1.0.0

MS2DeepScore 1.0.0

Last version using Tensorflow. Next versions will be using PyTorch (and come with many changes and improvements!).

Added

• Added split_positive_and_negative_mode.py #148
• Added SettingMS2Deepscore #151
• Clearer Warnings when too little input spectra are used in data generator. #155

Changed

• Change the max oversampling rate to max_pairs_per_bin #148
• Made spectrum pair selection a lot simpler and fixed mistake #148
• Use DataGeneratorCherrypicked instead of DataGeneratorAllInchikeys in pipelines #148
• Removed M1 Chip compatibility which lead to faulty results depending on Tensorflow version #200

0.5.0

ms2deepscore 0.5.0

Added

• New DataGeneratorCherrypicked as an alternative to former data generators #145. This will work better for large datasets and also tried to counteract biases in the chemical similarity scores.
• Models can now be trained on selected metadata entries in addition to the spectrum peaks #128.
• New MetadataFeatureGenerator class to handle additional metadata more robustly #128
• Workflow scripts for training a new MS2DeepScore model #124. The ease of training MS2Deepscore models is improved, including standard settings and splitting validation and training data.

Changed

• In SiameseModel, the attributes are not passed as an argument but instead used by the class.
• Improved plotting functionality. Some additional plotting options were added and plots previously created in notebooks are now functions.
• Linting (code and imports) #145.

0.4.0

MS2DeepScore 0.4.0

Added

• Functions to cover the full pipeline of training a new model #129

Fixed

• Tensorflow issues when saving/loading models #123

Changed

• Random seed is now optional when fixed_set=True for the data generator #134
• load_model() functions now auto-detects if a model is multi_inputs or not
• Python version support was changed to 3.8, 3.9, 3.10 (other versions should still work but are not systematically tested)

0.3.0.1

Release

What's Changed

• make_tensorflow_macos_m1_chip_compatible by @niekdejonge in #110

Full Changelog: 0.3.0...0.3.0.1

0.3.1

MS2DeepScore 0.3.1

Minor changes to make tests work with new matchms (>=0.18.0). Older versions should work as well though. #120

0.3.0

ms2deepscore 0.3.0

Added

• Allow adding metadata to the network inputs, e.g. precursor-m/z using the additional_inputs parameter #115

Fixed

• Update test to work with Tensorflow 2.11 #114

v0.2.3

Fixed

• Fixes issue #97 by raising a ValueError when duplicate InChiKey14 are specified by the user in the reference_scores_df DataFrame.

0.2.2

Minor changes only

Fixed

• now compatible with new Tensorflow 2.6, also checked by additional CI runs for Tensorflow 2.4, 2.5 and 2.6 #92

0.2.1

This release does not change any functionality, but improves speed of spectrum binning.

Changed

• Speed improvement of spectrum binning step #90

0.2.0

This release expands the functionalities of MS2DeepScore. Most important is the option to use Monte-Carlo Dropout for uncertainty evaluation of the predicted spectral similarity scores.

Added

• MS2DeepScoreMonteCarlo Monte-Carlo dropout based ensembling do obtain mean/median score and STD #65
• choice between median (default) and mean ensemble score which come with IQR and STD as uncertainty measures #86
• dropout_in_first_layer option for SiameseModel (default is False) #86
• use_fixed_set option for data generators to create deterministic training/testing data with fixed random seed #73

Changed

• small update of create_histograms_plot to make the plot prettier/better to read #85

Fixed

• solved minor unclarity with the pair selection for non-available reference scores #79
• solved minor unclarity with the addition of noise peaks during data augmentation #78