Esempi in Python per picked_rocs_from_thresholds

Esempio n. 1

File: count_gapped_pwm_sites.py Progetto: pombredanne/biopsy

def run_pwm_forward_backward(tag, freqs, gaps, positive_seqs, negative_seqs):
    """
    Run the PWM using forward-backward.
    """
    logging.info('Running PWM: %s', tag)
    logo = L.pssm_as_image(freqs, size=None, transparencies=gaps)
    logo_filename = '%s-logo.png' % tag
    logo.save(logo_filename)
    logging.info('%s: Created logo: %s', tag, logo_filename)
    # build model
    model = build_hmm_model(freqs, gaps, .001)
    hmm.graph_as_svg(model, '%s-states' % tag, neato_properties={'-Elen': 1.4})
    logging.debug('%s: Graphed model', tag)
    positive_scores = test_hmm_forward_backward(model, positive_seqs.values())
    negative_scores = test_hmm_forward_backward(model, negative_seqs.values())
    return roc.picked_rocs_from_thresholds(positive_scores, negative_scores)

Esempio n. 2

File: count_gapped_pwm_sites.py Progetto: JohnReid/biopsy

def run_pwm_forward_backward(tag, freqs, gaps, positive_seqs, negative_seqs):
    """
    Run the PWM using forward-backward.
    """
    logging.info('Running PWM: %s', tag)
    logo = L.pssm_as_image(freqs, size=None, transparencies=gaps)
    logo_filename = '%s-logo.png' % tag
    logo.save(logo_filename)
    logging.info('%s: Created logo: %s', tag, logo_filename)
    # build model
    model = build_hmm_model(freqs, gaps, .001)
    hmm.graph_as_svg(model, '%s-states' % tag, neato_properties={'-Elen':1.4})
    logging.debug('%s: Graphed model', tag)
    positive_scores = test_hmm_forward_backward(model, positive_seqs.values())
    negative_scores = test_hmm_forward_backward(model, negative_seqs.values())
    return roc.picked_rocs_from_thresholds(positive_scores, negative_scores)

Esempio n. 3

File: run_sp1_eval.py Progetto: JohnReid/biopsy

    if 'Gapped-new' == method:
        return 'Gapped'
    if 'Ungapped-new' == method:
        return 'Ungapped'
    if 'GLAM2-i7' == method:
        return 'GLAM2'
    return method

for bg in backgrounds:

    # ROC curves
    P.figure()
    for method in methods:
        rocs = R.picked_rocs_from_thresholds(
            scores[(method,)],
            scores[(method, bg)],
            num_points=options.num_points
        )
        auc = R.area_under_curve(rocs)
        R.plot_roc_points(rocs, label='%.2f %s'%(auc,name(method)), marker=markers[method])
    R.plot_random_classifier(label='0.50 Random')
    R.label_plot()
    P.legend(loc='lower right')
    P.title('Full Sp1 - %s' % bg)
    P.savefig('ROC-Sp1-%s.png' % bg)
    P.savefig('ROC-Sp1-%s.eps' % bg)

    # precision-recall curves
    P.figure()
    for method in methods:
        rocs = R.picked_rocs_from_thresholds(

Esempio n. 4

File: run_sp1_eval.py Progetto: pombredanne/biopsy

    if 'Gapped-new' == method:
        return 'Gapped'
    if 'Ungapped-new' == method:
        return 'Ungapped'
    if 'GLAM2-i7' == method:
        return 'GLAM2'
    return method


for bg in backgrounds:

    # ROC curves
    P.figure()
    for method in methods:
        rocs = R.picked_rocs_from_thresholds(scores[(method, )],
                                             scores[(method, bg)],
                                             num_points=options.num_points)
        auc = R.area_under_curve(rocs)
        R.plot_roc_points(rocs,
                          label='%.2f %s' % (auc, name(method)),
                          marker=markers[method])
    R.plot_random_classifier(label='0.50 Random')
    R.label_plot()
    P.legend(loc='lower right')
    P.title('Full Sp1 - %s' % bg)
    P.savefig('ROC-Sp1-%s.png' % bg)
    P.savefig('ROC-Sp1-%s.eps' % bg)

    # precision-recall curves
    P.figure()
    for method in methods: