msaf/plotting.py
def plot_boundaries(all_boundaries, est_file, algo_ids=None, title=None,
                    output_file=None):
    """Plots all the boundaries.

    Parameters
    ----------
    all_boundaries: list
        A list of np.arrays containing the times of the boundaries, one array
        for each algorithm.
    est_file: str
        Path to the estimated file (JSON file)
    algo_ids : list
        List of algorithm ids to to read boundaries from.
        If None, all algorithm ids are read.
    title : str
        Title of the plot. If None, the name of the file is printed instead.
    """
    import matplotlib.pyplot as plt
    N = len(all_boundaries)  # Number of lists of boundaries
    if algo_ids is None:
        algo_ids = io.get_algo_ids(est_file)

    # Translate ids
    for i, algo_id in enumerate(algo_ids):
        algo_ids[i] = translate_ids[algo_id]
    algo_ids = ["GT"] + algo_ids

    figsize = (6, 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)
        plt.axhline(i / float(N), color="k", linewidth=1)

    # Format plot
    _plot_formatting(title, est_file, algo_ids, all_boundaries[0][-1], N,
                     output_file)
def plot_boundaries(all_boundaries, est_file, algo_ids=None, title=None,
                    output_file=None):
    import matplotlib.pyplot as plt
    N = len(all_boundaries)  # Number of lists of boundaries
    if algo_ids is None:
        algo_ids = io.get_algo_ids(est_file)

    # Translate ids
    for i, algo_id in enumerate(algo_ids):
        algo_ids[i] = translate_ids[algo_id]
    algo_ids = ["GT"] + algo_ids

    figsize = (6, 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)
        plt.axhline(i / float(N), color="k", linewidth=1)

    # Format plot
    _plot_formatting(title, est_file, algo_ids, all_boundaries[0][-1], N,
                     output_file)
def plot_boundaries ( all_boundaries , est_file , algo_ids = None , title = None , output_file = None ) : import matplotlib . pyplot as plt N = len ( all_boundaries ) # Number of lists of boundaries if algo_ids is None : algo_ids = io . get_algo_ids ( est_file ) # Translate ids for i , algo_id in enumerate ( algo_ids ) : algo_ids [ i ] = translate_ids [ algo_id ] algo_ids = [ "GT" ] + algo_ids figsize = ( 6 , 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 ) plt . axhline ( i / float ( N ) , color = "k" , linewidth = 1 ) # Format plot _plot_formatting ( title , est_file , algo_ids , all_boundaries [ 0 ] [ - 1 ] , N , output_file )
Plots all the boundaries.

    Parameters
    ----------
    all_boundaries: list
        A list of np.arrays containing the times of the boundaries, one array
        for each algorithm.
    est_file: str
        Path to the estimated file (JSON file)
    algo_ids : list
        List of algorithm ids to to read boundaries from.
        If None, all algorithm ids are read.
    title : str
        Title of the plot. If None, the name of the file is printed instead.
Plots all the boundaries .