def plotROC(alg_fpr_tpr_rocDict, color_paletteList, tuple_size, path_name):
    colors = []
    for p in color_paletteList:
        for c in plt.get_cmap(p).colors:
            colors += [c]
    plt.figure(figsize=tuple_size)
    col = 0
    for al in alg_fpr_tpr_rocDict:
        fpr = alg_fpr_tpr_rocDict[al]['fpr']
        tpr = alg_fpr_tpr_rocDict[al]['tpr']
        roc_auc = alg_fpr_tpr_rocDict[al]['roc_auc']
        alg_name = alg_fpr_tpr_rocDict[al]['alg_name']
        plt.plot(fpr[1], tpr[1], color=colors[col], alpha=0.7, label=(alg_name + (' (area = %0.3f)' % roc_auc[1])))
        col += 1
    plt.plot([0, 1], [0, 1], color='black', linestyle='--')
    plt.xlim([0.0, 1.0])
    plt.ylim([0.0, 1.0])
    plt.xlabel('False Positive Rate')
    plt.ylabel('True Positive Rate')
    plt.title('ROC curves per each algorithm')
    plt.legend(loc='lower right')
    plt.savefig((path_name + '_ROC-AUC.png'))
    plt.show()
def plotROC(alg_fpr_tpr_rocDict, color_paletteList, tuple_size, path_name):
    colors = []
    for p in color_paletteList:
        for c in plt.get_cmap(p).colors:
            colors += [c]
    plt.figure(figsize=tuple_size)
    col = 0
    for al in alg_fpr_tpr_rocDict:
        fpr = alg_fpr_tpr_rocDict[al]['fpr']
        tpr = alg_fpr_tpr_rocDict[al]['tpr']
        roc_auc = alg_fpr_tpr_rocDict[al]['roc_auc']
        alg_name = alg_fpr_tpr_rocDict[al]['alg_name']
        plt.plot(fpr[1], tpr[1], color=colors[col], alpha=0.7, label=(alg_name + (' (area = %0.3f)' % roc_auc[1])))
        col += 1
    plt.plot([0, 1], [0, 1], color='black', linestyle='--')
    plt.xlim([0.0, 1.0])
    plt.ylim([0.0, 1.0])
    plt.xlabel('False Positive Rate')
    plt.ylabel('True Positive Rate')
    plt.title('ROC curves per each algorithm')
    plt.legend(loc='lower right')
    plt.savefig((path_name + '_ROC-AUC.png'))
    plt.show()