some intro

Author: JoschD

docs/guis/betabeat/beam_selection.md

@@ -1,13 +1,25 @@
-# The beam selection Window
+# The Beam Selection Window
+
+<figure>
+  <img src="../../assets/images/betabeat_gui/beam_selection.png" width="100%" />
+  <figcaption>The Beam Selection Window.</figcaption>
+</figure>
+
+The Beam Selection Window is your entry point to the GUI.
+Here, you set which machine you will be using and which `python` backend to run.
+The options chosen here will also define the **folder-structure** you will be using during your current analysis session.
 
 !!! tip "Setting Your Defaults"
     You can set all entries in this window to your preferred defaults for a quick start!
     Check the [Defaults Page](defaults.md) for more details.
 
-!!! todo
-    Include screenshot of Beam-Selection Window and describe the settings.
+## Beam
+
+## Output
 
-### Python
+## Input
+
+## Python Executable
 
 In the Beam-Selection Window you need to give it a python-binary (e.g. `venv/bin/python`).
 Best would be if you have a local virtual environment.
@@ -20,4 +32,3 @@ This is because python calls are now made by module, i.e.:
 ```bash
 python -m omc3.module arg1 arg2 ...
 ```
-

docs/guis/betabeat/defaults.md

@@ -38,17 +38,17 @@ consoleLogging=False   # activate additional logging  (visible if started from t
 checkFreeSpace=False   # check fee space at GUI start (visible if started from terminal)
 
 # BPM-Panel
-runOptics=False  # set the tickbox next to the `Analyse` button
+runOptics=False  # set the tickbox next to the `Run Analysis` button
 
 # Analysis-Panel
-autoclean.limit=0.1  # set the autoclean limit
-clean.sigmas=2       # set the number of sigmas for the autoclean
+autoclean.limit=0.1  # keep points within this limit, even if they are outliers
+clean.sigmas=2       # remove points beyond this many sigmas from the mean
 clean.bounds=0.7     # this ratio of points needs to remain otherwise cleaning aborts
 
 # Amplitude-Detuning-Window
 ampdet.tunecut=0.05  # limit around the given tune to exclude from the BBQ tune
 ampdet.window=100    # length of the moving average window for the BBQ tune
-ampdet.outlierLimit=0.0002  # Cut on outliears around the mean
+ampdet.outlierLimit=0.0002   # Cut on outliers around the mean
 ampdet.usePreviousBBQ=False  # Use previously extraced BBQ data if present
 ```