Create app.py

app.py

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+import gradio as gr
+import pandas as pd
+import plotly.graph_objects as go
+from pymatgen.core import Structure
+from pymatgen.analysis.diffraction.xrd import XRDCalculator
+import tempfile # To create temporary files for download
+import os
+import traceback # For detailed error logging
+
+# Define the core processing function
+def generate_xrd_pattern(cif_file):
+    """
+    Processes an uploaded CIF file, calculates the XRD pattern,
+    and returns a Plotly figure, a Pandas DataFrame, and the path to a CSV file.
+
+    Args:
+        cif_file: A file object from Gradio's gr.File component.
+
+    Returns:
+        tuple: (plotly_fig, dataframe, csv_filepath) or (None, None, None) if processing fails.
+               plotly_fig: A Plotly figure object.
+               dataframe: A Pandas DataFrame containing the peak data.
+               csv_filepath: Path to the generated temporary CSV file.
+    """
+    if cif_file is None:
+        # Return None for all outputs if no file is uploaded
+        return None, None, None
+
+    try:
+        # Get the temporary path of the uploaded file
+        cif_filepath = cif_file.name
+
+        # 1. Load structure from CIF
+        structure = Structure.from_file(cif_filepath)
+
+        # 2. Calculate XRD pattern
+        calculator = XRDCalculator()
+        pattern = calculator.get_pattern(structure, two_theta_range=(10, 90)) # Adjust range if needed
+
+        # 3. Prepare data for DataFrame and Plot
+        miller_indices = []
+        for hkl_list in pattern.hkls:
+             if hkl_list:
+                 # Format Miller indices: take the first set if multiple exist for a peak
+                 #h, k, l = hkl_list[0]['hkl']
+                 # Use standard tuple representation for display
+                 miller_indices.append(str(tuple(hkl_list[0]['hkl'])))
+                 # Alternative concise string: miller_indices.append(f"({h}{k}{l})")
+             else:
+                 miller_indices.append("N/A")
+
+        # Round data for cleaner display
+        two_theta_rounded = [round(x, 3) for x in pattern.x]
+        intensity_rounded = [round(y, 3) for y in pattern.y]
+
+        data = pd.DataFrame({
+            "2θ (°)": two_theta_rounded,
+            "Intensity (norm)": intensity_rounded, # Assuming normalized intensity from pymatgen
+            "Miller Indices (hkl)": miller_indices
+        })
+
+        # --- Create Plotly Figure ---
+        fig = go.Figure()
+
+        fig.add_trace(go.Bar(
+            x=data["2θ (°)"],
+            y=data["Intensity (norm)"],
+            hovertext=[f"2θ: {t:.3f}<br>Intensity: {i:.1f}<br>hkl: {m}"
+                       for t, i, m in zip(data["2θ (°)"], data["Intensity (norm)"], data["Miller Indices (hkl)"])],
+            hoverinfo="text", # Show only the custom hover text
+            width=0.1, # Slightly wider bars might look better
+            marker_color="#4682B4", # SteelBlue color
+            marker_line_width=0,
+            name='Peaks'
+        ))
+
+        # Customize Layout
+        max_intensity = data["Intensity (norm)"].max() if not data.empty else 100
+        min_2theta = data["2θ (°)"].min() if not data.empty else 10
+        max_2theta = data["2θ (°)"].max() if not data.empty else 90
+
+        fig.update_layout(
+            title=dict(text=f"Simulated XRD Pattern: {structure.formula}", x=0.5, xanchor='center'), # Centered title
+            xaxis_title="2θ (°)",
+            yaxis_title="Intensity (Arb. Unit)",
+            xaxis_title_font_size=16,
+            yaxis_title_font_size=16,
+            xaxis=dict(
+                range=[min_2theta - 2, max_2theta + 2], # Slightly tighter range
+                showline=True, linewidth=1.5, linecolor='black', mirror=True,
+                ticks='outside', tickwidth=1.5, tickcolor='black',
+                tickfont_size=12
+            ),
+            yaxis=dict(
+                range=[0, max_intensity * 1.05],
+                showline=True, linewidth=1.5, linecolor='black', mirror=True,
+                ticks='outside', tickwidth=1.5, tickcolor='black',
+                tickfont_size=12
+            ),
+            plot_bgcolor='white',
