所以我一直在尝试从那里的散景示例中构建一些东西：https://demo.bokehplots.com/apps/weather。
我的数据集非常相似，这应该非常直接，但我有一个我无法解释的问题。
import os , pickle
import pandas as pd
from bokeh.io import curdoc
from bokeh.layouts import row, column
from bokeh.models import ColumnDataSource, Select
from bokeh.plotting import figure
base_path = '/Users/xxxxxx/Desktop/data/'
domain = 'IEM_Domain'
metric = 'total_area_burned'
def get_dataset(dic , selection , scenario):
def _get_mean(thing):
_df = pd.DataFrame(thing)
_df = _df.mean(axis = 1).cumsum(axis=0)
return _df
data = { model : _get_mean( dic[model] ) for model in dic.keys() if all([scenario in model , selection in model])}
df = pd.DataFrame(data)
return ColumnDataSource(data=df)
def make_plot(source, title):
plot = figure(x_axis_type="datetime", plot_width=800, tools="")
plot.title.text = title
for _df in source :
for col in _df.to_df().columns :
if 'index' not in col :
plot.line( _df.to_df()['index'] , _df.to_df()[col] , source = _df)
else : pass
# fixed attributes
plot.xaxis.axis_label = 'Year'
plot.yaxis.axis_label = "Area burned (km)"
plot.axis.axis_label_text_font_style = "bold"
return plot
def update_plot(attrname, old, new):
rcp45 = rcp45_select.value
rcp85 = rcp85_select.value
src45 = get_dataset(dic , rcp45 , 'rcp45')
src85 = get_dataset(dic , rcp85 , 'rcp85')
source45.data = src45.data
source85.data = src85.data
rcp45 = 'CCSM4_rcp45'
rcp85 = 'CCSM4_rcp85'
dic = pickle.load(open(os.path.join(base_path , "_".join([domain , metric ]) + '.p'), 'rb'),encoding='latin1')
rcp45_models = [ i for i in dic.keys() if 'rcp45' in i]
rcp85_models = [ i for i in dic.keys() if 'rcp85' in i]
rcp45_select = Select(value=rcp45, title='RCP 45', options=sorted(rcp45_models))
rcp85_select = Select(value=rcp85, title='RCP 85', options=sorted(rcp85_models))
source45 = get_dataset(dic , rcp45 , 'rcp45')
source85 = get_dataset(dic , rcp85 ,'rcp85')
print(source45.data)
plot = make_plot([source45 , source85], "Total area burned ")
rcp45_select.on_change('value', update_plot)
rcp85_select.on_change('value', update_plot)
controls = column(rcp45_select, rcp85_select)
curdoc().add_root(row(plot, controls))
curdoc().title = "Total Area burned"
在我尝试更改下拉列表中的值之前，所有内容都会运行，我可以看到函数update_plot()正在执行此任务，在使用下拉列表时更新数据。但由于某种原因，情节不会改变，但这个例子工作得很好。我一直在挖掘代码中的任何地方，但似乎无法找到我做错了什么。
我试图简化make_plot（）以查看它是否可以来自那里，但这并没有改变任何东西，所以我没有想法。
我发现但无法应用它：Bokeh: chart from pandas dataframe won't update on trigger
第一次回答后编辑
我试图乘坐columndatasource并将其替换为传统的词典但仍然遇到同样的问题。 这是更新的代码：
import os , pickle
import pandas as pd
from bokeh.io import curdoc
from bokeh.layouts import row, column
from bokeh.models import ColumnDataSource, Select
from bokeh.plotting import figure
base_path = '/Users/julienschroder/Desktop/data/'
domain = 'IEM_Domain'
metric = 'total_area_burned'
scenarios = ['rcp45','rcp85']
def get_dataset(dic ,selection , scenario = scenarios):
#function taking the raw source as dic and a selection of models, it return a dictionnary
