6aa0f1f4e275098948d4b312530119e5d95b8884,ot/da.py,,jcpot_barycenter,#,749

Before Change


        D2 = np.zeros((nbclasses, nb_elem))
        classes_d = np.zeros(nbclasses)

        classes_d[np.unique(Ys[d]).astype(int)] = 1
        dom["classes"] = classes_d

        for c in classes:

After Change


                print("{:5d}|{:8e}|".format(cpt, err))

    bary = bary / np.sum(bary)
    couplings = [all_domains[d]["K"] for d in range(nbdomains)]

    if log:
        log["niter"] = cpt
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 4

Instances


Project Name: rflamary/POT
Commit Name: 6aa0f1f4e275098948d4b312530119e5d95b8884
Time: 2020-03-31
Author: ievgen.redko@univ-st-etienne.fr
File Name: ot/da.py
Class Name:
Method Name: jcpot_barycenter


Project Name: scikit-learn-contrib/categorical-encoding
Commit Name: b5034279b48ae96ffdd4714f96e0f62b0f4807fc
Time: 2018-10-26
Author: jcastaldo08@gmail.com
File Name: category_encoders/ordinal.py
Class Name: OrdinalEncoder
Method Name: ordinal_encoding


Project Name: librosa/librosa
Commit Name: b9a5f7d2bf056e397ee527425c41d214265ca59c
Time: 2013-11-14
Author: brm2132@columbia.edu
File Name: librosa/display.py
Class Name:
Method Name: specshow