2ddf94e48476ff253260a3364f76ee13a932e252,src/pyscenic/binarization.py,,plot_binarization,#,47

Before Change


    auc_mtx[regulon_name].hist(bins=bins)
    if threshold is None:
        threshold = _derive_threshold(auc_mtx, regulon_name)
    ylim = plt.ylim()
    plt.plot([threshold]*2, ylim, "r:")
    plt.ylim(ylim)
    plt.xlabel("AUC")
    plt.ylabel("//")

After Change


    :param bins: The number of bins to use in the AUC histogram.
    :param threshold: The threshold to use for binarization. If None then this will be derived automatically.
    
    if ax is None:
        ax=plt.gca()
    auc_mtx[regulon_name].hist(bins=bins,ax=ax)
    if threshold is None:
        threshold = _derive_threshold(auc_mtx, regulon_name)
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 6

Instances


Project Name: aertslab/pySCENIC
Commit Name: 2ddf94e48476ff253260a3364f76ee13a932e252
Time: 2018-06-15
Author: vandesande.bram@gmail.com
File Name: src/pyscenic/binarization.py
Class Name:
Method Name: plot_binarization


Project Name: kundajelab/dragonn
Commit Name: 38512d92a8682a62e73c5b9e86366888be374532
Time: 2019-05-29
Author: annashcherbina@gmail.com
File Name: dragonn/vis/__init__.py
Class Name:
Method Name: plot_motif_scores


Project Name: rasbt/mlxtend
Commit Name: 209663123a5a96c62267e10556c3d90716a39c6f
Time: 2015-05-28
Author: se.raschka@me.com
File Name: mlxtend/matplotlib/enrichment_plot.py
Class Name:
Method Name: enrichment_plot