Delete zebris_extractor.py

zebris_extractor.py

@@ -1,255 +0,0 @@
-import io
-import numpy as np
-import pandas as pd
-
-
-STANDARD_COLUMNS = [
-    "Nom",
-    "Date",
-    "Poids (kg)",
-    "Vitesse (km/h)",
-    "Cadence (pas/min)",
-    "Contact (%)",
-    "Flight (%)",
-    "Force talon G (N)",
-    "Force talon D (N)",
-    "Force avant-pied G (N)",
-    "Force avant-pied D (N)",
-    "Pression talon G (N/cm²)",
-    "Pression talon D (N/cm²)",
-    "COP G (mm)",
-    "COP D (mm)",
-    "Rotation G (°)",
-    "Rotation D (°)",
-    "Transition G (s)",
-    "Transition D (s)",
-    "Longueur foulée (cm)",
-    "Largeur pas (cm)",
-]
-
-
-def _norm(text):
-    return (
-        str(text)
-        .strip()
-        .lower()
-        .replace("é", "e")
-        .replace("è", "e")
-        .replace("ê", "e")
-        .replace("à", "a")
-        .replace("ù", "u")
-        .replace("ç", "c")
-        .replace("²", "2")
-        .replace("°", "")
-    )
-
-
-COLUMN_CANDIDATES = {
-    "Nom": [
-        ("last name", "first name"),
-        ("nom", "prenom"),
-        ("last name", "first name "),
-    ],
-    "Date": [
-        "date",
-        "recording date",
-        "enregistrement",
-    ],
-    "Poids (kg)": [
-        "weight (kg)",
-        "poids (kg)",
-        "weight",
-        "poids",
-    ],
-    "Vitesse (km/h)": [
-        "speed (km/h)",
-        "vitesse (km/h)",
-        "speed",
-        "vitesse",
-    ],
-    "Cadence (pas/min)": [
-        "cadence (steps/min)",
-        "cadence (pas/min)",
-        "cadence",
-        "cadence, pass/min",
-    ],
-    "Contact (%)": [
-        "total contact (%)",
-        "contact (%)",
-        "total contact",
-    ],
-    "Flight (%)": [
-        "total flight (%)",
-        "flight (%)",
-        "total flight",
-    ],
-    "Force talon G (N)": [
-        "heel (three zones) left force max (n)",
-        "mean force heel left (n)",
-        "heel left force max (n)",
-        "heel left (n)",
-    ],
-    "Force talon D (N)": [
-        "heel (three zones) right force max (n)",
-        "mean force heel right (n)",
-        "heel right force max (n)",
-        "heel right (n)",
-    ],
-    "Force avant-pied G (N)": [
-        "forefoot (three zones) left force max (n)",
-        "mean force forefoot left (n)",
-        "forefoot left force max (n)",
-        "forefoot left (n)",
-    ],
-    "Force avant-pied D (N)": [
-        "forefoot (three zones) right force max (n)",
-        "mean force forefoot right (n)",
-        "forefoot right force max (n)",
-        "forefoot right (n)",
-    ],
-    "Pression talon G (N/cm²)": [
-        "heel (three zones) left pressure max (n/cm2)",
-        "mean pressure heel left (n/cm2)",
-        "heel left pressure max (n/cm2)",
-    ],
-    "Pression talon D (N/cm²)": [
-        "heel (three zones) right pressure max (n/cm2)",
-        "mean pressure heel right (n/cm2)",
-        "heel right pressure max (n/cm2)",
-    ],
-    "COP G (mm)": [
-        "cop length left (mm)",
-        "cop parameters running left length (mm)",
-        "cop left (mm)",
-    ],
-    "COP D (mm)": [
-        "cop length right (mm)",
-        "cop parameters running right length (mm)",
-        "cop right (mm)",
-    ],
-    "Rotation G (°)": [
-        "foot rotation left (deg)",
-        "foot rotation left",
-        "rotation left",
-    ],
-    "Rotation D (°)": [
-        "foot rotation right (deg)",
-        "foot rotation right",
-        "rotation right",
-    ],
-    "Transition G (s)": [
-        "heel to forefoot transition left (s)",
-        "transition left (s)",
-        "instant du passage du talon vers l'avant-pied gauche (s)",
-    ],
-    "Transition D (s)": [
-        "heel to forefoot transition right (s)",
-        "transition right (s)",
-        "instant du passage du talon vers l'avant-pied droite (s)",
-    ],
-    "Longueur foulée (cm)": [
-        "stride length (cm)",
-        "longueur de la foulee (cm)",
-        "longueur de la foulee",
-    ],
-    "Largeur pas (cm)": [
-        "step width (cm)",
-        "largeur du pas (cm)",
-        "largeur du pas",
-    ],
-}
-
-
-def _to_numeric(series):
-    return pd.to_numeric(
-        series.astype(str).str.replace(",", ".", regex=False),
-        errors="coerce"
-    )
-
-
-def _read_csv_flex(uploaded_file):
-    raw = uploaded_file.read()
-    uploaded_file.seek(0)
-
-    for encoding in ["utf-8-sig", "utf-8", "latin1", "cp1252"]:
-        for sep in [";", ",", "\t"]:
-            try:
-                txt = raw.decode(encoding)
-                df = pd.read_csv(io.StringIO(txt), sep=sep)
-                if df.shape[1] > 1:
-                    return df
-            except Exception:
-                pass
-
-    # dernier essai naïf
-    return pd.read_csv(uploaded_file)
-
-
-def _find_column(df, candidates):
-    normalized_cols = {_norm(c): c for c in df.columns}
-    for cand in candidates:
-        key = _norm(cand)
-        if key in normalized_cols:
-            return normalized_cols[key]
-    return None
-
-
-def extract_zebris_csv(uploaded_file):
-    df = _read_csv_flex(uploaded_file)
-
-    out = pd.DataFrame(index=df.index)
-    mapping_debug = {}
-    manquantes = []
-
-    # Nom
-    nom_done = False
-    for cand_pair in COLUMN_CANDIDATES["Nom"]:
-        if isinstance(cand_pair, tuple):
-            c1 = _find_column(df, [cand_pair[0]])
-            c2 = _find_column(df, [cand_pair[1]])
-            if c1 and c2:
-                out["Nom"] = df[c1].astype(str).str.strip() + " " + df[c2].astype(str).str.strip()
-                mapping_debug["Nom"] = [c1, c2]
-                nom_done = True
-                break
-
-    if not nom_done:
-        c = _find_column(df, ["nom"])
-        if c:
-            out["Nom"] = df[c].astype(str)
-            mapping_debug["Nom"] = c
-        else:
-            out["Nom"] = "Inconnu"
-            manquantes.append("Nom")
-
-    # Autres colonnes
-    for target in STANDARD_COLUMNS:
-        if target == "Nom":
-            continue
-
-        candidates = COLUMN_CANDIDATES.get(target, [])
-        col = _find_column(df, candidates)
-
-        if col is None:
-            out[target] = np.nan
-            manquantes.append(target)
-        else:
-            mapping_debug[target] = col
-            if target == "Date":
-                out[target] = df[col]
-            else:
-                out[target] = _to_numeric(df[col])
-
-    # Garde lignes avec allure
-    if "Vitesse (km/h)" in out.columns:
-        out = out[out["Vitesse (km/h)"].notna()].copy()
-
-    out = out.reindex(columns=STANDARD_COLUMNS).reset_index(drop=True)
-
-    debug = {
-        "mapping": mapping_debug,
-        "manquantes": manquantes,
-        "colonnes_csv": list(df.columns),
-    }
-
-    return out, debug