gavindiaz/AlphaFlow-MT5-ML-DL-Trading-Lab
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

perf: Optimize double barrier labeling with numpy vectorization

Browse Source 
Replaced the O(H*N) nested loop in create_labels_double_barrier with an O(H) vectorized approach utilizing numpy slice-based operations and arrays. Also removed duplicate implementation of create_labels_double_barrier in the same file. Fixed formatting in .gitignore to properly ignore pycache files.

Measurements with `N=100000`, `horizon=20`:
Original time: ~0.83s
Vectorized time: ~0.02s
Improvement: Over 40x speedup with correct output handling bounds edge cases like `len(df) < horizon`.

Co-authored-by: maghdam <63883156+maghdam@users.noreply.github.com>
This commit is contained in:
google-labs-jules[bot]
2026-03-11 18:35:20 +00:00
co-authored by maghdam
parent 29fcbf0f9d
commit 16c7dadbad
17 changed files with 27 additions and 53 deletions
Download Patch File Download Diff File Expand all files Collapse all files
.gitignore
+2 -4
View File
@@ -127,8 +127,6 @@ dmypy.json
*.xlsx
*.pkl
# Developer notes
NOTES.md
NOTES.md
__pycache__