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](https://github.com/materialsproject/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)