Cholesky AttributeError from DeepLC fix by down versioning to scikit-learn==1.3.2, scipy==1.11.4

Hi Robbin,

I think you should take a look at tightening up some version requirements on DeepLC python dependency packages. Specifically, pygam, scipy, scikit-learn. Here's what I experienced:

On July 1, 2024 From my python script which calls the DeepLC function dlc.calibrate_preds, I got the error below after setting up a Windows 10 computer with a new Python installation of DeepLC with ‘pip install DeepLC’ after installing a minimal Python: Miniconda3 py311_23.10.0-1.

This installed: deeplc==2.2.36, deeplcretrainer==0.2.12, pygam==0.9.0

After reading the comments in the dependency file triggering the error: Lib\site-packages\pygam\utils.py I could see that the error is only triggered if there has been trouble installing dependencies that the pygam developer has foreseen.

import scipy as sp
from scipy import sparse
import numpy as np
from numpy.linalg import LinAlgError
try:
  from sksparse.cholmod import cholesky as spcholesky
  from sksparse.test_cholmod import CholmodNotPositiveDefiniteError
  SKSPIMPORT = True
except ImportError:
  SKSPIMPORT = False

Because I had another working system set up in January I could check some package versioning and was able to eliminate the warning by revising downward the versioning of 2 packages. From scikit-learn==1.5.0 scipy==1.14.0 To scikit-learn==1.3.2 scipy==1.11.4

There may be some higher versions of these packages that work, I just went to the last known good that I had previously set up on another computer.

The Error

  File "D:\SpectrumMill\millpy\DeepLCwrapper.py", line 421, in fRunDeepLC
    dlc.calibrate_preds(seq_df=dfCalIn)
  File "C:\ProgramData\Miniconda3\Lib\site-packages\deeplc\deeplc.py", line 1173, in calibrate_preds
    calibrate_output = self.calibrate_preds_func_pygam(
                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\ProgramData\Miniconda3\Lib\site-packages\deeplc\deeplc.py", line 845, in calibrate_preds_func_pygam
    gam_model_cv = LinearGAM(s(0), verbose=True).fit(predicted_tr, measured_tr)
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\ProgramData\Miniconda3\Lib\site-packages\pygam\pygam.py", line 920, in fit
    self._pirls(X, y, weights)
  File "C:\ProgramData\Miniconda3\Lib\site-packages\pygam\pygam.py", line 705, in _pirls
    E = self._cholesky(S + P, sparse=False, verbose=self.verbose)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\ProgramData\Miniconda3\Lib\site-packages\pygam\pygam.py", line 485, in _cholesky
    L = cholesky(A, **kwargs)
        ^^^^^^^^^^^^^^^^^^^^^
  File "C:\ProgramData\Miniconda3\Lib\site-packages\pygam\utils.py", line 81, in cholesky
    A = A.A
        ^^^
AttributeError: 'csr_matrix' object has no attribute 'A'

compomics / DeepLC

Cholesky AttributeError from DeepLC fix by down versioning to scikit-learn==1.3.2, scipy==1.11.4 #74

The Error