Change 'source' to 'conda' and add blurb for job scripts.

content/Applications/Using_Your_Own_Software/using_anaconda_package_manager.md

@@ -89,7 +89,7 @@ If the package is available, this will also display available package
 versions and compatible Python versions the package may be installed
 under.
 
-### Creating Custom Anaconda Environment
+### Creating Custom Anaconda Environments
 
 The `create` command is used to create a new environment.  It requires
 at a minimum a name for the environment, and at least one package to
@@ -113,14 +113,25 @@ To use the environment, we must first *activate* it.
 
 {{% panel theme="info" header="Activate environment" %}}
 {{< highlight bash >}}
-source activate mynumpy
+conda activate mynumpy
 {{< /highlight >}}
 {{% /panel %}}
 
 Our new environment is now active, and we can use it.  The shell prompt
 will change to indicate this as well (this can be disable if desired).
 
-### Creating Custom GPU Anaconda Environment
+To use your environment in a job, add the lines
+
+{{% panel theme="info" header="Use your environment in a SLURM job" %}}
+{{< highlight bash >}}
+module load anaconda
+conda activate mynumpy
+{{< /highlight >}}
+{{% /panel %}}
+
+to the beginning of your submit script (replacing `mynumpy` with your environment's name).
+
+### Creating Custom GPU Anaconda Environments
 
 We provide GPU versions of various frameworks such as `tensorflow`, `keras`, `theano`, via [modules](../module_commands). However, sometimes you may need additional libraries or packages that are not available as part of these modules. In this case, you will need to create your own GPU Anaconda environment.
 
@@ -142,7 +153,7 @@ This will create a new `tensorflow-gpu-1.12-custom` environment in your home dir
 {{% panel theme="info" header="Install new packages in the currently active environment" %}}
 {{< highlight bash >}}
 module load anaconda
-source activate tensorflow-gpu-1.12-custom
+conda activate tensorflow-gpu-1.12-custom
 conda install <packages>
 {{< /highlight >}}
 {{% /panel %}}
@@ -150,11 +161,11 @@ conda install <packages>
 Next, whenever you want to use this custom GPU Anaconda environment, you need to add these two lines in your submit script:
 {{< highlight bash >}}
 module load anaconda
-source activate tensorflow-gpu-1.12-custom
+conda activate tensorflow-gpu-1.12-custom
 {{< /highlight >}}
 
 {{% notice info %}}
-If you have custom GPU Anaconda environment please only use the two lines from above and **DO NOT** load the module you have cloned earlier. Using `module load tensorflow-gpu/py36/1.12` and `source activate tensorflow-gpu-1.12-custom` in the same script is **wrong** and may give you various errors and incorrect results.
+If you have custom GPU Anaconda environment please only use the two lines from above and **DO NOT** load the module you have cloned earlier. Using `module load tensorflow-gpu/py36/1.12` and `conda activate tensorflow-gpu-1.12-custom` in the same script is **wrong** and may give you various errors and incorrect results.
 {{% /notice %}}
 
 
@@ -236,7 +247,7 @@ Jupyter Notebook. To do so, follow the steps below, replacing
           
 2.  Using the command-line environment, load the target conda
     environment:
-    {{< highlight bash >}}source activate myenv{{< /highlight >}}
+    {{< highlight bash >}}conda activate myenv{{< /highlight >}}
 
 3.  Install the Jupyter kernel and add the environment: