Skip to content

Updated flat sigmoid to match birdnet_analyzer #25

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
stefantaubert merged 2 commits into from
Feb 22, 2026
Merged

Updated flat sigmoid to match birdnet_analyzer #25

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
002cf42
Updated flat sigmoid to match birdnet_analyzer
Josef-Haupt Feb 18, 2026
568ad4b
add changelog
stefantaubert Feb 22, 2026
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 4 additions & 0 deletions CHANGELOG.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -12,6 +12,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
- Added convenience functions to export embeddings by @Josef-Haupt
- Added some code documentation

### Changed

- Updated flat sigmoid to match birdnet_analyzer by @Josef-Haupt

### Bugfixes

- Fixed issue with one test on Python 3.11 & 3.12
Expand Down
5 changes: 3 additions & 2 deletions src/birdnet/utils/helper.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -316,9 +316,10 @@ def fillup_with_silence(


def flat_sigmoid_logaddexp_fast(
x: npt.NDArray, sensitivity: float, clip_val: float = 15.0
x: npt.NDArray, sensitivity: float, clip_val: float = 15.0, bias: float = 1.0

Copilot AI Feb 18, 2026

Copy link

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

The new bias parameter lacks test coverage. Consider adding unit tests to verify:

  1. Backward compatibility when bias=1.0 (default)
  2. Correct behavior for various bias values
  3. The transformed_bias calculation matches the BirdNET-Analyzer reference implementation

This is especially important since there are comprehensive tests for other functions in the repository (e.g., in src/birdnet_tests/), and this function is used in the prediction pipeline.

Copilot uses AI. Check for mistakes.
) -> npt.NDArray:
y = sensitivity * np.clip(x, -clip_val, clip_val)
transformed_bias = (bias - 1.0) * 10.0
y = sensitivity * np.clip(x + transformed_bias, -clip_val, clip_val)

positive_mask = y >= 0
abs_y = np.abs(y)
Expand Down
Loading