Improve reaction detail plot parsing and defaults

app.py

@@ -2,6 +2,7 @@ from __future__ import annotations
 
 import os
 import math
+import re
 from textwrap import dedent
 from typing import List, Sequence, Tuple
 
@@ -39,6 +40,24 @@ FIELD_CHOICES = [
     ("Squib", FieldName.squib.value),
 ]
 
+
+def _safe_float(value: str | None) -> float | None:
+    if value is None:
+        return None
+    text = str(value).strip()
+    if not text:
+        return None
+    sci_match = re.fullmatch(r"([+-]?\d+(?:\.\d+)?)\s*[x×*]\s*10\^?([+-]?\d+)", text, re.IGNORECASE)
+    if sci_match:
+        base = float(sci_match.group(1))
+        exponent = int(sci_match.group(2))
+        return base * (10 ** exponent)
+    cleaned = text.replace(",", "")
+    try:
+        return float(cleaned)
+    except ValueError:
+        return None
+
 RELATION_CHOICES = [
     ("contains", Relation.contains.value),
     ("is", Relation.equals.value),
@@ -237,24 +256,44 @@ def fetch_detail(selected_url: str, manual_url: str):
     plot_fig = None
     if detail.datasets:
         dataset = detail.datasets[0]
-        try:
-            A_str = dataset.pre_exponential_factor or ""
-            n_str = dataset.temperature_exponent or ""
-            Ea_str = dataset.activation_energy or ""
-            A = float(A_str) if A_str else 0
-            n = float(n_str) if n_str else 0
-            Ea = float(Ea_str) if Ea_str else 0
-            if A > 0 and A_str and n_str:  # Ensure A and n are present
-                # Generate plot similar to generate_arrhenius_plot
-                Tmin, Tmax, num_points = 300, 2000, 100
-                temps = [Tmin + (Tmax - Tmin) * i / (num_points - 1) for i in range(num_points)]
-                R = 8.314462618  # J/mol·K
-                rates = [
-                    A * ((t / 298.0) ** n) * math.exp(-Ea / (R * t))
-                    for t in temps
-                ]
-                arrhenius_x = [1000.0 / t for t in temps]
-                arrhenius_y = [math.log(k) for k in rates]
+        A = _safe_float(getattr(dataset, "pre_exponential_factor", None))
+        n_val = _safe_float(getattr(dataset, "temperature_exponent", None))
+        Ea_val = _safe_float(getattr(dataset, "activation_energy", None))
+        if A and A > 0:
+            n = n_val if n_val is not None else 0.0
+            Ea = Ea_val if Ea_val is not None else 0.0
+
+            Tmin, Tmax = 300.0, 2000.0
+            range_text = getattr(dataset, "temperature_range", None)
+            if isinstance(range_text, str):
+                tokens = re.findall(r"[+-]?\d+(?:\.\d+)?(?:[eE][+-]?\d+)?", range_text)
+                temp_vals = [_safe_float(tok) for tok in tokens]
+                temp_vals = [val for val in temp_vals if val is not None]
+                if len(temp_vals) >= 2:
+                    Tmin, Tmax = min(temp_vals), max(temp_vals)
+                elif len(temp_vals) == 1:
+                    center = temp_vals[0]
+                    Tmin, Tmax = max(1.0, center - 50.0), center + 50.0
+            if Tmin < 1.0:
+                Tmin = 1.0
+            if Tmax <= Tmin:
+                Tmax = Tmin + 100.0
+
+            num_points = 120
+            temps = [Tmin + (Tmax - Tmin) * i / (num_points - 1) for i in range(num_points)]
+            R = 8.314462618  # J/mol·K
+            rates = [
+                A * ((t / 298.0) ** n) * math.exp(-Ea / (R * t))
+                for t in temps
+            ]
+            plot_points = [
+                (1000.0 / t, math.log(k))
+                for t, k in zip(temps, rates)
+                if k > 0
+            ]
+            if plot_points:
+                arrhenius_x, arrhenius_y = zip(*plot_points)
+                arrhenius_x, arrhenius_y = list(arrhenius_x), list(arrhenius_y)
 
                 fig = go.Figure()
                 fig.add_trace(
@@ -266,15 +305,29 @@ def fetch_detail(selected_url: str, manual_url: str):
                         line=dict(color="#2563eb"),
                     )
                 )
+
+                k_298 = _safe_float(getattr(dataset, "rate_at_298", None))
+                if k_298 and k_298 > 0:
+                    fig.add_trace(
+                        go.Scatter(
+                            x=[1000.0 / 298.0],
+                            y=[math.log(k_298)],
+                            mode="markers",
+                            name="k(298 K)",
+                            marker=dict(size=10, color="#dc2626"),
+                            hovertemplate="T = 298 K<br>k = %{customdata[0]:.3e}",
+                            customdata=[[k_298]],
+                        )
+                    )
+
                 fig.update_layout(
                     title=f"Arrhenius Plot for {detail.title or 'Reaction'}",
                     xaxis_title="1000 / T (K⁻¹)",
                     yaxis_title="ln k",
-                    height=400,
+                    height=360,
+                    margin=dict(l=40, r=20, t=60, b=40),
                 )
                 plot_fig = fig
-        except (ValueError, TypeError):
-            pass  # Skip plotting if data invalid
 
     return markdown, table, plot_fig