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mscompress-test.py

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+"""
+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