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CHANGELOG.md

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Changelog for Depthcharge

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[Unreleased]

[v0.4.8]

Changed

  • Tokenizer.detokenize() now truncates the output to the first stop token it finds, if trim_stop_token=True.

[v0.4.7]

Fixed

  • Add stop and start tokens for AnnotatedSpectrumDataset, when available.
  • When reverse is used for the PeptideTokenizer, automatically reverse the decoded peptide.

[v0.4.6]

Added

  • Added support for unsigned modification masses that don't quite conform to the Proforma standard.

[v0.4.5]

Changed

  • The scan_id column for parsed spectra is not a sting instead of an integer. This is less space efficient, but we ran into issues with Sciex indexing when trying to use only an integer.

[v0.4.4]

Changed

  • Partially revert length changes to SpectrumDataset and AnnotatedSpectrumDataset. We removed __len__ from both due to problems with PyTorch Lightning compatibility.
  • Simplify dataset code by removing redundancy with lance.pytorch.LanceDatset.
  • Improved warning message for skipped spectra.

[v0.4.3]

Changed

  • Length of the SpectrumDataset and AnnotatedSpectrumDataset now reflect the samples parameter of the lance.pytorch.LanceDataset parent class.

[v0.4.2]

Changed

  • The length of SpectrumDataset and AnnotatedSpectrumDataset is now the number of batches, not the number of spectra. This let's tools like PyTorch Lighting create their progress bars properly.
  • Parsing a dataset now no longer requires reading essentially the whole first file. Now the schema is inferred from the first 128 spectra.

[v0.4.1]

Added

  • Significant updates to documentation. Add how to model mass spectra.
  • Reading and writing from cloud storage on everything!

Changed

  • Migrated to Mike for mkdocs to manage multiple versions.
  • Moved test GitHub Action from pip to uv.

[v0.4.0]

We have completely reworked of the data module. Depthcharge now uses Apache Arrow-based formats instead of HDF5; spectra are converted either Parquet or streamed with PyArrow, optionally into Lance datasets.

We now also have full support for small molecules, with the MoleculeTokenizer, AnalyteTransformerEncoder, and AnalyteTransformerDecoder classes.

Breaking Changes

  • PeptideTransformer* are now AnalyteTransformer*, providing full support for small molecule analytes. Additionally the interface has been completely reworked.
  • Mass spectrometry data parsers now function as iterators, yielding batches of spectra as pyarrow.RecordBatch objects.
  • Parsers can now be told to read arbitrary fields from their respective file formats with the custom_fields parameter.
  • The parsing functionality of SpctrumDataset and its subclasses have been moved to the spectra_to_* functions in the data module.
  • SpectrumDataset and its subclasses now return dictionaries of data rather than a tuple of data. This allows us to incorporate arbitrary additional data
  • SpectrumDataset and its subclasses are now lance.torch.data.LanceDataset subclasses, providing native PyTorch integration.
  • All dataset classes now do not have a loader() method.

Added

  • Support for small molecules.
  • Added the StreamingSpectrumDataset for fast inference.
  • Added spectra_to_df, spectra_to_df, spectra_to_stream to the depthcharge.data module.

Changed

  • Determining the mass spectrometry data file format is now less fragile. It now looks for known line contents, rather than relying on the extension.

[v0.3.1] - 2023-08-18

Added

  • Support for fine-tuning the wavelengths used for encoding floating point numbers like m/z and intensity to the FloatEncoder and PeakEncoder.

Fixed

  • The tgt_mask in the PeptideTransformerDecoder was the incorrect type. Now it is bool as it should be. Thanks @justin-a-sanders!

[v0.3.0] - 2023-06-06

Added

  • Providing a proper tokenization class (also resolves #24 and #18)
  • First-class support for ProForma peptide annotations, thanks to spectrum_utils and pyteomics.
  • Adding primitive dataclasses for peptides, peptide ions, mass spectra ... and even small molecules 🚀
  • Adding type hints to everything and stricter linting with Ruff.
  • Adding a ton of tests.
  • Tight integration with spectrum_utils 💪

Changed

  • Moving preprocessing onto parsing instead of data loading (similar to @bittremieux's proposal in #31)
  • Combining the SpectrumIndex and SpectrumDataset classes into one.
  • Changing peak encodings. Instead of encoding the intensity using a linear projection and summing with the sinusoidal m/z encodings, now the intensity is also sinusoidally encoded and is combined with the sinusoidal m/z encodings using a linear layer.

[v0.2.3] - 2023-08-18

Fixed

  • Applied hotfix from v0.3.1

[v0.2.2] - 2023-05-15

Fixed

  • Fixed retrieving version information.

[v0.2.1] - 2023-05-13

Changed

  • Change target mask from float to boolean.
  • Log the number spectra that are skipped due to an invalid precursor charge.

[v0.2.0] - 2023-03-06

Breaking Changes

  • Dropped pytorch-lightning as a dependency.
  • Removed SpectrumDataModule
  • Removed full-blown models (depthcharge.models)
  • Fixed sinusoidal encoders (Issue #27)
  • MassEncoder is now FloatEncoder, because its generally useful for encoding floating-point numbers.

Added

  • pre-commit hooks and linting with Ruff.

Changed

  • Tensorboard is now an optional dependency.

Removed

  • The example de novo peptide sequencing model.

[v0.1.0] - 2022-11-15

Changed

  • The detokenize() method now returns a list instead of a string.

[v0.0.1] - 2022-09-29

Added

  • This if the first release! All changes from this point forward will be recorded in this changelog.