polish: Add chart labels and use library for SG naming conventions

Author: Linked-Liszt

src/ui/app/model_inference.py

@@ -6,6 +6,7 @@
 from typing import Dict, List, Tuple, Optional
 import torch
 import numpy as np
+import spglib
 
 
 class XRDModelInference:
@@ -32,7 +33,7 @@ def load_model(self):
             from .model import AlphaDiffractMultiscaleLightning
 
             # Load checkpoint
-            checkpoint = torch.load(self.model_path, map_location=self.device)
+            checkpoint = torch.load(self.model_path, map_location=self.device, weights_only=False)
 
             # Initialize model (you may need to adjust hyperparameters based on your checkpoint)
             # For now, using placeholder values - these should match your trained model
@@ -243,20 +244,19 @@ def _process_model_output(self, output) -> Dict:
         }
 
     def _get_space_group_symbol(self, sg_number: int) -> str:
-        """Get space group symbol from number (simplified mapping)"""
-        # Common space group symbols - this is a simplified mapping
-        # In production, you'd want a complete lookup table
-        symbols = {
-            1: "P1", 2: "P-1", 3: "P2", 4: "P21", 5: "C2",
-            10: "P2/m", 15: "C2/c", 16: "P222", 19: "P212121",
-            38: "Amm2", 47: "Pmmm", 62: "Pnma", 63: "Cmcm",
-            71: "Immm", 74: "Imma", 82: "I-4", 87: "I4/m",
-            123: "P4/mmm", 129: "P4/nmm", 139: "I4/mmm", 148: "R-3",
-            160: "R3m", 162: "P-31m", 164: "P-3m1", 166: "R-3m",
-            167: "R-3c", 186: "P63mc", 194: "P63/mmc", 221: "Pm-3m",
-            225: "Fm-3m", 227: "Fd-3m", 229: "Im-3m", 230: "Ia-3d"
-        }
-        return symbols.get(sg_number, f"SG{sg_number}")
+        """Get space group symbol from number using spglib"""
+        if sg_number < 1 or sg_number > 230:
+            return f"SG{sg_number}"
+        
+        try:
+            # Get space group type information from spglib
+            sg_type = spglib.get_spacegroup_type(sg_number)
+            if sg_type is not None:
+                # Use the international short symbol (Hermann-Mauguin notation)
+                return sg_type['international_short']
+            return f"SG{sg_number}"
+        except Exception:
+            return f"SG{sg_number}"
 
     def _dummy_predictions(self) -> Dict:
         """Return dummy predictions when model is not available"""

src/ui/frontend/src/components/XRDGraph.jsx

@@ -47,7 +47,14 @@ const XRDGraph = () => {
   // Layout for raw data graph
   const rawLayout = {
     xaxis: {
-      title: '2θ (degrees)',
+      title: {
+        text: '2θ (degrees)',
+        font: {
+          size: 14,
+          color: '#333',
+        },
+        standoff: 10,
+      },
       gridcolor: 'rgba(128, 128, 128, 0.2)',
       showline: true,
       linewidth: 1,
@@ -56,7 +63,14 @@ const XRDGraph = () => {
       range: [Math.min(...rawData.x) - 0.5, Math.max(...rawData.x) + 0.5],
     },
     yaxis: {
-      title: 'Intensity (a.u.)',
+      title: {
+        text: 'Intensity (a.u.)',
+        font: {
+          size: 14,
+          color: '#333',
+        },
+        standoff: 10,
+      },
       gridcolor: 'rgba(128, 128, 128, 0.2)',
       showline: true,
       linewidth: 1,
@@ -79,7 +93,14 @@ const XRDGraph = () => {
   // Layout for processed data graph
   const processedLayout = {
     xaxis: {
-      title: '2θ (degrees)',
+      title: {
+        text: '2θ (degrees)',
+        font: {
+          size: 14,
+          color: '#333',
+        },
+        standoff: 10,
+      },
       gridcolor: 'rgba(128, 128, 128, 0.2)',
       range: [MODEL_MIN_2THETA - 0.5, MODEL_MAX_2THETA + 0.5],
       showline: true,
@@ -88,7 +109,14 @@ const XRDGraph = () => {
       mirror: true,
     },
     yaxis: {
-      title: 'Standardized Intensity (0-100)',
+      title: {
+        text: 'Normalized Intensity',
+        font: {
+          size: 14,
+          color: '#333',
+        },
+        standoff: 10,
+      },
       gridcolor: 'rgba(128, 128, 128, 0.2)',
       range: [-5, 105],
       showline: true,