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.gitignore

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marimo/_lsp/
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__marimo__/
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datasets/data_tmfc/
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# Claude Code helper files (local only)
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.claude/
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AGENTS.md

README.md

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For more information on TFNBS's features, modules and usage, please refer to the [official documentation](https://IHB-IBR-department.github.io/TFNBS/).
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Examples of usage on fMRI and EEG data are avaialble in [notebooks]() and [data]().
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Examples of usage on fMRI and EEG data are avaialble in [notebooks]() and [data]().
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## Project structure
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```
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TFNBS/
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tfnbs/ # core library modules (scores, stats, utils)
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tests/ # unit tests (unittest)
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syntetic_experiments/ # synthetic data experiments and scripts
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generate_topology_example.py
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sim_topology_examples.py
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sim_method_comparisons/
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power_test/
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fpr/
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output/
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datasets/ # sample data files
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docs/ # Sphinx docs source
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```
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## Synthetic experiments
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Generate a single topology dataset (saves z-matrices, effect mask, t-stats, and a PNG visualization):
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```bash
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python syntetic_experiments/generate_topology_example.py \
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--topology within_module_dense \
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--effect-size 0.25 \
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--n-samples 20 \
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--output-dir syntetic_experiments/output/my_data
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```
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Generate multiple datasets from a config:
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```bash
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python syntetic_experiments/generate_topology_example.py \
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--config syntetic_experiments/topology_config.yaml
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```
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Method comparison sweep (quick config available in the folder):
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```bash
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python syntetic_experiments/sim_method_comparisons/sim_method_comparisons.py \
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--all-scenarios --effect-size 0.25 --time-points 50 --n-permutations 50
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```
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Power analysis sweep:
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```bash
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python syntetic_experiments/power_test/power_analysis.py \
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--config syntetic_experiments/power_test/sweep_config_power_quick.yaml
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```
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FPR calibration:
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```bash
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python syntetic_experiments/fpr/fpr_calibration.py \
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--config syntetic_experiments/fpr/fpr_config_quick.yaml
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```
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## Permutation p-values (`compute_p_val`)
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## Synthetic method-comparison example
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See `examples/sim_method_comparisons.py` which compares all methods via `compute_p_val` and saves GT/t-stat/`1-p` heatmaps:
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See `syntetic_experiments/sim_method_comparisons/sim_method_comparisons.py` which compares all methods via `compute_p_val` and saves GT/t-stat/`1-p` heatmaps:
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```bash
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python examples/sim_method_comparisons.py --all-scenarios --effect-size 0.25 --time-points 50 --n-permutations 50
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python syntetic_experiments/sim_method_comparisons/sim_method_comparisons.py --all-scenarios --effect-size 0.25 --time-points 50 --n-permutations 50
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```
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