af-05b4-4540-b4b5-567cc1cbe8f2",
-   "metadata": {},
-   "source": [
-    "### Big blob of passive C with depth in pAD"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c10babf2-4530-4ca9-b304-4db7fb6a965d",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {