Update app.py

app.py

@@ -2,14 +2,17 @@ import gradio as gr
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
-from typing import Dict, List, Optional
+from typing import Dict, List, Optional, Tuple
 from periodictable import elements
 
-# ---------- helpers ----------
+# =========================
+# Helpers & data utilities
+# =========================
 def to_float(x):
+    """Coerce periodictable values (incl. uncertainties) to float; else NaN."""
     if x is None:
         return np.nan
-    v = getattr(x, "nominal_value", x)  # handles uncertainties.UFloat
+    v = getattr(x, "nominal_value", x)
     try:
         return float(v)
     except Exception:
@@ -26,39 +29,39 @@ NUMERIC_PROPS = [
 ]
 
 CURATED_FACTS: Dict[str, List[str]] = {
-    "H": ["Lightest element; ~74% of visible matter is H in stars."],
-    "He": ["Inert and super light; cryogenics & balloons."],
-    "Li": ["Lithium-ion batteries power phones & EVs."],
-    "C": ["Diamond vs graphite = same element, different structure."],
-    "N": ["~78% of Earth's atmosphere is N₂."],
-    "O": ["~21% of air; essential for respiration."],
-    "Na": ["Reacts violently with water."],
-    "Mg": ["Bright white flame in flares."],
+    "H": ["Lightest element; dominant in stars."],
+    "He": ["Inert; used in cryogenics and balloons."],
+    "Li": ["Key in Li-ion batteries."],
+    "C": ["Same element → diamond vs graphite (allotropy)."],
+    "N": ["~78% of Earth’s atmosphere (N₂)."],
+    "O": ["~21% of air; crucial for respiration."],
+    "Na": ["Violently reacts with water."],
+    "Mg": ["Burns with bright white flame."],
     "Si": ["Semiconductor backbone."],
     "Cl": ["Disinfectant; elemental Cl₂ is toxic."],
-    "Fe": ["Steel core; oxygen transport in blood (heme)."],
-    "Cu": ["Great conductor; forms green patina."],
+    "Fe": ["Steel & blood (heme) MVP."],
+    "Cu": ["Great conductor; green patina."],
     "Ag": ["Highest electrical conductivity."],
     "Au": ["Very unreactive; great for electronics/jewelry."],
     "Hg": ["Liquid metal at room temp; toxic."],
-    "Pb": ["Dense, malleable; toxic—phase-out in fuels/paints."],
-    "U": ["Reactor fuel (U-235)."],
+    "Pb": ["Dense; toxicity drove phase-outs."],
+    "U": ["Nuclear fuel (U-235)."],
     "Pu": ["Man-made in quantity; nuclear uses."],
     "F": ["Most electronegative; extremely reactive."],
-    "Ne": ["Classic red-orange neon glow."],
-    "Xe": ["Used in bright flashes/HID lamps."],
+    "Ne": ["Classic red-orange glow tubes."],
+    "Xe": ["HID lamps & flashes."],
 }
 
 GROUP_FACTS = {
-    "alkali": "Alkali metal: very reactive; forms +1 cations; reacts with water.",
-    "alkaline-earth": "Alkaline earth metal: reactive; forms +2 cations.",
-    "transition": "Transition metal: catalysts, colorful compounds, multiple oxidation states.",
-    "post-transition": "Post-transition metal: softer, lower melting than transition metals.",
+    "alkali": "Alkali metal: very reactive; forms +1; reacts with water.",
+    "alkaline-earth": "Alkaline earth metal: reactive; forms +2.",
+    "transition": "Transition metal: variable oxidation states; often colored compounds.",
+    "post-transition": "Post-transition metal: softer; lower melting than transition metals.",
     "metalloid": "Metalloid: between metals and nonmetals; often semiconductors.",
-    "nonmetal": "Nonmetal: forms covalent compounds; huge biological roles.",
-    "halogen": "Halogen: very reactive nonmetals; −1 state; forms salts.",
-    "noble-gas": "Noble gas: inert, monatomic gases.",
-    "lanthanide": "Lanthanide: rare earths; magnets, lasers, phosphors.",
+    "nonmetal": "Nonmetal: covalent chemistry; key biological roles.",
+    "halogen": "Halogen: ns²np⁵; gains 1e⁻; forms salts.",
+    "noble-gas": "Noble gas: ns²np⁶; inert, monatomic.",
+    "lanthanide": "Lanthanide: rare earths; magnets/lasers/phosphors.",
     "actinide": "Actinide: radioactive; nuclear materials.",
 }
 
