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app (3).py

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+
+import math
+from typing import Dict, List, Optional
+
+import gradio as gr
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+from periodictable import elements
+
+NUMERIC_PROPS = [
+    ("mass", "Atomic mass (u)"),
+    ("density", "Density (g/cm^3)"),
+    ("electronegativity", "Pauling electronegativity"),
+    ("boiling_point", "Boiling point (K)"),
+    ("melting_point", "Melting point (K)"),
+    ("vdw_radius", "van der Waals radius (pm)"),
+    ("covalent_radius", "Covalent radius (pm)"),
+]
+
+CURATED_FACTS: Dict[str, List[str]] = {
+    "H": ["Lightest element; ~74% of the visible universe by mass is hydrogen in stars."],
+    "He": ["Inert, used in cryogenics and balloons; second lightest element."],
+    "Li": ["Batteries MVP: lithium-ion cells power phones and EVs."],
+    "C": ["Backbone of life; diamond and graphite are pure carbon with wildly different properties."],
+    "N": ["~78% of Earth's atmosphere is nitrogen (mostly N₂)."],
+    "O": ["Essential for respiration; ~21% of Earth's atmosphere."],
+    "Na": ["Sodium metal reacts violently with water—handle only under oil or inert gas."],
+    "Mg": ["Burns with a bright white flame; used in flares and fireworks."],
+    "Al": ["Light and strong; forms a protective oxide layer that resists corrosion."],
+    "Si": ["Silicon is the basis of modern electronics—hello, semiconductors."],
+    "Cl": ["Powerful disinfectant; elemental chlorine is toxic, compounds are widely useful."],
+    "Ar": ["Argon is used to provide inert atmospheres for welding and 3D printing."],
+    "Fe": ["Core of steel; iron is essential in hemoglobin for oxygen transport."],
+    "Cu": ["Excellent electrical conductor; iconic blue-green patina (verdigris)."],
+    "Ag": ["Highest electrical conductivity of all metals; historically used as currency."],
+    "Au": ["Very unreactive ('noble'); prized for electronics and jewelry."],
+    "Hg": ["Only metal that's liquid at room temperature; toxic—use with care."],
+    "Pb": ["Dense and malleable; toxicity led to phase-out from gasoline and paints."],
+    "U": ["Radioactive; used as nuclear reactor fuel (U-235)."],
+    "Pu": ["Man-made in quantity; key in certain nuclear technologies."],
+    "F": ["Most electronegative element; extremely reactive."],
+    "Ne": ["Neon glows striking red-orange in discharge tubes—classic signs."],
+    "Xe": ["Xenon makes bright camera flashes and high-intensity lamps."],
+}
+
+GROUP_FACTS = {
+    "alkali": "Alkali metal: very reactive soft metal; forms +1 cations and reacts with water.",
+    "alkaline-earth": "Alkaline earth metal: reactive (less than Group 1); forms +2 cations.",
+    "transition": "Transition metal: often good catalysts, colorful compounds, multiple oxidation states.",
+    "post-transition": "Post-transition metal: softer metals with lower melting points than transition metals.",
+    "metalloid": "Metalloid: properties between metals and nonmetals; often semiconductors.",
+    "nonmetal": "Nonmetal: tends to form covalent compounds; wide range of roles in biology and materials.",
+    "halogen": "Halogen: very reactive nonmetals; form salts with metals and −1 oxidation state.",
+    "noble-gas": "Noble gas: chemically inert under most conditions; monatomic gases.",
+    "lanthanide": "Lanthanide: f-block rare earths; notable for magnets, lasers, and phosphors.",
+    "actinide": "Actinide: radioactive f-block; includes nuclear fuel materials.",
+}
+
+def classify_category(el) -> str:
+    try:
+        if el.block == "s" and el.group == 1 and el.number != 1:
+            return "alkali"
+        if el.block == "s" and el.group == 2:
+            return "alkaline-earth"
+        if el.block == "p" and el.group in (13, 14, 15, 16) and el.metallic:
+            return "post-transition"
+        if el.block == "d":
+            return "transition"
+        if el.block == "p" and el.group == 17:
+            return "halogen"
+        if el.block == "p" and el.group == 18:
+            return "noble-gas"
+        if el.block == "p" and not el.metallic:
+            return "nonmetal"
+        if el.block == "f" and 57 <= el.number <= 71:
+            return "lanthanide"
+        if el.block == "f" and 89 <= el.number <= 103:
+            return "actinide"
+    except Exception:
+        pass
+    return "nonmetal" if not getattr(el, "metallic", False) else "post-transition"
+
+def build_elements_df() -> pd.DataFrame:
+    rows = []
+    for Z in range(1, 119):
+        el = elements[Z]
+        if el is None:
+            continue
+        data = {
+            "Z": el.number,
+            "symbol": el.symbol,
+            "name": el.name.title(),
+            "period": getattr(el, "period", None),
+            "group": getattr(el, "group", None),
+            "block": getattr(el, "block", None),
+            "mass": getattr(el, "mass", None),
+            "density": getattr(el, "density", None),
+            "electronegativity": getattr(el, "electronegativity", None),
+            "boiling_point": getattr(el, "boiling_point", None),
+            "melting_point": getattr(el, "melting_point", None),
+            "vdw_radius": getattr(el, "vdw_radius", None),
+            "covalent_radius": getattr(el, "covalent_radius", None),
+            "category": classify_category(el),
