Projection of 2d density contour on 3D volume axis

[andcar]

Hi all, I’m new to plotly and to this forum. I’m still studying how to use plotly at it’s max capabilities. Sorry for the long post , but I’m trying to merge these plots in a single combined plot.
I really don’t know how to move.

1. 3D volume plot of two series of data (S) and (R)

# Create the 3D volume plot for 'S' series
fig_s = go.Figure(data=go.Volume(
    x=X.flatten(), y=Y.flatten(), z=Z.flatten(),
    value=density_values_s.flatten(),
    isomin=density_s.min(),
    isomax=density_s.max(),
    opacity=0.1,
    surface_count=25,
    colorscale='PuBu',
    colorbar={"title": 'Density (S)', "showticksuffix": 'none'}  # Combine colorbar properties into a single dictionary
))

# Create the 3D volume plot for 'R' series
fig_r = go.Figure(data=go.Volume(
    x=X.flatten(), y=Y.flatten(), z=Z.flatten(),
    value=density_values_r.flatten(),
    isomin=density_r.min(),
    isomax=density_r.max(),
    opacity=0.1,
    surface_count=25,
    colorscale='Reds',
    colorbar={"title": 'Density (R)', "showticksuffix": 'none', }  # Combine colorbar properties into a single dictionary
))

# Update layout to include column names and set background color and axis tick line color
layout = dict(
    scene=dict(
        xaxis=dict(title='SELF_SO (kcal/mol)', tickcolor='black'),
        yaxis=dict(title='SELF_SA (kcal/mol)', tickcolor='black'),
        zaxis=dict(title='INTER (kcal/mol)', tickcolor='black'),
        bgcolor='white'  # Set background color to white
    ),
    width=800,  # Set width to 800 pixels
    height=800,  # Set height to 800 pixels
    plot_bgcolor='white',  # Set plot background color to white
    paper_bgcolor='white'  # Set paper background color to white
)

fig_s.update_layout(title='3D Volume Scatter Plot (S)', **layout)
fig_r.update_layout(title='3D Volume Scatter Plot (R)', **layout)
# Combine the two subplots into one
combined_fig = go.Figure()

# Add 'S' subplot to the combined figure
combined_fig.add_trace(fig_s.data[0])
combined_fig.update_traces(colorbar = dict(x = -0.15))

# Add 'R' subplot to the combined figure
combined_fig.add_trace(fig_r.data[0])
# Add projections
#combined_fig.add_trace(fig_xz.data[0])
#combined_fig.add_trace(fig_yz.data[0])

# Update layout to include column names and set background color and axis tick line color
layout = dict(
    scene=dict(
        xaxis=dict(title='SELF_SO (kcal/mol)', tickcolor='black'),
        yaxis=dict(title='SELF_SA (kcal/mol)', tickcolor='black'),
        zaxis=dict(title='INTER (kcal/mol)', tickcolor='black'),
        bgcolor='white'  # Set background color to white
    ),
    width=800,  # Set width to 800 pixels
    height=800,  # Set height to 800 pixels
    plot_bgcolor='white',  # Set plot background color to white
    paper_bgcolor='white'  # Set paper background color to white
)


# Update layout and title
combined_fig.update_layout(title='Combined 3D Volume Scatter Plot', **layout)

# Show the combined plot
combined_fig.show()

That gives me this plot

2. I would like to add 2 density contours on the xz and yz planes, using these plots

# Construct the graph and style it. Further customize your graph by editing this code.
# See Plotly Documentation for help: https://plotly.com/python/plotly-express/
fig_xz = px.density_contour(df_concat, x='SELF_SO', y='INTERENEDIR', color="SA")
# Update layout to include column names and set background color and axis tick line color
layout = dict(
    scene=dict(
        bgcolor='white'  # Set background color to white
    ),
    width=800,  # Set width to 800 pixels
    height=800,  # Set height to 800 pixels
    plot_bgcolor='white',  # Set plot background color to white
    paper_bgcolor='white'  # Set paper background color to white
)
fig_xz.update_xaxes(range=[0,None])
fig_xz.update_layout(title='2D Density Contour Plot', xaxis=dict(title='SELF_SO (kcal/mol)', tickcolor='black'),
        yaxis=dict(title='INTER (kcal/mol)', tickcolor='black'), **layout)
fig_yz = px.density_contour(df_concat, x='SELF_SA', y='INTERENEDIR', color="SA")
layout = dict(
    scene=dict(
        bgcolor='white'  # Set background color to white
    ),
    width=800,  # Set width to 800 pixels
    height=800,  # Set height to 800 pixels
    plot_bgcolor='white',  # Set plot background color to white
    paper_bgcolor='white'  # Set paper background color to white
)
fig_yz.update_xaxes(range=[0,None])
fig_yz.update_layout(title='2D Density Contour Plot', xaxis=dict(title='SELF_SO (kcal/mol)', tickcolor='black'),
        yaxis=dict(title='INTER (kcal/mol)', tickcolor='black'), **layout)
fig_xz.show()
fig_yz.show()

that gives me

I don’t need the series name (legend) in the final combined plot, but I want to keep the blue and the red colors of the R and S series.
I would like “only” to add the density contour on the first 3D plot.
Thanks for your help