Пример #1
0
def save_plot(name, threshold, save_name='default', level="INFO"):
    from view import plot_utils
    path = resource_manager.Properties.getDefaultDataFold(
    ) + "result/temp/" + name + "/" + save_name + "/" "threshold.png"

    plot_utils.save_scatter_diagram(None,
                                    x=threshold['d_c'].values,
                                    y=threshold['H'].values,
                                    x_label='delta',
                                    y_label='H',
                                    title='threshold scatter figure',
                                    path=path)

    plot_utils.save_scatter_diagram(None,
                                    x=threshold['d_c'].values,
                                    y=threshold['H'].values,
                                    x_label='delta',
                                    y_label='H',
                                    title='threshold scatter figure',
                                    path=path)
    if level == "DEBUG":
        plot_utils.plot_scatter_diagram(None,
                                        x=threshold['d_c'].values,
                                        y=threshold['H'].values,
                                        x_label='delta',
                                        y_label='H',
                                        title='threshold scatter figure')
        plot_utils.plot_scatter_diagram(None,
                                        x=threshold['H'].values,
                                        y=threshold['d_c'].values,
                                        x_label='delta',
                                        y_label='H',
                                        title='threshold scatter figure')
Пример #2
0
def show_cluster(index_id, data, distance_c, pile_id):
    from view import plot_utils
    pile_id = pile_id.sort_values('size', ascending=False)
    x = []
    y = []
    label = []
    i = 1
    for m in range(len(pile_id)):
        # l=pile_id.irow(m)['pile']
        l = pile_id.iloc[m]['pile']
        # size=pile_id.irow(m)['size']
        size = pile_id.iloc[m]['size']
        if size >= 1 and i < 15:
            for node in l:
                index = index_id[node]
                x.append(data[index][0])
                y.append(data[index][1])
                label.append(i)
            i = i + 1
        else:
            for node in l:
                index = index_id[node]
                x.append(data[index][0])
                y.append(data[index][1])
                label.append(0)

    plot_utils.plot_scatter_diagram(None,
                                    x=x,
                                    y=y,
                                    x_label='x',
                                    y_label='y',
                                    title='scatter figure',
                                    label=label)

    log.debug(pile_id)
Пример #3
0
def save_show_cluster(index_id, data, distance_c, pile_id, dataset="/", level="INFO", level_info='scatter figure'):
    from view import plot_utils
    from context import resource_manager
    path = resource_manager.Properties.getDefaultDataFold() + "result" + resource_manager.getSeparator() + "temp/" + dataset + "/" + resource_manager.Properties.name_str_static() + "/"

    level_path = resource_manager.Properties.getDefaultDataFold() + "result" + resource_manager.getSeparator() + "temp/" + level + "/" + resource_manager.Properties.name_str_static() + "/" + str(
        distance_c) + "/"

    if not os.path.exists(path[:path.rfind('/')]):
        os.makedirs(path[:path.rfind('/')])
    if not os.path.exists(level_path[:level_path.rfind('/')]):
        os.makedirs(level_path[:level_path.rfind('/')])

    pile_id = pile_id.sort_values('size', ascending=False)
    x = []
    y = []
    label = []
    i = 1
    for m in range(len(pile_id)):
        # l=pile_id.irow(m)['pile']
        l = pile_id.iloc[m]['pile']
        # size=pile_id.irow(m)['size']
        size = pile_id.iloc[m]['size']

        if pile_id.loc[m]['outlier'] is False:
            for node in l:
                index = index_id[node]
                x.append(data[index][0])
                y.append(data[index][1])
                label.append(i)
            i = i + 1
        else:
            for node in l:
                index = index_id[node]
                x.append(data[index][0])
                y.append(data[index][1])
                label.append(0)
    if level is "SEE":
        plot_utils.plot_scatter_diagram(None, x=x, y=y, x_label='x', y_label='y', title=level_info, label=label)
    if level is "DEBUG":
        # plot_utils.save_scatter_diagram(None, x=x, y=y, x_label='x', y_label='y', title='scatter figure', label=label,path=level_path+resource_manager.Properties.name_str_FULL()+".png")

        plot_utils.save_all_scatter_diagram(None, x=x, y=y, x_label='x', y_label='y', title=level_info, label=label,
                                            path=level_path + resource_manager.Properties.name_str_FULL() + ".png")
    else:
        plot_utils.save_scatter_diagram(None, x=x, y=y, x_label='x', y_label='y', title='scatter figure', label=label,
                                        path=path + str(
                                            distance_c) + ".png")
        plot_utils.save_all_scatter_diagram(None, x=x, y=y, x_label='x', y_label='y', title='scatter figure',
                                            label=label,
                                            path=path + str(
                                                distance_c) + ".png")

    # plot_utils.plot_scatter_diagram(None, x=x, y=y, x_label='x', y_label='y', title='scatter figure', label=label)
    log.debug(("\n") + str(pile_id))
    try:
        p = Properties.getDefaultDataFold() + "/csv/" + dataset + "/" + resource_manager.Properties.name_str_static() + "/" + str(
            distance_c) + ".csv"
        pile_id.to_csv(p)
    except:
        if not os.path.exists(p[:p.rfind('/')]):
            pp = p.rfind('/')
            os.makedirs(p[:pp])
        os.mknod(p)
        pile_id.to_csv(p)
Пример #4
0

if __name__ == '__main__':
    get_threshold()
    from context.resource_manager import Properties
    from view import shape_view
    from view import plot_utils
    from cluster import density_cluster
    threshold = pandas.read_csv(Properties.getDefaultDataFold() +
                                "/csv/threshold.csv")
    d_c = np.asarray(threshold['d_c'].values)
    log.debug(d_c)
    log.critical(type(d_c))
    plot_utils.plot_scatter_diagram(None,
                                    x=d_c,
                                    y=threshold['H'].values,
                                    x_label='delta',
                                    y_label='H',
                                    title='threshold scatter figure')
    """
    delta_index=Series(id,index=id,dtype=np.float)

    i=0
    order_id=Series(result[:,0],index=id_index.values)
    # to find the rho_j>rho_i
    order_id=order_id.sort_values()
    j=order_id.index[1]
    # to find the
    j=int(index_id[j])
    # to find the i'key
    k=str(id_index[i])