How to get access to selection source in multiple selections in Graph's selectedData

Dash Python
1

Hello!
I would like to plot an average signal (graph below) for each separate selection in the scatterplot (top graph). The problem is that I cannot differentiate between different selections.
curveNumber in selectedData is always 0 in my case. Is there a way to extract this information? Thank you!

def update_scatterplot():
    fig = go.Figure()
    fig.add_trace(go.Scatter(
        x=df['water'],
        y=df['cell'],
        mode='markers',
        marker=dict(size=10, opacity=0.7, color=df['lysis'].astype("category").cat.codes, colorscale='Viridis'),
        # customdata=np.arange(len(df)),  # Ensure customdata matches signal_array indices
        name="Scatterplot"
    ))
    fig.update_layout(
        title="Scatterplot",
        xaxis_title="X-axis",
        yaxis_title="Y-axis",
        dragmode='select'
    )
    return fig

# Initialize Dash app
app = Dash(__name__)

styles = {
    'pre': {
        'border': 'thin lightgrey solid',
        'overflowX': 'scroll'
    }
}

# Layout of the app
app.layout = html.Div([
    dcc.Graph(
        id='scatterplot',
        figure=update_scatterplot(),
    ),
    dcc.Graph(id='signal-plot'),
    html.Div([
        dcc.Markdown("**Selection Data**"),
        html.Pre(id='selected-data', style=styles['pre']),
    ], className='three columns'),
])



@app.callback(
    Output('selected-data', 'children'),
    Input('scatterplot', 'selectedData')
    )
def display_selected_data(selectedData):
    return json.dumps(selectedData, indent=2)

# Callback to update signal plot based on selection
@app.callback(
    Output('signal-plot', 'figure'),
    Input('scatterplot', 'selectedData')
)
def update_signal_plot(selected_data):
    fig = go.Figure()
    print(selected_data)
    if selected_data:
        # Extract selected points
        selected_ids = [point['pointIndex'] for point in selected_data['points']]
        avg_signal = signal_array[selected_ids, :].mean(axis=0)
    else:
        avg_signal = signal_array.mean(axis=0)

    # Create line plot for the average signal
    fig.add_trace(go.Scatter(
        x=wl,
        y=avg_signal,
        mode='lines',
        name="Average Signal"
    ))

    fig.update_layout(
        title="Average Signal",
        xaxis_title="Timepoint",
        yaxis_title="Signal Value"
    )

    return fig

The selectedData for the provided image:

{
  "points": [
    {
      "curveNumber": 0,
      "pointNumber": 19,
      "pointIndex": 19,
      "x": 0.23084526968953495,
      "y": 0.2632524731791809,
      "customdata": 19,
      "marker.color": 1
    },
    # ...
    {
      "curveNumber": 0,
      "pointNumber": 9983,
      "pointIndex": 9983,
      "x": 0.04727233565169021,
      "y": 0.5013248475937009,
      "customdata": 9983,
      "marker.color": 0
    }
  ],
  "range": {
    "x": [
      0.14421608454120896,
      0.2879316670537672
    ],
    "y": [
      0.15162525690270545,
      0.3464139081061809
    ]
  }
}

image
image923×853 115 KB