# like this {scenario : pd.Dataframe(models)} that way i can plot each scenario on their own
def _get_mean_cumsum(df ,name):
#Extract, average and cumsum the raw data to a dataframe
_df = pd.DataFrame(df)
_df = _df.mean(axis = 1).cumsum(axis=0)
_df = _df.to_frame(name=name)
return _df
#Just one model at a time for now but hoping to get multilines and so multi models in the future
data = { scenario : pd.concat([_get_mean_cumsum(dic[model] , model) for model in selection if scenario in model ] ,axis=1) for scenario in scenarios }
return data
def make_plot(source, title):
plot = figure(x_axis_type="datetime", plot_width=800, tools="")
plot.title.text = title
#for now it will just deal with one model at a time but in the future I hope to have some multiline plotting hence the for loops
for col in source['rcp45']:
plot.line(source['rcp45'].index,source['rcp45'][col] )
for col in source['rcp85']:
plot.line(source['rcp85'].index , source['rcp85'][col])
# fixed attributes
plot.xaxis.axis_label = 'Year'
plot.yaxis.axis_label = "Area burned (km)"
plot.axis.axis_label_text_font_style = "bold"
return plot
def update_plot(attrname, old, new):
rcp45 = rcp45_select.value
rcp85 = rcp85_select.value
source = get_dataset(dic,[rcp45 ,rcp85])
#check to see if source gets updated
print(source) # <- gets updated properly after dropdown action
rcp45 = 'CCSM4_rcp45'
rcp85 = 'CCSM4_rcp85'
# dic = pickle.load(open(os.path.join(base_path , "_".join([domain , metric ]) + '.p'), 'rb'),encoding='latin1')
dic = pickle.load(open('IEM_Domain_total_area_burned.p', 'rb'),encoding='latin1') #data available there : https://github.com/julienschroder/Bokeh_app/tree/master/1
rcp45_models = [ i for i in dic.keys() if 'rcp45' in i]
rcp85_models = [ i for i in dic.keys() if 'rcp85' in i]
rcp45_select = Select(value=rcp45, title='RCP 45', options=sorted(rcp45_models))
rcp85_select = Select(value=rcp85, title='RCP 85', options=sorted(rcp85_models))
source = get_dataset(dic,[rcp45 ,rcp85])
plot = make_plot(source , "Total area burned ")
rcp45_select.on_change('value', update_plot)
rcp85_select.on_change('value', update_plot)
controls = column(rcp45_select, rcp85_select)
curdoc().add_root(row(plot, controls))
curdoc().title = "Total Area burned"
我得到了我的两个第一行，但在使用下拉列表时没有任何反应。 如果有人想要试用数据，我在这个github页面上传了一个较小的数据集 https://github.com/julienschroder/Bokeh_app/tree/master/1
答案 0 :(得分：2)
好吧，我不能100％肯定地说，因为我没有数据就无法运行代码，但我对这个问题可能有什么好主意。 .data属性ColumnDataSource实际上不是一个简单的Python字典：
In [4]: s = ColumnDataSource(data=dict(a=[1,2], b=[3,4]))
In [5]: type(s.data)
Out[5]: bokeh.core.property.containers.PropertyValueDict
它实际上是一个特殊包装的字典，可以在内容更改时自动发出事件通知。这是让Bokeh以这种方便的方式自动响应和更新事物的机器的一部分。我猜测使用另一个来源的.data来设置一个来源的.data是导致问题的原因。我假设除了真正的Python dicts之外的东西设置.data可以防止事件处理程序无法正确连接。
因此，建议立即使用解决方法：不要在ColumnDataSource中构建get_dataset。只构造并返回一个普通的Python字典。 df.to_dict可能只会给你一个正确的dict。或者你可以手工制作一个词典，放入你需要的列。
请求：可能会修复此限制。或者如果没有，如果用户这样做，当然可以发出响亮的警告。请在GitHub issue tracker上提交包含所有这些信息的错误报告。