Merge branch 'dev'

README.md

@@ -44,8 +44,8 @@ _citation for `SWprepost`, please use the citation tool for that specific_
 _version on the `SWprepost` [archive](https://doi.org/10.5281/zenodo.3839998)._
 
 For the motivation behind the development of `SWprepost` and its role in a
-larger project focused on developing a complete workflow for surface wave
-inversion please refer to and consider citing the following:
+larger project focused on developing a complete and rigorous workflow for
+surface wave inversion please refer to and consider citing the following:
 
 > Vantassel, J.P., Cox, B.R., (2020). SWinvert: A workflow for performing
 > rigorous 1D surface wave inversions. Geophysical Journal International
@@ -95,7 +95,6 @@ plt.show()
 
 ```Python
 fig, ax = plt.subplots(figsize=(2,4), dpi=150)
-# Calculate Median
 disc_depth, siglnvs = gm_suite.sigma_ln()
 ax.plot(siglnvs, disc_depth, color="#00ff00")
 ax.set_xlim(0, 0.2)
@@ -128,17 +127,19 @@ last few lines of text displayed in the console.
 
 ### Using _SWprepost_
 
-1.  Download the contents of the [examples](https://github.com/jpvantassel/swprepost/tree/master/examples)
+1.  Download the contents of the
+  [examples](https://github.com/jpvantassel/swprepost/tree/master/examples)
   directory to any location of your choice.
 
-2.  Explore Jupyter notebooks in the
+2.  Explore the Jupyter notebooks in the
   [basic](https://github.com/jpvantassel/swprepost/tree/master/examples/basic)
   directory for a no-coding-required introduction to the `swprepost` package.
   If you have not installed `Jupyter`, detailed instructions can be found
   [here](https://jpvantassel.github.io/python3-course/#/intro/installing_jupyter).
 
 3.  Move to the [adv](https://github.com/jpvantassel/swprepost/tree/master/examples/adv)
   directory and follow the Jupyter notebook title `SWinvertWorkflow.ipynb` for
-  an example application of the SWinvert workflow.
+  an example application of `swprepost` to the SWinvert workflow
+  (Vantassel and Cox, 2020).
 
 4.  Enjoy!

examples/adv/SWinvertWorkflow.ipynb

@@ -31,7 +31,7 @@
     "[swprepost](https://github.com/jpvantassel/swprepost/) is a Python package for performing surface wave inversion pre- and post-processing (Vantassel, 2020).\n",
     "[swbatch](https://github.com/jpvantassel/swbatch) is an application on the [DesignSafe-CI](https://www.designsafe-ci.org/) (Vantassel et al., 2020) which allows user to perform batch-style surface wave inversions on the high performance cluster Stampede2 directly from Jupyter (recommended, code provided below) or through an easy to use web interface.\n",
     "This notebook is __an__ example of a workflow that can be built using the concepts from SWinvert and the tools `swprepost` and `swbatch`.\n",
-    "The SWinvert workflow, `swprepost`, `swbatch`, and this notebook were developed by Joseph P. Vantassel, under the supervision of Brady R. Cox at the University of Texas at Austin. If you use this notebook in your research we ask that you please cite the following:\n",
+    "The SWinvert workflow, `swprepost`, `swbatch`, and this notebook were developed by Joseph P. Vantassel, under the supervision of Brady R. Cox at The University of Texas at Austin. If you use this notebook in your research we ask that you please cite the following:\n",
     "\n",
     "> Vantassel, J.P., Cox, B.R., (2020). SWinvert: A workflow for performing rigorous 1D surface wave inversions. Geophys. J. Int. (Accepted) https://doi.org/10.1093/gji/ggaa426\n",
     "\n",
@@ -65,6 +65,24 @@
     "\\- Joe"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Import `swprepost`\n",
+    "\n",
+    "This will install `swprepost` if you have not done so already."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip install --user swprepost"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

examples/basic/ReadmeExamples.ipynb

@@ -122,7 +122,6 @@
    ],
    "source": [
     "fig, ax = plt.subplots(figsize=(2,4), dpi=150)\n",
-    "# Calculate Median\n",
     "disc_depth, siglnvs = gm_suite.sigma_ln()\n",
     "ax.plot(siglnvs, disc_depth, color=\"#00ff00\")\n",
     "ax.set_xlim(0, 0.2)\n",