plot_proj

plot_proj

It plots the projections of the data (i.e., latent variables).

Syntax

  plot_proj(res, mod, level, sidvar, split, colour, func, varargin)

Inputs

res [struct]

res structure containing information about results and plot specifications
mod [cell array]

modality of data to be used for plotting (i.e., {'X', 'Y'})
level [int or numeric array]

level of associative effect with same dimensionality as mod or automatically extended (e.g., from int to numeric array)
sidvar ['osplit', 'otrid', 'oteid', 'isplit', 'itrid', 'iteid']

specifies subjects to be used for plotting

first letter can be 'o' for outer or 'i' for inner split, followed by either 'trid' for training, 'teid' for test or 'split' for both training and test data
split [int or numeric array]

index of data split to be used with same dimensionality as mod or automatically extended (e.g., from int to numeric array)
colour ['none', char]

'none' for scatterplot with same colour for all subjects or it can be used as a continuous colormap or for colouring different groups; there are three ways to define the colour

specify a variable, which can be loaded from a data file (e.g., Y.mat) using the name of the variable defined in a label file (e.g., LabelsY.csv)

use 'training+test' to colour-code the training and test sets

use any other string with a '+' sign (e.g., 'MDD+HC') to define the colour-code based on group.mat
func ['2d', '2d_group', '2d_cmap']

name of the specific plotting function (after plot_proj_* prefix) to be called
varargin [name-value pairs]

additional options can be passed via name-value pairs with dot notation supported

Examples

Simple plots

Most often, we plot a brain latent variable vs. a behavioural latent variable for a specific level (i.e., associative effect).

   % Plot data projections coloured by groups
   plot_proj(res, {'X' 'Y'}, res.frwork.level, 'osplit', res.frwork.split.best, ...
   'training+test', '2d_group', 'gen.axes.FontSize', 20, ...
   'gen.legend.FontSize', 20, 'gen.legend.Location', 'NorthWest', ... 
   'proj.scatter.SizeData', 120, 'proj.scatter.MarkerEdgeColor', 'k', ...
   'proj.scatter.MarkerFaceColor', [0.3 0.3 0.9; 0.9 0.3 0.3]);

projection_plot

Multi-level plots

To plot projections aggregated over multiple levels, all you need to specify is res.proj.multi_level = 1 and provide a 2D cell array of input variable 'mod'. Input variables 'level' and 'split' should have the same dimensionality or they will be extended automatically from 1-D or 2-D arrays (e.g. level = repmat(level, size(mod))).

   % Plot data projections across levels (and averaged across modalities 
   % in a level after standardization)
   plot_proj(res, {'X' 'Y'; 'X' 'Y'}, [1 1; 2 2], 'osplit', res.frwork.split.best, ...
             'none', '2d', 'proj.multi_label', 1);