@@ -96,6 +96,7 @@ Component classification can only be done on files that have successfully run th
* Heartbeat
* Muscle
* 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.
@@ -105,8 +106,20 @@ 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
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.
We are currently working on this section of the Wiki.
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Sample matrix representation of the calculate->flag->mark path for a channel mark.