import json
import datasets

_DESCRIPTION = "Neural data with intent context"
_CITATION = ""
_HOMEPAGE = ""
_LICENSE = ""

class NeuralData(datasets.GeneratorBasedBuilder):
    VERSION = datasets.Version("1.0.0")
    
    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features({
                "timestamp": datasets.Value("int64"),
                "session_time": datasets.Value("int64"),
                "channels": {
                    f"channel_{i}": datasets.Value("float64") for i in range(32)
                },
                "intent_context": {
                    "mouse_movement": datasets.Sequence(datasets.Value("int64")),
                    "keyboard_state": {
                        "mouse": datasets.Value("bool")
                    },
                    "camera_rotation": datasets.Sequence(datasets.Value("float64")),
                    "active_targets": datasets.Value("int64")
                }
            }),
            supervised_keys=None,
            homepage=_HOMEPAGE,
            citation=_CITATION,
            license=_LICENSE,
        )
    
    def _split_generators(self, dl_manager):
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={"filepath": "neural_data.txt"}
            )
        ]
    
    def _generate_examples(self, filepath):
        with open(filepath, "r") as f:
            for idx, line in enumerate(f):
                if line.strip():
                    data = json.loads(line)
                    yield idx, data