jiawen wang

Yes, and it breaks as "segment fault" when treating some datasets. But when setting numba_parallel=False and n_jobs=1, the problem was solved, and faster than using all the cores.

it also worked when numba_parallel=False and n_jobs=2, why ?

Sorry, I mean sq.gr.ligrec can also use all cores. But when setting numba_parallel=False and n_jobs=1, the problem was solved, and faster than using all the cores. In the case of...

My dataset have 59847 rows and 401 columns, I can run binarization with top 10000 rows and 401 columns successfully, and top 40000 rows or random sample 40000 rows from...

Besides, theere are no good documentation on binarization, for example, the "seed" parameter in derive_threshold() are not well explained, and some tutorials are needed.

here is my conda env: # Name Version Build Channel _libgcc_mutex 0.1 conda_forge conda-forge _openmp_mutex 4.5 0_gnu conda-forge arboreto 0.1.5 pypi_0 pypi attrs 19.3.0 pypi_0 pypi backcall 0.1.0 py_0 conda-forge...

And pip list: Package Version ----------------------- ------------------- arboreto 0.1.5 attrs 19.3.0 backcall 0.1.0 bokeh 2.0.1 boltons 20.1.0 certifi 2020.4.5.1 click 7.1.2 cloudpickle 1.4.1 cycler 0.10.0 cytoolz 0.10.1 dask 1.0.0 decorator...

If num_workers was set default, binarize can run, while failed when set to more than 1. I am working on Centos 7 server.

No, it didn't work for the full dataset, no matter what num_workers is. I agree with you, this could be something specific to my dataset. I filtered cells and genes...

It took several hours to run 40000 cells and 401 regulons (num_workers=1). Will the program be interrupted when two cells have the same expression pattern or some regulons have the...