ad66bf0a8faf1f230891faea92c31d8a3a0baa3f,niftynet/engine/sampler_selective.py,,candidate_indices,#Any#Any#Any#,112

Before Change


            seg_label = np.copy(data)
            seg_label = np.asarray(seg_label, dtype=np.int32)
            // print(np.sum(seg_label))
            seg_label = np.where(seg_label == value, np.ones_like(data),
                                 np.zeros_like(data))
            // print(np.sum(seg_label), " num values in seg_label ", value)
            label_size = create_label_size_map(seg_label, 1)
            // print(value, np.sum(seg_label), seg_label.shape,
            //       window_mean.shape, num_min)

After Change


        for value in unique:
            // print(np.sum(data), "sum in data", np.prod(data.shape),
            //       " elements in data")
            seg_label = (data == value).astype(data.dtype)
            // print(np.sum(seg_label), " num values in seg_label ", value)
            label_size = create_label_size_map(seg_label)
            // print(value, np.sum(seg_label), seg_label.shape,
            //       window_ones.shape, num_min)
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 4

Non-data size: 5

Instances


Project Name: NifTK/NiftyNet
Commit Name: ad66bf0a8faf1f230891faea92c31d8a3a0baa3f
Time: 2017-10-04
Author: wenqi.li@ucl.ac.uk
File Name: niftynet/engine/sampler_selective.py
Class Name:
Method Name: candidate_indices


Project Name: nilearn/nilearn
Commit Name: 380c0681bf8b9252befec411d12b71b0678222c6
Time: 2015-02-10
Author: danilobzdok@gmail.com
File Name: nilearn/input_data/tests/test_nifti_masker.py
Class Name:
Method Name: test_mask_4d


Project Name: scipy/scipy
Commit Name: ae151484780b389b5c7b4530c9ac1ef4bb659e23
Time: 2020-01-13
Author: rlucas7@users.noreply.github.com
File Name: scipy/special/_basic.py
Class Name:
Method Name: factorial


Project Name: scikit-learn-contrib/DESlib
Commit Name: 8115a167b0f280a62aa0d5560709ab9790d96e15
Time: 2020-05-19
Author: rafaelmenelau@gmail.com
File Name: deslib/util/aggregation.py
Class Name:
Method Name: weighted_majority_voting_rule