diff --git a/README.md b/README.md
index 1a48c59..1b2c713 100644
--- a/README.md
+++ b/README.md
@@ -3,14 +3,6 @@
 AI categorization of spectra from LIBS/XRF analyzers.
 
 
-# Status
-Alpha software under development.
-Need to check:
-
-* *API: 501 Not Implemented*
- https://spacecruft.org/spacecruft/pysalx/issues/2
-
-
 # Install
 ## Install Dependencies
 Get system dependency and upgrade Python pip.
@@ -35,7 +27,6 @@ cd pysalx/
 ..
 ```
 
-
 ## Clone Git Repo
 Get source code with `git`.
 
@@ -43,21 +34,23 @@ The default `requirements.txt` installs a Tensorflow without
 GPU support. You can edit the `requirements.txt` file to change
 which is supported. The "generic" version supports both.
 
-
 ```
 git clone https://spacecruft.org/spacecruft/witzit
 cd witzit/
 pip install --user --upgrade -r requirements.txt
 ```
 
+
 # witzit scripts
 
-* `witzit-load.py` --- Load and text display an example MCA.
+* `witzit-load-x555` --- Load and text display data from SciAps X-555 XRF.
+* `witzit-load-vanta` --- Load and text display data from Olympus Vanta XRF.
 
 Development is most easily done under Jupyter with Tensorboard
 for training models. These files are in the `notebooks/` directory.
 
-* `witzit-plot.ipynb` --- witzit Jupyter notebook, plotting application.
+* `witzit-plot-x555.ipynb` --- witzit Jupyter notebook, plotting application for SciAps X-555 XRF.
+* `witzit-plot-vanta.ipynb` --- witzit Jupyter notebook, plotting application for Olympus Vanta XRF.
 * `witzit-predict.ipynb` --- witzit Jupyter notebook, prediction application.
 * `witzit-train.ipynb` --- witzit Jupyter notebook, training application.
 
@@ -95,7 +88,7 @@ HOWTO USE. Getting closer...
 
 ```
 # Example:
-debian@workstation:~/spacecruft/witzit$ ./witzit-load.py
+debian@workstation:~/spacecruft/witzit$ ./witzit-load-x555
        energy (eV)   2048
 0        20.590676      0
 1        45.021816      0
@@ -111,9 +104,12 @@ debian@workstation:~/spacecruft/witzit$ ./witzit-load.py
 ```
 
 ## Jupyter Notebooks
-Example plot:
+Example plot from SciAps X-555 XRF:
 
-![xrf-spectrum](notebooks/xrf-spectrum.png)
+![xrf-spectrum-sciaps](notebooks/xrf-spectrum.png)
+
+Example plot from Olympus Vanta XRF:
+![xrf-spectrum-vanta](notebooks/xrf-spectrum-vanta.png)
 
 
 Run jupyter thusly:
@@ -129,6 +125,8 @@ jupyter-lab
 
 * SciAps XRF Analyzer
 
+* Olympus XRF Analyzer
+
 
 # Deep Learning Algorithm
 Can use lots from `wut`.
@@ -187,15 +185,6 @@ same as in `wut`, so makes a good reference.
 *Feature selection of infrared spectra analysis with convolutional neural network*
 
 
-# Misc
-
-Will likely work best with binary categorizations. E.g. like this:
-Is it element A or not element A?
-Is it element B or not element B?
-Is it element C or not element C?
-Not "is it element A, B, or C?" 
-
-
 # See Also
 
 * `pysalx` --- Unofficial scripts for interacting with the SciAps LIBS
@@ -208,6 +197,14 @@ https://spacecruft.org/spacecruft/pysalx/
 https://spacecruft.org/spacecruft/satnogs-wut/
 
 
+# Status
+Alpha software under development.
+Need to check:
+
+* *API: 501 Not Implemented*
+ https://spacecruft.org/spacecruft/pysalx/issues/2
+
+
 # Unofficial
 Unofficial, unaffiliated with SciAps.
 
diff --git a/notebooks/witzit-plot-vanta.ipynb b/notebooks/witzit-plot-vanta.ipynb
index d1002ea..31ac54a 100644
--- a/notebooks/witzit-plot-vanta.ipynb
+++ b/notebooks/witzit-plot-vanta.ipynb
@@ -61,7 +61,11 @@
    "outputs": [],
    "source": [
     "df = pd.read_csv('examples/olympus-vanta.csv', header = 0,\n",
-    "                 skiprows=[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40], usecols = [0, 1])"
+    "                 skiprows=40,\n",
+    "                 names=('eV', 'Counts'),\n",
+    "                 usecols = [0, 1])\n",
+    "\n",
+    "df['eV'] = df['eV'] * 1000"
    ]
   },
   {
@@ -82,14 +86,14 @@
     "sns.set_theme()\n",
     "plt.figure(facecolor='xkcd:off white', figsize=(15, 8))\n",
     "# XXX y=\n",
-    "g=sns.lineplot(x=\"Date\", y=\"2022-04-08\", data=df, linestyle='-', linewidth=1, color='xkcd:pale orange')\n",
+    "g=sns.lineplot(x=\"eV\", y=\"Counts\", data=df, linestyle='-', linewidth=1, color='xkcd:pale orange')\n",
     "g.set_title('XRF Spectrum'.format('seaborn'), color='xkcd:cornflower blue', fontsize='large', fontweight='bold')\n",
-    "g.set_xlabel('energy (keV)', color='xkcd:goldenrod', fontsize='large', fontweight='bold')\n",
+    "g.set_xlabel('energy (eV)', color='xkcd:goldenrod', fontsize='large', fontweight='bold')\n",
     "g.set_ylabel('Counts', color='xkcd:cerulean', fontsize='large', fontweight='bold')\n",
     "g.patch.set_alpha(1.0)\n",
     "g.set_facecolor('xkcd:powder blue')\n",
     "plt.tight_layout()\n",
-    "plt.savefig(\"xrf-spectrum.png\", dpi=72, transparent=False, facecolor='xkcd:off white', edgecolor=g.get_facecolor())\n",
+    "plt.savefig(\"xrf-spectrum-vanta.png\", dpi=72, transparent=False, facecolor='xkcd:off white', edgecolor=g.get_facecolor())\n",
     "plt.show()\n",
     "plt.close()"
    ]
diff --git a/notebooks/xrf-spectrum-vanta.png b/notebooks/xrf-spectrum-vanta.png
new file mode 100644
index 0000000..8cc49da
Binary files /dev/null and b/notebooks/xrf-spectrum-vanta.png differ