Add component to choose experiment parameters v. simulation parameters

[EZoni]

Add a switch (e.g., VSwitch) or button (e.g., VBtnToggle) that allows the user to choose whether the parameters displayed in the sliders and plots are the experiment parameters or the simulation parameters (which can be mapped into each other through the calibration constants).

Options:

1. Add a secondary x-axis at the top of each plot to display the simulation parameter axis, with the experiment parameter axis remaining at the bottom. I think this is the simplest and most effective solution, but I have not managed to make it work with Plotly yet...
2. Add a switch or button and reload both the parameters panel and the plot panel when the switch or button is toggled. This is more complicated as it requires reloading the panels, possibly losing the current status of the state.
3. Display both the experiment parameters and the simulation parameters simultaneously in separate plots. We may not have enough horizontal space to accomodate two plots per row.

[EZoni]

FYI, this is a minimal working example for option 1. above, but I have not managed to make it work with the more complex Plotly figures in our dashboard:

import pandas as pd
import plotly.graph_objects as go
from plotly.graph_objs.layout import XAxis, YAxis
import numpy as np

# 1. Create a sample DataFrame
df = pd.DataFrame({
    'Days': [1, 2, 3, 4, 5],
    'Dates': pd.to_datetime(['2025-01-01', '2025-01-02', '2025-01-03', '2025-01-04', '2025-01-05']),
    'Value': [43, 45, 52, 55, 63]
})

# 2. Initialize the figure with the primary x-axis data
fig = go.Figure()

# 3. Add the primary trace (uses default 'x' and 'y' axes)
fig.add_trace(go.Scatter(
    x=df['Days'],
    y=df['Value'],
    mode='lines+markers',
    name='Data by Days'
))

# Add a transparent trace that references the secondary x-axis ('x2')
# This trace doesn't add new visual data but binds the 'Dates' column to the 'x2' axis definition.
fig.add_trace(go.Scatter(
    x=df['Dates'],
    y=df['Value'], # Use the same y-values
    opacity=0, # Make the trace invisible
    showlegend=False,
    xaxis='x2'
))

# 4. Update the layout to define and position the secondary x-axis
fig.update_layout(
    title='Plot with Two X-Axes',
    xaxis=dict(
        title='Days (Primary X-Axis)',
        domain=[0, 1] # Occupy the full width
    ),
    yaxis=dict(
        title='Value (Y-Axis)'
    ),
    xaxis2=dict(
        title='Dates (Secondary X-Axis)',
        overlaying='x', # Overlay on top of the primary x-axis
        side='top',     # Position it at the top of the plot
        anchor='y',     # Anchor to the y-axis
        showgrid=False  # Optional: hide the grid lines for the secondary axis
    )
)

fig.show()