@@ -113,30 +116,83 @@ def build_elements_df() -> pd.DataFrame:
 
 DF = build_elements_df()
 
-# ---------- hardcoded main-grid layout (periods 1–7, groups 1–18) ----------
-# None = empty cell; numbers = atomic numbers
+# =========================
+# Hard-coded periodic layout
+# =========================
+# Periods 1–7, groups 1–18; La/Ac shown in group 3; f-block split below.
 GRID = [
-    # P1
     [1, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, 2],
-    # P2
     [3, 4, None, None, None, None, None, None, None, None, None, None, 5, 6, 7, 8, 9, 10],
-    # P3
     [11, 12, None, None, None, None, None, None, None, None, None, None, 13, 14, 15, 16, 17, 18],
-    # P4
     [19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36],
-    # P5
     [37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54],
-    # P6 (La shown at group 3)
     [55, 56, 57, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86],
-    # P7 (Ac shown at group 3)
     [87, 88, 89, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118],
 ]
-
-# f-block lists we display separately (omit La & Ac because they’re in the main grid)
 LAN = list(range(58, 72))   # Ce..Lu
 ACT = list(range(90, 104))  # Th..Lr
 
-# ---------- plotting ----------
+def find_pos_in_grid(Z:int) -> Tuple[Optional[int], Optional[int]]:
+    for r in range(len(GRID)):
+        for c in range(len(GRID[0])):
+            if GRID[r][c] == Z:
+                return (r+1, c+1)  # human-friendly (period, group)
+    return (None, None)
+
+# =========================
+# Explanations
+# =========================
+def valence_pattern(period:int, group:int, block:str) -> str:
+    if period is None or group is None or block is None:
+        return "Valence pattern unavailable."
+    n = period
+    if block == "s":
+        return f"{n}s¹" if group == 1 else f"{n}s²"
+    if block == "p" and 13 <= group <= 18:
+        p_e = group - 12  # 1..6
+        return f"{n}s²{n}p^{p_e}"
+    if block == "d":
+        return f"{n-1}d^(1–10){n}s^(0–2) (incomplete d-subshell)"
+    if block == "f":
+        return f"{n-2}f^(1–14){n-1}d^(0–1){n}s² (f-block)"
+    return "Valence pattern unavailable."
+
+def explain_element(row:dict, Z:int) -> str:
+    period, group = find_pos_in_grid(Z)
+    block = row["block"]
+    cat = row["category"]
+    en = row["electronegativity"]
+    dens = row["density"]
+
+    lines = []
+    # Valence / block logic
+    lines.append(f"**Valence & block:** {valence_pattern(period, group, block)}; {cat.replace('-', ' ')}.")
+    # Reactivity / tendencies
+    if group == 1:
+        lines.append("**Reactivity:** Group 1 (ns¹) → easily loses 1 e⁻ (forms +1), reacts strongly with water.")
+    elif group == 2:
+        lines.append("**Reactivity:** Group 2 (ns²) → tends to lose 2 e⁻ (forms +2).")
+    elif group == 17:
+        lines.append("**Reactivity:** Halogen (ns²np⁵) → tends to gain 1 e⁻; oxidizing; reactivity decreases down the group.")
+    elif group == 18:
+        lines.append("**Reactivity:** Noble gas (ns²np⁶) → filled shell, minimal reactivity.")
+    elif block == "d":
+        lines.append("**d-block behavior:** Partially filled d-orbitals → multiple oxidation states; often colored complexes.")
+    # Property tie-ins
+    if not pd.isna(en) and not pd.isna(row["period"]):
+        same_period = DF[(DF["period"] == row["period"]) & (~DF["electronegativity"].isna())]
+        if len(same_period):
+            med = same_period["electronegativity"].median()
+            qual = "higher-than-average" if en > med else "lower-than-average"
+            lines.append(f"**Electronegativity:** {en:.2f} ({qual} within period {int(row['period'])}).")
+    if not pd.isna(dens):
+        lines.append(f"**Density:** {dens:g} g/cm³ — linked to atomic mass and packing typical for its category.")
+
+    return "### Why it behaves this way\n" + "\n".join(f"- {t}" for t in lines)
+
+# =========================
+# Plotting (Matplotlib -> gr.Plot)
+# =========================
 def plot_trend(trend_df: pd.DataFrame, prop_key: str, Z: int, symbol: str):
     fig, ax = plt.subplots()
     ax.scatter(trend_df["Z"], trend_df[prop_key])
@@ -162,21 +218,48 @@ def plot_heatmap(property_key: str):
             val = DF.loc[DF["Z"] == z, property_key].values[0]
             if not pd.isna(val):
                 grid_vals[r, c] = float(val)
+
+    if np.isnan(grid_vals).all():
+        fig, ax = plt.subplots()
+        ax.axis("off")
+        ax.text(0.5, 0.5, f"No data for {prop_label}", ha="center", va="center", fontsize=12)
+        fig.tight_layout()
+        return fig
+
+    masked = np.ma.masked_invalid(grid_vals)
+    finite_vals = grid_vals[~np.isnan(grid_vals)]
+    if finite_vals.size >= 2:
+        vmin, vmax = np.nanpercentile(finite_vals, [5, 95])
+    else:
+        vmin, vmax = np.nanmin(finite_vals), np.nanmax(finite_vals)
+
     fig, ax = plt.subplots()
-    im = ax.imshow(grid_vals, origin="upper", aspect="auto")
-    ax.set_xticks(range(max_group))
-    ax.set_xticklabels([str(i) for i in range(1, max_group + 1)])
-    ax.set_yticks(range(max_period))
-    ax.set_yticklabels([str(i) for i in range(1, max_period + 1)])
-    ax.set_xlabel("Group")
-    ax.set_ylabel("Period")
+    im = ax.imshow(masked, origin="upper", aspect="auto", vmin=vmin, vmax=vmax)
+    ax.set_xticks(range(max_group)); ax.set_xticklabels([str(i) for i in range(1, max_group + 1)])
+    ax.set_yticks(range(max_period)); ax.set_yticklabels([str(i) for i in range(1, max_period + 1)])
+    ax.set_xlabel("Group"); ax.set_ylabel("Period")
     ax.set_title(f"Periodic heatmap: {prop_label}")
     fig.colorbar(im, ax=ax, label=prop_label)
     fig.tight_layout()
     return fig
 
