Reimplement most of spectrum_output for v4.0.0

ms2pip/_utils/dlib.py

@@ -1,6 +1,8 @@
 """Database configuration for EncyclopeDIA DLIB SQLite format."""
 
 import zlib
+from pathlib import Path
+from typing import Union
 
 import numpy
 import sqlalchemy
@@ -91,7 +93,7 @@ def copy(self):
 )
 
 
-def open_sqlite(filename):
+def open_sqlite(filename: Union[str, Path]) -> sqlalchemy.engine.Connection:
     engine = sqlalchemy.create_engine(f"sqlite:///{filename}")
     metadata.bind = engine
     return engine.connect()

ms2pip/plot.py

@@ -0,0 +1,23 @@
+from pathlib import Path
+from typing import Union
+
+from ms2pip.spectrum import Spectrum
+
+try:
+    import matplotlib.pyplot as plt
+    import spectrum_utils.plot as sup
+
+    _can_plot = True
+except ImportError:
+    _can_plot = False
+
+
+def spectrum_to_png(spectrum: Spectrum, filepath: Union[str, Path]):
+    """Plot a single spectrum and write to a PNG file."""
+    if not _can_plot:
+        raise ImportError("Matplotlib and spectrum_utils are required to plot spectra.")
+    ax = plt.gca()
+    ax.set_title("MS²PIP prediction for " + str(spectrum.peptidoform))
+    sup.spectrum(spectrum.to_spectrum_utils(), ax=ax)
+    plt.savefig(Path(filepath).with_suffix(".png"))
+    plt.close()

ms2pip/spectrum.py

@@ -72,10 +72,10 @@ def __repr__(self) -> str:
     @model_validator(mode="after")
     @classmethod
     def check_array_lengths(cls, data: dict):
-        if len(data["mz"]) != len(data["intensity"]):
+        if len(data.mz) != len(data.intensity):
             raise ValueError("Array lengths do not match.")
-        if data["annotations"] is not None:
-            if len(data["annotations"]) != len(data["intensity"]):
+        if data.annotations is not None:
+            if len(data.annotations) != len(data.intensity):
                 raise ValueError("Array lengths do not match.")
         return data