+            paper_bgcolor='white', # Ensure background outside plot is also white
+            bargap=0.9, # Adjust gap based on new width
+            font=dict(family="Arial, sans-serif", size=12, color="black"),
+            margin=dict(l=70, r=30, t=60, b=70),
+            # Adjust height/width as needed, None allows more flexibility
+            height=450,
+            # width=None # Let Gradio manage width for responsiveness
+        )
+        fig.update_xaxes(showgrid=False, zeroline=False)
+        fig.update_yaxes(showgrid=False, zeroline=False)
+
+
+        # --- Create CSV File ---
+        with tempfile.NamedTemporaryFile(mode='w', delete=False, suffix='.csv', newline='', encoding='utf-8') as temp_csv:
+            data.to_csv(temp_csv.name, index=False)
+            csv_filepath_out = temp_csv.name
+
+        # Return figure, dataframe, and csv path
+        return fig, data, csv_filepath_out
+
+    except Exception as e:
+        print(f"Error processing file: {e}") # Log error to console
+        traceback.print_exc() # Print detailed traceback
+        # Raise a Gradio error to display it in the UI
+        raise gr.Error(f"Failed to process CIF file. Please ensure it's a valid CIF. Error: {str(e)}")
+        # return None, None, None # Alternative: clear outputs
+
+
+# --- Build Gradio Interface ---
+# Use a theme for better aesthetics
+theme = gr.themes.Soft(
+    primary_hue="sky",       # Adjust colors if desired
+    secondary_hue="blue",
+    neutral_hue="slate"
+)
+
+with gr.Blocks(theme=theme, title="XRD Pattern Generator") as demo:
+    gr.Markdown(
+        """
+        #  XRD Pattern Simulator from CIF
+        Upload a Crystallographic Information File (.cif) to generate its simulated
+        X-ray Diffraction (XRD) pattern using pymatgen.
+        """
+    )
+
+    with gr.Row():
+        with gr.Column(scale=1): # Column for input
+            cif_input = gr.File(
+                label="Upload CIF File",
+                file_types=[".cif"],
+                type="filepath" # Use filepath directly
+            )
+            gr.Markdown("*(Example source: [Crystallography Open Database](http://crystallography.net/cod/))*")
+
+        with gr.Column(scale=3): # Column for outputs, make it wider
+             with gr.Tabs():
+                with gr.TabItem("📊 XRD Plot"):
+                    # Wrap plot in a column/row to help with centering if needed,
+                    # but Plotly's layout(title_x=0.5) is the primary centering method for the title.
+                    # The plot component itself usually fills container width.
+                    plot_output = gr.Plot(label="XRD Pattern") # Label might be redundant with Tab title
+
+                with gr.TabItem("📄 Peak Data Table"):
+                    dataframe_output = gr.DataFrame(
+                        label="Calculated Peak Data",
+                        headers=["2θ (°)", "Intensity (norm)", "Miller Indices (hkl)"],
+                        wrap=True, # Allow text wrapping for long indices
+                        #max_rows=15, # Limit initial display height
+                        #overflow_row_behaviour='paginate' # Add pagination if many rows
+                        )
+
+                with gr.TabItem("⬇️ Download Data"):
+                    csv_output = gr.File(label="Download Peak Data as CSV")
+                    gr.Markdown("Click the link above to download the full data.")
+
+
+    # Clear outputs when input is cleared
+    cif_input.clear(
+        lambda: (None, None, None),
+        inputs=[],
+        outputs=[plot_output, dataframe_output, csv_output]
+    )
+
+    # Connect the input changes to the processing function
+    cif_input.change(
+        fn=generate_xrd_pattern,
+        inputs=cif_input,
+        outputs=[plot_output, dataframe_output, csv_output],
+        # show_progress="full" # Show progress indicator during calculation
+    )
+    examples = gr.Examples(
+        examples=[
+            ["example_cif/NaCl_1000041.cif"],
+            ["example_cif/Al2O3_1000017.cif"],
+        ],
+        inputs=[cif_input],
+    )
+
+# --- Launch the App ---
+if __name__ == "__main__":
+    demo.launch()
+    # Add share=True for a public link: demo.launch(share=True)