Falling at plot-bin step, even after adjusting -tR and -tB

[immuneAI]

Hello,

I'm using v1.1.1 and facing this error below in few samples :

Traceback (most recent call last): File "/software/miniconda3/envs/hatchet-1.1.1/lib/python3.9/site-packages/scipy/stats/_kde.py", line 223, in __init__ self.set_bandwidth(bw_method=bw_method) File "/software/miniconda3/envs/hatchet-1.1.1/lib/python3.9/site-packages/scipy/stats/_kde.py", line 571, in set_bandwidth self._compute_covariance() File "/software/miniconda3/envs/hatchet-1.1.1/lib/python3.9/site-packages/scipy/stats/_kde.py", line 583, in _compute_covariance self._data_cho_cov = linalg.cholesky(self._data_covariance, File "/software/miniconda3/envs/hatchet-1.1.1/lib/python3.9/site-packages/scipy/linalg/_decomp_cholesky.py", line 89, in cholesky c, lower = _cholesky(a, lower=lower, overwrite_a=overwrite_a, clean=True, File "/software/miniconda3/envs/hatchet-1.1.1/lib/python3.9/site-packages/scipy/linalg/_decomp_cholesky.py", line 37, in _cholesky raise LinAlgError("%d-th leading minor of the array is not positive " numpy.linalg.LinAlgError: 2-th leading minor of the array is not positive definite

The above exception was the direct cause of the following exception:

Traceback (most recent call last): File "/software/miniconda3/envs/hatchet-1.1.1/bin/hatchet", line 33, in <module> sys.exit(load_entry_point('hatchet==1.1.1', 'console_scripts', 'hatchet')()) File "/software/miniconda3/envs/hatchet-1.1.1/lib/python3.9/site-packages/hatchet/__main__.py", line 61, in main globals()[command](args) File "/software/miniconda3/envs/hatchet-1.1.1/lib/python3.9/site-packages/hatchet/utils/plot_bins.py", line 67, in main bb(bbc, clusters, args, out) File "/software/miniconda3/envs/hatchet-1.1.1/lib/python3.9/site-packages/hatchet/utils/plot_bins.py", line 302, in bb z = gaussian_kde(xy)(xy) File "/software/miniconda3/envs/hatchet-1.1.1/lib/python3.9/site-packages/scipy/stats/_kde.py", line 232, in __init__ raise linalg.LinAlgError(msg) from e numpy.linalg.LinAlgError: The data appears to lie in a lower-dimensional subspace of the space in which it is expressed. This has resulted in a singular data covariance matrix, which cannot be treated using the algorithms implemented in gaussian_kde. Consider performing principle component analysis / dimensionality reduction and using gaussian_kde with the transformed data.

I'm running these commands with cluster-bins & plot-cn

> hatchet cluster-bins bb/bulk.bb -o bbc/bulk.seg -O bbc/bulk.bbc -d 0.1

> hatchet plot-bins bbc/bulk.bbc -s bbc/bulk.seg --ymin 0.5 --ymax 4 --colwrap 3 -tS 0.008