bugfix resample only if type is not contour or contourf #2656
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@@ Coverage Diff @@
## master #2656 +/- ##
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+ Coverage 87.57% 87.60% +0.03%
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Files 100 100
Lines 13148 13159 +11
Branches 2552 2555 +3
==========================================
+ Hits 11514 11528 +14
+ Misses 1026 1024 -2
+ Partials 608 607 -1
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bthirion
reviewed
Jan 13, 2021
| @@ -750,7 +750,10 @@ def add_contours(self, img, threshold=1e-6, filled=False, **kwargs): | |||
| def _map_show(self, img, type='imshow', | |||
| resampling_interpolation='continuous', | |||
| threshold=None, **kwargs): | |||
| img = reorder_img(img, resample=resampling_interpolation) | |||
| if _utils.niimg._is_binary_niimg(img): | |||
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Maybe you should explain the logic implemented here.
NicolasGensollen
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@bthirion do you think there is still something to improve here ? |
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Merging, thanks ! |
bthirion
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May 19, 2021
* 'master' of github.com:nilearn/nilearn: Release 0.7.1 (nilearn#2727) Add two_sided flag to get_clusters_table (nilearn#2719) bugfix resample only if type is not contour or contourf (nilearn#2656) Support atlases in plot_carpet (nilearn#2702) Fix whatsnew entry with public function reference (nilearn#2716) EHN signal.clean standardise option PSC to allow negative mean signal (nilearn#2714) Replace NaNs with zeros in NiftiLabelsMasker (nilearn#2712) [MRG] Allow asymmetric matrices in plot_connectome (nilearn#2703) [MRG] Mosaic mode of displaying brain images (nilearn#2684) Resampling functionality for NeuroVault (nilearn#2696) Solving "NiftiMapsMasker and NiftiLabelsMasker cannot transform 3D images" (nilearn#2708) Raise warning for FirstLevelModel fit when confounds and design_matrices are both specified (nilearn#2710) Fixed numpy warning when img has NaNs. (nilearn#2709) [MRG] High variance confounds in maskers (nilearn#2697) fix sampling (nilearn#2706) [MRG] Handle nans in surf plotting (nilearn#2691) [FIX] get_clusters_table: ensure input is 3D and accept filenames (nilearn#2701) Warn in nifti masker report when no image provided to fit (nilearn#2694) fix for FirstLevelModel compute_contrast for multiple runs with varying matrice size or columns (nilearn#2688)
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Fixes #2537
See explanations in #2537.
Not sure this is the best fix although it's pretty straightforward.