More details here:
https://git-scm.com/book/en/v2/Git-Tools-Submodules
I add 2 dummy repo I created on my account as submodules
"""Script to get all files touched by PRs.""" | |
import shutil | |
from pathlib import Path | |
from warnings import warn | |
import requests | |
from rich import print |
X = [ normrnd(0,1,10,3) normrnd(0,.1,10,1) ]; % generate data | |
D = pdist(X, 'euclidean'); % compute euclidiant distance | |
% do multidimensional scaling | |
% find a configuration with those inter-point distances | |
% If the first k elements of E are much larger than the remaining (n-k), then you | |
% can use the first k columns of Y as k-dimensional points, whose interpoint | |
% distances approximate D. This can provide a useful dimension reduction for | |
% visualization, e.g., for k==2. |
% extracts confounds of interest from fmriprep timeseries.tsv | |
% and saves them for easier ingestion by SPM model specification | |
% | |
% the output should have a BIDS like structure too a bit like this | |
% | |
% spm12 | |
% ├── CHANGES | |
% ├── dataset_description.json | |
% ├── README | |
% └── sub-01 |
name: update submodules | |
# requires sudmodules URL to be "https..." (no ssh) | |
# | |
# requires submodule to be specified to follow a specific branch (stored in .gitmodules) | |
# | |
# clone them with: | |
# | |
# git submodule add -b branch_to_follow https://github.com/... submodule_path | |
# |
function [audio_config] = triggerSend(action, device, audio_config) | |
% a wrapper function to interact with psychport audio in case you are using a Fireface UC Mac / RME_RCAtrig | |
% external sound card. | |
% | |
% usage: | |
% [audio_config] = triggerSend('open', device, audio_config) | |
% Will open PsychPortAudio and return audio_config with the relevant | |
% field that are needed later (pahandle, dev_n_channels, devID). Will also set volume of trigger | |
% channel when using the external sound card. | |
% |
% small script to show how stat significance filters results and leads to | |
% overestimation of effect size if only positive findings are considered | |
clear; | |
clc; | |
STD = 1; % Standard deviation of the effect (true std of the population we are modelling) | |
UES = 0.1:.1:1; % Unstandardized Effect size (true mean of the population we are modelling) | |
SES = UES/STD; % Standardized effect size (for info) |
% small script to show some basic way to render volume data on surfaces using SPM | |
clear | |
close all | |
clc | |
% which surface to use | |
% uses one of the default SPM surfaces but it should be doable to create you own | |
% from the results of a segmentation or from some freesurfer output to have | |
% a better group template |
% small matlab script to show how p-hacking "increases power" : | |
% number of false negatives drops as more studies are "p-hacked" | |
% from Iaonnidis 2005; table 2 ; DOI: 10.1371/journal.pmed.0020124 | |
R = 0.1; % pre-study odds | |
u = 0:.02:1; % bias : proportion of study that should have given a | |
% negative but turn out positive (QRPs or other errors). | |
c = 100; %number of relationship tested | |
alpha = 0.05; | |
beta = 0.5; |
% script that prints the results of an SPM contrats (obtained via the GUI on SPM) | |
% to a csv file | |
%% Print a csv files of the results | |
Results_file = 'result.csv'; | |
fid = fopen (Results_file, 'w'); | |
fprintf (fid, '%s', xSPM.title); | |
fprintf (fid, '\n\n'); |