+            "is_radioactive": bool(getattr(el, "radioactive", False)),
+        }
+        rows.append(data)
+    df = pd.DataFrame(rows).sort_values("Z").reset_index(drop=True)
+    return df
+
+DF = build_elements_df()
+MAX_GROUP = 18
+MAX_PERIOD = 7
+
+GRID: List[List[Optional[int]]] = [[None for _ in range(MAX_GROUP)] for _ in range(MAX_PERIOD)]
+for _, row in DF.iterrows():
+    period, group, Z = int(row["period"]), row["group"], int(row["Z"])
+    if group is None:
+        continue
+    GRID[period-1][group-1] = Z
+
+LAN = [z for z in DF["Z"] if 57 <= z <= 71]
+ACT = [z for z in DF["Z"] if 89 <= z <= 103]
+
+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])
+    # highlight
+    sel = trend_df.loc[trend_df["Z"] == Z, prop_key]
+    if not sel.empty and not pd.isna(sel.values[0]):
+        ax.scatter([Z], [sel.values[0]], s=80)
+        ax.text(Z, sel.values[0], symbol, ha="center", va="bottom")
+    ax.set_xlabel("Atomic number (Z)")
+    ax.set_ylabel(dict(NUMERIC_PROPS)[prop_key])
+    ax.set_title(f"{dict(NUMERIC_PROPS)[prop_key]} across the periodic table")
+    fig.tight_layout()
+    return fig
+
+def plot_heatmap(property_key: str):
+    prop_label = dict(NUMERIC_PROPS)[property_key]
+    grid_vals = np.full((MAX_PERIOD, MAX_GROUP), np.nan, dtype=float)
+    for r in range(MAX_PERIOD):
+        for c in range(MAX_GROUP):
+            z = GRID[r][c]
+            if z is None:
+                continue
+            val = DF.loc[DF['Z'] == z, property_key].values[0]
+            if not pd.isna(val):
+                grid_vals[r, c] = float(val)
+
+    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")
+    ax.set_title(f"Periodic heatmap: {prop_label}")
+    fig.colorbar(im, ax=ax, label=prop_label)
+    fig.tight_layout()
+    return fig
+
+def element_info(z_or_symbol: str):
+    try:
+        if z_or_symbol.isdigit():
+            Z = int(z_or_symbol)
+            _ = elements[Z]
+        else:
+            el = elements.symbol(z_or_symbol)
+            Z = el.number
+    except Exception:
+        return f"Unknown element: {z_or_symbol}", None, None
+
+    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]
+
+    props_lines = [
+        f"{row['name']} ({symbol}), Z = {Z}",
+        f"Period {int(row['period'])}, Group {row['group']}, Block {row['block']} | Category: {row['category'].replace('-', ' ').title()}",
+        f"Atomic mass: {row['mass'] if row['mass'] else '—'} u",
+        f"Density: {row['density'] if row['density'] else '—'} g/cm³",
+        f"Electronegativity: {row['electronegativity'] if row['electronegativity'] else '—'} (Pauling)",
+        f"Melting point: {row['melting_point'] if row['melting_point'] else '—'} K | Boiling point: {row['boiling_point'] if row['boiling_point'] else '—'} K",
+        f"vdW radius: {row['vdw_radius'] if row['vdw_radius'] else '—'} pm | Covalent radius: {row['covalent_radius'] if row['covalent_radius'] else '—'} pm",
+        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))
+
+def search_element(query: str):
+    query = (query or '').strip()
+    if not query:
+        return gr.update(), gr.update(), gr.update()
+    return element_info(query)
+
+with gr.Blocks(title="Interactive Periodic Table") as demo:
+    gr.Markdown("# 🧪 Interactive Periodic Table\nClick an element or search by symbol/name/atomic number.")
+
+    with gr.Row():
+        with gr.Column(scale=2):
+            gr.Markdown("### Main Table")
+            with gr.Row():
+                for g in range(1, 19):
+                    gr.Markdown(f"**{g}**")
+            for r in range(MAX_PERIOD):
+                with gr.Row():
+                    for c in range(MAX_GROUP):
+                        z = GRID[r][c]
+                        if z is None:
+                            gr.Button("", interactive=False)
+                        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=[
+                                gr.Textbox(interactive=False), gr.Markdown(), gr.Matplotlib()])
+
+            gr.Markdown("### f-block (lanthanides & actinides)")
+            with gr.Row():
+                for z in LAN:
+                    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=[
+                        gr.Textbox(interactive=False), gr.Markdown(), gr.Matplotlib()])
+            with gr.Row():
+                for z in ACT:
+                    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=[
+                        gr.Textbox(interactive=False), gr.Markdown(), gr.Matplotlib()])
+
+        with gr.Column(scale=1):
+            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.")
+            trend = gr.Matplotlib()
+
+            search.submit(search_element, inputs=[search], outputs=[info, facts, trend])
+
+            gr.Markdown("### Trend heatmap")
+            prop = gr.Dropdown(choices=[k for k, _ in NUMERIC_PROPS], value="electronegativity", label="Property")
+            heat = gr.Matplotlib()
+
+            def heatmap_callback(property_key):
+                return plot_heatmap(property_key)
+            prop.change(heatmap_callback, inputs=[prop], outputs=[heat])
+            heat.update(plot_heatmap("electronegativity"))
+
+if __name__ == "__main__":
+    demo.launch()

requirements (2).txt

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+gradio>=4.29.0
+pandas>=2.2.2
+periodictable>=1.6.1
+numpy>=1.26.0
+matplotlib>=3.8.0