08233b4ed9bdc1fa2016de0d0e9856c00b28c282,pynets/fmri/clustools.py,,nil_parcellate,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,358

Before Change

                print("Warning: NaN\"s detected in confound regressor file. Filling these with mean values, but the "
                      "regressor file should be checked manually.")
                confounds_nonan = confounds.apply(lambda x: x.fillna(x.mean()), axis=0)
                conf_corr = dir_path + "/confounds_mean_corrected_" + str(random.randint(1, 1000)) + ".tsv"
                confounds_nonan.to_csv(conf_corr, sep="\t")
                clust_est.fit(func_img, confounds=conf_corr)
            else:

After Change

            if confounds.isnull().values.any():
                import uuid
                from time import strftime
                run_uuid = "%s_%s" % (strftime("%Y%m%d-%H%M%S"), uuid.uuid4())
                print("Warning: NaN\"s detected in confound regressor file. Filling these with mean values, but the "
                      "regressor file should be checked manually.")
                confounds_nonan = confounds.apply(lambda x: x.fillna(x.mean()), axis=0)
                conf_corr = "/tmp/confounds_mean_corrected_" + str(run_uuid) + ".tsv"
                confounds_nonan.to_csv(conf_corr, sep="\t")
                clust_est.fit(func_img, confounds=conf_corr)
            else:

Instances