-# ---------- callbacks ----------
-def element_info(z_or_symbol: str):
+# =========================
+# Core callbacks
+# =========================
+def compose_facts(row:dict, Z:int, show_expl:bool) -> str:
+    symbol = row["symbol"]
+    facts = []
+    facts.extend(CURATED_FACTS.get(symbol, []))
+    gf = GROUP_FACTS.get(row["category"], None)
+    if gf:
+        facts.append(gf)
+    facts_text = "\n• ".join(["**Interesting facts:**"] + facts) if facts else ""
+    if show_expl:
+        expl = explain_element(row, Z)
+        facts_text = (facts_text + "\n\n" if facts_text else "") + expl
+    return facts_text if facts_text else "No fact on file—still cool though!"
+
+def element_info(z_or_symbol: str, show_expl: bool):
     try:
         if z_or_symbol.isdigit():
             Z = int(z_or_symbol)
@@ -185,17 +268,12 @@ def element_info(z_or_symbol: str):
             el = elements.symbol(z_or_symbol)
             Z = el.number
     except Exception:
-        return f"Unknown element: {z_or_symbol}", None, None
+        return f"Unknown element: {z_or_symbol}", "No data", None, None  # info, facts, fig, current_Z
 
     row = DF.loc[DF["Z"] == Z].iloc[0].to_dict()
     symbol = row["symbol"]
 
-    facts = []
-    facts.extend(CURATED_FACTS.get(symbol, []))
-    facts.append(GROUP_FACTS.get(row["category"], None))
-    facts = [f for f in facts if f]
-
-    def show(v):  # nicer NaN -> —
+    def show(v):
         return v if (v is not None and not pd.isna(v)) else "—"
 
     props_lines = [
@@ -211,35 +289,48 @@ def element_info(z_or_symbol: str):
         f"Radioactive: {'Yes' if row['is_radioactive'] else 'No'}",
     ]
     info_text = "\n".join(props_lines)
-    facts_text = "\n• ".join(["Interesting facts:"] + facts) if facts else "No fact on file—still cool though!"
 
