performance optimizations about scirpy HOT 3 CLOSED

In GitLab by @grst on Mar 31, 2020, 13:30

At least some of them are required to be able to compute the case study on 100k cells.
The rest can be done at a later stage.

• vectorize chain pairings
• tcr_neighbors: expanding dist matrix to cells takes a long time.
  • Optimize (sparse matrix types?)
  • Only compute the matrices that are necessary
• tcr_neighbors show tqdm progress bar when computing distances.
  • Use heuristic: if length difference > gap open + gap extend depending on cutoff, don't calculate levenshtein or alignment.

from scirpy.

In GitLab by @grst on Mar 31, 2020, 16:43

assigned to @grst

from scirpy.

In GitLab by @grst on Apr 1, 2020, 14:23

closed

from scirpy.