"""
MSZ Mass Spectrometry Dataset Loader

This dataset contains compressed mass spectrometry data in MSZ format.
Requires the 'mscompress' library for loading.

Install: pip install mscompress
"""

import datasets
from pathlib import Path
from typing import List, Dict, Any


_DESCRIPTION = """
Mass spectrometry dataset in compressed MSZ format.
"""

_HOMEPAGE = ""

_LICENSE = ""

_DATA_FILES = ['test.msz']

_MS_LEVEL_FILTER = None

_GRANULARITY = "spectrum"


class MSZDatasetConfig(datasets.BuilderConfig):
    """BuilderConfig for MSZ dataset."""
    
    def __init__(self, **kwargs):
        super(MSZDatasetConfig, self).__init__(**kwargs)


class MSZDataset(datasets.GeneratorBasedBuilder):
    """MSZ mass spectrometry dataset."""
    
    VERSION = datasets.Version("1.0.0")
    
    BUILDER_CONFIGS = [
        MSZDatasetConfig(
            name="default",
            version=VERSION,
            description="Default configuration for MSZ dataset",
        ),
    ]
    
    DEFAULT_CONFIG_NAME = "default"
    
    def _info(self):
        if _GRANULARITY == "spectrum":
            features = datasets.Features({
                "source_file": datasets.Value("string"),
                "spectrum_index": datasets.Value("int64"),
                "scan_number": datasets.Value("int64"),
                "ms_level": datasets.Value("int32"),
                "retention_time": datasets.Value("float64"),
                "num_peaks": datasets.Value("int64"),
                "mz": datasets.Sequence(datasets.Value("float64")),
                "intensity": datasets.Sequence(datasets.Value("float64")),
            })
        else:  # file-level
            features = datasets.Features({
                "file_path": datasets.Value("string"),
                "file_name": datasets.Value("string"),
                "num_spectra": datasets.Value("int64"),
                "file_size_bytes": datasets.Value("int64"),
                "compression_format": datasets.Value("string"),
            })
        
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            homepage=_HOMEPAGE,
            license=_LICENSE,
        )
    
    def _split_generators(self, dl_manager):
        """Download and extract MSZ files"""
        try:
            import mscompress
        except ImportError:
            raise ImportError(
                "The mscompress library is required to load this dataset. "
                "Install it with: pip install mscompress"
            )
        
        # Download data files
        data_dir = dl_manager.download_and_extract({
            "data": ["data/" + f for f in _DATA_FILES]
        })
        
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "msz_files": data_dir["data"],
                },
            ),
        ]
    
    def _generate_examples(self, msz_files: List[str]):
        """Generate examples from MSZ files"""
        import mscompress
        
        idx = 0
        
        if _GRANULARITY == "file":
            # File-level granularity
            for file_path in msz_files:
                msz = mscompress.read(file_path)
                yield idx, {
                    "file_path": file_path,
                    "file_name": Path(file_path).name,
                    "num_spectra": len(msz.spectra),
                    "file_size_bytes": msz.size,
                    "compression_format": msz.data_format.mz_original_compression,
                }
                idx += 1
        else:
            # Spectrum-level granularity
            for file_path in msz_files:
                msz = mscompress.read(file_path)
                
                for spectrum in msz.spectra:
                    # Apply MS level filter
                    if _MS_LEVEL_FILTER and spectrum.ms_level not in _MS_LEVEL_FILTER:
                        continue
                    
                    yield idx, {
                        "source_file": Path(file_path).name,
                        "spectrum_index": spectrum.index,
                        "scan_number": spectrum.scan_number,
                        "ms_level": spectrum.ms_level,
                        "retention_time": spectrum.retention_time,
                        "num_peaks": spectrum.num_peaks,
                        "mz": spectrum.mz.tolist(),
                        "intensity": spectrum.intensity.tolist(),
                    }
                    idx += 1