Create app.py

app.py

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+import pandas as pd
+import streamlit as st
+
+st.set_page_config(page_title="Seuils individualisés - Zebris", layout="wide")
+
+st.title("Générateur de seuils individualisés")
+st.caption("Poids + volume horaire d'entraînement → seuils personnalisés de référence")
+
+st.subheader("Entrées athlète")
+
+c1, c2 = st.columns(2)
+with c1:
+    nom = st.text_input("Nom de l'athlète", value="Lucas Martin")
+    poids_kg = st.number_input("Poids (kg)", min_value=30.0, max_value=150.0, value=72.0, step=0.1)
+
+with c2:
+    sport = st.text_input("Sport", value="Course sur route")
+    volume_horaire = st.number_input("Volume horaire / semaine", min_value=0.5, max_value=30.0, value=5.0, step=0.5)
+
+poids_n = poids_kg * 9.81
+
+# Définition de la catégorie de charge
+if volume_horaire <= 3:
+    charge = "faible"
+elif volume_horaire <= 6:
+    charge = "modérée"
+else:
+    charge = "élevée"
+
+st.info(f"Catégorie de charge retenue : **{charge}**")
+
+# Seuils selon la charge
+if charge == "faible":
+    force_bw_low = 0.75
+    force_bw_high = 1.00
+    pression_low = 20
+    pression_high = 26
+    cadence_low = 160
+    cadence_high = 172
+    contact_low = 70
+    contact_high = 74
+    flight_low = 26
+    flight_high = 30
+    asym_low = 6
+    asym_high = 10
+    rotation_low = 6
+    rotation_high = 10
+
+elif charge == "modérée":
+    force_bw_low = 0.70
+    force_bw_high = 0.95
+    pression_low = 20
+    pression_high = 25
+    cadence_low = 165
+    cadence_high = 176
+    contact_low = 69
+    contact_high = 73
+    flight_low = 27
+    flight_high = 31
+    asym_low = 5
+    asym_high = 9
+    rotation_low = 5
+    rotation_high = 9
+
+else:
+    force_bw_low = 0.65
+    force_bw_high = 0.90
+    pression_low = 20
+    pression_high = 24
+    cadence_low = 168
+    cadence_high = 180
+    contact_low = 68
+    contact_high = 72
+    flight_low = 28
+    flight_high = 32
+    asym_low = 4
+    asym_high = 8
+    rotation_low = 4
+    rotation_high = 8
+
+# Conversion en Newton
+force_n_low = force_bw_low * poids_n
+force_n_high = force_bw_high * poids_n
+
+st.subheader("Résumé athlète")
+r1, r2, r3 = st.columns(3)
+with r1:
+    st.metric("Poids", f"{poids_kg:.1f} kg")
+with r2:
+    st.metric("Poids en Newton", f"{poids_n:.1f} N")
+with r3:
+    st.metric("Charge", charge)
+
+st.subheader("Seuils individualisés")
+
+impact_df = pd.DataFrame({
+    "Variable": [
+        "Force talon normalisée",
+        "Force talon convertie",
+        "Pression talon",
+    ],
+    "Zone basse / faible": [
+        f"< {force_bw_low:.2f} BW",
+        f"< {force_n_low:.1f} N",
+        f"< {pression_low} N/cm²",
+    ],
+    "Zone attendue": [
+        f"{force_bw_low:.2f} à {force_bw_high:.2f} BW",
+        f"{force_n_low:.1f} à {force_n_high:.1f} N",
+        f"{pression_low} à {pression_high} N/cm²",
+    ],
+    "Zone haute / élevée": [
+        f"> {force_bw_high:.2f} BW",
+        f"> {force_n_high:.1f} N",
+        f"> {pression_high} N/cm²",
+    ],
+})
+
+dynamique_df = pd.DataFrame({
+    "Variable": [
+        "Cadence",
+        "Temps de contact",
+        "Temps de vol",
+    ],
+    "Zone basse / faible": [
+        f"< {cadence_low} pas/min",
+        f"< {contact_low} %",
+        f"< {flight_low} %",
+    ],
+    "Zone attendue": [
+        f"{cadence_low} à {cadence_high} pas/min",
+        f"{contact_low} à {contact_high} %",
+        f"{flight_low} à {flight_high} %",
+    ],
+    "Zone haute / élevée": [
+        f"> {cadence_high} pas/min",
+        f"> {contact_high} %",
+        f"> {flight_high} %",
+    ],
+})
+
+symetrie_df = pd.DataFrame({
+    "Variable": [
+        "Asymétrie force talon",
+        "Asymétrie force avant-pied",
+        "Asymétrie COP",
+        "Différence rotation G/D",
+    ],
+    "Zone faible": [
+        f"< {asym_low} %",
+        f"< {asym_low} %",
+        f"< {asym_low} %",
+        f"< {rotation_low}°",
+    ],
+    "Zone modérée": [
+        f"{asym_low} à {asym_high} %",
+        f"{asym_low} à {asym_high} %",
+        f"{asym_low} à {asym_high} %",
+        f"{rotation_low} à {rotation_high}°",
+    ],
+    "Zone marquée": [
+        f"> {asym_high} %",
+        f"> {asym_high} %",
+        f"> {asym_high} %",
+        f"> {rotation_high}°",
+    ],
+})
+
+tab1, tab2, tab3 = st.tabs(["Impact", "Dynamique", "Symétrie"])
+
+with tab1:
+    st.dataframe(impact_df, hide_index=True, use_container_width=True)
+
+with tab2:
+    st.dataframe(dynamique_df, hide_index=True, use_container_width=True)
+
+with tab3:
+    st.dataframe(symetrie_df, hide_index=True, use_container_width=True)
+
+st.subheader("Lecture méthodologique")
+st.write(
+    "Ces seuils sont individualisés à partir du poids et du volume horaire d’entraînement hebdomadaire. "
+    "Ils constituent une base de référence personnelle de l’athlète avant toute analyse ou recommandation."
+)