precision_recall_vs_threshold.py

def plot_precision_recall_vs_threshold(precisions, recalls, thresholds, metric_name=None, metric_perc=None):
    plt.figure(figsize=(15, 10))
    plt.plot(thresholds, precisions[:-1], 'b--', label='Precision')
    plt.plot(thresholds, recalls[:-1], 'g-', label='Recall')
    plt.xlabel('Threshold', fontsize=15)
    plt.axis([-50000, 50000, 0, 1])
    plt.legend(loc='best', fontsize=16)
    
    if metric_name=='precision':
        metric = precisions
        tradedoff_metric = recalls
        tradedoff_metric_name = 'Recall'
        # tradedoff metric & threshold at percentage metric we want.
        tradedoff_atperc_metric = tradedoff_metric[np.argmax(metric >= metric_perc)] 
        threshold_atperc_metric = thresholds[np.argmax(metric >= metric_perc)]
    elif metric_name == 'recall':
        metric = recalls
        tradedoff_metric = precisions
        tradedoff_metric_name = 'Precision'
        # tradedoff metric & threshold at percentage metric we want.
        tradedoff_atperc_metric = tradedoff_metric[np.argmax(metric <= metric_perc)] 
        threshold_atperc_metric = thresholds[np.argmax(metric <= metric_perc)]
    else:
        return
    # Draw the threholds, red dotted vertical line
    plt.plot([threshold_atperc_metric, threshold_atperc_metric], [0., metric_perc], "r:")
    # Draw the two horizontal dotted line for precision and recall
    plt.plot([-50000, threshold_atperc_metric], [metric_perc, metric_perc], "r:")
    plt.plot([-50000, threshold_atperc_metric], [tradedoff_atperc_metric, tradedoff_atperc_metric ], "r:")
    # Draw the two dots
    plt.plot([threshold_atperc_metric], [metric_perc], "ro")
    plt.plot([threshold_atperc_metric], [tradedoff_atperc_metric], "ro")
    plt.title("Precision/Recall vs Threshold plot with Threshold Set to {}% of {}\n trading off {} at {:.3f}%".format(
        metric_perc*100, 
        metric_name.capitalize(), 
        tradedoff_metric_name,
        tradedoff_atperc_metric*100), fontsize=20)
    plt.show()
    return threshold_atperc_metric
    
threshold = plot_precision_recall_vs_threshold(precisions, recalls, thresholds, 'precision', 0.9)