#範例4-23：桑基圖：桑基圖通過定義視覺化到流動的貢獻源來表示源節點，目標為目標節點，數值以設置流volum，和標籤，顯示了節點名稱,在流量分析中常用
import plotly.graph_objects as go 
import urllib, json 
 
url = 'https://raw.githubusercontent.com/plotly/plotly.js/master/test/image/mocks/sankey_energy.json' 
response = urllib.request.urlopen(url) 
data = json.loads(response.read()) 
 
# override gray link colors with 'source' colors 
opacity = 0.4 
# change 'magenta' to its 'rgba' value to add opacity 
data['data'][0]['node']['color'] = ['rgba(255,0,255, 0.8)' if color == "magenta" else color for color in data['data'][0]['node']['color']] 
data['data'][0]['link']['color'] = [data['data'][0]['node']['color'][src].replace("0.8", str(opacity)) 
                                    for src in data['data'][0]['link']['source']] 
 
fig = go.Figure(data=[go.Sankey( 
    valueformat = ".0f", 
    valuesuffix = "TWh", 
    # Define nodes 
    node = dict( 
      pad = 15, 
      thickness = 15, 
      line = dict(color = "black", width = 0.5), 
      label =  data['data'][0]['node']['label'], 
      color =  data['data'][0]['node']['color'] 
    ), 
    # Add links 
    link = dict( 
      source =  data['data'][0]['link']['source'], 
      target =  data['data'][0]['link']['target'], 
      value =  data['data'][0]['link']['value'], 
      label =  data['data'][0]['link']['label'], 
      color =  data['data'][0]['link']['color'] 
))]) 
 
fig.update_layout(title_text="Energy forecast for 2050<br>Source: Department of Energy & Climate Change, Tom Counsell via <a href='https://bost.ocks.org/mike/sankey/'>Mike Bostock</a>", 
                  font_size=10) 

fig.write_html('exp4-23.html', auto_open=True)