@@ -95,7 +95,8 @@ Component classification can only be done on files that have successfully run th
* Lateral Eye Movement
* Heartbeat
* Muscle
* Mixed Signal
* Mixed Signal
These percentages sum to 100% and the category with the highest % is selected as the guessed type. This information is useful in getting a general overview of what type of components can be found in your data, even if you don not completely trust its choices.
@@ -104,18 +105,27 @@ The pie graph in diagnostics shows the fraction of components that were placed i
These figures can give you a quick idea on how well you are isolating components. Ideally you are looking for components that have have a high % in one category, indicating a clear isolation.
#Creating your own plotting functions
# Creating your own plotting functions
In order to create your own diagnostics tool you should make sure you are familiar with:
* The above content
*[Marks](https://git.sharcnet.ca/bucanl_eeglab_extensions/vised_marks/wikis/home) structure and creating by script.
This section will use these concepts along with [plotting in matlab](https://www.mathworks.com/help/matlab/creating_plots/types-of-matlab-plots.html) and the EEG. structure.
Sample matrix representation of the calculate->flag->mark path for a channel mark.