wfondrie / depthcharge Goto Github PK

This is the version that introduced the batch_first parameter for transformer models.

Update the API for Peptide transformers to be more flexible, like we did with the Spectrum transformers.

Hi, casanovo and depthcharge are excellent work. However, there is some confuse in transformer.py. Why there is a replacement from "I" to "L" in peptide sequence during the tokenize function of _PeptideTransformer? Will this replacement influence the predict precusion of peptide sequence incuding "I" during inference?

Thanks for your excellent contributions to the computational mass spectrum community.
Can we obtain the retention time and ActivationType (e.g., HCD) from mgf files using the depthcharge package? And how?

Warning should include why the spectra were invalid e.g. WARNING: Skipped 6745 spectra with invalid charge > 5.

Hi, I would like to know how to read and preprocess a .mgf file using the package. Can you please help me by providing an example code for that, which can then be used to pass on other package functions such as Encoder and Transformer? Thank You

See Noble-Lab/casanovo#145.

When trying to re-use an existing HDF5 index, I get the following error in hdf5.py on line 80:

AttributeError: 'AnnotatedSpectrumIndex' object has no attribute 'annotated'

Looking at the code, I don't know when the annotated attribute should be set. In fact, _handle is set to None in line 63, so I'm not fully understanding how this piece of code is supposed to work.

Have a separate tokenization function to unify this behavior across depthcharge (i.e. to calculate masses from peptide sequences) and Casanovo (during evaluation of the predictions).

Hi there,
I started to use depthcharge and I really like it :)
However, I have a bit of a problem with the dataset AnnotatedSpectrumDataset from the latest depthcharge version. I am testing it with the function from https://github.com/wfondrie/depthcharge/blob/main/tests/unit_tests/test_data/test_loaders.py#L47
That works well. However, whenever I increase the number of workers it gets stuck and the code never terminates.
Have you encountered problems like this? Do you have any idea why this may happen?
I am using Python 3.10.12 on a Linux machine. Here are some of my package versions:

torch==2.1.0
pytorch-lightning==1.9.5
pylance==0.8.16
pyteomics==4.6.3

Thanks a lot in advance!