%% Data preprocessing Example
%  June 14, 2017
% 
% Import and standardize data for a single patient


%% PARAMETERS
% 1. data_dir: Directory containing folders (labeled as patient initials)
% 2. rhopls_dir: RHOPLS toolbox directory
% 3. patient: Patient initials, also name of folder containing patient
% data. Inside this directory are three files:
% '<patient_initials>_TFR_ao_LowFreq.m', '<patient_initials>_TFR_ao.mat',
% and '<patient_initials>_trial_labels.mat'
data_dir = '';
rhopls_dir = '';
patient = 'patient initials';


%% Set up required paths
% Install RHOPLS package
cd(rhopls_dir);
addpath(pwd);
savepath;
% Install required toolboxes
rhopls_setup();
% Check contents of patient directory
patient_dir = fullfile(data_dir, patient);


%% Load and process ECoG data
% Import design matrix for patient k
% Create the data matrix that we use for patient k
% Description of data loaded: This is a 3-dimensional tensor 
% Dimensions: (trials X label) - Fred's data
std_method = 'flatten_trials';
center = true;
scaled = true;
rm_outliers = true;
overwrite = true;
verbose = true;
[X, trial_labels, metadata] = load_patient_data(patient_dir, ... 
                        'standardizationMethod', std_method, ... 
                        'center', center, ...
                        'scaled', scaled, ...
                        'removeOutliers', rm_outliers, ...
                        'overwrite', overwrite, ...
                        'verbose', verbose);