msaf/plotting.py
def plot_one_track(file_struct, est_times, est_labels, boundaries_id, labels_id,
                   title=None):
    """Plots the results of one track, with ground truth if it exists."""
    import matplotlib.pyplot as plt
    # Set up the boundaries id
    bid_lid = boundaries_id
    if labels_id is not None:
        bid_lid += " + " + labels_id
    try:
        # Read file
        jam = jams.load(file_struct.ref_file)
        ann = jam.search(namespace='segment_.*')[0]
        ref_inters, ref_labels = ann.to_interval_values()

        # To times
        ref_times = utils.intervals_to_times(ref_inters)
        all_boundaries = [ref_times, est_times]
        all_labels = [ref_labels, est_labels]
        algo_ids = ["GT", bid_lid]
    except:
        logging.warning("No references found in %s. Not plotting groundtruth"
                        % file_struct.ref_file)
        all_boundaries = [est_times]
        all_labels = [est_labels]
        algo_ids = [bid_lid]

    N = len(all_boundaries)

    # Index the labels to normalize them
    for i, labels in enumerate(all_labels):
        all_labels[i] = mir_eval.util.index_labels(labels)[0]

    # Get color map
    cm = plt.get_cmap('gist_rainbow')
    max_label = max(max(labels) for labels in all_labels)

    figsize = (8, 4)
    plt.figure(1, figsize=figsize, dpi=120, facecolor='w', edgecolor='k')
    for i, boundaries in enumerate(all_boundaries):
        color = "b"
        if i == 0:
            color = "g"
        for b in boundaries:
            plt.axvline(b, i / float(N), (i + 1) / float(N), color=color)
        if labels_id is not None:
            labels = all_labels[i]
            inters = utils.times_to_intervals(boundaries)
            for label, inter in zip(labels, inters):
                plt.axvspan(inter[0], inter[1], ymin=i / float(N),
                            ymax=(i + 1) / float(N), alpha=0.6,
                            color=cm(label / float(max_label)))
        plt.axhline(i / float(N), color="k", linewidth=1)

    # Format plot
    _plot_formatting(title, os.path.basename(file_struct.audio_file), algo_ids,
                     all_boundaries[0][-1], N, None)
def plot_one_track(file_struct, est_times, est_labels, boundaries_id, labels_id,
                   title=None):
    """Plots the results of one track, with ground truth if it exists."""
    import matplotlib.pyplot as plt
    # Set up the boundaries id
    bid_lid = boundaries_id
    if labels_id is not None:
        bid_lid += " + " + labels_id
    try:
        # Read file
        jam = jams.load(file_struct.ref_file)
        ann = jam.search(namespace='segment_.*')[0]
        ref_inters, ref_labels = ann.to_interval_values()

        # To times
        ref_times = utils.intervals_to_times(ref_inters)
        all_boundaries = [ref_times, est_times]
        all_labels = [ref_labels, est_labels]
        algo_ids = ["GT", bid_lid]
    except:
        logging.warning("No references found in %s. Not plotting groundtruth"
                        % file_struct.ref_file)
        all_boundaries = [est_times]
        all_labels = [est_labels]
        algo_ids = [bid_lid]

    N = len(all_boundaries)

    # Index the labels to normalize them
    for i, labels in enumerate(all_labels):
        all_labels[i] = mir_eval.util.index_labels(labels)[0]

    # Get color map
    cm = plt.get_cmap('gist_rainbow')
    max_label = max(max(labels) for labels in all_labels)

    figsize = (8, 4)
    plt.figure(1, figsize=figsize, dpi=120, facecolor='w', edgecolor='k')
    for i, boundaries in enumerate(all_boundaries):
        color = "b"
        if i == 0:
            color = "g"
        for b in boundaries:
            plt.axvline(b, i / float(N), (i + 1) / float(N), color=color)
        if labels_id is not None:
            labels = all_labels[i]
            inters = utils.times_to_intervals(boundaries)
            for label, inter in zip(labels, inters):
                plt.axvspan(inter[0], inter[1], ymin=i / float(N),
                            ymax=(i + 1) / float(N), alpha=0.6,
                            color=cm(label / float(max_label)))
        plt.axhline(i / float(N), color="k", linewidth=1)

    # Format plot
    _plot_formatting(title, os.path.basename(file_struct.audio_file), algo_ids,
                     all_boundaries[0][-1], N, None)
def plot_one_track ( file_struct , est_times , est_labels , boundaries_id , labels_id , title = None ) : import matplotlib . pyplot as plt # Set up the boundaries id bid_lid = boundaries_id if labels_id is not None : bid_lid += " + " + labels_id try : # Read file jam = jams . load ( file_struct . ref_file ) ann = jam . search ( namespace = 'segment_.*' ) [ 0 ] ref_inters , ref_labels = ann . to_interval_values ( ) # To times ref_times = utils . intervals_to_times ( ref_inters ) all_boundaries = [ ref_times , est_times ] all_labels = [ ref_labels , est_labels ] algo_ids = [ "GT" , bid_lid ] except : logging . warning ( "No references found in %s. Not plotting groundtruth" % file_struct . ref_file ) all_boundaries = [ est_times ] all_labels = [ est_labels ] algo_ids = [ bid_lid ] N = len ( all_boundaries ) # Index the labels to normalize them for i , labels in enumerate ( all_labels ) : all_labels [ i ] = mir_eval . util . index_labels ( labels ) [ 0 ] # Get color map cm = plt . get_cmap ( 'gist_rainbow' ) max_label = max ( max ( labels ) for labels in all_labels ) figsize = ( 8 , 4 ) plt . figure ( 1 , figsize = figsize , dpi = 120 , facecolor = 'w' , edgecolor = 'k' ) for i , boundaries in enumerate ( all_boundaries ) : color = "b" if i == 0 : color = "g" for b in boundaries : plt . axvline ( b , i / float ( N ) , ( i + 1 ) / float ( N ) , color = color ) if labels_id is not None : labels = all_labels [ i ] inters = utils . times_to_intervals ( boundaries ) for label , inter in zip ( labels , inters ) : plt . axvspan ( inter [ 0 ] , inter [ 1 ] , ymin = i / float ( N ) , ymax = ( i + 1 ) / float ( N ) , alpha = 0.6 , color = cm ( label / float ( max_label ) ) ) plt . axhline ( i / float ( N ) , color = "k" , linewidth = 1 ) # Format plot _plot_formatting ( title , os . path . basename ( file_struct . audio_file ) , algo_ids , all_boundaries [ 0 ] [ - 1 ] , N , None )
Plots the results of one track, with ground truth if it exists.
Plots the results of one track with ground truth if it exists .