Python FigureFactory.create_dendrogram方法代码示例

# 需要导入模块: from plotly.tools import FigureFactory [as 别名]
# 或者: from plotly.tools.FigureFactory import create_dendrogram [as 别名]
base = '/home/vanessa/Documents/Work/SINGULARITY'
results_folder = "%s/results" %(base)

results_files = glob("%s/*.tsv" %(results_folder))

# From https://plot.ly/python/dendrogram/, thanks plotly! :)

# Load each data file and make html heatmap
for results_file in results_files:
    data = pandas.read_csv(results_file,index_col=0,sep="\t")
    lookup = {x:x.split("-")[0] for x in data.index.tolist()}
    labels = [lookup[x] for x in data.index.tolist()]

    # Initialize figure by creating upper dendrogram
    figure = FF.create_dendrogram(data, orientation='bottom', labels=labels)
    for i in range(len(figure['data'])):
        figure['data'][i]['yaxis'] = 'y2'

    # Create Side Dendrogram
    dendro_side = FF.create_dendrogram(data, orientation='right')
    for i in range(len(dendro_side['data'])):
        dendro_side['data'][i]['xaxis'] = 'x2'

    # Add Side Dendrogram Data to Figure
    figure['data'].extend(dendro_side['data'])

    # Create Heatmap
    dendro_leaves = dendro_side['layout']['yaxis']['ticktext']
    dendro_leaves = list(map(int, dendro_leaves))
    data_dist = pdist(data)

# 需要导入模块: from plotly.tools import FigureFactory [as 别名]
# 或者: from plotly.tools.FigureFactory import create_dendrogram [as 别名]
 def __init__(self, dendrogram):
     x = np.array(dendrogram)
     fig = FigureFactory.create_dendrogram(x, orientation='left')
     fig['layout'].update({'width':800, 'height':800})
     plotly.offline.plot(fig, filename='dendrogram_with_labels')

# 需要导入模块: from plotly.tools import FigureFactory [as 别名]
# 或者: from plotly.tools.FigureFactory import create_dendrogram [as 别名]
    def generate_dendrogram(self):
        labels = self.names
        x = np.array(self.data.distance_matrix)

        # Initialize figure by creating upper dendrogram
        figure = FF.create_dendrogram(x, orientation='bottom', labels=labels)
        for i in range(len(figure['data'])):
            figure['data'][i]['yaxis'] = 'y2'

        # Create Side Dendrogram
        dendro_side = FF.create_dendrogram(x, orientation='right')
        for i in range(len(dendro_side['data'])):
            dendro_side['data'][i]['xaxis'] = 'x2'

        # Add Side Dendrogram Data to Figure
        figure['data'].extend(dendro_side['data'])

        # Create Heatmap
        dendro_leaves = dendro_side['layout']['yaxis']['ticktext']
        dendro_leaves = list(map(int, dendro_leaves))
        data_dist = pdist(x)
        heat_data = squareform(data_dist)
        heat_data = heat_data[dendro_leaves,:]
        heat_data = heat_data[:,dendro_leaves]

        heatmap = go.Data([
            go.Heatmap(
                x = dendro_leaves,
                y = dendro_leaves,
                z = heat_data,
                colorscale = 'YIGnBu'
            )
        ])

        heatmap[0]['x'] = figure['layout']['xaxis']['tickvals']
        heatmap[0]['y'] = dendro_side['layout']['yaxis']['tickvals']

        # Add Heatmap Data to Figure
        figure['data'].extend(go.Data(heatmap))

        # Edit Layout
        figure['layout'].update({'width':1600, 'height':1600,
                                 'showlegend':False, 'hovermode': 'closest',
                                 'margin': { 'b': 400 }
                                 })

        # Edit xaxis
        figure['layout']['xaxis'].update({'domain': [.15, 1],
                                          'mirror': False,
                                          'showgrid': False,
                                          'showline': False,
                                          'zeroline': False,
                                          'ticks':""})
        # Edit xaxis2
        figure['layout'].update({'xaxis2': {'domain': [0, .15],
                                           'mirror': False,
                                           'showgrid': False,
                                           'showline': False,
                                           'zeroline': False,
                                           'showticklabels': False,
                                           'ticks':""}})

