Merge branch 'main' of https://github.com/LMBooth/pybci

docs/source/BackgroundInformation/Epoch_Timing.rst

@@ -16,7 +16,7 @@ Setting the :py:data:`globalEpochSettings` with the :class:`GlobalEpochSettings(
 Setting Custom Epoch Times
 --------------------------
 
-The figure below illustrates when you may have epochs of differing lengths received on the LSL marker stream. A baseline marker may signify an extended period, in this case 10 seconds, and our motor task is only 1 second long. To account for this set :py:data:`customEpochSettings` and :py:data:`globalEpochSettings` accordingly:
+The figure below illustrates when you may have epochs of differing lengths received on the LSL marker stream. A baseline marker may signify an extended period, in this case 10 seconds, and our motor task is only 1 second long. To account for this set :py:data:`customEpochSettings` and :py:data:`globalEpochSettings` accordingly, note the LSL Marker for baseline should match the key for the :py:data:`customEpochSettings` dict:
 
 .. code-block:: python
 
@@ -26,10 +26,11 @@ The figure below illustrates when you may have epochs of differing lengths recei
    gs.splitCheck = False # splits samples between tmin and tmax
    gs.windowLength = 1 # window length of 1 s
    gs.windowOverlap = 0.5 # windows overap by 50%, so for a total len
-   baselineSettings = IndividualEpochSetting()
-   baselineSettings.splitCheck = False
-   baselineSettings.tmin = 0      # time in seconds to capture samples before trigger
-   baselineSettings.tmax=  10      # time in seconds to capture samples after trigger
+   baselineSettings = {}
+   baselineSettings["baseline"] = IndividualEpochSetting()
+   baselineSettings["baseline"].splitCheck = False
+   baselineSettings["baseline"].tmin = 0      # time in seconds to capture samples before trigger
+   baselineSettings["baseline"].tmax=  10      # time in seconds to capture samples after trigger
    bci = PyBCI(customEpochSettings=baselineSettings, globalEpochSettings=gs)
 
 Highlighting these epochs on some psuedo emg data looks like the following: