Quickstart

This minimal example shows how to train an encoding model using the LeBel assembly with word rate features. This is the simplest and fastest way to get started with LITcoder.

from encoding.assembly.assembly_loader import load_assembly
from encoding.features.factory import FeatureExtractorFactory
from encoding.downsample.downsampling import Downsampler
from encoding.models.nested_cv import NestedCVModel
from encoding.trainer import AbstractTrainer

# 1) Load prepackaged assembly
assembly_path = "assembly_lebel_uts03.pkl"
assembly = load_assembly(assembly_path)

# 2) Configure components (wordrate-only)
extractor = FeatureExtractorFactory.create_extractor(
    modality="wordrate",
    model_name="wordrate",
    config={},
    cache_dir="cache",
)

downsampler = Downsampler()
model = NestedCVModel(model_name="ridge_regression")

# FIR, downsampling, and trimming match our LeBel defaults
fir_delays = [1, 2, 3, 4]
trimming_config = {
    "train_features_start": 10, "train_features_end": -5,
    "train_targets_start": 0,  "train_targets_end": None,
    "test_features_start": 50,  "test_features_end": -5,
    "test_targets_start": 40,   "test_targets_end": None,
}

downsample_config = {}

# 3) Train
trainer = AbstractTrainer(
    assembly=assembly,
    feature_extractors=[extractor],
    downsampler=downsampler,
    model=model,
    fir_delays=fir_delays,
    trimming_config=trimming_config,
    use_train_test_split=True,
    logger_backend="wandb",
    wandb_project_name="lebel-wordrate",
    dataset_type="lebel",
    results_dir="results",
    downsample_config=downsample_config,
)

metrics = trainer.train()
print({
    "median_correlation": metrics.get("median_score", float("nan")),
    "n_significant": metrics.get("n_significant"),
})

Prerequisites

Before running this example, you need to:

1. Download the LeBel assembly:

   gdown 1q-XLPjvhd8doGFhYBmeOkcenS9Y59x64
   

2. Install LITcoder:

   git clone git@github.com:GT-LIT-Lab/litcoder_core.git
   cd litcoder_core
   conda create -n litcoder -y python=3.12.8
   conda activate litcoder
   conda install pip
   pip install -e .