        # Edit yaxis
        figure['layout']['yaxis'].update({'domain': [0, .85],
                                          'mirror': False,
                                          'showgrid': False,
                                          'showline': False,
                                          'zeroline': False,
                                          'showticklabels': False,
                                          'ticks': ""})
        # Edit yaxis2
        figure['layout'].update({'yaxis2':{'domain':[.825, .975],
                                           'mirror': False,
                                           'showgrid': False,
                                           'showline': False,
                                           'zeroline': False,
                                           'showticklabels': False,
                                           'ticks':""}})

        # Plot!
        plotly.offline.plot(figure, filename='output/dendrogram_with_heatmap.html')

# 需要导入模块: from plotly.tools import FigureFactory [as 别名]
# 或者: from plotly.tools.FigureFactory import create_dendrogram [as 别名]
def generate_dendrogram_plotly(json_data, tree_filename="infomap/output/"+"author_graph.tree"):
    author_graph = nx.Graph()
    dist_queue = linkage_matrix = pair_queue = list()

    print("Reading author UIDs from JSON file...")
    with open('author_uid_map.json', 'r') as map_file:
        author_uid_map = json.load(map_file)
        map_file.close()

    # Use node_limit to limit the number of authors
    # node_limit = len(author_uid_map)
    node_limit = 100

    # buffer_queue = numpy.ndarray((node_limit,2), dtype=float)
    #
    # print("Adding nodes to author's graph...")
    # for msg_id, message in json_data.items():
    #     if message['Cc'] is None:
    #         addr_list = message['To']
    #     else:
    #         addr_list = message['To'] | message['Cc']
    #     for to_address in addr_list:
    #         if author_graph.has_edge(message['From'], to_address):
    #             author_graph[message['From']][to_address]['weight'] *= \
    #                 author_graph[message['From']][to_address]['weight'] / (author_graph[message['From']][to_address]['weight'] + 1)
    #         else:
    #             author_graph.add_edge(message['From'], to_address, weight=1)
    # shortest_paths = nx.single_source_shortest_path_length(author_graph, '[email protected]')
    #
    # print("Parsing", tree_filename + "...")
    # with open(tree_filename, 'r') as tree_file:
    #     for line in tree_file:
    #         if not line or line[0] == '#':
    #             continue
    #         line = line.split()
    #         author_uid = author_uid_map[line[2][1:-1]]
    #         if author_uid < node_limit:
    #             if line[2][1:-1] in shortest_paths.keys():
    #                 buffer_queue[author_uid][0] = shortest_paths[line[2][1:-1]]
    #             else:
    #                 buffer_queue[author_uid][0] = 1000.0
    #             buffer_queue[author_uid][1] = float(line[1])
    #     tree_file.close()


    dist_matrix = numpy.ndarray((node_limit, node_limit), dtype=float)

    for msg_id, message in json_data.items():
        if author_uid_map[message['From']] < node_limit:
            if message['Cc'] is None:
                addr_list = message['To']
            else:
                addr_list = message['To'] | message['Cc']
            for to_address in addr_list:
                if author_uid_map[to_address] < node_limit:
                    if author_graph.has_edge(message['From'], to_address):
                        author_graph[message['From']][to_address]['weight'] *= \
                            author_graph[message['From']][to_address]['weight'] / (
                            author_graph[message['From']][to_address]['weight'] + 1)
                    else:
                        author_graph.add_edge(message['From'], to_address, weight=1)
    shortest_paths = nx.all_pairs_shortest_path_length(author_graph)
    print("Nodes added to the author's graph.")

    for i1 in author_graph.nodes():
        for i2 in author_graph.nodes():
            if i2 in shortest_paths[i1]:
                dist_matrix[author_uid_map[i1]][author_uid_map[i2]] = shortest_paths[i1][i2]
            else:
                dist_matrix[author_uid_map[i1]][author_uid_map[i2]] = 100

    print("Drawing the dendrogram...")
    # linkage_matrix = linkage(buffer_queue, 'single')
    # dendro = FF.create_dendrogram(linkage_matrix)

    dendro = FF.create_dendrogram(dist_matrix)
    dendro['layout'].update({'width': 1200, 'height': 800})
    plotly.offline.plot(dendro, filename='dendrogram_infomaps.html')