NetworkX Plot 標題 - 交互式繪圖

Question

我一直在關注可視化多重共線性的教程，並一直在構建交互式網絡圖。 我想為 plot 添加一個標題，我發現這個SO question我認為這會有所幫助，但它與交互式 plot 無關，當我嘗試答案時，我最終得到了相同的交互式圖表，沒有標題，並且然后是一個小的空的非交互式 plot 下面有一個標題。

我的代碼目前看起來像：

plt.title('Network Graph Showing Correlated Metabolites at Adjustable Correlation Thresholds')
threshold_choice = widgets.FloatSlider(description="Threshold", value=0.8, min=0.1, max=1, step=0.05, 
                                    continuous_update=False, orientation='horizontal', layout=Layout(width='500px'), 
                                    style=dict(description_width= 'initial'))

network = go.FigureWidget(data=[go.Scatter(x=[], y=[], mode='lines', text=[],  line=dict(color='#cc78bc', width=2.5), 
                                    marker=dict(size=16, line_width=5,line=dict(color='#cc78bc',width=2))),
                                    go.Scatter(x=[], y=[],mode='markers+text', textposition="top center", text=[], 
                                    hoverinfo='text',textfont_size=12, marker=dict(size=10, color=[],line_width=1))],
                                    layout=go.Layout( showlegend=False, annotations=[], margin=dict(t=40, b=0, l=0, r=0), 
                                    width=950, height=800))
df = AlzZ.copy()
correlation_matrix = cor.to_numpy()

def plot_corr_graph(change):
    threshold, corr_mode = None, None
    threshold = change.new
    
    tr_ind = np.triu_indices(correlation_matrix.shape[0])
    correlation_matrix[tr_ind] = 0
    G = nx.from_numpy_matrix(correlation_matrix)
    G = nx.relabel_nodes(G, lambda x: df.columns.tolist()[x])
   
    remove = []
    
    for col1, col2, weight in G.edges(data=True):
      if math.isnan(weight["weight"]):
        remove.append((col1,col2))
    
      if abs(weight["weight"]) < threshold:
        remove.append((col1,col2))
    
    G.remove_edges_from(remove)
    
    remove = []
    edges = list(sum(G.edges, ()))
    
    for node in G.nodes:
      if node not in edges:
        remove.append(node)
    G.remove_nodes_from(remove)
    mst = nx.maximum_spanning_tree(G)
    
    def assign_color(col):
      return colorlistMCLN

    def assign_color_edge(correlation):
      if correlation < 0:
        return "#BF0603"
      else:
        return "#00CC66"
    edge_colors = []
    node_colors = []
    for key, value in nx.get_edge_attributes(mst, 'weight').items():
        edge_colors.append(assign_color_edge(value))
    for key, value in dict(mst.degree).items():
        node_colors.append(assign_color(key))
      
    labels = {n:n for n in mst.nodes()}
    node_x = []
    node_y = []
    
    tree = nx.fruchterman_reingold_layout(mst, k=0.25).items()
    
    for node, (x_,y_) in tree:
        node_x.append(x_)
        node_y.append(y_)
        
    def get_dim_of_node(name):
        for node, (x,y) in tree:
            if node == name:
                return x,y
        
    edge_x = []
    edge_y = []
    
    weights= []
    for node1, node2, w in mst.edges(data=True):
        x0, y0 = get_dim_of_node(node1)
        x1, y1 =  get_dim_of_node(node2)
        edge_x.append(x0)
        edge_x.append(x1)
        edge_x.append(None)
        edge_y.append(y0)
        edge_y.append(y1)
        edge_y.append(None)
        weights.append((round(w["weight"],1), (x0+x1)/2, (y0+y1)/2))
                              
    with network.batch_update():
        network.data[1].x = node_x
        network.data[1].y = node_y
        network.data[1].text = list(labels)
        network.data[1].marker.color = node_colors
                          
        network.data[0].x = edge_x
        network.data[0].y = edge_y
        network.data[0].text = list(weights)
        network.update_layout(xaxis_zeroline=False, yaxis_zeroline=False, xaxis_showgrid=False, yaxis_showgrid=False, 
                              plot_bgcolor='rgba(0,0,0,0)')

threshold_choice.observe(plot_corr_graph, names="value")
widgets.VBox([threshold_choice, network])

我的 output 看起來像： output 圖像

我也試過把

plt.title('title')

在 threshold_choice object 和網絡 object 之間，並嘗試過

ax = plt.gca()
ax.set_title('title')

在correlation_matrix object下方 - 結果相同。

當我將它放在 function 中，低於閾值 object 時，它沒有產生任何帶有標題的圖，只是原始網絡圖。

Answer 1

我想通了：

問題是從代碼的角度來看，交互式圖實際上根本不是 plot。 它是一個FigureWidget 。 了解這一點可以更輕松地找到正確的文檔。

最初我一直在看這里： NetworkX Documentation

但是，您實際上需要查看 plotly 文檔中的此頁面。

在上面的示例中（在問題中），這意味着將網絡 object 更改為：

network = go.FigureWidget(data=[go.Scatter(x=[], y=[], mode='lines', text=[],  line=dict(color='#cc78bc', width=2.5), 
                                    marker=dict(size=16, line_width=5,line=dict(color='#cc78bc',width=2))),
                                    go.Scatter(x=[], y=[],mode='markers+text', textposition="top center", text=[], 
                                    hoverinfo='text',textfont_size=12, marker=dict(size=10, color=[],line_width=1))],
                                    layout=go.Layout(showlegend=False, annotations=[], margin=dict(t=40, b=0, l=0, r=0), 
                                    width=950, height=800, title='Network Graph Showing Correlated Metabolites at Adjustable Correlation Thresholds')) 

標題作為title='your title'包含在布局參數中