a9fa0782dc1df24bd3e9c9ee9ddd3ab1dc9fd5e0,dipy/segment/mask.py,,segment_from_cfa,#Any#Any#Any#,226
Before Change
if (np.min(threshold) < 0 or np.max(threshold) > 1):
raise ValueError("threshold must be between 0 and 1")
if (np.min(cfa) < 0 or np.max(cfa) > 1):
raise ValueError("cfa must be between 0 and 1")
if cfa.shape[-1] != 3:
After Change
Binary mask of the segmentation.
FA = fractional_anisotropy(tensorfit.evals)
FA[np.isnan(FA) ] = 0
FA = np.clip(FA, 0, 1) // Clamp the FA to remove degenerate tensors
cfa = color_fa(FA, tensorfit.evecs)
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 5
Instances Project Name: nipy/dipy
Commit Name: a9fa0782dc1df24bd3e9c9ee9ddd3ab1dc9fd5e0
Time: 2013-09-11
Author: Samuel.St-Jean@usherbrooke.ca
File Name: dipy/segment/mask.py
Class Name:
Method Name: segment_from_cfa
Project Name: nipy/dipy
Commit Name: 990702bedcfd4bfd62b3c96f82a26fd8e1b6354a
Time: 2013-09-11
Author: Samuel.St-Jean@usherbrooke.ca
File Name: dipy/segment/mask.py
Class Name:
Method Name: segment_from_cfa
Project Name: scikit-optimize/scikit-optimize
Commit Name: 9cdd21160f4b4352b05f7b7ce9f0f63506c585c9
Time: 2017-04-17
Author: iaroslav-ai@users.noreply.github.com
File Name: benchmarks/bench_ml.py
Class Name: MLBench
Method Name: evaluate