68 lines
No EOL
2.5 KiB
YAML
68 lines
No EOL
2.5 KiB
YAML
# Project Folder
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project:
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analysis_info: "analysis_info.xlsx"
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experiment_info: "clustering_dataset_6groups_300exps.xlsx"
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# ALE Parameters
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# DO NOT CHANGE THESE IF YOU ARE NOT AN ALE EXPERT!
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parameters:
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# If enabled pools multiple experiments from same paper into one experiment; Default: True
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pool_experiments: True
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# TFCE is a method for multiple comparison correction (Frahm et al., 2022)
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tfce_enabled: True
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# if enabled ALE map (and therefore all following maps) will be masked by ICBM 10% GM mask
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gm_masking: True
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# Size of bins used in MA histogram
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bin_steps: 0.0001 # Default: 0.0001
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# If enabled uses xgboost models to predict cutoffs instead of monte carlo simulation (Frahm et al., 2024)
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cutoff_predict_enabled: True
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# P-value required for significance
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# !! ONLY IF CUTOFF PREDICT IS DISABLED, OTHERWISE WON'T HAVE EFFECT !!
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significance_threshold: 0.05 # Default: 0.05
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# Preliminary cluster forming threshold used in cluster-level family wise error correction
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# !! ONLY IF CUTOFF PREDICT IS DISABLED, OTHERWISE WON'T HAVE EFFECT !!
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cluster_forming_threshold: 0.001 # Default: 0.001
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# Iterations used for monte-carlo based multiple comparison correction
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# !! ONLY IF CUTOFF PREDICT IS DISABLED, OTHERWISE WON'T HAVE EFFECT !!
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monte_carlo_iterations: 5000 # Default: 5000
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# N subsamples calculated for probabilistic ALE algorithm
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subsample_n: 2500 # Default: 2500
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# Iterations used in classic contrast algorithm
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contrast_permutations: 10000 # Default: 10000
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# Correction Method on which to base contrast algorithm
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contrast_correction_method: "cFWE" # Default: "cFWE"; Options: "cFWE", "vFWE", "tfce"
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# Sub-Iterations used in balanced contrast algorithm
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difference_iterations: 1000 # Default: 1000
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# Number of parallel processes used for many different steps in the ALE algorith - maximum depends on your machine
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nprocesses: 2 # Default: 2
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# DO NOT CHANGE THESE IF YOU ARE NOT AN ALE EXPERT
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# MA_Clustering Parameters
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# DO NOT CHANGE THESE IF YOU ARE NOT AN ALE EXPERT!
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clustering_parameters:
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max_clusters: 10 # Default: 10
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subsample_fraction: 0.9 # Default: 0.9
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sampling_iterations: 100 # Default: 1000
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null_iterations: 100 # Default: 5000
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correlation_type: "spearman" # Default: "spearman"; Options: "spearman", "pearson"
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clustering_method: "hierarchical" # Default: "hierarchical"; Options: "hierarchical", "kmeans"
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linkage_method: "complete" # Default: "complete"; Options: "complete", "average", "ward"
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use_pooled_std: False # Default: False
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# DO NOT CHANGE THESE IF YOU ARE NOT AN ALE EXPERT |