No scopes or spectra to display
", + "csv_data": csv_payload, + "message": "Pathsim simulation completed successfully", + } + ) + + absolute_vertical_spacing = 0.05 + relative_vertical_spacing = absolute_vertical_spacing / n_rows + fig = make_subplots( + rows=n_rows, + cols=1, + shared_xaxes=shared_x, + subplot_titles=[scope.label for scope in scopes] + + [spec.label for spec in spectra], + vertical_spacing=relative_vertical_spacing, + ) + + # make scope plots + for i, scope in enumerate(scopes): + sim_time, data = scope.read() + + for p, d in enumerate(data): + lb = scope.labels[p] if p < len(scope.labels) else f"port {p}" + if isinstance(scope, Spectrum): + d = abs(d) + fig.add_trace( + go.Scatter(x=sim_time, y=d, mode="lines", name=lb), + row=i + 1, + col=1, + ) + + fig.update_xaxes(title_text="Time", row=len(scopes), col=1) + + # make spectrum plots + for i, spec in enumerate(spectra): + freq, data = spec.read() + + for p, d in enumerate(data): + lb = spec.labels[p] if p < len(spec.labels) else f"port {p}" + d = abs(d) + fig.add_trace( + go.Scatter(x=freq, y=d, mode="lines", name=lb), + row=len(scopes) + i + 1, + col=1, + ) + fig.update_xaxes(title_text="Frequency", row=len(scopes) + i + 1, col=1) + + fig.update_layout(height=500 * (len(scopes) + len(spectra)), hovermode="x unified") + + return fig, csv_payload + + # Function to convert graph to pathsim and run simulation @app.route("/run-pathsim", methods=["POST"]) def run_pathsim(): @@ -354,93 +425,43 @@ def run_pathsim(): my_simulation.run(duration) # Generate the plot - scopes = [block for block in my_simulation.blocks if isinstance(block, Scope)] - spectra = [ - block for block in my_simulation.blocks if isinstance(block, Spectrum) - ] - - # FIXME right now only the scopes are converted to CSV - # extra work is needed since spectra and scopes don't share the same x axis - csv_payload = make_csv_payload(scopes) + try: + fig, csv_payload = make_plot(my_simulation) + print("Created plot figure") - # Share x only if there are only scopes or only spectra - shared_x = len(scopes) * len(spectra) == 0 - n_rows = len(scopes) + len(spectra) + # Convert plot to JSON + try: + plot_data = plotly_json.dumps(fig, cls=plotly.utils.PlotlyJSONEncoder) + plot_html = fig.to_html() + print("Converted plot to JSON and HTML") + except Exception as plot_error: + print(f"Error converting plot to JSON: {str(plot_error)}") + return jsonify( + { + "success": False, + "error": f"Plot generation error: {str(plot_error)}", + } + ), 500 - if n_rows == 0: - # No scopes or spectra to plot return jsonify( { "success": True, - "plot": "{}", - "html": "No scopes or spectra to display
", + "plot": plot_data, + "html": plot_html, "csv_data": csv_payload, "message": "Pathsim simulation completed successfully", } ) - absolute_vertical_spacing = 0.05 - relative_vertical_spacing = absolute_vertical_spacing / n_rows - fig = make_subplots( - rows=n_rows, - cols=1, - shared_xaxes=shared_x, - subplot_titles=[scope.label for scope in scopes] - + [spec.label for spec in spectra], - vertical_spacing=relative_vertical_spacing, - ) - - # make scope plots - for i, scope in enumerate(scopes): - sim_time, data = scope.read() - - for p, d in enumerate(data): - lb = scope.labels[p] if p < len(scope.labels) else f"port {p}" - if isinstance(scope, Spectrum): - d = abs(d) - fig.add_trace( - go.Scatter(x=sim_time, y=d, mode="lines", name=lb), row=i + 1, col=1 - ) - - fig.update_xaxes(title_text="Time", row=len(scopes), col=1) - - # make spectrum plots - for i, spec in enumerate(spectra): - freq, data = spec.read() - - for p, d in enumerate(data): - lb = spec.labels[p] if p < len(spec.labels) else f"port {p}" - d = abs(d) - fig.add_trace( - go.Scatter(x=freq, y=d, mode="lines", name=lb), - row=len(scopes) + i + 1, - col=1, - ) - fig.update_xaxes(title_text="Frequency", row=len(scopes) + i + 1, col=1) - - fig.update_layout( - height=500 * (len(scopes) + len(spectra)), hovermode="x unified" - ) - - # Convert plot to JSON - try: - plot_data = plotly_json.dumps(fig, cls=plotly.utils.PlotlyJSONEncoder) - plot_html = fig.to_html() - except Exception as plot_error: + except Exception as plot_creation_error: + print(f"Error during plot creation: {str(plot_creation_error)}") return jsonify( - {"success": False, "error": f"Plot generation error: {str(plot_error)}"} + { + "success": False, + "error": f"Plot creation error: {str(plot_creation_error)}", + } ), 500 - return jsonify( - { - "success": True, - "plot": plot_data, - "html": plot_html, - "csv_data": csv_payload, - "message": "Pathsim simulation completed successfully", - } - ) - except Exception as e: # Log the full error for debugging import traceback