3.5 KiB
3.5 KiB
How to Create a YAML Configuration File for Your Project
This guide provides step-by-step instructions on how to create a YAML file for configuring your ALE analysis. YAML (YAML Ain't Markup Language) is a human-readable format commonly used for configuration files.
Step 1: Open a Text Editor
You can use any text editor to create a YAML file. Popular options include:
- Visual Studio Code
- Notepad++
- Sublime Text
- nano or vim (for terminal users)
Step 2: Save the File with a .yaml or .yml Extension
When you create the file, save it with an appropriate name, such as config.yaml. Ensure the file extension is .yaml or .yml.
Step 3: Copy the YAML Template Below
Below is the YAML template for your project. Copy this content into your file:
# Project Folder
project:
analysis_info: "analysis_info.xlsx"
experiment_info: "experiment_info.xlsx"
# ALE Parameters
# DO NOT CHANGE THESE IF YOU ARE NOT AN ALE EXPERT!
parameters:
# If enabled pools multiple experiments from same paper into one experiment;
pool_experiments: False
# TFCE is a method for multiple comparison correction (Frahm et al., 2022)
tfce_enabled: True
# if enabled ALE map (and therefore all following maps) will be masked by ICBM 10% GM mask
gm_masking: True
# Size of bins used in MA histogram
# Default: 0.0001
bin_steps: 0.0001
# If enabled uses xgboost models to predict cutoffs instead of monte carlo simulation (Frahm et al., 2024)
cutoff_predict_enabled: True
# P-value required for significance
# !! ONLY IF CUTOFF PREDICT IS DISABLED, OTHERWISE WON'T HAVE EFFECT !!
# Default: 0.05
significance_threshold: 0.05
# Preliminary cluster forming threshold used in cluster-level family wise error correction
# !! ONLY IF CUTOFF PREDICT IS DISABLED, OTHERWISE WON'T HAVE EFFECT !!
# Default: 0.001
cluster_forming_threshold: 0.001
# Iterations used for monte-carlo based multiple comparison correction
# !! ONLY IF CUTOFF PREDICT IS DISABLED, OTHERWISE WON'T HAVE EFFECT !!
# Default: 5000
monte_carlo_iterations: 5000
# N subsamples calculated for probabilistic ALE algorithm
# Default: 2500
subsample_n: 2500
# Iterations used in classic contrast algorithm
# Default: 10000
contrast_permutations: 10000
# Correction Method on which to base contrast algorithm
# Default: "cFWE"; Options: "cFWE", "vFWE", "tfce"
contrast_correction_method: "cFWE"
# Sub-Iterations used in balanced contrast algorithm
# Default: 1000
difference_iterations: 1000
# Number of parallel processes used for many different steps in the ALE algorith - maximum depends on your machine
# Default: 2
nprocesses: 2
# DO NOT CHANGE THESE IF YOU ARE NOT AN ALE EXPERT
# MA_Clustering Parameters
# DO NOT CHANGE THESE IF YOU ARE NOT AN ALE EXPERT!
clustering_parameters:
max_clusters: 10 # Default: 10
subsample_fraction: 0.9 # Default: 0.9
sampling_iterations: 1000 # Default: 1000
null_iterations: 5000 # Default: 5000
correlation_type: "spearman" # Default: "spearman"; Options: "spearman", "pearson"
clustering_method: "hierarchical" # Default: "hierarchical"; Options: "hierarchical", "kmedoids"
linkage_method: "complete" # Default: "complete"; Options: "complete", "average"
use_pooled_std: False # Default: False
# DO NOT CHANGE THESE IF YOU ARE NOT AN ALE EXPERT
Step 4: Save the File
After pasting the content change the names of your experiment and analysis info file and save the file with the name config.yaml.