Fix typo in HPC setup (#326)

* Fix typo in HPC setup

* Fix port

* Fixed it the wrong way around in the previous commit

* use default ports for examples

docs/setup_guides/hpc.rst

@@ -122,7 +122,7 @@ in the Jupyter documentation.
 From here, we have two options. Option 1 will start a Jupyter Notebook server
 and manage dask using the `dask-jobqueue`_ package. Option 2 will start a dask
 cluster using `dask-mpi` and will run a Jupyter server as part of the dask cluster.
-We generally recommend starting with Option 1, espcially if you will be working
+We generally recommend starting with Option 1, especially if you will be working
 interactively, unless you have a reason for managing the job submission scripts
 on your own. Users that will be using dask in batch-style workflows may prefer
 Option 2.
@@ -163,32 +163,32 @@ later.
 
 ::
 
-    (pangeo) $ echo "ssh -N -L 8877:`hostname`:8877 -L 8878:`hostname`:8878 $USER@cheyenne.ucar.edu"
-    ssh -N -L 8877:r8i4n0:8877 -L 8878:r8i4n0:8878 username@cheyenne.ucar.edu
+    (pangeo) $ echo "ssh -N -L 8888:`hostname`:8888 -L 8787:`hostname`:8787 $USER@cheyenne.ucar.edu"
+    ssh -N -L 8888:r8i4n0:8888 -L 8787:r8i4n0:8787 username@cheyenne.ucar.edu
 
 Now we can launch the notebook server:
 
 ::
 
-    (pangeo) $ jupyter lab --no-browser --ip=`hostname` --port=8877
+    (pangeo) $ jupyter lab --no-browser --ip=`hostname` --port=8888
     ...
     [I 13:36:52.321 LabApp] The Jupyter Notebook is running at:
-    [I 13:36:52.321 LabApp] http://r8i4n0:8877/
+    [I 13:36:52.321 LabApp] http://r8i4n0:8888/
     [I 13:36:52.321 LabApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
 
 Now, connect to the server using an ssh tunnel from your local machine
 (this could be your laptop or desktop).
 
 ::
 
-    $ ssh -N -L 8877:r8i4n0:8877 -L 8878:r8i4n0:8787 username@cheyenne.ucar.edu
+    $ ssh -N -L 8888:r8i4n0:8888 -L 8787:r8i4n0:8787 username@cheyenne.ucar.edu
 
 You'll want to change the details in the command above but the basic idea is
-that we're passing the ports 8877 and 8878 from the compute node `r8i4n0` to our
-local system. Now open http://localhost:8877 on your local machine, you should
+that we're passing the ports 8888 and 8787 from the compute node `r8i4n0` to our
+local system. Now open http://localhost:8888 on your local machine, you should
 find a jupyter server running!
 
-*Note that we're also passing the 8878 port through so we can access the dask
+*Note that we're also passing the 8787 port through so we can access the dask
 dashboard later.*
 
 
@@ -246,10 +246,10 @@ cluster. MPI is **NOT** used for communication by dask.
    .. code:: bash
 
        Run the following command from your local machine:
-       ssh -N -L 8877:r7i3n13:8877 -L 8878:r7i3n13:8787 username@cheyenne.ucar.edu
+       ssh -N -L 8888:r7i3n13:8888 -L 8787:r7i3n13:8787 username@cheyenne.ucar.edu
        Then open the following URLs:
-           Jupyter lab: http://localhost:8877
-           Dask dashboard: http://localhost:8878
+           Jupyter lab: http://localhost:8888
+           Dask dashboard: http://localhost:8787
 
    It may be ncessessary to modify the included scripts to use different PBS
    project number, conda environment, or notebook directory.
@@ -350,7 +350,7 @@ From your same session on the login node, run the following code:
 
     client.run_on_scheduler(start_jlab)
 
-    print("ssh -N -L 8787:%s:8787 -L 8888:%s:8888 cheyenne.ucar.edu" % (host, host))
+    print("ssh -N -L 8888:%s:8888  -L 8787:%s:8787 cheyenne.ucar.edu" % (host, host))
 
 This should print out a statement like the following: