[ENH] Add mask argument to t2smap, tedana #108
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@@ Coverage Diff @@
## master #108 +/- ##
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+ Coverage 45.36% 45.44% +0.07%
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Files 28 28
Lines 1587 1602 +15
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+ Hits 720 728 +8
- Misses 867 874 +7
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emdupre
changed the title
tedana/utils/utils.py
Outdated
| @@ -169,6 +169,9 @@ def make_adaptive_mask(data, minimum=True, getsum=False): | |||
| data : (S x E x T) array_like | |||
| Multi-echo data array, where `S` is samples, `E` is echos, and `T` is | |||
| time | |||
| mask : :obj:`str`, optional | |||
| Binary mask for voxels to consider in TE Dependent ANAlysis. Default is | |||
| to generate mask from data with good signal across echoes | |||
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This can be a string (filename), a numpy array, or an image, right?
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Right now I'm only accepting a file name, since it's user-specified. Can you explain how it could be an image or numpy array ?
| else: | ||
| # if the user has supplied a binary mask | ||
| mask = load_image(mask).astype(bool) | ||
| masksum = masksum * mask |
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Should there be shape/affine checks or would the ValueError numpy will raise when dimensions are incompatible be sufficient?
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OK, merging ! 🎉 |
jbteves
added
breaking change
Closes #96.
Changes proposed in this pull request:
tedanaandt2smapworkflows