     prop_key = "electronegativity" if not pd.isna(row["electronegativity"]) else "mass"
     trend_df = DF[["Z", "symbol", prop_key]].dropna()
     fig = plot_trend(trend_df, prop_key, Z, symbol)
-    return info_text, facts_text, fig
 
-def handle_button_click(z: int):
-    return element_info(str(z))
+    facts_text = compose_facts(row, Z, show_expl)
+    return info_text, facts_text, fig, Z
+
+def handle_button_click(z: int, show_expl: bool):
+    return element_info(str(z), show_expl)
 
-def search_element(query: str):
+def search_element(query: str, show_expl: bool):
     query = (query or "").strip()
     if not query:
-        return gr.update(), gr.update(), gr.update()
-    return element_info(query)
+        return gr.update(), gr.update(), gr.update(), gr.update()
+    return element_info(query, show_expl)
+
+def refresh_facts(current_Z: Optional[int], show_expl: bool):
+    if current_Z is None:
+        return gr.update()
+    row = DF.loc[DF["Z"] == current_Z].iloc[0].to_dict()
+    return compose_facts(row, int(current_Z), show_expl)
 
-# ---------- UI ----------
+# =========================
+# UI (Gradio 4.29.0)
+# =========================
 with gr.Blocks(title="Interactive Periodic Table") as demo:
     gr.Markdown("Click an element or search by symbol/name/atomic number.")
 
     with gr.Row():
-        # Inspector
+        # Inspector & controls
         with gr.Column(scale=1):
             gr.Markdown("### Inspector")
+            show_expl = gr.Checkbox(label="Show advanced explanation", value=False)
             search = gr.Textbox(label="Search (symbol/name/Z)", placeholder="e.g., C, Iron, 79")
             info = gr.Textbox(label="Properties", lines=10, interactive=False)
-            facts = gr.Markdown("Select an element to see fun facts.")
+            facts = gr.Markdown("Select an element to see facts and explanations.")
             trend = gr.Plot()
-            search.submit(search_element, inputs=[search], outputs=[info, facts, trend])
+            current_Z = gr.State(value=None)
+
+            search.submit(search_element, inputs=[search, show_expl], outputs=[info, facts, trend, current_Z])
+            show_expl.change(refresh_facts, inputs=[current_Z, show_expl], outputs=[facts])
 
             gr.Markdown("### Trend heatmap")
             prop = gr.Dropdown(choices=[k for k, _ in NUMERIC_PROPS], value="electronegativity", label="Property")
@@ -262,21 +353,29 @@ with gr.Blocks(title="Interactive Periodic Table") as demo:
                         else:
                             sym = DF.loc[DF["Z"] == z, "symbol"].values[0]
                             btn = gr.Button(sym)
-                            btn.click(handle_button_click, inputs=[gr.Number(z, visible=False)],
-                                      outputs=[info, facts, trend])
+                            btn.click(
+                                handle_button_click,
+                                inputs=[gr.Number(z, visible=False), show_expl],
+                                outputs=[info, facts, trend, current_Z],
+                            )
 
             gr.Markdown("### f-block (lanthanides & actinides)")
             with gr.Row():
                 for z in LAN:
                     sym = DF.loc[DF["Z"] == z, "symbol"].values[0]
-                    gr.Button(sym).click(handle_button_click, inputs=[gr.Number(z, visible=False)],
-                                         outputs=[info, facts, trend])
+                    gr.Button(sym).click(
+                        handle_button_click,
+                        inputs=[gr.Number(z, visible=False), show_expl],
+                        outputs=[info, facts, trend, current_Z],
+                    )
             with gr.Row():
                 for z in ACT:
                     sym = DF.loc[DF["Z"] == z, "symbol"].values[0]
-                    gr.Button(sym).click(handle_button_click, inputs=[gr.Number(z, visible=False)],
-                                         outputs=[info, facts, trend])
+                    gr.Button(sym).click(
+                        handle_button_click,
+                        inputs=[gr.Number(z, visible=False), show_expl],
+                        outputs=[info, facts, trend, current_Z],
+                    )
 
 if __name__ == "__main__":
     demo.launch()
-