英文:
Dash: how to maintain selected legends when callback is triggered on histogram
问题
我正在使用Dash开发一个仪表板应用程序。我有一个回调函数，用于更改直方图的xbins大小，但当触发回调时，选定的图例会被重置（即之前取消选择的类别不再被选中）。
我想知道在触发回调时是否有一种方法可以保持先前选择的图例。
def make_histogram(df, xbin_type):
now = datetime.now()
tmr = now + timedelta(days=1)
fig = go.Figure()
for name in df['field'].unique():
df_of_table = df.loc[df['field'] == name]
fig.add_trace(go.Histogram(name=name, x=df_of_table['timestamp'],
xbins=dict(
start='2022-01-01',
end=tmr.strftime("%Y-%m-%d"),
size=xbin_type
)))
fig.update_layout(xaxis_title_text='Date', # x轴标签
yaxis_title_text='Count', # y轴标签
bargap=0.2, barmode='stack')
return fig
@callback(
Output('change-log-histogram', 'figure'),
Input('xbin-type', 'value')
)
def update_xbin(xbin_type):
if xbin_type == 'W1':
return make_histogram(df, 604_800_000)
return make_histogram(df, xbin_type)
我无法找到有关如何访问go.Figure并检索当前选择的迹线/类别/图例（不确定哪个术语是正确的）的任何信息。
英文:
I'm working on a dashboard app using Dash. I have a callback that changes the xbins size of a histogram but when the callback is fired, the selected legends are reset (ie no previously de-selected categories are selected again).
I'm wondering if there is a way to keep the previously selected legends when the callback is triggered.
def make_histogram(df, xbin_type):
now = datetime.now()
tmr = now + timedelta(days=1)
fig = go.Figure()
for name in df['field'].unique():
df_of_table = df.loc[df['field'] == name]
fig.add_trace(go.Histogram(name=name, x=df_of_table['timestamp'],
xbins=dict(
start='2022-01-01',
end=tmr.strftime("%Y-%m-%d"),
size=xbin_type
)))
fig.update_layout(xaxis_title_text='Date', # xaxis label
yaxis_title_text='Count', # yaxis label
bargap=0.2, barmode='stack')
return fig
@callback(
Output('change-log-histogram', 'figure'),
Input('xbin-type', 'value')
)
def update_xbin(xbin_type):
if xbin_type == 'W1':
return make_histogram(df, 604_800_000)
return make_histogram(df, xbin_type)
I cannot find any information about reaching into go.Figure and retrieve the currently selected trace/category/legend (not sure what's the right lingo)
答案1
得分: 0
为了"保留先前选择的图例"或保留图形的任何当前属性，您需要将图形添加为回调定义中的State（请参阅Basic Dash Callbacks文档中的"Dash App With State"部分）。
State允许您传递额外的值，而不触发回调。
例如：
@callback(
Output('change-log-histogram', 'figure'),
Input('xbin-type', 'value'),
State('change-log-histogram', 'figure'),
)
def update_xbin(xbin_type, current_figure):
# ...
这样，您可以在回调函数内访问图形的当前"状态"。您可以知道：
- 创建一个全新的图形，并从当前图形复制/粘贴一些属性（例如可见的跟踪），或者
- 如果更容易，只需更新当前图形并返回它。
State在需要更新交互式组件而不完全覆盖它时特别有用。
英文:
In order to "keep the previously selected legends", or to keep any current properties of the figure, you need to add the figure as a State in the callback definition (see the "Dash App With State" section of the Basic Dash Callbacks doc)
> State allows you to pass along extra values without firing the callbacks.
, something like:
@callback(
Output('change-log-histogram', 'figure'),
Input('xbin-type', 'value'),
State('change-log-histogram', 'figure'),
)
def update_xbin(xbin_type, current_figure):
# ...
That way, you have access to the figure's current "state" inside the callback function. You can know
- create a completely new figure and copy/paste some properties from the current figure to this new one (e.g which traces are visible), or
- if it's easier, simply update the current figure and return it.
State is particularly useful when one needs to update an interactive component without completely overwriting it.
通过集体智慧和协作来改善编程学习和解决问题的方式。致力于成为全球开发者共同参与的知识库，让每个人都能够通过互相帮助和分享经验来进步。
评论