add functionality to parse spectra directly from ms2spectrum objects …

README.rst

@@ -57,6 +57,8 @@ The MS³PIP Python application can perform the following tasks:
 - ``predict-batch``: Predict fragmentation spectra for a batch of peptides.
 - ``predict-library``: Predict a spectral library from protein FASTA file.
 - ``correlate``: Compare predicted and observed intensities and optionally compute correlations.
+- ``correlate-preloaded``: Compare predicted and observed intensities for PSMs with preloaded
+  spectra (Python API only).
 - ``correlate-single``: Compare predicted and observed intensities for a single peptide spectrum.
 - ``get-training-data``: Extract feature vectors and target intensities from observed spectra for
   training.

docs/source/usage.rst

@@ -68,6 +68,22 @@ For instance:
     ms2pip correlate --psm-filetype sage results.sage.tsv spectra.mgf
 
 
+``correlate-preloaded``
+----------------------
+
+Compare predicted and observed intensities for PSMs that already have
+:py:class:`ms2rescore_rs.MS2Spectrum` objects attached to their ``spectrum`` attribute. This is
+useful when spectra are already loaded in memory, e.g., when using MS²PIP within
+`ms2rescore <https://github.com/compomics/ms2rescore/>`_. This mode is only available through the
+Python API.
+
+.. code-block:: python
+
+    import ms2pip
+
+    results = ms2pip.correlate_preloaded(psm_list, compute_correlations=True)
+
+
 ``correlate-single``
 --------------------
 

ms2pip/__init__.py

@@ -1,7 +1,17 @@
 # isort: skip_file
 """MS2PIP: Accurate and versatile peptide fragmentation spectrum prediction."""
 
-__version__ = "4.1.2"
+__version__ = "4.2.0-alpha.0"
+__all__ = [
+    "predict_single",
+    "predict_batch",
+    "predict_library",
+    "correlate",
+    "correlate_preloaded",
+    "get_training_data",
+    "annotate_spectra",
+    "download_models",
+]
 
 from warnings import filterwarnings
 
@@ -10,11 +20,12 @@
 )
 
 
-from ms2pip.core import (  # noqa: F401 E402
+from ms2pip.core import (  # noqa: E402
     predict_single,
     predict_batch,
     predict_library,
     correlate,
+    correlate_preloaded,
     get_training_data,
     annotate_spectra,
     download_models,